PyCitySchools/main.ipynb

{
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Student ID</th>\n",
       "      <th>student_name</th>\n",
       "      <th>gender</th>\n",
       "      <th>grade</th>\n",
       "      <th>school_name</th>\n",
       "      <th>reading_score</th>\n",
       "      <th>math_score</th>\n",
       "      <th>School ID</th>\n",
       "      <th>type</th>\n",
       "      <th>size</th>\n",
       "      <th>budget</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Paul Bradley</td>\n",
       "      <td>M</td>\n",
       "      <td>9th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>66</td>\n",
       "      <td>79</td>\n",
       "      <td>0</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Victor Smith</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>94</td>\n",
       "      <td>61</td>\n",
       "      <td>0</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Kevin Rodriguez</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>90</td>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Dr. Richard Scott</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>67</td>\n",
       "      <td>58</td>\n",
       "      <td>0</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Bonnie Ray</td>\n",
       "      <td>F</td>\n",
       "      <td>9th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>97</td>\n",
       "      <td>84</td>\n",
       "      <td>0</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Student ID       student_name gender grade        school_name  \\\n",
       "0           0       Paul Bradley      M   9th  Huang High School   \n",
       "1           1       Victor Smith      M  12th  Huang High School   \n",
       "2           2    Kevin Rodriguez      M  12th  Huang High School   \n",
       "3           3  Dr. Richard Scott      M  12th  Huang High School   \n",
       "4           4         Bonnie Ray      F   9th  Huang High School   \n",
       "\n",
       "   reading_score  math_score  School ID      type  size   budget  \n",
       "0             66          79          0  District  2917  1910635  \n",
       "1             94          61          0  District  2917  1910635  \n",
       "2             90          60          0  District  2917  1910635  \n",
       "3             67          58          0  District  2917  1910635  \n",
       "4             97          84          0  District  2917  1910635  "
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd \n",
    "\n",
    "#read schools and students csv files\n",
    "schools_list = pd.read_csv('Resources/schools_complete.csv')\n",
    "students_list = pd.read_csv('Resources/students_complete.csv')\n",
    "\n",
    "#combine dataset  \n",
    "school_list_complete = pd.merge(students_list, schools_list, how=\"left\", on=[\"school_name\", \"school_name\"])\n",
    "school_list_complete.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>School ID</th>\n",
       "      <th>school_name</th>\n",
       "      <th>type</th>\n",
       "      <th>size</th>\n",
       "      <th>budget</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Figueroa High School</td>\n",
       "      <td>District</td>\n",
       "      <td>2949</td>\n",
       "      <td>1884411</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Shelton High School</td>\n",
       "      <td>Charter</td>\n",
       "      <td>1761</td>\n",
       "      <td>1056600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Hernandez High School</td>\n",
       "      <td>District</td>\n",
       "      <td>4635</td>\n",
       "      <td>3022020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Griffin High School</td>\n",
       "      <td>Charter</td>\n",
       "      <td>1468</td>\n",
       "      <td>917500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>Wilson High School</td>\n",
       "      <td>Charter</td>\n",
       "      <td>2283</td>\n",
       "      <td>1319574</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>Cabrera High School</td>\n",
       "      <td>Charter</td>\n",
       "      <td>1858</td>\n",
       "      <td>1081356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>Bailey High School</td>\n",
       "      <td>District</td>\n",
       "      <td>4976</td>\n",
       "      <td>3124928</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>Holden High School</td>\n",
       "      <td>Charter</td>\n",
       "      <td>427</td>\n",
       "      <td>248087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>Pena High School</td>\n",
       "      <td>Charter</td>\n",
       "      <td>962</td>\n",
       "      <td>585858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10</td>\n",
       "      <td>Wright High School</td>\n",
       "      <td>Charter</td>\n",
       "      <td>1800</td>\n",
       "      <td>1049400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11</td>\n",
       "      <td>Rodriguez High School</td>\n",
       "      <td>District</td>\n",
       "      <td>3999</td>\n",
       "      <td>2547363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>12</td>\n",
       "      <td>Johnson High School</td>\n",
       "      <td>District</td>\n",
       "      <td>4761</td>\n",
       "      <td>3094650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>13</td>\n",
       "      <td>Ford High School</td>\n",
       "      <td>District</td>\n",
       "      <td>2739</td>\n",
       "      <td>1763916</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>14</td>\n",
       "      <td>Thomas High School</td>\n",
       "      <td>Charter</td>\n",
       "      <td>1635</td>\n",
       "      <td>1043130</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    School ID            school_name      type  size   budget\n",
       "0           0      Huang High School  District  2917  1910635\n",
       "1           1   Figueroa High School  District  2949  1884411\n",
       "2           2    Shelton High School   Charter  1761  1056600\n",
       "3           3  Hernandez High School  District  4635  3022020\n",
       "4           4    Griffin High School   Charter  1468   917500\n",
       "5           5     Wilson High School   Charter  2283  1319574\n",
       "6           6    Cabrera High School   Charter  1858  1081356\n",
       "7           7     Bailey High School  District  4976  3124928\n",
       "8           8     Holden High School   Charter   427   248087\n",
       "9           9       Pena High School   Charter   962   585858\n",
       "10         10     Wright High School   Charter  1800  1049400\n",
       "11         11  Rodriguez High School  District  3999  2547363\n",
       "12         12    Johnson High School  District  4761  3094650\n",
       "13         13       Ford High School  District  2739  1763916\n",
       "14         14     Thomas High School   Charter  1635  1043130"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "schools_list"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# District Summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Total number of unique schools \n",
    "#schools_list['school_name'].count()\n",
    "school_count = school_list_complete['school_name'].nunique()\n",
    "school_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "39170"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Total students \n",
    "student_count = school_list_complete['Student ID'].nunique()\n",
    "student_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "24649428"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Total budget\n",
    "total_budget = schools_list['budget'].sum()\n",
    "total_budget"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "78.98537145774827"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#average math score \n",
    "avg_math_score = school_list_complete['math_score'].mean()\n",
    "avg_math_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "81.87784018381414"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#average reading score\n",
    "avg_reading_score = school_list_complete['reading_score'].mean()\n",
    "avg_reading_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "74.9808526933878"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#% passing math \n",
    "pass_math_count = school_list_complete[school_list_complete['math_score'] >= 70].count()['student_name']\n",
    "pass_math_perc = pass_math_count/student_count*100\n",
    "pass_math_perc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "85.80546336482001"
      ]
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     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "#% passing reading\n",
    "pass_reading_count = school_list_complete[school_list_complete['reading_score'] >= 70].count()['student_name']\n",
    "pass_reading_perc = pass_reading_count/student_count*100\n",
    "pass_reading_perc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "65.17232575950983"
      ]
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     "execution_count": 10,
     "metadata": {},
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   ],
   "source": [
    "#% overall passing \n",
    "pass_math_reading_count = school_list_complete[(school_list_complete[\"math_score\"] >= 70) \n",
    "& (school_list_complete[\"reading_score\"] >= 70)].count()[\"student_name\"]\n",
    "overall_passing_rate = pass_math_reading_count /  float(student_count) * 100\n",
    "overall_passing_rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Total Schools</th>\n",
       "      <th>Total Students</th>\n",
       "      <th>Total Budget</th>\n",
       "      <th>Average Math Score</th>\n",
       "      <th>% Passing Math</th>\n",
       "      <th>% Passing Reading</th>\n",
       "      <th>% Overall Passing</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>15</td>\n",
       "      <td>39,170</td>\n",
       "      <td>$24,649,428.00</td>\n",
       "      <td>81.87784</td>\n",
       "      <td>74.980853</td>\n",
       "      <td>85.805463</td>\n",
       "      <td>65.172326</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Total Schools Total Students    Total Budget  Average Math Score  \\\n",
       "0             15         39,170  $24,649,428.00            81.87784   \n",
       "\n",
       "   % Passing Math  % Passing Reading  % Overall Passing  \n",
       "0       74.980853          85.805463          65.172326  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
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    }
   ],
   "source": [
    "district_summary = pd.DataFrame({'Total Schools' :[school_count],\n",
    "                        'Total Students' :[student_count],\n",
    "                        'Total Budget' :[total_budget],\n",
    "                        'Average Math Score' :[avg_math_score],\n",
    "                        'Average Math Score' :[avg_reading_score],\n",
    "                        '% Passing Math' :[pass_math_perc],\n",
    "                        '% Passing Reading' :[pass_reading_perc],\n",
    "                        '% Overall Passing' :[overall_passing_rate]\n",
    "                    })\n",
    "\n",
    "district_summary[\"Total Students\"] = district_summary[\"Total Students\"].map(\"{:,}\".format)\n",
    "district_summary[\"Total Budget\"] = district_summary[\"Total Budget\"].map(\"${:,.2f}\".format)\n",
    "\n",
    "district_summary"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# School Summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Use the code provided to select the school type\n",
