Data cleaning 2-practice.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sqlalchemy import create_engine\n",
    "import warnings\n",
    "\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "postgres_user = 'dsbc_student'\n",
    "postgres_pw = '7*.8G9QH21'\n",
    "postgres_host = '142.93.121.174'\n",
    "postgres_port = '5432'\n",
    "postgres_db = 'useducation'\n",
    "\n",
    "engine = create_engine('postgresql://{}:{}@{}:{}/{}'.format(\n",
    "    postgres_user, postgres_pw, postgres_host, postgres_port, postgres_db))\n",
    "\n",
    "useducation_df = pd.read_sql_query('select * from useducation',con=engine)\n",
    "\n",
    "engine.dispose()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1.Determine all the variable types and find the fraction of the missing values for each variable.\n",
    "\n",
    "\n",
    "2.Notice that the data has a time dimension (year). For this assignment, forget about time and treat all the observations as if they're from the same year. Choose a strategy to deal with the missing values for each variables. For which variables would filling in the missing values with some value make sense? For which might tossing out the records entirely make sense?\n",
    "\n",
    "\n",
    "3.Now, take into account the time factor. Replicate your second answer but this time fill in the missing values by using a statistic that is calculated within the year of the observation. For example, if you want to fill a missing value for a variable with the mean of that variable, calculate the mean by using only the observations for that specific year.\n",
    "\n",
    "\n",
    "4.This time, fill in the missing values using interpolation (extrapolation).\n",
    "\n",
    "\n",
    "5.Compare your results for the 2nd, 3rd, and 4th questions. Do you find any meaningful differences?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.Determine all the variable types and find the fraction of the missing values for each variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1492 entries, 0 to 1491\n",
      "Data columns (total 25 columns):\n",
      "PRIMARY_KEY                     1492 non-null object\n",
      "STATE                           1492 non-null object\n",
      "YEAR                            1492 non-null int64\n",
      "ENROLL                          1229 non-null float64\n",
      "TOTAL_REVENUE                   1280 non-null float64\n",
      "FEDERAL_REVENUE                 1280 non-null float64\n",
      "STATE_REVENUE                   1280 non-null float64\n",
      "LOCAL_REVENUE                   1280 non-null float64\n",
      "TOTAL_EXPENDITURE               1280 non-null float64\n",
      "INSTRUCTION_EXPENDITURE         1280 non-null float64\n",
      "SUPPORT_SERVICES_EXPENDITURE    1280 non-null float64\n",
      "OTHER_EXPENDITURE               1229 non-null float64\n",
      "CAPITAL_OUTLAY_EXPENDITURE      1280 non-null float64\n",
      "GRADES_PK_G                     1319 non-null float64\n",
      "GRADES_KG_G                     1360 non-null float64\n",
      "GRADES_4_G                      1361 non-null float64\n",
      "GRADES_8_G                      1361 non-null float64\n",
      "GRADES_12_G                     1361 non-null float64\n",
      "GRADES_1_8_G                    1361 non-null float64\n",
      "GRADES_9_12_G                   1361 non-null float64\n",
      "GRADES_ALL_G                    1319 non-null float64\n",
      "AVG_MATH_4_SCORE                536 non-null float64\n",
      "AVG_MATH_8_SCORE                532 non-null float64\n",
      "AVG_READING_4_SCORE             533 non-null float64\n",
      "AVG_READING_8_SCORE             498 non-null float64\n",
      "dtypes: float64(22), int64(1), object(2)\n",
      "memory usage: 291.5+ KB\n"
     ]
    }
   ],
   "source": [
    "useducation_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PRIMARY_KEY                      0.000000\n",
       "STATE                            0.000000\n",
       "YEAR                             0.000000\n",
       "ENROLL                          17.627346\n",
       "TOTAL_REVENUE                   14.209115\n",
       "FEDERAL_REVENUE                 14.209115\n",
       "STATE_REVENUE                   14.209115\n",
       "LOCAL_REVENUE                   14.209115\n",
       "TOTAL_EXPENDITURE               14.209115\n",
       "INSTRUCTION_EXPENDITURE         14.209115\n",
       "SUPPORT_SERVICES_EXPENDITURE    14.209115\n",
       "OTHER_EXPENDITURE               17.627346\n",
       "CAPITAL_OUTLAY_EXPENDITURE      14.209115\n",
       "GRADES_PK_G                     11.595174\n",
       "GRADES_KG_G                      8.847185\n",
       "GRADES_4_G                       8.780161\n",
       "GRADES_8_G                       8.780161\n",
       "GRADES_12_G                      8.780161\n",
       "GRADES_1_8_G                     8.780161\n",
       "GRADES_9_12_G                    8.780161\n",
       "GRADES_ALL_G                    11.595174\n",
       "AVG_MATH_4_SCORE                64.075067\n",
       "AVG_MATH_8_SCORE                64.343164\n",
       "AVG_READING_4_SCORE             64.276139\n",
       "AVG_READING_8_SCORE             66.621984\n",
       "dtype: float64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "useducation_df.isnull().sum()*100/useducation_df.isnull().count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.Notice that the data has a time dimension (year). For this assignment, forget about time and treat all the observations as if they're from the same year. Choose a strategy to deal with the missing values for each variables. For which variables would filling in the missing values with some value make sense? For which might tossing out the records entirely make sense?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PRIMARY_KEY</th>\n",
       "      <th>STATE</th>\n",
       "      <th>YEAR</th>\n",
       "      <th>ENROLL</th>\n",
       "      <th>TOTAL_REVENUE</th>\n",
       "      <th>FEDERAL_REVENUE</th>\n",
       "      <th>STATE_REVENUE</th>\n",
       "      <th>LOCAL_REVENUE</th>\n",
       "      <th>TOTAL_EXPENDITURE</th>\n",
       "      <th>INSTRUCTION_EXPENDITURE</th>\n",
       "      <th>...</th>\n",
       "      <th>GRADES_4_G</th>\n",
       "      <th>GRADES_8_G</th>\n",
       "      <th>GRADES_12_G</th>\n",
       "      <th>GRADES_1_8_G</th>\n",
       "      <th>GRADES_9_12_G</th>\n",
       "      <th>GRADES_ALL_G</th>\n",
       "      <th>AVG_MATH_4_SCORE</th>\n",
       "      <th>AVG_MATH_8_SCORE</th>\n",
       "      <th>AVG_READING_4_SCORE</th>\n",
       "      <th>AVG_READING_8_SCORE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1992_ALABAMA</td>\n",
       "      <td>ALABAMA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2678885.0</td>\n",
       "      <td>304177.0</td>\n",
       "      <td>1659028.0</td>\n",
       "      <td>715680.0</td>\n",
       "      <td>2653798.0</td>\n",
       "      <td>1481703.0</td>\n",
       "      <td>...</td>\n",
       "      <td>57948.0</td>\n",
       "      <td>58025.0</td>\n",
       "      <td>41167.0</td>\n",
       "      <td>471564.0</td>\n",
       "      <td>196386.0</td>\n",
       "      <td>676174.0</td>\n",
       "      <td>208.327876</td>\n",
       "      <td>252.187522</td>\n",
       "      <td>207.963517</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1992_ALASKA</td>\n",
       "      <td>ALASKA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1049591.0</td>\n",
       "      <td>106780.0</td>\n",
       "      <td>720711.0</td>\n",
       "      <td>222100.0</td>\n",
       "      <td>972488.0</td>\n",
       "      <td>498362.0</td>\n",
       "      <td>...</td>\n",
       "      <td>9748.0</td>\n",
       "      <td>8789.0</td>\n",
       "      <td>6714.0</td>\n",
       "      <td>79117.0</td>\n",
       "      <td>30847.0</td>\n",
       "      <td>112335.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>258.859712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>1992_ARIZONA</td>\n",
       "      <td>ARIZONA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3258079.0</td>\n",
       "      <td>297888.0</td>\n",
       "      <td>1369815.0</td>\n",
       "      <td>1590376.0</td>\n",
       "      <td>3401580.0</td>\n",
       "      <td>1435908.0</td>\n",
       "      <td>...</td>\n",
       "      <td>55433.0</td>\n",
       "      <td>49081.0</td>\n",
       "      <td>37410.0</td>\n",
       "      <td>437127.0</td>\n",
       "      <td>175210.0</td>\n",
       "      <td>614881.0</td>\n",
       "      <td>215.253932</td>\n",
       "      <td>265.366278</td>\n",
       "      <td>206.212716</td>\n",
       "      <td>262.169895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1992_ARKANSAS</td>\n",
       "      <td>ARKANSAS</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1711959.0</td>\n",
       "      <td>178571.0</td>\n",
       "      <td>958785.0</td>\n",
       "      <td>574603.0</td>\n",
       "      <td>1743022.0</td>\n",
       "      <td>964323.0</td>\n",
       "      <td>...</td>\n",
       "      <td>34632.0</td>\n",
       "      <td>36011.0</td>\n",
       "      <td>27651.0</td>\n",
       "      <td>281338.0</td>\n",
       "      <td>123113.0</td>\n",
       "      <td>405259.0</td>\n",
       "      <td>210.206028</td>\n",
       "      <td>256.312090</td>\n",
       "      <td>208.634458</td>\n",
       "      <td>264.619665</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>1992_CALIFORNIA</td>\n",
       "      <td>CALIFORNIA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26260025.0</td>\n",
       "      <td>2072470.0</td>\n",
       "      <td>16546514.0</td>\n",
       "      <td>7641041.0</td>\n",
       "      <td>27138832.0</td>\n",
       "      <td>14358922.0</td>\n",
       "      <td>...</td>\n",
       "      <td>418418.0</td>\n",
       "      <td>363296.0</td>\n",
       "      <td>270675.0</td>\n",
       "      <td>3286034.0</td>\n",
       "      <td>1372011.0</td>\n",
       "      <td>4717112.0</td>\n",
       "      <td>208.398961</td>\n",
       "      <td>260.892247</td>\n",
       "      <td>196.764414</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>1992_COLORADO</td>\n",
       "      <td>COLORADO</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3185173.0</td>\n",
       "      <td>163253.0</td>\n",
       "      <td>1307986.0</td>\n",
       "      <td>1713934.0</td>\n",
       "      <td>3264826.0</td>\n",
       "      <td>1642466.0</td>\n",
       "      <td>...</td>\n",
       "      <td>50648.0</td>\n",
       "      <td>45025.0</td>\n",
       "      <td>34533.0</td>\n",
       "      <td>394904.0</td>\n",
       "      <td>160299.0</td>\n",
       "      <td>562613.0</td>\n",
       "      <td>221.023429</td>\n",
       "      <td>272.398433</td>\n",
       "      <td>213.480890</td>\n",
       "      <td>266.419687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>1992_CONNECTICUT</td>\n",
       "      <td>CONNECTICUT</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3834302.0</td>\n",
       "      <td>143542.0</td>\n",
       "      <td>1342539.0</td>\n",
       "      <td>2348221.0</td>\n",
       "      <td>3721338.0</td>\n",
       "      <td>2148041.0</td>\n",
       "      <td>...</td>\n",
       "      <td>38058.0</td>\n",
       "      <td>33691.0</td>\n",
       "      <td>28366.0</td>\n",
       "      <td>304284.0</td>\n",
       "      <td>126917.0</td>\n",
       "      <td>436932.0</td>\n",
       "      <td>226.798480</td>\n",
       "      <td>273.739345</td>\n",
       "      <td>222.417599</td>\n",
       "      <td>264.713904</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>1992_DELAWARE</td>\n",
       "      <td>DELAWARE</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>645233.0</td>\n",
       "      <td>45945.0</td>\n",
       "      <td>420942.0</td>\n",
       "      <td>178346.0</td>\n",
       "      <td>638784.0</td>\n",
       "      <td>372722.0</td>\n",
       "      <td>...</td>\n",
       "      <td>8272.0</td>\n",
       "      <td>8012.0</td>\n",
       "      <td>6129.0</td>\n",
       "      <td>67495.0</td>\n",
       "      <td>28338.0</td>\n",
       "      <td>96296.0</td>\n",
       "      <td>217.899972</td>\n",
       "      <td>262.868585</td>\n",
       "      <td>206.389052</td>\n",
       "      <td>261.577921</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>1992_DISTRICT_OF_COLUMBIA</td>\n",
       "      <td>DISTRICT_OF_COLUMBIA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>709480.0</td>\n",
       "      <td>64749.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>644731.0</td>\n",
       "      <td>742893.0</td>\n",
       "      <td>329160.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5832.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>3433.0</td>\n",
