airbnb_final_analysis_v3.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from geopy.distance import vincenty\n",
    "from tqdm import tqdm\n",
    "tqdm.pandas()\n",
    "from sklearn.metrics import r2_score\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.ensemble import GradientBoostingRegressor\n",
    "from sklearn.model_selection import RandomizedSearchCV\n",
    "from nltk.sentiment.vader import SentimentIntensityAnalyzer\n",
    "from collections import Counter\n",
    "from scipy import stats\n",
    "from dateutil import parser\n",
    "import eli5\n",
    "from eli5.sklearn import PermutationImportance\n",
    "from skopt.space import Real\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "# Change pandas viewing options\n",
    "pd.set_option('display.max_rows', 500)\n",
    "pd.set_option('display.max_columns', 500)\n",
    "pd.set_option('display.width', 1000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**4 Business questions to ask with Airbnb data:**\n",
    "\n",
    "* **(Q1)** what are the positive and negative reviews (based on review text); \n",
    "* **(Q2)** what are the main distinctions of Airbnb superhosts from ordinary hosts;\n",
    "* **(Q3)** what are the main factors that influence Airbnb renting price;\n",
    "* **(Q4)** how well can we predict the Airbnb renting price based on the data from a different city. \n",
    "\n",
    "To answer all these questions, I have downloaded [the recent Airbnb apartment listings](http:https://insideairbnb.com/get-the-data.html) for August 2018."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It takes several seconds to download approx. 133 MBytes of archived listings and reviews from Aug 2018 on Boston (MA, USA), Seattle (WA, USA) and Copenhagen (Denmark, Europe):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "133M\tdata.insideairbnb.com\n",
      "CPU times: user 4.33 s, sys: 1.01 s, total: 5.33 s\n",
      "Wall time: 1min 31s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "! rm -r data.insideairbnb.com\n",
    "# Seattle data:\n",
    "! wget -xq http:https://data.insideairbnb.com/united-states/wa/seattle/2018-08-16/data/listings.csv.gz\n",
    "! wget -xq http:https://data.insideairbnb.com/united-states/wa/seattle/2018-08-16/data/reviews.csv.gz\n",
    "# Boston data:\n",
    "! wget -xq http:https://data.insideairbnb.com/united-states/ma/boston/2018-08-17/data/listings.csv.gz\n",
    "! wget -xq http:https://data.insideairbnb.com/united-states/ma/boston/2018-08-17/data/reviews.csv.gz\n",
    "# Copenhagen data:\n",
    "! wget -xq http:https://data.insideairbnb.com/denmark/hovedstaden/copenhagen/2018-08-21/data/listings.csv.gz\n",
    "! wget -xq http:https://data.insideairbnb.com/denmark/hovedstaden/copenhagen/2018-08-21/data/reviews.csv.gz\n",
    "\n",
    "! du -sh data.insideairbnb.com "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Open the data as `pandas` Dataframes:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "seattle_path = 'data.insideairbnb.com/united-states/wa/seattle/2018-08-16/data/'\n",
    "seattle_reviews =  pd.read_csv(seattle_path + 'reviews.csv.gz')\n",
    "seattle_listings = pd.read_csv(seattle_path + 'listings.csv.gz')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "boston_path = 'data.insideairbnb.com/united-states/ma/boston/2018-08-17/data/'\n",
    "boston_reviews =  pd.read_csv(boston_path + 'reviews.csv.gz')\n",
    "boston_listings = pd.read_csv(boston_path + 'listings.csv.gz')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "copenhagen_path = 'data.insideairbnb.com/denmark/hovedstaden/copenhagen/2018-08-21/data/'\n",
    "copenhagen_reviews =  pd.read_csv(copenhagen_path + 'reviews.csv.gz')\n",
    "copenhagen_listings = pd.read_csv(copenhagen_path + 'listings.csv.gz')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data preprocessing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## First, we need to look on *_reviews:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((177559, 6), (344065, 6), (323658, 6))"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "boston_reviews.shape, seattle_reviews.shape, copenhagen_reviews.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 177559 entries, 0 to 177558\n",
      "Data columns (total 6 columns):\n",
      "listing_id       177559 non-null int64\n",
      "id               177559 non-null int64\n",
      "date             177559 non-null object\n",
      "reviewer_id      177559 non-null int64\n",
      "reviewer_name    177559 non-null object\n",
      "comments         177361 non-null object\n",
      "dtypes: int64(3), object(3)\n",
      "memory usage: 8.1+ MB\n"
     ]
    }
   ],
   "source": [
    "boston_reviews.info(max_cols=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
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       "      <th>listing_id</th>\n",
       "      <th>id</th>\n",
       "      <th>date</th>\n",
       "      <th>reviewer_id</th>\n",
       "      <th>reviewer_name</th>\n",
       "      <th>comments</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>323321</th>\n",
       "      <td>21883885</td>\n",
       "      <td>243650573</td>\n",
       "      <td>2018-03-16</td>\n",
       "      <td>126168643</td>\n",
       "      <td>Julio</td>\n",
       "      <td>Very conveniently placed location. Other than ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>250677</th>\n",
       "      <td>15435193</td>\n",
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       "      <td>2017-05-01</td>\n",
       "      <td>54633845</td>\n",
       "      <td>Olivia</td>\n",
       "      <td>The room was very clean and comfortable, as wa...</td>\n",
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       "      <th>136580</th>\n",
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       "      <td>2016-05-19</td>\n",
       "      <td>57563701</td>\n",
       "      <td>Yuesong</td>\n",
       "      <td>A good experience! Julian is very kind!!!! And...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100160</th>\n",
       "      <td>5174876</td>\n",
       "      <td>43756612</td>\n",
       "      <td>2015-08-22</td>\n",
       "      <td>32841859</td>\n",
       "      <td>Kristjana</td>\n",
       "      <td>I live in the neighborhood and when my whole f...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>252240</th>\n",
       "      <td>15537773</td>\n",
       "      <td>173137916</td>\n",
       "      <td>2017-07-22</td>\n",
       "      <td>50079968</td>\n",
       "      <td>Robert</td>\n",
       "      <td>Clean, comfortable multi-family home close to ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>295115</th>\n",
       "      <td>19364598</td>\n",
       "      <td>198529335</td>\n",
       "      <td>2017-09-29</td>\n",
       "      <td>20034634</td>\n",
       "      <td>Rich</td>\n",
       "      <td>Eric is super cordial and warm. The location i...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30171</th>\n",
       "      <td>1003469</td>\n",
       "      <td>270281789</td>\n",
       "      <td>2018-05-28</td>\n",
       "      <td>10153172</td>\n",
       "      <td>Beck</td>\n",
       "      <td>Great location and space! Steven was very resp...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>288730</th>\n",
       "      <td>18733199</td>\n",
       "      <td>171092727</td>\n",
       "      <td>2017-07-16</td>\n",
       "      <td>61328468</td>\n",
       "      <td>Apryl</td>\n",
       "      <td>James was a great host! He responded to all my...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9720</th>\n",
       "      <td>193836</td>\n",
       "      <td>290086330</td>\n",
       "      <td>2018-07-13</td>\n",
       "      <td>40845129</td>\n",
       "      <td>Yuan</td>\n",
       "      <td>Amy and Nathan are extremely friendly.  kids a...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173006</th>\n",
       "      <td>9698202</td>\n",
       "      <td>136970826</td>\n",
       "      <td>2017-03-12</td>\n",
       "      <td>4447497</td>\n",
       "      <td>Alexander</td>\n",
       "      <td>A great spot, excellent communication and just...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183204</th>\n",
       "      <td>10752600</td>\n",
       "      <td>122605771</td>\n",
       "      <td>2016-12-24</td>\n",
       "      <td>66991758</td>\n",
       "      <td>Ruolan</td>\n",
       "      <td>It is very noisy at bedtime, because there is ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249887</th>\n",
       "      <td>15407909</td>\n",
       "      <td>270914599</td>\n",
       "      <td>2018-05-30</td>\n",
       "      <td>8389761</td>\n",
       "      <td>Stacy</td>\n",
       "      <td>Jeffrey and Madeline’s home was perfect for ou...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>228942</th>\n",
       "      <td>13848321</td>\n",
       "      <td>162172699</td>\n",
       "      <td>2017-06-19</td>\n",
       "      <td>89372420</td>\n",
       "      <td>Erwin</td>\n",
       "      <td>Dave and Megan's home is close to a Link stati...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169222</th>\n",
       "      <td>9436832</td>\n",
       "      <td>168065862</td>\n",
       "      <td>2017-07-08</td>\n",
       "      <td>13452070</td>\n",
       "      <td>Tim</td>\n",
       "      <td>Great place to stay! Can get to the Link Train...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195342</th>\n",
       "      <td>11638678</td>\n",
       "      <td>77455577</td>\n",
       "      <td>2016-06-01</td>\n",
       "      <td>46000599</td>\n",
       "      <td>Cassandra</td>\n",
       "      <td>Had a great stay. For the price and location, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17542</th>\n",
       "      <td>461234</td>\n",
       "      <td>80082091</td>\n",
       "      <td>2016-06-16</td>\n",
       "      <td>69824712</td>\n",
       "      <td>Laura</td>\n",
       "      <td>Wir waren drei Nächte bei Diana und haben uns ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>218127</th>\n",
       "      <td>13247942</td>\n",
       "      <td>103455488</td>\n",
       "      <td>2016-09-22</td>\n",
       "      <td>83400170</td>\n",
       "      <td>Hanna</td>\n",
       "      <td>We had great communication before and during. ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27233</th>\n",
       "      <td>823989</td>\n",
       "      <td>129707557</td>\n",
       "      <td>2017-02-01</td>\n",
       "      <td>67278573</td>\n",
       "      <td>Clarissa</td>\n",
       "      <td>Nice place to stay in northgate area :)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56153</th>\n",
       "      <td>2522091</td>\n",
       "      <td>109620115</td>\n",
       "      <td>2016-10-22</td>\n",
       "      <td>37675878</td>\n",
       "      <td>Douglas</td>\n",
       "      <td>Michelle greeted us when we arrived to check-i...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>324497</th>\n",
       "      <td>22089984</td>\n",
       "      <td>273046203</td>\n",
       "      <td>2018-06-04</td>\n",
       "      <td>114915246</td>\n",
       "      <td>Marissa</td>\n",
       "      <td>Great place with a nice view, roughly 15 minut...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        listing_id         id        date  reviewer_id reviewer_name                                           comments\n",
       "323321    21883885  243650573  2018-03-16    126168643         Julio  Very conveniently placed location. Other than ...\n",
       "250677    15435193  148944528  2017-05-01     54633845        Olivia  The room was very clean and comfortable, as wa...\n",
       "136580     7411863   75200129  2016-05-19     57563701       Yuesong  A good experience! Julian is very kind!!!! And...\n",
       "100160     5174876   43756612  2015-08-22     32841859     Kristjana  I live in the neighborhood and when my whole f...\n",
       "252240    15537773  173137916  2017-07-22     50079968        Robert  Clean, comfortable multi-family home close to ...\n",
       "295115    19364598  198529335  2017-09-29     20034634          Rich  Eric is super cordial and warm. The location i...\n",
       "30171      1003469  270281789  2018-05-28     10153172          Beck  Great location and space! Steven was very resp...\n",
       "288730    18733199  171092727  2017-07-16     61328468         Apryl  James was a great host! He responded to all my...\n",
       "9720        193836  290086330  2018-07-13     40845129          Yuan  Amy and Nathan are extremely friendly.  kids a...\n",
       "173006     9698202  136970826  2017-03-12      4447497     Alexander  A great spot, excellent communication and just...\n",
       "183204    10752600  122605771  2016-12-24     66991758        Ruolan  It is very noisy at bedtime, because there is ...\n",
       "249887    15407909  270914599  2018-05-30      8389761         Stacy  Jeffrey and Madeline’s home was perfect for ou...\n",
       "228942    13848321  162172699  2017-06-19     89372420         Erwin  Dave and Megan's home is close to a Link stati...\n",
       "169222     9436832  168065862  2017-07-08     13452070           Tim  Great place to stay! Can get to the Link Train...\n",
       "195342    11638678   77455577  2016-06-01     46000599     Cassandra  Had a great stay. For the price and location, ...\n",
       "17542       461234   80082091  2016-06-16     69824712         Laura  Wir waren drei Nächte bei Diana und haben uns ...\n",
       "218127    13247942  103455488  2016-09-22     83400170         Hanna  We had great communication before and during. ...\n",
       "27233       823989  129707557  2017-02-01     67278573      Clarissa            Nice place to stay in northgate area :)\n",
       "56153      2522091  109620115  2016-10-22     37675878       Douglas  Michelle greeted us when we arrived to check-i...\n",
       "324497    22089984  273046203  2018-06-04    114915246       Marissa  Great place with a nice view, roughly 15 minut..."
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "seattle_reviews.sample(20, random_state=42) # note that 42 is the answer for everything :-)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th>listing_id</th>\n",
       "      <th>id</th>\n",
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       "      <th>149527</th>\n",
       "      <td>19676676</td>\n",
       "      <td>193222953</td>\n",
       "      <td>2017-09-12</td>\n",
       "      <td>116471884</td>\n",
       "      <td>Shelley</td>\n",
       "      <td>Fiona's apartment is so much more than adverti...</td>\n",
       "    </tr>\n",
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       "      <th>57968</th>\n",
       "      <td>6300089</td>\n",
       "      <td>171043397</td>\n",
       "      <td>2017-07-16</td>\n",
       "      <td>128756927</td>\n",
       "      <td>Sarah</td>\n",
       "      <td>Irida was a great host and her apartment was c...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98689</th>\n",
       "      <td>13378923</td>\n",
       "      <td>187823962</td>\n",
       "      <td>2017-08-27</td>\n",
       "      <td>126891761</td>\n",
       "      <td>David</td>\n",
       "      <td>We thoroughly enjoyed our stay. Kathe and Lisa...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30936</th>\n",
       "      <td>2701124</td>\n",
       "      <td>254668379</td>\n",
       "      <td>2018-04-17</td>\n",
       "      <td>4704201</td>\n",
       "      <td>Sam</td>\n",
       "      <td>We stayed at Varouj's apartment for Marathon w...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123931</th>\n",
       "      <td>16238114</td>\n",
       "      <td>144069970</td>\n",
       "      <td>2017-04-14</td>\n",
       "      <td>12549902</td>\n",
       "      <td>Elizabeth</td>\n",
       "      <td>Really comfortable cozy apartment in a great a...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160750</th>\n",
       "      <td>21346776</td>\n",
       "      <td>243571913</td>\n",
       "      <td>2018-03-16</td>\n",
       "      <td>103625046</td>\n",
       "      <td>Rio</td>\n",
       "      <td>Matthew is very precise with his instructions ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22988</th>\n",
       "      <td>1584362</td>\n",
       "      <td>132857678</td>\n",
       "      <td>2017-02-19</td>\n",
       "      <td>25203627</td>\n",
       "      <td>Ososanya</td>\n",
       "      <td>Absolutely beautiful home, cleaner than almost...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71329</th>\n",
       "      <td>8065282</td>\n",
       "      <td>200207390</td>\n",
       "      <td>2017-10-04</td>\n",
       "      <td>65788783</td>\n",
       "      <td>Zach</td>\n",
       "      <td>It was a very nice, easy place to stay!</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32792</th>\n",
       "      <td>2931165</td>\n",
       "      <td>81956860</td>\n",
       "      <td>2016-06-26</td>\n",
       "      <td>61109757</td>\n",
       "      <td>Ramya + Tucker</td>\n",
       "      <td>Cynthia and her family were so welcoming. We h...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119465</th>\n",
       "      <td>15521407</td>\n",
       "      <td>299233493</td>\n",
       "      <td>2018-07-30</td>\n",
       "      <td>33131420</td>\n",
       "      <td>Anna</td>\n",
       "      <td>Good host. Clean space. Beautiful home and bac...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79840</th>\n",
       "      <td>9362821</td>\n",
       "      <td>65530212</td>\n",
       "      <td>2016-03-15</td>\n",
       "      <td>16871228</td>\n",
       "      <td>Hannes</td>\n",
       "      <td>Marcia did a very good job preparing the room ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163715</th>\n",
       "      <td>21735562</td>\n",
       "      <td>219692824</td>\n",
       "      <td>2017-12-18</td>\n",
       "      <td>12246092</td>\n",
       "      <td>Crystal</td>\n",
       "      <td>Just perfect!  So close to the train.  Hosts w...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159263</th>\n",
       "      <td>21182192</td>\n",
       "      <td>244347756</td>\n",
       "      <td>2018-03-18</td>\n",
       "      <td>30842558</td>\n",
       "      <td>Udare</td>\n",
       "      <td>Margarita's place is beautiful. Very clean and...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46934</th>\n",
       "      <td>4699828</td>\n",
       "      <td>194338297</td>\n",
       "      <td>2017-09-16</td>\n",
       "      <td>73553502</td>\n",
       "      <td>Jackie</td>\n",
       "      <td>We really appreciated the well equipped kitche...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89238</th>\n",
       "      <td>11758169</td>\n",
       "      <td>168939581</td>\n",
       "      <td>2017-07-10</td>\n",
       "      <td>14218857</td>\n",
       "      <td>Michelle</td>\n",
       "      <td>Julie was a phenomenal host. Always quick to r...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167942</th>\n",
       "      <td>22731313</td>\n",
       "      <td>269554720</td>\n",
       "      <td>2018-05-27</td>\n",
       "      <td>963412</td>\n",
       "      <td>Catherine</td>\n",
       "      <td>This is a very nice room in a brand new buildi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58040</th>\n",
       "      <td>6310903</td>\n",
       "      <td>77931666</td>\n",
       "      <td>2016-06-04</td>\n",
       "      <td>21390901</td>\n",
       "      <td>Verna</td>\n",
       "      <td>We had really good communication with James.  ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113222</th>\n",
       "      <td>15020558</td>\n",
       "      <td>102896255</td>\n",
       "      <td>2016-09-19</td>\n",
       "      <td>51690347</td>\n",
       "      <td>Charese</td>\n",
       "      <td>Had an awesome stay in Charlestown! The condo ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117066</th>\n",
       "      <td>15343566</td>\n",
       "      <td>148773553</td>\n",
       "      <td>2017-05-01</td>\n",
       "      <td>110738336</td>\n",
       "      <td>Vincent</td>\n",
       "      <td>The room is very nice and quiet, very close to...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48097</th>\n",
       "      <td>4879579</td>\n",
       "      <td>112754978</td>\n",
       "      <td>2016-11-07</td>\n",
       "      <td>35699348</td>\n",
       "      <td>Jiapeng</td>\n",
       "      <td>Dan's place is very clean and comfortable. The...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        listing_id         id        date  reviewer_id   reviewer_name                                           comments\n",
       "149527    19676676  193222953  2017-09-12    116471884         Shelley  Fiona's apartment is so much more than adverti...\n",
       "57968      6300089  171043397  2017-07-16    128756927           Sarah  Irida was a great host and her apartment was c...\n",
       "98689     13378923  187823962  2017-08-27    126891761           David  We thoroughly enjoyed our stay. Kathe and Lisa...\n",
       "30936      2701124  254668379  2018-04-17      4704201             Sam  We stayed at Varouj's apartment for Marathon w...\n",
       "123931    16238114  144069970  2017-04-14     12549902       Elizabeth  Really comfortable cozy apartment in a great a...\n",
       "160750    21346776  243571913  2018-03-16    103625046             Rio  Matthew is very precise with his instructions ...\n",
       "22988      1584362  132857678  2017-02-19     25203627        Ososanya  Absolutely beautiful home, cleaner than almost...\n",
       "71329      8065282  200207390  2017-10-04     65788783            Zach            It was a very nice, easy place to stay!\n",
       "32792      2931165   81956860  2016-06-26     61109757  Ramya + Tucker  Cynthia and her family were so welcoming. We h...\n",
       "119465    15521407  299233493  2018-07-30     33131420            Anna  Good host. Clean space. Beautiful home and bac...\n",
       "79840      9362821   65530212  2016-03-15     16871228          Hannes  Marcia did a very good job preparing the room ...\n",
       "163715    21735562  219692824  2017-12-18     12246092         Crystal  Just perfect!  So close to the train.  Hosts w...\n",
       "159263    21182192  244347756  2018-03-18     30842558           Udare  Margarita's place is beautiful. Very clean and...\n",
       "46934      4699828  194338297  2017-09-16     73553502          Jackie  We really appreciated the well equipped kitche...\n",
       "89238     11758169  168939581  2017-07-10     14218857        Michelle  Julie was a phenomenal host. Always quick to r...\n",
       "167942    22731313  269554720  2018-05-27       963412       Catherine  This is a very nice room in a brand new buildi...\n",
       "58040      6310903   77931666  2016-06-04     21390901           Verna  We had really good communication with James.  ...\n",
       "113222    15020558  102896255  2016-09-19     51690347         Charese  Had an awesome stay in Charlestown! The condo ...\n",
       "117066    15343566  148773553  2017-05-01    110738336         Vincent  The room is very nice and quiet, very close to...\n",
       "48097      4879579  112754978  2016-11-07     35699348         Jiapeng  Dan's place is very clean and comfortable. The..."
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "boston_reviews.sample(20, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>listing_id</th>\n",
       "      <th>id</th>\n",
       "      <th>date</th>\n",
       "      <th>reviewer_id</th>\n",
       "      <th>reviewer_name</th>\n",
       "      <th>comments</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>169321</th>\n",
       "      <td>9111211</td>\n",
       "      <td>71515076</td>\n",
       "      <td>2016-04-25</td>\n",
       "      <td>37666249</td>\n",
       "      <td>Anthony</td>\n",
       "      <td>Rasmus' apartment is incredible, it's in a gre...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237465</th>\n",
       "      <td>15337225</td>\n",
       "      <td>218694016</td>\n",
       "      <td>2017-12-14</td>\n",
       "      <td>50188804</td>\n",
       "      <td>Kristiina</td>\n",
       "      <td>Very nice, cozy flat. Good location in Østerbr...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7123</th>\n",
       "      <td>353025</td>\n",
       "      <td>13488683</td>\n",
       "      <td>2014-05-28</td>\n",
       "      <td>766215</td>\n",
       "      <td>Matthew</td>\n",
       "      <td>Ben's place was wonderful during our 10-day st...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189419</th>\n",
       "      <td>11536155</td>\n",
       "      <td>114522588</td>\n",
       "      <td>2016-11-19</td>\n",
       "      <td>6075818</td>\n",
       "      <td>Victoria</td>\n",
       "      <td>Jakob so kindly hosted me very last minute in ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>281056</th>\n",
       "      <td>19527393</td>\n",
       "      <td>164581460</td>\n",
       "      <td>2017-06-28</td>\n",
       "      <td>82712115</td>\n",
       "      <td>Deividas</td>\n",
       "      <td>The host canceled this reservation 39 days bef...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8186</th>\n",
       "      <td>421110</td>\n",
       "      <td>58685724</td>\n",
       "      <td>2016-01-03</td>\n",
       "      <td>2527400</td>\n",
       "      <td>Sebastian</td>\n",
       "      <td>Everything was fine. The flat is exactly like ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158410</th>\n",
       "      <td>8074752</td>\n",
       "      <td>243519351</td>\n",
       "      <td>2018-03-16</td>\n",
       "      <td>118425341</td>\n",
       "      <td>Becky</td>\n",
       "      <td>Thomas's place has two extra-great perks: 1)be...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260356</th>\n",
       "      <td>17820007</td>\n",
       "      <td>158099065</td>\n",
       "      <td>2017-06-05</td>\n",
       "      <td>56220911</td>\n",
       "      <td>Marie- Theres</td>\n",
       "      <td>Very fancy appartment!!! \\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247551</th>\n",
       "      <td>16550558</td>\n",
       "      <td>154121546</td>\n",
       "      <td>2017-05-23</td>\n",
       "      <td>3243989</td>\n",
       "      <td>Gareth</td>\n",
       "      <td>The flat is in a lively location near bars and...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187586</th>\n",
       "      <td>11329621</td>\n",
       "      <td>141479162</td>\n",
       "      <td>2017-04-03</td>\n",
       "      <td>8608348</td>\n",
       "      <td>Craig</td>\n",
       "      <td>We had a great stay at the apartment, it was p...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>245477</th>\n",
       "      <td>16255436</td>\n",
       "      <td>132705847</td>\n",
       "      <td>2017-02-19</td>\n",
       "      <td>107228318</td>\n",
       "      <td>Manon Gabs</td>\n",
       "      <td>Vi lejede Pers lejlighed i forbindelse med en ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>276917</th>\n",
       "      <td>19237509</td>\n",
       "      <td>164698351</td>\n",
       "      <td>2017-06-28</td>\n",
       "      <td>15345917</td>\n",
       "      <td>Peter</td>\n",
       "      <td>Super fint ophold hos Louise.\\nMeget venlig mo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40826</th>\n",
       "      <td>1457864</td>\n",
       "      <td>111843201</td>\n",
       "      <td>2016-11-02</td>\n",
       "      <td>48588375</td>\n",
       "      <td>Kate</td>\n",
       "      <td>Mariannes place was perfect! So close to every...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113257</th>\n",
       "      <td>5495140</td>\n",
       "      <td>263871869</td>\n",
       "      <td>2018-05-13</td>\n",
       "      <td>33885363</td>\n",
       "      <td>Mathieu</td>\n",
       "      <td>Stine was a very good host, she was listening ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>246277</th>\n",
       "      <td>16332695</td>\n",
       "      <td>162068843</td>\n",
       "      <td>2017-06-19</td>\n",
       "      <td>50052757</td>\n",
       "      <td>Adam</td>\n",
       "      <td>Very nice apartment in a great part of town. A...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44888</th>\n",
       "      <td>1669801</td>\n",
       "      <td>143923190</td>\n",
       "      <td>2017-04-14</td>\n",
       "      <td>391905</td>\n",
       "      <td>Kevin</td>\n",
       "      <td>We had a superb experience in Nicolai's place....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>275502</th>\n",
       "      <td>19154209</td>\n",
       "      <td>228785805</td>\n",
       "      <td>2018-01-21</td>\n",
       "      <td>53603074</td>\n",
       "      <td>Lars</td>\n",
       "      <td>Byhuset er det helt perfekte udgangspunkt for ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126961</th>\n",
       "      <td>6309403</td>\n",
       "      <td>184627546</td>\n",
       "      <td>2017-08-20</td>\n",
       "      <td>137324317</td>\n",
       "      <td>Angelica</td>\n",
       "      <td>Mysig och rymlig lägenhet (vi var 5 personer) ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66249</th>\n",
       "      <td>2816989</td>\n",
       "      <td>193052179</td>\n",
       "      <td>2017-09-12</td>\n",
       "      <td>17043348</td>\n",
       "      <td>Matthew</td>\n",
       "      <td>Wonderful, spacious apartment in a great centr...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>238267</th>\n",
       "      <td>15429597</td>\n",
       "      <td>154316260</td>\n",
       "      <td>2017-05-24</td>\n",
       "      <td>115821264</td>\n",
       "      <td>Sven</td>\n",
       "      <td>Wer die Stadt Kopenhagen besuchen möchte, um s...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        listing_id         id        date  reviewer_id  reviewer_name                                           comments\n",
       "169321     9111211   71515076  2016-04-25     37666249        Anthony  Rasmus' apartment is incredible, it's in a gre...\n",
       "237465    15337225  218694016  2017-12-14     50188804      Kristiina  Very nice, cozy flat. Good location in Østerbr...\n",
       "7123        353025   13488683  2014-05-28       766215        Matthew  Ben's place was wonderful during our 10-day st...\n",
       "189419    11536155  114522588  2016-11-19      6075818       Victoria  Jakob so kindly hosted me very last minute in ...\n",
       "281056    19527393  164581460  2017-06-28     82712115       Deividas  The host canceled this reservation 39 days bef...\n",
       "8186        421110   58685724  2016-01-03      2527400      Sebastian  Everything was fine. The flat is exactly like ...\n",
       "158410     8074752  243519351  2018-03-16    118425341          Becky  Thomas's place has two extra-great perks: 1)be...\n",
       "260356    17820007  158099065  2017-06-05     56220911  Marie- Theres                        Very fancy appartment!!! \\n\n",
       "247551    16550558  154121546  2017-05-23      3243989         Gareth  The flat is in a lively location near bars and...\n",
       "187586    11329621  141479162  2017-04-03      8608348          Craig  We had a great stay at the apartment, it was p...\n",
       "245477    16255436  132705847  2017-02-19    107228318     Manon Gabs  Vi lejede Pers lejlighed i forbindelse med en ...\n",
       "276917    19237509  164698351  2017-06-28     15345917          Peter  Super fint ophold hos Louise.\\nMeget venlig mo...\n",
       "40826      1457864  111843201  2016-11-02     48588375           Kate  Mariannes place was perfect! So close to every...\n",
       "113257     5495140  263871869  2018-05-13     33885363        Mathieu  Stine was a very good host, she was listening ...\n",
       "246277    16332695  162068843  2017-06-19     50052757           Adam  Very nice apartment in a great part of town. A...\n",
       "44888      1669801  143923190  2017-04-14       391905          Kevin  We had a superb experience in Nicolai's place....\n",
       "275502    19154209  228785805  2018-01-21     53603074           Lars  Byhuset er det helt perfekte udgangspunkt for ...\n",
       "126961     6309403  184627546  2017-08-20    137324317       Angelica  Mysig och rymlig lägenhet (vi var 5 personer) ...\n",
       "66249      2816989  193052179  2017-09-12     17043348        Matthew  Wonderful, spacious apartment in a great centr...\n",
       "238267    15429597  154316260  2017-05-24    115821264           Sven  Wer die Stadt Kopenhagen besuchen möchte, um s..."