    "school_types = schools_list.set_index([\"school_name\"])[\"type\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate the total student count\n",
    "per_school_counts = schools_list.set_index([\"school_name\"])[\"size\"].sort_index()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\icanhearme\\AppData\\Local\\Temp\\ipykernel_42120\\3621813686.py:2: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  per_school_budget = school_list_complete.groupby([\"school_name\"]).mean()[\"budget\"]\n"
     ]
    }
   ],
   "source": [
    "# Calculate the total school budget and per capita spending\n",
    "per_school_budget = school_list_complete.groupby([\"school_name\"]).mean()[\"budget\"]\n",
    "per_school_capita = per_school_budget / per_school_counts\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\icanhearme\\AppData\\Local\\Temp\\ipykernel_42120\\534456567.py:2: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  per_school_math = school_list_complete.groupby([\"school_name\"]).mean()[\"math_score\"]\n",
      "C:\\Users\\icanhearme\\AppData\\Local\\Temp\\ipykernel_42120\\534456567.py:3: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  per_school_reading = school_list_complete.groupby([\"school_name\"]).mean()[\"reading_score\"]\n"
     ]
    }
   ],
   "source": [
    "# Calculate the average test scores\n",
    "per_school_math = school_list_complete.groupby([\"school_name\"]).mean()[\"math_score\"]\n",
    "per_school_reading = school_list_complete.groupby([\"school_name\"]).mean()[\"reading_score\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate the number of schools with math scores of 70 or higher\n",
    "school_passing_math = school_list_complete[(school_list_complete[\"math_score\"] >= 70)].groupby([\"school_name\"]).count()['math_score']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate the number of schools with reading scores of 70 or higher\n",
    "school_passing_reading = school_list_complete[(school_list_complete[\"reading_score\"] >= 70)].groupby([\"school_name\"]).count()['reading_score']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Use the provided code to calculate the schools that passed both math and reading with scores of 70 or higher\n",
    "passing_math_and_reading = school_list_complete[\n",
    "    (school_list_complete[\"reading_score\"] >= 70) & (school_list_complete[\"math_score\"] >= 70)\n",
    "].groupby('school_name').count()['reading_score']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Use the provided code to calculate the passing rates\n",
    "per_school_passing_math = school_passing_math / per_school_counts * 100\n",
    "per_school_passing_reading = school_passing_reading / per_school_counts * 100\n",
    "overall_passing_rate = passing_math_and_reading/ per_school_counts * 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\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>School Type</th>\n",
       "      <th>Total Students</th>\n",
       "      <th>Total School Budget</th>\n",
       "      <th>Per Student Budget</th>\n",
       "      <th>Average Math Score</th>\n",
       "      <th>Average Reading Score</th>\n",
       "      <th>% Passing Math</th>\n",
       "      <th>% Passing Reading</th>\n",
       "      <th>% Overall Passing</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Bailey High School</th>\n",
       "      <td>District</td>\n",
       "      <td>4976</td>\n",
       "      <td>$3,124,928.00</td>\n",
       "      <td>$628.00</td>\n",
       "      <td>77.048432</td>\n",
       "      <td>81.033963</td>\n",
       "      <td>66.680064</td>\n",
       "      <td>81.933280</td>\n",
       "      <td>54.642283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabrera High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1858</td>\n",
       "      <td>$1,081,356.00</td>\n",
       "      <td>$582.00</td>\n",
       "      <td>83.061895</td>\n",
       "      <td>83.975780</td>\n",
       "      <td>94.133477</td>\n",
       "      <td>97.039828</td>\n",
       "      <td>91.334769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Figueroa High School</th>\n",
       "      <td>District</td>\n",
       "      <td>2949</td>\n",
       "      <td>$1,884,411.00</td>\n",
       "      <td>$639.00</td>\n",
       "      <td>76.711767</td>\n",
       "      <td>81.158020</td>\n",
       "      <td>65.988471</td>\n",
       "      <td>80.739234</td>\n",
       "      <td>53.204476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ford High School</th>\n",
       "      <td>District</td>\n",
       "      <td>2739</td>\n",
       "      <td>$1,763,916.00</td>\n",
       "      <td>$644.00</td>\n",
       "      <td>77.102592</td>\n",
       "      <td>80.746258</td>\n",
       "      <td>68.309602</td>\n",
       "      <td>79.299014</td>\n",
       "      <td>54.289887</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Griffin High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1468</td>\n",
       "      <td>$917,500.00</td>\n",
       "      <td>$625.00</td>\n",
       "      <td>83.351499</td>\n",
       "      <td>83.816757</td>\n",
       "      <td>93.392371</td>\n",
       "      <td>97.138965</td>\n",
       "      <td>90.599455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hernandez High School</th>\n",
       "      <td>District</td>\n",
       "      <td>4635</td>\n",
       "      <td>$3,022,020.00</td>\n",
       "      <td>$652.00</td>\n",
       "      <td>77.289752</td>\n",
       "      <td>80.934412</td>\n",
       "      <td>66.752967</td>\n",
       "      <td>80.862999</td>\n",
       "      <td>53.527508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Holden High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>427</td>\n",
       "      <td>$248,087.00</td>\n",
       "      <td>$581.00</td>\n",
       "      <td>83.803279</td>\n",
       "      <td>83.814988</td>\n",
       "      <td>92.505855</td>\n",
       "      <td>96.252927</td>\n",
       "      <td>89.227166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Huang High School</th>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>$1,910,635.00</td>\n",
       "      <td>$655.00</td>\n",
       "      <td>76.629414</td>\n",
       "      <td>81.182722</td>\n",
       "      <td>65.683922</td>\n",
       "      <td>81.316421</td>\n",
       "      <td>53.513884</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Johnson High School</th>\n",
       "      <td>District</td>\n",
       "      <td>4761</td>\n",
       "      <td>$3,094,650.00</td>\n",
       "      <td>$650.00</td>\n",
       "      <td>77.072464</td>\n",
       "      <td>80.966394</td>\n",
       "      <td>66.057551</td>\n",
       "      <td>81.222432</td>\n",
       "      <td>53.539172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pena High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>962</td>\n",
       "      <td>$585,858.00</td>\n",
       "      <td>$609.00</td>\n",
       "      <td>83.839917</td>\n",
       "      <td>84.044699</td>\n",
       "      <td>94.594595</td>\n",
       "      <td>95.945946</td>\n",
       "      <td>90.540541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rodriguez High School</th>\n",
       "      <td>District</td>\n",
       "      <td>3999</td>\n",
       "      <td>$2,547,363.00</td>\n",
       "      <td>$637.00</td>\n",
       "      <td>76.842711</td>\n",
       "      <td>80.744686</td>\n",
       "      <td>66.366592</td>\n",
       "      <td>80.220055</td>\n",
       "      <td>52.988247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shelton High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1761</td>\n",
       "      <td>$1,056,600.00</td>\n",
       "      <td>$600.00</td>\n",
       "      <td>83.359455</td>\n",
       "      <td>83.725724</td>\n",
       "      <td>93.867121</td>\n",
       "      <td>95.854628</td>\n",
       "      <td>89.892107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thomas High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1635</td>\n",
       "      <td>$1,043,130.00</td>\n",
       "      <td>$638.00</td>\n",
       "      <td>83.418349</td>\n",
       "      <td>83.848930</td>\n",
       "      <td>93.272171</td>\n",
       "      <td>97.308869</td>\n",
       "      <td>90.948012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wilson High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>2283</td>\n",
       "      <td>$1,319,574.00</td>\n",
       "      <td>$578.00</td>\n",
       "      <td>83.274201</td>\n",
       "      <td>83.989488</td>\n",
       "      <td>93.867718</td>\n",
       "      <td>96.539641</td>\n",
       "      <td>90.582567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wright High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1800</td>\n",
       "      <td>$1,049,400.00</td>\n",
       "      <td>$583.00</td>\n",
       "      <td>83.682222</td>\n",
       "      <td>83.955000</td>\n",
       "      <td>93.333333</td>\n",
       "      <td>96.611111</td>\n",
       "      <td>90.333333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      School Type  Total Students Total School Budget  \\\n",
       "Bailey High School       District            4976       $3,124,928.00   \n",
       "Cabrera High School       Charter            1858       $1,081,356.00   \n",
       "Figueroa High School     District            2949       $1,884,411.00   \n",
       "Ford High School         District            2739       $1,763,916.00   \n",
       "Griffin High School       Charter            1468         $917,500.00   \n",
       "Hernandez High School    District            4635       $3,022,020.00   \n",
       "Holden High School        Charter             427         $248,087.00   \n",
       "Huang High School        District            2917       $1,910,635.00   \n",
       "Johnson High School      District            4761       $3,094,650.00   \n",
       "Pena High School          Charter             962         $585,858.00   \n",
       "Rodriguez High School    District            3999       $2,547,363.00   \n",
       "Shelton High School       Charter            1761       $1,056,600.00   \n",
       "Thomas High School        Charter            1635       $1,043,130.00   \n",
       "Wilson High School        Charter            2283       $1,319,574.00   \n",
       "Wright High School        Charter            1800       $1,049,400.00   \n",
       "\n",
       "                      Per Student Budget  Average Math Score  \\\n",
       "Bailey High School               $628.00           77.048432   \n",
       "Cabrera High School              $582.00           83.061895   \n",
       "Figueroa High School             $639.00           76.711767   \n",
       "Ford High School                 $644.00           77.102592   \n",
       "Griffin High School              $625.00           83.351499   \n",
       "Hernandez High School            $652.00           77.289752   \n",
       "Holden High School               $581.00           83.803279   \n",
       "Huang High School                $655.00           76.629414   \n",
       "Johnson High School              $650.00           77.072464   \n",
       "Pena High School                 $609.00           83.839917   \n",
       "Rodriguez High School            $637.00           76.842711   \n",
       "Shelton High School              $600.00           83.359455   \n",
       "Thomas High School               $638.00           83.418349   \n",
       "Wilson High School               $578.00           83.274201   \n",
       "Wright High School               $583.00           83.682222   \n",
       "\n",
