843 lines
262 KiB
Plaintext
843 lines
262 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"from matplotlib import pyplot as plt\n",
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"import seaborn as sns\n",
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"sns.set(style=\"whitegrid\")\n",
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"tips = sns.load_dataset(\"tips\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"Index(['Private', 'Apps', 'Accept', 'Enroll', 'Top10perc', 'Top25perc',\n",
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" 'F.Undergrad', 'P.Undergrad', 'Outstate', 'Room.Board', 'Books',\n",
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" 'Personal', 'PhD', 'Terminal', 'S.F.Ratio', 'perc.alumni', 'Expend',\n",
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" 'Grad.Rate'],\n",
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" dtype='object')"
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]
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},
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"execution_count": 2,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"college = pd.read_csv(\"./../datasets/College.csv\")\n",
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"college.set_index(\"Unnamed: 0\", inplace=True)\n",
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"college.columns"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>Apps</th>\n",
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" <th>Accept</th>\n",
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" <th>Enroll</th>\n",
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" <th>Top10perc</th>\n",
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" <th>Top25perc</th>\n",
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" <th>F.Undergrad</th>\n",
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" <th>P.Undergrad</th>\n",
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" <th>Outstate</th>\n",
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" <th>Room.Board</th>\n",
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" <th>Books</th>\n",
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" <th>Personal</th>\n",
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" <th>PhD</th>\n",
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" <th>Terminal</th>\n",
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" <th>S.F.Ratio</th>\n",
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" <th>perc.alumni</th>\n",
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" <th>Expend</th>\n",
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" <th>Grad.Rate</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>count</th>\n",
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" <td>777.000000</td>\n",
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" <td>777.000000</td>\n",
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" <td>777.000000</td>\n",
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" <td>777.000000</td>\n",
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" <td>777.000000</td>\n",
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" <td>777.000000</td>\n",
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" <td>777.000000</td>\n",
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" <td>777.000000</td>\n",
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" <td>777.000000</td>\n",
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" <td>777.000000</td>\n",
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" <td>777.000000</td>\n",
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" <td>777.000000</td>\n",
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" <td>777.000000</td>\n",
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" <td>777.000000</td>\n",
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" <td>777.000000</td>\n",
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" <td>777.000000</td>\n",
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" <td>777.00000</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>mean</th>\n",
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" <td>3001.638353</td>\n",
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" <td>2018.804376</td>\n",
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" <td>779.972973</td>\n",
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" <td>27.558559</td>\n",
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" <td>55.796654</td>\n",
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" <td>3699.907336</td>\n",
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" <td>855.298584</td>\n",
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" <td>10440.669241</td>\n",
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" <td>4357.526384</td>\n",
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" <td>549.380952</td>\n",
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" <td>1340.642214</td>\n",
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" <td>72.660232</td>\n",
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" <td>79.702703</td>\n",
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" <td>14.089704</td>\n",
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" <td>22.743887</td>\n",
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" <td>9660.171171</td>\n",
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" <td>65.46332</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>std</th>\n",
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" <td>3870.201484</td>\n",
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" <td>2451.113971</td>\n",
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" <td>929.176190</td>\n",
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" <td>17.640364</td>\n",
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" <td>19.804778</td>\n",