       "      <td>47009.0</td>\n",
       "      <td>18173.0</td>\n",
       "      <td>70000.0</td>\n",
       "      <td>192.600553</td>\n",
       "      <td>234.924621</td>\n",
       "      <td>178.557612</td>\n",
       "      <td>265.976765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>1992_FLORIDA</td>\n",
       "      <td>FLORIDA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11506299.0</td>\n",
       "      <td>788420.0</td>\n",
       "      <td>5683949.0</td>\n",
       "      <td>5033930.0</td>\n",
       "      <td>11305642.0</td>\n",
       "      <td>5166374.0</td>\n",
       "      <td>...</td>\n",
       "      <td>164416.0</td>\n",
       "      <td>142372.0</td>\n",
       "      <td>100835.0</td>\n",
       "      <td>1276685.0</td>\n",
       "      <td>511557.0</td>\n",
       "      <td>1819706.0</td>\n",
       "      <td>213.689751</td>\n",
       "      <td>259.908848</td>\n",
       "      <td>204.882606</td>\n",
       "      <td>262.118986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>1992_GEORGIA</td>\n",
       "      <td>GEORGIA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5536901.0</td>\n",
       "      <td>398701.0</td>\n",
       "      <td>2798674.0</td>\n",
       "      <td>2339526.0</td>\n",
       "      <td>5535942.0</td>\n",
       "      <td>3043984.0</td>\n",
       "      <td>...</td>\n",
       "      <td>99648.0</td>\n",
       "      <td>92374.0</td>\n",
       "      <td>63646.0</td>\n",
       "      <td>787599.0</td>\n",
       "      <td>315539.0</td>\n",
       "      <td>1106441.0</td>\n",
       "      <td>215.594906</td>\n",
       "      <td>259.359434</td>\n",
       "      <td>206.844175</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>1992_HAWAII</td>\n",
       "      <td>HAWAII</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>996809.0</td>\n",
       "      <td>71273.0</td>\n",
       "      <td>903443.0</td>\n",
       "      <td>22093.0</td>\n",
       "      <td>1040121.0</td>\n",
       "      <td>536115.0</td>\n",
       "      <td>...</td>\n",
       "      <td>13754.0</td>\n",
       "      <td>11750.0</td>\n",
       "      <td>9051.0</td>\n",
       "      <td>107242.0</td>\n",
       "      <td>43882.0</td>\n",
       "      <td>151649.0</td>\n",
       "      <td>214.056666</td>\n",
       "      <td>257.410887</td>\n",
       "      <td>200.880272</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>1992_IDAHO</td>\n",
       "      <td>IDAHO</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>859329.0</td>\n",
       "      <td>69138.0</td>\n",
       "      <td>531912.0</td>\n",
       "      <td>258279.0</td>\n",
       "      <td>886161.0</td>\n",
       "      <td>473505.0</td>\n",
       "      <td>...</td>\n",
       "      <td>18607.0</td>\n",
       "      <td>18880.0</td>\n",
       "      <td>14593.0</td>\n",
       "      <td>146573.0</td>\n",
       "      <td>66541.0</td>\n",
       "      <td>214345.0</td>\n",
       "      <td>221.562534</td>\n",
       "      <td>275.090294</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>1992_ILLINOIS</td>\n",
       "      <td>ILLINOIS</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9748650.0</td>\n",
       "      <td>597077.0</td>\n",
       "      <td>3073178.0</td>\n",
       "      <td>6078395.0</td>\n",
       "      <td>9850560.0</td>\n",
       "      <td>5010400.0</td>\n",
       "      <td>...</td>\n",
       "      <td>133120.0</td>\n",
       "      <td>134317.0</td>\n",
       "      <td>106475.0</td>\n",
       "      <td>1111167.0</td>\n",
       "      <td>495562.0</td>\n",
       "      <td>1646411.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>1992_INDIANA</td>\n",
       "      <td>INDIANA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5060274.0</td>\n",
       "      <td>257044.0</td>\n",
       "      <td>2578149.0</td>\n",
       "      <td>2225081.0</td>\n",
       "      <td>5182754.0</td>\n",
       "      <td>2598925.0</td>\n",
       "      <td>...</td>\n",
       "      <td>73760.0</td>\n",
       "      <td>75477.0</td>\n",
       "      <td>62234.0</td>\n",
       "      <td>601890.0</td>\n",
       "      <td>278161.0</td>\n",
       "      <td>883276.0</td>\n",
       "      <td>221.037742</td>\n",
       "      <td>270.098944</td>\n",
       "      <td>219.763258</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>1992_IOWA</td>\n",
       "      <td>IOWA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2663934.0</td>\n",
       "      <td>125665.0</td>\n",
       "      <td>1176205.0</td>\n",
       "      <td>1362064.0</td>\n",
       "      <td>2795774.0</td>\n",
       "      <td>1446478.0</td>\n",
       "      <td>...</td>\n",
       "      <td>37692.0</td>\n",
       "      <td>36892.0</td>\n",
       "      <td>33057.0</td>\n",
       "      <td>299253.0</td>\n",
       "      <td>138907.0</td>\n",
       "      <td>442752.0</td>\n",
       "      <td>229.884078</td>\n",
       "      <td>283.360009</td>\n",
       "      <td>222.852939</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>1992_KANSAS</td>\n",
       "      <td>KANSAS</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2245348.0</td>\n",
       "      <td>121625.0</td>\n",
       "      <td>903199.0</td>\n",
       "      <td>1220524.0</td>\n",
       "      <td>2234915.0</td>\n",
       "      <td>1165749.0</td>\n",
       "      <td>...</td>\n",
       "      <td>36013.0</td>\n",
       "      <td>33288.0</td>\n",
       "      <td>26706.0</td>\n",
       "      <td>284143.0</td>\n",
       "      <td>120960.0</td>\n",
       "      <td>407494.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>1992_KENTUCKY</td>\n",
       "      <td>KENTUCKY</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2642902.0</td>\n",
       "      <td>289902.0</td>\n",
       "      <td>1643109.0</td>\n",
       "      <td>709891.0</td>\n",
       "      <td>2518082.0</td>\n",
       "      <td>1343438.0</td>\n",
       "      <td>...</td>\n",
       "      <td>49666.0</td>\n",
       "      <td>49993.0</td>\n",
       "      <td>38029.0</td>\n",
       "      <td>400849.0</td>\n",
       "      <td>181786.0</td>\n",
       "      <td>597199.0</td>\n",
       "      <td>215.048158</td>\n",
       "      <td>262.241282</td>\n",
       "      <td>211.562307</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>1992_LOUISIANA</td>\n",
       "      <td>LOUISIANA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3341253.0</td>\n",
       "      <td>367822.0</td>\n",
       "      <td>1848734.0</td>\n",
       "      <td>1124697.0</td>\n",
       "      <td>3362853.0</td>\n",
       "      <td>1888349.0</td>\n",
       "      <td>...</td>\n",
       "      <td>61125.0</td>\n",
       "      <td>55942.0</td>\n",
       "      <td>38368.0</td>\n",
       "      <td>490112.0</td>\n",
       "      <td>196891.0</td>\n",
       "      <td>698442.0</td>\n",
       "      <td>204.140211</td>\n",
       "      <td>249.983926</td>\n",
       "      <td>196.762268</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>1992_MAINE</td>\n",
       "      <td>MAINE</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1206819.0</td>\n",
       "      <td>73160.0</td>\n",
       "      <td>511654.0</td>\n",
       "      <td>622005.0</td>\n",
       "      <td>1228869.0</td>\n",
       "      <td>685350.0</td>\n",
       "      <td>...</td>\n",
       "      <td>17154.0</td>\n",
       "      <td>15969.0</td>\n",
       "      <td>13882.0</td>\n",
       "      <td>135320.0</td>\n",
       "      <td>59289.0</td>\n",
       "      <td>195882.0</td>\n",
       "      <td>231.638840</td>\n",
       "      <td>278.635384</td>\n",
       "      <td>228.380027</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>20</td>\n",
       "      <td>1992_MARYLAND</td>\n",
       "      <td>MARYLAND</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4658498.0</td>\n",
       "      <td>228336.0</td>\n",
       "      <td>1778834.0</td>\n",
       "      <td>2651328.0</td>\n",
       "      <td>4698374.0</td>\n",
       "      <td>2628891.0</td>\n",
       "      <td>...</td>\n",
       "      <td>60287.0</td>\n",
       "      <td>52815.0</td>\n",
       "      <td>40426.0</td>\n",
       "      <td>472622.0</td>\n",
       "      <td>189795.0</td>\n",
       "      <td>678498.0</td>\n",
       "      <td>217.317708</td>\n",
       "      <td>264.825493</td>\n",
       "      <td>209.645497</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21</td>\n",
       "      <td>1992_MASSACHUSETTS</td>\n",
       "      <td>MASSACHUSETTS</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5517659.0</td>\n",
       "      <td>273946.0</td>\n",
       "      <td>1439051.0</td>\n",
       "      <td>3804662.0</td>\n",
       "      <td>5245560.0</td>\n",
       "      <td>2751871.0</td>\n",
       "      <td>...</td>\n",
       "      <td>66822.0</td>\n",
       "      <td>60702.0</td>\n",
       "      <td>52425.0</td>\n",
       "      <td>536029.0</td>\n",
       "      <td>230299.0</td>\n",
       "      <td>777050.0</td>\n",
       "      <td>226.597918</td>\n",
       "      <td>272.783201</td>\n",
       "      <td>223.160076</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>22</td>\n",
       "      <td>1992_MICHIGAN</td>\n",
       "      <td>MICHIGAN</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9963137.0</td>\n",
       "      <td>537917.0</td>\n",
       "      <td>2539380.0</td>\n",
       "      <td>6885840.0</td>\n",
       "      <td>10170688.0</td>\n",
       "      <td>4681327.0</td>\n",
       "      <td>...</td>\n",
       "      <td>118963.0</td>\n",
       "      <td>114282.0</td>\n",
       "      <td>90655.0</td>\n",
       "      <td>968910.0</td>\n",
       "      <td>419351.0</td>\n",
       "      <td>1398802.0</td>\n",
       "      <td>219.878352</td>\n",
       "      <td>267.353194</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>23</td>\n",
       "      <td>1992_MINNESOTA</td>\n",
       "      <td>MINNESOTA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4684684.0</td>\n",
       "      <td>194092.0</td>\n",
       "      <td>2380754.0</td>\n",
       "      <td>2109838.0</td>\n",
       "      <td>4981125.0</td>\n",
       "      <td>2534882.0</td>\n",
       "      <td>...</td>\n",
       "      <td>62606.0</td>\n",
       "      <td>59810.0</td>\n",
       "      <td>53813.0</td>\n",
       "      <td>500938.0</td>\n",
       "      <td>224426.0</td>\n",
       "      <td>731758.0</td>\n",
       "      <td>228.493596</td>\n",
       "      <td>282.392205</td>\n",
       "      <td>218.301709</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24</td>\n",
       "      <td>1992_MISSISSIPPI</td>\n",
       "      <td>MISSISSIPPI</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1684706.0</td>\n",
       "      <td>277706.0</td>\n",
       "      <td>901199.0</td>\n",
       "      <td>505801.0</td>\n",
       "      <td>1691990.0</td>\n",
       "      <td>956104.0</td>\n",
       "      <td>...</td>\n",
       "      <td>39839.0</td>\n",
       "      <td>38132.0</td>\n",
       "      <td>26328.0</td>\n",
       "      <td>321614.0</td>\n",
       "      <td>129554.0</td>\n",
       "      <td>451986.0</td>\n",
       "      <td>201.828261</td>\n",
       "      <td>246.458035</td>\n",
       "      <td>201.529328</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>25 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  PRIMARY_KEY                 STATE  YEAR  ENROLL  \\\n",
       "0                1992_ALABAMA               ALABAMA  1992     NaN   \n",
       "1                 1992_ALASKA                ALASKA  1992     NaN   \n",
       "2                1992_ARIZONA               ARIZONA  1992     NaN   \n",
       "3               1992_ARKANSAS              ARKANSAS  1992     NaN   \n",
       "4             1992_CALIFORNIA            CALIFORNIA  1992     NaN   \n",
       "5               1992_COLORADO              COLORADO  1992     NaN   \n",
       "6            1992_CONNECTICUT           CONNECTICUT  1992     NaN   \n",
       "7               1992_DELAWARE              DELAWARE  1992     NaN   \n",
       "8   1992_DISTRICT_OF_COLUMBIA  DISTRICT_OF_COLUMBIA  1992     NaN   \n",
       "9                1992_FLORIDA               FLORIDA  1992     NaN   \n",
       "10               1992_GEORGIA               GEORGIA  1992     NaN   \n",
       "11                1992_HAWAII                HAWAII  1992     NaN   \n",
       "12                 1992_IDAHO                 IDAHO  1992     NaN   \n",
       "13              1992_ILLINOIS              ILLINOIS  1992     NaN   \n",
       "14               1992_INDIANA               INDIANA  1992     NaN   \n",