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "copenhagen_reviews.sample(20, random_state=42)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that some reviews are not in English! E.g., there are some reviews in German, Danish, Swedish."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Then, we need to look on *_listings:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((8494, 96), (6036, 96), (26202, 96))"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "seattle_listings.shape, boston_listings.shape, copenhagen_listings.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we see, there are much more columns than in `*_reviews`, so we need combine them and preprocess appropriately:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_listings = pd.concat([seattle_listings, boston_listings, copenhagen_listings],\n",
    "                        keys = [1, 2, 3])\n",
    "all_listings.reset_index(level=0, inplace=True)\n",
    "all_listings.rename(columns={'level_0': 'city_index'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>city_index</th>\n",
       "      <th>id</th>\n",
       "      <th>listing_url</th>\n",
       "      <th>scrape_id</th>\n",
       "      <th>last_scraped</th>\n",
       "      <th>name</th>\n",
       "      <th>summary</th>\n",
       "      <th>space</th>\n",
       "      <th>description</th>\n",
       "      <th>experiences_offered</th>\n",
       "      <th>neighborhood_overview</th>\n",
       "      <th>notes</th>\n",
       "      <th>transit</th>\n",
       "      <th>access</th>\n",
       "      <th>interaction</th>\n",
       "      <th>house_rules</th>\n",
       "      <th>thumbnail_url</th>\n",
       "      <th>medium_url</th>\n",
       "      <th>picture_url</th>\n",
       "      <th>xl_picture_url</th>\n",
       "      <th>host_id</th>\n",
       "      <th>host_url</th>\n",
       "      <th>host_name</th>\n",
       "      <th>host_since</th>\n",
       "      <th>host_location</th>\n",
       "      <th>host_about</th>\n",
       "      <th>host_response_time</th>\n",
       "      <th>host_response_rate</th>\n",
       "      <th>host_acceptance_rate</th>\n",
       "      <th>host_is_superhost</th>\n",
       "      <th>host_thumbnail_url</th>\n",
       "      <th>host_picture_url</th>\n",
       "      <th>host_neighbourhood</th>\n",
       "      <th>host_listings_count</th>\n",
       "      <th>host_total_listings_count</th>\n",
       "      <th>host_verifications</th>\n",
       "      <th>host_has_profile_pic</th>\n",
       "      <th>host_identity_verified</th>\n",
       "      <th>street</th>\n",
       "      <th>neighbourhood</th>\n",
       "      <th>neighbourhood_cleansed</th>\n",
       "      <th>neighbourhood_group_cleansed</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>market</th>\n",
       "      <th>smart_location</th>\n",
       "      <th>country_code</th>\n",
       "      <th>country</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>is_location_exact</th>\n",
       "      <th>property_type</th>\n",
       "      <th>room_type</th>\n",
       "      <th>accommodates</th>\n",
       "      <th>bathrooms</th>\n",
       "      <th>bedrooms</th>\n",
       "      <th>beds</th>\n",
       "      <th>bed_type</th>\n",
       "      <th>amenities</th>\n",
       "      <th>square_feet</th>\n",
       "      <th>price</th>\n",
       "      <th>weekly_price</th>\n",
       "      <th>monthly_price</th>\n",
       "      <th>security_deposit</th>\n",
       "      <th>cleaning_fee</th>\n",
       "      <th>guests_included</th>\n",
       "      <th>extra_people</th>\n",
       "      <th>minimum_nights</th>\n",
       "      <th>maximum_nights</th>\n",
       "      <th>calendar_updated</th>\n",
       "      <th>has_availability</th>\n",
       "      <th>availability_30</th>\n",
       "      <th>availability_60</th>\n",
       "      <th>availability_90</th>\n",
       "      <th>availability_365</th>\n",
       "      <th>calendar_last_scraped</th>\n",
       "      <th>number_of_reviews</th>\n",
       "      <th>first_review</th>\n",
       "      <th>last_review</th>\n",
       "      <th>review_scores_rating</th>\n",
       "      <th>review_scores_accuracy</th>\n",
       "      <th>review_scores_cleanliness</th>\n",
       "      <th>review_scores_checkin</th>\n",
       "      <th>review_scores_communication</th>\n",
       "      <th>review_scores_location</th>\n",
       "      <th>review_scores_value</th>\n",
       "      <th>requires_license</th>\n",
       "      <th>license</th>\n",
       "      <th>jurisdiction_names</th>\n",
       "      <th>instant_bookable</th>\n",
       "      <th>is_business_travel_ready</th>\n",
       "      <th>cancellation_policy</th>\n",
       "      <th>require_guest_profile_picture</th>\n",
       "      <th>require_guest_phone_verification</th>\n",
       "      <th>calculated_host_listings_count</th>\n",
       "      <th>reviews_per_month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2318</td>\n",
       "      <td>https://www.airbnb.com/rooms/2318</td>\n",
       "      <td>20180816121209</td>\n",
       "      <td>2018-08-16</td>\n",
       "      <td>Casa Madrona - Urban Oasis, 1 block from the P...</td>\n",
       "      <td>Gorgeous, architect remodeled, 1917 Dutch Colo...</td>\n",
       "      <td>Casa Madrona is a gorgeous, architect remodele...</td>\n",
       "      <td>Gorgeous, architect remodeled, 1917 Dutch Colo...</td>\n",
       "      <td>none</td>\n",
       "      <td>NaN</td>\n",
       "      <td>We adhere to a 10pm -9am quiet hour schedule, ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Guests can access any part of the house.</td>\n",
       "      <td>We are a family of three, who live next door a...</td>\n",
       "      <td>four day minimum stay</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://a0.muscache.com/im/pictures/ac08892c-f...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2536</td>\n",
       "      <td>https://www.airbnb.com/users/show/2536</td>\n",
       "      <td>Megan</td>\n",
       "      <td>2008-08-26</td>\n",
       "      <td>Seattle, Washington, United States</td>\n",
       "      <td>We love travel and adventure! We have stayed i...</td>\n",
       "      <td>within an hour</td>\n",
       "      <td>100%</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>https://a0.muscache.com/im/pictures/user/36c67...</td>\n",
       "      <td>https://a0.muscache.com/im/pictures/user/36c67...</td>\n",
       "      <td>Minor</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>['email', 'phone', 'reviews', 'jumio', 'govern...</td>\n",
       "      <td>t</td>\n",
       "      <td>t</td>\n",
       "      <td>Seattle, WA, United States</td>\n",
       "      <td>Madrona</td>\n",
       "      <td>Madrona</td>\n",
       "      <td>Central Area</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>WA</td>\n",
       "      <td>98122</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Seattle, WA</td>\n",
       "      <td>US</td>\n",
       "      <td>United States</td>\n",
       "      <td>47.610819</td>\n",
       "      <td>-122.290816</td>\n",
       "      <td>t</td>\n",
       "      <td>House</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>8</td>\n",
       "      <td>2.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Real Bed</td>\n",
       "      <td>{Internet,Wifi,Kitchen,\"Free parking on premis...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>$296.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>$500.00</td>\n",
       "      <td>$275.00</td>\n",
       "      <td>8</td>\n",
       "      <td>$20.00</td>\n",
       "      <td>4</td>\n",
       "      <td>300</td>\n",
       "      <td>2 days ago</td>\n",
       "      <td>t</td>\n",
       "      <td>3</td>\n",
       "      <td>30</td>\n",
       "      <td>60</td>\n",
       "      <td>329</td>\n",
       "      <td>2018-08-16</td>\n",
       "      <td>19</td>\n",
       "      <td>2008-09-15</td>\n",
       "      <td>2018-06-25</td>\n",
       "      <td>100.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>f</td>\n",
       "      <td>NaN</td>\n",
       "      <td>{WASHINGTON}</td>\n",
       "      <td>t</td>\n",
       "      <td>f</td>\n",
       "      <td>strict_14_with_grace_period</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>2</td>\n",
       "      <td>0.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>4291</td>\n",
       "      <td>https://www.airbnb.com/rooms/4291</td>\n",
       "      <td>20180816121209</td>\n",
       "      <td>2018-08-16</td>\n",
       "      <td>Sunrise in Seattle Master Suite</td>\n",
       "      <td>This property is located in the lovely Maple L...</td>\n",
       "      <td>Located in Seattle, this is a spacious, clean ...</td>\n",
       "      <td>This property is located in the lovely Maple L...</td>\n",
       "      <td>none</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>We do not live on the property, however we do ...</td>\n",
       "      <td>We ask that you please use nearby street parki...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://a0.muscache.com/im/pictures/19407574/6...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35749</td>\n",
       "      <td>https://www.airbnb.com/users/show/35749</td>\n",
       "      <td>Jess &amp; Joey</td>\n",
       "      <td>2009-09-02</td>\n",
       "      <td>Seattle, Washington, United States</td>\n",
       "      <td>We're a former Seattle couple who just couldn'...</td>\n",
       "      <td>within an hour</td>\n",
       "      <td>100%</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>https://a0.muscache.com/im/pictures/user/a3c77...</td>\n",
       "      <td>https://a0.muscache.com/im/pictures/user/a3c77...</td>\n",
       "      <td>Roosevelt</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>['email', 'phone', 'facebook', 'reviews', 'kba']</td>\n",
       "      <td>t</td>\n",
       "      <td>t</td>\n",
       "      <td>Seattle, WA, United States</td>\n",
       "      <td>Roosevelt</td>\n",
       "      <td>Roosevelt</td>\n",
       "      <td>Other neighborhoods</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>WA</td>\n",
       "      <td>98115</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Seattle, WA</td>\n",
       "      <td>US</td>\n",
       "      <td>United States</td>\n",
       "      <td>47.687801</td>\n",
       "      <td>-122.313427</td>\n",
       "      <td>t</td>\n",
       "      <td>House</td>\n",
       "      <td>Private room</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Real Bed</td>\n",
       "      <td>{TV,\"Cable TV\",Internet,Wifi,\"Free parking on ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>$82.00</td>\n",
       "      <td>$525.00</td>\n",
       "      <td>$1,925.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>$30.00</td>\n",
       "      <td>1</td>\n",
       "      <td>$0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>60</td>\n",
       "      <td>2 weeks ago</td>\n",
       "      <td>t</td>\n",
       "      <td>13</td>\n",
       "      <td>43</td>\n",
       "      <td>73</td>\n",
       "      <td>348</td>\n",
       "      <td>2018-08-16</td>\n",
       "      <td>57</td>\n",
       "      <td>2013-07-01</td>\n",
       "      <td>2018-08-01</td>\n",
       "      <td>91.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>f</td>\n",
       "      <td>NaN</td>\n",
       "      <td>{WASHINGTON}</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>moderate</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>5</td>\n",
       "      <td>0.91</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   city_index    id                        listing_url       scrape_id last_scraped                                               name                                            summary                                              space                                        description experiences_offered neighborhood_overview                                              notes transit                                    access                                        interaction                                        house_rules  thumbnail_url  medium_url                                        picture_url  xl_picture_url  host_id                                 host_url    host_name  host_since                       host_location                                         host_about host_response_time host_response_rate  host_acceptance_rate host_is_superhost                                 host_thumbnail_url                                   host_picture_url host_neighbourhood  \\\n",
       "0           1  2318  https://www.airbnb.com/rooms/2318  20180816121209   2018-08-16  Casa Madrona - Urban Oasis, 1 block from the P...  Gorgeous, architect remodeled, 1917 Dutch Colo...  Casa Madrona is a gorgeous, architect remodele...  Gorgeous, architect remodeled, 1917 Dutch Colo...                none                   NaN  We adhere to a 10pm -9am quiet hour schedule, ...     NaN  Guests can access any part of the house.  We are a family of three, who live next door a...                              four day minimum stay            NaN         NaN  https://a0.muscache.com/im/pictures/ac08892c-f...             NaN     2536   https://www.airbnb.com/users/show/2536        Megan  2008-08-26  Seattle, Washington, United States  We love travel and adventure! We have stayed i...     within an hour               100%                   NaN                 f  https://a0.muscache.com/im/pictures/user/36c67...  https://a0.muscache.com/im/pictures/user/36c67...              Minor   \n",
       "1           1  4291  https://www.airbnb.com/rooms/4291  20180816121209   2018-08-16                    Sunrise in Seattle Master Suite  This property is located in the lovely Maple L...  Located in Seattle, this is a spacious, clean ...  This property is located in the lovely Maple L...                none                   NaN                                                NaN     NaN                                       NaN  We do not live on the property, however we do ...  We ask that you please use nearby street parki...            NaN         NaN  https://a0.muscache.com/im/pictures/19407574/6...             NaN    35749  https://www.airbnb.com/users/show/35749  Jess & Joey  2009-09-02  Seattle, Washington, United States  We're a former Seattle couple who just couldn'...     within an hour               100%                   NaN                 f  https://a0.muscache.com/im/pictures/user/a3c77...  https://a0.muscache.com/im/pictures/user/a3c77...          Roosevelt   \n",
       "\n",
       "   host_listings_count  host_total_listings_count                                 host_verifications host_has_profile_pic host_identity_verified                      street neighbourhood neighbourhood_cleansed neighbourhood_group_cleansed     city state zipcode   market smart_location country_code        country   latitude   longitude is_location_exact property_type        room_type  accommodates  bathrooms  bedrooms  beds  bed_type                                          amenities  square_feet    price weekly_price monthly_price security_deposit cleaning_fee  guests_included extra_people  minimum_nights  maximum_nights calendar_updated has_availability  availability_30  availability_60  availability_90  availability_365 calendar_last_scraped  number_of_reviews first_review last_review  review_scores_rating  review_scores_accuracy  review_scores_cleanliness  review_scores_checkin  review_scores_communication  review_scores_location  review_scores_value requires_license license  \\\n",
       "0                  2.0                        2.0  ['email', 'phone', 'reviews', 'jumio', 'govern...                    t                      t  Seattle, WA, United States       Madrona                Madrona                 Central Area  Seattle    WA   98122  Seattle    Seattle, WA           US  United States  47.610819 -122.290816                 t         House  Entire home/apt             8        2.5       4.0   4.0  Real Bed  {Internet,Wifi,Kitchen,\"Free parking on premis...          NaN  $296.00          NaN           NaN          $500.00      $275.00                8       $20.00               4             300       2 days ago                t                3               30               60               329            2018-08-16                 19   2008-09-15  2018-06-25                 100.0                    10.0                       10.0                   10.0                         10.0                    10.0                 10.0                f     NaN   \n",
       "1                  5.0                        5.0   ['email', 'phone', 'facebook', 'reviews', 'kba']                    t                      t  Seattle, WA, United States     Roosevelt              Roosevelt          Other neighborhoods  Seattle    WA   98115  Seattle    Seattle, WA           US  United States  47.687801 -122.313427                 t         House     Private room             2        1.0       1.0   1.0  Real Bed  {TV,\"Cable TV\",Internet,Wifi,\"Free parking on ...          NaN   $82.00      $525.00     $1,925.00              NaN       $30.00                1        $0.00               2              60      2 weeks ago                t               13               43               73               348            2018-08-16                 57   2013-07-01  2018-08-01                  91.0                     9.0                        9.0                   10.0                          9.0                     9.0                  9.0                f     NaN   \n",
       "\n",
       "  jurisdiction_names instant_bookable is_business_travel_ready          cancellation_policy require_guest_profile_picture require_guest_phone_verification  calculated_host_listings_count  reviews_per_month  \n",
       "0       {WASHINGTON}                t                        f  strict_14_with_grace_period                             f                                f                               2               0.16  \n",
       "1       {WASHINGTON}                f                        f                     moderate                             f                                f                               5               0.91  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_listings.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 40732 entries, 0 to 26201\n",
      "Data columns (total 97 columns):\n",
      "city_index                          40732 non-null int64\n",
      "id                                  40732 non-null int64\n",
      "listing_url                         40732 non-null object\n",
      "scrape_id                           40732 non-null int64\n",
      "last_scraped                        40732 non-null object\n",
      "name                                40651 non-null object\n",
      "summary                             39340 non-null object\n",
      "space                               26306 non-null object\n",
      "description                         40425 non-null object\n",
      "experiences_offered                 40732 non-null object\n",
      "neighborhood_overview               23380 non-null object\n",
      "notes                               15360 non-null object\n",
      "transit                             24787 non-null object\n",
      "access                              22319 non-null object\n",
      "interaction                         21721 non-null object\n",
      "house_rules                         25025 non-null object\n",
      "thumbnail_url                       0 non-null float64\n",
      "medium_url                          0 non-null float64\n",
      "picture_url                         40732 non-null object\n",
      "xl_picture_url                      0 non-null float64\n",
      "host_id                             40732 non-null int64\n",
      "host_url                            40732 non-null object\n",
      "host_name                           40723 non-null object\n",
      "host_since                          40723 non-null object\n",
      "host_location                       40596 non-null object\n",
      "host_about                          23329 non-null object\n",
      "host_response_time                  27231 non-null object\n",
      "host_response_rate                  27231 non-null object\n",
      "host_acceptance_rate                0 non-null float64\n",
      "host_is_superhost                   40723 non-null object\n",
      "host_thumbnail_url                  40723 non-null object\n",
      "host_picture_url                    40723 non-null object\n",
      "host_neighbourhood                  32233 non-null object\n",
      "host_listings_count                 40723 non-null float64\n",
      "host_total_listings_count           40723 non-null float64\n",
      "host_verifications                  40732 non-null object\n",
      "host_has_profile_pic                40723 non-null object\n",
      "host_identity_verified              40723 non-null object\n",
      "street                              40732 non-null object\n",
      "neighbourhood                       39168 non-null object\n",
      "neighbourhood_cleansed              40732 non-null object\n",
      "neighbourhood_group_cleansed        8494 non-null object\n",
      "city                                40717 non-null object\n",
      "state                               19804 non-null object\n",
      "zipcode                             39852 non-null object\n",
      "market                              39624 non-null object\n",
      "smart_location                      40732 non-null object\n",
      "country_code                        40732 non-null object\n",
      "country                             40732 non-null object\n",
      "latitude                            40732 non-null float64\n",
      "longitude                           40732 non-null float64\n",
      "is_location_exact                   40732 non-null object\n",
      "property_type                       40732 non-null object\n",
      "room_type                           40732 non-null object\n",
      "accommodates                        40732 non-null int64\n",
      "bathrooms                           40704 non-null float64\n",
      "bedrooms                            40719 non-null float64\n",
      "beds                                40710 non-null float64\n",
      "bed_type                            40732 non-null object\n",
      "amenities                           40732 non-null object\n",
      "square_feet                         847 non-null float64\n",
      "price                               40732 non-null object\n",
      "weekly_price                        6355 non-null object\n",
      "monthly_price                       3602 non-null object\n",
      "security_deposit                    22711 non-null object\n",
      "cleaning_fee                        29993 non-null object\n",
      "guests_included                     40732 non-null int64\n",
      "extra_people                        40732 non-null object\n",
      "minimum_nights                      40732 non-null int64\n",
      "maximum_nights                      40732 non-null int64\n",
      "calendar_updated                    40732 non-null object\n",
      "has_availability                    40732 non-null object\n",
      "availability_30                     40732 non-null int64\n",
      "availability_60                     40732 non-null int64\n",
      "availability_90                     40732 non-null int64\n",
      "availability_365                    40732 non-null int64\n",
      "calendar_last_scraped               40732 non-null object\n",
      "number_of_reviews                   40732 non-null int64\n",
      "first_review                        34232 non-null object\n",
      "last_review                         34232 non-null object\n",
      "review_scores_rating                33652 non-null float64\n",
      "review_scores_accuracy              33614 non-null float64\n",
      "review_scores_cleanliness           33622 non-null float64\n",
      "review_scores_checkin               33580 non-null float64\n",
      "review_scores_communication         33614 non-null float64\n",
      "review_scores_location              33578 non-null float64\n",
      "review_scores_value                 33572 non-null float64\n",
      "requires_license                    40732 non-null object\n",
      "license                             6 non-null object\n",
      "jurisdiction_names                  8408 non-null object\n",
      "instant_bookable                    40732 non-null object\n",
      "is_business_travel_ready            40732 non-null object\n",
      "cancellation_policy                 40732 non-null object\n",
      "require_guest_profile_picture       40732 non-null object\n",
      "require_guest_phone_verification    40732 non-null object\n",
      "calculated_host_listings_count      40732 non-null int64\n",
      "reviews_per_month                   34232 non-null float64\n",
      "dtypes: float64(20), int64(14), object(63)\n",
      "memory usage: 30.5+ MB\n"
     ]
    }
   ],
   "source": [
    "all_listings.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, we look the columns with zero non-null values:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['thumbnail_url', 'medium_url', 'xl_picture_url', 'host_acceptance_rate']"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unique_nums = all_listings.nunique()\n",
    "masked_columns = [col for col in all_listings.columns if unique_nums[col] == 0]\n",
    "masked_columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Column `license` is not informative, so I drop it as well:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Counter({'81-5461832': 4, 37468959.0: 2})"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Counter(all_listings.license.dropna())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "masked_columns.append('license')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Look other columns for more details:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>city_index</th>\n",
       "      <th>id</th>\n",
       "      <th>listing_url</th>\n",
       "      <th>scrape_id</th>\n",
       "      <th>last_scraped</th>\n",
       "      <th>name</th>\n",
       "      <th>summary</th>\n",
       "      <th>space</th>\n",
       "      <th>description</th>\n",
       "      <th>experiences_offered</th>\n",
       "      <th>neighborhood_overview</th>\n",
       "      <th>notes</th>\n",
       "      <th>transit</th>\n",
       "      <th>access</th>\n",
       "      <th>interaction</th>\n",
       "      <th>house_rules</th>\n",
       "      <th>thumbnail_url</th>\n",
       "      <th>medium_url</th>\n",
       "      <th>picture_url</th>\n",
       "      <th>xl_picture_url</th>\n",
       "      <th>host_id</th>\n",
       "      <th>host_url</th>\n",
       "      <th>host_name</th>\n",
       "      <th>host_since</th>\n",
       "      <th>host_location</th>\n",
       "      <th>host_about</th>\n",
       "      <th>host_response_time</th>\n",
       "      <th>host_response_rate</th>\n",
       "      <th>host_acceptance_rate</th>\n",
       "      <th>host_is_superhost</th>\n",
       "      <th>host_thumbnail_url</th>\n",
       "      <th>host_picture_url</th>\n",
       "      <th>host_neighbourhood</th>\n",
       "      <th>host_listings_count</th>\n",
       "      <th>host_total_listings_count</th>\n",
       "      <th>host_verifications</th>\n",
       "      <th>host_has_profile_pic</th>\n",
       "      <th>host_identity_verified</th>\n",
       "      <th>street</th>\n",
       "      <th>neighbourhood</th>\n",
       "      <th>neighbourhood_cleansed</th>\n",
       "      <th>neighbourhood_group_cleansed</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>market</th>\n",
       "      <th>smart_location</th>\n",
       "      <th>country_code</th>\n",
       "      <th>country</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>is_location_exact</th>\n",
       "      <th>property_type</th>\n",
       "      <th>room_type</th>\n",
       "      <th>accommodates</th>\n",
       "      <th>bathrooms</th>\n",
       "      <th>bedrooms</th>\n",
       "      <th>beds</th>\n",
       "      <th>bed_type</th>\n",
       "      <th>amenities</th>\n",
       "      <th>square_feet</th>\n",
       "      <th>price</th>\n",
       "      <th>weekly_price</th>\n",
       "      <th>monthly_price</th>\n",
       "      <th>security_deposit</th>\n",
       "      <th>cleaning_fee</th>\n",
       "      <th>guests_included</th>\n",
       "      <th>extra_people</th>\n",
       "      <th>minimum_nights</th>\n",
       "      <th>maximum_nights</th>\n",
       "      <th>calendar_updated</th>\n",
       "      <th>has_availability</th>\n",
       "      <th>availability_30</th>\n",
       "      <th>availability_60</th>\n",
       "      <th>availability_90</th>\n",
       "      <th>availability_365</th>\n",
       "      <th>calendar_last_scraped</th>\n",
       "      <th>number_of_reviews</th>\n",
       "      <th>first_review</th>\n",
       "      <th>last_review</th>\n",
       "      <th>review_scores_rating</th>\n",
       "      <th>review_scores_accuracy</th>\n",
       "      <th>review_scores_cleanliness</th>\n",
       "      <th>review_scores_checkin</th>\n",
       "      <th>review_scores_communication</th>\n",
       "      <th>review_scores_location</th>\n",
       "      <th>review_scores_value</th>\n",
       "      <th>requires_license</th>\n",
       "      <th>license</th>\n",
       "      <th>jurisdiction_names</th>\n",
       "      <th>instant_bookable</th>\n",
       "      <th>is_business_travel_ready</th>\n",
       "      <th>cancellation_policy</th>\n",
       "      <th>require_guest_profile_picture</th>\n",
       "      <th>require_guest_phone_verification</th>\n",
       "      <th>calculated_host_listings_count</th>\n",
       "      <th>reviews_per_month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2318</td>\n",
       "      <td>https://www.airbnb.com/rooms/2318</td>\n",
       "      <td>20180816121209</td>\n",
       "      <td>2018-08-16</td>\n",
       "      <td>Casa Madrona - Urban Oasis, 1 block from the P...</td>\n",
       "      <td>Gorgeous, architect remodeled, 1917 Dutch Colo...</td>\n",
       "      <td>Casa Madrona is a gorgeous, architect remodele...</td>\n",
       "      <td>Gorgeous, architect remodeled, 1917 Dutch Colo...</td>\n",
       "      <td>none</td>\n",
       "      <td>NaN</td>\n",
       "      <td>We adhere to a 10pm -9am quiet hour schedule, ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Guests can access any part of the house.</td>\n",
       "      <td>We are a family of three, who live next door a...</td>\n",
       "      <td>four day minimum stay</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://a0.muscache.com/im/pictures/ac08892c-f...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2536</td>\n",
       "      <td>https://www.airbnb.com/users/show/2536</td>\n",
       "      <td>Megan</td>\n",
       "      <td>2008-08-26</td>\n",
       "      <td>Seattle, Washington, United States</td>\n",
       "      <td>We love travel and adventure! We have stayed i...</td>\n",
       "      <td>within an hour</td>\n",
       "      <td>100%</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>https://a0.muscache.com/im/pictures/user/36c67...</td>\n",
       "      <td>https://a0.muscache.com/im/pictures/user/36c67...</td>\n",
       "      <td>Minor</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>['email', 'phone', 'reviews', 'jumio', 'govern...</td>\n",
       "      <td>t</td>\n",
       "      <td>t</td>\n",
       "      <td>Seattle, WA, United States</td>\n",
       "      <td>Madrona</td>\n",
       "      <td>Madrona</td>\n",
       "      <td>Central Area</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>WA</td>\n",
       "      <td>98122</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Seattle, WA</td>\n",
       "      <td>US</td>\n",
       "      <td>United States</td>\n",
       "      <td>47.610819</td>\n",
       "      <td>-122.290816</td>\n",
       "      <td>t</td>\n",
       "      <td>House</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>8</td>\n",
       "      <td>2.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Real Bed</td>\n",
       "      <td>{Internet,Wifi,Kitchen,\"Free parking on premis...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>$296.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>$500.00</td>\n",
       "      <td>$275.00</td>\n",
       "      <td>8</td>\n",
       "      <td>$20.00</td>\n",
       "      <td>4</td>\n",
       "      <td>300</td>\n",
       "      <td>2 days ago</td>\n",
       "      <td>t</td>\n",
       "      <td>3</td>\n",
       "      <td>30</td>\n",
       "      <td>60</td>\n",
       "      <td>329</td>\n",
       "      <td>2018-08-16</td>\n",
       "      <td>19</td>\n",
       "      <td>2008-09-15</td>\n",
       "      <td>2018-06-25</td>\n",
       "      <td>100.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>f</td>\n",
       "      <td>NaN</td>\n",
       "      <td>{WASHINGTON}</td>\n",
       "      <td>t</td>\n",
       "      <td>f</td>\n",
       "      <td>strict_14_with_grace_period</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>2</td>\n",
       "      <td>0.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>4291</td>\n",
       "      <td>https://www.airbnb.com/rooms/4291</td>\n",
       "      <td>20180816121209</td>\n",
       "      <td>2018-08-16</td>\n",
       "      <td>Sunrise in Seattle Master Suite</td>\n",
       "      <td>This property is located in the lovely Maple L...</td>\n",
       "      <td>Located in Seattle, this is a spacious, clean ...</td>\n",
       "      <td>This property is located in the lovely Maple L...</td>\n",
       "      <td>none</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>We do not live on the property, however we do ...</td>\n",
       "      <td>We ask that you please use nearby street parki...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://a0.muscache.com/im/pictures/19407574/6...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35749</td>\n",
       "      <td>https://www.airbnb.com/users/show/35749</td>\n",
       "      <td>Jess &amp; Joey</td>\n",
       "      <td>2009-09-02</td>\n",
       "      <td>Seattle, Washington, United States</td>\n",
       "      <td>We're a former Seattle couple who just couldn'...</td>\n",
       "      <td>within an hour</td>\n",
       "      <td>100%</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>https://a0.muscache.com/im/pictures/user/a3c77...</td>\n",
       "      <td>https://a0.muscache.com/im/pictures/user/a3c77...</td>\n",
       "      <td>Roosevelt</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>['email', 'phone', 'facebook', 'reviews', 'kba']</td>\n",
       "      <td>t</td>\n",
       "      <td>t</td>\n",
       "      <td>Seattle, WA, United States</td>\n",
       "      <td>Roosevelt</td>\n",
       "      <td>Roosevelt</td>\n",
       "      <td>Other neighborhoods</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>WA</td>\n",
       "      <td>98115</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Seattle, WA</td>\n",
       "      <td>US</td>\n",
       "      <td>United States</td>\n",
       "      <td>47.687801</td>\n",
       "      <td>-122.313427</td>\n",
       "      <td>t</td>\n",
       "      <td>House</td>\n",
       "      <td>Private room</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Real Bed</td>\n",
       "      <td>{TV,\"Cable TV\",Internet,Wifi,\"Free parking on ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>$82.00</td>\n",
       "      <td>$525.00</td>\n",
       "      <td>$1,925.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>$30.00</td>\n",
       "      <td>1</td>\n",
       "      <td>$0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>60</td>\n",
       "      <td>2 weeks ago</td>\n",
       "      <td>t</td>\n",
       "      <td>13</td>\n",
       "      <td>43</td>\n",
       "      <td>73</td>\n",
       "      <td>348</td>\n",
       "      <td>2018-08-16</td>\n",
       "      <td>57</td>\n",
       "      <td>2013-07-01</td>\n",
       "      <td>2018-08-01</td>\n",
       "      <td>91.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>f</td>\n",
       "      <td>NaN</td>\n",
       "      <td>{WASHINGTON}</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>moderate</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>5</td>\n",
       "      <td>0.91</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   city_index    id                        listing_url       scrape_id last_scraped                                               name                                            summary                                              space                                        description experiences_offered neighborhood_overview                                              notes transit                                    access                                        interaction                                        house_rules  thumbnail_url  medium_url                                        picture_url  xl_picture_url  host_id                                 host_url    host_name  host_since                       host_location                                         host_about host_response_time host_response_rate  host_acceptance_rate host_is_superhost                                 host_thumbnail_url                                   host_picture_url host_neighbourhood  \\\n",
       "0           1  2318  https://www.airbnb.com/rooms/2318  20180816121209   2018-08-16  Casa Madrona - Urban Oasis, 1 block from the P...  Gorgeous, architect remodeled, 1917 Dutch Colo...  Casa Madrona is a gorgeous, architect remodele...  Gorgeous, architect remodeled, 1917 Dutch Colo...                none                   NaN  We adhere to a 10pm -9am quiet hour schedule, ...     NaN  Guests can access any part of the house.  We are a family of three, who live next door a...                              four day minimum stay            NaN         NaN  https://a0.muscache.com/im/pictures/ac08892c-f...             NaN     2536   https://www.airbnb.com/users/show/2536        Megan  2008-08-26  Seattle, Washington, United States  We love travel and adventure! We have stayed i...     within an hour               100%                   NaN                 f  https://a0.muscache.com/im/pictures/user/36c67...  https://a0.muscache.com/im/pictures/user/36c67...              Minor   \n",