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" <td>4850.420531</td>\n",
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" <td>1522.431887</td>\n",
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" <td>4023.016484</td>\n",
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" <td>1096.696416</td>\n",
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" <td>165.105360</td>\n",
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" <td>677.071454</td>\n",
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" <td>16.328155</td>\n",
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" <td>14.722359</td>\n",
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" <td>3.958349</td>\n",
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" <td>12.391801</td>\n",
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" <td>5221.768440</td>\n",
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" <td>17.17771</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>min</th>\n",
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" <td>81.000000</td>\n",
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" <td>72.000000</td>\n",
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" <td>35.000000</td>\n",
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" <td>1.000000</td>\n",
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" <td>9.000000</td>\n",
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" <td>139.000000</td>\n",
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" <td>1.000000</td>\n",
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" <td>2340.000000</td>\n",
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" <td>1780.000000</td>\n",
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" <td>96.000000</td>\n",
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" <td>250.000000</td>\n",
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" <td>8.000000</td>\n",
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" <td>24.000000</td>\n",
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" <td>2.500000</td>\n",
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" <td>0.000000</td>\n",
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" <td>3186.000000</td>\n",
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" <td>10.00000</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>25%</th>\n",
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" <td>776.000000</td>\n",
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" <td>604.000000</td>\n",
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" <td>242.000000</td>\n",
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" <td>15.000000</td>\n",
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" <td>41.000000</td>\n",
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" <td>992.000000</td>\n",
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" <td>95.000000</td>\n",
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" <td>7320.000000</td>\n",
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" <td>3597.000000</td>\n",
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" <td>470.000000</td>\n",
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" <td>850.000000</td>\n",
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" <td>62.000000</td>\n",
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" <td>71.000000</td>\n",
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" <td>11.500000</td>\n",
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" <td>13.000000</td>\n",
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" <td>6751.000000</td>\n",
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" <td>53.00000</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>50%</th>\n",
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" <td>1558.000000</td>\n",
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" <td>1110.000000</td>\n",
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" <td>434.000000</td>\n",
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" <td>23.000000</td>\n",
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" <td>54.000000</td>\n",
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" <td>1707.000000</td>\n",
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" <td>353.000000</td>\n",
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" <td>9990.000000</td>\n",
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" <td>4200.000000</td>\n",
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" <td>500.000000</td>\n",
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" <td>1200.000000</td>\n",
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" <td>75.000000</td>\n",
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" <td>82.000000</td>\n",
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" <td>13.600000</td>\n",
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" <td>21.000000</td>\n",
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" <td>8377.000000</td>\n",
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" <td>65.00000</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>75%</th>\n",
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" <td>3624.000000</td>\n",
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" <td>2424.000000</td>\n",
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" <td>902.000000</td>\n",
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" <td>35.000000</td>\n",
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" <td>69.000000</td>\n",
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" <td>4005.000000</td>\n",
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" <td>967.000000</td>\n",
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" <td>12925.000000</td>\n",
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" <td>5050.000000</td>\n",
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" <td>600.000000</td>\n",
