Aula_01.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "5PGNQ2pACcmg"
   },
   "source": [
    "# Importando os dados\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 422
    },
    "id": "n4nsCvloshsm",
    "outputId": "30a896a7-9c03-40f3-c50b-765eb40b156a"
   },
   "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>id</th>\n",
       "      <th>tratamento</th>\n",
       "      <th>tempo</th>\n",
       "      <th>dose</th>\n",
       "      <th>droga</th>\n",
       "      <th>g-0</th>\n",
       "      <th>g-1</th>\n",
       "      <th>g-2</th>\n",
       "      <th>g-3</th>\n",
       "      <th>g-4</th>\n",
       "      <th>...</th>\n",
       "      <th>c-90</th>\n",
       "      <th>c-91</th>\n",
       "      <th>c-92</th>\n",
       "      <th>c-93</th>\n",
       "      <th>c-94</th>\n",
       "      <th>c-95</th>\n",
       "      <th>c-96</th>\n",
       "      <th>c-97</th>\n",
       "      <th>c-98</th>\n",
       "      <th>c-99</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>id_000644bb2</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>24</td>\n",
       "      <td>D1</td>\n",
       "      <td>b68db1d53</td>\n",
       "      <td>1.0620</td>\n",
       "      <td>0.5577</td>\n",
       "      <td>-0.2479</td>\n",
       "      <td>-0.6208</td>\n",
       "      <td>-0.1944</td>\n",
       "      <td>...</td>\n",
       "      <td>0.2862</td>\n",
       "      <td>0.2584</td>\n",
       "      <td>0.8076</td>\n",
       "      <td>0.5523</td>\n",
       "      <td>-0.1912</td>\n",
       "      <td>0.6584</td>\n",
       "      <td>-0.3981</td>\n",
       "      <td>0.2139</td>\n",
       "      <td>0.3801</td>\n",
       "      <td>0.4176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>id_000779bfc</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>72</td>\n",
       "      <td>D1</td>\n",
       "      <td>df89a8e5a</td>\n",
       "      <td>0.0743</td>\n",
       "      <td>0.4087</td>\n",
       "      <td>0.2991</td>\n",
       "      <td>0.0604</td>\n",
       "      <td>1.0190</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.4265</td>\n",
       "      <td>0.7543</td>\n",
       "      <td>0.4708</td>\n",
       "      <td>0.0230</td>\n",
       "      <td>0.2957</td>\n",
       "      <td>0.4899</td>\n",
       "      <td>0.1522</td>\n",
       "      <td>0.1241</td>\n",
       "      <td>0.6077</td>\n",
       "      <td>0.7371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>id_000a6266a</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>48</td>\n",
       "      <td>D1</td>\n",
       "      <td>18bb41b2c</td>\n",
       "      <td>0.6280</td>\n",
       "      <td>0.5817</td>\n",
       "      <td>1.5540</td>\n",
       "      <td>-0.0764</td>\n",
       "      <td>-0.0323</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.7250</td>\n",
       "      <td>-0.6297</td>\n",
       "      <td>0.6103</td>\n",
       "      <td>0.0223</td>\n",
       "      <td>-1.3240</td>\n",
       "      <td>-0.3174</td>\n",
       "      <td>-0.6417</td>\n",
       "      <td>-0.2187</td>\n",
       "      <td>-1.4080</td>\n",
       "      <td>0.6931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>id_0015fd391</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>48</td>\n",
       "      <td>D1</td>\n",
       "      <td>8c7f86626</td>\n",
       "      <td>-0.5138</td>\n",
       "      <td>-0.2491</td>\n",
       "      <td>-0.2656</td>\n",
       "      <td>0.5288</td>\n",
       "      <td>4.0620</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.0990</td>\n",
       "      <td>-0.6441</td>\n",
       "      <td>-5.6300</td>\n",
       "      <td>-1.3780</td>\n",
       "      <td>-0.8632</td>\n",
       "      <td>-1.2880</td>\n",
       "      <td>-1.6210</td>\n",
       "      <td>-0.8784</td>\n",
       "      <td>-0.3876</td>\n",
       "      <td>-0.8154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>id_001626bd3</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>72</td>\n",
       "      <td>D2</td>\n",
       "      <td>7cbed3131</td>\n",
       "      <td>-0.3254</td>\n",
       "      <td>-0.4009</td>\n",
       "      <td>0.9700</td>\n",
       "      <td>0.6919</td>\n",
       "      <td>1.4180</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0042</td>\n",
       "      <td>0.0048</td>\n",
       "      <td>0.6670</td>\n",
       "      <td>1.0690</td>\n",
       "      <td>0.5523</td>\n",
       "      <td>-0.3031</td>\n",
       "      <td>0.1094</td>\n",
       "      <td>0.2885</td>\n",
       "      <td>-0.3786</td>\n",
       "      <td>0.7125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23809</th>\n",
       "      <td>id_fffb1ceed</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>24</td>\n",
       "      <td>D2</td>\n",
       "      <td>df1d0a5a1</td>\n",
       "      <td>0.1394</td>\n",
       "      <td>-0.0636</td>\n",
       "      <td>-0.1112</td>\n",
       "      <td>-0.5080</td>\n",
       "      <td>-0.4713</td>\n",
       "      <td>...</td>\n",
       "      <td>0.1969</td>\n",
       "      <td>0.0262</td>\n",
       "      <td>-0.8121</td>\n",
       "      <td>0.3434</td>\n",
       "      <td>0.5372</td>\n",
       "      <td>-0.3246</td>\n",
       "      <td>0.0631</td>\n",
       "      <td>0.9171</td>\n",
       "      <td>0.5258</td>\n",
       "      <td>0.4680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23810</th>\n",
       "      <td>id_fffb70c0c</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>24</td>\n",
       "      <td>D2</td>\n",
       "      <td>ecf3b6b74</td>\n",
       "      <td>-1.3260</td>\n",
       "      <td>0.3478</td>\n",
       "      <td>-0.3743</td>\n",
       "      <td>0.9905</td>\n",
       "      <td>-0.7178</td>\n",
       "      <td>...</td>\n",
       "      <td>0.4286</td>\n",
       "      <td>0.4426</td>\n",
       "      <td>0.0423</td>\n",
       "      <td>-0.3195</td>\n",
       "      <td>-0.8086</td>\n",
       "      <td>-0.9798</td>\n",
       "      <td>-0.2084</td>\n",
       "      <td>-0.1224</td>\n",
       "      <td>-0.2715</td>\n",
       "      <td>0.3689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23811</th>\n",
       "      <td>id_fffc1c3f4</td>\n",
       "      <td>com_controle</td>\n",
       "      <td>48</td>\n",
       "      <td>D2</td>\n",
       "      <td>cacb2b860</td>\n",
       "      <td>0.3942</td>\n",
       "      <td>0.3756</td>\n",
       "      <td>0.3109</td>\n",
       "      <td>-0.7389</td>\n",
       "      <td>0.5505</td>\n",
       "      <td>...</td>\n",
       "      <td>0.5409</td>\n",
       "      <td>0.3755</td>\n",
       "      <td>0.7343</td>\n",
       "      <td>0.2807</td>\n",
       "      <td>0.4116</td>\n",
       "      <td>0.6422</td>\n",
       "      <td>0.2256</td>\n",
       "      <td>0.7592</td>\n",
       "      <td>0.6656</td>\n",
       "      <td>0.3808</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23812</th>\n",
       "      <td>id_fffcb9e7c</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>24</td>\n",
       "      <td>D1</td>\n",
       "      <td>8b87a7a83</td>\n",
       "      <td>0.6660</td>\n",
       "      <td>0.2324</td>\n",
       "      <td>0.4392</td>\n",
       "      <td>0.2044</td>\n",
       "      <td>0.8531</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1105</td>\n",
       "      <td>0.4258</td>\n",
       "      <td>-0.2012</td>\n",
       "      <td>0.1506</td>\n",
       "      <td>1.5230</td>\n",
       "      <td>0.7101</td>\n",
       "      <td>0.1732</td>\n",
       "      <td>0.7015</td>\n",
       "      <td>-0.6290</td>\n",
       "      <td>0.0740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23813</th>\n",
       "      <td>id_ffffdd77b</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>72</td>\n",
       "      <td>D1</td>\n",
       "      <td>972f41291</td>\n",
       "      <td>-0.8598</td>\n",
       "      <td>1.0240</td>\n",
       "      <td>-0.1361</td>\n",
       "      <td>0.7952</td>\n",
       "      <td>-0.3611</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.3890</td>\n",
       "      <td>-1.7450</td>\n",
       "      <td>-6.6300</td>\n",
       "      <td>-4.0950</td>\n",
       "      <td>-7.3860</td>\n",
       "      <td>-1.4160</td>\n",
       "      <td>-3.5770</td>\n",
       "      <td>-0.4775</td>\n",
       "      <td>-2.1500</td>\n",
       "      <td>-4.2520</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>23814 rows × 877 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 id    tratamento  tempo dose      droga     g-0     g-1  \\\n",
       "0      id_000644bb2     com_droga     24   D1  b68db1d53  1.0620  0.5577   \n",
       "1      id_000779bfc     com_droga     72   D1  df89a8e5a  0.0743  0.4087   \n",
       "2      id_000a6266a     com_droga     48   D1  18bb41b2c  0.6280  0.5817   \n",
       "3      id_0015fd391     com_droga     48   D1  8c7f86626 -0.5138 -0.2491   \n",
       "4      id_001626bd3     com_droga     72   D2  7cbed3131 -0.3254 -0.4009   \n",
       "...             ...           ...    ...  ...        ...     ...     ...   \n",
       "23809  id_fffb1ceed     com_droga     24   D2  df1d0a5a1  0.1394 -0.0636   \n",
       "23810  id_fffb70c0c     com_droga     24   D2  ecf3b6b74 -1.3260  0.3478   \n",
       "23811  id_fffc1c3f4  com_controle     48   D2  cacb2b860  0.3942  0.3756   \n",
       "23812  id_fffcb9e7c     com_droga     24   D1  8b87a7a83  0.6660  0.2324   \n",
       "23813  id_ffffdd77b     com_droga     72   D1  972f41291 -0.8598  1.0240   \n",
       "\n",
       "          g-2     g-3     g-4  ...    c-90    c-91    c-92    c-93    c-94  \\\n",