       "1           1  4291  https://www.airbnb.com/rooms/4291  20180816121209   2018-08-16                    Sunrise in Seattle Master Suite  This property is located in the lovely Maple L...  Located in Seattle, this is a spacious, clean ...  This property is located in the lovely Maple L...                none                   NaN                                                NaN     NaN                                       NaN  We do not live on the property, however we do ...  We ask that you please use nearby street parki...            NaN         NaN  https://a0.muscache.com/im/pictures/19407574/6...             NaN    35749  https://www.airbnb.com/users/show/35749  Jess & Joey  2009-09-02  Seattle, Washington, United States  We're a former Seattle couple who just couldn'...     within an hour               100%                   NaN                 f  https://a0.muscache.com/im/pictures/user/a3c77...  https://a0.muscache.com/im/pictures/user/a3c77...          Roosevelt   \n",
       "\n",
       "   host_listings_count  host_total_listings_count                                 host_verifications host_has_profile_pic host_identity_verified                      street neighbourhood neighbourhood_cleansed neighbourhood_group_cleansed     city state zipcode   market smart_location country_code        country   latitude   longitude is_location_exact property_type        room_type  accommodates  bathrooms  bedrooms  beds  bed_type                                          amenities  square_feet    price weekly_price monthly_price security_deposit cleaning_fee  guests_included extra_people  minimum_nights  maximum_nights calendar_updated has_availability  availability_30  availability_60  availability_90  availability_365 calendar_last_scraped  number_of_reviews first_review last_review  review_scores_rating  review_scores_accuracy  review_scores_cleanliness  review_scores_checkin  review_scores_communication  review_scores_location  review_scores_value requires_license license  \\\n",
       "0                  2.0                        2.0  ['email', 'phone', 'reviews', 'jumio', 'govern...                    t                      t  Seattle, WA, United States       Madrona                Madrona                 Central Area  Seattle    WA   98122  Seattle    Seattle, WA           US  United States  47.610819 -122.290816                 t         House  Entire home/apt             8        2.5       4.0   4.0  Real Bed  {Internet,Wifi,Kitchen,\"Free parking on premis...          NaN  $296.00          NaN           NaN          $500.00      $275.00                8       $20.00               4             300       2 days ago                t                3               30               60               329            2018-08-16                 19   2008-09-15  2018-06-25                 100.0                    10.0                       10.0                   10.0                         10.0                    10.0                 10.0                f     NaN   \n",
       "1                  5.0                        5.0   ['email', 'phone', 'facebook', 'reviews', 'kba']                    t                      t  Seattle, WA, United States     Roosevelt              Roosevelt          Other neighborhoods  Seattle    WA   98115  Seattle    Seattle, WA           US  United States  47.687801 -122.313427                 t         House     Private room             2        1.0       1.0   1.0  Real Bed  {TV,\"Cable TV\",Internet,Wifi,\"Free parking on ...          NaN   $82.00      $525.00     $1,925.00              NaN       $30.00                1        $0.00               2              60      2 weeks ago                t               13               43               73               348            2018-08-16                 57   2013-07-01  2018-08-01                  91.0                     9.0                        9.0                   10.0                          9.0                     9.0                  9.0                f     NaN   \n",
       "\n",
       "  jurisdiction_names instant_bookable is_business_travel_ready          cancellation_policy require_guest_profile_picture require_guest_phone_verification  calculated_host_listings_count  reviews_per_month  \n",
       "0       {WASHINGTON}                t                        f  strict_14_with_grace_period                             f                                f                               2               0.16  \n",
       "1       {WASHINGTON}                f                        f                     moderate                             f                                f                               5               0.91  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_listings.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we see, it is worth to drop columns such as `id`, `listing_url`, `scrape_id`, `picture_url`, `host_url`, `host_thumbnail_url`, `host_picture_url`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "masked_columns += ['id', \n",
    "                   'listing_url', \n",
    "                   'scrape_id', \n",
    "                   'host_id',\n",
    "                   'picture_url', \n",
    "                   'host_url', \n",
    "                   'host_thumbnail_url', \n",
    "                   'host_picture_url']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_listings.drop(masked_columns, axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Some categorical columns need to be converted into numeric. For example, look on price columns, they are categorical because of '$' sign before the total price:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "price_cols = ['price', \n",
    "              'weekly_price', \n",
    "              'monthly_price', \n",
    "              'security_deposit', \n",
    "              'cleaning_fee', \n",
    "              'extra_people']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['$296.00'], dtype=object)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_listings.head(1).price.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "s1 = '$296.00'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "296.0"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def prices_to_numbers(price_string):\n",
    "    '''\n",
    "    Converts USD prices from string to numeric format\n",
    "    \n",
    "    Args:\n",
    "        price_string (string): USD price in string format (e.g., '$123,456.00')\n",
    "    \n",
    "    Returns:\n",
    "        price_numeric (float): USD price in numeric format (e.g., 123456.00)\n",
    "    '''\n",
    "    \n",
    "    price_numeric = float(str(price_string).replace(',', '').split('$')[-1])\n",
    "    return price_numeric\n",
    "\n",
    "prices_to_numbers(s1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "price\n",
      "weekly_price\n",
      "monthly_price\n",
      "security_deposit\n",
      "cleaning_fee\n",
      "extra_people\n"
     ]
    }
   ],
   "source": [
    "for col in price_cols:\n",
    "    print(col)\n",
    "    all_listings[col] = all_listings[col].apply(prices_to_numbers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>city_index</th>\n",
       "      <th>last_scraped</th>\n",
       "      <th>name</th>\n",
       "      <th>summary</th>\n",
       "      <th>space</th>\n",
       "      <th>description</th>\n",
       "      <th>experiences_offered</th>\n",
       "      <th>neighborhood_overview</th>\n",
       "      <th>notes</th>\n",
       "      <th>transit</th>\n",
       "      <th>access</th>\n",
       "      <th>interaction</th>\n",
       "      <th>house_rules</th>\n",
       "      <th>host_name</th>\n",
       "      <th>host_since</th>\n",
       "      <th>host_location</th>\n",
       "      <th>host_about</th>\n",
       "      <th>host_response_time</th>\n",
       "      <th>host_response_rate</th>\n",
       "      <th>host_is_superhost</th>\n",
       "      <th>host_neighbourhood</th>\n",
       "      <th>host_listings_count</th>\n",
       "      <th>host_total_listings_count</th>\n",
       "      <th>host_verifications</th>\n",
       "      <th>host_has_profile_pic</th>\n",
       "      <th>host_identity_verified</th>\n",
       "      <th>street</th>\n",
       "      <th>neighbourhood</th>\n",
       "      <th>neighbourhood_cleansed</th>\n",
       "      <th>neighbourhood_group_cleansed</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>market</th>\n",
       "      <th>smart_location</th>\n",
       "      <th>country_code</th>\n",
       "      <th>country</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>is_location_exact</th>\n",
       "      <th>property_type</th>\n",
       "      <th>room_type</th>\n",
       "      <th>accommodates</th>\n",
       "      <th>bathrooms</th>\n",
       "      <th>bedrooms</th>\n",
       "      <th>beds</th>\n",
       "      <th>bed_type</th>\n",
       "      <th>amenities</th>\n",
       "      <th>square_feet</th>\n",
       "      <th>price</th>\n",
       "      <th>weekly_price</th>\n",
       "      <th>monthly_price</th>\n",
       "      <th>security_deposit</th>\n",
       "      <th>cleaning_fee</th>\n",
       "      <th>guests_included</th>\n",
       "      <th>extra_people</th>\n",
       "      <th>minimum_nights</th>\n",
       "      <th>maximum_nights</th>\n",
       "      <th>calendar_updated</th>\n",
       "      <th>has_availability</th>\n",
       "      <th>availability_30</th>\n",
       "      <th>availability_60</th>\n",
       "      <th>availability_90</th>\n",
       "      <th>availability_365</th>\n",
       "      <th>calendar_last_scraped</th>\n",
       "      <th>number_of_reviews</th>\n",
       "      <th>first_review</th>\n",
       "      <th>last_review</th>\n",
       "      <th>review_scores_rating</th>\n",
       "      <th>review_scores_accuracy</th>\n",
       "      <th>review_scores_cleanliness</th>\n",
       "      <th>review_scores_checkin</th>\n",
       "      <th>review_scores_communication</th>\n",
       "      <th>review_scores_location</th>\n",
       "      <th>review_scores_value</th>\n",
       "      <th>requires_license</th>\n",
       "      <th>jurisdiction_names</th>\n",
       "      <th>instant_bookable</th>\n",
       "      <th>is_business_travel_ready</th>\n",
       "      <th>cancellation_policy</th>\n",
       "      <th>require_guest_profile_picture</th>\n",
       "      <th>require_guest_phone_verification</th>\n",
       "      <th>calculated_host_listings_count</th>\n",
       "      <th>reviews_per_month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2018-08-16</td>\n",
       "      <td>Casa Madrona - Urban Oasis, 1 block from the P...</td>\n",
       "      <td>Gorgeous, architect remodeled, 1917 Dutch Colo...</td>\n",
       "      <td>Casa Madrona is a gorgeous, architect remodele...</td>\n",
       "      <td>Gorgeous, architect remodeled, 1917 Dutch Colo...</td>\n",
       "      <td>none</td>\n",
       "      <td>NaN</td>\n",
       "      <td>We adhere to a 10pm -9am quiet hour schedule, ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Guests can access any part of the house.</td>\n",
       "      <td>We are a family of three, who live next door a...</td>\n",
       "      <td>four day minimum stay</td>\n",
       "      <td>Megan</td>\n",
       "      <td>2008-08-26</td>\n",
       "      <td>Seattle, Washington, United States</td>\n",
       "      <td>We love travel and adventure! We have stayed i...</td>\n",
       "      <td>within an hour</td>\n",
       "      <td>100%</td>\n",
       "      <td>f</td>\n",
       "      <td>Minor</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>['email', 'phone', 'reviews', 'jumio', 'govern...</td>\n",
       "      <td>t</td>\n",
       "      <td>t</td>\n",
       "      <td>Seattle, WA, United States</td>\n",
       "      <td>Madrona</td>\n",
       "      <td>Madrona</td>\n",
       "      <td>Central Area</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>WA</td>\n",
       "      <td>98122</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Seattle, WA</td>\n",
       "      <td>US</td>\n",
       "      <td>United States</td>\n",
       "      <td>47.610819</td>\n",
       "      <td>-122.290816</td>\n",
       "      <td>t</td>\n",
       "      <td>House</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>8</td>\n",
       "      <td>2.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Real Bed</td>\n",
       "      <td>{Internet,Wifi,Kitchen,\"Free parking on premis...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>296.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>500.0</td>\n",
       "      <td>275.0</td>\n",
       "      <td>8</td>\n",
       "      <td>20.0</td>\n",
       "      <td>4</td>\n",
       "      <td>300</td>\n",
       "      <td>2 days ago</td>\n",
       "      <td>t</td>\n",
       "      <td>3</td>\n",
       "      <td>30</td>\n",
       "      <td>60</td>\n",
       "      <td>329</td>\n",
       "      <td>2018-08-16</td>\n",
       "      <td>19</td>\n",
       "      <td>2008-09-15</td>\n",
       "      <td>2018-06-25</td>\n",
       "      <td>100.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>f</td>\n",
       "      <td>{WASHINGTON}</td>\n",
       "      <td>t</td>\n",
       "      <td>f</td>\n",
       "      <td>strict_14_with_grace_period</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>2</td>\n",
       "      <td>0.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2018-08-16</td>\n",
       "      <td>Sunrise in Seattle Master Suite</td>\n",
       "      <td>This property is located in the lovely Maple L...</td>\n",
       "      <td>Located in Seattle, this is a spacious, clean ...</td>\n",
       "      <td>This property is located in the lovely Maple L...</td>\n",
       "      <td>none</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>We do not live on the property, however we do ...</td>\n",
       "      <td>We ask that you please use nearby street parki...</td>\n",
       "      <td>Jess &amp; Joey</td>\n",
       "      <td>2009-09-02</td>\n",
       "      <td>Seattle, Washington, United States</td>\n",
       "      <td>We're a former Seattle couple who just couldn'...</td>\n",
       "      <td>within an hour</td>\n",
       "      <td>100%</td>\n",
       "      <td>f</td>\n",
       "      <td>Roosevelt</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>['email', 'phone', 'facebook', 'reviews', 'kba']</td>\n",
       "      <td>t</td>\n",
       "      <td>t</td>\n",
       "      <td>Seattle, WA, United States</td>\n",
       "      <td>Roosevelt</td>\n",
       "      <td>Roosevelt</td>\n",
       "      <td>Other neighborhoods</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>WA</td>\n",
       "      <td>98115</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Seattle, WA</td>\n",
       "      <td>US</td>\n",
       "      <td>United States</td>\n",
       "      <td>47.687801</td>\n",
       "      <td>-122.313427</td>\n",
       "      <td>t</td>\n",
       "      <td>House</td>\n",
       "      <td>Private room</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Real Bed</td>\n",
       "      <td>{TV,\"Cable TV\",Internet,Wifi,\"Free parking on ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>82.0</td>\n",
       "      <td>525.0</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>60</td>\n",
       "      <td>2 weeks ago</td>\n",
       "      <td>t</td>\n",
       "      <td>13</td>\n",
       "      <td>43</td>\n",
       "      <td>73</td>\n",
       "      <td>348</td>\n",
       "      <td>2018-08-16</td>\n",
       "      <td>57</td>\n",
       "      <td>2013-07-01</td>\n",
       "      <td>2018-08-01</td>\n",
       "      <td>91.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>f</td>\n",
       "      <td>{WASHINGTON}</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>moderate</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>5</td>\n",
       "      <td>0.91</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   city_index last_scraped                                               name                                            summary                                              space                                        description experiences_offered neighborhood_overview                                              notes transit                                    access                                        interaction                                        house_rules    host_name  host_since                       host_location                                         host_about host_response_time host_response_rate host_is_superhost host_neighbourhood  host_listings_count  host_total_listings_count                                 host_verifications host_has_profile_pic host_identity_verified                      street neighbourhood neighbourhood_cleansed neighbourhood_group_cleansed     city state zipcode   market smart_location country_code        country   latitude   longitude  \\\n",
       "0           1   2018-08-16  Casa Madrona - Urban Oasis, 1 block from the P...  Gorgeous, architect remodeled, 1917 Dutch Colo...  Casa Madrona is a gorgeous, architect remodele...  Gorgeous, architect remodeled, 1917 Dutch Colo...                none                   NaN  We adhere to a 10pm -9am quiet hour schedule, ...     NaN  Guests can access any part of the house.  We are a family of three, who live next door a...                              four day minimum stay        Megan  2008-08-26  Seattle, Washington, United States  We love travel and adventure! We have stayed i...     within an hour               100%                 f              Minor                  2.0                        2.0  ['email', 'phone', 'reviews', 'jumio', 'govern...                    t                      t  Seattle, WA, United States       Madrona                Madrona                 Central Area  Seattle    WA   98122  Seattle    Seattle, WA           US  United States  47.610819 -122.290816   \n",
       "1           1   2018-08-16                    Sunrise in Seattle Master Suite  This property is located in the lovely Maple L...  Located in Seattle, this is a spacious, clean ...  This property is located in the lovely Maple L...                none                   NaN                                                NaN     NaN                                       NaN  We do not live on the property, however we do ...  We ask that you please use nearby street parki...  Jess & Joey  2009-09-02  Seattle, Washington, United States  We're a former Seattle couple who just couldn'...     within an hour               100%                 f          Roosevelt                  5.0                        5.0   ['email', 'phone', 'facebook', 'reviews', 'kba']                    t                      t  Seattle, WA, United States     Roosevelt              Roosevelt          Other neighborhoods  Seattle    WA   98115  Seattle    Seattle, WA           US  United States  47.687801 -122.313427   \n",
       "\n",
       "  is_location_exact property_type        room_type  accommodates  bathrooms  bedrooms  beds  bed_type                                          amenities  square_feet  price  weekly_price  monthly_price  security_deposit  cleaning_fee  guests_included  extra_people  minimum_nights  maximum_nights calendar_updated has_availability  availability_30  availability_60  availability_90  availability_365 calendar_last_scraped  number_of_reviews first_review last_review  review_scores_rating  review_scores_accuracy  review_scores_cleanliness  review_scores_checkin  review_scores_communication  review_scores_location  review_scores_value requires_license jurisdiction_names instant_bookable is_business_travel_ready          cancellation_policy require_guest_profile_picture require_guest_phone_verification  calculated_host_listings_count  reviews_per_month  \n",
       "0                 t         House  Entire home/apt             8        2.5       4.0   4.0  Real Bed  {Internet,Wifi,Kitchen,\"Free parking on premis...          NaN  296.0           NaN            NaN             500.0         275.0                8          20.0               4             300       2 days ago                t                3               30               60               329            2018-08-16                 19   2008-09-15  2018-06-25                 100.0                    10.0                       10.0                   10.0                         10.0                    10.0                 10.0                f       {WASHINGTON}                t                        f  strict_14_with_grace_period                             f                                f                               2               0.16  \n",
       "1                 t         House     Private room             2        1.0       1.0   1.0  Real Bed  {TV,\"Cable TV\",Internet,Wifi,\"Free parking on ...          NaN   82.0         525.0         1925.0               NaN          30.0                1           0.0               2              60      2 weeks ago                t               13               43               73               348            2018-08-16                 57   2013-07-01  2018-08-01                  91.0                     9.0                        9.0                   10.0                          9.0                     9.0                  9.0                f       {WASHINGTON}                f                        f                     moderate                             f                                f                               5               0.91  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_listings.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Also, some of the categorical columns are in fact Boolean and require conversion:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "boolean_cols = ['host_is_superhost', \n",
    "               'host_has_profile_pic',\n",
    "               'host_identity_verified',\n",
    "               'is_location_exact',\n",
    "               'has_availability',\n",
    "               'requires_license',\n",
    "               'instant_bookable',\n",
    "               'is_business_travel_ready',\n",
    "               'require_guest_profile_picture',\n",
    "               'require_guest_phone_verification']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "def booleans_to_numbers(s):\n",
    "    '''\n",
    "    Converts \"first letter boolean\" strings to integers\n",
    "    \n",
    "    Args:\n",
    "        bool_string (string): 't', 'f' or other\n",
    "    \n",
    "    Returns:\n",
    "        bool_number (int): 1, 0 or None\n",
    "    '''\n",
    "    \n",
    "    \n",
    "    if s == 'f':\n",
    "        return 0\n",
    "    elif s == 't':\n",
    "        return 1\n",
    "    return None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "host_is_superhost\n",
      "host_has_profile_pic\n",
      "host_identity_verified\n",
      "is_location_exact\n",
      "has_availability\n",
      "requires_license\n",
      "instant_bookable\n",
      "is_business_travel_ready\n",
      "require_guest_profile_picture\n",
      "require_guest_phone_verification\n"
     ]
    }
   ],
   "source": [
    "for col in boolean_cols:\n",
    "    print(col)\n",
    "    all_listings[col] = all_listings[col].apply(booleans_to_numbers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>last_scraped</th>\n",
       "      <th>name</th>\n",
       "      <th>summary</th>\n",
       "      <th>space</th>\n",
       "      <th>description</th>\n",
       "      <th>experiences_offered</th>\n",
       "      <th>neighborhood_overview</th>\n",
       "      <th>notes</th>\n",
       "      <th>transit</th>\n",
       "      <th>access</th>\n",
       "      <th>interaction</th>\n",
       "      <th>house_rules</th>\n",
       "      <th>host_name</th>\n",
       "      <th>host_since</th>\n",
       "      <th>host_location</th>\n",
       "      <th>host_about</th>\n",
       "      <th>host_response_time</th>\n",
       "      <th>host_response_rate</th>\n",
       "      <th>host_neighbourhood</th>\n",
       "      <th>host_verifications</th>\n",
       "      <th>street</th>\n",
       "      <th>neighbourhood</th>\n",
       "      <th>neighbourhood_cleansed</th>\n",
       "      <th>neighbourhood_group_cleansed</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>market</th>\n",
       "      <th>smart_location</th>\n",
       "      <th>country_code</th>\n",
       "      <th>country</th>\n",
       "      <th>property_type</th>\n",
       "      <th>room_type</th>\n",
       "      <th>bed_type</th>\n",
       "      <th>amenities</th>\n",
       "      <th>calendar_updated</th>\n",
       "      <th>calendar_last_scraped</th>\n",
       "      <th>first_review</th>\n",
       "      <th>last_review</th>\n",
       "      <th>jurisdiction_names</th>\n",
       "      <th>cancellation_policy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-08-16</td>\n",
       "      <td>Casa Madrona - Urban Oasis, 1 block from the P...</td>\n",
       "      <td>Gorgeous, architect remodeled, 1917 Dutch Colo...</td>\n",
       "      <td>Casa Madrona is a gorgeous, architect remodele...</td>\n",
       "      <td>Gorgeous, architect remodeled, 1917 Dutch Colo...</td>\n",
       "      <td>none</td>\n",
       "      <td>NaN</td>\n",
       "      <td>We adhere to a 10pm -9am quiet hour schedule, ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Guests can access any part of the house.</td>\n",
       "      <td>We are a family of three, who live next door a...</td>\n",
       "      <td>four day minimum stay</td>\n",
       "      <td>Megan</td>\n",
       "      <td>2008-08-26</td>\n",
       "      <td>Seattle, Washington, United States</td>\n",
       "      <td>We love travel and adventure! We have stayed i...</td>\n",
       "      <td>within an hour</td>\n",
       "      <td>100%</td>\n",
       "      <td>Minor</td>\n",
       "      <td>['email', 'phone', 'reviews', 'jumio', 'govern...</td>\n",
       "      <td>Seattle, WA, United States</td>\n",
       "      <td>Madrona</td>\n",
       "      <td>Madrona</td>\n",
       "      <td>Central Area</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>WA</td>\n",
       "      <td>98122</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Seattle, WA</td>\n",
       "      <td>US</td>\n",
       "      <td>United States</td>\n",
       "      <td>House</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>Real Bed</td>\n",
       "      <td>{Internet,Wifi,Kitchen,\"Free parking on premis...</td>\n",
       "      <td>2 days ago</td>\n",
       "      <td>2018-08-16</td>\n",
       "      <td>2008-09-15</td>\n",
       "      <td>2018-06-25</td>\n",
       "      <td>{WASHINGTON}</td>\n",
       "      <td>strict_14_with_grace_period</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-08-16</td>\n",
       "      <td>Sunrise in Seattle Master Suite</td>\n",
       "      <td>This property is located in the lovely Maple L...</td>\n",
       "      <td>Located in Seattle, this is a spacious, clean ...</td>\n",
       "      <td>This property is located in the lovely Maple L...</td>\n",
       "      <td>none</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>We do not live on the property, however we do ...</td>\n",
       "      <td>We ask that you please use nearby street parki...</td>\n",
       "      <td>Jess &amp; Joey</td>\n",
       "      <td>2009-09-02</td>\n",
       "      <td>Seattle, Washington, United States</td>\n",
       "      <td>We're a former Seattle couple who just couldn'...</td>\n",
       "      <td>within an hour</td>\n",
       "      <td>100%</td>\n",
       "      <td>Roosevelt</td>\n",
       "      <td>['email', 'phone', 'facebook', 'reviews', 'kba']</td>\n",
       "      <td>Seattle, WA, United States</td>\n",
       "      <td>Roosevelt</td>\n",
       "      <td>Roosevelt</td>\n",
       "      <td>Other neighborhoods</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>WA</td>\n",
       "      <td>98115</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Seattle, WA</td>\n",
       "      <td>US</td>\n",
       "      <td>United States</td>\n",
       "      <td>House</td>\n",
       "      <td>Private room</td>\n",
       "      <td>Real Bed</td>\n",
       "      <td>{TV,\"Cable TV\",Internet,Wifi,\"Free parking on ...</td>\n",
       "      <td>2 weeks ago</td>\n",
       "      <td>2018-08-16</td>\n",
       "      <td>2013-07-01</td>\n",
       "      <td>2018-08-01</td>\n",
       "      <td>{WASHINGTON}</td>\n",
       "      <td>moderate</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  last_scraped                                               name                                            summary                                              space                                        description experiences_offered neighborhood_overview                                              notes transit                                    access                                        interaction                                        house_rules    host_name  host_since                       host_location                                         host_about host_response_time host_response_rate host_neighbourhood                                 host_verifications                      street neighbourhood neighbourhood_cleansed neighbourhood_group_cleansed     city state zipcode   market smart_location country_code        country property_type        room_type  bed_type                                          amenities calendar_updated calendar_last_scraped first_review  \\\n",
       "0   2018-08-16  Casa Madrona - Urban Oasis, 1 block from the P...  Gorgeous, architect remodeled, 1917 Dutch Colo...  Casa Madrona is a gorgeous, architect remodele...  Gorgeous, architect remodeled, 1917 Dutch Colo...                none                   NaN  We adhere to a 10pm -9am quiet hour schedule, ...     NaN  Guests can access any part of the house.  We are a family of three, who live next door a...                              four day minimum stay        Megan  2008-08-26  Seattle, Washington, United States  We love travel and adventure! We have stayed i...     within an hour               100%              Minor  ['email', 'phone', 'reviews', 'jumio', 'govern...  Seattle, WA, United States       Madrona                Madrona                 Central Area  Seattle    WA   98122  Seattle    Seattle, WA           US  United States         House  Entire home/apt  Real Bed  {Internet,Wifi,Kitchen,\"Free parking on premis...       2 days ago            2018-08-16   2008-09-15   \n",
       "1   2018-08-16                    Sunrise in Seattle Master Suite  This property is located in the lovely Maple L...  Located in Seattle, this is a spacious, clean ...  This property is located in the lovely Maple L...                none                   NaN                                                NaN     NaN                                       NaN  We do not live on the property, however we do ...  We ask that you please use nearby street parki...  Jess & Joey  2009-09-02  Seattle, Washington, United States  We're a former Seattle couple who just couldn'...     within an hour               100%          Roosevelt   ['email', 'phone', 'facebook', 'reviews', 'kba']  Seattle, WA, United States     Roosevelt              Roosevelt          Other neighborhoods  Seattle    WA   98115  Seattle    Seattle, WA           US  United States         House     Private room  Real Bed  {TV,\"Cable TV\",Internet,Wifi,\"Free parking on ...      2 weeks ago            2018-08-16   2013-07-01   \n",
       "\n",
       "  last_review jurisdiction_names          cancellation_policy  \n",
       "0  2018-06-25       {WASHINGTON}  strict_14_with_grace_period  \n",
       "1  2018-08-01       {WASHINGTON}                     moderate  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_listings.select_dtypes(object).head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, we will not use textual description columns and datetime columns (except `date_scraped` and `host_since`, which will be used to calculate host experience), it is time to drop them:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "textual_datetime_cols = ['name',\n",
    "                        'summary',\n",
    "                        'space',\n",
    "                        'description',\n",
    "                        'neighborhood_overview',\n",
    "                        'notes',\n",
    "                        'transit',\n",
    "                        'access',\n",
    "                        'interaction',\n",
    "                        'host_name',\n",
    "                        'host_location',\n",
    "                        'host_about',\n",
    "                        'host_neighbourhood',\n",
    "                        'street',\n",
    "                        'neighbourhood',\n",
    "                        'neighbourhood_cleansed',\n",
    "                        'neighbourhood_group_cleansed',\n",
    "                        'state',\n",
    "                        'zipcode',\n",
    "                        'market',\n",
    "                        'smart_location',\n",
    "                        'city',\n",
    "                        'country_code',\n",
    "                        'country', \n",
    "                        'calendar_updated', \n",
    "                        'calendar_last_scraped', \n",
    "                        'first_review',\n",
    "                        'last_review', \n",
    "                        'jurisdiction_names',\n",
    "                        'experiences_offered']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_listings.drop(textual_datetime_cols, axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>city_index</th>\n",
       "      <th>last_scraped</th>\n",
       "      <th>house_rules</th>\n",
       "      <th>host_since</th>\n",
       "      <th>host_response_time</th>\n",
       "      <th>host_response_rate</th>\n",
       "      <th>host_is_superhost</th>\n",
       "      <th>host_listings_count</th>\n",
       "      <th>host_total_listings_count</th>\n",
       "      <th>host_verifications</th>\n",
       "      <th>host_has_profile_pic</th>\n",
       "      <th>host_identity_verified</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>is_location_exact</th>\n",
       "      <th>property_type</th>\n",
       "      <th>room_type</th>\n",
       "      <th>accommodates</th>\n",
       "      <th>bathrooms</th>\n",
       "      <th>bedrooms</th>\n",
       "      <th>beds</th>\n",
       "      <th>bed_type</th>\n",
       "      <th>amenities</th>\n",
       "      <th>square_feet</th>\n",
       "      <th>price</th>\n",
       "      <th>weekly_price</th>\n",
       "      <th>monthly_price</th>\n",
       "      <th>security_deposit</th>\n",
       "      <th>cleaning_fee</th>\n",
       "      <th>guests_included</th>\n",
       "      <th>extra_people</th>\n",
       "      <th>minimum_nights</th>\n",
       "      <th>maximum_nights</th>\n",
       "      <th>has_availability</th>\n",
       "      <th>availability_30</th>\n",
       "      <th>availability_60</th>\n",
       "      <th>availability_90</th>\n",
       "      <th>availability_365</th>\n",
       "      <th>number_of_reviews</th>\n",
       "      <th>review_scores_rating</th>\n",
       "      <th>review_scores_accuracy</th>\n",
       "      <th>review_scores_cleanliness</th>\n",
       "      <th>review_scores_checkin</th>\n",
       "      <th>review_scores_communication</th>\n",
       "      <th>review_scores_location</th>\n",
       "      <th>review_scores_value</th>\n",
       "      <th>requires_license</th>\n",
       "      <th>instant_bookable</th>\n",
       "      <th>is_business_travel_ready</th>\n",
       "      <th>cancellation_policy</th>\n",
       "      <th>require_guest_profile_picture</th>\n",
       "      <th>require_guest_phone_verification</th>\n",
       "      <th>calculated_host_listings_count</th>\n",
       "      <th>reviews_per_month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2018-08-16</td>\n",
       "      <td>four day minimum stay</td>\n",
       "      <td>2008-08-26</td>\n",
       "      <td>within an hour</td>\n",
       "      <td>100%</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>['email', 'phone', 'reviews', 'jumio', 'govern...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>47.610819</td>\n",
       "      <td>-122.290816</td>\n",
       "      <td>1</td>\n",
       "      <td>House</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>8</td>\n",
       "      <td>2.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Real Bed</td>\n",
       "      <td>{Internet,Wifi,Kitchen,\"Free parking on premis...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>296.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>500.0</td>\n",
       "      <td>275.0</td>\n",
       "      <td>8</td>\n",
       "      <td>20.0</td>\n",
       "      <td>4</td>\n",
       "      <td>300</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>30</td>\n",
       "      <td>60</td>\n",
       "      <td>329</td>\n",
       "      <td>19</td>\n",
       "      <td>100.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>strict_14_with_grace_period</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2018-08-16</td>\n",
       "      <td>We ask that you please use nearby street parki...</td>\n",
       "      <td>2009-09-02</td>\n",
       "      <td>within an hour</td>\n",
       "      <td>100%</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>['email', 'phone', 'facebook', 'reviews', 'kba']</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>47.687801</td>\n",
       "      <td>-122.313427</td>\n",
       "      <td>1</td>\n",
       "      <td>House</td>\n",
       "      <td>Private room</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Real Bed</td>\n",
       "      <td>{TV,\"Cable TV\",Internet,Wifi,\"Free parking on ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>82.0</td>\n",
       "      <td>525.0</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>60</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>43</td>\n",
       "      <td>73</td>\n",
       "      <td>348</td>\n",
       "      <td>57</td>\n",
       "      <td>91.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>moderate</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0.91</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   city_index last_scraped                                        house_rules  host_since host_response_time host_response_rate  host_is_superhost  host_listings_count  host_total_listings_count                                 host_verifications  host_has_profile_pic  host_identity_verified   latitude   longitude  is_location_exact property_type        room_type  accommodates  bathrooms  bedrooms  beds  bed_type                                          amenities  square_feet  price  weekly_price  monthly_price  security_deposit  cleaning_fee  guests_included  extra_people  minimum_nights  maximum_nights  has_availability  availability_30  availability_60  availability_90  availability_365  number_of_reviews  review_scores_rating  review_scores_accuracy  review_scores_cleanliness  review_scores_checkin  review_scores_communication  review_scores_location  review_scores_value  requires_license  instant_bookable  is_business_travel_ready          cancellation_policy  \\\n",