       "15                  1992_IOWA                  IOWA  1992     NaN   \n",
       "16                1992_KANSAS                KANSAS  1992     NaN   \n",
       "17              1992_KENTUCKY              KENTUCKY  1992     NaN   \n",
       "18             1992_LOUISIANA             LOUISIANA  1992     NaN   \n",
       "19                 1992_MAINE                 MAINE  1992     NaN   \n",
       "20              1992_MARYLAND              MARYLAND  1992     NaN   \n",
       "21         1992_MASSACHUSETTS         MASSACHUSETTS  1992     NaN   \n",
       "22              1992_MICHIGAN              MICHIGAN  1992     NaN   \n",
       "23             1992_MINNESOTA             MINNESOTA  1992     NaN   \n",
       "24           1992_MISSISSIPPI           MISSISSIPPI  1992     NaN   \n",
       "\n",
       "    TOTAL_REVENUE  FEDERAL_REVENUE  STATE_REVENUE  LOCAL_REVENUE  \\\n",
       "0       2678885.0         304177.0      1659028.0       715680.0   \n",
       "1       1049591.0         106780.0       720711.0       222100.0   \n",
       "2       3258079.0         297888.0      1369815.0      1590376.0   \n",
       "3       1711959.0         178571.0       958785.0       574603.0   \n",
       "4      26260025.0        2072470.0     16546514.0      7641041.0   \n",
       "5       3185173.0         163253.0      1307986.0      1713934.0   \n",
       "6       3834302.0         143542.0      1342539.0      2348221.0   \n",
       "7        645233.0          45945.0       420942.0       178346.0   \n",
       "8        709480.0          64749.0            0.0       644731.0   \n",
       "9      11506299.0         788420.0      5683949.0      5033930.0   \n",
       "10      5536901.0         398701.0      2798674.0      2339526.0   \n",
       "11       996809.0          71273.0       903443.0        22093.0   \n",
       "12       859329.0          69138.0       531912.0       258279.0   \n",
       "13      9748650.0         597077.0      3073178.0      6078395.0   \n",
       "14      5060274.0         257044.0      2578149.0      2225081.0   \n",
       "15      2663934.0         125665.0      1176205.0      1362064.0   \n",
       "16      2245348.0         121625.0       903199.0      1220524.0   \n",
       "17      2642902.0         289902.0      1643109.0       709891.0   \n",
       "18      3341253.0         367822.0      1848734.0      1124697.0   \n",
       "19      1206819.0          73160.0       511654.0       622005.0   \n",
       "20      4658498.0         228336.0      1778834.0      2651328.0   \n",
       "21      5517659.0         273946.0      1439051.0      3804662.0   \n",
       "22      9963137.0         537917.0      2539380.0      6885840.0   \n",
       "23      4684684.0         194092.0      2380754.0      2109838.0   \n",
       "24      1684706.0         277706.0       901199.0       505801.0   \n",
       "\n",
       "    TOTAL_EXPENDITURE  INSTRUCTION_EXPENDITURE  ...  GRADES_4_G  GRADES_8_G  \\\n",
       "0           2653798.0                1481703.0  ...     57948.0     58025.0   \n",
       "1            972488.0                 498362.0  ...      9748.0      8789.0   \n",
       "2           3401580.0                1435908.0  ...     55433.0     49081.0   \n",
       "3           1743022.0                 964323.0  ...     34632.0     36011.0   \n",
       "4          27138832.0               14358922.0  ...    418418.0    363296.0   \n",
       "5           3264826.0                1642466.0  ...     50648.0     45025.0   \n",
       "6           3721338.0                2148041.0  ...     38058.0     33691.0   \n",
       "7            638784.0                 372722.0  ...      8272.0      8012.0   \n",
       "8            742893.0                 329160.0  ...      5832.0      5000.0   \n",
       "9          11305642.0                5166374.0  ...    164416.0    142372.0   \n",
       "10          5535942.0                3043984.0  ...     99648.0     92374.0   \n",
       "11          1040121.0                 536115.0  ...     13754.0     11750.0   \n",
       "12           886161.0                 473505.0  ...     18607.0     18880.0   \n",
       "13          9850560.0                5010400.0  ...    133120.0    134317.0   \n",
       "14          5182754.0                2598925.0  ...     73760.0     75477.0   \n",
       "15          2795774.0                1446478.0  ...     37692.0     36892.0   \n",
       "16          2234915.0                1165749.0  ...     36013.0     33288.0   \n",
       "17          2518082.0                1343438.0  ...     49666.0     49993.0   \n",
       "18          3362853.0                1888349.0  ...     61125.0     55942.0   \n",
       "19          1228869.0                 685350.0  ...     17154.0     15969.0   \n",
       "20          4698374.0                2628891.0  ...     60287.0     52815.0   \n",
       "21          5245560.0                2751871.0  ...     66822.0     60702.0   \n",
       "22         10170688.0                4681327.0  ...    118963.0    114282.0   \n",
       "23          4981125.0                2534882.0  ...     62606.0     59810.0   \n",
       "24          1691990.0                 956104.0  ...     39839.0     38132.0   \n",
       "\n",
       "    GRADES_12_G  GRADES_1_8_G  GRADES_9_12_G  GRADES_ALL_G  AVG_MATH_4_SCORE  \\\n",
       "0       41167.0      471564.0       196386.0      676174.0        208.327876   \n",
       "1        6714.0       79117.0        30847.0      112335.0               NaN   \n",
       "2       37410.0      437127.0       175210.0      614881.0        215.253932   \n",
       "3       27651.0      281338.0       123113.0      405259.0        210.206028   \n",
       "4      270675.0     3286034.0      1372011.0     4717112.0        208.398961   \n",
       "5       34533.0      394904.0       160299.0      562613.0        221.023429   \n",
       "6       28366.0      304284.0       126917.0      436932.0        226.798480   \n",
       "7        6129.0       67495.0        28338.0       96296.0        217.899972   \n",
       "8        3433.0       47009.0        18173.0       70000.0        192.600553   \n",
       "9      100835.0     1276685.0       511557.0     1819706.0        213.689751   \n",
       "10      63646.0      787599.0       315539.0     1106441.0        215.594906   \n",
       "11       9051.0      107242.0        43882.0      151649.0        214.056666   \n",
       "12      14593.0      146573.0        66541.0      214345.0        221.562534   \n",
       "13     106475.0     1111167.0       495562.0     1646411.0               NaN   \n",
       "14      62234.0      601890.0       278161.0      883276.0        221.037742   \n",
       "15      33057.0      299253.0       138907.0      442752.0        229.884078   \n",
       "16      26706.0      284143.0       120960.0      407494.0               NaN   \n",
       "17      38029.0      400849.0       181786.0      597199.0        215.048158   \n",
       "18      38368.0      490112.0       196891.0      698442.0        204.140211   \n",
       "19      13882.0      135320.0        59289.0      195882.0        231.638840   \n",
       "20      40426.0      472622.0       189795.0      678498.0        217.317708   \n",
       "21      52425.0      536029.0       230299.0      777050.0        226.597918   \n",
       "22      90655.0      968910.0       419351.0     1398802.0        219.878352   \n",
       "23      53813.0      500938.0       224426.0      731758.0        228.493596   \n",
       "24      26328.0      321614.0       129554.0      451986.0        201.828261   \n",
       "\n",
       "    AVG_MATH_8_SCORE  AVG_READING_4_SCORE  AVG_READING_8_SCORE  \n",
       "0         252.187522           207.963517                  NaN  \n",
       "1                NaN                  NaN           258.859712  \n",
       "2         265.366278           206.212716           262.169895  \n",
       "3         256.312090           208.634458           264.619665  \n",
       "4         260.892247           196.764414                  NaN  \n",
       "5         272.398433           213.480890           266.419687  \n",
       "6         273.739345           222.417599           264.713904  \n",
       "7         262.868585           206.389052           261.577921  \n",
       "8         234.924621           178.557612           265.976765  \n",
       "9         259.908848           204.882606           262.118986  \n",
       "10        259.359434           206.844175                  NaN  \n",
       "11        257.410887           200.880272                  NaN  \n",
       "12        275.090294                  NaN                  NaN  \n",
       "13               NaN                  NaN                  NaN  \n",
       "14        270.098944           219.763258                  NaN  \n",
       "15        283.360009           222.852939                  NaN  \n",
       "16               NaN                  NaN                  NaN  \n",
       "17        262.241282           211.562307                  NaN  \n",
       "18        249.983926           196.762268                  NaN  \n",
       "19        278.635384           228.380027                  NaN  \n",
       "20        264.825493           209.645497                  NaN  \n",
       "21        272.783201           223.160076                  NaN  \n",
       "22        267.353194                  NaN                  NaN  \n",
       "23        282.392205           218.301709                  NaN  \n",
       "24        246.458035           201.529328                  NaN  \n",
       "\n",
       "[25 rows x 25 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "useducation_df.head(25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##For ENROLL and AVG_READING_8_SCORE, there are too many NaN, so it make sense if I toss out. For other items, I will use the average of the states.\n",
    "=> more than 40-50%, don't use imputation\n",
    "\n",
    "## what is inplace=True doing?\n",
    "## what is \":\" doing?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>PRIMARY_KEY</th>\n",
       "      <th>STATE</th>\n",
       "      <th>YEAR</th>\n",
       "      <th>ENROLL</th>\n",
       "      <th>TOTAL_REVENUE</th>\n",
       "      <th>FEDERAL_REVENUE</th>\n",
       "      <th>STATE_REVENUE</th>\n",
       "      <th>LOCAL_REVENUE</th>\n",
       "      <th>TOTAL_EXPENDITURE</th>\n",
       "      <th>INSTRUCTION_EXPENDITURE</th>\n",
       "      <th>...</th>\n",
       "      <th>GRADES_4_G</th>\n",
       "      <th>GRADES_8_G</th>\n",
       "      <th>GRADES_12_G</th>\n",
       "      <th>GRADES_1_8_G</th>\n",
       "      <th>GRADES_9_12_G</th>\n",
       "      <th>GRADES_ALL_G</th>\n",
       "      <th>AVG_MATH_4_SCORE</th>\n",
       "      <th>AVG_MATH_8_SCORE</th>\n",
       "      <th>AVG_READING_4_SCORE</th>\n",
       "      <th>AVG_READING_8_SCORE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1992_ALABAMA</td>\n",
       "      <td>ALABAMA</td>\n",
       "      <td>1992</td>\n",
       "      <td>915930.820993</td>\n",
       "      <td>2678885.0</td>\n",
       "      <td>304177.0</td>\n",
       "      <td>1659028.0</td>\n",
       "      <td>715680.0</td>\n",
       "      <td>2653798.0</td>\n",
       "      <td>1481703.0</td>\n",
       "      <td>...</td>\n",
       "      <td>57948.0</td>\n",
       "      <td>58025.0</td>\n",
       "      <td>41167.0</td>\n",
       "      <td>471564.0</td>\n",
       "      <td>196386.0</td>\n",
       "      <td>676174.0</td>\n",
       "      <td>208.327876</td>\n",
       "      <td>252.187522</td>\n",
       "      <td>207.963517</td>\n",
       "      <td>263.661132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1992_ALASKA</td>\n",
       "      <td>ALASKA</td>\n",
       "      <td>1992</td>\n",
       "      <td>915930.820993</td>\n",
       "      <td>1049591.0</td>\n",
       "      <td>106780.0</td>\n",
       "      <td>720711.0</td>\n",
       "      <td>222100.0</td>\n",
       "      <td>972488.0</td>\n",
       "      <td>498362.0</td>\n",
       "      <td>...</td>\n",
       "      <td>9748.0</td>\n",
       "      <td>8789.0</td>\n",
       "      <td>6714.0</td>\n",
       "      <td>79117.0</td>\n",
       "      <td>30847.0</td>\n",
       "      <td>112335.0</td>\n",
       "      <td>234.768293</td>\n",
       "      <td>278.414711</td>\n",
       "      <td>218.866154</td>\n",
       "      <td>258.859712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>1992_ARIZONA</td>\n",
       "      <td>ARIZONA</td>\n",
       "      <td>1992</td>\n",
       "      <td>915930.820993</td>\n",
       "      <td>3258079.0</td>\n",
       "      <td>297888.0</td>\n",
       "      <td>1369815.0</td>\n",
       "      <td>1590376.0</td>\n",
       "      <td>3401580.0</td>\n",