       "0     -0.2479 -0.6208 -0.1944  ...  0.2862  0.2584  0.8076  0.5523 -0.1912   \n",
       "1      0.2991  0.0604  1.0190  ... -0.4265  0.7543  0.4708  0.0230  0.2957   \n",
       "2      1.5540 -0.0764 -0.0323  ... -0.7250 -0.6297  0.6103  0.0223 -1.3240   \n",
       "3     -0.2656  0.5288  4.0620  ... -2.0990 -0.6441 -5.6300 -1.3780 -0.8632   \n",
       "4      0.9700  0.6919  1.4180  ...  0.0042  0.0048  0.6670  1.0690  0.5523   \n",
       "...       ...     ...     ...  ...     ...     ...     ...     ...     ...   \n",
       "23809 -0.1112 -0.5080 -0.4713  ...  0.1969  0.0262 -0.8121  0.3434  0.5372   \n",
       "23810 -0.3743  0.9905 -0.7178  ...  0.4286  0.4426  0.0423 -0.3195 -0.8086   \n",
       "23811  0.3109 -0.7389  0.5505  ...  0.5409  0.3755  0.7343  0.2807  0.4116   \n",
       "23812  0.4392  0.2044  0.8531  ... -0.1105  0.4258 -0.2012  0.1506  1.5230   \n",
       "23813 -0.1361  0.7952 -0.3611  ... -3.3890 -1.7450 -6.6300 -4.0950 -7.3860   \n",
       "\n",
       "         c-95    c-96    c-97    c-98    c-99  \n",
       "0      0.6584 -0.3981  0.2139  0.3801  0.4176  \n",
       "1      0.4899  0.1522  0.1241  0.6077  0.7371  \n",
       "2     -0.3174 -0.6417 -0.2187 -1.4080  0.6931  \n",
       "3     -1.2880 -1.6210 -0.8784 -0.3876 -0.8154  \n",
       "4     -0.3031  0.1094  0.2885 -0.3786  0.7125  \n",
       "...       ...     ...     ...     ...     ...  \n",
       "23809 -0.3246  0.0631  0.9171  0.5258  0.4680  \n",
       "23810 -0.9798 -0.2084 -0.1224 -0.2715  0.3689  \n",
       "23811  0.6422  0.2256  0.7592  0.6656  0.3808  \n",
       "23812  0.7101  0.1732  0.7015 -0.6290  0.0740  \n",
       "23813 -1.4160 -3.5770 -0.4775 -2.1500 -4.2520  \n",
       "\n",
       "[23814 rows x 877 columns]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "url_dados = 'https://github.com/alura-cursos/imersaodados3/blob/main/dados/dados_experimentos.zip?raw=true'\n",
    "\n",
    "dados = pd.read_csv(url_dados, compression = 'zip')\n",
    "dados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 244
    },
    "id": "ongQ8MkFsnWY",
    "outputId": "55731c1e-f7fc-4e41-ae6c-86d40d0a1304"
   },
   "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>id</th>\n",
       "      <th>tratamento</th>\n",
       "      <th>tempo</th>\n",
       "      <th>dose</th>\n",
       "      <th>droga</th>\n",
       "      <th>g-0</th>\n",
       "      <th>g-1</th>\n",
       "      <th>g-2</th>\n",
       "      <th>g-3</th>\n",
       "      <th>g-4</th>\n",
       "      <th>...</th>\n",
       "      <th>c-90</th>\n",
       "      <th>c-91</th>\n",
       "      <th>c-92</th>\n",
       "      <th>c-93</th>\n",
       "      <th>c-94</th>\n",
       "      <th>c-95</th>\n",
       "      <th>c-96</th>\n",
       "      <th>c-97</th>\n",
       "      <th>c-98</th>\n",
       "      <th>c-99</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>id_000644bb2</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>24</td>\n",
       "      <td>D1</td>\n",
       "      <td>b68db1d53</td>\n",
       "      <td>1.0620</td>\n",
       "      <td>0.5577</td>\n",
       "      <td>-0.2479</td>\n",
       "      <td>-0.6208</td>\n",
       "      <td>-0.1944</td>\n",
       "      <td>...</td>\n",
       "      <td>0.2862</td>\n",
       "      <td>0.2584</td>\n",
       "      <td>0.8076</td>\n",
       "      <td>0.5523</td>\n",
       "      <td>-0.1912</td>\n",
       "      <td>0.6584</td>\n",
       "      <td>-0.3981</td>\n",
       "      <td>0.2139</td>\n",
       "      <td>0.3801</td>\n",
       "      <td>0.4176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>id_000779bfc</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>72</td>\n",
       "      <td>D1</td>\n",
       "      <td>df89a8e5a</td>\n",
       "      <td>0.0743</td>\n",
       "      <td>0.4087</td>\n",
       "      <td>0.2991</td>\n",
       "      <td>0.0604</td>\n",
       "      <td>1.0190</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.4265</td>\n",
       "      <td>0.7543</td>\n",
       "      <td>0.4708</td>\n",
       "      <td>0.0230</td>\n",
       "      <td>0.2957</td>\n",
       "      <td>0.4899</td>\n",
       "      <td>0.1522</td>\n",
       "      <td>0.1241</td>\n",
       "      <td>0.6077</td>\n",
       "      <td>0.7371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>id_000a6266a</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>48</td>\n",
       "      <td>D1</td>\n",
       "      <td>18bb41b2c</td>\n",
       "      <td>0.6280</td>\n",
       "      <td>0.5817</td>\n",
       "      <td>1.5540</td>\n",
       "      <td>-0.0764</td>\n",
       "      <td>-0.0323</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.7250</td>\n",
       "      <td>-0.6297</td>\n",
       "      <td>0.6103</td>\n",
       "      <td>0.0223</td>\n",
       "      <td>-1.3240</td>\n",
       "      <td>-0.3174</td>\n",
       "      <td>-0.6417</td>\n",
       "      <td>-0.2187</td>\n",
       "      <td>-1.4080</td>\n",
       "      <td>0.6931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>id_0015fd391</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>48</td>\n",
       "      <td>D1</td>\n",
       "      <td>8c7f86626</td>\n",
       "      <td>-0.5138</td>\n",
       "      <td>-0.2491</td>\n",
       "      <td>-0.2656</td>\n",
       "      <td>0.5288</td>\n",
       "      <td>4.0620</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.0990</td>\n",
       "      <td>-0.6441</td>\n",
       "      <td>-5.6300</td>\n",
       "      <td>-1.3780</td>\n",
       "      <td>-0.8632</td>\n",
       "      <td>-1.2880</td>\n",
       "      <td>-1.6210</td>\n",
       "      <td>-0.8784</td>\n",
       "      <td>-0.3876</td>\n",
       "      <td>-0.8154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>id_001626bd3</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>72</td>\n",
       "      <td>D2</td>\n",
       "      <td>7cbed3131</td>\n",
       "      <td>-0.3254</td>\n",
       "      <td>-0.4009</td>\n",
       "      <td>0.9700</td>\n",
       "      <td>0.6919</td>\n",
       "      <td>1.4180</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0042</td>\n",
       "      <td>0.0048</td>\n",
       "      <td>0.6670</td>\n",
       "      <td>1.0690</td>\n",
       "      <td>0.5523</td>\n",
       "      <td>-0.3031</td>\n",
       "      <td>0.1094</td>\n",
       "      <td>0.2885</td>\n",
       "      <td>-0.3786</td>\n",
       "      <td>0.7125</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 877 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             id tratamento  tempo dose      droga     g-0     g-1     g-2  \\\n",
       "0  id_000644bb2  com_droga     24   D1  b68db1d53  1.0620  0.5577 -0.2479   \n",
       "1  id_000779bfc  com_droga     72   D1  df89a8e5a  0.0743  0.4087  0.2991   \n",
       "2  id_000a6266a  com_droga     48   D1  18bb41b2c  0.6280  0.5817  1.5540   \n",
       "3  id_0015fd391  com_droga     48   D1  8c7f86626 -0.5138 -0.2491 -0.2656   \n",
       "4  id_001626bd3  com_droga     72   D2  7cbed3131 -0.3254 -0.4009  0.9700   \n",
       "\n",
       "      g-3     g-4  ...    c-90    c-91    c-92    c-93    c-94    c-95  \\\n",
       "0 -0.6208 -0.1944  ...  0.2862  0.2584  0.8076  0.5523 -0.1912  0.6584   \n",
       "1  0.0604  1.0190  ... -0.4265  0.7543  0.4708  0.0230  0.2957  0.4899   \n",
       "2 -0.0764 -0.0323  ... -0.7250 -0.6297  0.6103  0.0223 -1.3240 -0.3174   \n",
       "3  0.5288  4.0620  ... -2.0990 -0.6441 -5.6300 -1.3780 -0.8632 -1.2880   \n",
       "4  0.6919  1.4180  ...  0.0042  0.0048  0.6670  1.0690  0.5523 -0.3031   \n",
       "\n",
       "     c-96    c-97    c-98    c-99  \n",
       "0 -0.3981  0.2139  0.3801  0.4176  \n",
       "1  0.1522  0.1241  0.6077  0.7371  \n",
       "2 -0.6417 -0.2187 -1.4080  0.6931  \n",
       "3 -1.6210 -0.8784 -0.3876 -0.8154  \n",
       "4  0.1094  0.2885 -0.3786  0.7125  \n",
       "\n",
       "[5 rows x 877 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dados.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "Q_5RP0HKs1Sy",
    "outputId": "f4cd24a8-03fe-4e0f-e835-dbc8c024691f"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(23814, 877)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dados.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "a8Og_8PIwdAS",
    "outputId": "f6f15d1a-7c5d-4c17-dea9-75b6479ca554"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0           com_droga\n",
       "1           com_droga\n",
       "2           com_droga\n",
       "3           com_droga\n",
       "4           com_droga\n",
       "             ...     \n",
       "23809       com_droga\n",
       "23810       com_droga\n",
       "23811    com_controle\n",
       "23812       com_droga\n",
       "23813       com_droga\n",
       "Name: tratamento, Length: 23814, dtype: object"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dados['tratamento']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "_RkLWqqrwtJG",
    "outputId": "a4ca6ec7-c59b-474d-a580-72b5ce083102"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['com_droga', 'com_controle'], dtype=object)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dados['tratamento'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "uceNBUhKkkUt"
   },
   "source": [
    "Agora vamos analisar a coluna do tempo:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "IOPFkJW5w5i-",
    "outputId": "125880f9-762c-453f-f8f2-5f8859dc7051"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([24, 72, 48], dtype=int64)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dados['tempo'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "e1ObXppVlkS2"