       "0           1   2018-08-16                              four day minimum stay  2008-08-26     within an hour               100%                0.0                  2.0                        2.0  ['email', 'phone', 'reviews', 'jumio', 'govern...                   1.0                     1.0  47.610819 -122.290816                  1         House  Entire home/apt             8        2.5       4.0   4.0  Real Bed  {Internet,Wifi,Kitchen,\"Free parking on premis...          NaN  296.0           NaN            NaN             500.0         275.0                8          20.0               4             300                 1                3               30               60               329                 19                 100.0                    10.0                       10.0                   10.0                         10.0                    10.0                 10.0                 0                 1                         0  strict_14_with_grace_period   \n",
       "1           1   2018-08-16  We ask that you please use nearby street parki...  2009-09-02     within an hour               100%                0.0                  5.0                        5.0   ['email', 'phone', 'facebook', 'reviews', 'kba']                   1.0                     1.0  47.687801 -122.313427                  1         House     Private room             2        1.0       1.0   1.0  Real Bed  {TV,\"Cable TV\",Internet,Wifi,\"Free parking on ...          NaN   82.0         525.0         1925.0               NaN          30.0                1           0.0               2              60                 1               13               43               73               348                 57                  91.0                     9.0                        9.0                   10.0                          9.0                     9.0                  9.0                 0                 0                         0                     moderate   \n",
       "\n",
       "   require_guest_profile_picture  require_guest_phone_verification  calculated_host_listings_count  reviews_per_month  \n",
       "0                              0                                 0                               2               0.16  \n",
       "1                              0                                 0                               5               0.91  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_listings.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then, we look on individual features for more details.\n",
    "\n",
    "For example, `host_response_time` is ordinal (ordered categorical) feature, it makes sence to transform it to integers:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['within an hour', 'within a few hours', 'within a day',\n",
       "       'a few days or more', nan], dtype=object)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_listings.host_response_time.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "host_response_dict = {'within an hour': 1, \n",
    "                      'within a few hours': 2, \n",
    "                      'within a day': 3,\n",
    "                     'a few days or more': 4}\n",
    "\n",
    "all_listings.host_response_time.replace(host_response_dict, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we are interested to write the difference between features `last_scraped` and `host_since` into a new feature, `host_experience`, and drop the initial features:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['2018-08-16', '2018-08-16'], dtype=object)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_listings.last_scraped.head(2).values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_listings.dropna(axis=0, how='any', subset=['host_since'], inplace=True)\n",
    "all_listings['host_experience'] = all_listings.last_scraped.apply(lambda s: parser.parse(s)) - all_listings.host_since.apply(lambda s: parser.parse(s))\n",
    "all_listings.host_experience = all_listings.host_experience.astype(str).apply(lambda s: int(s.split(' ')[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_listings.drop(['last_scraped', 'host_since'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>city_index</th>\n",
       "      <th>house_rules</th>\n",
       "      <th>host_response_time</th>\n",
       "      <th>host_response_rate</th>\n",
       "      <th>host_is_superhost</th>\n",
       "      <th>host_listings_count</th>\n",
       "      <th>host_total_listings_count</th>\n",
       "      <th>host_verifications</th>\n",
       "      <th>host_has_profile_pic</th>\n",
       "      <th>host_identity_verified</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>is_location_exact</th>\n",
       "      <th>property_type</th>\n",
       "      <th>room_type</th>\n",
       "      <th>accommodates</th>\n",
       "      <th>bathrooms</th>\n",
       "      <th>bedrooms</th>\n",
       "      <th>beds</th>\n",
       "      <th>bed_type</th>\n",
       "      <th>amenities</th>\n",
       "      <th>square_feet</th>\n",
       "      <th>price</th>\n",
       "      <th>weekly_price</th>\n",
       "      <th>monthly_price</th>\n",
       "      <th>security_deposit</th>\n",
       "      <th>cleaning_fee</th>\n",
       "      <th>guests_included</th>\n",
       "      <th>extra_people</th>\n",
       "      <th>minimum_nights</th>\n",
       "      <th>maximum_nights</th>\n",
       "      <th>has_availability</th>\n",
       "      <th>availability_30</th>\n",
       "      <th>availability_60</th>\n",
       "      <th>availability_90</th>\n",
       "      <th>availability_365</th>\n",
       "      <th>number_of_reviews</th>\n",
       "      <th>review_scores_rating</th>\n",
       "      <th>review_scores_accuracy</th>\n",
       "      <th>review_scores_cleanliness</th>\n",
       "      <th>review_scores_checkin</th>\n",
       "      <th>review_scores_communication</th>\n",
       "      <th>review_scores_location</th>\n",
       "      <th>review_scores_value</th>\n",
       "      <th>requires_license</th>\n",
       "      <th>instant_bookable</th>\n",
       "      <th>is_business_travel_ready</th>\n",
       "      <th>cancellation_policy</th>\n",
       "      <th>require_guest_profile_picture</th>\n",
       "      <th>require_guest_phone_verification</th>\n",
       "      <th>calculated_host_listings_count</th>\n",
       "      <th>reviews_per_month</th>\n",
       "      <th>host_experience</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>four day minimum stay</td>\n",
       "      <td>1.0</td>\n",
       "      <td>100%</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>['email', 'phone', 'reviews', 'jumio', 'govern...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>47.610819</td>\n",
       "      <td>-122.290816</td>\n",
       "      <td>1</td>\n",
       "      <td>House</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>8</td>\n",
       "      <td>2.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Real Bed</td>\n",
       "      <td>{Internet,Wifi,Kitchen,\"Free parking on premis...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>296.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>500.0</td>\n",
       "      <td>275.0</td>\n",
       "      <td>8</td>\n",
       "      <td>20.0</td>\n",
       "      <td>4</td>\n",
       "      <td>300</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>30</td>\n",
       "      <td>60</td>\n",
       "      <td>329</td>\n",
       "      <td>19</td>\n",
       "      <td>100.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>strict_14_with_grace_period</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.16</td>\n",
       "      <td>3642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>We ask that you please use nearby street parki...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>100%</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>['email', 'phone', 'facebook', 'reviews', 'kba']</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>47.687801</td>\n",
       "      <td>-122.313427</td>\n",
       "      <td>1</td>\n",
       "      <td>House</td>\n",
       "      <td>Private room</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Real Bed</td>\n",
       "      <td>{TV,\"Cable TV\",Internet,Wifi,\"Free parking on ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>82.0</td>\n",
       "      <td>525.0</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>60</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>43</td>\n",
       "      <td>73</td>\n",
       "      <td>348</td>\n",
       "      <td>57</td>\n",
       "      <td>91.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>moderate</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0.91</td>\n",
       "      <td>3270</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   city_index                                        house_rules  host_response_time host_response_rate  host_is_superhost  host_listings_count  host_total_listings_count                                 host_verifications  host_has_profile_pic  host_identity_verified   latitude   longitude  is_location_exact property_type        room_type  accommodates  bathrooms  bedrooms  beds  bed_type                                          amenities  square_feet  price  weekly_price  monthly_price  security_deposit  cleaning_fee  guests_included  extra_people  minimum_nights  maximum_nights  has_availability  availability_30  availability_60  availability_90  availability_365  number_of_reviews  review_scores_rating  review_scores_accuracy  review_scores_cleanliness  review_scores_checkin  review_scores_communication  review_scores_location  review_scores_value  requires_license  instant_bookable  is_business_travel_ready          cancellation_policy  require_guest_profile_picture  \\\n",
       "0           1                              four day minimum stay                 1.0               100%                0.0                  2.0                        2.0  ['email', 'phone', 'reviews', 'jumio', 'govern...                   1.0                     1.0  47.610819 -122.290816                  1         House  Entire home/apt             8        2.5       4.0   4.0  Real Bed  {Internet,Wifi,Kitchen,\"Free parking on premis...          NaN  296.0           NaN            NaN             500.0         275.0                8          20.0               4             300                 1                3               30               60               329                 19                 100.0                    10.0                       10.0                   10.0                         10.0                    10.0                 10.0                 0                 1                         0  strict_14_with_grace_period                              0   \n",
       "1           1  We ask that you please use nearby street parki...                 1.0               100%                0.0                  5.0                        5.0   ['email', 'phone', 'facebook', 'reviews', 'kba']                   1.0                     1.0  47.687801 -122.313427                  1         House     Private room             2        1.0       1.0   1.0  Real Bed  {TV,\"Cable TV\",Internet,Wifi,\"Free parking on ...          NaN   82.0         525.0         1925.0               NaN          30.0                1           0.0               2              60                 1               13               43               73               348                 57                  91.0                     9.0                        9.0                   10.0                          9.0                     9.0                  9.0                 0                 0                         0                     moderate                              0   \n",
       "\n",
       "   require_guest_phone_verification  calculated_host_listings_count  reviews_per_month  host_experience  \n",
       "0                                 0                               2               0.16             3642  \n",
       "1                                 0                               5               0.91             3270  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_listings.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then, we extract some meaningful information from `house_rules`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                                 four day minimum stay\n",
       "1     We ask that you please use nearby street parki...\n",
       "2     **PLEASE READ** NO SMOKING NO VAPING NO MARIJU...\n",
       "3     Please treat the cottage as if it were your ow...\n",
       "4     No drugs,no smoking inside *outside in front o...\n",
       "5     Dear Prospective Guest,   There aren’t really ...\n",
       "6     *The Sweet Orange is a No Smoking house.  The ...\n",
       "7     *The Tangerine Dream is a Non-Smoking house an...\n",
       "8     Please treat the apartment as if it were your ...\n",
       "9     You agree to the following terms and condition...\n",
       "10    Clean up after yourself in the Kitchen and Bat...\n",
       "11    We ask that you please use nearby street parki...\n",
       "12    We ask that you use adjacent street parking, b...\n",
       "13    no smoking.recycle, do unto others.. treat thi...\n",
       "14    We ask that you use nearby street parking, but...\n",
       "15    Consideration for others is the name of the ga...\n",
       "16    Consideration for others is the name of the ga...\n",
       "17    While staying with us, we welcome you to spend...\n",
       "18    Be a clean, respectfull house mates,  we are a...\n",
       "19    You agree to the following terms and condition...\n",
       "20    -Due to insurance reasons, the responsible par...\n",
       "21    - Due to insurance requirements, renter must b...\n",
       "22    - Due to insurance requirements, renter must b...\n",
       "23                                                  NaN\n",
       "24    The cottage only accomodates 2 people - there ...\n",
       "25    The Alchemist Den only accommodates 2 people -...\n",
       "26    - House Rules -   Please review our conditions...\n",
       "27    - Due to insurance requirements, renter must b...\n",
       "28    - Due to insurance requirements, renter must b...\n",
       "29    1. I'm happy to accommodate one night stays, b...\n",
       "30    OCCUPANCY The person making the reservation mu...\n",
       "31                                                  NaN\n",
       "32    Very quiet neighborhood, so please come and go...\n",
       "33    no smoking, no pets, no gatherings or events. ...\n",
       "34    CHECK IN /CHECK OUT TIMES: check is from (PHON...\n",
       "35    We are a 'scent free' house. Please do not use...\n",
       "36    This a quiet peaceful house with friendly crea...\n",
       "37                                                  NaN\n",
       "38    - Check-in is after 3 PM - 420 friendly - No i...\n",
       "39    This a quiet peaceful house with creative peop...\n",
       "40    We both work during the week, so please  be co...\n",
       "41    - Due to insurance requirements, renter must b...\n",
       "42    - Due to insurance requirements, renter must b...\n",
       "43    PLEASE NO SMOKING! Even if you smoke outside, ...\n",
       "44    This a quiet peaceful house with friendly crea...\n",
       "45    We keep our common spaces pleasant and ready f...\n",
       "46    No smoking in or outside on our property. No p...\n",
       "47                                                  NaN\n",
       "48    Please no smoking in the unit or near the buil...\n",
       "49    No noise after 10 pm (neighbors prefer this). ...\n",
       "Name: house_rules, dtype: object"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_listings.house_rules.head(50)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For example, no smoking and no pets are often requied, so it is good to contain special features for such apartments:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "def no_smoking(house_rules_txt):\n",
    "    '''\n",
    "    Checks whether smoking is prohibited by the house rules\n",
    "    \n",
    "    Args:\n",
    "        house_rules_txt (string): house rules as specified by the host\n",
    "    \n",
    "    Returns:\n",
    "        is_no_smoking (int): 1 if smoking is prohibited else 0\n",
    "    '''\n",
    "    \n",
    "    is_no_smoking = int('no smoking' in str(house_rules_txt).lower() or 'smoking is not allowed' in str(house_rules_txt).lower())  \n",
    "\n",
    "    return is_no_smoking"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "def no_pets(house_rules_txt):\n",
    "    '''\n",
    "    Checks whether pets are prohibited by the house rules\n",
    "    \n",
    "    Args:\n",
    "        house_rules_txt (string): house rules as specified by the host\n",
    "    \n",
    "    Returns:\n",
    "        is_no_pets (int): 1 if pets are prohibited else 0\n",
    "    ''' \n",
    "    \n",
    "    is_no_pets = int('no pets' in str(house_rules_txt).lower() or 'no smoking or pets' in str(house_rules_txt).lower())\n",
    "    \n",
    "    return is_no_pets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_listings['house_rules_no_smoking'] = all_listings.house_rules.apply(no_smoking)\n",
    "all_listings['house_rules_no_pets'] = all_listings.house_rules.apply(no_pets)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_listings.drop(['house_rules'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us look on `host_verifications` column:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([\"['email', 'phone', 'reviews', 'jumio', 'government_id']\",\n",
       "       \"['email', 'phone', 'facebook', 'reviews', 'kba']\",\n",
       "       \"['email', 'phone', 'manual_online', 'reviews', 'manual_offline', 'jumio', 'offline_government_id', 'kba', 'selfie', 'government_id', 'identity_manual']\",\n",
       "       \"['email', 'phone', 'facebook', 'reviews', 'kba']\",\n",
       "       \"['email', 'phone', 'reviews', 'jumio', 'government_id']\",\n",
       "       \"['email', 'phone', 'reviews', 'kba', 'work_email']\",\n",
       "       \"['email', 'phone', 'reviews', 'kba']\",\n",
       "       \"['email', 'phone', 'reviews', 'kba']\",\n",
       "       \"['email', 'phone', 'facebook', 'reviews', 'kba']\",\n",
       "       \"['email', 'phone', 'reviews', 'jumio', 'offline_government_id', 'selfie', 'government_id', 'identity_manual']\"],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_listings.host_verifications.head(10).values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It makes sense to count the number of different verifications and to create a new feature, `host_verification_level`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_listings['host_verification_level'] = all_listings.host_verifications.apply(lambda s: len(s.split(', ')))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    40723.000000\n",
       "mean         4.955553\n",
       "std          1.986457\n",
       "min          1.000000\n",
       "25%          3.000000\n",
       "50%          5.000000\n",
       "75%          6.000000\n",
       "max         13.000000\n",
       "Name: host_verification_level, dtype: float64"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_listings.host_verification_level.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_listings.drop(['host_verifications'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then, we simply drop the columns `property_type`, `bed_type` and `cancellation_policy`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['House', 'Guest suite', 'Apartment', 'Condominium', 'Guesthouse',\n",
       "       'Cabin', 'Townhouse', 'Bungalow', 'Loft', 'Cottage',\n",
       "       'Bed and breakfast', 'Boat', 'Serviced apartment', 'Castle',\n",
       "       'Houseboat', 'Hostel', 'Camper/RV', 'Tent', 'Other', 'Tiny house',\n",
       "       'Treehouse', 'Yurt', 'Aparthotel', 'Chalet', 'Villa', 'Lighthouse',\n",
       "       'Earth house', 'Boutique hotel', 'Hut', 'Resort', 'Bus',\n",
       "       'Nature lodge', 'In-law', 'Casa particular (Cuba)', 'Hotel',\n",
       "       'Island', 'Casa particular', 'Dammuso (Italy)'], dtype=object)"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_listings.property_type.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Real Bed', 'Futon', 'Pull-out Sofa', 'Airbed', 'Couch'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_listings.bed_type.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['strict_14_with_grace_period', 'moderate', 'flexible',\n",
       "       'super_strict_60', 'strict', 'super_strict_30'], dtype=object)"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_listings.cancellation_policy.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_listings.drop(['property_type', 'bed_type', 'cancellation_policy'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Column `host_response_rate` can be easily converted to numerical `host_response_fraction`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['100%', '94%', '99%', '80%', '20%', nan, '70%', '86%', '90%',\n",
       "       '92%', '96%', '95%', '67%', '75%', '88%', '60%', '50%', '72%',\n",
       "       '98%', '56%', '97%', '89%', '83%', '43%', '0%', '91%', '93%',\n",
       "       '82%', '58%', '77%', '40%', '33%', '38%', '25%', '84%', '57%',\n",
       "       '62%', '81%', '78%', '73%', '63%', '29%', '76%', '46%', '71%',\n",
       "       '35%', '6%', '30%', '69%', '65%', '74%', '87%', '68%', '85%',\n",
       "       '47%', '44%', '64%', '10%', '79%', '42%', '53%', '14%', '17%',\n",
       "       '28%', '55%', '61%', '54%', '22%', '13%', '27%', '9%', '31%', '8%',\n",
       "       '7%', '19%'], dtype=object)"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_listings.host_response_rate.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "def rate_to_fraction(rate_str):\n",
    "    '''\n",
    "    Converts rates in '%' into float fractions\n",
    "    \n",
    "    Args:\n",
    "        rate_str (str): percentage rate (e.g., '94%')\n",
    "    \n",
    "    Returns:\n",
    "        rate_frac (float): percentage fraction (e.g., 0.94)\n",
    "    \n",
    "    '''\n",
    "    if rate_str == 0:\n",
    "        rate_frac = None\n",
    "    else:\n",
    "        rate_frac = 0.01*int(str(rate_str).split('%')[0])\n",
    "\n",
    "        return rate_frac"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_listings['host_response_fraction'] = all_listings.host_response_rate.fillna(0).apply(rate_to_fraction)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_listings.drop(['host_response_rate'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Feature `room_type` can be also written as ordinal:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Entire home/apt', 'Private room', 'Shared room'], dtype=object)"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_listings.room_type.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "room_type_dict = {'Shared room': 1, 'Private room': 2, 'Entire home/apt': 3}\n",
    "all_listings.room_type.replace(room_type_dict, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, look on categorical feature `amenities`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['{Internet,Wifi,Kitchen,\"Free parking on premises\",\"Pets allowed\",\"Indoor fireplace\",Heating,\"Family/kid friendly\",Washer,Dryer,\"Smoke detector\",\"Carbon monoxide detector\",\"First aid kit\",\"Fire extinguisher\",Essentials,Shampoo,Hangers,\"Hair dryer\",Iron,\"Laptop friendly workspace\"}',\n",
       "       '{TV,\"Cable TV\",Internet,Wifi,\"Free parking on premises\",Heating,Washer,Dryer,\"Smoke detector\",\"Fire extinguisher\",Essentials,Shampoo}',\n",
       "       '{TV,Internet,Wifi,\"Free street parking\",Heating,\"Family/kid friendly\",\"Smoke detector\",\"Carbon monoxide detector\",\"First aid kit\",Essentials,Shampoo,\"24-hour check-in\",Hangers,\"Hair dryer\",Iron,\"translation missing: en.hosting_amenity_49\",\"Self check-in\",Lockbox,\"Private entrance\",\"Hot water\",Microwave,\"Coffee maker\",Refrigerator,\"Single level home\",\"Flat path to front door\"}',\n",
       "       '{TV,\"Cable TV\",Internet,Wifi,Kitchen,\"Free parking on premises\",Heating,\"Smoke detector\",\"Carbon monoxide detector\",\"Fire extinguisher\",Essentials,Shampoo,\"24-hour check-in\",Hangers,\"Hair dryer\",Iron,\"Laptop friendly workspace\",\"translation missing: en.hosting_amenity_50\"}',\n",
       "       '{Internet,Wifi,\"Air conditioning\",Kitchen,\"Free parking on premises\",\"Pets live on this property\",Dog(s),\"Free street parking\",Heating,Washer,Dryer,\"Smoke detector\",\"First aid kit\",\"Safety card\",\"Fire extinguisher\",Essentials,Shampoo,\"Lock on bedroom door\",Hangers,\"Hair dryer\",Iron,\"Laptop friendly workspace\",\"Private living room\",\"Hot water\",\"Bed linens\",\"Extra pillows and blankets\",Microwave,\"Coffee maker\",Refrigerator,\"Dishes and silverware\",\"Cooking basics\",Oven,Stove,\"Host greets you\"}'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_listings.amenities.head().values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, we create three new features, `is_TV`, `is_Wifi` and the number of different amenities `amenities_number`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_listings['is_TV'] = all_listings.amenities.apply(lambda s: int('TV' in str(s)[1:].split(',')))\n",
    "all_listings['is_Wifi'] = all_listings.amenities.apply(lambda s: int('Wifi' in str(s)[1:].split(',')))\n",
    "all_listings['amenities_number'] = all_listings.amenities.apply(lambda s: len(str(s)[1:].split(',')))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_listings.drop('amenities', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Treatment of missing variables:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we see, `all_listings` contain 18 columns with missing values:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "square_feet                    39877\n",
       "monthly_price                  37124\n",
       "weekly_price                   34372\n",
       "security_deposit               18013\n",
       "host_response_time             13492\n",
       "host_response_fraction         13492\n",
       "cleaning_fee                   10732\n",
       "review_scores_value             7155\n",
       "review_scores_location          7149\n",
       "review_scores_checkin           7147\n",
       "review_scores_accuracy          7113\n",
       "review_scores_communication     7113\n",
       "review_scores_cleanliness       7105\n",
       "review_scores_rating            7075\n",
       "reviews_per_month               6496\n",
       "bathrooms                         28\n",
       "beds                              22\n",
       "bedrooms                          13\n",
       "guests_included                    0\n",
       "accommodates                       0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_listings.isnull().sum().sort_values(ascending=False).head(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Because columns `bathrooms`, `beds` and `bedrooms` contain very small number of NaNs, we just dropped the corresponding instances:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_listings.dropna(axis=0, how='any', subset=['bathrooms', 'beds', 'bedrooms'], inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we fully drop the columns `square_feet`, `monthly_price` and `weekly_price`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_listings.drop(axis=1, columns=['square_feet', 'monthly_price', 'weekly_price'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(40670, 50)"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_listings.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we drop the duplicate columns `host_total_listings_count` and `is_business_travel_ready`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_listings_1 = all_listings.T.drop_duplicates().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(40670, 48)"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_listings_1.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "duplicate_cols = [i for i in all_listings.columns if i not in all_listings_1.columns]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "del all_listings_1\n",
    "all_listings.drop(duplicate_cols, axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>city_index</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>2.434423</td>\n",
       "      <td>0.814264</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.00000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>host_response_time</th>\n",
       "      <td>27206.0</td>\n",
       "      <td>1.582261</td>\n",
       "      <td>0.835823</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>4.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>host_is_superhost</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>0.175731</td>\n",
       "      <td>0.380596</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>host_listings_count</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>33.319892</td>\n",
       "      <td>160.153333</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.320000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>host_has_profile_pic</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>0.998107</td>\n",
       "      <td>0.043471</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>host_identity_verified</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>0.450430</td>\n",
       "      <td>0.497543</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>latitude</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>52.022549</td>\n",
       "      <td>5.151997</td>\n",
       "      <td>42.235760</td>\n",
       "      <td>47.62099</td>\n",
       "      <td>55.665870</td>\n",
       "      <td>55.688551</td>\n",
       "      <td>5.573220e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>longitude</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>-27.989411</td>\n",
       "      <td>56.479304</td>\n",
       "      <td>-122.419637</td>\n",
       "      <td>-71.10250</td>\n",
       "      <td>12.537862</td>\n",
       "      <td>12.563865</td>\n",
       "      <td>1.263980e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>is_location_exact</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>0.768183</td>\n",
       "      <td>0.421998</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>room_type</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>2.777723</td>\n",
       "      <td>0.435142</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.00000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>accommodates</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>3.395820</td>\n",
       "      <td>1.859799</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.00000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>2.800000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bathrooms</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>1.147787</td>\n",
       "      <td>0.433425</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bedrooms</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>1.489771</td>\n",
       "      <td>0.909963</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beds</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>2.065429</td>\n",
       "      <td>1.465168</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.000000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>price</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>575.025744</td>\n",
       "      <td>1057.792454</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>179.00000</td>\n",
       "      <td>498.000000</td>\n",
       "      <td>802.000000</td>\n",
       "      <td>6.712900e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>security_deposit</th>\n",
       "      <td>22693.0</td>\n",
       "      <td>852.481073</td>\n",
       "      <td>2235.466536</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>200.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "      <td>3.522700e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cleaning_fee</th>\n",
       "      <td>29965.0</td>\n",
       "      <td>202.582146</td>\n",
       "      <td>206.374094</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>55.00000</td>\n",
       "      <td>145.000000</td>\n",
       "      <td>300.000000</td>\n",
       "      <td>3.000000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>guests_included</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>1.622621</td>\n",
       "      <td>1.242885</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.600000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>extra_people</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>44.504696</td>\n",
       "      <td>96.448073</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>2.000000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>minimum_nights</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>3.628473</td>\n",
       "      <td>13.210481</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>maximum_nights</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>3112.312097</td>\n",
       "      <td>495861.931538</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>21.00000</td>\n",
       "      <td>1125.000000</td>\n",
       "      <td>1125.000000</td>\n",
       "      <td>1.000000e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>has_availability</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>availability_30</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>4.256036</td>\n",
       "      <td>7.411396</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>3.000000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>availability_60</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>11.496779</td>\n",
       "      <td>17.217815</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>6.000000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>availability_90</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>20.391984</td>\n",
       "      <td>28.364379</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>9.000000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>availability_365</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>84.421244</td>\n",
       "      <td>118.613231</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>143.000000</td>\n",
       "      <td>3.650000e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>number_of_reviews</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>20.738062</td>\n",
       "      <td>40.327376</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.00000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>7.050000e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_scores_rating</th>\n",
       "      <td>33610.0</td>\n",
       "      <td>94.791788</td>\n",
       "      <td>6.882770</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>93.00000</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1.000000e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_scores_accuracy</th>\n",
       "      <td>33572.0</td>\n",
       "      <td>9.692512</td>\n",
       "      <td>0.688739</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>10.00000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>1.000000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_scores_cleanliness</th>\n",
       "      <td>33580.0</td>\n",
       "      <td>9.454169</td>\n",
       "      <td>0.905073</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>9.00000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>1.000000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_scores_checkin</th>\n",
       "      <td>33538.0</td>\n",
       "      <td>9.810126</td>\n",
       "      <td>0.580386</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>10.00000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>1.000000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_scores_communication</th>\n",
       "      <td>33572.0</td>\n",
       "      <td>9.821637</td>\n",
       "      <td>0.565981</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>10.00000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>1.000000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_scores_location</th>\n",
       "      <td>33536.0</td>\n",
       "      <td>9.553614</td>\n",
       "      <td>0.704193</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>9.00000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>1.000000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_scores_value</th>\n",
       "      <td>33530.0</td>\n",
       "      <td>9.448762</td>\n",
       "      <td>0.765009</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>9.00000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>1.000000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>requires_license</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>instant_bookable</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>0.329727</td>\n",
       "      <td>0.470120</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>require_guest_profile_picture</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>0.018589</td>\n",
       "      <td>0.135069</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>require_guest_phone_verification</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>0.024932</td>\n",
       "      <td>0.155921</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>calculated_host_listings_count</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>11.982198</td>\n",
       "      <td>46.553947</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.020000e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>reviews_per_month</th>\n",
       "      <td>34189.0</td>\n",
       "      <td>1.429338</td>\n",
       "      <td>1.822495</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>0.26000</td>\n",
       "      <td>0.710000</td>\n",
       "      <td>1.860000</td>\n",
       "      <td>1.700000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>host_experience</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>1306.194025</td>\n",
       "      <td>655.570144</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>829.00000</td>\n",
       "      <td>1261.000000</td>\n",
       "      <td>1762.000000</td>\n",
       "      <td>3.818000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>house_rules_no_smoking</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>0.169634</td>\n",