       "                       Average Reading Score  % Passing Math  \\\n",
       "Bailey High School                 81.033963       66.680064   \n",
       "Cabrera High School                83.975780       94.133477   \n",
       "Figueroa High School               81.158020       65.988471   \n",
       "Ford High School                   80.746258       68.309602   \n",
       "Griffin High School                83.816757       93.392371   \n",
       "Hernandez High School              80.934412       66.752967   \n",
       "Holden High School                 83.814988       92.505855   \n",
       "Huang High School                  81.182722       65.683922   \n",
       "Johnson High School                80.966394       66.057551   \n",
       "Pena High School                   84.044699       94.594595   \n",
       "Rodriguez High School              80.744686       66.366592   \n",
       "Shelton High School                83.725724       93.867121   \n",
       "Thomas High School                 83.848930       93.272171   \n",
       "Wilson High School                 83.989488       93.867718   \n",
       "Wright High School                 83.955000       93.333333   \n",
       "\n",
       "                       % Passing Reading  % Overall Passing  \n",
       "Bailey High School             81.933280          54.642283  \n",
       "Cabrera High School            97.039828          91.334769  \n",
       "Figueroa High School           80.739234          53.204476  \n",
       "Ford High School               79.299014          54.289887  \n",
       "Griffin High School            97.138965          90.599455  \n",
       "Hernandez High School          80.862999          53.527508  \n",
       "Holden High School             96.252927          89.227166  \n",
       "Huang High School              81.316421          53.513884  \n",
       "Johnson High School            81.222432          53.539172  \n",
       "Pena High School               95.945946          90.540541  \n",
       "Rodriguez High School          80.220055          52.988247  \n",
       "Shelton High School            95.854628          89.892107  \n",
       "Thomas High School             97.308869          90.948012  \n",
       "Wilson High School             96.539641          90.582567  \n",
       "Wright High School             96.611111          90.333333  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a DataFrame called `per_school_summary` with columns for the calculations above.\n",
    "per_school_summary = pd.DataFrame({\n",
    "                         'School Type': school_types\n",
    "                        , 'Total Students': per_school_counts\n",
    "                        , 'Total School Budget': per_school_budget\n",
    "                        , 'Per Student Budget': per_school_capita\n",
    "                        , 'Average Math Score': per_school_math\n",
    "                        , 'Average Reading Score': per_school_reading\n",
    "                        , '% Passing Math': per_school_passing_math\n",
    "                        , '% Passing Reading': per_school_passing_reading\n",
    "                        , '% Overall Passing': overall_passing_rate})\n",
    "\n",
    "# Formatting\n",
    "per_school_summary[\"Total School Budget\"] = per_school_summary[\"Total School Budget\"].map(\"${:,.2f}\".format)\n",
    "per_school_summary[\"Per Student Budget\"] = per_school_summary[\"Per Student Budget\"].map(\"${:,.2f}\".format)\n",
    "\n",
    "per_school_summary.index.name = None\n",
    "\n",
    "# Display the DataFrame\n",
    "per_school_summary"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Highest-Performing Schools (by % Overall Passing)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>School Type</th>\n",
       "      <th>Total Students</th>\n",
       "      <th>Total School Budget</th>\n",
       "      <th>Per Student Budget</th>\n",
       "      <th>Average Math Score</th>\n",
       "      <th>Average Reading Score</th>\n",
       "      <th>% Passing Math</th>\n",
       "      <th>% Passing Reading</th>\n",
       "      <th>% Overall Passing</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Cabrera High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1858</td>\n",
       "      <td>$1,081,356.00</td>\n",
       "      <td>$582.00</td>\n",
       "      <td>83.061895</td>\n",
       "      <td>83.975780</td>\n",
       "      <td>94.133477</td>\n",
       "      <td>97.039828</td>\n",
       "      <td>91.334769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thomas High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1635</td>\n",
       "      <td>$1,043,130.00</td>\n",
       "      <td>$638.00</td>\n",
       "      <td>83.418349</td>\n",
       "      <td>83.848930</td>\n",
       "      <td>93.272171</td>\n",
       "      <td>97.308869</td>\n",
       "      <td>90.948012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Griffin High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1468</td>\n",
       "      <td>$917,500.00</td>\n",
       "      <td>$625.00</td>\n",
       "      <td>83.351499</td>\n",
       "      <td>83.816757</td>\n",
       "      <td>93.392371</td>\n",
       "      <td>97.138965</td>\n",
       "      <td>90.599455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wilson High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>2283</td>\n",
       "      <td>$1,319,574.00</td>\n",
       "      <td>$578.00</td>\n",
       "      <td>83.274201</td>\n",
       "      <td>83.989488</td>\n",
       "      <td>93.867718</td>\n",
       "      <td>96.539641</td>\n",
       "      <td>90.582567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pena High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>962</td>\n",
       "      <td>$585,858.00</td>\n",
       "      <td>$609.00</td>\n",
       "      <td>83.839917</td>\n",
       "      <td>84.044699</td>\n",
       "      <td>94.594595</td>\n",
       "      <td>95.945946</td>\n",
       "      <td>90.540541</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    School Type  Total Students Total School Budget  \\\n",
       "Cabrera High School     Charter            1858       $1,081,356.00   \n",
       "Thomas High School      Charter            1635       $1,043,130.00   \n",
       "Griffin High School     Charter            1468         $917,500.00   \n",
       "Wilson High School      Charter            2283       $1,319,574.00   \n",
       "Pena High School        Charter             962         $585,858.00   \n",
       "\n",
       "                    Per Student Budget  Average Math Score  \\\n",
       "Cabrera High School            $582.00           83.061895   \n",
       "Thomas High School             $638.00           83.418349   \n",
       "Griffin High School            $625.00           83.351499   \n",
       "Wilson High School             $578.00           83.274201   \n",
       "Pena High School               $609.00           83.839917   \n",
       "\n",
       "                     Average Reading Score  % Passing Math  % Passing Reading  \\\n",
       "Cabrera High School              83.975780       94.133477          97.039828   \n",
       "Thomas High School               83.848930       93.272171          97.308869   \n",
       "Griffin High School              83.816757       93.392371          97.138965   \n",
       "Wilson High School               83.989488       93.867718          96.539641   \n",
       "Pena High School                 84.044699       94.594595          95.945946   \n",
       "\n",
       "                     % Overall Passing  \n",
       "Cabrera High School          91.334769  \n",
       "Thomas High School           90.948012  \n",
       "Griffin High School          90.599455  \n",
       "Wilson High School           90.582567  \n",
       "Pena High School             90.540541  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Sort the schools by `% Overall Passing` in descending order and display the top 5 rows.\n",
    "per_school_summary.sort_values(by='% Overall Passing', ascending=False).head()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Bottom Performing Schools (By % Overall Passing)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "        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>School Type</th>\n",
       "      <th>Total Students</th>\n",
       "      <th>Total School Budget</th>\n",
       "      <th>Per Student Budget</th>\n",
       "      <th>Average Math Score</th>\n",
       "      <th>Average Reading Score</th>\n",
       "      <th>% Passing Math</th>\n",
       "      <th>% Passing Reading</th>\n",
       "      <th>% Overall Passing</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Rodriguez High School</th>\n",
       "      <td>District</td>\n",
       "      <td>3999</td>\n",
       "      <td>$2,547,363.00</td>\n",
       "      <td>$637.00</td>\n",
       "      <td>76.842711</td>\n",
       "      <td>80.744686</td>\n",
       "      <td>66.366592</td>\n",
       "      <td>80.220055</td>\n",
       "      <td>52.988247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Figueroa High School</th>\n",
       "      <td>District</td>\n",
       "      <td>2949</td>\n",
       "      <td>$1,884,411.00</td>\n",
       "      <td>$639.00</td>\n",
       "      <td>76.711767</td>\n",
       "      <td>81.158020</td>\n",
       "      <td>65.988471</td>\n",
       "      <td>80.739234</td>\n",
       "      <td>53.204476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Huang High School</th>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>$1,910,635.00</td>\n",
       "      <td>$655.00</td>\n",
       "      <td>76.629414</td>\n",
       "      <td>81.182722</td>\n",
       "      <td>65.683922</td>\n",
       "      <td>81.316421</td>\n",
       "      <td>53.513884</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hernandez High School</th>\n",
       "      <td>District</td>\n",
       "      <td>4635</td>\n",
       "      <td>$3,022,020.00</td>\n",
       "      <td>$652.00</td>\n",
       "      <td>77.289752</td>\n",
       "      <td>80.934412</td>\n",
       "      <td>66.752967</td>\n",
       "      <td>80.862999</td>\n",
       "      <td>53.527508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Johnson High School</th>\n",
       "      <td>District</td>\n",
       "      <td>4761</td>\n",
       "      <td>$3,094,650.00</td>\n",
       "      <td>$650.00</td>\n",
       "      <td>77.072464</td>\n",
       "      <td>80.966394</td>\n",
       "      <td>66.057551</td>\n",
       "      <td>81.222432</td>\n",
       "      <td>53.539172</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      School Type  Total Students Total School Budget  \\\n",
       "Rodriguez High School    District            3999       $2,547,363.00   \n",
       "Figueroa High School     District            2949       $1,884,411.00   \n",
       "Huang High School        District            2917       $1,910,635.00   \n",
       "Hernandez High School    District            4635       $3,022,020.00   \n",
       "Johnson High School      District            4761       $3,094,650.00   \n",
       "\n",
       "                      Per Student Budget  Average Math Score  \\\n",
       "Rodriguez High School            $637.00           76.842711   \n",
       "Figueroa High School             $639.00           76.711767   \n",
       "Huang High School                $655.00           76.629414   \n",
       "Hernandez High School            $652.00           77.289752   \n",