   },
   "source": [
    "Além do tempo, podemos analisar também a coluna de dose:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "2UWEVupCx9M7",
    "outputId": "6e62e976-3b0b-43fe-f6e0-17c0629acedf"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['D1', 'D2'], dtype=object)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dados['dose'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "p1NaXGzCySfP",
    "outputId": "b9464461-f717-44b7-8aa5-fa4e6a2f13e3"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['b68db1d53', 'df89a8e5a', '18bb41b2c', ..., '573c787a2',\n",
       "       'b2fe3eca7', 'dd4a96d16'], dtype=object)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dados['droga'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "CgHdbkO9ye6g",
    "outputId": "a0195361-e58e-47d9-b3cb-c4ee33cd0316"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1.062 ,  0.0743,  0.628 , ...,  0.3942,  0.666 , -0.8598])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dados['g-0'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "pvSIUn9_zTWH",
    "outputId": "b3a06c09-41b1-464c-de21-a5e4e4c25329"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "com_droga       21948\n",
       "com_controle     1866\n",
       "Name: tratamento, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dados['tratamento'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "SlyZ2RiGeU80"
   },
   "source": [
    "Será que essa diferença entre os valores dentro das categorias continuam tão desproporcionais? Vamos investigar a categoria ```dose```:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "8F1qPq6h2WBl",
    "outputId": "923d0150-a27c-49fb-fa5e-58f096342850"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "D1    12147\n",
       "D2    11667\n",
       "Name: dose, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dados['dose'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "1sX66gG249OZ",
    "outputId": "57c3785c-f478-4b98-c396-09fbe463ac07"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "com_droga       0.921643\n",
       "com_controle    0.078357\n",
       "Name: tratamento, dtype: float64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dados['tratamento'].value_counts(normalize = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "wrLfRXx65NPP",
    "outputId": "49f70806-76cc-49de-ee06-25c487e0106b"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "D1    0.510078\n",
       "D2    0.489922\n",
       "Name: dose, dtype: float64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dados['dose'].value_counts(normalize = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 265
    },
    "id": "LYiMo76m5bnS",
    "outputId": "13506524-544f-4398-ce92-edd48dd484bc"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='tratamento'>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dados['tratamento'].value_counts().plot.pie()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 265
    },
    "id": "qmBQF9kx5uIc",
    "outputId": "3e2491b4-f0bb-4e50-c776-96e08b13ce3a"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='tempo'>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dados['tempo'].value_counts().plot.pie()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 285
    },
    "id": "TJ0MjBYZ6LOI",
    "outputId": "15f90942-77ae-4358-f266-799b4a3e5133"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dados['tempo'].value_counts().plot.bar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 244
    },
    "id": "_igXHK3A8wQr",
    "outputId": "1950b223-a1e5-49df-c1b6-19e55b75aa71"
   },
   "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>id</th>\n",
       "      <th>tratamento</th>\n",
       "      <th>tempo</th>\n",
       "      <th>dose</th>\n",
       "      <th>droga</th>\n",
       "      <th>g-0</th>\n",
       "      <th>g-1</th>\n",
       "      <th>g-2</th>\n",
       "      <th>g-3</th>\n",
       "      <th>g-4</th>\n",
       "      <th>...</th>\n",
       "      <th>c-90</th>\n",
       "      <th>c-91</th>\n",
       "      <th>c-92</th>\n",
       "      <th>c-93</th>\n",
       "      <th>c-94</th>\n",
       "      <th>c-95</th>\n",
       "      <th>c-96</th>\n",
       "      <th>c-97</th>\n",
       "      <th>c-98</th>\n",
       "      <th>c-99</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>id_000644bb2</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>24</td>\n",
       "      <td>D1</td>\n",
       "      <td>b68db1d53</td>\n",
       "      <td>1.0620</td>\n",
       "      <td>0.5577</td>\n",
       "      <td>-0.2479</td>\n",
       "      <td>-0.6208</td>\n",
       "      <td>-0.1944</td>\n",
       "      <td>...</td>\n",
       "      <td>0.2862</td>\n",
       "      <td>0.2584</td>\n",
       "      <td>0.8076</td>\n",
       "      <td>0.5523</td>\n",
       "      <td>-0.1912</td>\n",
       "      <td>0.6584</td>\n",
       "      <td>-0.3981</td>\n",
       "      <td>0.2139</td>\n",
       "      <td>0.3801</td>\n",
       "      <td>0.4176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>id_000779bfc</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>72</td>\n",
       "      <td>D1</td>\n",
       "      <td>df89a8e5a</td>\n",
       "      <td>0.0743</td>\n",
       "      <td>0.4087</td>\n",
       "      <td>0.2991</td>\n",
       "      <td>0.0604</td>\n",
       "      <td>1.0190</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.4265</td>\n",
       "      <td>0.7543</td>\n",
       "      <td>0.4708</td>\n",
       "      <td>0.0230</td>\n",
       "      <td>0.2957</td>\n",
       "      <td>0.4899</td>\n",
       "      <td>0.1522</td>\n",
       "      <td>0.1241</td>\n",
       "      <td>0.6077</td>\n",
       "      <td>0.7371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>id_000a6266a</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>48</td>\n",
       "      <td>D1</td>\n",
       "      <td>18bb41b2c</td>\n",
       "      <td>0.6280</td>\n",
       "      <td>0.5817</td>\n",
       "      <td>1.5540</td>\n",
       "      <td>-0.0764</td>\n",
       "      <td>-0.0323</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.7250</td>\n",
       "      <td>-0.6297</td>\n",
       "      <td>0.6103</td>\n",
       "      <td>0.0223</td>\n",
       "      <td>-1.3240</td>\n",
       "      <td>-0.3174</td>\n",
       "      <td>-0.6417</td>\n",
       "      <td>-0.2187</td>\n",
       "      <td>-1.4080</td>\n",
       "      <td>0.6931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>id_001bd861f</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>24</td>\n",
       "      <td>D2</td>\n",
       "      <td>746ca1f5a</td>\n",
       "      <td>2.0440</td>\n",
       "      <td>1.7000</td>\n",
       "      <td>-1.5390</td>\n",
       "      <td>5.9440</td>\n",
       "      <td>-2.1670</td>\n",
       "      <td>...</td>\n",
       "      <td>0.1855</td>\n",
       "      <td>1.1720</td>\n",
       "      <td>0.8325</td>\n",
       "      <td>0.6486</td>\n",
       "      <td>0.8090</td>\n",
       "      <td>1.5880</td>\n",
       "      <td>2.4670</td>\n",
       "      <td>0.0357</td>\n",
       "      <td>0.1351</td>\n",
       "      <td>-0.3179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>id_0020d0484</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>48</td>\n",
       "      <td>D1</td>\n",
       "      <td>8b87a7a83</td>\n",
       "      <td>0.2711</td>\n",
       "      <td>0.5133</td>\n",
       "      <td>-0.1327</td>\n",
       "      <td>2.5950</td>\n",
       "      <td>0.6980</td>\n",
       "      <td>...</td>\n",
       "      <td>0.3230</td>\n",
       "      <td>-0.4140</td>\n",
       "      <td>0.2532</td>\n",
       "      <td>0.0513</td>\n",
       "      <td>0.8600</td>\n",
       "      <td>1.4250</td>\n",
       "      <td>0.6633</td>\n",
       "      <td>0.4562</td>\n",
       "      <td>-0.9622</td>\n",
       "      <td>0.0260</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 877 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             id tratamento  tempo dose      droga     g-0     g-1     g-2  \\\n",
       "0  id_000644bb2  com_droga     24   D1  b68db1d53  1.0620  0.5577 -0.2479   \n",
       "1  id_000779bfc  com_droga     72   D1  df89a8e5a  0.0743  0.4087  0.2991   \n",
       "2  id_000a6266a  com_droga     48   D1  18bb41b2c  0.6280  0.5817  1.5540   \n",
       "6  id_001bd861f  com_droga     24   D2  746ca1f5a  2.0440  1.7000 -1.5390   \n",
       "7  id_0020d0484  com_droga     48   D1  8b87a7a83  0.2711  0.5133 -0.1327   \n",
       "\n",
       "      g-3     g-4  ...    c-90    c-91    c-92    c-93    c-94    c-95  \\\n",
       "0 -0.6208 -0.1944  ...  0.2862  0.2584  0.8076  0.5523 -0.1912  0.6584   \n",
       "1  0.0604  1.0190  ... -0.4265  0.7543  0.4708  0.0230  0.2957  0.4899   \n",
       "2 -0.0764 -0.0323  ... -0.7250 -0.6297  0.6103  0.0223 -1.3240 -0.3174   \n",
       "6  5.9440 -2.1670  ...  0.1855  1.1720  0.8325  0.6486  0.8090  1.5880   \n",
       "7  2.5950  0.6980  ...  0.3230 -0.4140  0.2532  0.0513  0.8600  1.4250   \n",
       "\n",
       "     c-96    c-97    c-98    c-99  \n",
       "0 -0.3981  0.2139  0.3801  0.4176  \n",
       "1  0.1522  0.1241  0.6077  0.7371  \n",
       "2 -0.6417 -0.2187 -1.4080  0.6931  \n",
       "6  2.4670  0.0357  0.1351 -0.3179  \n",
       "7  0.6633  0.4562 -0.9622  0.0260  \n",
       "\n",
       "[5 rows x 877 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dados_filtrados = dados[dados['g-0'] > 0]\n",
    "dados_filtrados.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "X_Lg2XTu20ND"
   },
   "source": [
    "### Desafio 01: Investigar por que a classe tratamento é tão desbalanceada?"