       "      <td>0.375315</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>house_rules_no_pets</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>0.074158</td>\n",
       "      <td>0.262031</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>host_verification_level</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>4.955815</td>\n",
       "      <td>1.986440</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.00000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1.300000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>host_response_fraction</th>\n",
       "      <td>27206.0</td>\n",
       "      <td>0.952648</td>\n",
       "      <td>0.140979</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.99000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>is_TV</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>0.713523</td>\n",
       "      <td>0.452120</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>is_Wifi</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>0.965282</td>\n",
       "      <td>0.183068</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>amenities_number</th>\n",
       "      <td>40670.0</td>\n",
       "      <td>19.774723</td>\n",
       "      <td>9.878517</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>12.00000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>7.500000e+01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    count         mean            std         min        25%          50%          75%           max\n",
       "city_index                        40670.0     2.434423       0.814264    1.000000    2.00000     3.000000     3.000000  3.000000e+00\n",
       "host_response_time                27206.0     1.582261       0.835823    1.000000    1.00000     1.000000     2.000000  4.000000e+00\n",
       "host_is_superhost                 40670.0     0.175731       0.380596    0.000000    0.00000     0.000000     0.000000  1.000000e+00\n",
       "host_listings_count               40670.0    33.319892     160.153333    0.000000    1.00000     1.000000     2.000000  1.320000e+03\n",
       "host_has_profile_pic              40670.0     0.998107       0.043471    0.000000    1.00000     1.000000     1.000000  1.000000e+00\n",
       "host_identity_verified            40670.0     0.450430       0.497543    0.000000    0.00000     0.000000     1.000000  1.000000e+00\n",
       "latitude                          40670.0    52.022549       5.151997   42.235760   47.62099    55.665870    55.688551  5.573220e+01\n",
       "longitude                         40670.0   -27.989411      56.479304 -122.419637  -71.10250    12.537862    12.563865  1.263980e+01\n",
       "is_location_exact                 40670.0     0.768183       0.421998    0.000000    1.00000     1.000000     1.000000  1.000000e+00\n",
       "room_type                         40670.0     2.777723       0.435142    1.000000    3.00000     3.000000     3.000000  3.000000e+00\n",
       "accommodates                      40670.0     3.395820       1.859799    1.000000    2.00000     3.000000     4.000000  2.800000e+01\n",
       "bathrooms                         40670.0     1.147787       0.433425    0.000000    1.00000     1.000000     1.000000  1.000000e+01\n",
       "bedrooms                          40670.0     1.489771       0.909963    0.000000    1.00000     1.000000     2.000000  1.000000e+01\n",
       "beds                              40670.0     2.065429       1.465168    0.000000    1.00000     2.000000     3.000000  2.000000e+01\n",
       "price                             40670.0   575.025744    1057.792454    0.000000  179.00000   498.000000   802.000000  6.712900e+04\n",
       "security_deposit                  22693.0   852.481073    2235.466536    0.000000    0.00000   200.000000  1000.000000  3.522700e+04\n",
       "cleaning_fee                      29965.0   202.582146     206.374094    0.000000   55.00000   145.000000   300.000000  3.000000e+03\n",
       "guests_included                   40670.0     1.622621       1.242885    1.000000    1.00000     1.000000     2.000000  1.600000e+01\n",
       "extra_people                      40670.0    44.504696      96.448073    0.000000    0.00000     0.000000    35.000000  2.000000e+03\n",
       "minimum_nights                    40670.0     3.628473      13.210481    1.000000    1.00000     2.000000     3.000000  1.000000e+03\n",
       "maximum_nights                    40670.0  3112.312097  495861.931538    1.000000   21.00000  1125.000000  1125.000000  1.000000e+08\n",
       "has_availability                  40670.0     1.000000       0.000000    1.000000    1.00000     1.000000     1.000000  1.000000e+00\n",
       "availability_30                   40670.0     4.256036       7.411396    0.000000    0.00000     0.000000     6.000000  3.000000e+01\n",
       "availability_60                   40670.0    11.496779      17.217815    0.000000    0.00000     0.000000    20.000000  6.000000e+01\n",
       "availability_90                   40670.0    20.391984      28.364379    0.000000    0.00000     1.000000    41.000000  9.000000e+01\n",
       "availability_365                  40670.0    84.421244     118.613231    0.000000    0.00000    10.000000   143.000000  3.650000e+02\n",
       "number_of_reviews                 40670.0    20.738062      40.327376    0.000000    2.00000     6.000000    21.000000  7.050000e+02\n",
       "review_scores_rating              33610.0    94.791788       6.882770   20.000000   93.00000    97.000000   100.000000  1.000000e+02\n",
       "review_scores_accuracy            33572.0     9.692512       0.688739    2.000000   10.00000    10.000000    10.000000  1.000000e+01\n",
       "review_scores_cleanliness         33580.0     9.454169       0.905073    2.000000    9.00000    10.000000    10.000000  1.000000e+01\n",
       "review_scores_checkin             33538.0     9.810126       0.580386    2.000000   10.00000    10.000000    10.000000  1.000000e+01\n",
       "review_scores_communication       33572.0     9.821637       0.565981    2.000000   10.00000    10.000000    10.000000  1.000000e+01\n",
       "review_scores_location            33536.0     9.553614       0.704193    2.000000    9.00000    10.000000    10.000000  1.000000e+01\n",
       "review_scores_value               33530.0     9.448762       0.765009    2.000000    9.00000    10.000000    10.000000  1.000000e+01\n",
       "requires_license                  40670.0     0.000000       0.000000    0.000000    0.00000     0.000000     0.000000  0.000000e+00\n",
       "instant_bookable                  40670.0     0.329727       0.470120    0.000000    0.00000     0.000000     1.000000  1.000000e+00\n",
       "require_guest_profile_picture     40670.0     0.018589       0.135069    0.000000    0.00000     0.000000     0.000000  1.000000e+00\n",
       "require_guest_phone_verification  40670.0     0.024932       0.155921    0.000000    0.00000     0.000000     0.000000  1.000000e+00\n",
       "calculated_host_listings_count    40670.0    11.982198      46.553947    1.000000    1.00000     1.000000     2.000000  3.020000e+02\n",
       "reviews_per_month                 34189.0     1.429338       1.822495    0.010000    0.26000     0.710000     1.860000  1.700000e+01\n",
       "host_experience                   40670.0  1306.194025     655.570144    1.000000  829.00000  1261.000000  1762.000000  3.818000e+03\n",
       "house_rules_no_smoking            40670.0     0.169634       0.375315    0.000000    0.00000     0.000000     0.000000  1.000000e+00\n",
       "house_rules_no_pets               40670.0     0.074158       0.262031    0.000000    0.00000     0.000000     0.000000  1.000000e+00\n",
       "host_verification_level           40670.0     4.955815       1.986440    1.000000    3.00000     5.000000     6.000000  1.300000e+01\n",
       "host_response_fraction            27206.0     0.952648       0.140979    0.000000    0.99000     1.000000     1.000000  1.000000e+00\n",
       "is_TV                             40670.0     0.713523       0.452120    0.000000    0.00000     1.000000     1.000000  1.000000e+00\n",
       "is_Wifi                           40670.0     0.965282       0.183068    0.000000    1.00000     1.000000     1.000000  1.000000e+00\n",
       "amenities_number                  40670.0    19.774723       9.878517    1.000000   12.00000    17.000000    25.000000  7.500000e+01"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_description = all_listings.describe().T\n",
    "all_description"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we see, feature `requires_license` can be dropped. Also, there are several columns with high-end outliers, such as `maximum_nights`, `minimum_nights` and `price`. Let us drop them automatically with the help of the [interquartile range rule](https://www.thoughtco.com/what-is-the-interquartile-range-rule-3126244):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "maximum_nights\n",
      "minimum_nights\n",
      "price\n"
     ]
    }
   ],
   "source": [
    "all_description['iqr_max'] = all_description['75%'] + 1.5 * (all_description['75%'] - all_description['25%'])\n",
    "all_description['iqr_min'] = all_description['75%'] - 1.5 * (all_description['75%'] - all_description['25%'])\n",
    "\n",
    "cols_to_drop_outliers = ['maximum_nights', 'minimum_nights', 'price']\n",
    "\n",
    "for col in cols_to_drop_outliers:\n",
    "    print(col)\n",
    "    all_listings = all_listings[((all_listings[col] > all_description.loc[col, 'iqr_min']) & (all_listings[col] < all_description.loc[col, 'iqr_max']))]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we want to add geographical distance from cities to city centers (I take coordinates from [here](http:https://dateandtime.info/citycoordinates.php))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "lat_center_dict = {1: 47.6062100, 2: 42.3584300, 3: 55.675940}\n",
    "lon_center_dict = {1: -122.3320700, 2: -71.0597700, 3: 12.5655300}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_listings['lat_center'] = all_listings.city_index.replace(lat_center_dict)\n",
    "all_listings['lon_center'] = all_listings.city_index.replace(lon_center_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 3.02 s, sys: 6.02 ms, total: 3.03 s\n",
      "Wall time: 3.04 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "# calculates Vincenty distance from the city center using https://en.wikipedia.org/wiki/Vincenty%27s_formulae \n",
    "all_listings['distance_center'] = all_listings.apply(lambda x: vincenty((x['latitude'], x['longitude']), (x['lat_center'], x['lon_center'])).km, axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    36591.000000\n",
       "mean         3.382258\n",
       "std          2.383834\n",
       "min          0.049584\n",
       "25%          1.671923\n",
       "50%          2.825540\n",
       "75%          4.204325\n",
       "max         14.742323\n",
       "Name: distance_center, dtype: float64"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_listings['distance_center'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(36591, 51)"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_listings.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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8syUdi3ZwGmE0xP4K4ZxzzjnnOjzvTBTXprkS+cF2eSMThwCfiki/JurZiLCb0jPA1oRp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J6AclClHe5G51WEdmAoAvuOpuSUcwfJ1LSM1A/mhjrmleyfhS9jYzsQOMf7MF7LV8ABZkd0EF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\nWExIkiRJGsuvAT6rNIXcQONPAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 864x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,8))\n",
    "sns.heatmap(all_listings.corr());\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# (**Q1**) what are the positive and negative reviews?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The field of our interest is `comments` that contains the textual comments. To trasform it into review sentiments (to answer **Q1**), I will use the publicly available pre-trained [Vader sentiment model based on NLTK](http:https://www.nltk.org/_modules/nltk/sentiment/vader.html) ([here](http:https://www.nltk.org/howto/sentiment.html) is the detailed usage example):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.8112, -0.4767)"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_sentence_1 = 'Room was nice. Room was not awful at all. I really liked it.'\n",
    "test_sentence_2 = 'I detest this room. It was terrible. I will not stay there any longer.'\n",
    "\n",
    "# calculates compound sentiment polarity of the sentence\n",
    "vader_polarity_compound = lambda s: (SentimentIntensityAnalyzer().polarity_scores(s))['compound']\n",
    "\n",
    "vader_polarity_compound(test_sentence_1), vader_polarity_compound(test_sentence_2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As expected, the sentiment score 1 is quite high and sentiment score 2 is rather low (note that positive reviews are scored up to +1 and negative reviews are scores down to -1).\n",
    "\n",
    "We also see that there are some null comments in these datasets:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(360, 198, 302)"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "seattle_reviews.comments.isnull().sum(), \\\n",
    "boston_reviews.comments.isnull().sum(), \\\n",
    "copenhagen_reviews.comments.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Becase it is unclear what the null comment should be, it is natural to drop these rows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 0, 0)"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "seattle_reviews.dropna(subset=['comments'], how='any', axis=0, inplace=True)\n",
    "boston_reviews.dropna(subset=['comments'], how='any', axis=0, inplace=True)\n",
    "copenhagen_reviews.dropna(subset=['comments'], how='any', axis=0, inplace=True)\n",
    "\n",
    "seattle_reviews.comments.isnull().sum(), \\\n",
    "boston_reviews.comments.isnull().sum(), \\\n",
    "copenhagen_reviews.comments.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Final sentiment polarity calculation for 845k entries takes about 2 hours. To briefly reproduce the result, I saved the updated dataframes in [hdf5](https://support.hdfgroup.org/HDF5/) format:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-rw-r--r-- 1 dima806 dima806  58M Sep 25 16:33 boston_reviews.h5\n",
      "-rw-r--r-- 1 dima806 dima806 109M Sep 25 17:57 copenhagen_reviews.h5\n",
      "-rw-r--r-- 1 dima806 dima806 114M Sep 25 17:16 seattle_reviews.h5\n"
     ]
    }
   ],
   "source": [
    "# %%time\n",
    "\n",
    "# seattle_reviews['polarity'] = seattle_reviews.comments.map(vader_polarity_compound)\n",
    "# seattle_reviews.to_hdf('seattle_reviews.h5', key='seattle_reviews', mode='w')\n",
    "\n",
    "# boston_reviews['polarity'] = boston_reviews.comments.map(vader_polarity_compound)\n",
    "# boston_reviews.to_hdf('boston_reviews.h5', key='boston_reviews', mode='w')\n",
    "\n",
    "# copenhagen_reviews['polarity'] = copenhagen_reviews.comments.map(vader_polarity_compound)\n",
    "# copenhagen_reviews.to_hdf('copenhagen_reviews.h5', key='copenhagen_reviews', mode='w')\n",
    "\n",
    "! ls -lh *_reviews.h5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>listing_id</th>\n",
       "      <th>id</th>\n",
       "      <th>date</th>\n",
       "      <th>reviewer_id</th>\n",
       "      <th>reviewer_name</th>\n",
       "      <th>comments</th>\n",
       "      <th>polarity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6983</td>\n",
       "      <td>8985</td>\n",
       "      <td>2009-09-04</td>\n",
       "      <td>31133</td>\n",
       "      <td>Jeff</td>\n",
       "      <td>Convenient location, clean apartment, great br...</td>\n",
       "      <td>0.9322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6983</td>\n",
       "      <td>9199</td>\n",
       "      <td>2009-09-07</td>\n",
       "      <td>11472</td>\n",
       "      <td>Andrea</td>\n",
       "      <td>We really enjoyed staying to Simon in our firs...</td>\n",
       "      <td>0.9256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6983</td>\n",
       "      <td>11763</td>\n",
       "      <td>2009-09-28</td>\n",
       "      <td>35317</td>\n",
       "      <td>Jeanine</td>\n",
       "      <td>Friendly host, save neighbourhood, clean appar...</td>\n",
       "      <td>0.9432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6983</td>\n",
       "      <td>20616</td>\n",
       "      <td>2009-12-17</td>\n",
       "      <td>53151</td>\n",
       "      <td>Sonja</td>\n",
       "      <td>Simon is great!  Fantastic place to stay, supe...</td>\n",
       "      <td>0.9606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6983</td>\n",
       "      <td>23168</td>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>50856</td>\n",
       "      <td>James</td>\n",
       "      <td>Great bed, clean apartment, comfy bed, accomod...</td>\n",
       "      <td>0.9041</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   listing_id     id        date  reviewer_id reviewer_name                                           comments  polarity\n",
       "0        6983   8985  2009-09-04        31133          Jeff  Convenient location, clean apartment, great br...    0.9322\n",
       "1        6983   9199  2009-09-07        11472        Andrea  We really enjoyed staying to Simon in our firs...    0.9256\n",
       "2        6983  11763  2009-09-28        35317       Jeanine  Friendly host, save neighbourhood, clean appar...    0.9432\n",
       "3        6983  20616  2009-12-17        53151         Sonja  Simon is great!  Fantastic place to stay, supe...    0.9606\n",
       "4        6983  23168  2010-01-04        50856         James  Great bed, clean apartment, comfy bed, accomod...    0.9041"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "seattle_reviews = pd.read_hdf('seattle_reviews.h5', 'seattle_reviews')\n",
    "boston_reviews = pd.read_hdf('boston_reviews.h5', 'boston_reviews')\n",
    "copenhagen_reviews = pd.read_hdf('copenhagen_reviews.h5', 'copenhagen_reviews')\n",
    "copenhagen_reviews.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plotting the histogram of review intensities reveals the following peculiarities:\n",
    "* huge asymmetry between positive and negative reviews, 80+ k of them (or almost 50%) are close to maximally positive (`polarity > 0.92`);\n",
    "* prominent peak of ~10k 'neutral' reviews."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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RiVVGu9rMrBswGbjF3ceY2WjgEGBdVOUGd3/GzAYCQ4EKYJy7jzez5sADQGegHDjT3T8x\nswOAO4FK4F13HxIdaxhwUlQ+wt2fzeS5iYhIejKWeMysNTAaeCGhuA1wtru/Xa3e5cCPgRLgLTN7\nEjgWWO3uA83sGGAU8CvgVuAid59rZo+aWT9gAXAKIantALxqZlPdvTxT5yciIunJZFdbMXAMsCyh\nrG2SegcDc929yN03ArOAQ4E+wKSozlSgp5m1APZ097lR+WSgL9AbeM7dS9y9EFgEdG3g8xERkQaQ\nsRaPu5cBZWaWWNwGuMLM2gGfAxcCHYDChDorgI6J5e5ebmYVUdmqJHVX1rCP92qKr127VuTlNavp\n5ToVFCTLodkjm+NTbOnL5vgUW/riiG9hs/TaGZmILe7h1OOAD9x9oZn9FRgBvF6tTg7hOk310RA5\nNZTVVLfWUWurVm2oR9hb0iiZ9Cm29GVzfIotfXHFV1FekdZ2WzmqLWl5rKPa3H2Suy+Mnk4C9geW\nEloyVToByxPLo4EGOYRuu51rq1utXEREskysicfMnjKzqlvnewHvA3OAHma2o5m1IVzfmQU8Txil\nBmGgwQx3LwUWmFnPqPx4YArwIvBzM2thZrsSEs/8OM5JRETqJ5Oj2roDNwFdgFIzOxG4A3jczNYD\n6wlDpDea2SWEAQRVQ6GLzOwR4Egzm00YqHBGtOuhwDgzywXmuPv06Hj3ADOjfQxx9/TalSIiklGa\nuSAN6jNOn2JLXzbHp9jSp5kLREREMkyJR0REYqXEIyIisVLiERGRWCnxiIhIrJR4REQkVko8IiIS\nKyUeERGJlRKPiIjESolHRERipcQjIiKxUuIREZFYKfGIiEislHhERCRWSjwiIhIrJR4REYmVEo+I\niMSqzqWvzawdsKu7f2BmRwE/Bu5x9xUZj05ERJqcVFo8fwd2NbO9gJuBlcB9GY1KRESarFQSTyt3\nnwacBIx29zuAFpkNS0REmqpUEk9rMysATgSeMbMcoF1mwxIRkaYq1a62j4AX3X0JcDnwUiaDEhGR\npqvOwQXA50Bndy+Knt/m7qtT2bmZdQMmA7e4+xgz2x24H2gOlAKnuvsKM1sOeMKmfQhJ8QGgM1AO\nnOnun5jZAcCdQCXwrrsPiY41jNAdWAmMcPdnU4lRRETilUqL52fAK2Y228wuByzqbquVmbUGRgMv\nJBRfDdzt7kcAk4A/RPta5u69Ev6VAwOA1e7eE7gOGBXt41bgInc/FNjZzPqZ2Z7AKUBPoD9wm5k1\nS+HcREQkZnUmHncf7O7dCK2Jj4G/AoUp7LsYOAZYllB2LvB49LgQ2BloDSRLEn0IyQlgKtDTzFoA\ne7r73Kh8MtAX6A085+4l7l4ILAK6phCjiIjELJX7eHYHjgB6Ef6YLwNG1rWdu5cBZWaWWLY+2mcz\n4LxoP22A9mb2GLAr8E93vx3oQJTg3L3czCqislUJh1kBdCQM8S5MUv5eTfG1a9eKvLz0G0UFBW3T\n3jYO2RyfYktfNsen2NIXR3wLm6U3X0AmYkvlGs8iQovjRnd/cWsPGCWdhwiDFV4ws+2B4YRBDM2B\nmWb2ClC9Oy+nhrLKWsprtGrVhvROgPCDKCxcm/b2mZbN8Sm29GVzfIotfXHFV1FekdZ2WxNbTUkr\nlcRzIKHFc56ZXUVoRbzk7v9MM5b7gY/cfQSAu6/h6xtSi81sOrA/sJTQwnnHzJoTkskyQvdclU7A\n8qiuJSkXEZEsk8o1nvfcfQxwOnAV4Y/6+HQOZmYDgRJ3vyKh7AdmNsHMcswsjzBA4APgecJ1JYBj\ngRnuXgosMLOeUfnxwBTgReDnZtbCzHaNYpyfTowiIpJZqVzjuQk4DNiO8Af+LsIIsrq26w7cBHQB\nSs3sRKA9sMnMXoqqzXf3c81sJTAHqACedvf/mNk84Egzm00YqHBGtM1QYJyZ5QJz3H16dLx7gJmE\nLrYh7p5eu1JERDIqla629wkJZLm713rdJJG7zyMMSEil7h+SlJUDZyYpn09IhNXLRxOGb4uISBZL\nZZjDW8BTwIcAZjbczA7OaFQiItJkpZJ4bgQG8fXF+kcIs1SLiIjUWyqJp8Ld36164u4LgbLMhSQi\nIk1ZSncURVPSVEaP+/HN+2ZERERSksrggj8RpqYxMysi3FB6eiaDEhGRpqvOxBN1s+0frcmzyd2z\n9xZgERHJejUmHjP7i7uPMrOHSJh+pmruNXc/LfPhiYhIU1Nbi+fN6P/pcQQiIiLbhhoTj7tPjR72\nAx4Epmg2ABER2VqpjGp7GhgMLDKz28zsRxmOSUREmrBUJgmd6O6/AH5AmMXgMjN7P+ORiYhIk5Tq\nfTw5wEFAD8LyA29nMigREWm6Upmd+i7CsgRvAQ8Dw9w9/VXURERkm5bKDaTvAn9195WZDkZERJq+\nVLraniWsfzMDwMzONrO9MhuWiIg0VakknrGE4dRVdRcCd2csIhERadJSSTzN3f0pwuqguPvMzIYk\nIiJNWUqJx8x25OvZqfcDWmY0KhERabJSGVwwEngd6Ghm7wK7AKdmNCoREWmyUkk8LxHu4ekGFAML\n3X1TJoMSEZGmK5XE86K79wbmZjoYERFp+lJJPG+b2UjgVaCkqtDdX8xYVCIi0mSlkngOjP4/LKGs\nEqgz8ZhZN8Lqpbe4+xgz2x14CGgGLAd+4+7FZjYQGEoYOTfO3cebWXPgAaAzUA6c6e6fmNkBwJ1R\nDO+6+5DoWMOAk6LyEe7+bArnJiIiMUtlBdLe6ezYzFoDo4EXEopHAmPd/V9mdj0wyMweBC4Hfkxo\nUb1lZk8SpulZ7e4DzewYYBTwK+BW4CJ3n2tmj5pZP2ABcApwCLAD8KqZTXX38nRiFxGRzElpktA0\nFQPHAMsSynoBT0WPJwN9gYOBue5e5O4bgVnAoUAfYFJUdyrQ08xaAHu6+9xq++gNPOfuJe5eCCwC\numbovEREZCuk0tWWFncvA8qqlsqOtHb34ujxCqAj0AEoTKjzjXJ3LzeziqhsVZK6K2vYx3s1xdeu\nXSvy8prV/8QiBQVt0942Dtkcn2JLXzbHp9jSF0d8C5ul187IRGw1Jh4zO9Pd7zezs9393gY6XmXC\n45zoeU61OrWV16duJbVYtSr9CbYLCtpSWLg27e0zLZvjU2zpy+b4FFv64oqvojy9BaS3JraaklZt\nLZ7Loq6toVFrYwvuPj6NONabWcuoS60TYYDBUqB/Qp1OhBtWlxJaOO9EAw1yCN12O1erW7UPS1Iu\nIiJZpra21zDCwm87Eka0Jf7rmebxpgMnRI9PAKYAc4AeZrajmbUhXN+ZBTxPGKUGYaDBDHcvBRaY\nWdXxj4/28SLwczNrYWa7EhLP/DRjFBGRDKqxxePuTwBPmNkJ7v54fXdsZt2Bm4AuQKmZnQgMBB4w\ns98Bi4EJ7l5qZpcQBhBUDYUuMrNHgCPNbDZhoMIZ0a6HEpZpyAXmuPv06Hj3ADOjfQxx9/TalSIi\nklE5lZW1XgohakFcRWj9VBK6wS6LRo99axUWrq39xGuhPuP0Kbb0ZXN8ii19ccW34Jf71Xubw179\nbGuv8VS//g6kNpx6HPAm8GtCi+VD4L60IxERkW1aKsOpW7n72ITn75vZLzIVkIiING2ptHham1nH\nqidmthuwXeZCEhGRpiyVFs9VwDwzW0EY0lwAnJXRqEREpMlKZa62Z8zse8DeXxdpPR4REUlPSlPm\nRDd8vpPhWEREZBuQyUlCRUREvqHOxGNmScdhi4iIpCOVFo9WGhURkQajpa9FRCRWGV36WkREpLqU\nl742sxx3T3t+MxEREUhtcMEBZvYGYY42zGy4mR2c8chERKRJSmVwwU3AIL5eWO0R4OaMRSQiIk1a\nKomnwt3frXri7guBssyFJCIiTVlKN5Ca2Z6EAQWYWT/CnG0iIiL1lsqotj8CkwEzszXAp8DpGY1K\nRESarFRGtb0H7G9mBcAmd8/epfxERCTr1Zl4zKwrcCWwH1BpZu8BV7q7Zzg2ERFpglLpansQuAO4\nnHBtpyfwd6BHBuMSEZEGNHLh7fXeZloG4oDUEk+hu49PeP6hmZ2QoXhERKSJqzHxmFnViLdZZnY8\nMB2oAPoAM2OITUREmqDaWjxlhCHUyYZOlwHX1vdgZnYW8JuEoh8BM4B2fH1v0B/dfZ6ZDQNOimIY\n4e7PmtkOwMPADsA6YIC7f2VmfaN4yoFn3f2q+sYmIiLxqDHxuHuDLxLn7vcB9wGY2RHAyUBXoL+7\nr66qF903dApwCCHJvGpmU4GhwEvufoOZnQtcHP27HTgKWArMNrPH3X1+Q8cvIiJbL5VRbbsCJwA7\nktD6cfeRW3nsy4GBwL+TvNYbeM7dS4BCM1tESFB9CNP3QLi36Ckz+y7wlbsvieJ9JqqnxCMikoVS\nGVzwLPAW8HlDHdTMegBL3H2FmbUBxprZHsB7wB+ADkBhwiYrgI7VypOVVZV/r6FiFRGRhpVK4vnK\n3c9s4OOeDTwQPR4FPE9IGOOA8/jmdaUcvnm9KVlZYnmt2rVrRV5es/rGvVlBQdu0t41DNsen2NKX\nzfEptvTFEl9uejOdZSK2VBLPJDMbCLxGwuSg7v7ZVhy3F3BBtJ8JVYVm9iTwK8KAA0uo34kwO/ZS\nQgunKElZ9bq1WrVqQ9rBFxS0pbAweydwyOb4FFv6sjk+xZa+2OKrSG85ta2JraaklUri2Z9wLWZl\nQlklsEc6gUTXjNa5e4mZNSO0dv7X3dcQEtL7hNVN/2BmVwC7EJLJ/KjuScDVhOtOU9x9kZltb2Zd\nCN2B/aN4RUQkC6WSeH4C7OTumxromB2BLwDcvdzM7gdmmNl6QuvlSnffYGb3EO4XqgSGuHuFmd0O\n/N3MZgGrgVOjfQ4B/hE9fiRaukFERLJQKolnLpAPNEjicfd5QL+E538nTMFTvd5oYHS1snXAcUnq\nziQMvRYRkSyXSuLZDVhkZh+y5TWewzMWlYiINFmpJJ5rMh6FiIhsM1JJPOmPORYREakmlcQzPOFx\nC8K6PK8QRp6JiIjUSyorkPZOfG5m7Qk3fYqISCMZPG1Q3ZW2kD13mdR7IlB3/wLYNwOxiIjINiCV\nSUIfYsspaHYnLD8gIiJSb6lc45me8LgSWEOYQUBERKTeUrnGM6GuOiIiIqmqbenrT9myi61q1ud8\noIO7a5i1iIjUW20rkO5ZvczMjiOMaBufyaBERKTpSuUaD2a2F2F56RLg5+7+SUajEhGRJqvWxGNm\nrQlLVP8cGObuz8USlYiINFk13sdjZr8G5gFfAQcq6YiISEOorcUzEVgIHA0cZbZ5QdAcoNLdf5rh\n2EREpAmqLfF8Y3CBiIjI1qptVNviOAMREZFtQ73nahMREdkaSjwiIhIrJR4REYmVEo+IiMRKiUdE\nRGKV0pQ5DcXMugOTgY+joveA64GHgGbAcuA37l5sZgOBoUAFMM7dx5tZc+ABoDNhTaAz3f0TMzsA\nuJMwiem77j4kxtMSEZF6iLvF0wZ4zN17Rf8uAEYCY939MGARMChhqp6+QC/gz2a2EzAAWO3uPYHr\n+HoJ7luBi9z9UGBnM+sX50mJiEjq4k48bZOU9QKeih5PJiSbg4G57l7k7huBWcChQB9gUlR3KtDT\nzFoAe7r73Gr7EBGRLBRrVxuhxdPTzJ4DWgNXAK3dvTh6fQXQEegAFCZs941ydy83s4qobFWSuiIi\nkoXiTjzvACPd/Skz25uwrHbzhNerFpvLqbZdbeU11a1Vu3atyMtLfy27goJkjbfskc3xKbb0ZXN8\nii196cSXn9+87kqJcqv/qUxNJt67WBOPu38IfBg9XmhmK4Ddzaxl1KXWiTDAYCnQP2HTTsDrUXkH\n4J1ooEEOsAzYuVrd5XXFsmrVhrTPo6CgLYWFa9PePtOyOT7Flr5sjk+xpS/d+IbcNLte9UdWnFzv\nYwBb9d7VlLRivcZjZoPM7MLocQfgO8D9wAlRlROAKcAcoIeZ7WhmbQjXd2YBzwMnRXWPBWa4eymw\nwMx6RuXHR/sQEZEsFHdX2yRgopmdCOQDQ4C3gAfN7HfAYmCCu5ea2SWEAQSVwAh3LzKzR4AjzWw2\nUAycEe13KDDOzHKBOe4+PdazEhGRlMXd1bYKOCbJS0cmqfsY8Fi1snLgzCR15wOHNVCYIiKSQZq5\nQEREYqXEIyIisVLiERGRWCnxiIhIrJR4REQkVko8IiISq7jv4xGRWrQdPKjmF/Ob07a49BvFa+8a\nn8GIRBqeWjwiIhIrJR4REYnoDkcBAAAPcklEQVSVEo+IiMRKiUdERGKlxCMiIrFS4hERkVhpOLWI\nyLfQyIW3N3YIaVOLR0REYqXEIyIisVLiERGRWCnxiIhIrDS4QESkkQ2eVsscfTUa2OBxxEUtHhER\niZUSj4iIxEqJR0REYhX7NR4zux44LDr2KKA3cAiwLqpyg7s/Y2YDgaFABTDO3cebWXPgAaAzUA6c\n6e6fmNkBwJ1AJfCuuw+J85xERCR1sbZ4zKw30M3dDwGOBm4F2gBnu3uv6N8zZtYauBzoC/QC/mxm\nOwEDgNXu3hO4jpC4iPZzkbsfCuxsZv3iPC8REUld3F1tM4GTosergNbAjknqHQzMdfcid98IzAIO\nBfoAk6I6U4GeZtYC2NPd50blkwkJS0REslCsXW3uXg6sj56eDTwLFABXmFk74HPgQqADUJiw6Qqg\nY2K5u5ebWUVUtipJXRERyUKNch+Pmf0SOAv4GfBT4AN3X2hmfwVGAK9X2ySHcP0mJ0l5srLKumJo\n164VeXnN0og+KChom/a2ccjm+BRbLfKb1/rydkle366xY440+ntXi2yODSC/jp97UrnV//RlRibe\nu8YYXHAU8FfgaHcv4uuuM6LHdwKPA/0TyjsRktFSQgvnnWigQQ6wDNi5Wt3ldcWxatWGtM+hoKAt\nhYVr094+07I5PsVWu7bFpTW+tl1+czYleX1tFryf2fDe1SSbY4MQX3EtP/caVdT5/bpBbM17V1PS\nintwwQ7ADUB/d/8qKnvKzPaIqvQC3gfmAD3MbEcza0O4vjMLeJ6vrxEdC8xw91JggZn1jMqPB6bE\ncT4iIlJ/cbd4fgXsAjxqZlVl44HHzWw94frPme6+0cwuIQwgqARGuHuRmT0CHGlms4Fi4IxoH0OB\ncWaWC8xx9+mxnZGIiNRL3IML7gbuTvLSg0nqPgY8Vq2sHDgzSd35hHuDREQky2mSUBGRRjZ0zJx6\nbzNSk4SKiIikRolHRERipcQjIiKxUuIREZFYaXCBiEgjG7nw9sYOIVZq8YiISKyUeEREJFbqahMR\nqcXgaYPqvc1dR47PQCRNhxKPiEgDq0+yCjNTn5y5YLKQutpERCRWSjwiIhIrJR4REYmVrvGIiDSw\n+kz6mdsslyu3sWs8SjwiWeT0/1zEVxu/TP5ibk7SVScfznBMIg1NiUdEpBZrLqzf8gOX731hhiJp\nOpR4REQaUL2nv8nNISy0vO1Q4hGRbUbbwfW/GZRv8YJr2UqJR0S2KXOX13e1TyWehqbh1CIiEiu1\neEQkKyz45X4Z2e/CZrlUlFdkZN+SHiUeEalTnddG8pvTtrh0i6K1d2V+osyULuTXMAxdGk+TSjxm\ndgvwE8IQkYvcfW6mjlXfi5Rx/BKKZJP0LuTLtqDJJB4zOwLYy90PMbOuwP3AwY0cVtZTApVssa2t\nwrktazKJB+gDPAng7vPNrJ2Zbe/uaxo5LiCeb39xJIV0ziOduBrl23KS7qKt1VQSdV0jwXIb5DqK\nRo9tK5pS4ukAzEt4/t+oLCOJ59iXs/CXZN8Xwv/16tOO4Tyq4oJ6xNYI728mrgUknnuGDIjhGFBH\na0TXUaQemlLiyUnyvMbfhIKCttXr18u0L4/bms1FRL4VCgraNvg+m9J9PEsJLZwquwIrGikWERGp\nQVNKPM8DJwKY2UHAMndf27ghiYhIdTmVlU2nX9bM/gYcDlQA57n7O40ckoiIVNOkEo+IiGS/ptTV\nJiIi3wJKPCIiEqumNJy6wUWzIfwLGOTu/07y+kBgKOGa0jh3H29mzYEHgM5AOXCmu3/SwHHVegwz\n6w7clLBJV+A44BDgTKBqbeWH3P2+howtlfiiOssBTyjqQ/giVOt2McX2K+CPhJ/rC+7+VzM7AbgO\n+DyqNs3dr2nAuGqc7snM+gLXRvE+6+5X1bVNQ6ojtt7AqCg2B84GDgImAx9H1d5z9wsyEVsK8b0F\nFCVUH+juSxv7vTOzTsDEhKrfBS4Bisng5yxJfN0IP6tb3H1Mtdcy9rlT4qmBmX0P+AMwu4bXWwOX\nAz8GSoC3zOxJ4FhgtbsPNLNjCL+Uv2rg8AbUdgx3nwf0iuLcEXgKeB04ErjM3Z9s4HjqFZ+Z5RBG\nHfZK3MjMTq1tu5hia0X4xf8BsA543cwmAm2AMe5+awPHk8p0T7cDRxFuGZhtZo8DBXVsE1dsdwO9\n3f1zM/sXcDSwHnjM3Yc2dDxpxEeSz1ks02vVdhx3X8rXv6N5wEuE39MTyNDnLEl8rYHRQE13IGfs\nc6eutpotB46n5pkPDgbmunuRu28EZgGHEr65T4rqTAV6ZiC2+hzjT4RvMxVAw98Jllxd8bUGmqWx\nXcZjc/cNwA/cfa27VwIrgZ3J7Hu3xXRPQDsz2x7AzL4LfOXuS6Kf4TNR/Rq3iSu2SHd3r/p2Xkjm\n36v6xpcslmx576qcATzu7utqiDdTioFjgGXVX8j0506JpwbuvsHdy2up0oHwi1ZlBdAxsTzavsLM\nWjRweCkdw8xaEr6xTI6K2gBDzGy6mU02s84NHFeq8bUB2pvZY2b2qpldmOJ2ccRG1f1fUTdEF0Jr\nsQ1wvJk9b2bTzOyATMQUqZruKdlr3/icJdmmIdV6nKq5EM2sI6FF/SzhveppZs+Z2cyoOy5T6nof\ndjaziWb2ipldHbW2s+K9S3A2UNXlncnP2RbcvSz60pxMRj936moDzOxswg8/0RXuPrWWzWqaoqde\nU/ekGVv1pm1NxzgOeCb6xgLwGKGb6Y3o+tQYQtdg2tKMbwMwHPg70ByYaWavkEXvnZntBfwDGODu\npWb2IjDH3WeY2WHAQ8D+6caWJIaaYorlc1aLOo9jZu2Bpwn3zq00s3eAke7+lJntDUw3s++7e0kj\nxHcp4VrKRsIXsONT2Cau2DCzQ4AFCZMZZ/JzVh8Z/dwp8QDufi9wbz03Wwr0T3jeifDNuGrqnnei\nC9k57p72lMfJYjOzB1I8Rn/gzoR9TU94bRLhwuFWSSe+6Jes6htesZlNJ/xyZcV7Z2a7EboTfuPu\nb0f7+k/CfmeZWXsza1ZHqzhVtU33VP21ToRu4NJatmlItU5FFXWzPEe4dvg8gLt/CHwYPV5oZiui\nuD+NOz533/z5N7N/s+XnLOk2ccUW6Q9s/r3M8OesPjL6uVNXW/rmAD3MbEcza0O4vjOLMHXPSVGd\nY4EZGTh2qsfoAWyevcHM7jKzqm/8vYD3MxBbnfGZ2Q/MbIKZ5UQXVnsCH9S1XRyxRe4Dhrj7mwkx\nD49GtlV1wRU24B+DGqd7cvdFwPZm1iV6r/pH9eOaIqqu49xEuIb4XFWBmQ2q6j41sw7Adwh/yDKh\nxvjMbBczezb6ggFwBOEzny3vHXzzdzSTn7OUZfpzp5kLamBmPweGAfsQ+jSXu/vPzOwS4GV3f83M\nTozqVAKj3X2imTUjfMvei3Dx7gx3X9LAsSU9RmJsUb0v3L19wnY/BMYSRuFVAL9194+/cYAY4jOz\nmwkJpwJ42t2vyYb3jjCY4G3gPwmb3Qy8SxiGnUPoKfh94rfTBohri+meCEOSi9x9kpkdThhpB+Ei\n9I3JtvEMTRFVU2yEwRmrgNcSqj9MuAWhaiRgPjDC3Z/NRGy1xRe9d8MIoxaLgbeAC929orHfO3ef\nFL3+HtDX3f8bPe9CBj9n1WKruu2iC6Els5Qwsu7TTH/ulHhERCRW6moTEZFYKfGIiEislHhERCRW\nSjwiIhIrJR4REYmVEo80aWbW0czKzOziauX/tDBDcPX6D0QzHqS6/zPM7O8NEWstx0gaa1zMrDK6\nlyPV+pdEtyNgZgPMTH9nZAuauUCaujOA+YTlIKruScDdT2msgOrr2xQrgLv/LeHpCOBRwj0fIoDu\n45EmzswWAkMIN+WdnHBz7SKgL+Em1v5AO8KNoicRbrDdhXCT6QPufpOZXUmYebkTsDcww90vMLMz\nCDcoriKsqfIJYaqdzXebm1kv4DLCTYyPE+aoGwt8nzBL92TgVmAJ0COaMh8z+wj4BWFKmr7u/rGZ\nXUuYJaMSmAv8OTrmQe6+2sLSBGvdfVA0a8A0d/9BtViuBhYDewKrgVPcfY2ZDQIGE+bS+y/hBuM1\nZlZJmFNvZ8LcYXnADsBt7v5g9B5Ufw9nA7sTlg6ZSUj+K9x9RBTHxcBO7r5FS1S2DWoCS5NlYT2U\nPMLEiw8SWj3JHAgc4+7PRM93JayLchhwqZntFJUfRPij2gM408zaJZT/jrDQ3m5AvyTH6EFISOOB\niwhTjfQGegOnAPsRWgZV06V0J9zh/mHC+ZwEdHL3IzysMfN9wh/8FwizQecA7YHvRZv0JkxxUl13\n4M/u/j+EmRrOMLM9CK2TPtG+lwC/r7bdroS1Yn4aHffmWt5D3P2K6GEfQmvz1ChGovdxfJLYZBug\nxCNN2VmEFksl4Y/cyRYWeqvuTXcvTng+3d0r3X01YRXNvaLy2e5eHk0l/yVQlZBe96/X73mNkESq\nc3f/KnrcG/hfM3uJkDS2IySRh4nmwSK0oh6qto/ewCFm9lK0bRdCq2UaYQqTHwALgBVmtntUP9kM\n6x9UtaqAVwgr1P4QmJcw79ZLhGSZaBnwazObDfyT0AKqUv09rH7yiwjv5eEWFlnc4O5eU31p2nSN\nR5qkaNbk44HPzOz4qDgvKqs+GKD6dP2J1yMSp30vq1av6tt7TfVrOkYxYdmAx5LE3d7C2jbHE7rU\nqLbd3VVzZiVsszNwIWGurZcJCfEIwvLEF/JNiV84a4o3WfnVwEfu/utoYtzEySFTWfJgHHAaIQE1\n+JLr8u2hFo80VQMIE5J2dfcD3f1A4Bxq7m5L9FOAqCvtu8DCOuofbGato26kQ4D36qg/m2iGbDPL\nNbObE7rz/klYq2hh1cSR1bb736oRZmZ2uZnt5e4rCb/LxxBaKjMJLabl7r4pyfH3iZIbhGtc7wJv\nAN3NrGoFzL6EZT4SfQf4v+jxAMIievl1nGsl0DJ6/G/CUvG/IEwkKtsoJR5pqs4iYS2iyGPAftEM\nwLVZZmZPEpa5GBl1udXmDcI3+DmENWdqW0AQwsCC9Wb2GuGP++qEbriJhASZbIj2E8CrwKtm9joh\nEXwSvfYS0MXdlxES309Ifn0HwhIUo8xsFmGp5Qc9LF89nLBo20yggDDgIdEYwjWvaYTWzguE7sHa\nTAFeN7PvuXsZYaDEOx6WGJdtlEa1iWxDqka1uXvPRjh2C0Kr7Qx3nx/38SV7qMUjIhlnZv0ILcMH\nlXRELR4REYmVWjwiIhIrJR4REYmVEo+IiMRKiUdERGKlxCMiIrFS4hERkVj9P23EGGEMShV9AAAA\nAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(seattle_reviews.polarity, bins=25, color='g', alpha=0.65)\n",
    "plt.hist(copenhagen_reviews.polarity, bins=25, color='r', alpha=0.65)\n",
    "plt.hist(boston_reviews.polarity, bins=25, color='b', alpha=0.65)\n",
    "plt.legend(['Seattle', 'Copenhagen', 'Boston'])\n",
    "plt.xlabel('Airbnb review polarity')\n",
    "plt.ylabel('Number of reviews')\n",
    "plt.subplots_adjust(left=0.15, right=0.95, top=0.95, bottom=0.12)\n",
    "plt.savefig('airbnb_reviews_polarity.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Importantly, very small fraction (`< 5%`) of all reviews of our interest are negative:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.012539823395062627, 0.02678717418147169, 0.0465029255681045)"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(seattle_reviews.polarity.values < -0.05).mean(), \\\n",
    "(boston_reviews.polarity.values < -0.05).mean(), \\\n",
    "(copenhagen_reviews.polarity.values < -0.05).mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us look on their distribution in more details:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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TJJNxwFkEgw5SZRGcq6nTyuLShokwSf0HpK2ovNwcCguL0lZeuuXHeL/j1kmc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\nmFXibA4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(seattle_reviews.polarity, bins=50, color='g', alpha=0.65)\n",
    "plt.hist(copenhagen_reviews.polarity, bins=50, color='r', alpha=0.65)\n",
    "plt.hist(boston_reviews.polarity, bins=50, color='b', alpha=0.65)\n",
    "plt.legend(['Seattle', 'Copenhagen', 'Boston'])\n",
    "plt.xlim([-1.00, 0.00])\n",
    "plt.ylim([0, 2000])\n",
    "plt.xlabel('Airbnb review polarity (negative)')\n",
    "plt.ylabel('Number of negative reviews')\n",
    "plt.subplots_adjust(left=0.15, right=0.95, top=0.95, bottom=0.12)\n",
    "plt.savefig('airbnb_reviews_negative_polarity.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we see, the negative review structure is Boston, Seattle in Copenhagen is quite similar, alhough in Copenhagen some broad and narrow peaks (such as very negative reviews with `polarity < -0.8`) are much more pronounced."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0028949244264703743, 0.006681288445599652, 0.01723796682294437)"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(seattle_reviews.polarity.values < -0.8).mean(), \\\n",
    "(boston_reviews.polarity.values < -0.8).mean(), \\\n",
    "(copenhagen_reviews.polarity.values < -0.8).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "def show_most_common_duplicates(df, top_number=3):\n",
    "    '''\n",
    "    Shows several most common duplicates together with their occurence frequency\n",
    "    \n",
    "    Args:\n",
    "        df (pandas dataframe): dataframe that contains ['polarity'] column\n",
    "        top_number (int, default = 3): number of most common duplicates to show\n",
    "    \n",
    "    Returns:\n",
    "        val_freq_list (list): sorted list that contains the top value and the corresponding frequency\n",
    "    \n",
    "    '''\n",
    "    \n",
    "    res = list(Counter(df.polarity.values).most_common(top_number))\n",
    "    val_freq_list = [(i[0], i[1]/df.shape[0]) for i in res]\n",
    "    return val_freq_list "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([(0.0, 0.027567245166639998),\n",
       "  (0.6249, 0.013703612109221571),\n",
       "  (0.6588, 0.0093714086207649)],\n",
       " [(0.0, 0.05343903112860212),\n",
       "  (0.6249, 0.01719656519753497),\n",
       "  (0.6588, 0.010470171007154899)],\n",
       " [(0.0, 0.12667153230495182),\n",
       "  (0.5994, 0.00689333118915375),\n",
       "  (0.2732, 0.006265540147700986)])"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "show_most_common_duplicates(seattle_reviews), \\\n",
    "show_most_common_duplicates(boston_reviews), \\\n",
    "show_most_common_duplicates(copenhagen_reviews)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we see, for all datasets the top unique review polarity is `0.0`. Also, there is a large variations between cities for its apparent frequency - while for Seattle it is only `2.8%`, for Copenhagen it is as much as `12.7%`.\n",
    "\n",
    "Look closer for reviews with polarity `0.0`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "22     Simon est gentil, il habite dans un très joli ...\n",
       "24     Det var herligt at bo Simon, godt centralt ste...\n",
       "51     Gutterne var meget hjælpsom og rare. Huset var...\n",
       "65     Nous avons passé un bon séjour. La chambre est...\n",
       "81     Simón y su novia son excelentes anfitriones el...\n",
       "97                                     Très bon accueil!\n",
       "98     Simon ist ein hilfsbereiter und entspannter Ga...\n",
       "110                                           tusen tak!\n",
       "128    Ihana ja moderni asunto lähellä keskustaa. Sim...\n",
       "143    The host canceled this reservation 19 days bef...\n",
       "149            Bra beliggenhet og et koselig sted å være\n",
       "155    The host canceled this reservation 51 days bef...\n",
       "208    Wirklich im Herzen von Copenhagen. Dadurch lei...\n",
       "224    The reservation was canceled 11 days before ar...\n",
       "259    Excellente situation de la maison.\\r\\nService ...\n",
       "286    Fin leilighet med flere sengeplasser, lå nært ...\n",
       "296    Siamo stati a Copenhagen soltanto pochi giorni...\n",
       "300    Erittäin ystävällinen yhteydenpito,nopeat vast...\n",
       "303    Svært sjarmerende hus! Nabolaget er virkelig u...\n",
       "313    Vi hadde et fint opphold i leiligheten! Sentra...\n",
       "315    The host canceled this reservation 8 days befo...\n",
       "317    The host canceled this reservation 44 days bef...\n",
       "322    The host canceled this reservation 4 days befo...\n",
       "337    Nous avons séjourné dans cet appartement 4 jou...\n",
       "341    The host canceled this reservation 134 days be...\n",
       "342    The host canceled this reservation 142 days be...\n",
       "355    The host canceled this reservation 8 days befo...\n",
       "356    La casa tiene una ubicación inmejorable.\\r\\nEl...\n",
       "358                                       Alles perfekt!\n",
       "362    Tolle Lage - guter Ausgangspunkt für Touren - ...\n",
       "Name: comments, dtype: object"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "copenhagen_reviews[copenhagen_reviews.polarity == 0.0].comments.head(30)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Not surprisingly, most of such reviews are written in languages different from English (e.g. French, German, Spanish, Danish), so it is natural that Copenhagen, being a European city very attractive for foreign tourists, has more comments on foreign languages than Boston or Seattle."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Other comments made in English, such as `'The host canceled ...'` or `'The reservation was canceled ...'`, are probably automatic messages generated by the system."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.005917865611498233, 0.00888583172174266, 0.035276908422914685)"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def zero_technical_reviews(df):\n",
    "    '''\n",
    "    Returns the fraction of \"technical\" reviews (staring from \"The host canceled\" or\n",
    "    \"The reservation was canceled\") of zero polarity\n",
    "    \n",
    "    Args:\n",
    "        df (pandas dataframe): dataframe that contacts columns ['comments'] and ['polarity']\n",
    "    \n",
    "    Returns:\n",
    "        zero_polarity_fraction (float): fraction of \"technical\" reviews of zero polarity\n",
    "    '''\n",
    "    \n",
    "    res1 = df[df.polarity == 0.0].comments.map(lambda s: s.startswith('The host canceled')).sum()\n",
    "    res2 = df[df.polarity == 0.0].comments.map(lambda s: s.startswith('The reservation was canceled')).sum()\n",
    "    zero_polarity_fraction = (res1+res2)/df.shape[0]\n",
    "    return zero_polarity_fraction\n",
    "\n",
    "zero_technical_reviews(seattle_reviews), \\\n",
    "zero_technical_reviews(boston_reviews), \\\n",
    "zero_technical_reviews(copenhagen_reviews)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we see, **the technical messages fraction about apartment cancellation in Copenhagen 4-6 times larger than in Boston and Seattle**!\n",
    "\n",