       "      <td>1435908.0</td>\n",
       "      <td>...</td>\n",
       "      <td>55433.0</td>\n",
       "      <td>49081.0</td>\n",
       "      <td>37410.0</td>\n",
       "      <td>437127.0</td>\n",
       "      <td>175210.0</td>\n",
       "      <td>614881.0</td>\n",
       "      <td>215.253932</td>\n",
       "      <td>265.366278</td>\n",
       "      <td>206.212716</td>\n",
       "      <td>262.169895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1992_ARKANSAS</td>\n",
       "      <td>ARKANSAS</td>\n",
       "      <td>1992</td>\n",
       "      <td>915930.820993</td>\n",
       "      <td>1711959.0</td>\n",
       "      <td>178571.0</td>\n",
       "      <td>958785.0</td>\n",
       "      <td>574603.0</td>\n",
       "      <td>1743022.0</td>\n",
       "      <td>964323.0</td>\n",
       "      <td>...</td>\n",
       "      <td>34632.0</td>\n",
       "      <td>36011.0</td>\n",
       "      <td>27651.0</td>\n",
       "      <td>281338.0</td>\n",
       "      <td>123113.0</td>\n",
       "      <td>405259.0</td>\n",
       "      <td>210.206028</td>\n",
       "      <td>256.312090</td>\n",
       "      <td>208.634458</td>\n",
       "      <td>264.619665</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>1992_CALIFORNIA</td>\n",
       "      <td>CALIFORNIA</td>\n",
       "      <td>1992</td>\n",
       "      <td>915930.820993</td>\n",
       "      <td>26260025.0</td>\n",
       "      <td>2072470.0</td>\n",
       "      <td>16546514.0</td>\n",
       "      <td>7641041.0</td>\n",
       "      <td>27138832.0</td>\n",
       "      <td>14358922.0</td>\n",
       "      <td>...</td>\n",
       "      <td>418418.0</td>\n",
       "      <td>363296.0</td>\n",
       "      <td>270675.0</td>\n",
       "      <td>3286034.0</td>\n",
       "      <td>1372011.0</td>\n",
       "      <td>4717112.0</td>\n",
       "      <td>208.398961</td>\n",
       "      <td>260.892247</td>\n",
       "      <td>196.764414</td>\n",
       "      <td>263.661132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>1992_COLORADO</td>\n",
       "      <td>COLORADO</td>\n",
       "      <td>1992</td>\n",
       "      <td>915930.820993</td>\n",
       "      <td>3185173.0</td>\n",
       "      <td>163253.0</td>\n",
       "      <td>1307986.0</td>\n",
       "      <td>1713934.0</td>\n",
       "      <td>3264826.0</td>\n",
       "      <td>1642466.0</td>\n",
       "      <td>...</td>\n",
       "      <td>50648.0</td>\n",
       "      <td>45025.0</td>\n",
       "      <td>34533.0</td>\n",
       "      <td>394904.0</td>\n",
       "      <td>160299.0</td>\n",
       "      <td>562613.0</td>\n",
       "      <td>221.023429</td>\n",
       "      <td>272.398433</td>\n",
       "      <td>213.480890</td>\n",
       "      <td>266.419687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>1992_CONNECTICUT</td>\n",
       "      <td>CONNECTICUT</td>\n",
       "      <td>1992</td>\n",
       "      <td>915930.820993</td>\n",
       "      <td>3834302.0</td>\n",
       "      <td>143542.0</td>\n",
       "      <td>1342539.0</td>\n",
       "      <td>2348221.0</td>\n",
       "      <td>3721338.0</td>\n",
       "      <td>2148041.0</td>\n",
       "      <td>...</td>\n",
       "      <td>38058.0</td>\n",
       "      <td>33691.0</td>\n",
       "      <td>28366.0</td>\n",
       "      <td>304284.0</td>\n",
       "      <td>126917.0</td>\n",
       "      <td>436932.0</td>\n",
       "      <td>226.798480</td>\n",
       "      <td>273.739345</td>\n",
       "      <td>222.417599</td>\n",
       "      <td>264.713904</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>1992_DELAWARE</td>\n",
       "      <td>DELAWARE</td>\n",
       "      <td>1992</td>\n",
       "      <td>915930.820993</td>\n",
       "      <td>645233.0</td>\n",
       "      <td>45945.0</td>\n",
       "      <td>420942.0</td>\n",
       "      <td>178346.0</td>\n",
       "      <td>638784.0</td>\n",
       "      <td>372722.0</td>\n",
       "      <td>...</td>\n",
       "      <td>8272.0</td>\n",
       "      <td>8012.0</td>\n",
       "      <td>6129.0</td>\n",
       "      <td>67495.0</td>\n",
       "      <td>28338.0</td>\n",
       "      <td>96296.0</td>\n",
       "      <td>217.899972</td>\n",
       "      <td>262.868585</td>\n",
       "      <td>206.389052</td>\n",
       "      <td>261.577921</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>1992_DISTRICT_OF_COLUMBIA</td>\n",
       "      <td>DISTRICT_OF_COLUMBIA</td>\n",
       "      <td>1992</td>\n",
       "      <td>915930.820993</td>\n",
       "      <td>709480.0</td>\n",
       "      <td>64749.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>644731.0</td>\n",
       "      <td>742893.0</td>\n",
       "      <td>329160.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5832.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>3433.0</td>\n",
       "      <td>47009.0</td>\n",
       "      <td>18173.0</td>\n",
       "      <td>70000.0</td>\n",
       "      <td>192.600553</td>\n",
       "      <td>234.924621</td>\n",
       "      <td>178.557612</td>\n",
       "      <td>265.976765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>1992_FLORIDA</td>\n",
       "      <td>FLORIDA</td>\n",
       "      <td>1992</td>\n",
       "      <td>915930.820993</td>\n",
       "      <td>11506299.0</td>\n",
       "      <td>788420.0</td>\n",
       "      <td>5683949.0</td>\n",
       "      <td>5033930.0</td>\n",
       "      <td>11305642.0</td>\n",
       "      <td>5166374.0</td>\n",
       "      <td>...</td>\n",
       "      <td>164416.0</td>\n",
       "      <td>142372.0</td>\n",
       "      <td>100835.0</td>\n",
       "      <td>1276685.0</td>\n",
       "      <td>511557.0</td>\n",
       "      <td>1819706.0</td>\n",
       "      <td>213.689751</td>\n",
       "      <td>259.908848</td>\n",
       "      <td>204.882606</td>\n",
       "      <td>262.118986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>1992_GEORGIA</td>\n",
       "      <td>GEORGIA</td>\n",
       "      <td>1992</td>\n",
       "      <td>915930.820993</td>\n",
       "      <td>5536901.0</td>\n",
       "      <td>398701.0</td>\n",
       "      <td>2798674.0</td>\n",
       "      <td>2339526.0</td>\n",
       "      <td>5535942.0</td>\n",
       "      <td>3043984.0</td>\n",
       "      <td>...</td>\n",
       "      <td>99648.0</td>\n",
       "      <td>92374.0</td>\n",
       "      <td>63646.0</td>\n",
       "      <td>787599.0</td>\n",
       "      <td>315539.0</td>\n",
       "      <td>1106441.0</td>\n",
       "      <td>215.594906</td>\n",
       "      <td>259.359434</td>\n",
       "      <td>206.844175</td>\n",
       "      <td>263.661132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>1992_HAWAII</td>\n",
       "      <td>HAWAII</td>\n",
       "      <td>1992</td>\n",
       "      <td>915930.820993</td>\n",
       "      <td>996809.0</td>\n",
       "      <td>71273.0</td>\n",
       "      <td>903443.0</td>\n",
       "      <td>22093.0</td>\n",
       "      <td>1040121.0</td>\n",
       "      <td>536115.0</td>\n",
       "      <td>...</td>\n",
       "      <td>13754.0</td>\n",
       "      <td>11750.0</td>\n",
       "      <td>9051.0</td>\n",
       "      <td>107242.0</td>\n",
       "      <td>43882.0</td>\n",
       "      <td>151649.0</td>\n",
       "      <td>214.056666</td>\n",
       "      <td>257.410887</td>\n",
       "      <td>200.880272</td>\n",
       "      <td>263.661132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>1992_IDAHO</td>\n",
       "      <td>IDAHO</td>\n",
       "      <td>1992</td>\n",
       "      <td>915930.820993</td>\n",
       "      <td>859329.0</td>\n",
       "      <td>69138.0</td>\n",
       "      <td>531912.0</td>\n",
       "      <td>258279.0</td>\n",
       "      <td>886161.0</td>\n",
       "      <td>473505.0</td>\n",
       "      <td>...</td>\n",
       "      <td>18607.0</td>\n",
       "      <td>18880.0</td>\n",
       "      <td>14593.0</td>\n",
       "      <td>146573.0</td>\n",
       "      <td>66541.0</td>\n",
       "      <td>214345.0</td>\n",
       "      <td>221.562534</td>\n",
       "      <td>275.090294</td>\n",
       "      <td>218.866154</td>\n",
       "      <td>263.661132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>1992_ILLINOIS</td>\n",
       "      <td>ILLINOIS</td>\n",
       "      <td>1992</td>\n",
       "      <td>915930.820993</td>\n",
       "      <td>9748650.0</td>\n",
       "      <td>597077.0</td>\n",
       "      <td>3073178.0</td>\n",
       "      <td>6078395.0</td>\n",
       "      <td>9850560.0</td>\n",
       "      <td>5010400.0</td>\n",
       "      <td>...</td>\n",
       "      <td>133120.0</td>\n",
       "      <td>134317.0</td>\n",
       "      <td>106475.0</td>\n",
       "      <td>1111167.0</td>\n",
       "      <td>495562.0</td>\n",
       "      <td>1646411.0</td>\n",
       "      <td>234.768293</td>\n",
       "      <td>278.414711</td>\n",
       "      <td>218.866154</td>\n",
       "      <td>263.661132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>1992_INDIANA</td>\n",
       "      <td>INDIANA</td>\n",
       "      <td>1992</td>\n",
       "      <td>915930.820993</td>\n",
       "      <td>5060274.0</td>\n",
       "      <td>257044.0</td>\n",
       "      <td>2578149.0</td>\n",
       "      <td>2225081.0</td>\n",
       "      <td>5182754.0</td>\n",
       "      <td>2598925.0</td>\n",
       "      <td>...</td>\n",
       "      <td>73760.0</td>\n",
       "      <td>75477.0</td>\n",
       "      <td>62234.0</td>\n",
       "      <td>601890.0</td>\n",
       "      <td>278161.0</td>\n",
       "      <td>883276.0</td>\n",
       "      <td>221.037742</td>\n",
       "      <td>270.098944</td>\n",
       "      <td>219.763258</td>\n",
       "      <td>263.661132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>1992_IOWA</td>\n",
       "      <td>IOWA</td>\n",
       "      <td>1992</td>\n",
       "      <td>915930.820993</td>\n",
       "      <td>2663934.0</td>\n",
       "      <td>125665.0</td>\n",
       "      <td>1176205.0</td>\n",
       "      <td>1362064.0</td>\n",
       "      <td>2795774.0</td>\n",
       "      <td>1446478.0</td>\n",
       "      <td>...</td>\n",
       "      <td>37692.0</td>\n",
       "      <td>36892.0</td>\n",
       "      <td>33057.0</td>\n",
       "      <td>299253.0</td>\n",
       "      <td>138907.0</td>\n",
       "      <td>442752.0</td>\n",
       "      <td>229.884078</td>\n",
       "      <td>283.360009</td>\n",
       "      <td>222.852939</td>\n",
       "      <td>263.661132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>1992_KANSAS</td>\n",
       "      <td>KANSAS</td>\n",
       "      <td>1992</td>\n",
       "      <td>915930.820993</td>\n",
       "      <td>2245348.0</td>\n",
       "      <td>121625.0</td>\n",
       "      <td>903199.0</td>\n",
       "      <td>1220524.0</td>\n",
       "      <td>2234915.0</td>\n",
       "      <td>1165749.0</td>\n",
       "      <td>...</td>\n",
       "      <td>36013.0</td>\n",
       "      <td>33288.0</td>\n",
       "      <td>26706.0</td>\n",
       "      <td>284143.0</td>\n",
       "      <td>120960.0</td>\n",
       "      <td>407494.0</td>\n",
       "      <td>234.768293</td>\n",
       "      <td>278.414711</td>\n",
       "      <td>218.866154</td>\n",
       "      <td>263.661132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>1992_KENTUCKY</td>\n",
       "      <td>KENTUCKY</td>\n",
       "      <td>1992</td>\n",
       "      <td>915930.820993</td>\n",
       "      <td>2642902.0</td>\n",
       "      <td>289902.0</td>\n",
       "      <td>1643109.0</td>\n",
       "      <td>709891.0</td>\n",
       "      <td>2518082.0</td>\n",
       "      <td>1343438.0</td>\n",
       "      <td>...</td>\n",
       "      <td>49666.0</td>\n",
       "      <td>49993.0</td>\n",
       "      <td>38029.0</td>\n",
       "      <td>400849.0</td>\n",
       "      <td>181786.0</td>\n",
       "      <td>597199.0</td>\n",
       "      <td>215.048158</td>\n",
       "      <td>262.241282</td>\n",
       "      <td>211.562307</td>\n",
       "      <td>263.661132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>1992_LOUISIANA</td>\n",
       "      <td>LOUISIANA</td>\n",
       "      <td>1992</td>\n",
       "      <td>915930.820993</td>\n",
       "      <td>3341253.0</td>\n",
       "      <td>367822.0</td>\n",
       "      <td>1848734.0</td>\n",
       "      <td>1124697.0</td>\n",
       "      <td>3362853.0</td>\n",
       "      <td>1888349.0</td>\n",
       "      <td>...</td>\n",
       "      <td>61125.0</td>\n",
       "      <td>55942.0</td>\n",
       "      <td>38368.0</td>\n",
       "      <td>490112.0</td>\n",
       "      <td>196891.0</td>\n",