   ]
  },
  {
   "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>dose</th>\n",
       "      <th>D1</th>\n",
       "      <th>D2</th>\n",
       "      <th>All</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tratamento</th>\n",
       "      <th>tempo</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">com_controle</th>\n",
       "      <th>24</th>\n",
       "      <td>301</td>\n",
       "      <td>305</td>\n",
       "      <td>606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>343</td>\n",
       "      <td>305</td>\n",
       "      <td>648</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>307</td>\n",
       "      <td>305</td>\n",
       "      <td>612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">com_droga</th>\n",
       "      <th>24</th>\n",
       "      <td>3585</td>\n",
       "      <td>3581</td>\n",
       "      <td>7166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>4011</td>\n",
       "      <td>3591</td>\n",
       "      <td>7602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>3600</td>\n",
       "      <td>3580</td>\n",
       "      <td>7180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>All</th>\n",
       "      <th></th>\n",
       "      <td>12147</td>\n",
       "      <td>11667</td>\n",
       "      <td>23814</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "dose                   D1     D2    All\n",
       "tratamento   tempo                     \n",
       "com_controle 24       301    305    606\n",
       "             48       343    305    648\n",
       "             72       307    305    612\n",
       "com_droga    24      3585   3581   7166\n",
       "             48      4011   3591   7602\n",
       "             72      3600   3580   7180\n",
       "All                 12147  11667  23814"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Verificando a relação do tratamento com relação a dose e tempo\n",
    "pd.crosstab([dados.tratamento,dados.tempo],\n",
    "            dados.dose,\n",
    "            margins=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th>tratamento</th>\n",
       "      <th colspan=\"2\" halign=\"left\">com_controle</th>\n",
       "      <th colspan=\"2\" halign=\"left\">com_droga</th>\n",
       "      <th>All</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dose</th>\n",
       "      <th>D1</th>\n",
       "      <th>D2</th>\n",
       "      <th>D1</th>\n",
       "      <th>D2</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tempo</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>301</td>\n",
       "      <td>305</td>\n",
       "      <td>3585</td>\n",
       "      <td>3581</td>\n",
       "      <td>7772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>343</td>\n",
       "      <td>305</td>\n",
       "      <td>4011</td>\n",
       "      <td>3591</td>\n",
       "      <td>8250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>307</td>\n",
       "      <td>305</td>\n",
       "      <td>3600</td>\n",
       "      <td>3580</td>\n",
       "      <td>7792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>All</th>\n",
       "      <td>951</td>\n",
       "      <td>915</td>\n",
       "      <td>11196</td>\n",
       "      <td>10752</td>\n",
       "      <td>23814</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "tratamento com_controle      com_droga           All\n",
       "dose                 D1   D2        D1     D2       \n",
       "tempo                                               \n",
       "24                  301  305      3585   3581   7772\n",
       "48                  343  305      4011   3591   8250\n",
       "72                  307  305      3600   3580   7792\n",
       "All                 951  915     11196  10752  23814"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Verificando a relação do tratamento com relação a dose e tempo\n",
    "pd.crosstab(dados.tempo,\n",
    "            [dados.tratamento, dados.dose],\n",
    "             margins=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "X_Lg2XTu20ND"
   },
   "source": [
    "### Desafio 02: Plotar as 5 últimas linhas da tabela"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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>id</th>\n",
       "      <th>tratamento</th>\n",
       "      <th>tempo</th>\n",
       "      <th>dose</th>\n",
       "      <th>droga</th>\n",
       "      <th>g-0</th>\n",
       "      <th>g-1</th>\n",
       "      <th>g-2</th>\n",
       "      <th>g-3</th>\n",
       "      <th>g-4</th>\n",
       "      <th>...</th>\n",
       "      <th>c-90</th>\n",
       "      <th>c-91</th>\n",
       "      <th>c-92</th>\n",
       "      <th>c-93</th>\n",
       "      <th>c-94</th>\n",
       "      <th>c-95</th>\n",
       "      <th>c-96</th>\n",
       "      <th>c-97</th>\n",
       "      <th>c-98</th>\n",
       "      <th>c-99</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>23809</th>\n",
       "      <td>id_fffb1ceed</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>24</td>\n",
       "      <td>D2</td>\n",
       "      <td>df1d0a5a1</td>\n",
       "      <td>0.1394</td>\n",
       "      <td>-0.0636</td>\n",
       "      <td>-0.1112</td>\n",
       "      <td>-0.5080</td>\n",
       "      <td>-0.4713</td>\n",
       "      <td>...</td>\n",
       "      <td>0.1969</td>\n",
       "      <td>0.0262</td>\n",
       "      <td>-0.8121</td>\n",
       "      <td>0.3434</td>\n",
       "      <td>0.5372</td>\n",
       "      <td>-0.3246</td>\n",
       "      <td>0.0631</td>\n",
       "      <td>0.9171</td>\n",
       "      <td>0.5258</td>\n",
       "      <td>0.4680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23810</th>\n",
       "      <td>id_fffb70c0c</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>24</td>\n",
       "      <td>D2</td>\n",
       "      <td>ecf3b6b74</td>\n",
       "      <td>-1.3260</td>\n",
       "      <td>0.3478</td>\n",
       "      <td>-0.3743</td>\n",
       "      <td>0.9905</td>\n",
       "      <td>-0.7178</td>\n",
       "      <td>...</td>\n",
       "      <td>0.4286</td>\n",
       "      <td>0.4426</td>\n",
       "      <td>0.0423</td>\n",
       "      <td>-0.3195</td>\n",
       "      <td>-0.8086</td>\n",
       "      <td>-0.9798</td>\n",
       "      <td>-0.2084</td>\n",
       "      <td>-0.1224</td>\n",
       "      <td>-0.2715</td>\n",
       "      <td>0.3689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23811</th>\n",
       "      <td>id_fffc1c3f4</td>\n",
       "      <td>com_controle</td>\n",
       "      <td>48</td>\n",
       "      <td>D2</td>\n",
       "      <td>cacb2b860</td>\n",
       "      <td>0.3942</td>\n",
       "      <td>0.3756</td>\n",
       "      <td>0.3109</td>\n",
       "      <td>-0.7389</td>\n",
       "      <td>0.5505</td>\n",
       "      <td>...</td>\n",
       "      <td>0.5409</td>\n",
       "      <td>0.3755</td>\n",
       "      <td>0.7343</td>\n",
       "      <td>0.2807</td>\n",
       "      <td>0.4116</td>\n",
       "      <td>0.6422</td>\n",
       "      <td>0.2256</td>\n",
       "      <td>0.7592</td>\n",
       "      <td>0.6656</td>\n",
       "      <td>0.3808</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23812</th>\n",
       "      <td>id_fffcb9e7c</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>24</td>\n",
       "      <td>D1</td>\n",
       "      <td>8b87a7a83</td>\n",
       "      <td>0.6660</td>\n",
       "      <td>0.2324</td>\n",
       "      <td>0.4392</td>\n",
       "      <td>0.2044</td>\n",
       "      <td>0.8531</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1105</td>\n",
       "      <td>0.4258</td>\n",
       "      <td>-0.2012</td>\n",
       "      <td>0.1506</td>\n",
       "      <td>1.5230</td>\n",
       "      <td>0.7101</td>\n",
       "      <td>0.1732</td>\n",
       "      <td>0.7015</td>\n",
       "      <td>-0.6290</td>\n",
       "      <td>0.0740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23813</th>\n",
       "      <td>id_ffffdd77b</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>72</td>\n",
       "      <td>D1</td>\n",
       "      <td>972f41291</td>\n",
       "      <td>-0.8598</td>\n",
       "      <td>1.0240</td>\n",
       "      <td>-0.1361</td>\n",
       "      <td>0.7952</td>\n",
       "      <td>-0.3611</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.3890</td>\n",
       "      <td>-1.7450</td>\n",
       "      <td>-6.6300</td>\n",
       "      <td>-4.0950</td>\n",
       "      <td>-7.3860</td>\n",
       "      <td>-1.4160</td>\n",
       "      <td>-3.5770</td>\n",
       "      <td>-0.4775</td>\n",
       "      <td>-2.1500</td>\n",
       "      <td>-4.2520</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 877 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 id    tratamento  tempo dose      droga     g-0     g-1  \\\n",
       "23809  id_fffb1ceed     com_droga     24   D2  df1d0a5a1  0.1394 -0.0636   \n",
       "23810  id_fffb70c0c     com_droga     24   D2  ecf3b6b74 -1.3260  0.3478   \n",
       "23811  id_fffc1c3f4  com_controle     48   D2  cacb2b860  0.3942  0.3756   \n",
       "23812  id_fffcb9e7c     com_droga     24   D1  8b87a7a83  0.6660  0.2324   \n",
       "23813  id_ffffdd77b     com_droga     72   D1  972f41291 -0.8598  1.0240   \n",
       "\n",
       "          g-2     g-3     g-4  ...    c-90    c-91    c-92    c-93    c-94  \\\n",
       "23809 -0.1112 -0.5080 -0.4713  ...  0.1969  0.0262 -0.8121  0.3434  0.5372   \n",
       "23810 -0.3743  0.9905 -0.7178  ...  0.4286  0.4426  0.0423 -0.3195 -0.8086   \n",