    "Note also that although most of such technical messages are identified with score `0.0`, some of them are not:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2.0366302497781528e-05, 3.3829308585314695e-05, 0.0001422580685065377)"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def nonzero_technical_reviews(df):\n",
    "    '''\n",
    "    Returns the fraction of \"technical\" reviews (staring from \"The host canceled\" or\n",
    "    \"The reservation was canceled\") of non-zero polarity\n",
    "    \n",
    "    Args:\n",
    "        df (pandas dataframe): dataframe that contacts columns ['comments'] and ['polarity']\n",
    "    \n",
    "    Returns:\n",
    "        nonzero_polarity_fraction (float): fraction of \"technical\" reviews of zero polarity\n",
    "    '''\n",
    "    \n",
    "    res1 = df[df.polarity != 0.0].comments.map(lambda s: s.startswith('The host canceled')).sum()\n",
    "    res2 = df[df.polarity != 0.0].comments.map(lambda s: s.startswith('The reservation was canceled')).sum()\n",
    "    nonzero_polarity_fraction = (res1+res2)/df.shape[0]\n",
    "    \n",
    "    return nonzero_polarity_fraction\n",
    "    \n",
    "    \n",
    "nonzero_technical_reviews(seattle_reviews), \\\n",
    "nonzero_technical_reviews(boston_reviews), \\\n",
    "nonzero_technical_reviews(copenhagen_reviews)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In addition, there is a small fraction of other reviews that are likely to be misidentified by the system, for example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "listing_id                                                    6695\n",
       "id                                                       221743420\n",
       "date                                                    2017-12-27\n",
       "reviewer_id                                              135126263\n",
       "reviewer_name                                               Olivia\n",
       "comments         It's a really decent apartment！Love living her...\n",
       "polarity                                                         0\n",
       "Name: 145, dtype: object"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "boston_reviews[boston_reviews.polarity == 0.0].loc[145,:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What about very negative reviews? First, look into the Copenhagen dataset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Unser Aufenthalt in Simons Apartment war sehr angenehm. Das Zimmer ist gemütlich und die Innenstadt ist von dort aus gut zu Fuß erreichbar. Simon und sein Mitbewohner sind sehr nett und gastfreundlich. Leider konnten wir Simon nicht persönlich kennen lernen, er hat uns aber vorher kontaktiert und sich um alles Wichtige gekümmert, sowie uns Reiseführer mit vielen Tipps hinterlassen.',\n",
       " 'Der Aufenthalt bei Simon und Singe war super. Simon ist ein sehr freundlicher Gastgeber, wir haben uns sehr schnell wie zuhause gefühlt. \\nDas Zimmer ist klein, aber wer nur zum schlafen zuhause ist, hat damit kein Problem. Das Fenster zeigt auf die Parkseite des Gebäudes, sodass man schö bei Fenster offen schlafen kann. Die Wohnung selbst ist wunderschön und liebevoll eingerichtet, das Bad geräumig. Morgens haben wir bei Simon gefrühstückt, was kein Problem für ihn war. Wir haben einen Platz im Kühlschrank bekommen und konnten so gemütlich in den Tag starten. Die Matratze war super bequem, trotz 2 Personen im Bett. \\nDas Viertel in dem die Beiden wohnen ist ziemlich cool. Es gibt viele Restaurants und Kneipen und Supermärkte in naheliegender Umgebung. Die Metro und Bushaltestellen sind 10 bzw 5 Minuten von der Wohnung entfernt. \\nEs gibt keinen Punkt, der zu bemägeln war. Gerne wieder und eine herzliche Empfehlung für alle Kopenhagen-Reisende!',\n",
       " 'Kari´s Haus ist irre sympathisch, es ist einfach schön, sich dort aufzuhalten. Der idyllische Patio, der große Esstisch, die hellen Farben - alles ist sehr geschmackvoll und einladend. Die Betten und Bäder sind prima, Infrastruktur wie Spülmaschine, Internet etc. funktioniert bestens. Die Gegend ist supernett und reell, das Café am Ende der Straße hat eine gute Bäckerei und ist der Morgen-Treff für die \"Lokals\". Kari ist eine sehr nette, entgegenkommende und fürsorgliche Gastgeberin, ihre Tipps für Lokale etc. waren prima, die Kommunikation mit ihr verlief perfekt. Unser Kopenhagen-Aufenthalt wird immer mit den Stunden in ihrem schönen Haus verbunden sein - jederzeit wieder!',\n",
       " 'Wir waren 11 Personen und hatten eine wunderbare Zeit! Die Unterkunft ist nur zu empfehlen. Die Organisation mit Oliver funktioniert perfekt. ',\n",
       " 'Ich denke, wenn 11 Leute, mit ganz unterschiedlichen Ansprüchen und Vorstellungen von einer Urlaubsunterkunft wieder abfahren , und ALLE der Meinung sind, das Haus war toll, spricht das wohl für sich!!!\\r\\nUnd wenn alle Anbieter so bemüht und entgegenkommend wären wie Oliver, wären gerade die An-und Ab(!!!)reisetage immer um einiges entspannter!\\r\\n']"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(copenhagen_reviews[copenhagen_reviews.polarity < -0.8].comments.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In fact, all these negatively classified reviews are in German, and have very positive tone.\n",
    "\n",
    "Let us look to Boston and Seattle, then:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[\"The penthouse apt. was very nice. However, the elevator wasn't working, and we had to climb 6 flights (4 times, as it ended up). That can happen. However there were other problems that a checklist would have corrected. The cooling did not work until an air conditioning contractor was called (the apt was in the 80s when we arrived after climbing stairs). First, the thermostat in the LR didn't control the cooling, though the sign on it warned against setting it too low. We later were told the cooling was controlled by a thermostat behind the front door, in a closet or niche, but it was inoperable because the battery needed replacement. There was no bath or hand soap, an omission we did not discover until we were ready to shower -- then an 8 block walk to buy soap. The coffeemaker is broken (line that distributes hot water to the grounds was missing); the filters provided were the wrong type (we poured boiling water manually); the toaster oven on/off knob was missing; remote controls on bedroom TVs didn't work (discovered 2 could be turned on at the device on last morning); the front lights in sw bedroom didn't work (had to climb riser to turn on the rear set); the shower head in upstairs hall bathroom aimed at the wall (bracket was broken), so couldn't be used.  I always leave a tip for housekeepers -- they have the worst job -- but didn't this time because a basic review would have solved most of these problems. If they had turned the AC on before our arrival on a hot day, they would have known it didnt work.  A great apartment made very unpleasant by neglect of little things.\",\n",
       " 'Hermina in Dorchester ist eine nette Gastgeberin, die wir, da wir selber nur kurz dort waren, nur einmal gesehen hatten. Die Unterkunft ist ist preisleistungsmäßig entsprechend. Das Badezimmer ist mit einem anderen Apartement zu teilen. Die Nachbarschaft ist ruhig. Es gibt eine nette kleine Terrasse hinter dem Haus, der Parkplatz bei Hermina ist kostenlos und die Subway direkt in der Nähe, was den Anschluss an Boston gut ermöglicht, da in Dorchster nicht so viel zu erleben ist. Bis 1Uhr nachts kommt man damit zurück nach Dorchster.',\n",
       " 'Check-in war sehr unkompliziert da der Code für die Tür vorab per Email geschickt wurde. Das Zimmer war sehr groß, hatte ein Waschbecken und das Bad immer sauber. Von den anderen Mitbewohnern haben wir nicht viel mitbekommen. Die Ubahn ist in 5 Minuten zu Fuß zu erreichen und auf dem Weg sind Restaurants und ein Supermarkt.\\nVielen Dank für die schöne Unterkunft! 5Sterne für die Gastgeberin!',\n",
       " \"our FIRST use of Airbnb. When we arrived Hermina wasn't there and another guest opened the door for us. when I called her she told me that our room is in the basement and told me where I can find the key. But I couldn't find it because previous guests hadn't leaved yet!! After they left we went to the room, it was messy and DIRTY. WE had to changed the bed sheets ourselves! We didn't expect it at all! The bathroom was so DIRTY, the trashcan was full and the carpet was wet and gross  and smelled awful!\\r\\nthe advantages of this house was that it is so near to the RED line subway station. \\r\\nAll in all, it was my LAST use of Airnbb!\\r\\n\",\n",
       " 'Zwei Freunde  und ich schliefen dort für eine Nacht. Es war alles ordentlich und gemütlich eingrrichtet. Auch das Badezimmer war in einem guten Zustand. Hermina antwortete jedesmal sehr schnell und gab uns genaue Angaben,  wo wir alles finden können.  Außerdem  ist ihr aus  sehr nah zu einer Bahnhaltestelle- max. 10min. \\r\\nIch würde bei ihr immer wieder eine Unterkunft nehmen.']"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(boston_reviews[boston_reviews.polarity < -0.8].comments.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[\"Greatly enjoyed our quick stay here. We booked the same day or the day before and they happened to have the room available and check in and everything was a breeze. They do have a couple other rooms that had other airbnber's occupying it at the time and the room next door to us was occupied by a family member. The room is very roomy and plenty of space as well as the restroom. The location is kind of on a busy street and you do get the noise if you choose to leave your window open but that didn't seem to be much of a problem for us. The view at sunrise is to die for and I suggest waking up even if just to go back to sleep to see it!\",\n",
       " 'Had basic amenities. Maddy answered our concerns right away.  The bus stop is right across the street to get to downtown.  Unfortunately, there is no central air and we were there when it was quite hot so it was uncomfortable.  The area was a bit sketchy.',\n",
       " 'Wallingford war uns sofort sympathisch. Alle Gärten und Häuser sind liebevoll gestaltet und wirken einladend. Für die heißen Sommertemperaturen war Joyces down house perfekt. Wir waren drei Generationen und fünf Personen ( (Phone number hidden by Airbnb) und 72 Jahre). Joyce hat uns sehr herzlich empfangen und uns mit den perfekten Tipps für unseren Aufenthalt versorgt. Danke an Joyce. Wir würden sofort wiederkommen. ',\n",
       " 'First of all, what a great location!  Close to everything in Fremont and Wallingford.  Gasworks park is a short walk away and we loved it.  The basement apt was well equipped and had everything we needed The price was also fantastic.\\r\\n\\r\\nWe\\'re only giving this a 3 star rating because of a few negatives.  First, being a basement apt you could hear every move of the tenants upstairs.  Joyce (owner) was very quiet but when there were other renters above us the noise was a bit too much.  Second, upon arrival the apt was dirty.  Not Joyce\\'s fault, but it appeared their cleaners did a very poor job and it was not checked/inspected before we arrived.  Lastly, a few days before our arrival the host contacted us and requested to \"rent back\" the unit for one weekend of our 3 week stay because of family emergency.  Our only options were to vacate the apt or have our entire reservation cancelled (which would have left us with no where to stay and very little options given how busy Seattle summer season is).  It all worked out, but this was unwanted stress, not an ideal situation, and not something I\\'d expect to happen if you are running a \"business\" of renting your home and apt.\\r\\n\\r\\nI would think this would be perfect for a quick weekend getaway, but for a longer stay like our (3+ weeks) I\\'d suggest looking elsewhere. ',\n",
       " 'Wir waren 12 Tage bei Bob und ,wurden sehr herzlich aufgenommen.\\r\\nEs war alles so wie beschrieben.Der Garten ist eine Oase der Ruhe,\\r\\nund man konnte den Wirlpool benutzen oder einfach nur entspannen\\r\\nDass wir das Bad teilen mussten war auch kein Problem.Die Katzen genossen ihre Streicheleinheiten,und wenn unsere Zimmertür offen war ,schwupps,lagen sie im Bett! (wenn nicht,kratzten sie an der Tür ),Bob ist ein ausergewöhlicher hilfsbereiter und lieber Gastgeber.Ich habe ihm so gerne zugehört wenn er auf  seinem  Klavier spielte oder singend das Geschirr spülte.Dieses Haus lebt und hat eine positive Energie.Leider spreche ich nur ein wenig Englisch,und doch klappte die Verständigung weil Bob sich sehr große Mühe gab.\\r\\nBob ,wenn es wirklich klappt dass wir uns sehen wenn du in Italien bist werde ich bis dahin mein Englisch aufbessern!!!! \\r\\nDanke für alles, Es war  schön dich kennenzulernen.\\r\\n\\r\\n.\\r\\nLiebe Grüße auch von Franziska\\r\\nUlrike']"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(seattle_reviews[seattle_reviews.polarity < -0.8].comments.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, in addition to misclassified reviews in German, are some reviews in English with different (positive, negative or neutral) polarity that can also be interpreted as the model misinterpretation.\n",
    "\n",
    "Finally, let us investigate the most positive reviews:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[\"Mekkin (pronounced McKeen) met me somewhat late in the evening. Very nice of her to stay up and show me around. The room was great, very comfortable bed, and was really impressed with what they are doing inside. (They have an old 3 story Victorian style home they are renovating. The bathrooms, kitchen, and some of the bedrooms have been redone and are beautiful, and the rest are sure to follow. Don't be fooled by the outside appearance of the house. The inside of the house is great, and only getting better!) Her husband, Rashiek (sp?)  is a great guy! Really friendly, and helpful with suggestions with transit  questions, places to eat, or things to do. (He is kind of the social one, and Mekkin is very nice, but she stays to herself a bit more.) They have a dog that looks imposing, but is a SWEETHEART, once she smells you, once you get introduced to her. (yeah, she is REALLY imposing the way she rolls on her back and wants you to rub her tummy :-)\\r\\n\\r\\nI was visiting my daughter, who is attending Northeastern. This place is perfectly located if you have a kid staying at NEU. The walk to Dudley bus station is 5 minutes, if that. The ride to Ruggles Station is 5 minutes, max. Super easy. Super quick. Super cheap.\\r\\n\\r\\nSo the house is great, they are great, the dog is great, everything is cool, and/but I want to tell you about the neighborhood, just so you're clear about what to expect. \\r\\n\\r\\nThe neighborhood used to be pretty rough, from what I was told, but has definitely turned the corner. It is a black neighborhood, and I am white, and I felt totally comfortable. I walked to and from the bus stop, and the bus station many times, and was totally comfortable. But you need to make that decision based on your own comfort level. The house is about 4 blocks from the Dudley Bus terminal, and is an easy walk in both directions, even though you are coming back up a small hill on your way back from the station or the bus stop.  (There is a phenomenal sub sandwich place called Joe's just a couple of short blocks away. They have great coffee, too.) I walked at all hours, and was fine, but if I was a single woman, I'd probably feel more comfortable taking a taxi or Uber after 9, but that's just my opinion.\\r\\n\\r\\nIn closing, if you want to stay in a nice home, with very nice down to earth, hard working people, then by all means, stay here. If you do not need to have places to walk to for entertainment, or things like that, then stay here. It is well priced, comfortable, safe, clean, and welcoming. \\r\\n\\r\\n\\r\\n\",\n",
       " \"We had a wonderful time in Boston staying in Jason's beautiful apartment. We spent a week there at the end of October/beginning of November 2015.  \\r\\n\\r\\nThe apartment is on the third floor of a lovely old brick building and is immaculately clean and well equipped with everything we could possibly need. The décor is tasteful and the rooms are light and airy but still cosy. We certainly slept soundly in the large, comfortable bed and the bathroom has a great shower. The kitchen area is well equipped with modern appliances, plenty of crockery, cutlery and glassware so we had everything we needed. There is a washing machine and tumble drier downstairs on the ground floor so we were able to do some laundry. You need $1.50 in quarters for each and there is laundry detergent supplied for you. The living room area has a large comfortable sofa with lots of TV channels so we were happy to stay home some evenings. There are also books, board games and fast reliable WiFi access provided. \\r\\n\\r\\nThe location is excellent in a quiet, leafy, residential street but with shops and bars just a few steps away. The Boston T train is about five minutes walk away so you can travel quickly and easily to wherever you want to go. There is a corner shop where you can pick up supplies and on the other corner is a little bar down some steps that serves great beer and food - the mac and cheese is delicious! There are bigger shops, bars, parks and museums nearby which you can easily walk to or take the T. \\r\\n\\r\\nJason was the perfect host. His communication with us before and during our stay was superb. We had a rental car and he sorted out parking for us - always tricky in Boston. He was incredibly friendly and was on hand to offer advice on everything from sight seeing ideas to great places to eat. Nothing was too much trouble; he made sure we had everything we needed but at the same time he left us to enjoy our holiday as we wanted. It was the perfect balance of being welcoming and super helpful while being non-intrusive and laid back. \\r\\n\\r\\nI don't think there's anything Jason could've done better. Being on the third floor the apartment is up several flights of stairs. This wasn't a problem for us but if you have mobility problems, this might be an issue. Aside from that we found everything about the apartment wonderful; a relaxing haven to return to after a long day sight-seeing and the perfect base to see and do everything we wanted to and more. Maybe for English guests who like drinking tea the addition of an electric 'tea kettle' would've been good but there is a great coffee maker so we didn't mind at all. \\r\\n\\r\\nWe absolutely loved our time in this apartment and would come back in a heartbeat! Thanks so much to Jason for everything! \",\n",
       " 'I will try my best to capture in words the absolutely amazing experience my husband and I had.  We feel so lucky to have stayed in Julie\\'s Treetop Haven, which lives up to its name with the nature we experienced right outside the windows!\\r\\n\\r\\nJulie was so kind and very easy to communicate with.  She quickly responded to all my messages and even checked to make sure all was well during our stay.  Julie went above and beyond to make our stay magical.  We were in town for our sister-in-law\\'s wedding and we were also celebrating our 14th anniversary.  Julie left us a gorgeous handmade flower arrangement, a sweet card, delicious chocolates, wine, and little snacks.  She also gave us amazing coffee from her Keurig and even asked what kind of creamer I like, leaving organic nondairy creamer to accommodate my lactose intolerance.  So amazingly kind!  \\r\\n\\r\\nAs far a location is concerned, Julie\\'s home is in a super safe neighborhood where we felt comfortable walking around at night.  It\\'s a 5 minute walk to a gorgeous arboretum, a 10 minute walk to the  Green St. T station (it\\'s about a 20 minute ride into downtown Boston), and a 10 minute walk to all the downtown JP goodness.  We loved spending time in JP with all the great places to eat.  Our favorites were Fiore\\'s for breakfast, City Feed and Supply for groceries and lunch, and JP Licks for dessert.  Everything you need is walking distance in town, from a dry cleaners to drug store to a grocery store.  There is a great farmer\\'s market on Thursday afternoon.  The JP Pond is also worth a visit.  I would love to live in JP! \\r\\n\\r\\nJulie\\'s home is clean and comfortable, with beautiful artifacts from all her world travels.  I loved coming \"home\" from our daily adventures.  The air conditioning works very well, the claw foot bathtub is to die for, and the bed is extremely comfortable!  We appreciated the awesome closet unit in the bedroom, with tons of drawer space and room to hang our nice clothes.  Julie\\'s relaxation room is heaven and there is so much beautiful natural light in every room.  You will love the tree in the front yard.  In the mornings, I took my coffee to the living room windows and just watched all the squirrels and birds frolic and eat.  Being on the second floor was perfect for observing the nature.   \\r\\n\\r\\nWhen I\\'m back in Boston, I will definitely stay at Julie\\'s Treetop Haven!  \\r\\n\\r\\n\\r\\n\\r\\n\\r\\n\\r\\n',\n",
       " 'Perfectly wonderful and welcoming is the best way to describe Nicholas’s beautiful home. This flat is also in an incredible location...a stone’s throw away from Newbury and Boylston Streets along with amazing restaurants and shops. Additionally, it is so close to all of the awesome sites and attractions that beautiful Boston has to offer. This home is so charming, spotlessly clean and unbelievably roomy. There are three very large bedrooms which are all cozy and very comfortable and the main bedroom is adorned with a beautiful fireplace. There is an amazing and very large kitchen, a centrally located full bathroom which had a very nice, hot shower, and a cozy and relaxing parlor with Apple TV. It is  just gorgeous, really! Nicholas’s place had all of the conveniences needed to make our stay perfect~and I do mean ALL of the amenities needed. There is a washer and dryer on the lower level and a charming outdoor patio with a wonderful sitting area which looks like something out of Tuscany. The full kitchen is very modern and the delicious coffee, bagels and cream cheese, water, and snacks were so graciously left for us to enjoy. The dining area is roomy and inviting. This flat is truly special! And Nicholas and John are the best!!! They are courteous, informative, professional, and were very easy to reach for any questions that we had. Honestly, they are extremely considerate and thoughtful. The communication before, during, and after our stay was stellar. We came into Boston for our daughter’s parent’s weekend at Boston College, which again, was very readily accessible as are all of the universities in Boston. That said, Back Bay is a happening place, with Newbury and Boylston Streets just around the corner allowing access to all of the delightful restaurants and marvelous shops that your heart should desire. We also walked The Freedom Trail, across to the Charles River and also made our way to Fenway Park for Thursday’s Red-Sox game, which was oh so fun! We ventured to the North End for delicious Italian and of course, to Modern Pastry, which is absolutely our favorite for cannoli. We also made our way to Faneuil Hall and Quincy Market, Copley and the Prudential. Parking is available along with a parking pass. However, there is easy access to everywhere in this very special and historic city and though we did not have a need for the use of the\" T\"~ it is merely steps away! We will ABSOLUTELY be contacting Nicholas and John for our future visits to Boston College and to this this most spectacular and amazing city! This place is excellent and made our stay most enjoyable and perfect!']"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(boston_reviews[boston_reviews.polarity > 0.9993].comments)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Awesome location about a mile from downtown Ballard with tons of cute places to visit.  I did brewery and distillery tours and lots of gift shopping for the holidays.  Lara also lent me a great bike that got me super easily over to the Fremont area as well, where there is more of the same- great restaurants etc.  The bike trail (Burke-Gilman) is just at the bottom of the hill from the house which is in a very nice quiet neighborhood.  I did not ride super far on the trail, but apparently it is quite long and will take you to tons of great Seattle spots!  \\r\\n\\r\\nThe room itself is more than a room- has its own bathroom, kitchenette and everything I would need if I wanted a totally private stay.  Pretty much the entire downstairs to the whole house is all yours.  Very clean and comfortable with a fun tiki theme.  It was raining when I was up there and somewhat cold, but I was plenty warm and cozy in the space and Lara left out extra blankets just in case.  As it was wet outside, I did not utilize the patio, but nice area with a little fire pit and plenty of seating that would be great for use during better weather.  Would be an awesome reading spot with all of the passion fruit vines in bloom!    \\r\\n\\r\\nMore on the host: As I mentioned before, I could have had a completely private and solitary stay if desired, but Lara was super helpful and sweet.  When getting all the bike stuff from her she was also great about giving directions and suggestions which were all perfect for what I was looking for.  We actually walked to a little happy hour spot for some evening snacks and had a great visit.  Awesome lady who has travelled a lot, as have I, with tons of great stories.  Very friendly and genuine, but also perfectly respectful of \"my\" space downstairs.  \\r\\n\\r\\nOverall:  would highly recommend this place!  Amazing location, super digs that are clean and comfortable and private as well as my favorite airbnb hosts so far!  And of course the icing on the cake: the bicycle borrowing availability!...and the easy access to trails and local spots via bike- or walking for that matter- major bonus in my travel preferences.  Would definitely stay at Lara\\'s again and will most likely try to book again soon when I\\'m up there checking out grad school at UW!  \\r\\n\\r\\nOh yeah- forgot to mention, she has the cutest little puppy!  A bit shy at first, but once she warms up, she is the biggest sweetheart with the funkiest hair do ever;)  Love love love!  \\r\\n\\r\\n ',\n",
       " \"Roy is by far the BEST host you could possibly hope for!!! Not only a great host, but just an all around GREAT person! Roy told me the cheapest way to get to his place and greeted me with open arms and much enthusiasm. He took his time explaining the ins and outs of the building, all the cool spots to eat/drink/sightsee around town, where the grocery store was if I needed anything and he showed me all around the apartment explaining everything. \\r\\n\\r\\nThe apartment is located in a super high end amazing apartment building which is only accessible with a key. Roy's apartment is clean and decorated with amazing pieces he has collected. He has Apple TV, Wifi, a washer/dryer and he even had the fridge stocked with some beer! :) The patio is super cute with a gorgeous view. It is a clean, quiet and beautiful neighborhood, which is walking distance to all the cool local spots you want to see! For me, Capitol Hill is where I wanted to bar hop and visit all the historic bars. From Linda's Tavern to The Unicorn, Capitol Hill has all the entertainment nightlife you could possibly ask for. I also stumbled upon Neumos and Chop Suey walking home two different nights and caught some awesome shows for free! Something always going on in every corner and very busy with people roaming the streets, however, quiet once you get closer to the buildings where Roy's apartment is. The people just made me so happy! Everyone is always having a great time! I made so many friends and had a smile from ear to ear every day! I love the love the district represents and felt proud to stay in Capitol Hill for just a few days. The rainbow crosswalks were the first thing I noticed and I instantly fell in love with Seattle! This is by far the perfect neighborhood to stay! You can easily get downtown to do the touristy things during the day, but at night, Capitol hill is definitely where you want to be. In my opinion, being where the locals are is the most fun I ever have on trips. \\r\\n\\r\\nI honestly can't say enough good things about Roy. He was always available to reach if I ever needed anything. He welcomed me with such high spirits and made me laugh so much; it was such an amazing welcome to my very first trip to Seattle! I felt like we were already friends! He took his time and gave me so many recommendations on places to go. He is hilarious, sweet, friendly, knowledgeable and just a great, great person. Roy is probably my most favorite person I have ever met! haha It definitely won't be my last visit to Seattle and I will definitely be back to rent out any of Roy's available properties in the future!! I highly recommend Roy's place, you will not be disappointed!\\r\\n\\r\\nI love Seattle and can't wait to come back! \",\n",
       " 'He gave us detailed instructions and was a welcoming and friendly host. The porch is beautiful and the place is perfect for anyone looking to visit Seattle in a central location that is easily accessible to all attractions.  One can find easy transportation to get to most major areas in the great Seattle area. Inside the unit, there were several helpful books. A great place to stay! Highly recommend. \\r\\n\\r\\nHe gave us detailed instructions and was a welcoming and friendly host. The porch is beautiful and the place is perfect for anyone looking to visit Seattle in a central location that is easily accessible to all attractions.  One can find easy transportation to get to most major areas in the great Seattle area. Inside the unit, there were several helpful books.\\r\\nHe gave us detailed instructions and was a welcoming and friendly host. The porch is beautiful and the place is perfect for anyone looking to visit Seattle in a central location that is easily accessible to all attractions.  One can find easy transportation to get to most major areas in the great Seattle area. Inside the unit, there were several helpful (Website hidden by Airbnb) gave us detailed instructions and was a welcoming and friendly host. The porch is beautiful and the place is perfect for anyone looking to visit Seattle in a central location that is easily accessible to all attractions.  One can find easy transportation to get to most major areas in the great Seattle area. Inside the unit, there were several helpful (Website hidden by Airbnb) gave us detailed instructions and was a welcoming and friendly host. The porch is beautiful and the place is perfect for anyone looking to visit Seattle in a central location that is easily accessible to all attractions.  One can find easy transportation to get to most major areas in the great Seattle area. Inside the unit, there were several helpful (Website hidden by Airbnb) gave us detailed instructions and was a welcoming and friendly host. The porch is beautiful and the place is perfect for anyone looking to visit Seattle in a central location that is easily accessible to all attractions.  One can find easy transportation to get to most major areas in the great Seattle area. Inside the unit, there were several helpful (Website hidden by Airbnb) gave us detailed instructions and was a welcoming and friendly host. The porch is beautiful and the place is perfect for anyone looking to visit Seattle in a central location that is easily accessible to all attractions.  One can find easy transportation to get to most major areas in the great Seattle area. Inside the unit, there were several helpful (Website hidden by Airbnb) gave us detailed instructions and was a welcoming and friendly host. The porch is beautiful and the place is perfect for anyone looking to visit Seattle in a central location that is easily accessible to all attractions.  One can find easy transportation to get to most major areas in the great Seattle area. Tthere were several helpful books. A great place to stay!']"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(seattle_reviews[seattle_reviews.polarity > 0.9996].comments)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Everything was very good. According to discription and very friendly host. Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good!Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good!Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good!Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good! Very good!...',\n",
       " \"This apartment was so great! I had my share of mediocre flats in AirBNB, but this one is a gem - super clean, super comfortable, super central, and the host is also... well... super :) Details: we were a group of 4 single ~40 year old friends - and the place suited us perfectly. It would also be perfect for a family of four (maybe even 5), or two (maybe even 3) couples. The place looks exactly like in the photos (even cuter!). Location couldn't be better - 60sec walk from  Georg Brandes Plads Parkmuseerne, 9min walk from Nørreport metro station, several bus lines and 3 beautiful parks just around the corner, as well as supermarkets, shops, cafes - everything you may need. The flat is on the ground floor - you enter the building through a gate leading to a cute inner courtyard which is shared by all the neighbors (who were, BTW, also extremely friendly and welcoming) - this means that the flat is not on the main road and is therefore very quiet. It is SUPER CLEAN and magnificently decorated, with a large dining table, small living room with a comfortable sofa, TV, Netflix etc., a children room with 2 child beds (which were stretched especially for us adults to be longer), and a bedroom with a comfy king size double bed. Our host, Ingi, added another large and comfy floor double mattress. We didn't use the kitchen much (mostly the kettle and espresso machine), but it sure looked very nice. The bathroom was clean and spacious, and everything was just SO comfortable. Outside, on the front, there's a nice table with some chairs, where you can drink coffee or smoke when the weather is nice (and it sure was!). And, finally - Ingi - was such a great host! He was highly responsive, he made a great effort to find an extra mattress and provide as many key sets as he could, was flexible with check in/out times, and gave us advice about the city. His mother-in-law met us to deliver the keys - and she was also adorable. To conclude - Ingi - thanx for a great stay, your place is lovely, and I would definitely stay again!\",\n",
       " \"This place is great! I highly recommend it. The couple is very sweet and had great travel tips for the area. My only regret is that I didn't have time to stay longer. As a solo female traveler I felt very safe here with them and in all of Copenhagen. \\n\\nIt's very easy to get to the location taking the train from the airport to Osterport station. I like that the room is in a residential neighborhood and is quiet (until 8am when churchbells ring, this happens all over Copenhagen). Also, if you rely on (Hidden by Airbnb) maps it's easy to figure out buses and metro stations to get around outside of the main area. \\n\\nThe entire city is walkable from this place. Emilie offered me a bike, if you ride I recommend biking everywhere. I walked (haven't been on a bike since an accident in 2005), but the biking lands are wide and the town is super bike friendly. \\n\\nMy favorite spot is Kastellet, it was calm, walkable, cool. A nice place to read a book or do yoga. The little mermaid was crowded because of the tour buses, so go super super super early if you want a good picture of that. \\n\\nAmalienborg and Frederiks kirke were cool. I did a Canal tour in Nyhavn that i loved. I also toured christiania which was an experience. I loved all the art and murals on the walls. I took Emilie's suggestion to go down by the water, then i walked all around. \\n\\nI wasn't that excited with old town because of all the shops, but i LOVE the parks. The one in front of the rosenborg was nice. The cheesecake is amazing here. \\nI packed a quick dry towel and was excited they gave me a real towel. \\n\\nThe place is very clean and the mattress had a memory foam topper on it which is super comfy.  I slept really well on it. The view is nice from the window. Mostly the location is what really makes this place a great choice. I would definitely stay here again. \\n\\nThe bathroom is a fun experience that reminds me of camping. Each time i was in it i laughed (european things are mini). I loved that it was clean, the water was hot, and the body wash is chemical free and smells nice. You'll get used to the tiny space of it. There are cute little touches like some good hand lotion on the shelf of the room and some books to read. \\n\\nI did a day trip to malmo because it sounded cool and the place i did the canal tour told me about it. They had a good canal tour in malmo too but i would say skip it. I did enjoy going over the bridge. \\n\\nOverall this was a great experience. two or three blocks down is a grocery store if you want to get stuff to make sandwiches. \\n\\nThanks for the great stay.\"]"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(copenhagen_reviews[copenhagen_reviews.polarity > 0.9994].comments)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we see, all top positive reviews are indeed very positive.\n",
    "\n",
    "To summarize **Q1**, publicly available pre-trained [Vader sentiment model based on NLTK](http:https://www.nltk.org/_modules/nltk/sentiment/vader.html) is used to predict the sentiment polarity of recent reviews for Airbnb listings from Boston (MA, USA), Seattle (WA, USA) and Copenhagen (Denmark, EU). The model describes the sentiment polarity of English-written reviews fairly well but does not generalise for other common languages (German, French, Spanish etc.). As expected, the majority (95+% of all reviews) are positively- or neutrally-classified, and the large part of negatively- and neutrally-classified reviews are in fact misclassified positive reviews written in other languages. In addition to that, a subdominant part of neutrally-classified reviews are the typical technical messages due to host cancellation. Interestingly, **the fraction of such technical messages in Copenhagen is quite big, 3.5%, or 4-6 times larger than in Boston and Seattle**. This seems odd and may deserve further detailed investigation."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# **(Q2)** what are the main distinctions of Airbnb superhosts from ordinary hosts?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Frist, we calculate the fraction of superhosts in each city:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "city_index\n",
       "1    0.395308\n",
       "2    0.226783\n",
       "3    0.099771\n",