       "Johnson High School              $650.00           77.072464   \n",
       "\n",
       "                       Average Reading Score  % Passing Math  \\\n",
       "Rodriguez High School              80.744686       66.366592   \n",
       "Figueroa High School               81.158020       65.988471   \n",
       "Huang High School                  81.182722       65.683922   \n",
       "Hernandez High School              80.934412       66.752967   \n",
       "Johnson High School                80.966394       66.057551   \n",
       "\n",
       "                       % Passing Reading  % Overall Passing  \n",
       "Rodriguez High School          80.220055          52.988247  \n",
       "Figueroa High School           80.739234          53.204476  \n",
       "Huang High School              81.316421          53.513884  \n",
       "Hernandez High School          80.862999          53.527508  \n",
       "Johnson High School            81.222432          53.539172  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Sort the schools by `% Overall Passing` in ascending order and display the top 5 rows.\n",
    "per_school_summary.sort_values(by='% Overall Passing', ascending=True).head()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Math Scores by Grade"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\icanhearme\\AppData\\Local\\Temp\\ipykernel_42120\\1191751550.py:8: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  ninth_graders_scores = ninth_graders.groupby('school_name').mean()\n",
      "C:\\Users\\icanhearme\\AppData\\Local\\Temp\\ipykernel_42120\\1191751550.py:9: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  tenth_graders_scores = tenth_graders.groupby('school_name').mean()\n",
      "C:\\Users\\icanhearme\\AppData\\Local\\Temp\\ipykernel_42120\\1191751550.py:10: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  eleventh_graders_scores = eleventh_graders.groupby('school_name').mean()\n",
      "C:\\Users\\icanhearme\\AppData\\Local\\Temp\\ipykernel_42120\\1191751550.py:11: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  twelfth_graders_scores = twelfth_graders.groupby('school_name').mean()\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>9th</th>\n",
       "      <th>10th</th>\n",
       "      <th>11th</th>\n",
       "      <th>12th</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Bailey High School</th>\n",
       "      <td>77.083676</td>\n",
       "      <td>76.996772</td>\n",
       "      <td>80.575873</td>\n",
       "      <td>76.492218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabrera High School</th>\n",
       "      <td>83.094697</td>\n",
       "      <td>83.154506</td>\n",
       "      <td>80.575873</td>\n",
       "      <td>83.277487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Figueroa High School</th>\n",
       "      <td>76.403037</td>\n",
       "      <td>76.539974</td>\n",
       "      <td>80.575873</td>\n",
       "      <td>77.151369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ford High School</th>\n",
       "      <td>77.361345</td>\n",
       "      <td>77.672316</td>\n",
       "      <td>80.575873</td>\n",
       "      <td>76.179963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Griffin High School</th>\n",
       "      <td>82.044010</td>\n",
       "      <td>84.229064</td>\n",
       "      <td>80.575873</td>\n",
       "      <td>83.356164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hernandez High School</th>\n",
       "      <td>77.438495</td>\n",
       "      <td>77.337408</td>\n",
       "      <td>80.575873</td>\n",
       "      <td>77.186567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Holden High School</th>\n",
       "      <td>83.787402</td>\n",
       "      <td>83.429825</td>\n",
       "      <td>80.575873</td>\n",
       "      <td>82.855422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Huang High School</th>\n",
       "      <td>77.027251</td>\n",
       "      <td>75.908735</td>\n",
       "      <td>80.575873</td>\n",
       "      <td>77.225641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Johnson High School</th>\n",
       "      <td>77.187857</td>\n",
       "      <td>76.691117</td>\n",
       "      <td>80.575873</td>\n",
       "      <td>76.863248</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pena High School</th>\n",
       "      <td>83.625455</td>\n",
       "      <td>83.372000</td>\n",
       "      <td>80.575873</td>\n",
       "      <td>84.121547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rodriguez High School</th>\n",
       "      <td>76.859966</td>\n",
       "      <td>76.612500</td>\n",
       "      <td>80.575873</td>\n",
       "      <td>77.690748</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shelton High School</th>\n",
       "      <td>83.420755</td>\n",
       "      <td>82.917411</td>\n",
       "      <td>80.575873</td>\n",
       "      <td>83.778976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thomas High School</th>\n",
       "      <td>83.590022</td>\n",
       "      <td>83.087886</td>\n",
       "      <td>80.575873</td>\n",
       "      <td>83.497041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wilson High School</th>\n",
       "      <td>83.085578</td>\n",
       "      <td>83.724422</td>\n",
       "      <td>80.575873</td>\n",
       "      <td>83.035794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wright High School</th>\n",
       "      <td>83.264706</td>\n",
       "      <td>84.010288</td>\n",
       "      <td>80.575873</td>\n",
       "      <td>83.644986</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             9th       10th       11th       12th\n",
       "Bailey High School     77.083676  76.996772  80.575873  76.492218\n",
       "Cabrera High School    83.094697  83.154506  80.575873  83.277487\n",
       "Figueroa High School   76.403037  76.539974  80.575873  77.151369\n",
       "Ford High School       77.361345  77.672316  80.575873  76.179963\n",
       "Griffin High School    82.044010  84.229064  80.575873  83.356164\n",
       "Hernandez High School  77.438495  77.337408  80.575873  77.186567\n",
       "Holden High School     83.787402  83.429825  80.575873  82.855422\n",
       "Huang High School      77.027251  75.908735  80.575873  77.225641\n",
       "Johnson High School    77.187857  76.691117  80.575873  76.863248\n",
       "Pena High School       83.625455  83.372000  80.575873  84.121547\n",
       "Rodriguez High School  76.859966  76.612500  80.575873  77.690748\n",
       "Shelton High School    83.420755  82.917411  80.575873  83.778976\n",
       "Thomas High School     83.590022  83.087886  80.575873  83.497041\n",
       "Wilson High School     83.085578  83.724422  80.575873  83.035794\n",
       "Wright High School     83.264706  84.010288  80.575873  83.644986"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Use the code provided to separate the data by grade\n",
    "ninth_graders = school_list_complete[(school_list_complete[\"grade\"] == \"9th\")]\n",
    "tenth_graders = school_list_complete[(school_list_complete[\"grade\"] == \"10th\")]\n",
    "eleventh_graders = school_list_complete[(school_list_complete[\"grade\"] == \"11th\")]\n",
    "twelfth_graders = school_list_complete[(school_list_complete[\"grade\"] == \"12th\")]\n",
    "\n",
    "# Group by \"school_name\" and take the mean of each.\n",
    "ninth_graders_scores = ninth_graders.groupby('school_name').mean()\n",
    "tenth_graders_scores = tenth_graders.groupby('school_name').mean()\n",
    "eleventh_graders_scores = eleventh_graders.groupby('school_name').mean()\n",
    "twelfth_graders_scores = twelfth_graders.groupby('school_name').mean()\n",
    "\n",
    "# # Use the code to select only the `math_score`.\n",
    "ninth_grade_math_scores = ninth_graders_scores[\"math_score\"]\n",
    "tenth_grader_math_scores = tenth_graders_scores[\"math_score\"]\n",
    "eleventh_grader_math_scores = eleventh_graders_scores.mean()[\"math_score\"]\n",
    "twelfth_grader_math_scores = twelfth_graders_scores[\"math_score\"]\n",
    "\n",
    "# # Combine each of the scores above into single DataFrame called `math_scores_by_grade`\n",
    "math_scores_by_grade = pd.DataFrame({'9th':ninth_grade_math_scores,'10th':tenth_grader_math_scores,'11th':eleventh_grader_math_scores,'12th':twelfth_grader_math_scores})\n",
    "\n",
    "# # Minor data wrangling\n",
    "math_scores_by_grade.index.name = None\n",
    "\n",
    "# # Display the DataFrame\n",
    "math_scores_by_grade"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Reading Score by Grade"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\icanhearme\\AppData\\Local\\Temp\\ipykernel_42120\\2833117024.py:8: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  ninth_graders_scores = ninth_graders.groupby('school_name').mean()\n",
      "C:\\Users\\icanhearme\\AppData\\Local\\Temp\\ipykernel_42120\\2833117024.py:9: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  tenth_graders_scores = tenth_graders.groupby('school_name').mean()\n",
      "C:\\Users\\icanhearme\\AppData\\Local\\Temp\\ipykernel_42120\\2833117024.py:10: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  eleventh_graders_scores = eleventh_graders.groupby('school_name').mean()\n",
      "C:\\Users\\icanhearme\\AppData\\Local\\Temp\\ipykernel_42120\\2833117024.py:11: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  twelfth_graders_scores = twelfth_graders.groupby('school_name').mean()\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>9th</th>\n",
       "      <th>10th</th>\n",
       "      <th>11th</th>\n",
       "      <th>12th</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Bailey High School</th>\n",
       "      <td>81.303155</td>\n",
       "      <td>80.907183</td>\n",
       "      <td>82.559485</td>\n",
       "      <td>80.912451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabrera High School</th>\n",
       "      <td>83.676136</td>\n",
       "      <td>84.253219</td>\n",
       "      <td>82.559485</td>\n",
       "      <td>84.287958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Figueroa High School</th>\n",
       "      <td>81.198598</td>\n",
       "      <td>81.408912</td>\n",
       "      <td>82.559485</td>\n",
       "      <td>81.384863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ford High School</th>\n",
       "      <td>80.632653</td>\n",
       "      <td>81.262712</td>\n",
       "      <td>82.559485</td>\n",
       "      <td>80.662338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Griffin High School</th>\n",
       "      <td>83.369193</td>\n",
       "      <td>83.706897</td>\n",
       "      <td>82.559485</td>\n",
       "      <td>84.013699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hernandez High School</th>\n",
       "      <td>80.866860</td>\n",
       "      <td>80.660147</td>\n",
       "      <td>82.559485</td>\n",
       "      <td>80.857143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Holden High School</th>\n",
       "      <td>83.677165</td>\n",
       "      <td>83.324561</td>\n",
       "      <td>82.559485</td>\n",
       "      <td>84.698795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Huang High School</th>\n",
       "      <td>81.290284</td>\n",
       "      <td>81.512386</td>\n",
       "      <td>82.559485</td>\n",
       "      <td>80.305983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Johnson High School</th>\n",
       "      <td>81.260714</td>\n",
       "      <td>80.773431</td>\n",
       "      <td>82.559485</td>\n",