       "23811  0.3109 -0.7389  0.5505  ...  0.5409  0.3755  0.7343  0.2807  0.4116   \n",
       "23812  0.4392  0.2044  0.8531  ... -0.1105  0.4258 -0.2012  0.1506  1.5230   \n",
       "23813 -0.1361  0.7952 -0.3611  ... -3.3890 -1.7450 -6.6300 -4.0950 -7.3860   \n",
       "\n",
       "         c-95    c-96    c-97    c-98    c-99  \n",
       "23809 -0.3246  0.0631  0.9171  0.5258  0.4680  \n",
       "23810 -0.9798 -0.2084 -0.1224 -0.2715  0.3689  \n",
       "23811  0.6422  0.2256  0.7592  0.6656  0.3808  \n",
       "23812  0.7101  0.1732  0.7015 -0.6290  0.0740  \n",
       "23813 -1.4160 -3.5770 -0.4775 -2.1500 -4.2520  \n",
       "\n",
       "[5 rows x 877 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dados.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "X_Lg2XTu20ND"
   },
   "source": [
    "### Desafio 03: Proporção das classes tratamento."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "com_droga       92.16\n",
       "com_controle     7.84\n",
       "Name: tratamento, dtype: float64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dados.tratamento.value_counts(normalize=True).round(4) * 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotando em um gráfico\n",
    "dados.tratamento.value_counts().plot(kind='bar')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "X_Lg2XTu20ND"
   },
   "source": [
    "### Desafio 04: Quantas tipos de drogas foram investigados."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Quantidade de tipos de drogas: 3289\n"
     ]
    }
   ],
   "source": [
    "print('Quantidade de tipos de drogas: %.d' % len(dados.droga.unique()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "X_Lg2XTu20ND"
   },
   "source": [
    "### Desafio 05: Procurar na documentação o método query(pandas). "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.query.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>id</th>\n",
       "      <th>tratamento</th>\n",
       "      <th>tempo</th>\n",
       "      <th>dose</th>\n",
       "      <th>droga</th>\n",
       "      <th>g-0</th>\n",
       "      <th>g-1</th>\n",
       "      <th>g-2</th>\n",
       "      <th>g-3</th>\n",
       "      <th>g-4</th>\n",
       "      <th>...</th>\n",
       "      <th>c-90</th>\n",
       "      <th>c-91</th>\n",
       "      <th>c-92</th>\n",
       "      <th>c-93</th>\n",
       "      <th>c-94</th>\n",
       "      <th>c-95</th>\n",
       "      <th>c-96</th>\n",
       "      <th>c-97</th>\n",
       "      <th>c-98</th>\n",
       "      <th>c-99</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>id_000644bb2</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>24</td>\n",
       "      <td>D1</td>\n",
       "      <td>b68db1d53</td>\n",
       "      <td>1.0620</td>\n",
       "      <td>0.5577</td>\n",
       "      <td>-0.2479</td>\n",
       "      <td>-0.6208</td>\n",
       "      <td>-0.1944</td>\n",
       "      <td>...</td>\n",
       "      <td>0.2862</td>\n",
       "      <td>0.2584</td>\n",
       "      <td>0.8076</td>\n",
       "      <td>0.5523</td>\n",
       "      <td>-0.1912</td>\n",
       "      <td>0.6584</td>\n",
       "      <td>-0.3981</td>\n",
       "      <td>0.2139</td>\n",
       "      <td>0.3801</td>\n",
       "      <td>0.4176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>id_000779bfc</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>72</td>\n",
       "      <td>D1</td>\n",
       "      <td>df89a8e5a</td>\n",
       "      <td>0.0743</td>\n",
       "      <td>0.4087</td>\n",
       "      <td>0.2991</td>\n",
       "      <td>0.0604</td>\n",
       "      <td>1.0190</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.4265</td>\n",
       "      <td>0.7543</td>\n",
       "      <td>0.4708</td>\n",
       "      <td>0.0230</td>\n",
       "      <td>0.2957</td>\n",
       "      <td>0.4899</td>\n",
       "      <td>0.1522</td>\n",
       "      <td>0.1241</td>\n",
       "      <td>0.6077</td>\n",
       "      <td>0.7371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>id_000a6266a</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>48</td>\n",
       "      <td>D1</td>\n",
       "      <td>18bb41b2c</td>\n",
       "      <td>0.6280</td>\n",
       "      <td>0.5817</td>\n",
       "      <td>1.5540</td>\n",
       "      <td>-0.0764</td>\n",
       "      <td>-0.0323</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.7250</td>\n",
       "      <td>-0.6297</td>\n",
       "      <td>0.6103</td>\n",
       "      <td>0.0223</td>\n",
       "      <td>-1.3240</td>\n",
       "      <td>-0.3174</td>\n",
       "      <td>-0.6417</td>\n",
       "      <td>-0.2187</td>\n",
       "      <td>-1.4080</td>\n",
       "      <td>0.6931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>id_0015fd391</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>48</td>\n",
       "      <td>D1</td>\n",
       "      <td>8c7f86626</td>\n",
       "      <td>-0.5138</td>\n",
       "      <td>-0.2491</td>\n",
       "      <td>-0.2656</td>\n",
       "      <td>0.5288</td>\n",
       "      <td>4.0620</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.0990</td>\n",
       "      <td>-0.6441</td>\n",
       "      <td>-5.6300</td>\n",
       "      <td>-1.3780</td>\n",
       "      <td>-0.8632</td>\n",
       "      <td>-1.2880</td>\n",
       "      <td>-1.6210</td>\n",
       "      <td>-0.8784</td>\n",
       "      <td>-0.3876</td>\n",
       "      <td>-0.8154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>id_001626bd3</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>72</td>\n",
       "      <td>D2</td>\n",
       "      <td>7cbed3131</td>\n",
       "      <td>-0.3254</td>\n",
       "      <td>-0.4009</td>\n",
       "      <td>0.9700</td>\n",
       "      <td>0.6919</td>\n",
       "      <td>1.4180</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0042</td>\n",
       "      <td>0.0048</td>\n",
       "      <td>0.6670</td>\n",
       "      <td>1.0690</td>\n",
       "      <td>0.5523</td>\n",
       "      <td>-0.3031</td>\n",
       "      <td>0.1094</td>\n",
       "      <td>0.2885</td>\n",
       "      <td>-0.3786</td>\n",
       "      <td>0.7125</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 877 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             id tratamento  tempo dose      droga     g-0     g-1     g-2  \\\n",
       "0  id_000644bb2  com_droga     24   D1  b68db1d53  1.0620  0.5577 -0.2479   \n",
       "1  id_000779bfc  com_droga     72   D1  df89a8e5a  0.0743  0.4087  0.2991   \n",
       "2  id_000a6266a  com_droga     48   D1  18bb41b2c  0.6280  0.5817  1.5540   \n",
       "3  id_0015fd391  com_droga     48   D1  8c7f86626 -0.5138 -0.2491 -0.2656   \n",
       "4  id_001626bd3  com_droga     72   D2  7cbed3131 -0.3254 -0.4009  0.9700   \n",
       "\n",
       "      g-3     g-4  ...    c-90    c-91    c-92    c-93    c-94    c-95  \\\n",
       "0 -0.6208 -0.1944  ...  0.2862  0.2584  0.8076  0.5523 -0.1912  0.6584   \n",
       "1  0.0604  1.0190  ... -0.4265  0.7543  0.4708  0.0230  0.2957  0.4899   \n",
       "2 -0.0764 -0.0323  ... -0.7250 -0.6297  0.6103  0.0223 -1.3240 -0.3174   \n",
       "3  0.5288  4.0620  ... -2.0990 -0.6441 -5.6300 -1.3780 -0.8632 -1.2880   \n",
       "4  0.6919  1.4180  ...  0.0042  0.0048  0.6670  1.0690  0.5523 -0.3031   \n",
       "\n",
       "     c-96    c-97    c-98    c-99  \n",
       "0 -0.3981  0.2139  0.3801  0.4176  \n",
       "1  0.1522  0.1241  0.6077  0.7371  \n",
       "2 -0.6417 -0.2187 -1.4080  0.6931  \n",
       "3 -1.6210 -0.8784 -0.3876 -0.8154  \n",
       "4  0.1094  0.2885 -0.3786  0.7125  \n",
       "\n",
       "[5 rows x 877 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dados.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "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>id</th>\n",
       "      <th>tratamento</th>\n",
       "      <th>tempo</th>\n",
       "      <th>dose</th>\n",
       "      <th>droga</th>\n",
       "      <th>g-0</th>\n",
       "      <th>g-1</th>\n",
       "      <th>g-2</th>\n",
       "      <th>g-3</th>\n",
       "      <th>g-4</th>\n",
       "      <th>...</th>\n",
       "      <th>c-90</th>\n",
       "      <th>c-91</th>\n",
       "      <th>c-92</th>\n",
       "      <th>c-93</th>\n",
       "      <th>c-94</th>\n",
       "      <th>c-95</th>\n",
       "      <th>c-96</th>\n",
       "      <th>c-97</th>\n",
       "      <th>c-98</th>\n",
       "      <th>c-99</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>id_000644bb2</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>24</td>\n",
       "      <td>D1</td>\n",
       "      <td>b68db1d53</td>\n",
       "      <td>1.0620</td>\n",
       "      <td>0.5577</td>\n",
       "      <td>-0.2479</td>\n",
       "      <td>-0.6208</td>\n",
       "      <td>-0.1944</td>\n",
       "      <td>...</td>\n",
       "      <td>0.2862</td>\n",
       "      <td>0.2584</td>\n",
       "      <td>0.8076</td>\n",
       "      <td>0.5523</td>\n",
       "      <td>-0.1912</td>\n",
       "      <td>0.6584</td>\n",
       "      <td>-0.3981</td>\n",
       "      <td>0.2139</td>\n",
       "      <td>0.3801</td>\n",
       "      <td>0.4176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>id_001762a82</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>24</td>\n",
       "      <td>D1</td>\n",
       "      <td>e06749542</td>\n",
       "      <td>-0.6111</td>\n",
       "      <td>0.2941</td>\n",
       "      <td>-0.9901</td>\n",
       "      <td>0.2277</td>\n",