       "      <td>698442.0</td>\n",
       "      <td>204.140211</td>\n",
       "      <td>249.983926</td>\n",
       "      <td>196.762268</td>\n",
       "      <td>263.661132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>1992_MAINE</td>\n",
       "      <td>MAINE</td>\n",
       "      <td>1992</td>\n",
       "      <td>915930.820993</td>\n",
       "      <td>1206819.0</td>\n",
       "      <td>73160.0</td>\n",
       "      <td>511654.0</td>\n",
       "      <td>622005.0</td>\n",
       "      <td>1228869.0</td>\n",
       "      <td>685350.0</td>\n",
       "      <td>...</td>\n",
       "      <td>17154.0</td>\n",
       "      <td>15969.0</td>\n",
       "      <td>13882.0</td>\n",
       "      <td>135320.0</td>\n",
       "      <td>59289.0</td>\n",
       "      <td>195882.0</td>\n",
       "      <td>231.638840</td>\n",
       "      <td>278.635384</td>\n",
       "      <td>228.380027</td>\n",
       "      <td>263.661132</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>20 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  PRIMARY_KEY                 STATE  YEAR         ENROLL  \\\n",
       "0                1992_ALABAMA               ALABAMA  1992  915930.820993   \n",
       "1                 1992_ALASKA                ALASKA  1992  915930.820993   \n",
       "2                1992_ARIZONA               ARIZONA  1992  915930.820993   \n",
       "3               1992_ARKANSAS              ARKANSAS  1992  915930.820993   \n",
       "4             1992_CALIFORNIA            CALIFORNIA  1992  915930.820993   \n",
       "5               1992_COLORADO              COLORADO  1992  915930.820993   \n",
       "6            1992_CONNECTICUT           CONNECTICUT  1992  915930.820993   \n",
       "7               1992_DELAWARE              DELAWARE  1992  915930.820993   \n",
       "8   1992_DISTRICT_OF_COLUMBIA  DISTRICT_OF_COLUMBIA  1992  915930.820993   \n",
       "9                1992_FLORIDA               FLORIDA  1992  915930.820993   \n",
       "10               1992_GEORGIA               GEORGIA  1992  915930.820993   \n",
       "11                1992_HAWAII                HAWAII  1992  915930.820993   \n",
       "12                 1992_IDAHO                 IDAHO  1992  915930.820993   \n",
       "13              1992_ILLINOIS              ILLINOIS  1992  915930.820993   \n",
       "14               1992_INDIANA               INDIANA  1992  915930.820993   \n",
       "15                  1992_IOWA                  IOWA  1992  915930.820993   \n",
       "16                1992_KANSAS                KANSAS  1992  915930.820993   \n",
       "17              1992_KENTUCKY              KENTUCKY  1992  915930.820993   \n",
       "18             1992_LOUISIANA             LOUISIANA  1992  915930.820993   \n",
       "19                 1992_MAINE                 MAINE  1992  915930.820993   \n",
       "\n",
       "    TOTAL_REVENUE  FEDERAL_REVENUE  STATE_REVENUE  LOCAL_REVENUE  \\\n",
       "0       2678885.0         304177.0      1659028.0       715680.0   \n",
       "1       1049591.0         106780.0       720711.0       222100.0   \n",
       "2       3258079.0         297888.0      1369815.0      1590376.0   \n",
       "3       1711959.0         178571.0       958785.0       574603.0   \n",
       "4      26260025.0        2072470.0     16546514.0      7641041.0   \n",
       "5       3185173.0         163253.0      1307986.0      1713934.0   \n",
       "6       3834302.0         143542.0      1342539.0      2348221.0   \n",
       "7        645233.0          45945.0       420942.0       178346.0   \n",
       "8        709480.0          64749.0            0.0       644731.0   \n",
       "9      11506299.0         788420.0      5683949.0      5033930.0   \n",
       "10      5536901.0         398701.0      2798674.0      2339526.0   \n",
       "11       996809.0          71273.0       903443.0        22093.0   \n",
       "12       859329.0          69138.0       531912.0       258279.0   \n",
       "13      9748650.0         597077.0      3073178.0      6078395.0   \n",
       "14      5060274.0         257044.0      2578149.0      2225081.0   \n",
       "15      2663934.0         125665.0      1176205.0      1362064.0   \n",
       "16      2245348.0         121625.0       903199.0      1220524.0   \n",
       "17      2642902.0         289902.0      1643109.0       709891.0   \n",
       "18      3341253.0         367822.0      1848734.0      1124697.0   \n",
       "19      1206819.0          73160.0       511654.0       622005.0   \n",
       "\n",
       "    TOTAL_EXPENDITURE  INSTRUCTION_EXPENDITURE  ...  GRADES_4_G  GRADES_8_G  \\\n",
       "0           2653798.0                1481703.0  ...     57948.0     58025.0   \n",
       "1            972488.0                 498362.0  ...      9748.0      8789.0   \n",
       "2           3401580.0                1435908.0  ...     55433.0     49081.0   \n",
       "3           1743022.0                 964323.0  ...     34632.0     36011.0   \n",
       "4          27138832.0               14358922.0  ...    418418.0    363296.0   \n",
       "5           3264826.0                1642466.0  ...     50648.0     45025.0   \n",
       "6           3721338.0                2148041.0  ...     38058.0     33691.0   \n",
       "7            638784.0                 372722.0  ...      8272.0      8012.0   \n",
       "8            742893.0                 329160.0  ...      5832.0      5000.0   \n",
       "9          11305642.0                5166374.0  ...    164416.0    142372.0   \n",
       "10          5535942.0                3043984.0  ...     99648.0     92374.0   \n",
       "11          1040121.0                 536115.0  ...     13754.0     11750.0   \n",
       "12           886161.0                 473505.0  ...     18607.0     18880.0   \n",
       "13          9850560.0                5010400.0  ...    133120.0    134317.0   \n",
       "14          5182754.0                2598925.0  ...     73760.0     75477.0   \n",
       "15          2795774.0                1446478.0  ...     37692.0     36892.0   \n",
       "16          2234915.0                1165749.0  ...     36013.0     33288.0   \n",
       "17          2518082.0                1343438.0  ...     49666.0     49993.0   \n",
       "18          3362853.0                1888349.0  ...     61125.0     55942.0   \n",
       "19          1228869.0                 685350.0  ...     17154.0     15969.0   \n",
       "\n",
       "    GRADES_12_G  GRADES_1_8_G  GRADES_9_12_G  GRADES_ALL_G  AVG_MATH_4_SCORE  \\\n",
       "0       41167.0      471564.0       196386.0      676174.0        208.327876   \n",
       "1        6714.0       79117.0        30847.0      112335.0        234.768293   \n",
       "2       37410.0      437127.0       175210.0      614881.0        215.253932   \n",
       "3       27651.0      281338.0       123113.0      405259.0        210.206028   \n",
       "4      270675.0     3286034.0      1372011.0     4717112.0        208.398961   \n",
       "5       34533.0      394904.0       160299.0      562613.0        221.023429   \n",
       "6       28366.0      304284.0       126917.0      436932.0        226.798480   \n",
       "7        6129.0       67495.0        28338.0       96296.0        217.899972   \n",
       "8        3433.0       47009.0        18173.0       70000.0        192.600553   \n",
       "9      100835.0     1276685.0       511557.0     1819706.0        213.689751   \n",
       "10      63646.0      787599.0       315539.0     1106441.0        215.594906   \n",
       "11       9051.0      107242.0        43882.0      151649.0        214.056666   \n",
       "12      14593.0      146573.0        66541.0      214345.0        221.562534   \n",
       "13     106475.0     1111167.0       495562.0     1646411.0        234.768293   \n",
       "14      62234.0      601890.0       278161.0      883276.0        221.037742   \n",
       "15      33057.0      299253.0       138907.0      442752.0        229.884078   \n",
       "16      26706.0      284143.0       120960.0      407494.0        234.768293   \n",
       "17      38029.0      400849.0       181786.0      597199.0        215.048158   \n",
       "18      38368.0      490112.0       196891.0      698442.0        204.140211   \n",
       "19      13882.0      135320.0        59289.0      195882.0        231.638840   \n",
       "\n",
       "    AVG_MATH_8_SCORE  AVG_READING_4_SCORE  AVG_READING_8_SCORE  \n",
       "0         252.187522           207.963517           263.661132  \n",
       "1         278.414711           218.866154           258.859712  \n",
       "2         265.366278           206.212716           262.169895  \n",
       "3         256.312090           208.634458           264.619665  \n",
       "4         260.892247           196.764414           263.661132  \n",
       "5         272.398433           213.480890           266.419687  \n",
       "6         273.739345           222.417599           264.713904  \n",
       "7         262.868585           206.389052           261.577921  \n",
       "8         234.924621           178.557612           265.976765  \n",
       "9         259.908848           204.882606           262.118986  \n",
       "10        259.359434           206.844175           263.661132  \n",
       "11        257.410887           200.880272           263.661132  \n",
       "12        275.090294           218.866154           263.661132  \n",
       "13        278.414711           218.866154           263.661132  \n",
       "14        270.098944           219.763258           263.661132  \n",
       "15        283.360009           222.852939           263.661132  \n",
       "16        278.414711           218.866154           263.661132  \n",
       "17        262.241282           211.562307           263.661132  \n",
       "18        249.983926           196.762268           263.661132  \n",
       "19        278.635384           228.380027           263.661132  \n",
       "\n",
       "[20 rows x 25 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "useducation2_df = useducation_df.copy()\n",
    "\n",
    "fill_list = [\"ENROLL\",\"TOTAL_REVENUE\",\"FEDERAL_REVENUE\",\"STATE_REVENUE\",\"LOCAL_REVENUE\",\"TOTAL_EXPENDITURE\",\"INSTRUCTION_EXPENDITURE\",\"SUPPORT_SERVICES_EXPENDITURE\",\"OTHER_EXPENDITURE\",\"CAPITAL_OUTLAY_EXPENDITURE\",\"GRADES_PK_G\",\"GRADES_KG_G\",\"GRADES_4_G\",\"GRADES_8_G\",\"GRADES_12_G\",\"GRADES_1_8_G\",\"GRADES_9_12_G\",\"GRADES_ALL_G\",\"AVG_MATH_4_SCORE\",\"AVG_MATH_8_SCORE\",\"AVG_READING_4_SCORE\",\"AVG_READING_8_SCORE\"]\n",
    "\n",
    "\n",
    "for col in fill_list:\n",
    "    useducation2_df.loc[:,col] = useducation2_df.loc[:,col].fillna(useducation2_df.loc[:,col].mean())\n",
    "    \n",
    "useducation2_df.head(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. Now, take into account the time factor. Replicate your second answer but this time fill in the missing values by using a statistic that is calculated within the year of the observation. For example, if you want to fill a missing value for a variable with the mean of that variable, calculate the mean by using only the observations for that specific year."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1992, 2001, 1993, 2016, 1994, 1995, 1996, 1997, 1998, 1999, 2017,\n",
       "       2000, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011,\n",
       "       2012, 2013, 2014, 2015])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "useducation3_df = useducation_df.copy()\n",
    "\n",
    "years = useducation3_df[\"YEAR\"].unique()\n",
    "\n",
    "years"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>PRIMARY_KEY</th>\n",
       "      <th>STATE</th>\n",
       "      <th>YEAR</th>\n",
       "      <th>ENROLL</th>\n",
       "      <th>TOTAL_REVENUE</th>\n",
       "      <th>FEDERAL_REVENUE</th>\n",
       "      <th>STATE_REVENUE</th>\n",
       "      <th>LOCAL_REVENUE</th>\n",
       "      <th>TOTAL_EXPENDITURE</th>\n",
       "      <th>INSTRUCTION_EXPENDITURE</th>\n",
       "      <th>...</th>\n",
       "      <th>GRADES_4_G</th>\n",
       "      <th>GRADES_8_G</th>\n",
       "      <th>GRADES_12_G</th>\n",
       "      <th>GRADES_1_8_G</th>\n",
       "      <th>GRADES_9_12_G</th>\n",
       "      <th>GRADES_ALL_G</th>\n",
       "      <th>AVG_MATH_4_SCORE</th>\n",
       "      <th>AVG_MATH_8_SCORE</th>\n",
       "      <th>AVG_READING_4_SCORE</th>\n",
       "      <th>AVG_READING_8_SCORE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1992_ALABAMA</td>\n",
       "      <td>ALABAMA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2678885.0</td>\n",
       "      <td>304177.0</td>\n",
       "      <td>1659028.0</td>\n",
       "      <td>715680.0</td>\n",
       "      <td>2653798.0</td>\n",