       "      <td>81.227564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pena High School</th>\n",
       "      <td>83.807273</td>\n",
       "      <td>83.612000</td>\n",
       "      <td>82.559485</td>\n",
       "      <td>84.591160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rodriguez High School</th>\n",
       "      <td>80.993127</td>\n",
       "      <td>80.629808</td>\n",
       "      <td>82.559485</td>\n",
       "      <td>80.376426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shelton High School</th>\n",
       "      <td>84.122642</td>\n",
       "      <td>83.441964</td>\n",
       "      <td>82.559485</td>\n",
       "      <td>82.781671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thomas High School</th>\n",
       "      <td>83.728850</td>\n",
       "      <td>84.254157</td>\n",
       "      <td>82.559485</td>\n",
       "      <td>83.831361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wilson High School</th>\n",
       "      <td>83.939778</td>\n",
       "      <td>84.021452</td>\n",
       "      <td>82.559485</td>\n",
       "      <td>84.317673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wright High School</th>\n",
       "      <td>83.833333</td>\n",
       "      <td>83.812757</td>\n",
       "      <td>82.559485</td>\n",
       "      <td>84.073171</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             9th       10th       11th       12th\n",
       "Bailey High School     81.303155  80.907183  82.559485  80.912451\n",
       "Cabrera High School    83.676136  84.253219  82.559485  84.287958\n",
       "Figueroa High School   81.198598  81.408912  82.559485  81.384863\n",
       "Ford High School       80.632653  81.262712  82.559485  80.662338\n",
       "Griffin High School    83.369193  83.706897  82.559485  84.013699\n",
       "Hernandez High School  80.866860  80.660147  82.559485  80.857143\n",
       "Holden High School     83.677165  83.324561  82.559485  84.698795\n",
       "Huang High School      81.290284  81.512386  82.559485  80.305983\n",
       "Johnson High School    81.260714  80.773431  82.559485  81.227564\n",
       "Pena High School       83.807273  83.612000  82.559485  84.591160\n",
       "Rodriguez High School  80.993127  80.629808  82.559485  80.376426\n",
       "Shelton High School    84.122642  83.441964  82.559485  82.781671\n",
       "Thomas High School     83.728850  84.254157  82.559485  83.831361\n",
       "Wilson High School     83.939778  84.021452  82.559485  84.317673\n",
       "Wright High School     83.833333  83.812757  82.559485  84.073171"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Use the code provided to separate the data by grade\n",
    "ninth_graders = school_list_complete[(school_list_complete[\"grade\"] == \"9th\")]\n",
    "tenth_graders = school_list_complete[(school_list_complete[\"grade\"] == \"10th\")]\n",
    "eleventh_graders = school_list_complete[(school_list_complete[\"grade\"] == \"11th\")]\n",
    "twelfth_graders = school_list_complete[(school_list_complete[\"grade\"] == \"12th\")]\n",
    "\n",
    "# Group by \"school_name\" and take the mean of each.\n",
    "ninth_graders_scores = ninth_graders.groupby('school_name').mean()\n",
    "tenth_graders_scores = tenth_graders.groupby('school_name').mean()\n",
    "eleventh_graders_scores = eleventh_graders.groupby('school_name').mean()\n",
    "twelfth_graders_scores = twelfth_graders.groupby('school_name').mean()\n",
    "\n",
    "# # Use the code to select only the `math_score`.\n",
    "ninth_grade_reading_scores = ninth_graders_scores[\"reading_score\"]\n",
    "tenth_grader_reading_scores = tenth_graders_scores[\"reading_score\"]\n",
    "eleventh_grader_reading_scores = eleventh_graders_scores.mean()[\"reading_score\"]\n",
    "twelfth_grader_reading_scores = twelfth_graders_scores[\"reading_score\"]\n",
    "\n",
    "# # Combine each of the scores above into single DataFrame called `math_scores_by_grade`\n",
    "reading_scores_by_grade = pd.DataFrame({'9th':ninth_grade_reading_scores,'10th':tenth_grader_reading_scores,'11th':eleventh_grader_reading_scores,'12th':twelfth_grader_reading_scores})\n",
    "\n",
    "# # Minor data wrangling\n",
    "reading_scores_by_grade = reading_scores_by_grade[[\"9th\", \"10th\", \"11th\", \"12th\"]]\n",
    "reading_scores_by_grade.index.name = None\n",
    "\n",
    "# # Display the DataFrame\n",
    "reading_scores_by_grade"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Scores by School Spending"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Establish the bins \n",
    "spending_bins = [0, 585, 630, 645, 680]\n",
    "labelx = [\"<$585\", \"$585-630\", \"$630-645\", \"$645-680\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a copy of the school summary since it has the \"Per Student Budget\" \n",
    "school_spending_df = per_school_summary.copy()"
   ]
  },
  {
   "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>School Type</th>\n",
       "      <th>Total Students</th>\n",
       "      <th>Total School Budget</th>\n",
       "      <th>Per Student Budget</th>\n",
       "      <th>Average Math Score</th>\n",
       "      <th>Average Reading Score</th>\n",
       "      <th>% Passing Math</th>\n",
       "      <th>% Passing Reading</th>\n",
       "      <th>% Overall Passing</th>\n",
       "      <th>Spending Ranges (Per Student)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Bailey High School</th>\n",
       "      <td>District</td>\n",
       "      <td>4976</td>\n",
       "      <td>$3,124,928.00</td>\n",
       "      <td>$628.00</td>\n",
       "      <td>77.048432</td>\n",
       "      <td>81.033963</td>\n",
       "      <td>66.680064</td>\n",
       "      <td>81.933280</td>\n",
       "      <td>54.642283</td>\n",
       "      <td>$585-630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabrera High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1858</td>\n",
       "      <td>$1,081,356.00</td>\n",
       "      <td>$582.00</td>\n",
       "      <td>83.061895</td>\n",
       "      <td>83.975780</td>\n",
       "      <td>94.133477</td>\n",
       "      <td>97.039828</td>\n",
       "      <td>91.334769</td>\n",
       "      <td>&lt;$585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Figueroa High School</th>\n",
       "      <td>District</td>\n",
       "      <td>2949</td>\n",
       "      <td>$1,884,411.00</td>\n",
       "      <td>$639.00</td>\n",
       "      <td>76.711767</td>\n",
       "      <td>81.158020</td>\n",
       "      <td>65.988471</td>\n",
       "      <td>80.739234</td>\n",
       "      <td>53.204476</td>\n",
       "      <td>$630-645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ford High School</th>\n",
       "      <td>District</td>\n",
       "      <td>2739</td>\n",
       "      <td>$1,763,916.00</td>\n",
       "      <td>$644.00</td>\n",
       "      <td>77.102592</td>\n",
       "      <td>80.746258</td>\n",
       "      <td>68.309602</td>\n",
       "      <td>79.299014</td>\n",
       "      <td>54.289887</td>\n",
       "      <td>$630-645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Griffin High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1468</td>\n",
       "      <td>$917,500.00</td>\n",
       "      <td>$625.00</td>\n",
       "      <td>83.351499</td>\n",
       "      <td>83.816757</td>\n",
       "      <td>93.392371</td>\n",
       "      <td>97.138965</td>\n",
       "      <td>90.599455</td>\n",
       "      <td>$585-630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hernandez High School</th>\n",
       "      <td>District</td>\n",
       "      <td>4635</td>\n",
       "      <td>$3,022,020.00</td>\n",
       "      <td>$652.00</td>\n",
       "      <td>77.289752</td>\n",
       "      <td>80.934412</td>\n",
       "      <td>66.752967</td>\n",
       "      <td>80.862999</td>\n",
       "      <td>53.527508</td>\n",
       "      <td>$645-680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Holden High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>427</td>\n",
       "      <td>$248,087.00</td>\n",
       "      <td>$581.00</td>\n",
       "      <td>83.803279</td>\n",
       "      <td>83.814988</td>\n",
       "      <td>92.505855</td>\n",
       "      <td>96.252927</td>\n",
       "      <td>89.227166</td>\n",
       "      <td>&lt;$585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Huang High School</th>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>$1,910,635.00</td>\n",
       "      <td>$655.00</td>\n",
       "      <td>76.629414</td>\n",
       "      <td>81.182722</td>\n",
       "      <td>65.683922</td>\n",
       "      <td>81.316421</td>\n",
       "      <td>53.513884</td>\n",
       "      <td>$645-680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Johnson High School</th>\n",
       "      <td>District</td>\n",
       "      <td>4761</td>\n",
       "      <td>$3,094,650.00</td>\n",
       "      <td>$650.00</td>\n",
       "      <td>77.072464</td>\n",
       "      <td>80.966394</td>\n",
       "      <td>66.057551</td>\n",
       "      <td>81.222432</td>\n",
       "      <td>53.539172</td>\n",
       "      <td>$645-680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pena High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>962</td>\n",
       "      <td>$585,858.00</td>\n",
       "      <td>$609.00</td>\n",
       "      <td>83.839917</td>\n",
       "      <td>84.044699</td>\n",
       "      <td>94.594595</td>\n",
       "      <td>95.945946</td>\n",
       "      <td>90.540541</td>\n",
       "      <td>$585-630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rodriguez High School</th>\n",
       "      <td>District</td>\n",
       "      <td>3999</td>\n",
       "      <td>$2,547,363.00</td>\n",
       "      <td>$637.00</td>\n",
       "      <td>76.842711</td>\n",
       "      <td>80.744686</td>\n",
       "      <td>66.366592</td>\n",
       "      <td>80.220055</td>\n",
       "      <td>52.988247</td>\n",
       "      <td>$630-645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shelton High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1761</td>\n",
       "      <td>$1,056,600.00</td>\n",
       "      <td>$600.00</td>\n",
       "      <td>83.359455</td>\n",
       "      <td>83.725724</td>\n",
       "      <td>93.867121</td>\n",
       "      <td>95.854628</td>\n",
       "      <td>89.892107</td>\n",
       "      <td>$585-630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thomas High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1635</td>\n",
       "      <td>$1,043,130.00</td>\n",
       "      <td>$638.00</td>\n",
       "      <td>83.418349</td>\n",
       "      <td>83.848930</td>\n",
       "      <td>93.272171</td>\n",
       "      <td>97.308869</td>\n",
       "      <td>90.948012</td>\n",
       "      <td>$630-645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wilson High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>2283</td>\n",
       "      <td>$1,319,574.00</td>\n",
       "      <td>$578.00</td>\n",
       "      <td>83.274201</td>\n",
       "      <td>83.989488</td>\n",
       "      <td>93.867718</td>\n",
       "      <td>96.539641</td>\n",
       "      <td>90.582567</td>\n",
       "      <td>&lt;$585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wright High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1800</td>\n",
       "      <td>$1,049,400.00</td>\n",
       "      <td>$583.00</td>\n",
       "      <td>83.682222</td>\n",
       "      <td>83.955000</td>\n",
       "      <td>93.333333</td>\n",
       "      <td>96.611111</td>\n",