       "      <td>1.2810</td>\n",
       "      <td>...</td>\n",
       "      <td>1.8390</td>\n",
       "      <td>1.1570</td>\n",
       "      <td>-1.0120</td>\n",
       "      <td>1.9010</td>\n",
       "      <td>1.4270</td>\n",
       "      <td>0.4519</td>\n",
       "      <td>1.2120</td>\n",
       "      <td>0.3765</td>\n",
       "      <td>0.7848</td>\n",
       "      <td>1.3990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>id_001bd861f</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>24</td>\n",
       "      <td>D2</td>\n",
       "      <td>746ca1f5a</td>\n",
       "      <td>2.0440</td>\n",
       "      <td>1.7000</td>\n",
       "      <td>-1.5390</td>\n",
       "      <td>5.9440</td>\n",
       "      <td>-2.1670</td>\n",
       "      <td>...</td>\n",
       "      <td>0.1855</td>\n",
       "      <td>1.1720</td>\n",
       "      <td>0.8325</td>\n",
       "      <td>0.6486</td>\n",
       "      <td>0.8090</td>\n",
       "      <td>1.5880</td>\n",
       "      <td>2.4670</td>\n",
       "      <td>0.0357</td>\n",
       "      <td>0.1351</td>\n",
       "      <td>-0.3179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>id_0031dd989</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>24</td>\n",
       "      <td>D2</td>\n",
       "      <td>96b9ac123</td>\n",
       "      <td>-0.4764</td>\n",
       "      <td>-0.5513</td>\n",
       "      <td>1.8560</td>\n",
       "      <td>-0.2618</td>\n",
       "      <td>-0.3310</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.4718</td>\n",
       "      <td>1.0620</td>\n",
       "      <td>0.3601</td>\n",
       "      <td>0.4402</td>\n",
       "      <td>0.2655</td>\n",
       "      <td>0.5741</td>\n",
       "      <td>0.8093</td>\n",
       "      <td>-0.0269</td>\n",
       "      <td>0.4259</td>\n",
       "      <td>0.9279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>id_006e27d96</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>24</td>\n",
       "      <td>D2</td>\n",
       "      <td>808cb9eea</td>\n",
       "      <td>0.0549</td>\n",
       "      <td>0.2602</td>\n",
       "      <td>1.6680</td>\n",
       "      <td>0.0603</td>\n",
       "      <td>-0.3156</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0946</td>\n",
       "      <td>0.0294</td>\n",
       "      <td>0.1041</td>\n",
       "      <td>-0.1413</td>\n",
       "      <td>-1.5430</td>\n",
       "      <td>-1.4180</td>\n",
       "      <td>0.0691</td>\n",
       "      <td>0.1536</td>\n",
       "      <td>0.2948</td>\n",
       "      <td>-0.9860</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23802</th>\n",
       "      <td>id_fff3976bd</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>24</td>\n",
       "      <td>D1</td>\n",
       "      <td>87d714366</td>\n",
       "      <td>3.2890</td>\n",
       "      <td>2.1270</td>\n",
       "      <td>0.9770</td>\n",
       "      <td>2.0490</td>\n",
       "      <td>2.3170</td>\n",
       "      <td>...</td>\n",
       "      <td>-8.6300</td>\n",
       "      <td>-8.1490</td>\n",
       "      <td>-6.2900</td>\n",
       "      <td>-8.0970</td>\n",
       "      <td>-8.7330</td>\n",
       "      <td>-2.3780</td>\n",
       "      <td>-8.4480</td>\n",
       "      <td>-4.4550</td>\n",
       "      <td>-5.7930</td>\n",
       "      <td>-3.7000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23804</th>\n",
       "      <td>id_fff506720</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>24</td>\n",
       "      <td>D1</td>\n",
       "      <td>74515bfd2</td>\n",
       "      <td>-1.0140</td>\n",
       "      <td>0.1709</td>\n",
       "      <td>-0.4291</td>\n",
       "      <td>1.8750</td>\n",
       "      <td>0.9859</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.6730</td>\n",
       "      <td>0.3175</td>\n",
       "      <td>-1.5510</td>\n",
       "      <td>-1.2800</td>\n",
       "      <td>-0.7632</td>\n",
       "      <td>-0.6736</td>\n",
       "      <td>-0.4097</td>\n",
       "      <td>0.2282</td>\n",
       "      <td>-0.3213</td>\n",
       "      <td>-0.0836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23809</th>\n",
       "      <td>id_fffb1ceed</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>24</td>\n",
       "      <td>D2</td>\n",
       "      <td>df1d0a5a1</td>\n",
       "      <td>0.1394</td>\n",
       "      <td>-0.0636</td>\n",
       "      <td>-0.1112</td>\n",
       "      <td>-0.5080</td>\n",
       "      <td>-0.4713</td>\n",
       "      <td>...</td>\n",
       "      <td>0.1969</td>\n",
       "      <td>0.0262</td>\n",
       "      <td>-0.8121</td>\n",
       "      <td>0.3434</td>\n",
       "      <td>0.5372</td>\n",
       "      <td>-0.3246</td>\n",
       "      <td>0.0631</td>\n",
       "      <td>0.9171</td>\n",
       "      <td>0.5258</td>\n",
       "      <td>0.4680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23810</th>\n",
       "      <td>id_fffb70c0c</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>24</td>\n",
       "      <td>D2</td>\n",
       "      <td>ecf3b6b74</td>\n",
       "      <td>-1.3260</td>\n",
       "      <td>0.3478</td>\n",
       "      <td>-0.3743</td>\n",
       "      <td>0.9905</td>\n",
       "      <td>-0.7178</td>\n",
       "      <td>...</td>\n",
       "      <td>0.4286</td>\n",
       "      <td>0.4426</td>\n",
       "      <td>0.0423</td>\n",
       "      <td>-0.3195</td>\n",
       "      <td>-0.8086</td>\n",
       "      <td>-0.9798</td>\n",
       "      <td>-0.2084</td>\n",
       "      <td>-0.1224</td>\n",
       "      <td>-0.2715</td>\n",
       "      <td>0.3689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23812</th>\n",
       "      <td>id_fffcb9e7c</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>24</td>\n",
       "      <td>D1</td>\n",
       "      <td>8b87a7a83</td>\n",
       "      <td>0.6660</td>\n",
       "      <td>0.2324</td>\n",
       "      <td>0.4392</td>\n",
       "      <td>0.2044</td>\n",
       "      <td>0.8531</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1105</td>\n",
       "      <td>0.4258</td>\n",
       "      <td>-0.2012</td>\n",
       "      <td>0.1506</td>\n",
       "      <td>1.5230</td>\n",
       "      <td>0.7101</td>\n",
       "      <td>0.1732</td>\n",
       "      <td>0.7015</td>\n",
       "      <td>-0.6290</td>\n",
       "      <td>0.0740</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7772 rows × 877 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 id tratamento  tempo dose      droga     g-0     g-1     g-2  \\\n",
       "0      id_000644bb2  com_droga     24   D1  b68db1d53  1.0620  0.5577 -0.2479   \n",
       "5      id_001762a82  com_droga     24   D1  e06749542 -0.6111  0.2941 -0.9901   \n",
       "6      id_001bd861f  com_droga     24   D2  746ca1f5a  2.0440  1.7000 -1.5390   \n",
       "17     id_0031dd989  com_droga     24   D2  96b9ac123 -0.4764 -0.5513  1.8560   \n",
       "32     id_006e27d96  com_droga     24   D2  808cb9eea  0.0549  0.2602  1.6680   \n",
       "...             ...        ...    ...  ...        ...     ...     ...     ...   \n",
       "23802  id_fff3976bd  com_droga     24   D1  87d714366  3.2890  2.1270  0.9770   \n",
       "23804  id_fff506720  com_droga     24   D1  74515bfd2 -1.0140  0.1709 -0.4291   \n",
       "23809  id_fffb1ceed  com_droga     24   D2  df1d0a5a1  0.1394 -0.0636 -0.1112   \n",
       "23810  id_fffb70c0c  com_droga     24   D2  ecf3b6b74 -1.3260  0.3478 -0.3743   \n",
       "23812  id_fffcb9e7c  com_droga     24   D1  8b87a7a83  0.6660  0.2324  0.4392   \n",
       "\n",
       "          g-3     g-4  ...    c-90    c-91    c-92    c-93    c-94    c-95  \\\n",
       "0     -0.6208 -0.1944  ...  0.2862  0.2584  0.8076  0.5523 -0.1912  0.6584   \n",
       "5      0.2277  1.2810  ...  1.8390  1.1570 -1.0120  1.9010  1.4270  0.4519   \n",
       "6      5.9440 -2.1670  ...  0.1855  1.1720  0.8325  0.6486  0.8090  1.5880   \n",
       "17    -0.2618 -0.3310  ... -0.4718  1.0620  0.3601  0.4402  0.2655  0.5741   \n",
       "32     0.0603 -0.3156  ...  0.0946  0.0294  0.1041 -0.1413 -1.5430 -1.4180   \n",
       "...       ...     ...  ...     ...     ...     ...     ...     ...     ...   \n",
       "23802  2.0490  2.3170  ... -8.6300 -8.1490 -6.2900 -8.0970 -8.7330 -2.3780   \n",
       "23804  1.8750  0.9859  ... -0.6730  0.3175 -1.5510 -1.2800 -0.7632 -0.6736   \n",
       "23809 -0.5080 -0.4713  ...  0.1969  0.0262 -0.8121  0.3434  0.5372 -0.3246   \n",
       "23810  0.9905 -0.7178  ...  0.4286  0.4426  0.0423 -0.3195 -0.8086 -0.9798   \n",
       "23812  0.2044  0.8531  ... -0.1105  0.4258 -0.2012  0.1506  1.5230  0.7101   \n",
       "\n",
       "         c-96    c-97    c-98    c-99  \n",
       "0     -0.3981  0.2139  0.3801  0.4176  \n",
       "5      1.2120  0.3765  0.7848  1.3990  \n",
       "6      2.4670  0.0357  0.1351 -0.3179  \n",
       "17     0.8093 -0.0269  0.4259  0.9279  \n",
       "32     0.0691  0.1536  0.2948 -0.9860  \n",
       "...       ...     ...     ...     ...  \n",
       "23802 -8.4480 -4.4550 -5.7930 -3.7000  \n",
       "23804 -0.4097  0.2282 -0.3213 -0.0836  \n",
       "23809  0.0631  0.9171  0.5258  0.4680  \n",
       "23810 -0.2084 -0.1224 -0.2715  0.3689  \n",
       "23812  0.1732  0.7015 -0.6290  0.0740  \n",
       "\n",
       "[7772 rows x 877 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Um exemplo de aplicação seria filtrar somente tempo igual a 24. \n",
    "dados.query(\"tempo == 24\")"
   ]
  },
  {
   "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>id</th>\n",