       "      <td>1481703.0</td>\n",
       "      <td>...</td>\n",
       "      <td>57948.0</td>\n",
       "      <td>58025.0</td>\n",
       "      <td>41167.0</td>\n",
       "      <td>471564.0</td>\n",
       "      <td>196386.0</td>\n",
       "      <td>676174.0</td>\n",
       "      <td>208.327876</td>\n",
       "      <td>252.187522</td>\n",
       "      <td>207.963517</td>\n",
       "      <td>263.307067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1992_ALASKA</td>\n",
       "      <td>ALASKA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1049591.0</td>\n",
       "      <td>106780.0</td>\n",
       "      <td>720711.0</td>\n",
       "      <td>222100.0</td>\n",
       "      <td>972488.0</td>\n",
       "      <td>498362.0</td>\n",
       "      <td>...</td>\n",
       "      <td>9748.0</td>\n",
       "      <td>8789.0</td>\n",
       "      <td>6714.0</td>\n",
       "      <td>79117.0</td>\n",
       "      <td>30847.0</td>\n",
       "      <td>112335.0</td>\n",
       "      <td>218.410116</td>\n",
       "      <td>266.360319</td>\n",
       "      <td>212.712256</td>\n",
       "      <td>258.859712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>1992_ARIZONA</td>\n",
       "      <td>ARIZONA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3258079.0</td>\n",
       "      <td>297888.0</td>\n",
       "      <td>1369815.0</td>\n",
       "      <td>1590376.0</td>\n",
       "      <td>3401580.0</td>\n",
       "      <td>1435908.0</td>\n",
       "      <td>...</td>\n",
       "      <td>55433.0</td>\n",
       "      <td>49081.0</td>\n",
       "      <td>37410.0</td>\n",
       "      <td>437127.0</td>\n",
       "      <td>175210.0</td>\n",
       "      <td>614881.0</td>\n",
       "      <td>215.253932</td>\n",
       "      <td>265.366278</td>\n",
       "      <td>206.212716</td>\n",
       "      <td>262.169895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1992_ARKANSAS</td>\n",
       "      <td>ARKANSAS</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1711959.0</td>\n",
       "      <td>178571.0</td>\n",
       "      <td>958785.0</td>\n",
       "      <td>574603.0</td>\n",
       "      <td>1743022.0</td>\n",
       "      <td>964323.0</td>\n",
       "      <td>...</td>\n",
       "      <td>34632.0</td>\n",
       "      <td>36011.0</td>\n",
       "      <td>27651.0</td>\n",
       "      <td>281338.0</td>\n",
       "      <td>123113.0</td>\n",
       "      <td>405259.0</td>\n",
       "      <td>210.206028</td>\n",
       "      <td>256.312090</td>\n",
       "      <td>208.634458</td>\n",
       "      <td>264.619665</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>1992_CALIFORNIA</td>\n",
       "      <td>CALIFORNIA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26260025.0</td>\n",
       "      <td>2072470.0</td>\n",
       "      <td>16546514.0</td>\n",
       "      <td>7641041.0</td>\n",
       "      <td>27138832.0</td>\n",
       "      <td>14358922.0</td>\n",
       "      <td>...</td>\n",
       "      <td>418418.0</td>\n",
       "      <td>363296.0</td>\n",
       "      <td>270675.0</td>\n",
       "      <td>3286034.0</td>\n",
       "      <td>1372011.0</td>\n",
       "      <td>4717112.0</td>\n",
       "      <td>208.398961</td>\n",
       "      <td>260.892247</td>\n",
       "      <td>196.764414</td>\n",
       "      <td>263.307067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>1992_COLORADO</td>\n",
       "      <td>COLORADO</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3185173.0</td>\n",
       "      <td>163253.0</td>\n",
       "      <td>1307986.0</td>\n",
       "      <td>1713934.0</td>\n",
       "      <td>3264826.0</td>\n",
       "      <td>1642466.0</td>\n",
       "      <td>...</td>\n",
       "      <td>50648.0</td>\n",
       "      <td>45025.0</td>\n",
       "      <td>34533.0</td>\n",
       "      <td>394904.0</td>\n",
       "      <td>160299.0</td>\n",
       "      <td>562613.0</td>\n",
       "      <td>221.023429</td>\n",
       "      <td>272.398433</td>\n",
       "      <td>213.480890</td>\n",
       "      <td>266.419687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>1992_CONNECTICUT</td>\n",
       "      <td>CONNECTICUT</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3834302.0</td>\n",
       "      <td>143542.0</td>\n",
       "      <td>1342539.0</td>\n",
       "      <td>2348221.0</td>\n",
       "      <td>3721338.0</td>\n",
       "      <td>2148041.0</td>\n",
       "      <td>...</td>\n",
       "      <td>38058.0</td>\n",
       "      <td>33691.0</td>\n",
       "      <td>28366.0</td>\n",
       "      <td>304284.0</td>\n",
       "      <td>126917.0</td>\n",
       "      <td>436932.0</td>\n",
       "      <td>226.798480</td>\n",
       "      <td>273.739345</td>\n",
       "      <td>222.417599</td>\n",
       "      <td>264.713904</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>1992_DELAWARE</td>\n",
       "      <td>DELAWARE</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>645233.0</td>\n",
       "      <td>45945.0</td>\n",
       "      <td>420942.0</td>\n",
       "      <td>178346.0</td>\n",
       "      <td>638784.0</td>\n",
       "      <td>372722.0</td>\n",
       "      <td>...</td>\n",
       "      <td>8272.0</td>\n",
       "      <td>8012.0</td>\n",
       "      <td>6129.0</td>\n",
       "      <td>67495.0</td>\n",
       "      <td>28338.0</td>\n",
       "      <td>96296.0</td>\n",
       "      <td>217.899972</td>\n",
       "      <td>262.868585</td>\n",
       "      <td>206.389052</td>\n",
       "      <td>261.577921</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>1992_DISTRICT_OF_COLUMBIA</td>\n",
       "      <td>DISTRICT_OF_COLUMBIA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>709480.0</td>\n",
       "      <td>64749.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>644731.0</td>\n",
       "      <td>742893.0</td>\n",
       "      <td>329160.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5832.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>3433.0</td>\n",
       "      <td>47009.0</td>\n",
       "      <td>18173.0</td>\n",
       "      <td>70000.0</td>\n",
       "      <td>192.600553</td>\n",
       "      <td>234.924621</td>\n",
       "      <td>178.557612</td>\n",
       "      <td>265.976765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>1992_FLORIDA</td>\n",
       "      <td>FLORIDA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11506299.0</td>\n",
       "      <td>788420.0</td>\n",
       "      <td>5683949.0</td>\n",
       "      <td>5033930.0</td>\n",
       "      <td>11305642.0</td>\n",
       "      <td>5166374.0</td>\n",
       "      <td>...</td>\n",
       "      <td>164416.0</td>\n",
       "      <td>142372.0</td>\n",
       "      <td>100835.0</td>\n",
       "      <td>1276685.0</td>\n",
       "      <td>511557.0</td>\n",
       "      <td>1819706.0</td>\n",
       "      <td>213.689751</td>\n",
       "      <td>259.908848</td>\n",
       "      <td>204.882606</td>\n",
       "      <td>262.118986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>1992_GEORGIA</td>\n",
       "      <td>GEORGIA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5536901.0</td>\n",
       "      <td>398701.0</td>\n",
       "      <td>2798674.0</td>\n",
       "      <td>2339526.0</td>\n",
       "      <td>5535942.0</td>\n",
       "      <td>3043984.0</td>\n",
       "      <td>...</td>\n",
       "      <td>99648.0</td>\n",
       "      <td>92374.0</td>\n",
       "      <td>63646.0</td>\n",
       "      <td>787599.0</td>\n",
       "      <td>315539.0</td>\n",
       "      <td>1106441.0</td>\n",
       "      <td>215.594906</td>\n",
       "      <td>259.359434</td>\n",
       "      <td>206.844175</td>\n",
       "      <td>263.307067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>1992_HAWAII</td>\n",
       "      <td>HAWAII</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>996809.0</td>\n",
       "      <td>71273.0</td>\n",
       "      <td>903443.0</td>\n",
       "      <td>22093.0</td>\n",
       "      <td>1040121.0</td>\n",
       "      <td>536115.0</td>\n",
       "      <td>...</td>\n",
       "      <td>13754.0</td>\n",
       "      <td>11750.0</td>\n",
       "      <td>9051.0</td>\n",
       "      <td>107242.0</td>\n",
       "      <td>43882.0</td>\n",
       "      <td>151649.0</td>\n",
       "      <td>214.056666</td>\n",
       "      <td>257.410887</td>\n",
       "      <td>200.880272</td>\n",
       "      <td>263.307067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>1992_IDAHO</td>\n",
       "      <td>IDAHO</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>859329.0</td>\n",
       "      <td>69138.0</td>\n",
       "      <td>531912.0</td>\n",
       "      <td>258279.0</td>\n",
       "      <td>886161.0</td>\n",
       "      <td>473505.0</td>\n",
       "      <td>...</td>\n",
       "      <td>18607.0</td>\n",
       "      <td>18880.0</td>\n",
       "      <td>14593.0</td>\n",
       "      <td>146573.0</td>\n",
       "      <td>66541.0</td>\n",
       "      <td>214345.0</td>\n",
       "      <td>221.562534</td>\n",
       "      <td>275.090294</td>\n",
       "      <td>212.712256</td>\n",
       "      <td>263.307067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>1992_ILLINOIS</td>\n",
       "      <td>ILLINOIS</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9748650.0</td>\n",
       "      <td>597077.0</td>\n",
       "      <td>3073178.0</td>\n",
       "      <td>6078395.0</td>\n",
       "      <td>9850560.0</td>\n",
       "      <td>5010400.0</td>\n",
       "      <td>...</td>\n",
       "      <td>133120.0</td>\n",
       "      <td>134317.0</td>\n",
       "      <td>106475.0</td>\n",
       "      <td>1111167.0</td>\n",
       "      <td>495562.0</td>\n",
       "      <td>1646411.0</td>\n",
       "      <td>218.410116</td>\n",
       "      <td>266.360319</td>\n",
       "      <td>212.712256</td>\n",
       "      <td>263.307067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>1992_INDIANA</td>\n",
       "      <td>INDIANA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5060274.0</td>\n",
       "      <td>257044.0</td>\n",
       "      <td>2578149.0</td>\n",
       "      <td>2225081.0</td>\n",
       "      <td>5182754.0</td>\n",
       "      <td>2598925.0</td>\n",
       "      <td>...</td>\n",
       "      <td>73760.0</td>\n",
       "      <td>75477.0</td>\n",
       "      <td>62234.0</td>\n",
       "      <td>601890.0</td>\n",
       "      <td>278161.0</td>\n",
       "      <td>883276.0</td>\n",
       "      <td>221.037742</td>\n",
       "      <td>270.098944</td>\n",
       "      <td>219.763258</td>\n",
       "      <td>263.307067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>1992_IOWA</td>\n",
       "      <td>IOWA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2663934.0</td>\n",
       "      <td>125665.0</td>\n",
       "      <td>1176205.0</td>\n",
       "      <td>1362064.0</td>\n",
       "      <td>2795774.0</td>\n",
       "      <td>1446478.0</td>\n",
       "      <td>...</td>\n",
       "      <td>37692.0</td>\n",
       "      <td>36892.0</td>\n",
       "      <td>33057.0</td>\n",
       "      <td>299253.0</td>\n",
       "      <td>138907.0</td>\n",
       "      <td>442752.0</td>\n",
       "      <td>229.884078</td>\n",
       "      <td>283.360009</td>\n",
       "      <td>222.852939</td>\n",
       "      <td>263.307067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>1992_KANSAS</td>\n",
       "      <td>KANSAS</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2245348.0</td>\n",
       "      <td>121625.0</td>\n",
       "      <td>903199.0</td>\n",
       "      <td>1220524.0</td>\n",
       "      <td>2234915.0</td>\n",
       "      <td>1165749.0</td>\n",
       "      <td>...</td>\n",
       "      <td>36013.0</td>\n",
       "      <td>33288.0</td>\n",
       "      <td>26706.0</td>\n",
       "      <td>284143.0</td>\n",
       "      <td>120960.0</td>\n",
       "      <td>407494.0</td>\n",
       "      <td>218.410116</td>\n",
       "      <td>266.360319</td>\n",
       "      <td>212.712256</td>\n",
       "      <td>263.307067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>1992_KENTUCKY</td>\n",
       "      <td>KENTUCKY</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2642902.0</td>\n",
       "      <td>289902.0</td>\n",
       "      <td>1643109.0</td>\n",
       "      <td>709891.0</td>\n",
       "      <td>2518082.0</td>\n",
       "      <td>1343438.0</td>\n",
       "      <td>...</td>\n",
       "      <td>49666.0</td>\n",
       "      <td>49993.0</td>\n",
       "      <td>38029.0</td>\n",
       "      <td>400849.0</td>\n",
       "      <td>181786.0</td>\n",
       "      <td>597199.0</td>\n",