       "Name: host_is_superhost, dtype: float64"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_listings.groupby('city_index').agg(np.mean)['host_is_superhost']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we see, **Copenhagen (3) has significantly smaller fraction of superhosts than Seattle (1) or Boston (2)**. This **may be related** to one of the results in **Q1** that **Copenhagen has much larger number of review messages containing host apartment cancellations**."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then, we calculate [t-test statistics](https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.ttest_ind.html) in order to understand the significant differences between the results. In our samples, both sample sizes and variances are unequal, so we used [Welsh's t-test](https://en.wikipedia.org/wiki/Welch%27s_t-test).\n",
    "Also, it is important to drop all NaN values when calculating t-test, it is done with [pandas.Series.dropna()](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.dropna.html).\n",
    "\n",
    "Usually, the lower `p-value`, the more significant difference between two datasets. There are different possible thresholds for `p-value` used in literature corresponding to a significant difference bewteen the datasets, e.g. `1%`, `5%` or `10%`. The sign of t-test statistics shows which value is larger in average."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "def superhost_significances(df, threshold = 0.01):\n",
    "    '''\n",
    "    Calculates superhost p-values and sorts them by ascending t-test statistics value\n",
    "    Returns only columns with p-value < threshold\n",
    "\n",
    "    Args:\n",
    "        df (pandas dataframe): dataframe that contains column 'host_is_superhost'\n",
    "        threshold (float, default = 0.01): upper bound for p-value to return\n",
    "        \n",
    "    Returns:\n",
    "        res (pandas series): sorted series of columns with values in tuple\n",
    "        (t-test statistic, p-value), an output of stats.ttest_ind\n",
    "    '''\n",
    "    \n",
    "    df_t = df[df.host_is_superhost == 1]\n",
    "    df_f = df[df.host_is_superhost == 0]\n",
    "    res = pd.Series()\n",
    "    for col in df.columns:\n",
    "        t_test, p_val = stats.ttest_ind(df_t[col].dropna(), df_f[col].dropna(), equal_var = False)\n",
    "        if p_val < threshold:\n",
    "            res[col] = (t_test, p_val)\n",
    "    return res.sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "host_is_superhost                                                       (inf, 0.0)\n",
       "amenities_number                       (31.700115453729484, 9.57580576241241e-205)\n",
       "number_of_reviews                     (28.764069899492302, 2.389779843741284e-168)\n",
       "review_scores_rating                   (26.52043907420906, 4.286790124926522e-146)\n",
       "reviews_per_month                      (25.19407820932703, 9.123270625368777e-134)\n",
       "review_scores_value                   (24.886780755588834, 9.269644288912752e-131)\n",
       "review_scores_accuracy                (23.40677904807568, 1.0616070795675122e-115)\n",
       "review_scores_cleanliness             (23.391680768315425, 3.358553127552447e-116)\n",
       "host_identity_verified                  (18.48926818540581, 1.415127964523318e-74)\n",
       "review_scores_communication            (18.17402436686198, 1.3899599796358734e-71)\n",
       "review_scores_checkin                 (17.546968734851646, 5.5744634783370434e-67)\n",
       "review_scores_location                 (13.560281743406545, 2.301945285420604e-41)\n",
       "host_response_fraction                (13.227004036753213, 2.9076623397325203e-39)\n",
       "host_verification_level               (10.900231630772932, 1.9338922397225815e-27)\n",
       "is_location_exact                      (10.894494491722845, 1.928410741106677e-27)\n",
       "is_Wifi                                (10.277365372934723, 1.346337029895817e-24)\n",
       "availability_90                          (9.37252852936646, 9.179825156057168e-21)\n",
       "host_experience                        (8.784420079927669, 1.9803746291447605e-18)\n",
       "availability_365                        (8.046785210325002, 9.883656959679942e-16)\n",
       "house_rules_no_smoking                 (7.440807970652274, 1.1324434797238533e-13)\n",
       "is_TV                                  (6.054503195570414, 1.4796600068490458e-09)\n",
       "distance_center                         (5.082878974427797, 3.811140904599212e-07)\n",
       "extra_people                             (4.016729423418055, 5.97366749695078e-05)\n",
       "availability_60                        (3.824851327033414, 0.00013190242064489577)\n",
       "host_has_profile_pic                     (2.6473910703239065, 0.00813781232544181)\n",
       "bathrooms                              (-2.7855900557895543, 0.005357627711299222)\n",
       "instant_bookable                        (-3.0217497395033037, 0.00252256716963829)\n",
       "bedrooms                               (-3.126034261620363, 0.0017792047537113415)\n",
       "availability_30                       (-3.3107655088887125, 0.0009346809214558998)\n",
       "require_guest_phone_verification      (-3.3325552487820156, 0.0008647377994592377)\n",
       "require_guest_profile_picture         (-3.9710365301321096, 7.222588795104102e-05)\n",
       "cleaning_fee                         (-6.4339091204537455, 1.3277528313984957e-10)\n",
       "host_response_time                     (-7.94623117045489, 2.2417023385162095e-15)\n",
       "price                                 (-8.231442944416923, 2.1759750968186732e-16)\n",
       "maximum_nights                         (-13.86450382333641, 4.018292118984352e-43)\n",
       "calculated_host_listings_count        (-19.344245738263723, 7.667356432192245e-81)\n",
       "host_listings_count                 (-21.772021587190746, 1.9273405769534435e-100)\n",
       "dtype: object"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "superhost_significances(all_listings[all_listings.city_index == 1]) # Seattle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "host_is_superhost                                                      (inf, 0.0)\n",
       "review_scores_rating                (26.592625979939733, 1.0417234442929131e-144)\n",
       "review_scores_cleanliness             (25.45740315110126, 1.983773871810968e-133)\n",
       "review_scores_accuracy                (24.68942778294737, 3.330439000264772e-126)\n",
       "review_scores_value                   (23.35158490248464, 8.698966252109741e-113)\n",
       "review_scores_communication          (23.244331147866667, 2.350735050152552e-112)\n",
       "number_of_reviews                     (20.608042205246303, 2.985961353695486e-83)\n",
       "review_scores_checkin                  (20.60590533852608, 8.079220728753538e-90)\n",
       "reviews_per_month                    (19.557741148178994, 2.1655228949234753e-77)\n",
       "amenities_number                      (18.22657637259726, 2.8169127040045863e-68)\n",
       "host_response_fraction                 (14.02783064938336, 8.752546749611347e-44)\n",
       "house_rules_no_smoking                  (12.2367235583858, 4.692004068485672e-33)\n",
       "host_identity_verified                (10.25798894860659, 4.4244775464509545e-24)\n",
       "extra_people                          (8.210511805703803, 4.2783851110583447e-16)\n",
       "guests_included                        (8.160873146639329, 6.539289302160259e-16)\n",
       "distance_center                       (7.2216143328182865, 7.447122186334317e-13)\n",
       "host_verification_level               (6.737369064352114, 2.1190568286537702e-11)\n",
       "availability_365                      (6.600652049692321, 5.1431894897597534e-11)\n",
       "is_Wifi                               (6.391331008534758, 1.8271229828384667e-10)\n",
       "house_rules_no_pets                    (4.619181452032921, 4.139281811558569e-06)\n",
       "review_scores_location                 (4.604269669756251, 4.312451022841782e-06)\n",
       "longitude                              (2.6933493130135884, 0.007137375814404762)\n",
       "require_guest_phone_verification     (-3.5942144006712082, 0.0003313236958919145)\n",
       "cleaning_fee                           (-4.976555824957042, 7.11946355423952e-07)\n",
       "minimum_nights                        (-5.868184322233486, 5.040293023995771e-09)\n",
       "latitude                             (-6.378380118332551, 2.2961213783092987e-10)\n",
       "room_type                            (-6.466072854712457, 1.2576932671137097e-10)\n",
       "availability_60                      (-6.681188100594705, 2.8498728301902817e-11)\n",
       "price                                (-10.141977213152831, 8.068441786351913e-24)\n",
       "availability_30                       (-11.60009416779571, 1.695776849667236e-30)\n",
       "maximum_nights                       (-12.366910434966083, 8.232157499690455e-34)\n",
       "host_response_time                   (-14.063282810953458, 1.096762370831679e-43)\n",
       "host_listings_count                 (-28.40973076484683, 1.7973968914294405e-162)\n",
       "calculated_host_listings_count       (-28.80519025830252, 3.022824667692792e-167)\n",
       "lat_center                                              (-64.51356446515724, 0.0)\n",
       "dtype: object"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "superhost_significances(all_listings[all_listings.city_index == 2]) # Boston"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "host_is_superhost                                                    (inf, 0.0)\n",
       "number_of_reviews                  (33.240198549296856, 3.266915089694422e-200)\n",
       "review_scores_rating              (33.177248410783065, 1.3149581306488886e-226)\n",
       "review_scores_accuracy             (33.12243350273923, 2.5609526810787566e-224)\n",
       "review_scores_cleanliness          (29.84199543958598, 1.8650635113521827e-180)\n",
       "reviews_per_month                 (28.239883454854795, 1.1449153958122792e-153)\n",
       "review_scores_communication        (27.69810014467264, 2.0622744577899896e-163)\n",
       "review_scores_checkin              (25.512153377697473, 6.395713270945861e-138)\n",
       "amenities_number                  (24.454460424432902, 1.7496532880031637e-119)\n",
       "host_response_fraction             (23.04775829969133, 1.4158600398860478e-113)\n",
       "lat_center                         (21.514424859813648, 1.1547634960183334e-96)\n",
       "review_scores_value                (18.631952806283252, 2.7016415357311192e-74)\n",
       "host_verification_level              (17.75328276863404, 4.583738508881972e-67)\n",
       "host_identity_verified             (15.599127328919879, 1.0578948552698114e-52)\n",
       "review_scores_location             (12.344378743231799, 2.5874695021145425e-34)\n",
       "availability_365                    (12.096743883132214, 7.531274816325573e-33)\n",
       "extra_people                       (10.357103145025269, 1.1136903364299422e-24)\n",
       "availability_90                      (9.593677486834403, 1.800732085445077e-21)\n",
       "host_experience                      (9.24252255823514, 4.5613686610090036e-20)\n",
       "is_Wifi                              (9.182325766728603, 6.746235525806301e-20)\n",
       "availability_60                     (8.001092958975935, 1.7742377203089696e-15)\n",
       "guests_included                     (7.2305144649498425, 6.180469117364907e-13)\n",
       "house_rules_no_smoking               (6.074020167955049, 1.422288836442442e-09)\n",
       "availability_30                     (5.299189977148938, 1.2498734971354183e-07)\n",
       "longitude                           (3.789306827354939, 0.00015413660979060587)\n",
       "is_location_exact                     (2.595351942075896, 0.009497325913771079)\n",
       "is_TV                               (-3.3689987650643487, 0.000764550929302983)\n",
       "latitude                           (-3.8995433416262344, 9.854893912626135e-05)\n",
       "beds                               (-5.0187134936361835, 5.511581055056826e-07)\n",
       "cleaning_fee                        (-6.191113291497002, 6.913040818355774e-10)\n",
       "minimum_nights                      (-7.395834571521629, 1.794823723628597e-13)\n",
       "accommodates                        (-7.551616583862305, 5.721844154067494e-14)\n",
       "bedrooms                           (-7.552812147458543, 5.5973917843411194e-14)\n",
       "distance_center                      (-7.599033191815512, 4.02343951860899e-14)\n",
       "maximum_nights                      (-8.775549634109028, 2.875093789963578e-18)\n",
       "room_type                         (-11.643459640403744, 1.3262707572943136e-30)\n",
       "host_response_time                   (-13.41343354337226, 5.83321165369482e-40)\n",
       "host_listings_count                (-14.806303796520938, 2.245531603844547e-49)\n",
       "calculated_host_listings_count    (-15.915088604042474, 1.0651569664689465e-56)\n",
       "dtype: object"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "superhost_significances(all_listings[all_listings.city_index == 3]) # Copenhagen"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we see, for all three locations (Boston, Seattle, and Copenhagen), superhosts tend to have larger total and monthly averaged number of reviews (`number_of_reviews` and `reviews_per_month`), review scores (`review_scores_*`) and yearly availability (`availability_365`) are larger for superhosts than for ordinary hosts. On the other hand, the number of minimum nights (`minimum_nights`), host response time (`host_response_time`) and the host listings counts (`host_listings_count`, `calculated_host_listings_count`) are smaller for superhosts than for ordinary hosts. This may reflect the higher popularity of superhosts and their higher level of service, compared to ordinary hosts.\n",
    "\n",
    "Also, there are several notable distinctions between different locations. While for Boston and Seattle the monthly availability (`availability_30`) is smaller for superhosts, for Copenhagen it is significantly higher than for ordinary hosts. Secondly, for Seattle and Copenhagen superhosts afford significantly less `bedrooms` while for Boston the difference is not significant. In Copenhagen, it is also significantly smaller `accomodates` for superhosts while for Boston and Seattle the difference is not significant."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# **(Q3)** what are the main factors that influence Airbnb renting price?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To answer this question, we will model the renting price with [`GradientBoostingRegressor`](http:https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.GradientBoostingRegressor.html) and study [`PermutationImportance`](https://www.kaggle.com/dansbecker/permutation-importance) of every feature. Note that we exclude several features (`longitude`, `latitude`, `cleaning_fee`, `extra_people`, `security_deposit`, `city_index`) from this analysis:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = all_listings.dropna(axis=0, how='any')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(14184, 51)"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Interestingly, for different cities, the distribution of permutation weights is very different!!!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For all three cities combined, the result is as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = data['price']\n",
    "X = data.drop(['price', 'lat_center', 'lon_center', 'longitude', 'latitude', 'city_index'], axis=1) \n",
    "X_train, X_val, y_train, y_val = train_test_split(X, y, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [],
   "source": [
    "# regr = GradientBoostingRegressor(random_state=42)\n",
    "# param_dist = {\"max_depth\": stats.randint(2, 6),\n",
    "#               \"n_estimators\": stats.randint(50, 200),\n",
    "#               \"learning_rate\": Real(10**-1, 10**0, \"log-uniform\", name='learning_rate')} #,\n",
    "# #              \"subsample\": stats.uniform(0.5, 0.5)}\n",
    "\n",
    "# n_iter_search = 50\n",
    "# random_search = RandomizedSearchCV(regr, param_distributions=param_dist,\n",
    "#                                    n_iter=n_iter_search, cv=3, verbose=2)\n",
    "\n",
    "# random_search.fit(X, y)\n",
    "# print(random_search.best_score_, random_search.best_estimator_)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, we tune the parameters of the best `GradientBoostingRegressor` model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.7880908555643148\n",
      "CPU times: user 2.11 s, sys: 0 ns, total: 2.11 s\n",
      "Wall time: 2.12 s\n"
     ]
    }
   ],
   "source": [
    "%%time \n",
    "regr = GradientBoostingRegressor(n_estimators=75, learning_rate=0.31, max_depth=4, subsample=1.0,\n",
    "                                 random_state=42)\n",
    "regr.fit(X_train, y_train)\n",
    "print(r2_score(y_val, regr.predict(X_val)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "R2 score is quite decent (0.788), so we apply this model to calculate `PermutationImportance` of different features:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <style>\n",
       "    table.eli5-weights tr:hover {\n",
       "        filter: brightness(85%);\n",
       "    }\n",
       "</style>\n",
       "\n",
       "\n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "        <table class=\"eli5-weights eli5-feature-importances\" style=\"border-collapse: collapse; border: none; margin-top: 0em; table-layout: auto;\">\n",
       "    <thead>\n",
       "    <tr style=\"border: none;\">\n",
       "        <th style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">Weight</th>\n",
       "        <th style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">Feature</th>\n",
       "    </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 80.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.4784\n",
       "                \n",
       "                    &plusmn; 0.0329\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                cleaning_fee\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 93.74%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0910\n",
       "                \n",
       "                    &plusmn; 0.0040\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                distance_center\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 95.43%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0580\n",
       "                \n",
       "                    &plusmn; 0.0062\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                extra_people\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 95.52%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0565\n",
       "                \n",
       "                    &plusmn; 0.0053\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                security_deposit\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 95.69%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0534\n",
       "                \n",
       "                    &plusmn; 0.0072\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                bedrooms\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 96.96%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0324\n",
       "                \n",
       "                    &plusmn; 0.0063\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                room_type\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 97.45%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0253\n",
       "                \n",
       "                    &plusmn; 0.0032\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_listings_count\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 98.14%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0160\n",
       "                \n",
       "                    &plusmn; 0.0033\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                availability_365\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 98.20%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0154\n",
       "                \n",
       "                    &plusmn; 0.0052\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                availability_60\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 98.22%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0151\n",
       "                \n",
       "                    &plusmn; 0.0021\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                availability_90\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 98.37%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0133\n",
       "                \n",
       "                    &plusmn; 0.0039\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                calculated_host_listings_count\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 98.50%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0118\n",
       "                \n",
       "                    &plusmn; 0.0018\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                beds\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 98.67%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0099\n",
       "                \n",
       "                    &plusmn; 0.0031\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                reviews_per_month\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 98.78%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0088\n",
       "                \n",
       "                    &plusmn; 0.0017\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                accommodates\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0066\n",
       "                \n",
       "                    &plusmn; 0.0016\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                bathrooms\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.29%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0041\n",
       "                \n",
       "                    &plusmn; 0.0011\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                amenities_number\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.31%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0039\n",
       "                \n",
       "                    &plusmn; 0.0013\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                guests_included\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.41%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0031\n",
       "                \n",
       "                    &plusmn; 0.0022\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_experience\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.56%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0021\n",
       "                \n",
       "                    &plusmn; 0.0028\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                number_of_reviews\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.60%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0018\n",
       "                \n",
       "                    &plusmn; 0.0015\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_verification_level\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.66%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0014\n",
       "                \n",
       "                    &plusmn; 0.0017\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                availability_30\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.69%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0012\n",
       "                \n",
       "                    &plusmn; 0.0006\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                minimum_nights\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.70%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0012\n",
       "                \n",
       "                    &plusmn; 0.0006\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                house_rules_no_smoking\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.71%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0011\n",
       "                \n",
       "                    &plusmn; 0.0005\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_identity_verified\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.72%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0011\n",
       "                \n",
       "                    &plusmn; 0.0012\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                review_scores_location\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.75%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0009\n",
       "                \n",
       "                    &plusmn; 0.0005\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                review_scores_accuracy\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.81%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0006\n",
       "                \n",
       "                    &plusmn; 0.0008\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                instant_bookable\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.84%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0005\n",
       "                \n",
       "                    &plusmn; 0.0012\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_response_fraction\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.85%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0005\n",
       "                \n",
       "                    &plusmn; 0.0008\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                is_TV\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.88%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0003\n",
       "                \n",
       "                    &plusmn; 0.0012\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                review_scores_value\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.91%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0002\n",
       "                \n",
       "                    &plusmn; 0.0002\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_is_superhost\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.91%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0002\n",
       "                \n",
       "                    &plusmn; 0.0005\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                review_scores_communication\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.94%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0001\n",
       "                \n",
       "                    &plusmn; 0.0003\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                review_scores_cleanliness\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0001\n",
       "                \n",
       "                    &plusmn; 0.0002\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                is_location_exact\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0000\n",
       "                \n",
       "                    &plusmn; 0.0000\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                review_scores_checkin\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0000\n",
       "                \n",
       "                    &plusmn; 0.0000\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                is_Wifi\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 100.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0\n",
       "                \n",
       "                    &plusmn; 0.0000\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_has_profile_pic\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 100.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0\n",
       "                \n",
       "                    &plusmn; 0.0000\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                require_guest_profile_picture\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 100.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0\n",
       "                \n",
       "                    &plusmn; 0.0000\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                requires_license\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 100.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0\n",
       "                \n",
       "                    &plusmn; 0.0000\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                has_availability\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 99.93%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0001\n",
       "                \n",
       "                    &plusmn; 0.0009\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                maximum_nights\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 99.93%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0002\n",
       "                \n",
       "                    &plusmn; 0.0001\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                require_guest_phone_verification\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 99.91%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0002\n",
       "                \n",
       "                    &plusmn; 0.0004\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_response_time\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 99.87%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0003\n",
       "                \n",
       "                    &plusmn; 0.0005\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                house_rules_no_pets\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 99.77%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0008\n",
       "                \n",
       "                    &plusmn; 0.0020\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                review_scores_rating\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "    \n",
       "    </tbody>\n",
       "</table>\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "perm = PermutationImportance(regr, random_state=42).fit(X_val, y_val)\n",
    "eli5.show_weights(perm, top=X.shape[1], feature_names = X.columns.tolist())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Interestingly, `cleaning_fee` appears to be the most important feature. Next-to-largest-important features are `distance_center`, `extra_people`, `security_deposit`, `bedrooms`, as expected.\n",
    "\n",
    "Let us then compare model predictions for different cities:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [],
   "source": [
    "y1 = data[data.city_index == 1]['price']\n",
    "X1 = data[data.city_index == 1].drop(['price', 'lat_center', 'lon_center', 'longitude', 'latitude'], \n",
    "                                     axis=1)\n",
    "X1_train, X1_val, y1_train, y1_val = train_test_split(X1, y1, random_state=42)\n",
    "\n",
    "y2 = data[data.city_index == 2]['price']\n",
    "X2 = data[data.city_index == 2].drop(['price', 'lat_center', 'lon_center', 'longitude', 'latitude'], \n",
    "                                     axis=1)\n",
    "X2_train, X2_val, y2_train, y2_val = train_test_split(X2, y2, random_state=42)\n",
    "\n",
    "y3 = data[data.city_index == 3]['price']\n",
    "X3 = data[data.city_index == 3].drop(['price', 'lat_center', 'lon_center', 'longitude', 'latitude'], \n",
    "                                     axis=1)\n",
    "X3_train, X3_val, y3_train, y3_val = train_test_split(X3, y3, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.6367146107515768 0.6052438418591303 0.5929277292760825\n",
      "CPU times: user 5.62 s, sys: 28.7 ms, total: 5.65 s\n",
      "Wall time: 5.65 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "regr1 = GradientBoostingRegressor(n_estimators=125, learning_rate=0.30, max_depth=8, random_state=42)\n",
    "regr1.fit(X1_train, y1_train)\n",
    "regr2 = GradientBoostingRegressor(n_estimators=135, learning_rate=0.24, max_depth=5, random_state=42)\n",
    "regr2.fit(X2_train, y2_train)\n",
    "regr3 = GradientBoostingRegressor(n_estimators=100, learning_rate=0.26, max_depth=2, random_state=42)\n",
    "regr3.fit(X3_train, y3_train)\n",
    "print(regr1.score(X1_val, y1_val), regr2.score(X2_val, y2_val), regr3.score(X3_val, y3_val))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <style>\n",
       "    table.eli5-weights tr:hover {\n",
       "        filter: brightness(85%);\n",
       "    }\n",
       "</style>\n",
       "\n",
       "\n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "        <table class=\"eli5-weights eli5-feature-importances\" style=\"border-collapse: collapse; border: none; margin-top: 0em; table-layout: auto;\">\n",
       "    <thead>\n",
       "    <tr style=\"border: none;\">\n",
       "        <th style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">Weight</th>\n",
       "        <th style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">Feature</th>\n",
       "    </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 80.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.1203\n",
       "                \n",
       "                    &plusmn; 0.0353\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                cleaning_fee\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 84.76%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0816\n",
       "                \n",
       "                    &plusmn; 0.0268\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                distance_center\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 85.65%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0749\n",
       "                \n",
       "                    &plusmn; 0.0024\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                bedrooms\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 87.34%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0626\n",
       "                \n",
       "                    &plusmn; 0.0240\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                room_type\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 87.44%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0619\n",
       "                \n",
       "                    &plusmn; 0.0172\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_listings_count\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 87.45%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0618\n",
       "                \n",
       "                    &plusmn; 0.0328\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                accommodates\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 93.11%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0263\n",
       "                \n",
       "                    &plusmn; 0.0057\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                security_deposit\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 93.26%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0254\n",
       "                \n",
       "                    &plusmn; 0.0101\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                availability_30\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 94.38%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0196\n",
       "                \n",
       "                    &plusmn; 0.0126\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                guests_included\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 94.73%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0179\n",
       "                \n",
       "                    &plusmn; 0.0082\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                number_of_reviews\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 95.19%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0157\n",
       "                \n",
       "                    &plusmn; 0.0137\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_verification_level\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 95.65%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0136\n",
       "                \n",
       "                    &plusmn; 0.0132\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                availability_365\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 95.76%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0131\n",
       "                \n",
       "                    &plusmn; 0.0109\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                beds\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 96.12%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0115\n",
       "                \n",
       "                    &plusmn; 0.0059\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                house_rules_no_smoking\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 96.28%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0109\n",
       "                \n",
       "                    &plusmn; 0.0099\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                maximum_nights\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 96.36%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0105\n",
       "                \n",
       "                    &plusmn; 0.0052\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                review_scores_rating\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 96.88%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0084\n",
       "                \n",
       "                    &plusmn; 0.0083\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                availability_90\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 97.33%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0068\n",
       "                \n",
       "                    &plusmn; 0.0037\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_is_superhost\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 98.04%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0044\n",
       "                \n",
       "                    &plusmn; 0.0040\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                review_scores_location\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 98.04%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0044\n",
       "                \n",
       "                    &plusmn; 0.0102\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_experience\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 98.08%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0042\n",
       "                \n",
       "                    &plusmn; 0.0081\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                extra_people\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 98.21%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0038\n",
       "                \n",