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" <td>1700.000000</td>\n",
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" <td>85.000000</td>\n",
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" <td>92.000000</td>\n",
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" <td>16.500000</td>\n",
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" <td>31.000000</td>\n",
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" <td>10830.000000</td>\n",
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" <td>78.00000</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>max</th>\n",
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" <td>48094.000000</td>\n",
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" <td>26330.000000</td>\n",
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" <td>6392.000000</td>\n",
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" <td>96.000000</td>\n",
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" <td>100.000000</td>\n",
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" <td>31643.000000</td>\n",
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" <td>21836.000000</td>\n",
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" <td>21700.000000</td>\n",
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" <td>8124.000000</td>\n",
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" <td>2340.000000</td>\n",
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" <td>6800.000000</td>\n",
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" <td>103.000000</td>\n",
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" <td>100.000000</td>\n",
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" <td>39.800000</td>\n",
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" <td>64.000000</td>\n",
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" <td>56233.000000</td>\n",
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" <td>118.00000</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" Apps Accept Enroll Top10perc Top25perc \\\n",
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"count 777.000000 777.000000 777.000000 777.000000 777.000000 \n",
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"mean 3001.638353 2018.804376 779.972973 27.558559 55.796654 \n",
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"std 3870.201484 2451.113971 929.176190 17.640364 19.804778 \n",
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"min 81.000000 72.000000 35.000000 1.000000 9.000000 \n",
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"25% 776.000000 604.000000 242.000000 15.000000 41.000000 \n",
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"50% 1558.000000 1110.000000 434.000000 23.000000 54.000000 \n",
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"75% 3624.000000 2424.000000 902.000000 35.000000 69.000000 \n",
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"max 48094.000000 26330.000000 6392.000000 96.000000 100.000000 \n",
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"\n",
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" F.Undergrad P.Undergrad Outstate Room.Board Books \\\n",
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"count 777.000000 777.000000 777.000000 777.000000 777.000000 \n",
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"mean 3699.907336 855.298584 10440.669241 4357.526384 549.380952 \n",
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"std 4850.420531 1522.431887 4023.016484 1096.696416 165.105360 \n",
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"min 139.000000 1.000000 2340.000000 1780.000000 96.000000 \n",
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"25% 992.000000 95.000000 7320.000000 3597.000000 470.000000 \n",
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"50% 1707.000000 353.000000 9990.000000 4200.000000 500.000000 \n",
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"75% 4005.000000 967.000000 12925.000000 5050.000000 600.000000 \n",
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"max 31643.000000 21836.000000 21700.000000 8124.000000 2340.000000 \n",
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"\n",
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" Personal PhD Terminal S.F.Ratio perc.alumni \\\n",
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"count 777.000000 777.000000 777.000000 777.000000 777.000000 \n",
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"mean 1340.642214 72.660232 79.702703 14.089704 22.743887 \n",
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"std 677.071454 16.328155 14.722359 3.958349 12.391801 \n",
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"min 250.000000 8.000000 24.000000 2.500000 0.000000 \n",
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"25% 850.000000 62.000000 71.000000 11.500000 13.000000 \n",
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"50% 1200.000000 75.000000 82.000000 13.600000 21.000000 \n",
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"75% 1700.000000 85.000000 92.000000 16.500000 31.000000 \n",
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"max 6800.000000 103.000000 100.000000 39.800000 64.000000 \n",
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"\n",
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" Expend Grad.Rate \n",
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"count 777.000000 777.00000 \n",
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"mean 9660.171171 65.46332 \n",
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"std 5221.768440 17.17771 \n",
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"min 3186.000000 10.00000 \n",
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"25% 6751.000000 53.00000 \n",
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"50% 8377.000000 65.00000 \n",
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"75% 10830.000000 78.00000 \n",
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"max 56233.000000 118.00000 "