       "      <td>215.048158</td>\n",
       "      <td>262.241282</td>\n",
       "      <td>211.562307</td>\n",
       "      <td>263.307067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>1992_LOUISIANA</td>\n",
       "      <td>LOUISIANA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3341253.0</td>\n",
       "      <td>367822.0</td>\n",
       "      <td>1848734.0</td>\n",
       "      <td>1124697.0</td>\n",
       "      <td>3362853.0</td>\n",
       "      <td>1888349.0</td>\n",
       "      <td>...</td>\n",
       "      <td>61125.0</td>\n",
       "      <td>55942.0</td>\n",
       "      <td>38368.0</td>\n",
       "      <td>490112.0</td>\n",
       "      <td>196891.0</td>\n",
       "      <td>698442.0</td>\n",
       "      <td>204.140211</td>\n",
       "      <td>249.983926</td>\n",
       "      <td>196.762268</td>\n",
       "      <td>263.307067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>1992_MAINE</td>\n",
       "      <td>MAINE</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1206819.0</td>\n",
       "      <td>73160.0</td>\n",
       "      <td>511654.0</td>\n",
       "      <td>622005.0</td>\n",
       "      <td>1228869.0</td>\n",
       "      <td>685350.0</td>\n",
       "      <td>...</td>\n",
       "      <td>17154.0</td>\n",
       "      <td>15969.0</td>\n",
       "      <td>13882.0</td>\n",
       "      <td>135320.0</td>\n",
       "      <td>59289.0</td>\n",
       "      <td>195882.0</td>\n",
       "      <td>231.638840</td>\n",
       "      <td>278.635384</td>\n",
       "      <td>228.380027</td>\n",
       "      <td>263.307067</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>20 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  PRIMARY_KEY                 STATE  YEAR  ENROLL  \\\n",
       "0                1992_ALABAMA               ALABAMA  1992     NaN   \n",
       "1                 1992_ALASKA                ALASKA  1992     NaN   \n",
       "2                1992_ARIZONA               ARIZONA  1992     NaN   \n",
       "3               1992_ARKANSAS              ARKANSAS  1992     NaN   \n",
       "4             1992_CALIFORNIA            CALIFORNIA  1992     NaN   \n",
       "5               1992_COLORADO              COLORADO  1992     NaN   \n",
       "6            1992_CONNECTICUT           CONNECTICUT  1992     NaN   \n",
       "7               1992_DELAWARE              DELAWARE  1992     NaN   \n",
       "8   1992_DISTRICT_OF_COLUMBIA  DISTRICT_OF_COLUMBIA  1992     NaN   \n",
       "9                1992_FLORIDA               FLORIDA  1992     NaN   \n",
       "10               1992_GEORGIA               GEORGIA  1992     NaN   \n",
       "11                1992_HAWAII                HAWAII  1992     NaN   \n",
       "12                 1992_IDAHO                 IDAHO  1992     NaN   \n",
       "13              1992_ILLINOIS              ILLINOIS  1992     NaN   \n",
       "14               1992_INDIANA               INDIANA  1992     NaN   \n",
       "15                  1992_IOWA                  IOWA  1992     NaN   \n",
       "16                1992_KANSAS                KANSAS  1992     NaN   \n",
       "17              1992_KENTUCKY              KENTUCKY  1992     NaN   \n",
       "18             1992_LOUISIANA             LOUISIANA  1992     NaN   \n",
       "19                 1992_MAINE                 MAINE  1992     NaN   \n",
       "\n",
       "    TOTAL_REVENUE  FEDERAL_REVENUE  STATE_REVENUE  LOCAL_REVENUE  \\\n",
       "0       2678885.0         304177.0      1659028.0       715680.0   \n",
       "1       1049591.0         106780.0       720711.0       222100.0   \n",
       "2       3258079.0         297888.0      1369815.0      1590376.0   \n",
       "3       1711959.0         178571.0       958785.0       574603.0   \n",
       "4      26260025.0        2072470.0     16546514.0      7641041.0   \n",
       "5       3185173.0         163253.0      1307986.0      1713934.0   \n",
       "6       3834302.0         143542.0      1342539.0      2348221.0   \n",
       "7        645233.0          45945.0       420942.0       178346.0   \n",
       "8        709480.0          64749.0            0.0       644731.0   \n",
       "9      11506299.0         788420.0      5683949.0      5033930.0   \n",
       "10      5536901.0         398701.0      2798674.0      2339526.0   \n",
       "11       996809.0          71273.0       903443.0        22093.0   \n",
       "12       859329.0          69138.0       531912.0       258279.0   \n",
       "13      9748650.0         597077.0      3073178.0      6078395.0   \n",
       "14      5060274.0         257044.0      2578149.0      2225081.0   \n",
       "15      2663934.0         125665.0      1176205.0      1362064.0   \n",
       "16      2245348.0         121625.0       903199.0      1220524.0   \n",
       "17      2642902.0         289902.0      1643109.0       709891.0   \n",
       "18      3341253.0         367822.0      1848734.0      1124697.0   \n",
       "19      1206819.0          73160.0       511654.0       622005.0   \n",
       "\n",
       "    TOTAL_EXPENDITURE  INSTRUCTION_EXPENDITURE  ...  GRADES_4_G  GRADES_8_G  \\\n",
       "0           2653798.0                1481703.0  ...     57948.0     58025.0   \n",
       "1            972488.0                 498362.0  ...      9748.0      8789.0   \n",
       "2           3401580.0                1435908.0  ...     55433.0     49081.0   \n",
       "3           1743022.0                 964323.0  ...     34632.0     36011.0   \n",
       "4          27138832.0               14358922.0  ...    418418.0    363296.0   \n",
       "5           3264826.0                1642466.0  ...     50648.0     45025.0   \n",
       "6           3721338.0                2148041.0  ...     38058.0     33691.0   \n",
       "7            638784.0                 372722.0  ...      8272.0      8012.0   \n",
       "8            742893.0                 329160.0  ...      5832.0      5000.0   \n",
       "9          11305642.0                5166374.0  ...    164416.0    142372.0   \n",
       "10          5535942.0                3043984.0  ...     99648.0     92374.0   \n",
       "11          1040121.0                 536115.0  ...     13754.0     11750.0   \n",
       "12           886161.0                 473505.0  ...     18607.0     18880.0   \n",
       "13          9850560.0                5010400.0  ...    133120.0    134317.0   \n",
       "14          5182754.0                2598925.0  ...     73760.0     75477.0   \n",
       "15          2795774.0                1446478.0  ...     37692.0     36892.0   \n",
       "16          2234915.0                1165749.0  ...     36013.0     33288.0   \n",
       "17          2518082.0                1343438.0  ...     49666.0     49993.0   \n",
       "18          3362853.0                1888349.0  ...     61125.0     55942.0   \n",
       "19          1228869.0                 685350.0  ...     17154.0     15969.0   \n",
       "\n",
       "    GRADES_12_G  GRADES_1_8_G  GRADES_9_12_G  GRADES_ALL_G  AVG_MATH_4_SCORE  \\\n",
       "0       41167.0      471564.0       196386.0      676174.0        208.327876   \n",
       "1        6714.0       79117.0        30847.0      112335.0        218.410116   \n",
       "2       37410.0      437127.0       175210.0      614881.0        215.253932   \n",
       "3       27651.0      281338.0       123113.0      405259.0        210.206028   \n",
       "4      270675.0     3286034.0      1372011.0     4717112.0        208.398961   \n",
       "5       34533.0      394904.0       160299.0      562613.0        221.023429   \n",
       "6       28366.0      304284.0       126917.0      436932.0        226.798480   \n",
       "7        6129.0       67495.0        28338.0       96296.0        217.899972   \n",
       "8        3433.0       47009.0        18173.0       70000.0        192.600553   \n",
       "9      100835.0     1276685.0       511557.0     1819706.0        213.689751   \n",
       "10      63646.0      787599.0       315539.0     1106441.0        215.594906   \n",
       "11       9051.0      107242.0        43882.0      151649.0        214.056666   \n",
       "12      14593.0      146573.0        66541.0      214345.0        221.562534   \n",
       "13     106475.0     1111167.0       495562.0     1646411.0        218.410116   \n",
       "14      62234.0      601890.0       278161.0      883276.0        221.037742   \n",
       "15      33057.0      299253.0       138907.0      442752.0        229.884078   \n",
       "16      26706.0      284143.0       120960.0      407494.0        218.410116   \n",
       "17      38029.0      400849.0       181786.0      597199.0        215.048158   \n",
       "18      38368.0      490112.0       196891.0      698442.0        204.140211   \n",
       "19      13882.0      135320.0        59289.0      195882.0        231.638840   \n",
       "\n",
       "    AVG_MATH_8_SCORE  AVG_READING_4_SCORE  AVG_READING_8_SCORE  \n",
       "0         252.187522           207.963517           263.307067  \n",
       "1         266.360319           212.712256           258.859712  \n",
       "2         265.366278           206.212716           262.169895  \n",
       "3         256.312090           208.634458           264.619665  \n",
       "4         260.892247           196.764414           263.307067  \n",
       "5         272.398433           213.480890           266.419687  \n",
       "6         273.739345           222.417599           264.713904  \n",
       "7         262.868585           206.389052           261.577921  \n",
       "8         234.924621           178.557612           265.976765  \n",
       "9         259.908848           204.882606           262.118986  \n",
       "10        259.359434           206.844175           263.307067  \n",
       "11        257.410887           200.880272           263.307067  \n",
       "12        275.090294           212.712256           263.307067  \n",
       "13        266.360319           212.712256           263.307067  \n",
       "14        270.098944           219.763258           263.307067  \n",
       "15        283.360009           222.852939           263.307067  \n",
       "16        266.360319           212.712256           263.307067  \n",
       "17        262.241282           211.562307           263.307067  \n",
       "18        249.983926           196.762268           263.307067  \n",
       "19        278.635384           228.380027           263.307067  \n",
       "\n",
       "[20 rows x 25 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for col in fill_list:\n",
    "    for year in years:\n",
    "        useducation3_df.loc[useducation3_df[\"YEAR\"] == year, col] = useducation3_df.loc[useducation3_df[\"YEAR\"] == year,col].fillna(useducation3_df.loc[useducation3_df[\"YEAR\"] == year,col].mean())\n",
    "        \n",
    "        \n",
    "useducation3_df.head(20)\n",
    "        "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4. This time, fill in the missing values using interpolation (extrapolation)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PRIMARY_KEY</th>\n",
       "      <th>STATE</th>\n",
       "      <th>YEAR</th>\n",
       "      <th>ENROLL</th>\n",
       "      <th>TOTAL_REVENUE</th>\n",
       "      <th>FEDERAL_REVENUE</th>\n",
       "      <th>STATE_REVENUE</th>\n",
       "      <th>LOCAL_REVENUE</th>\n",
       "      <th>TOTAL_EXPENDITURE</th>\n",
       "      <th>INSTRUCTION_EXPENDITURE</th>\n",
       "      <th>...</th>\n",
       "      <th>GRADES_4_G</th>\n",
       "      <th>GRADES_8_G</th>\n",
       "      <th>GRADES_12_G</th>\n",
       "      <th>GRADES_1_8_G</th>\n",
       "      <th>GRADES_9_12_G</th>\n",
       "      <th>GRADES_ALL_G</th>\n",
       "      <th>AVG_MATH_4_SCORE</th>\n",
       "      <th>AVG_MATH_8_SCORE</th>\n",
       "      <th>AVG_READING_4_SCORE</th>\n",
       "      <th>AVG_READING_8_SCORE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1992_ALABAMA</td>\n",
       "      <td>ALABAMA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2678885.0</td>\n",
       "      <td>304177.0</td>\n",
       "      <td>1659028.0</td>\n",
       "      <td>715680.0</td>\n",
       "      <td>2653798.0</td>\n",
       "      <td>1481703.0</td>\n",
       "      <td>...</td>\n",
       "      <td>57948.0</td>\n",
       "      <td>58025.0</td>\n",
       "      <td>41167.0</td>\n",
       "      <td>471564.0</td>\n",
       "      <td>196386.0</td>\n",
       "      <td>676174.0</td>\n",
       "      <td>208.327876</td>\n",
       "      <td>252.187522</td>\n",
       "      <td>207.963517</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1992_ALASKA</td>\n",
       "      <td>ALASKA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1049591.0</td>\n",