       "      <th>tratamento</th>\n",
       "      <th>tempo</th>\n",
       "      <th>dose</th>\n",
       "      <th>droga</th>\n",
       "      <th>g-0</th>\n",
       "      <th>g-1</th>\n",
       "      <th>g-2</th>\n",
       "      <th>g-3</th>\n",
       "      <th>g-4</th>\n",
       "      <th>...</th>\n",
       "      <th>c-90</th>\n",
       "      <th>c-91</th>\n",
       "      <th>c-92</th>\n",
       "      <th>c-93</th>\n",
       "      <th>c-94</th>\n",
       "      <th>c-95</th>\n",
       "      <th>c-96</th>\n",
       "      <th>c-97</th>\n",
       "      <th>c-98</th>\n",
       "      <th>c-99</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>id_000644bb2</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>24</td>\n",
       "      <td>D1</td>\n",
       "      <td>b68db1d53</td>\n",
       "      <td>1.0620</td>\n",
       "      <td>0.5577</td>\n",
       "      <td>-0.2479</td>\n",
       "      <td>-0.6208</td>\n",
       "      <td>-0.1944</td>\n",
       "      <td>...</td>\n",
       "      <td>0.2862</td>\n",
       "      <td>0.2584</td>\n",
       "      <td>0.8076</td>\n",
       "      <td>0.5523</td>\n",
       "      <td>-0.1912</td>\n",
       "      <td>0.6584</td>\n",
       "      <td>-0.3981</td>\n",
       "      <td>0.2139</td>\n",
       "      <td>0.3801</td>\n",
       "      <td>0.4176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>id_000779bfc</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>72</td>\n",
       "      <td>D1</td>\n",
       "      <td>df89a8e5a</td>\n",
       "      <td>0.0743</td>\n",
       "      <td>0.4087</td>\n",
       "      <td>0.2991</td>\n",
       "      <td>0.0604</td>\n",
       "      <td>1.0190</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.4265</td>\n",
       "      <td>0.7543</td>\n",
       "      <td>0.4708</td>\n",
       "      <td>0.0230</td>\n",
       "      <td>0.2957</td>\n",
       "      <td>0.4899</td>\n",
       "      <td>0.1522</td>\n",
       "      <td>0.1241</td>\n",
       "      <td>0.6077</td>\n",
       "      <td>0.7371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>id_000a6266a</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>48</td>\n",
       "      <td>D1</td>\n",
       "      <td>18bb41b2c</td>\n",
       "      <td>0.6280</td>\n",
       "      <td>0.5817</td>\n",
       "      <td>1.5540</td>\n",
       "      <td>-0.0764</td>\n",
       "      <td>-0.0323</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.7250</td>\n",
       "      <td>-0.6297</td>\n",
       "      <td>0.6103</td>\n",
       "      <td>0.0223</td>\n",
       "      <td>-1.3240</td>\n",
       "      <td>-0.3174</td>\n",
       "      <td>-0.6417</td>\n",
       "      <td>-0.2187</td>\n",
       "      <td>-1.4080</td>\n",
       "      <td>0.6931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>id_0015fd391</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>48</td>\n",
       "      <td>D1</td>\n",
       "      <td>8c7f86626</td>\n",
       "      <td>-0.5138</td>\n",
       "      <td>-0.2491</td>\n",
       "      <td>-0.2656</td>\n",
       "      <td>0.5288</td>\n",
       "      <td>4.0620</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.0990</td>\n",
       "      <td>-0.6441</td>\n",
       "      <td>-5.6300</td>\n",
       "      <td>-1.3780</td>\n",
       "      <td>-0.8632</td>\n",
       "      <td>-1.2880</td>\n",
       "      <td>-1.6210</td>\n",
       "      <td>-0.8784</td>\n",
       "      <td>-0.3876</td>\n",
       "      <td>-0.8154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>id_001762a82</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>24</td>\n",
       "      <td>D1</td>\n",
       "      <td>e06749542</td>\n",
       "      <td>-0.6111</td>\n",
       "      <td>0.2941</td>\n",
       "      <td>-0.9901</td>\n",
       "      <td>0.2277</td>\n",
       "      <td>1.2810</td>\n",
       "      <td>...</td>\n",
       "      <td>1.8390</td>\n",
       "      <td>1.1570</td>\n",
       "      <td>-1.0120</td>\n",
       "      <td>1.9010</td>\n",
       "      <td>1.4270</td>\n",
       "      <td>0.4519</td>\n",
       "      <td>1.2120</td>\n",
       "      <td>0.3765</td>\n",
       "      <td>0.7848</td>\n",
       "      <td>1.3990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23804</th>\n",
       "      <td>id_fff506720</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>24</td>\n",
       "      <td>D1</td>\n",
       "      <td>74515bfd2</td>\n",
       "      <td>-1.0140</td>\n",
       "      <td>0.1709</td>\n",
       "      <td>-0.4291</td>\n",
       "      <td>1.8750</td>\n",
       "      <td>0.9859</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.6730</td>\n",
       "      <td>0.3175</td>\n",
       "      <td>-1.5510</td>\n",
       "      <td>-1.2800</td>\n",
       "      <td>-0.7632</td>\n",
       "      <td>-0.6736</td>\n",
       "      <td>-0.4097</td>\n",
       "      <td>0.2282</td>\n",
       "      <td>-0.3213</td>\n",
       "      <td>-0.0836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23807</th>\n",
       "      <td>id_fff7e6992</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>48</td>\n",
       "      <td>D1</td>\n",
       "      <td>a28556d51</td>\n",
       "      <td>0.1420</td>\n",
       "      <td>-0.3696</td>\n",
       "      <td>-0.0093</td>\n",
       "      <td>-0.2495</td>\n",
       "      <td>-0.0175</td>\n",
       "      <td>...</td>\n",
       "      <td>0.8775</td>\n",
       "      <td>0.5230</td>\n",
       "      <td>0.1589</td>\n",
       "      <td>0.7715</td>\n",
       "      <td>0.5497</td>\n",
       "      <td>0.6929</td>\n",
       "      <td>0.3738</td>\n",
       "      <td>0.8636</td>\n",
       "      <td>0.4494</td>\n",
       "      <td>0.1218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23808</th>\n",
       "      <td>id_fff8c2444</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>72</td>\n",
       "      <td>D1</td>\n",
       "      <td>6c3a459be</td>\n",
       "      <td>0.1608</td>\n",
       "      <td>-1.0500</td>\n",
       "      <td>0.2551</td>\n",
       "      <td>-0.2239</td>\n",
       "      <td>-0.2431</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0789</td>\n",
       "      <td>0.3538</td>\n",
       "      <td>0.0558</td>\n",
       "      <td>0.3377</td>\n",
       "      <td>-0.4753</td>\n",
       "      <td>-0.2504</td>\n",
       "      <td>-0.7415</td>\n",
       "      <td>0.8413</td>\n",
       "      <td>-0.4259</td>\n",
       "      <td>0.2434</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23812</th>\n",
       "      <td>id_fffcb9e7c</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>24</td>\n",
       "      <td>D1</td>\n",
       "      <td>8b87a7a83</td>\n",
       "      <td>0.6660</td>\n",
       "      <td>0.2324</td>\n",
       "      <td>0.4392</td>\n",
       "      <td>0.2044</td>\n",
       "      <td>0.8531</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1105</td>\n",
       "      <td>0.4258</td>\n",
       "      <td>-0.2012</td>\n",
       "      <td>0.1506</td>\n",
       "      <td>1.5230</td>\n",
       "      <td>0.7101</td>\n",
       "      <td>0.1732</td>\n",
       "      <td>0.7015</td>\n",
       "      <td>-0.6290</td>\n",
       "      <td>0.0740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23813</th>\n",
       "      <td>id_ffffdd77b</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>72</td>\n",
       "      <td>D1</td>\n",
       "      <td>972f41291</td>\n",
       "      <td>-0.8598</td>\n",
       "      <td>1.0240</td>\n",
       "      <td>-0.1361</td>\n",
       "      <td>0.7952</td>\n",
       "      <td>-0.3611</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.3890</td>\n",
       "      <td>-1.7450</td>\n",
       "      <td>-6.6300</td>\n",
       "      <td>-4.0950</td>\n",
       "      <td>-7.3860</td>\n",
       "      <td>-1.4160</td>\n",
       "      <td>-3.5770</td>\n",
       "      <td>-0.4775</td>\n",
       "      <td>-2.1500</td>\n",
       "      <td>-4.2520</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>12147 rows × 877 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 id tratamento  tempo dose      droga     g-0     g-1     g-2  \\\n",
       "0      id_000644bb2  com_droga     24   D1  b68db1d53  1.0620  0.5577 -0.2479   \n",
       "1      id_000779bfc  com_droga     72   D1  df89a8e5a  0.0743  0.4087  0.2991   \n",
       "2      id_000a6266a  com_droga     48   D1  18bb41b2c  0.6280  0.5817  1.5540   \n",
       "3      id_0015fd391  com_droga     48   D1  8c7f86626 -0.5138 -0.2491 -0.2656   \n",
       "5      id_001762a82  com_droga     24   D1  e06749542 -0.6111  0.2941 -0.9901   \n",
       "...             ...        ...    ...  ...        ...     ...     ...     ...   \n",
       "23804  id_fff506720  com_droga     24   D1  74515bfd2 -1.0140  0.1709 -0.4291   \n",
       "23807  id_fff7e6992  com_droga     48   D1  a28556d51  0.1420 -0.3696 -0.0093   \n",
       "23808  id_fff8c2444  com_droga     72   D1  6c3a459be  0.1608 -1.0500  0.2551   \n",
       "23812  id_fffcb9e7c  com_droga     24   D1  8b87a7a83  0.6660  0.2324  0.4392   \n",
       "23813  id_ffffdd77b  com_droga     72   D1  972f41291 -0.8598  1.0240 -0.1361   \n",
       "\n",
       "          g-3     g-4  ...    c-90    c-91    c-92    c-93    c-94    c-95  \\\n",
       "0     -0.6208 -0.1944  ...  0.2862  0.2584  0.8076  0.5523 -0.1912  0.6584   \n",
       "1      0.0604  1.0190  ... -0.4265  0.7543  0.4708  0.0230  0.2957  0.4899   \n",