       "                    &plusmn; 0.0152\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                amenities_number\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 98.23%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0038\n",
       "                \n",
       "                    &plusmn; 0.0035\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                minimum_nights\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 98.53%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0029\n",
       "                \n",
       "                    &plusmn; 0.0034\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                review_scores_value\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.01%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0016\n",
       "                \n",
       "                    &plusmn; 0.0012\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                is_TV\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.23%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0011\n",
       "                \n",
       "                    &plusmn; 0.0026\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                review_scores_cleanliness\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.60%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0005\n",
       "                \n",
       "                    &plusmn; 0.0023\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                house_rules_no_pets\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.62%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0004\n",
       "                \n",
       "                    &plusmn; 0.0013\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_response_fraction\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.72%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0003\n",
       "                \n",
       "                    &plusmn; 0.0011\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                require_guest_phone_verification\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.91%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0001\n",
       "                \n",
       "                    &plusmn; 0.0006\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                require_guest_profile_picture\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 100.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0\n",
       "                \n",
       "                    &plusmn; 0.0000\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                has_availability\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 100.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0\n",
       "                \n",
       "                    &plusmn; 0.0000\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_has_profile_pic\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 100.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0\n",
       "                \n",
       "                    &plusmn; 0.0000\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                requires_license\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 100.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0\n",
       "                \n",
       "                    &plusmn; 0.0000\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                city_index\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 99.72%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0003\n",
       "                \n",
       "                    &plusmn; 0.0007\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                is_location_exact\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 99.70%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0003\n",
       "                \n",
       "                    &plusmn; 0.0011\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                instant_bookable\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 99.67%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0003\n",
       "                \n",
       "                    &plusmn; 0.0006\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_identity_verified\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 99.64%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0004\n",
       "                \n",
       "                    &plusmn; 0.0004\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                is_Wifi\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 99.60%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0004\n",
       "                \n",
       "                    &plusmn; 0.0006\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                review_scores_accuracy\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 99.33%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0009\n",
       "                \n",
       "                    &plusmn; 0.0111\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                calculated_host_listings_count\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 99.32%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0010\n",
       "                \n",
       "                    &plusmn; 0.0016\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                review_scores_communication\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 98.72%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0024\n",
       "                \n",
       "                    &plusmn; 0.0054\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_response_time\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 98.46%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0031\n",
       "                \n",
       "                    &plusmn; 0.0018\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                review_scores_checkin\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 98.30%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0035\n",
       "                \n",
       "                    &plusmn; 0.0107\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                availability_60\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 95.60%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0138\n",
       "                \n",
       "                    &plusmn; 0.0209\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                reviews_per_month\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 93.04%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0266\n",
       "                \n",
       "                    &plusmn; 0.0155\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                bathrooms\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "    \n",
       "    </tbody>\n",
       "</table>\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "perm1 = PermutationImportance(regr1, random_state=42).fit(X1_val, y1_val)\n",
    "eli5.show_weights(perm1, top=X1.shape[1], feature_names = X1.columns.tolist())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       "    \n",
       "        <table class=\"eli5-weights eli5-feature-importances\" style=\"border-collapse: collapse; border: none; margin-top: 0em; table-layout: auto;\">\n",
       "    <thead>\n",
       "    <tr style=\"border: none;\">\n",
       "        <th style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">Weight</th>\n",
       "        <th style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">Feature</th>\n",
       "    </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 80.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.2675\n",
       "                \n",
       "                    &plusmn; 0.0657\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_listings_count\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 87.16%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.1421\n",
       "                \n",
       "                    &plusmn; 0.0336\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                cleaning_fee\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 89.01%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.1138\n",
       "                \n",
       "                    &plusmn; 0.0478\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                number_of_reviews\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 91.89%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0737\n",
       "                \n",
       "                    &plusmn; 0.0294\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                distance_center\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 92.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0723\n",
       "                \n",
       "                    &plusmn; 0.0566\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                reviews_per_month\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 93.07%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0589\n",
       "                \n",
       "                    &plusmn; 0.0142\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                room_type\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 93.44%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0544\n",
       "                \n",
       "                    &plusmn; 0.0208\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                availability_30\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 94.38%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0436\n",
       "                \n",
       "                    &plusmn; 0.0165\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                bathrooms\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 94.45%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0429\n",
       "                \n",
       "                    &plusmn; 0.0130\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                security_deposit\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 95.02%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0367\n",
       "                \n",
       "                    &plusmn; 0.0111\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                review_scores_rating\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 96.43%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0228\n",
       "                \n",
       "                    &plusmn; 0.0238\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                availability_60\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 96.45%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0226\n",
       "                \n",
       "                    &plusmn; 0.0155\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                guests_included\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 96.53%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0219\n",
       "                \n",
       "                    &plusmn; 0.0189\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                maximum_nights\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 97.59%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0131\n",
       "                \n",
       "                    &plusmn; 0.0064\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                availability_365\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 98.19%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0086\n",
       "                \n",
       "                    &plusmn; 0.0091\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                accommodates\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 98.50%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0066\n",
       "                \n",
       "                    &plusmn; 0.0032\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                extra_people\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 98.51%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0066\n",
       "                \n",
       "                    &plusmn; 0.0038\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_experience\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 98.53%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0064\n",
       "                \n",
       "                    &plusmn; 0.0141\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                minimum_nights\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 98.58%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0061\n",
       "                \n",
       "                    &plusmn; 0.0080\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                bedrooms\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0037\n",
       "                \n",
       "                    &plusmn; 0.0082\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                calculated_host_listings_count\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.02%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0036\n",
       "                \n",
       "                    &plusmn; 0.0036\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_verification_level\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.22%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0026\n",
       "                \n",
       "                    &plusmn; 0.0119\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                review_scores_checkin\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.34%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0020\n",
       "                \n",
       "                    &plusmn; 0.0036\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                review_scores_value\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.53%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0013\n",
       "                \n",
       "                    &plusmn; 0.0026\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                is_TV\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.54%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0012\n",
       "                \n",
       "                    &plusmn; 0.0338\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                amenities_number\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.66%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0008\n",
       "                \n",
       "                    &plusmn; 0.0005\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                house_rules_no_smoking\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.67%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0008\n",
       "                \n",
       "                    &plusmn; 0.0001\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                require_guest_phone_verification\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.68%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0007\n",
       "                \n",
       "                    &plusmn; 0.0025\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_response_fraction\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.73%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0006\n",
       "                \n",
       "                    &plusmn; 0.0008\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                instant_bookable\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.73%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0006\n",
       "                \n",
       "                    &plusmn; 0.0004\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_is_superhost\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.80%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0004\n",
       "                \n",
       "                    &plusmn; 0.0011\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                is_location_exact\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.84%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0003\n",
       "                \n",
       "                    &plusmn; 0.0031\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                beds\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 100.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0\n",
       "                \n",
       "                    &plusmn; 0.0000\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_has_profile_pic\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 100.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0\n",
       "                \n",
       "                    &plusmn; 0.0000\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                requires_license\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 100.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0\n",
       "                \n",
       "                    &plusmn; 0.0000\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                has_availability\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 100.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0\n",
       "                \n",
       "                    &plusmn; 0.0000\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                require_guest_profile_picture\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 100.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0\n",
       "                \n",
       "                    &plusmn; 0.0000\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                city_index\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 99.87%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0002\n",
       "                \n",
       "                    &plusmn; 0.0002\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                is_Wifi\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 99.82%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0003\n",
       "                \n",
       "                    &plusmn; 0.0009\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_response_time\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 99.62%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0009\n",
       "                \n",
       "                    &plusmn; 0.0022\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                house_rules_no_pets\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 99.43%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0017\n",
       "                \n",
       "                    &plusmn; 0.0024\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_identity_verified\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 99.35%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0020\n",
       "                \n",
       "                    &plusmn; 0.0016\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                review_scores_cleanliness\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 98.98%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0038\n",
       "                \n",
       "                    &plusmn; 0.0216\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                availability_90\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 98.94%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0040\n",
       "                \n",
       "                    &plusmn; 0.0028\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                review_scores_accuracy\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 98.70%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0054\n",
       "                \n",
       "                    &plusmn; 0.0036\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                review_scores_location\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 98.19%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0087\n",
       "                \n",
       "                    &plusmn; 0.0079\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                review_scores_communication\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "    \n",
       "    </tbody>\n",
       "</table>\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "perm2 = PermutationImportance(regr2, random_state=42).fit(X2_val, y2_val)\n",
    "eli5.show_weights(perm2, top=X2.shape[1], feature_names = X2.columns.tolist())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <style>\n",
       "    table.eli5-weights tr:hover {\n",
       "        filter: brightness(85%);\n",
       "    }\n",
       "</style>\n",
       "\n",
       "\n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "        <table class=\"eli5-weights eli5-feature-importances\" style=\"border-collapse: collapse; border: none; margin-top: 0em; table-layout: auto;\">\n",
       "    <thead>\n",
       "    <tr style=\"border: none;\">\n",
       "        <th style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">Weight</th>\n",
       "        <th style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">Feature</th>\n",
       "    </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 80.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.1420\n",
       "                \n",
       "                    &plusmn; 0.0220\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                bedrooms\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 82.60%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.1164\n",
       "                \n",
       "                    &plusmn; 0.0109\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                room_type\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 84.18%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.1016\n",
       "                \n",
       "                    &plusmn; 0.0162\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                distance_center\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 91.45%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0422\n",
       "                \n",
       "                    &plusmn; 0.0060\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                accommodates\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 91.96%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0387\n",
       "                \n",
       "                    &plusmn; 0.0122\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                cleaning_fee\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 92.62%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0342\n",
       "                \n",
       "                    &plusmn; 0.0057\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                availability_30\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 94.63%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0217\n",
       "                \n",
       "                    &plusmn; 0.0060\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                extra_people\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 95.48%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0170\n",
       "                \n",
       "                    &plusmn; 0.0029\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                availability_365\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 96.10%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0137\n",
       "                \n",
       "                    &plusmn; 0.0023\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                guests_included\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 96.93%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0097\n",
       "                \n",
       "                    &plusmn; 0.0020\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                review_scores_location\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 97.56%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0070\n",
       "                \n",
       "                    &plusmn; 0.0035\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                bathrooms\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 97.84%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0059\n",
       "                \n",
       "                    &plusmn; 0.0048\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                amenities_number\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 98.05%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0051\n",
       "                \n",
       "                    &plusmn; 0.0038\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                review_scores_rating\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 98.11%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0049\n",
       "                \n",
       "                    &plusmn; 0.0015\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                is_TV\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 98.13%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0048\n",
       "                \n",
       "                    &plusmn; 0.0032\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                reviews_per_month\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 98.98%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0020\n",
       "                \n",
       "                    &plusmn; 0.0013\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                availability_60\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 98.98%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0020\n",
       "                \n",
       "                    &plusmn; 0.0025\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                calculated_host_listings_count\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.05%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0018\n",
       "                \n",
       "                    &plusmn; 0.0034\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                minimum_nights\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.05%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0018\n",
       "                \n",
       "                    &plusmn; 0.0020\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_response_fraction\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.27%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0012\n",
       "                \n",
       "                    &plusmn; 0.0007\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_response_time\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.30%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0012\n",
       "                \n",
       "                    &plusmn; 0.0013\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                security_deposit\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.44%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0009\n",
       "                \n",
       "                    &plusmn; 0.0016\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                review_scores_value\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.47%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0008\n",
       "                \n",
       "                    &plusmn; 0.0015\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                maximum_nights\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.60%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0005\n",
       "                \n",
       "                    &plusmn; 0.0004\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                beds\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.61%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0005\n",
       "                \n",
       "                    &plusmn; 0.0020\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_experience\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.62%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0005\n",
       "                \n",
       "                    &plusmn; 0.0019\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                number_of_reviews\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.70%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0003\n",
       "                \n",
       "                    &plusmn; 0.0005\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                review_scores_accuracy\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.73%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0003\n",
       "                \n",
       "                    &plusmn; 0.0016\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                instant_bookable\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.76%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0003\n",
       "                \n",
       "                    &plusmn; 0.0015\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                review_scores_cleanliness\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.78%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0002\n",
       "                \n",
       "                    &plusmn; 0.0004\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_verification_level\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.79%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0002\n",
       "                \n",
       "                    &plusmn; 0.0019\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_is_superhost\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.80%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0002\n",
       "                \n",
       "                    &plusmn; 0.0009\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                is_location_exact\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 99.80%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0002\n",
       "                \n",
       "                    &plusmn; 0.0005\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                availability_90\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 100.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0\n",
       "                \n",
       "                    &plusmn; 0.0000\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                is_Wifi\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 100.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0\n",
       "                \n",
       "                    &plusmn; 0.0000\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_identity_verified\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 100.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0\n",
       "                \n",
       "                    &plusmn; 0.0000\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_has_profile_pic\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 100.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0\n",
       "                \n",
       "                    &plusmn; 0.0000\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                has_availability\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 100.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0\n",
       "                \n",
       "                    &plusmn; 0.0000\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                house_rules_no_pets\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 100.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0\n",
       "                \n",
       "                    &plusmn; 0.0000\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                requires_license\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 100.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0\n",
       "                \n",
       "                    &plusmn; 0.0000\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                require_guest_profile_picture\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 100.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0\n",
       "                \n",
       "                    &plusmn; 0.0000\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                require_guest_phone_verification\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 100.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0\n",
       "                \n",
       "                    &plusmn; 0.0000\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                city_index\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 99.93%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0000\n",
       "                \n",
       "                    &plusmn; 0.0001\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                review_scores_communication\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 99.90%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0001\n",
       "                \n",
       "                    &plusmn; 0.0013\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                host_listings_count\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 99.80%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0002\n",
       "                \n",
       "                    &plusmn; 0.0004\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                house_rules_no_smoking\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(0, 100.00%, 99.74%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                -0.0003\n",
       "                \n",
       "                    &plusmn; 0.0011\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                review_scores_checkin\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "    \n",
       "    </tbody>\n",
       "</table>\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "perm3 = PermutationImportance(regr3, random_state=42).fit(X3_val, y3_val)\n",
    "eli5.show_weights(perm3, top=X3.shape[1], feature_names = X3.columns.tolist())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we see, there are significant differences between largest influencing features between different cities. For example, `hosting_listings_count` is valuable for US cities (especially for Boston) but is negligible for Copenhagen. On the other hand, `distance_center` and `room_type` are among the most important features for price prediction in every city of our interest, as expected."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# **(Q4)** how well can we predict the Airbnb renting price based on the data from a different city?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To answer this question, I implement manual cross-validation: we will test the model based on data on two cities and validate the model on remaining one. Clearly, `lat_center`, `lon_center`, `longitude`, `latitude` columns should be dropped:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [],
   "source": [
    "y12 = data[data.city_index != 3]['price']\n",
    "X12 = data[data.city_index != 3].drop(['price', 'lat_center', 'lon_center', 'longitude', 'latitude', 'city_index'], \n",
    "                                     axis=1)\n",
    "X12_train, X12_val, y12_train, y12_val = train_test_split(X12, y12, random_state=42)\n",
    "\n",
    "y13 = data[data.city_index != 2]['price']\n",
    "X13 = data[data.city_index != 2].drop(['price', 'lat_center', 'lon_center', 'longitude', 'latitude', 'city_index'], \n",
    "                                     axis=1)\n",
    "X13_train, X13_val, y13_train, y13_val = train_test_split(X13, y13, random_state=42)\n",
    "\n",
    "y23 = data[data.city_index != 1]['price']\n",
    "X23 = data[data.city_index != 1].drop(['price', 'lat_center', 'lon_center', 'longitude', 'latitude', 'city_index'], \n",
    "                                     axis=1)\n",
    "X23_train, X23_val, y23_train, y23_val = train_test_split(X23, y23, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.6967172981430158\n",
      "CPU times: user 11.9 s, sys: 14.4 ms, total: 11.9 s\n",
      "Wall time: 11.9 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "regr12 = GradientBoostingRegressor(n_estimators=120, learning_rate=0.30, max_depth=8, random_state=42)\n",
    "regr12.fit(X12_train, y12_train)\n",
    "regr23 = GradientBoostingRegressor(n_estimators=130, learning_rate=0.26, max_depth=5, random_state=42)\n",
    "regr23.fit(X23_train, y23_train)\n",
    "regr13 = GradientBoostingRegressor(n_estimators=105, learning_rate=0.26, max_depth=4, random_state=42)\n",
    "regr13.fit(X13_train, y13_train)\n",
    "val_scores = [regr13.score(X13_val, y13_val), \n",
    "               regr12.score(X12_val, y12_val), \n",
    "               regr23.score(X23_val, y23_val)]\n",
    "mean_val_score = np.mean(val_scores)\n",
    "print(mean_val_score)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we see, final [`R2 score`](http:https://scikit-learn.org/stable/modules/generated/sklearn.metrics.r2_score.html) is quite good (0.697) for such a simple model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0.7842457216842073, 0.5857315583410769, 0.7201746144037631]"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "val_scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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EUyIXEUk4JXIRkYRTIhcRSTglchGRhFMiFxFJOCVyEZGEUyIXEUk4JXIRkYRT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\ndofFT4XPP2EAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "barlist = plt.bar([3, 1, 2], val_scores, width=0.75, alpha=0.65)\n",
    "barlist[0].set_color('r')\n",
    "barlist[1].set_color('g')\n",
    "barlist[2].set_color('b')\n",
    "plt.plot((0.51, 3.49), (mean_val_score, mean_val_score), 'y--')\n",
    "plt.xticks([3, 1, 2], ('Copenhagen', 'Seattle', 'Boston'))\n",
    "plt.title('Validation R2 scores for daily prices prediction')\n",
    "plt.savefig('validation_scores_prices.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we see, the average validation score (0.697) is somewhat lower than for random validation (0.788) obtained in the previous question. Such a difference may mean that there are some significant local conditions, that should not be omitted by constructing a realistic model. ***It is well expected: our world is still far from being homogeneous.*** On the other hand, the difference may not be significant, given the large variation of validation score among the cities. ***One can even speculate that there is a trend to better describe the cities with smaller “Airbnb experience” for its hosts (e.g., the smaller percentage of superhosts, the larger fraction of host cancellation messages in reviews), which intuitively resembles the historical evidence (e.g., Airbnb was created on the West coast, being then spread over the USA and then over the rest of the globe).*** However, this speculation needs more data to check. Let me leave it for a future analysis :-)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}