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"college.describe()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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||
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"outputs": [
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||
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{
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"data": {
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||
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"text/html": [
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||
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"<div>\n",
|
||
|
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"<style scoped>\n",
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||
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" .dataframe tbody tr th:only-of-type {\n",
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||
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" vertical-align: middle;\n",
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" }\n",
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||
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"\n",
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||
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" .dataframe tbody tr th {\n",
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||
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" vertical-align: top;\n",
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||
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" }\n",
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||
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"\n",
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||
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" .dataframe thead th {\n",
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||
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" text-align: right;\n",
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||
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" }\n",
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||
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"</style>\n",
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||
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"<table border=\"1\" class=\"dataframe\">\n",
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||
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" <thead>\n",
|
||
|
|
" <tr style=\"text-align: right;\">\n",
|
||
|
|
" <th></th>\n",
|
||
|
|
" <th>Private</th>\n",
|
||
|
|
" <th>Apps</th>\n",
|
||
|
|
" <th>Accept</th>\n",
|
||
|
|
" <th>Enroll</th>\n",
|
||
|
|
" <th>Top10perc</th>\n",
|
||
|
|
" <th>Top25perc</th>\n",
|
||
|
|
" <th>F.Undergrad</th>\n",
|
||
|
|
" <th>P.Undergrad</th>\n",
|
||
|
|
" <th>Outstate</th>\n",
|
||
|
|
" <th>Room.Board</th>\n",
|
||
|
|
" <th>Books</th>\n",
|
||
|
|
" <th>Personal</th>\n",
|
||
|
|
" <th>PhD</th>\n",
|
||
|
|
" <th>Terminal</th>\n",
|
||
|
|
" <th>S.F.Ratio</th>\n",
|
||
|
|
" <th>perc.alumni</th>\n",
|
||
|
|
" <th>Expend</th>\n",
|
||
|
|
" <th>Grad.Rate</th>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>Unnamed: 0</th>\n",
|
||
|
|
" <th></th>\n",
|
||
|
|
" <th></th>\n",
|
||
|
|
" <th></th>\n",
|
||
|
|
" <th></th>\n",
|
||
|
|
" <th></th>\n",
|
||
|
|
" <th></th>\n",
|
||
|
|
" <th></th>\n",
|
||
|
|
" <th></th>\n",
|
||
|
|
" <th></th>\n",
|
||
|
|
" <th></th>\n",
|
||
|
|
" <th></th>\n",
|
||
|
|
" <th></th>\n",
|
||
|
|
" <th></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>Abilene Christian University</th>\n",
|
||
|
|
" <td>Yes</td>\n",
|
||
|
|
" <td>1660</td>\n",
|
||
|
|
" <td>1232</td>\n",
|
||
|
|
" <td>721</td>\n",
|
||
|
|
" <td>23</td>\n",
|
||
|
|
" <td>52</td>\n",
|
||
|
|
" <td>2885</td>\n",
|
||
|
|
" <td>537</td>\n",
|
||
|
|
" <td>7440</td>\n",
|
||
|
|
" <td>3300</td>\n",
|
||
|
|
" <td>450</td>\n",
|
||
|
|
" <td>2200</td>\n",
|
||
|
|
" <td>70</td>\n",
|
||
|
|
" <td>78</td>\n",
|
||
|
|
" <td>18.1</td>\n",
|
||
|
|
" <td>12</td>\n",
|
||
|
|
" <td>7041</td>\n",
|
||
|
|
" <td>60</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>Adelphi University</th>\n",
|
||
|
|
" <td>Yes</td>\n",
|
||
|
|
" <td>2186</td>\n",
|
||
|
|
" <td>1924</td>\n",
|
||
|
|
" <td>512</td>\n",
|
||
|
|
" <td>16</td>\n",
|
||
|
|
" <td>29</td>\n",
|
||
|
|
" <td>2683</td>\n",
|
||
|
|
" <td>1227</td>\n",
|
||
|
|
" <td>12280</td>\n",
|
||
|
|
" <td>6450</td>\n",
|
||
|
|
" <td>750</td>\n",
|
||
|
|
" <td>1500</td>\n",
|
||
|
|
" <td>29</td>\n",
|
||
|
|
" <td>30</td>\n",
|
||
|
|
" <td>12.2</td>\n",
|
||
|
|
" <td>16</td>\n",
|
||
|
|
" <td>10527</td>\n",
|
||
|
|
" <td>56</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>Adrian College</th>\n",
|
||
|
|
" <td>Yes</td>\n",
|
||
|
|
" <td>1428</td>\n",
|
||
|
|
" <td>1097</td>\n",
|
||
|
|
" <td>336</td>\n",
|
||
|
|
" <td>22</td>\n",
|
||
|
|
" <td>50</td>\n",
|
||
|
|
" <td>1036</td>\n",
|
||
|
|
" <td>99</td>\n",
|
||
|
|
" <td>11250</td>\n",
|
||
|
|
" <td>3750</td>\n",
|
||
|
|
" <td>400</td>\n",
|
||
|
|
" <td>1165</td>\n",
|
||
|
|
" <td>53</td>\n",
|
||
|
|
" <td>66</td>\n",
|
||
|
|
" <td>12.9</td>\n",
|
||
|
|
" <td>30</td>\n",
|
||
|
|
" <td>8735</td>\n",
|
||
|
|
" <td>54</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>Agnes Scott College</th>\n",
|
||
|
|
" <td>Yes</td>\n",
|
||
|
|
" <td>417</td>\n",
|
||
|
|
" <td>349</td>\n",
|
||
|
|
" <td>137</td>\n",
|
||
|
|
" <td>60</td>\n",
|
||
|
|
" <td>89</td>\n",
|
||
|
|
" <td>510</td>\n",
|
||
|
|
" <td>63</td>\n",
|
||
|
|
" <td>12960</td>\n",
|
||
|
|
" <td>5450</td>\n",
|
||
|
|
" <td>450</td>\n",
|
||
|
|
" <td>875</td>\n",
|
||
|
|
" <td>92</td>\n",
|
||
|
|
" <td>97</td>\n",
|
||
|
|
" <td>7.7</td>\n",
|
||
|
|
" <td>37</td>\n",
|
||
|
|
" <td>19016</td>\n",
|
||
|
|
" <td>59</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>Alaska Pacific University</th>\n",