       "2     -0.0764 -0.0323  ... -0.7250 -0.6297  0.6103  0.0223 -1.3240 -0.3174   \n",
       "3      0.5288  4.0620  ... -2.0990 -0.6441 -5.6300 -1.3780 -0.8632 -1.2880   \n",
       "5      0.2277  1.2810  ...  1.8390  1.1570 -1.0120  1.9010  1.4270  0.4519   \n",
       "...       ...     ...  ...     ...     ...     ...     ...     ...     ...   \n",
       "23804  1.8750  0.9859  ... -0.6730  0.3175 -1.5510 -1.2800 -0.7632 -0.6736   \n",
       "23807 -0.2495 -0.0175  ...  0.8775  0.5230  0.1589  0.7715  0.5497  0.6929   \n",
       "23808 -0.2239 -0.2431  ...  0.0789  0.3538  0.0558  0.3377 -0.4753 -0.2504   \n",
       "23812  0.2044  0.8531  ... -0.1105  0.4258 -0.2012  0.1506  1.5230  0.7101   \n",
       "23813  0.7952 -0.3611  ... -3.3890 -1.7450 -6.6300 -4.0950 -7.3860 -1.4160   \n",
       "\n",
       "         c-96    c-97    c-98    c-99  \n",
       "0     -0.3981  0.2139  0.3801  0.4176  \n",
       "1      0.1522  0.1241  0.6077  0.7371  \n",
       "2     -0.6417 -0.2187 -1.4080  0.6931  \n",
       "3     -1.6210 -0.8784 -0.3876 -0.8154  \n",
       "5      1.2120  0.3765  0.7848  1.3990  \n",
       "...       ...     ...     ...     ...  \n",
       "23804 -0.4097  0.2282 -0.3213 -0.0836  \n",
       "23807  0.3738  0.8636  0.4494  0.1218  \n",
       "23808 -0.7415  0.8413 -0.4259  0.2434  \n",
       "23812  0.1732  0.7015 -0.6290  0.0740  \n",
       "23813 -3.5770 -0.4775 -2.1500 -4.2520  \n",
       "\n",
       "[12147 rows x 877 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Utilizando o método query para filtrar somente dose D1\n",
    "dados.query(\"dose == 'D1'\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "X_Lg2XTu20ND"
   },
   "source": [
    "### Desafio 06: Renomear as colunas tirando o hífen.   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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>id</th>\n",
       "      <th>tratamento</th>\n",
       "      <th>tempo</th>\n",
       "      <th>dose</th>\n",
       "      <th>droga</th>\n",
       "      <th>g_0</th>\n",
       "      <th>g_1</th>\n",
       "      <th>g_2</th>\n",
       "      <th>g_3</th>\n",
       "      <th>g_4</th>\n",
       "      <th>...</th>\n",
       "      <th>c_90</th>\n",
       "      <th>c_91</th>\n",
       "      <th>c_92</th>\n",
       "      <th>c_93</th>\n",
       "      <th>c_94</th>\n",
       "      <th>c_95</th>\n",
       "      <th>c_96</th>\n",
       "      <th>c_97</th>\n",
       "      <th>c_98</th>\n",
       "      <th>c_99</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>id_000644bb2</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>24</td>\n",
       "      <td>D1</td>\n",
       "      <td>b68db1d53</td>\n",
       "      <td>1.0620</td>\n",
       "      <td>0.5577</td>\n",
       "      <td>-0.2479</td>\n",
       "      <td>-0.6208</td>\n",
       "      <td>-0.1944</td>\n",
       "      <td>...</td>\n",
       "      <td>0.2862</td>\n",
       "      <td>0.2584</td>\n",
       "      <td>0.8076</td>\n",
       "      <td>0.5523</td>\n",
       "      <td>-0.1912</td>\n",
       "      <td>0.6584</td>\n",
       "      <td>-0.3981</td>\n",
       "      <td>0.2139</td>\n",
       "      <td>0.3801</td>\n",
       "      <td>0.4176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>id_000779bfc</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>72</td>\n",
       "      <td>D1</td>\n",
       "      <td>df89a8e5a</td>\n",
       "      <td>0.0743</td>\n",
       "      <td>0.4087</td>\n",
       "      <td>0.2991</td>\n",
       "      <td>0.0604</td>\n",
       "      <td>1.0190</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.4265</td>\n",
       "      <td>0.7543</td>\n",
       "      <td>0.4708</td>\n",
       "      <td>0.0230</td>\n",
       "      <td>0.2957</td>\n",
       "      <td>0.4899</td>\n",
       "      <td>0.1522</td>\n",
       "      <td>0.1241</td>\n",
       "      <td>0.6077</td>\n",
       "      <td>0.7371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>id_000a6266a</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>48</td>\n",
       "      <td>D1</td>\n",
       "      <td>18bb41b2c</td>\n",
       "      <td>0.6280</td>\n",
       "      <td>0.5817</td>\n",
       "      <td>1.5540</td>\n",
       "      <td>-0.0764</td>\n",
       "      <td>-0.0323</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.7250</td>\n",
       "      <td>-0.6297</td>\n",
       "      <td>0.6103</td>\n",
       "      <td>0.0223</td>\n",
       "      <td>-1.3240</td>\n",
       "      <td>-0.3174</td>\n",
       "      <td>-0.6417</td>\n",
       "      <td>-0.2187</td>\n",
       "      <td>-1.4080</td>\n",
       "      <td>0.6931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>id_0015fd391</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>48</td>\n",
       "      <td>D1</td>\n",
       "      <td>8c7f86626</td>\n",
       "      <td>-0.5138</td>\n",
       "      <td>-0.2491</td>\n",
       "      <td>-0.2656</td>\n",
       "      <td>0.5288</td>\n",
       "      <td>4.0620</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.0990</td>\n",
       "      <td>-0.6441</td>\n",
       "      <td>-5.6300</td>\n",
       "      <td>-1.3780</td>\n",
       "      <td>-0.8632</td>\n",
       "      <td>-1.2880</td>\n",
       "      <td>-1.6210</td>\n",
       "      <td>-0.8784</td>\n",
       "      <td>-0.3876</td>\n",
       "      <td>-0.8154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>id_001626bd3</td>\n",
       "      <td>com_droga</td>\n",
       "      <td>72</td>\n",
       "      <td>D2</td>\n",
       "      <td>7cbed3131</td>\n",
       "      <td>-0.3254</td>\n",
       "      <td>-0.4009</td>\n",
       "      <td>0.9700</td>\n",
       "      <td>0.6919</td>\n",
       "      <td>1.4180</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0042</td>\n",
       "      <td>0.0048</td>\n",
       "      <td>0.6670</td>\n",
       "      <td>1.0690</td>\n",
       "      <td>0.5523</td>\n",
       "      <td>-0.3031</td>\n",
       "      <td>0.1094</td>\n",
       "      <td>0.2885</td>\n",
       "      <td>-0.3786</td>\n",
       "      <td>0.7125</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 877 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             id tratamento  tempo dose      droga     g_0     g_1     g_2  \\\n",
       "0  id_000644bb2  com_droga     24   D1  b68db1d53  1.0620  0.5577 -0.2479   \n",
       "1  id_000779bfc  com_droga     72   D1  df89a8e5a  0.0743  0.4087  0.2991   \n",
       "2  id_000a6266a  com_droga     48   D1  18bb41b2c  0.6280  0.5817  1.5540   \n",
       "3  id_0015fd391  com_droga     48   D1  8c7f86626 -0.5138 -0.2491 -0.2656   \n",
       "4  id_001626bd3  com_droga     72   D2  7cbed3131 -0.3254 -0.4009  0.9700   \n",
       "\n",
       "      g_3     g_4  ...    c_90    c_91    c_92    c_93    c_94    c_95  \\\n",
       "0 -0.6208 -0.1944  ...  0.2862  0.2584  0.8076  0.5523 -0.1912  0.6584   \n",
       "1  0.0604  1.0190  ... -0.4265  0.7543  0.4708  0.0230  0.2957  0.4899   \n",
       "2 -0.0764 -0.0323  ... -0.7250 -0.6297  0.6103  0.0223 -1.3240 -0.3174   \n",
       "3  0.5288  4.0620  ... -2.0990 -0.6441 -5.6300 -1.3780 -0.8632 -1.2880   \n",
       "4  0.6919  1.4180  ...  0.0042  0.0048  0.6670  1.0690  0.5523 -0.3031   \n",
       "\n",
       "     c_96    c_97    c_98    c_99  \n",
       "0 -0.3981  0.2139  0.3801  0.4176  \n",
       "1  0.1522  0.1241  0.6077  0.7371  \n",
       "2 -0.6417 -0.2187 -1.4080  0.6931  \n",
       "3 -1.6210 -0.8784 -0.3876 -0.8154  \n",
       "4  0.1094  0.2885 -0.3786  0.7125  \n",
       "\n",
       "[5 rows x 877 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# De modo a substituir o hífen por underline, utilizamos o método replace em uma list comprehension\n",
    "dados.columns = lst_cols = [i.replace('-','_') for i in dados.columns.to_list()]\n",
    "dados.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "X_Lg2XTu20ND"
   },
   "source": [
    "### Desafio 07: Deixar os gráficos bonitões. (Matplotlib.pyplot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Bibliotecas para customizar os gráficos\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import rc, rcParams\n",
    "\n",
    "# Define o estido do gráfico\n",
    "sns.set_theme(style=\"darkgrid\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Customizando o gráfico de tratamento\n",
    "fig, ax = plt.subplots(1, 1, figsize=(8,8))\n",
    "\n",
    "# Plot do gráfico\n",
    "sns.countplot(data=dados, x = 'tratamento', saturation=0.9, alpha=0.7, palette='YlGnBu')\n",
    "\n",
    "# Formatação do título\n",
    "plt.title('Balanceamento da classe tratamento', fontdict={'fontsize': 20}, weight='bold')\n",
    "\n",
    "# Configuração geral da fonte que será utilizada nos eixos\n",
    "font = {'fontsize':15, 'weight':'bold'}\n",
    "plt.tick_params(axis='both', labelsize=15)\n",
    "\n",
    "# Formatação do eixo x\n",
    "plt.xlabel('Tratamento', fontdict=font)\n",
    "\n",
    "# Formatação do eixo y\n",
    "plt.ylabel('Quantidade de tratamento', fontdict=font)\n",
    "\n",
    "fig.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "X_Lg2XTu20ND"
   },
   "source": [
    "### Desafio 08: Resumo do que você aprendeu com os dados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "ITVNag4B3c47"
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "colab": {
   "name": "Aula_01.ipynb",
   "provenance": [],
   "toc_visible": true
  },
  "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": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}