       "      <td>90.333333</td>\n",
       "      <td>&lt;$585</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      School Type  Total Students Total School Budget  \\\n",
       "Bailey High School       District            4976       $3,124,928.00   \n",
       "Cabrera High School       Charter            1858       $1,081,356.00   \n",
       "Figueroa High School     District            2949       $1,884,411.00   \n",
       "Ford High School         District            2739       $1,763,916.00   \n",
       "Griffin High School       Charter            1468         $917,500.00   \n",
       "Hernandez High School    District            4635       $3,022,020.00   \n",
       "Holden High School        Charter             427         $248,087.00   \n",
       "Huang High School        District            2917       $1,910,635.00   \n",
       "Johnson High School      District            4761       $3,094,650.00   \n",
       "Pena High School          Charter             962         $585,858.00   \n",
       "Rodriguez High School    District            3999       $2,547,363.00   \n",
       "Shelton High School       Charter            1761       $1,056,600.00   \n",
       "Thomas High School        Charter            1635       $1,043,130.00   \n",
       "Wilson High School        Charter            2283       $1,319,574.00   \n",
       "Wright High School        Charter            1800       $1,049,400.00   \n",
       "\n",
       "                      Per Student Budget  Average Math Score  \\\n",
       "Bailey High School               $628.00           77.048432   \n",
       "Cabrera High School              $582.00           83.061895   \n",
       "Figueroa High School             $639.00           76.711767   \n",
       "Ford High School                 $644.00           77.102592   \n",
       "Griffin High School              $625.00           83.351499   \n",
       "Hernandez High School            $652.00           77.289752   \n",
       "Holden High School               $581.00           83.803279   \n",
       "Huang High School                $655.00           76.629414   \n",
       "Johnson High School              $650.00           77.072464   \n",
       "Pena High School                 $609.00           83.839917   \n",
       "Rodriguez High School            $637.00           76.842711   \n",
       "Shelton High School              $600.00           83.359455   \n",
       "Thomas High School               $638.00           83.418349   \n",
       "Wilson High School               $578.00           83.274201   \n",
       "Wright High School               $583.00           83.682222   \n",
       "\n",
       "                       Average Reading Score  % Passing Math  \\\n",
       "Bailey High School                 81.033963       66.680064   \n",
       "Cabrera High School                83.975780       94.133477   \n",
       "Figueroa High School               81.158020       65.988471   \n",
       "Ford High School                   80.746258       68.309602   \n",
       "Griffin High School                83.816757       93.392371   \n",
       "Hernandez High School              80.934412       66.752967   \n",
       "Holden High School                 83.814988       92.505855   \n",
       "Huang High School                  81.182722       65.683922   \n",
       "Johnson High School                80.966394       66.057551   \n",
       "Pena High School                   84.044699       94.594595   \n",
       "Rodriguez High School              80.744686       66.366592   \n",
       "Shelton High School                83.725724       93.867121   \n",
       "Thomas High School                 83.848930       93.272171   \n",
       "Wilson High School                 83.989488       93.867718   \n",
       "Wright High School                 83.955000       93.333333   \n",
       "\n",
       "                       % Passing Reading  % Overall Passing  \\\n",
       "Bailey High School             81.933280          54.642283   \n",
       "Cabrera High School            97.039828          91.334769   \n",
       "Figueroa High School           80.739234          53.204476   \n",
       "Ford High School               79.299014          54.289887   \n",
       "Griffin High School            97.138965          90.599455   \n",
       "Hernandez High School          80.862999          53.527508   \n",
       "Holden High School             96.252927          89.227166   \n",
       "Huang High School              81.316421          53.513884   \n",
       "Johnson High School            81.222432          53.539172   \n",
       "Pena High School               95.945946          90.540541   \n",
       "Rodriguez High School          80.220055          52.988247   \n",
       "Shelton High School            95.854628          89.892107   \n",
       "Thomas High School             97.308869          90.948012   \n",
       "Wilson High School             96.539641          90.582567   \n",
       "Wright High School             96.611111          90.333333   \n",
       "\n",
       "                      Spending Ranges (Per Student)  \n",
       "Bailey High School                         $585-630  \n",
       "Cabrera High School                           <$585  \n",
       "Figueroa High School                       $630-645  \n",
       "Ford High School                           $630-645  \n",
       "Griffin High School                        $585-630  \n",
       "Hernandez High School                      $645-680  \n",
       "Holden High School                            <$585  \n",
       "Huang High School                          $645-680  \n",
       "Johnson High School                        $645-680  \n",
       "Pena High School                           $585-630  \n",
       "Rodriguez High School                      $630-645  \n",
       "Shelton High School                        $585-630  \n",
       "Thomas High School                         $630-645  \n",
       "Wilson High School                            <$585  \n",
       "Wright High School                            <$585  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Use `pd.cut` to categorize spending based on the bins.\n",
    "school_spending_df[\"Spending Ranges (Per Student)\"] = pd.cut(x=per_school_capita, bins=spending_bins, labels=labelx, right=False)\n",
    "school_spending_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\icanhearme\\AppData\\Local\\Temp\\ipykernel_42120\\4149390191.py:2: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  spending_math_scores = school_spending_df.groupby([\"Spending Ranges (Per Student)\"]).mean()[\"Average Math Score\"]\n",
      "C:\\Users\\icanhearme\\AppData\\Local\\Temp\\ipykernel_42120\\4149390191.py:3: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  spending_reading_scores = school_spending_df.groupby([\"Spending Ranges (Per Student)\"]).mean()[\"Average Reading Score\"]\n",
      "C:\\Users\\icanhearme\\AppData\\Local\\Temp\\ipykernel_42120\\4149390191.py:4: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  spending_passing_math = school_spending_df.groupby([\"Spending Ranges (Per Student)\"]).mean()[\"% Passing Math\"]\n",
      "C:\\Users\\icanhearme\\AppData\\Local\\Temp\\ipykernel_42120\\4149390191.py:5: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  spending_passing_reading = school_spending_df.groupby([\"Spending Ranges (Per Student)\"]).mean()[\"% Passing Reading\"]\n",
      "C:\\Users\\icanhearme\\AppData\\Local\\Temp\\ipykernel_42120\\4149390191.py:6: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  overall_passing_spending = school_spending_df.groupby([\"Spending Ranges (Per Student)\"]).mean()[\"% Overall Passing\"]\n"
     ]
    }
   ],
   "source": [
    "#  Calculate averages for the desired columns. \n",
    "spending_math_scores = school_spending_df.groupby([\"Spending Ranges (Per Student)\"]).mean()[\"Average Math Score\"]\n",
    "spending_reading_scores = school_spending_df.groupby([\"Spending Ranges (Per Student)\"]).mean()[\"Average Reading Score\"]\n",
    "spending_passing_math = school_spending_df.groupby([\"Spending Ranges (Per Student)\"]).mean()[\"% Passing Math\"]\n",
    "spending_passing_reading = school_spending_df.groupby([\"Spending Ranges (Per Student)\"]).mean()[\"% Passing Reading\"]\n",
    "overall_passing_spending = school_spending_df.groupby([\"Spending Ranges (Per Student)\"]).mean()[\"% Overall Passing\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Average Math Score</th>\n",
       "      <th>Average Reading Score</th>\n",
       "      <th>% Passing Math</th>\n",
       "      <th>% Passing Reading</th>\n",
       "      <th>% Overall Passing</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Spending Ranges (Per Student)</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>&lt;$585</th>\n",
       "      <td>83.455399</td>\n",
       "      <td>83.933814</td>\n",
       "      <td>93.460096</td>\n",
       "      <td>96.610877</td>\n",
       "      <td>90.369459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$585-630</th>\n",
       "      <td>81.899826</td>\n",
       "      <td>83.155286</td>\n",
       "      <td>87.133538</td>\n",
       "      <td>92.718205</td>\n",
       "      <td>81.418596</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$630-645</th>\n",
       "      <td>78.518855</td>\n",
       "      <td>81.624473</td>\n",
       "      <td>73.484209</td>\n",
       "      <td>84.391793</td>\n",
       "      <td>62.857656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$645-680</th>\n",
       "      <td>76.997210</td>\n",
       "      <td>81.027843</td>\n",
       "      <td>66.164813</td>\n",
       "      <td>81.133951</td>\n",
       "      <td>53.526855</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               Average Math Score  Average Reading Score  \\\n",
       "Spending Ranges (Per Student)                                              \n",
       "<$585                                   83.455399              83.933814   \n",
       "$585-630                                81.899826              83.155286   \n",
       "$630-645                                78.518855              81.624473   \n",
       "$645-680                                76.997210              81.027843   \n",
       "\n",
       "                               % Passing Math  % Passing Reading  \\\n",
       "Spending Ranges (Per Student)                                      \n",
       "<$585                               93.460096          96.610877   \n",
       "$585-630                            87.133538          92.718205   \n",
       "$630-645                            73.484209          84.391793   \n",
       "$645-680                            66.164813          81.133951   \n",
       "\n",
       "                               % Overall Passing  \n",
       "Spending Ranges (Per Student)                     \n",
       "<$585                                  90.369459  \n",
       "$585-630                               81.418596  \n",
       "$630-645                               62.857656  \n",
       "$645-680                               53.526855  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Assemble into DataFrame\n",
    "spending_summary = pd.DataFrame({\n",
    "    'Average Math Score': spending_math_scores, \n",
    "    'Average Reading Score': spending_reading_scores, \n",
    "    '% Passing Math': spending_passing_math, \n",
    "    '% Passing Reading': spending_passing_reading,\n",