|
||
|
|
" <td>Yes</td>\n",
|
||
|
|
" <td>193</td>\n",
|
||
|
|
" <td>146</td>\n",
|
||
|
|
" <td>55</td>\n",
|
||
|
|
" <td>16</td>\n",
|
||
|
|
" <td>44</td>\n",
|
||
|
|
" <td>249</td>\n",
|
||
|
|
" <td>869</td>\n",
|
||
|
|
" <td>7560</td>\n",
|
||
|
|
" <td>4120</td>\n",
|
||
|
|
" <td>800</td>\n",
|
||
|
|
" <td>1500</td>\n",
|
||
|
|
" <td>76</td>\n",
|
||
|
|
" <td>72</td>\n",
|
||
|
|
" <td>11.9</td>\n",
|
||
|
|
" <td>2</td>\n",
|
||
|
|
" <td>10922</td>\n",
|
||
|
|
" <td>15</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" </tbody>\n",
|
||
|
|
"</table>\n",
|
||
|
|
"</div>"
|
||
|
|
],
|
||
|
|
"text/plain": [
|
||
|
|
" Private Apps Accept Enroll Top10perc \\\n",
|
||
|
|
"Unnamed: 0 \n",
|
||
|
|
"Abilene Christian University Yes 1660 1232 721 23 \n",
|
||
|
|
"Adelphi University Yes 2186 1924 512 16 \n",
|
||
|
|
"Adrian College Yes 1428 1097 336 22 \n",
|
||
|
|
"Agnes Scott College Yes 417 349 137 60 \n",
|
||
|
|
"Alaska Pacific University Yes 193 146 55 16 \n",
|
||
|
|
"\n",
|
||
|
|
" Top25perc F.Undergrad P.Undergrad Outstate \\\n",
|
||
|
|
"Unnamed: 0 \n",
|
||
|
|
"Abilene Christian University 52 2885 537 7440 \n",
|
||
|
|
"Adelphi University 29 2683 1227 12280 \n",
|
||
|
|
"Adrian College 50 1036 99 11250 \n",
|
||
|
|
"Agnes Scott College 89 510 63 12960 \n",
|
||
|
|
"Alaska Pacific University 44 249 869 7560 \n",
|
||
|
|
"\n",
|
||
|
|
" Room.Board Books Personal PhD Terminal \\\n",
|
||
|
|
"Unnamed: 0 \n",
|
||
|
|
"Abilene Christian University 3300 450 2200 70 78 \n",
|
||
|
|
"Adelphi University 6450 750 1500 29 30 \n",
|
||
|
|
"Adrian College 3750 400 1165 53 66 \n",
|
||
|
|
"Agnes Scott College 5450 450 875 92 97 \n",
|
||
|
|
"Alaska Pacific University 4120 800 1500 76 72 \n",
|
||
|
|
"\n",
|
||
|
|
" S.F.Ratio perc.alumni Expend Grad.Rate \n",
|
||
|
|
"Unnamed: 0 \n",
|
||
|
|
"Abilene Christian University 18.1 12 7041 60 \n",
|
||
|
|
"Adelphi University 12.2 16 10527 56 \n",
|
||
|
|
"Adrian College 12.9 30 8735 54 \n",
|
||
|
|
"Agnes Scott College 7.7 37 19016 59 \n",
|
||
|
|
"Alaska Pacific University 11.9 2 10922 15 "
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 4,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"college.head()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 5,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"ax = sns.violinplot(x=\"Private\", y=\"Outstate\", data=college)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 6,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"ax = sns.boxplot(x=\"Private\", y=\"Outstate\", data=college)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 7,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"sep =pd.cut(college.Top10perc, pd.interval_range(start=0, end=100, periods=2), labels=[\"Not elite\", \"Elite\"])\n",
|
||
|
|
"college[\"Elite\"] = sep "
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 8,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"ax = sns.violinplot(x=\"Elite\", y=\"Outstate\", data=college)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 9,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"# Index(['Private', 'Apps', 'Accept', 'Enroll', 'Top10perc', 'Top25perc',\n",
|
||
|
|
"# 'F.Undergrad', 'P.Undergrad', 'Outstate', 'Room.Board', 'Books',\n",
|
||
|
|
"# 'Personal', 'PhD', 'Terminal', 'S.F.Ratio', 'perc.alumni', 'Expend',\n",
|
||
|
|
"# 'Grad.Rate'],\n",
|
||
|
|
"# dtype='object')\n",
|
||
|
|
"ax = sns.distplot(college.Apps)\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 10,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<matplotlib.axes._subplots.AxesSubplot at 0x7ff45d0085e0>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 10,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"# Index(['Private', 'Apps', 'Accept', 'Enroll', 'Top10perc', 'Top25perc',\n",
|
||
|
|
"# 'F.Undergrad', 'P.Undergrad', 'Outstate', 'Room.Board', 'Books',\n",
|
||
|
|
"# 'Personal', 'PhD', 'Terminal', 'S.F.Ratio', 'perc.alumni', 'Expend',\n",
|
||
|
|
"# 'Grad.Rate'],\n",
|
||
|
|
"sns.distplot(college.Accept)\n",
|
||
|
|
"sns.distplot(college.Enroll)\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 11,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"ax = sns.distplot(college.Top10perc)\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 12,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"ax = sns.distplot(college[\"F.Undergrad\"])\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 13,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"ax = sns.distplot(college[\"P.Undergrad\"])\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 14,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"ax = sns.distplot(college.Books)\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 15,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"ax = sns.distplot(college.Expend)\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 16,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"ax = sns.distplot(college.Terminal)\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 17,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"ax = sns.distplot(college.PhD)\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 18,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"ax = sns.distplot(college[\"Grad.Rate\"])"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"metadata": {
|
||
|
|
"kernelspec": {
|
||
|
|
"display_name": "Python 3",
|
||
|
|
"language": "python",
|
||
|
|
"name": "python3"
|
||
|
|
},
|
||
|
|
"language_info": {
|
||
|
|
"codemirror_mode": {
|
||
|
|
"name": "ipython",
|
||
|
|
"version": 3
|
||
|
|
},
|
||
|
|
"file_extension": ".py",
|
||
|
|
"mimetype": "text/x-python",
|
||
|
|
"name": "python",
|
||
|
|
"nbconvert_exporter": "python",
|
||
|
|
"pygments_lexer": "ipython3",
|
||
|
|
"version": "3.8.1"
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"nbformat": 4,
|
||
|
|
"nbformat_minor": 4
|
||
|
|
}
|