    "    '% Overall Passing': overall_passing_spending,\n",
    "})\n",
    "\n",
    "# Display results\n",
    "spending_summary"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Scores by School Size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Establish the bins.\n",
    "size_bins = [0, 1000, 2000, 5000]\n",
    "labels = [\"Small (<1000)\", \"Medium (1000-2000)\", \"Large (2000-5000)\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "    }\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>School Type</th>\n",
       "      <th>Total Students</th>\n",
       "      <th>Total School Budget</th>\n",
       "      <th>Per Student Budget</th>\n",
       "      <th>Average Math Score</th>\n",
       "      <th>Average Reading Score</th>\n",
       "      <th>% Passing Math</th>\n",
       "      <th>% Passing Reading</th>\n",
       "      <th>% Overall Passing</th>\n",
       "      <th>School Size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Bailey High School</th>\n",
       "      <td>District</td>\n",
       "      <td>4976</td>\n",
       "      <td>$3,124,928.00</td>\n",
       "      <td>$628.00</td>\n",
       "      <td>77.048432</td>\n",
       "      <td>81.033963</td>\n",
       "      <td>66.680064</td>\n",
       "      <td>81.933280</td>\n",
       "      <td>54.642283</td>\n",
       "      <td>Large (2000-5000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabrera High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1858</td>\n",
       "      <td>$1,081,356.00</td>\n",
       "      <td>$582.00</td>\n",
       "      <td>83.061895</td>\n",
       "      <td>83.975780</td>\n",
       "      <td>94.133477</td>\n",
       "      <td>97.039828</td>\n",
       "      <td>91.334769</td>\n",
       "      <td>Medium (1000-2000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Figueroa High School</th>\n",
       "      <td>District</td>\n",
       "      <td>2949</td>\n",
       "      <td>$1,884,411.00</td>\n",
       "      <td>$639.00</td>\n",
       "      <td>76.711767</td>\n",
       "      <td>81.158020</td>\n",
       "      <td>65.988471</td>\n",
       "      <td>80.739234</td>\n",
       "      <td>53.204476</td>\n",
       "      <td>Large (2000-5000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ford High School</th>\n",
       "      <td>District</td>\n",
       "      <td>2739</td>\n",
       "      <td>$1,763,916.00</td>\n",
       "      <td>$644.00</td>\n",
       "      <td>77.102592</td>\n",
       "      <td>80.746258</td>\n",
       "      <td>68.309602</td>\n",
       "      <td>79.299014</td>\n",
       "      <td>54.289887</td>\n",
       "      <td>Large (2000-5000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Griffin High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1468</td>\n",
       "      <td>$917,500.00</td>\n",
       "      <td>$625.00</td>\n",
       "      <td>83.351499</td>\n",
       "      <td>83.816757</td>\n",
       "      <td>93.392371</td>\n",
       "      <td>97.138965</td>\n",
       "      <td>90.599455</td>\n",
       "      <td>Medium (1000-2000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hernandez High School</th>\n",
       "      <td>District</td>\n",
       "      <td>4635</td>\n",
       "      <td>$3,022,020.00</td>\n",
       "      <td>$652.00</td>\n",
       "      <td>77.289752</td>\n",
       "      <td>80.934412</td>\n",
       "      <td>66.752967</td>\n",
       "      <td>80.862999</td>\n",
       "      <td>53.527508</td>\n",
       "      <td>Large (2000-5000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Holden High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>427</td>\n",
       "      <td>$248,087.00</td>\n",
       "      <td>$581.00</td>\n",
       "      <td>83.803279</td>\n",
       "      <td>83.814988</td>\n",
       "      <td>92.505855</td>\n",
       "      <td>96.252927</td>\n",
       "      <td>89.227166</td>\n",
       "      <td>Small (&lt;1000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Huang High School</th>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>$1,910,635.00</td>\n",
       "      <td>$655.00</td>\n",
       "      <td>76.629414</td>\n",
       "      <td>81.182722</td>\n",
       "      <td>65.683922</td>\n",
       "      <td>81.316421</td>\n",
       "      <td>53.513884</td>\n",
       "      <td>Large (2000-5000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Johnson High School</th>\n",
       "      <td>District</td>\n",
       "      <td>4761</td>\n",
       "      <td>$3,094,650.00</td>\n",
       "      <td>$650.00</td>\n",
       "      <td>77.072464</td>\n",
       "      <td>80.966394</td>\n",
       "      <td>66.057551</td>\n",
       "      <td>81.222432</td>\n",
       "      <td>53.539172</td>\n",
       "      <td>Large (2000-5000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pena High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>962</td>\n",
       "      <td>$585,858.00</td>\n",
       "      <td>$609.00</td>\n",
       "      <td>83.839917</td>\n",
       "      <td>84.044699</td>\n",
       "      <td>94.594595</td>\n",
       "      <td>95.945946</td>\n",
       "      <td>90.540541</td>\n",
       "      <td>Small (&lt;1000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rodriguez High School</th>\n",
       "      <td>District</td>\n",
       "      <td>3999</td>\n",
       "      <td>$2,547,363.00</td>\n",
       "      <td>$637.00</td>\n",
       "      <td>76.842711</td>\n",
       "      <td>80.744686</td>\n",
       "      <td>66.366592</td>\n",
       "      <td>80.220055</td>\n",
       "      <td>52.988247</td>\n",
       "      <td>Large (2000-5000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shelton High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1761</td>\n",
       "      <td>$1,056,600.00</td>\n",
       "      <td>$600.00</td>\n",
       "      <td>83.359455</td>\n",
       "      <td>83.725724</td>\n",
       "      <td>93.867121</td>\n",
       "      <td>95.854628</td>\n",
       "      <td>89.892107</td>\n",
       "      <td>Medium (1000-2000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thomas High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1635</td>\n",
       "      <td>$1,043,130.00</td>\n",
       "      <td>$638.00</td>\n",
       "      <td>83.418349</td>\n",
       "      <td>83.848930</td>\n",
       "      <td>93.272171</td>\n",
       "      <td>97.308869</td>\n",
       "      <td>90.948012</td>\n",
       "      <td>Medium (1000-2000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wilson High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>2283</td>\n",
       "      <td>$1,319,574.00</td>\n",
       "      <td>$578.00</td>\n",
       "      <td>83.274201</td>\n",
       "      <td>83.989488</td>\n",
       "      <td>93.867718</td>\n",
       "      <td>96.539641</td>\n",
       "      <td>90.582567</td>\n",
       "      <td>Large (2000-5000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wright High School</th>\n",
       "      <td>Charter</td>\n",
       "      <td>1800</td>\n",
       "      <td>$1,049,400.00</td>\n",
       "      <td>$583.00</td>\n",
       "      <td>83.682222</td>\n",
       "      <td>83.955000</td>\n",
       "      <td>93.333333</td>\n",
       "      <td>96.611111</td>\n",
       "      <td>90.333333</td>\n",
       "      <td>Medium (1000-2000)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      School Type  Total Students Total School Budget  \\\n",
       "Bailey High School       District            4976       $3,124,928.00   \n",
       "Cabrera High School       Charter            1858       $1,081,356.00   \n",
       "Figueroa High School     District            2949       $1,884,411.00   \n",
       "Ford High School         District            2739       $1,763,916.00   \n",
       "Griffin High School       Charter            1468         $917,500.00   \n",
       "Hernandez High School    District            4635       $3,022,020.00   \n",
       "Holden High School        Charter             427         $248,087.00   \n",
       "Huang High School        District            2917       $1,910,635.00   \n",
       "Johnson High School      District            4761       $3,094,650.00   \n",
       "Pena High School          Charter             962         $585,858.00   \n",
       "Rodriguez High School    District            3999       $2,547,363.00   \n",
       "Shelton High School       Charter            1761       $1,056,600.00   \n",
       "Thomas High School        Charter            1635       $1,043,130.00   \n",
       "Wilson High School        Charter            2283       $1,319,574.00   \n",
       "Wright High School        Charter            1800       $1,049,400.00   \n",
       "\n",
       "                      Per Student Budget  Average Math Score  \\\n",
       "Bailey High School               $628.00           77.048432   \n",
       "Cabrera High School              $582.00           83.061895   \n",
       "Figueroa High School             $639.00           76.711767   \n",
       "Ford High School                 $644.00           77.102592   \n",
       "Griffin High School              $625.00           83.351499   \n",
       "Hernandez High School            $652.00           77.289752   \n",
       "Holden High School               $581.00           83.803279   \n",
       "Huang High School                $655.00           76.629414   \n",
       "Johnson High School              $650.00           77.072464   \n",
       "Pena High School                 $609.00           83.839917   \n",
       "Rodriguez High School            $637.00           76.842711   \n",
       "Shelton High School              $600.00           83.359455   \n",
       "Thomas High School               $638.00           83.418349   \n",
       "Wilson High School               $578.00           83.274201   \n",
       "Wright High School               $583.00           83.682222   \n",
       "\n",
       "                       Average Reading Score  % Passing Math  \\\n",
       "Bailey High School                 81.033963       66.680064   \n",
       "Cabrera High School                83.975780       94.133477   \n",
       "Figueroa High School               81.158020       65.988471   \n",
       "Ford High School                   80.746258       68.309602   \n",
       "Griffin High School                83.816757       93.392371   \n",
       "Hernandez High School              80.934412       66.752967   \n",
       "Holden High School                 83.814988       92.505855   \n",
       "Huang High School                  81.182722       65.683922   \n",
       "Johnson High School                80.966394       66.057551   \n",
       "Pena High School                   84.044699       94.594595   \n",
       "Rodriguez High School              80.744686       66.366592   \n",
       "Shelton High School                83.725724       93.867121   \n",
       "Thomas High School                 83.848930       93.272171   \n",
       "Wilson High School                 83.989488       93.867718   \n",
       "Wright High School                 83.955000       93.333333   \n",
       "\n",
       "                       % Passing Reading  % Overall Passing  \\\n",
       "Bailey High School             81.933280          54.642283   \n",
       "Cabrera High School            97.039828          91.334769   \n",
       "Figueroa High School           80.739234          53.204476   \n",
       "Ford High School               79.299014          54.289887   \n",
       "Griffin High School            97.138965          90.599455   \n",
       "Hernandez High School          80.862999          53.527508   \n",
       "Holden High School             96.252927          89.227166   \n",
       "Huang High School              81.316421          53.513884   \n",
       "Johnson High School            81.222432          53.539172   \n",
       "Pena High School               95.945946          90.540541   \n",
       "Rodriguez High School          80.220055          52.988247   \n",
       "Shelton High School            95.854628          89.892107   \n",
       "Thomas High School             97.308869          90.948012   \n",
       "Wilson High School             96.539641          90.582567   \n",
       "Wright High School             96.611111          90.333333   \n",
       "\n",
       "                              School Size  \n",
       "Bailey High School      Large (2000-5000)  \n",
       "Cabrera High School    Medium (1000-2000)  \n",
       "Figueroa High School    Large (2000-5000)  \n",
       "Ford High School        Large (2000-5000)  \n",
       "Griffin High School    Medium (1000-2000)  \n",
       "Hernandez High School   Large (2000-5000)  \n",
       "Holden High School          Small (<1000)  \n",
       "Huang High School       Large (2000-5000)  \n",
       "Johnson High School     Large (2000-5000)  \n",
       "Pena High School            Small (<1000)  \n",
       "Rodriguez High School   Large (2000-5000)  \n",
       "Shelton High School    Medium (1000-2000)  \n",
       "Thomas High School     Medium (1000-2000)  \n",
       "Wilson High School      Large (2000-5000)  \n",
       "Wright High School     Medium (1000-2000)  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a copy of the school summary since it has the \"Per Student Budget\" \n",
    "school_size_df = per_school_summary.copy()\n",
    "\n",
    "# Categorize the spending based on the bins\n",
    "# Use `pd.cut` on the \"Total Students\" column of the `per_school_summary` DataFrame.\n",
    "school_size_df[\"School Size\"] = pd.cut(x=per_school_summary[\"Total Students\"], bins=size_bins, labels=labels, right=False)\n",
    "school_size_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\icanhearme\\AppData\\Local\\Temp\\ipykernel_42120\\1026156150.py:2: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  size_math_scores = school_size_df.groupby([\"School Size\"]).mean()[\"Average Math Score\"]\n",
      "C:\\Users\\icanhearme\\AppData\\Local\\Temp\\ipykernel_42120\\1026156150.py:3: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  size_reading_scores = school_size_df.groupby([\"School Size\"]).mean()[\"Average Reading Score\"]\n",
      "C:\\Users\\icanhearme\\AppData\\Local\\Temp\\ipykernel_42120\\1026156150.py:4: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  size_passing_math = school_size_df.groupby([\"School Size\"]).mean()[\"% Passing Math\"]\n",
      "C:\\Users\\icanhearme\\AppData\\Local\\Temp\\ipykernel_42120\\1026156150.py:5: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  size_passing_reading = school_size_df.groupby([\"School Size\"]).mean()[\"% Passing Reading\"]\n",
      "C:\\Users\\icanhearme\\AppData\\Local\\Temp\\ipykernel_42120\\1026156150.py:6: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  size_overall_passing = school_size_df.groupby([\"School Size\"]).mean()[\"% Overall Passing\"]\n"
     ]
    }
   ],
   "source": [
    "# Calculate averages for the desired columns. \n",
    "size_math_scores = school_size_df.groupby([\"School Size\"]).mean()[\"Average Math Score\"]\n",
    "size_reading_scores = school_size_df.groupby([\"School Size\"]).mean()[\"Average Reading Score\"]\n",
    "size_passing_math = school_size_df.groupby([\"School Size\"]).mean()[\"% Passing Math\"]\n",
    "size_passing_reading = school_size_df.groupby([\"School Size\"]).mean()[\"% Passing Reading\"]\n",
    "size_overall_passing = school_size_df.groupby([\"School Size\"]).mean()[\"% Overall Passing\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Average Math Score</th>\n",
       "      <th>Average Reading Score</th>\n",
       "      <th>% Passing Math</th>\n",
       "      <th>% Passing Reading</th>\n",
       "      <th>% Overall Passing</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>School Size</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>Small (&lt;1000)</th>\n",
       "      <td>83.821598</td>\n",
       "      <td>83.929843</td>\n",
       "      <td>93.550225</td>\n",
       "      <td>96.099437</td>\n",
       "      <td>89.883853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Medium (1000-2000)</th>\n",
       "      <td>83.374684</td>\n",
       "      <td>83.864438</td>\n",
       "      <td>93.599695</td>\n",
       "      <td>96.790680</td>\n",
       "      <td>90.621535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Large (2000-5000)</th>\n",
       "      <td>77.746417</td>\n",
       "      <td>81.344493</td>\n",
       "      <td>69.963361</td>\n",
       "      <td>82.766634</td>\n",
       "      <td>58.286003</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Average Math Score  Average Reading Score  % Passing Math  \\\n",
       "School Size                                                                     \n",
       "Small (<1000)                83.821598              83.929843       93.550225   \n",
       "Medium (1000-2000)           83.374684              83.864438       93.599695   \n",
       "Large (2000-5000)            77.746417              81.344493       69.963361   \n",
       "\n",
       "                    % Passing Reading  % Overall Passing  \n",
       "School Size                                               \n",
       "Small (<1000)               96.099437          89.883853  \n",
       "Medium (1000-2000)          96.790680          90.621535  \n",
       "Large (2000-5000)           82.766634          58.286003  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a DataFrame called `size_summary` that breaks down school performance based on school size (small, medium, or large).\n",
    "# Use the scores above to create a new DataFrame called `size_summary`\n",
    "size_summary = pd.DataFrame({\n",
    "    'Average Math Score': size_math_scores, \n",
    "    'Average Reading Score': size_reading_scores, \n",
    "    '% Passing Math': size_passing_math, \n",
    "    '% Passing Reading': size_passing_reading,\n",
    "    '% Overall Passing': size_overall_passing,\n",
    "})\n",
    "\n",
    "# Display results\n",
    "size_summary"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Scores by School Type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\icanhearme\\AppData\\Local\\Temp\\ipykernel_42120\\201418877.py:2: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  type_math_scores = per_school_summary.groupby([\"School Type\"]).mean()[\"Average Math Score\"]\n",
      "C:\\Users\\icanhearme\\AppData\\Local\\Temp\\ipykernel_42120\\201418877.py:3: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  type_reading_scores = per_school_summary.groupby([\"School Type\"]).mean()[\"Average Reading Score\"]\n",
      "C:\\Users\\icanhearme\\AppData\\Local\\Temp\\ipykernel_42120\\201418877.py:4: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  type_passing_math = per_school_summary.groupby([\"School Type\"]).mean()[\"% Passing Math\"]\n",
      "C:\\Users\\icanhearme\\AppData\\Local\\Temp\\ipykernel_42120\\201418877.py:5: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  type_passing_reading = per_school_summary.groupby([\"School Type\"]).mean()[\"% Passing Reading\"]\n",
      "C:\\Users\\icanhearme\\AppData\\Local\\Temp\\ipykernel_42120\\201418877.py:6: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  type_overall_passing = per_school_summary.groupby([\"School Type\"]).mean()[\"% Overall Passing\"]\n"
     ]
    }
   ],
   "source": [
    "# Group the per_school_summary DataFrame by \"School Type\" and average the results.\n",
    "type_math_scores = per_school_summary.groupby([\"School Type\"]).mean()[\"Average Math Score\"]\n",
    "type_reading_scores = per_school_summary.groupby([\"School Type\"]).mean()[\"Average Reading Score\"]\n",
    "type_passing_math = per_school_summary.groupby([\"School Type\"]).mean()[\"% Passing Math\"]\n",
    "type_passing_reading = per_school_summary.groupby([\"School Type\"]).mean()[\"% Passing Reading\"]\n",
    "type_overall_passing = per_school_summary.groupby([\"School Type\"]).mean()[\"% Overall Passing\"]\n",
    "\n",
    "# Use the code provided to select new column data\n",
    "# average_math_score_by_type = type_math_scores[\"Average Math Score\"]\n",
    "# average_reading_score_by_type = type_reading_scores[\"Average Reading Score\"]\n",
    "# average_percent_passing_math_by_type = type_passing_math[\"% Passing Math\"]\n",
    "# average_percent_passing_reading_by_type = type_passing_reading[\"% Passing Reading\"]\n",
    "# average_percent_overall_passing_by_type = type_overall_passing[\"% Overall Passing\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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>Average Math Score</th>\n",
       "      <th>Average Reading Score</th>\n",
       "      <th>% Passing Math</th>\n",
       "      <th>% Passing Reading</th>\n",
       "      <th>% Overall Passing</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>School Type</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>Charter</th>\n",
       "      <td>83.473852</td>\n",
       "      <td>83.896421</td>\n",
       "      <td>93.620830</td>\n",
       "      <td>96.586489</td>\n",
       "      <td>90.432244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>District</th>\n",
       "      <td>76.956733</td>\n",
       "      <td>80.966636</td>\n",
       "      <td>66.548453</td>\n",
       "      <td>80.799062</td>\n",
       "      <td>53.672208</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Average Math Score  Average Reading Score  % Passing Math  \\\n",
       "School Type                                                              \n",
       "Charter               83.473852              83.896421       93.620830   \n",
       "District              76.956733              80.966636       66.548453   \n",
       "\n",
       "             % Passing Reading  % Overall Passing  \n",
       "School Type                                        \n",
       "Charter              96.586489          90.432244  \n",
       "District             80.799062          53.672208  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Assemble the new data by type into a DataFrame called `type_summary`\n",
    "type_summary = pd.DataFrame({\n",
    "    'Average Math Score': type_math_scores, \n",
    "    'Average Reading Score': type_reading_scores, \n",
    "    '% Passing Math': type_passing_math, \n",
    "    '% Passing Reading': type_passing_reading,\n",
    "    '% Overall Passing': type_overall_passing,\n",
    "})\n",
    "\n",
    "# Display results\n",
    "type_summary"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Report \n",
    "\n",
    "Utilizing data of all the students in a district and all the school in the district (including all appropriate information). I was able to combine both datasets and summarize relevant information. \n",
    "From the summaries it can be noted that from Charter school tend to score higher than District schools. Schools that spend less on each student tend to score higher on tests as well. Also a students grade level isn't correlated to their test scores. "
   ]
  }
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