       "      <td>106780.0</td>\n",
       "      <td>720711.0</td>\n",
       "      <td>222100.0</td>\n",
       "      <td>972488.0</td>\n",
       "      <td>498362.0</td>\n",
       "      <td>...</td>\n",
       "      <td>9748.0</td>\n",
       "      <td>8789.0</td>\n",
       "      <td>6714.0</td>\n",
       "      <td>79117.0</td>\n",
       "      <td>30847.0</td>\n",
       "      <td>112335.0</td>\n",
       "      <td>211.790904</td>\n",
       "      <td>258.776900</td>\n",
       "      <td>207.088116</td>\n",
       "      <td>258.859712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>1992_ARIZONA</td>\n",
       "      <td>ARIZONA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3258079.0</td>\n",
       "      <td>297888.0</td>\n",
       "      <td>1369815.0</td>\n",
       "      <td>1590376.0</td>\n",
       "      <td>3401580.0</td>\n",
       "      <td>1435908.0</td>\n",
       "      <td>...</td>\n",
       "      <td>55433.0</td>\n",
       "      <td>49081.0</td>\n",
       "      <td>37410.0</td>\n",
       "      <td>437127.0</td>\n",
       "      <td>175210.0</td>\n",
       "      <td>614881.0</td>\n",
       "      <td>215.253932</td>\n",
       "      <td>265.366278</td>\n",
       "      <td>206.212716</td>\n",
       "      <td>262.169895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1992_ARKANSAS</td>\n",
       "      <td>ARKANSAS</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1711959.0</td>\n",
       "      <td>178571.0</td>\n",
       "      <td>958785.0</td>\n",
       "      <td>574603.0</td>\n",
       "      <td>1743022.0</td>\n",
       "      <td>964323.0</td>\n",
       "      <td>...</td>\n",
       "      <td>34632.0</td>\n",
       "      <td>36011.0</td>\n",
       "      <td>27651.0</td>\n",
       "      <td>281338.0</td>\n",
       "      <td>123113.0</td>\n",
       "      <td>405259.0</td>\n",
       "      <td>210.206028</td>\n",
       "      <td>256.312090</td>\n",
       "      <td>208.634458</td>\n",
       "      <td>264.619665</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>1992_CALIFORNIA</td>\n",
       "      <td>CALIFORNIA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26260025.0</td>\n",
       "      <td>2072470.0</td>\n",
       "      <td>16546514.0</td>\n",
       "      <td>7641041.0</td>\n",
       "      <td>27138832.0</td>\n",
       "      <td>14358922.0</td>\n",
       "      <td>...</td>\n",
       "      <td>418418.0</td>\n",
       "      <td>363296.0</td>\n",
       "      <td>270675.0</td>\n",
       "      <td>3286034.0</td>\n",
       "      <td>1372011.0</td>\n",
       "      <td>4717112.0</td>\n",
       "      <td>208.398961</td>\n",
       "      <td>260.892247</td>\n",
       "      <td>196.764414</td>\n",
       "      <td>265.519676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>1992_COLORADO</td>\n",
       "      <td>COLORADO</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3185173.0</td>\n",
       "      <td>163253.0</td>\n",
       "      <td>1307986.0</td>\n",
       "      <td>1713934.0</td>\n",
       "      <td>3264826.0</td>\n",
       "      <td>1642466.0</td>\n",
       "      <td>...</td>\n",
       "      <td>50648.0</td>\n",
       "      <td>45025.0</td>\n",
       "      <td>34533.0</td>\n",
       "      <td>394904.0</td>\n",
       "      <td>160299.0</td>\n",
       "      <td>562613.0</td>\n",
       "      <td>221.023429</td>\n",
       "      <td>272.398433</td>\n",
       "      <td>213.480890</td>\n",
       "      <td>266.419687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>1992_CONNECTICUT</td>\n",
       "      <td>CONNECTICUT</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3834302.0</td>\n",
       "      <td>143542.0</td>\n",
       "      <td>1342539.0</td>\n",
       "      <td>2348221.0</td>\n",
       "      <td>3721338.0</td>\n",
       "      <td>2148041.0</td>\n",
       "      <td>...</td>\n",
       "      <td>38058.0</td>\n",
       "      <td>33691.0</td>\n",
       "      <td>28366.0</td>\n",
       "      <td>304284.0</td>\n",
       "      <td>126917.0</td>\n",
       "      <td>436932.0</td>\n",
       "      <td>226.798480</td>\n",
       "      <td>273.739345</td>\n",
       "      <td>222.417599</td>\n",
       "      <td>264.713904</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>1992_DELAWARE</td>\n",
       "      <td>DELAWARE</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>645233.0</td>\n",
       "      <td>45945.0</td>\n",
       "      <td>420942.0</td>\n",
       "      <td>178346.0</td>\n",
       "      <td>638784.0</td>\n",
       "      <td>372722.0</td>\n",
       "      <td>...</td>\n",
       "      <td>8272.0</td>\n",
       "      <td>8012.0</td>\n",
       "      <td>6129.0</td>\n",
       "      <td>67495.0</td>\n",
       "      <td>28338.0</td>\n",
       "      <td>96296.0</td>\n",
       "      <td>217.899972</td>\n",
       "      <td>262.868585</td>\n",
       "      <td>206.389052</td>\n",
       "      <td>261.577921</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>1992_DISTRICT_OF_COLUMBIA</td>\n",
       "      <td>DISTRICT_OF_COLUMBIA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>709480.0</td>\n",
       "      <td>64749.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>644731.0</td>\n",
       "      <td>742893.0</td>\n",
       "      <td>329160.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5832.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>3433.0</td>\n",
       "      <td>47009.0</td>\n",
       "      <td>18173.0</td>\n",
       "      <td>70000.0</td>\n",
       "      <td>192.600553</td>\n",
       "      <td>234.924621</td>\n",
       "      <td>178.557612</td>\n",
       "      <td>265.976765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>1992_FLORIDA</td>\n",
       "      <td>FLORIDA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11506299.0</td>\n",
       "      <td>788420.0</td>\n",
       "      <td>5683949.0</td>\n",
       "      <td>5033930.0</td>\n",
       "      <td>11305642.0</td>\n",
       "      <td>5166374.0</td>\n",
       "      <td>...</td>\n",
       "      <td>164416.0</td>\n",
       "      <td>142372.0</td>\n",
       "      <td>100835.0</td>\n",
       "      <td>1276685.0</td>\n",
       "      <td>511557.0</td>\n",
       "      <td>1819706.0</td>\n",
       "      <td>213.689751</td>\n",
       "      <td>259.908848</td>\n",
       "      <td>204.882606</td>\n",
       "      <td>262.118986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>1992_GEORGIA</td>\n",
       "      <td>GEORGIA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5536901.0</td>\n",
       "      <td>398701.0</td>\n",
       "      <td>2798674.0</td>\n",
       "      <td>2339526.0</td>\n",
       "      <td>5535942.0</td>\n",
       "      <td>3043984.0</td>\n",
       "      <td>...</td>\n",
       "      <td>99648.0</td>\n",
       "      <td>92374.0</td>\n",
       "      <td>63646.0</td>\n",
       "      <td>787599.0</td>\n",
       "      <td>315539.0</td>\n",
       "      <td>1106441.0</td>\n",
       "      <td>215.594906</td>\n",
       "      <td>259.359434</td>\n",
       "      <td>206.844175</td>\n",
       "      <td>262.109773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>1992_HAWAII</td>\n",
       "      <td>HAWAII</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>996809.0</td>\n",
       "      <td>71273.0</td>\n",
       "      <td>903443.0</td>\n",
       "      <td>22093.0</td>\n",
       "      <td>1040121.0</td>\n",
       "      <td>536115.0</td>\n",
       "      <td>...</td>\n",
       "      <td>13754.0</td>\n",
       "      <td>11750.0</td>\n",
       "      <td>9051.0</td>\n",
       "      <td>107242.0</td>\n",
       "      <td>43882.0</td>\n",
       "      <td>151649.0</td>\n",
       "      <td>214.056666</td>\n",
       "      <td>257.410887</td>\n",
       "      <td>200.880272</td>\n",
       "      <td>262.100561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>1992_IDAHO</td>\n",
       "      <td>IDAHO</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>859329.0</td>\n",
       "      <td>69138.0</td>\n",
       "      <td>531912.0</td>\n",
       "      <td>258279.0</td>\n",
       "      <td>886161.0</td>\n",
       "      <td>473505.0</td>\n",
       "      <td>...</td>\n",
       "      <td>18607.0</td>\n",
       "      <td>18880.0</td>\n",
       "      <td>14593.0</td>\n",
       "      <td>146573.0</td>\n",
       "      <td>66541.0</td>\n",
       "      <td>214345.0</td>\n",
       "      <td>221.562534</td>\n",
       "      <td>275.090294</td>\n",
       "      <td>207.174601</td>\n",
       "      <td>262.091348</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>1992_ILLINOIS</td>\n",
       "      <td>ILLINOIS</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9748650.0</td>\n",
       "      <td>597077.0</td>\n",
       "      <td>3073178.0</td>\n",
       "      <td>6078395.0</td>\n",
       "      <td>9850560.0</td>\n",
       "      <td>5010400.0</td>\n",
       "      <td>...</td>\n",
       "      <td>133120.0</td>\n",
       "      <td>134317.0</td>\n",
       "      <td>106475.0</td>\n",
       "      <td>1111167.0</td>\n",
       "      <td>495562.0</td>\n",
       "      <td>1646411.0</td>\n",
       "      <td>221.300138</td>\n",
       "      <td>272.594619</td>\n",
       "      <td>213.468929</td>\n",
       "      <td>262.082135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>1992_INDIANA</td>\n",
       "      <td>INDIANA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5060274.0</td>\n",
       "      <td>257044.0</td>\n",
       "      <td>2578149.0</td>\n",
       "      <td>2225081.0</td>\n",
       "      <td>5182754.0</td>\n",
       "      <td>2598925.0</td>\n",
       "      <td>...</td>\n",
       "      <td>73760.0</td>\n",
       "      <td>75477.0</td>\n",
       "      <td>62234.0</td>\n",
       "      <td>601890.0</td>\n",
       "      <td>278161.0</td>\n",
       "      <td>883276.0</td>\n",
       "      <td>221.037742</td>\n",
       "      <td>270.098944</td>\n",
       "      <td>219.763258</td>\n",
       "      <td>262.072922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>1992_IOWA</td>\n",
       "      <td>IOWA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2663934.0</td>\n",
       "      <td>125665.0</td>\n",
       "      <td>1176205.0</td>\n",
       "      <td>1362064.0</td>\n",
       "      <td>2795774.0</td>\n",
       "      <td>1446478.0</td>\n",
       "      <td>...</td>\n",
       "      <td>37692.0</td>\n",
       "      <td>36892.0</td>\n",
       "      <td>33057.0</td>\n",
       "      <td>299253.0</td>\n",
       "      <td>138907.0</td>\n",
       "      <td>442752.0</td>\n",
       "      <td>229.884078</td>\n",
       "      <td>283.360009</td>\n",
       "      <td>222.852939</td>\n",
       "      <td>262.063710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>1992_KANSAS</td>\n",
       "      <td>KANSAS</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2245348.0</td>\n",
       "      <td>121625.0</td>\n",
       "      <td>903199.0</td>\n",
       "      <td>1220524.0</td>\n",
       "      <td>2234915.0</td>\n",
       "      <td>1165749.0</td>\n",
       "      <td>...</td>\n",
       "      <td>36013.0</td>\n",
       "      <td>33288.0</td>\n",
       "      <td>26706.0</td>\n",
       "      <td>284143.0</td>\n",
       "      <td>120960.0</td>\n",
       "      <td>407494.0</td>\n",
       "      <td>222.466118</td>\n",
       "      <td>272.800645</td>\n",
       "      <td>217.207623</td>\n",
       "      <td>262.054497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>1992_KENTUCKY</td>\n",
       "      <td>KENTUCKY</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2642902.0</td>\n",
       "      <td>289902.0</td>\n",
       "      <td>1643109.0</td>\n",
       "      <td>709891.0</td>\n",
       "      <td>2518082.0</td>\n",
       "      <td>1343438.0</td>\n",
       "      <td>...</td>\n",
       "      <td>49666.0</td>\n",
       "      <td>49993.0</td>\n",
       "      <td>38029.0</td>\n",
       "      <td>400849.0</td>\n",
       "      <td>181786.0</td>\n",
       "      <td>597199.0</td>\n",
       "      <td>215.048158</td>\n",
       "      <td>262.241282</td>\n",
       "      <td>211.562307</td>\n",
       "      <td>262.045284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>1992_LOUISIANA</td>\n",
       "      <td>LOUISIANA</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3341253.0</td>\n",
       "      <td>367822.0</td>\n",
       "      <td>1848734.0</td>\n",
       "      <td>1124697.0</td>\n",
       "      <td>3362853.0</td>\n",
       "      <td>1888349.0</td>\n",
       "      <td>...</td>\n",
       "      <td>61125.0</td>\n",
       "      <td>55942.0</td>\n",
       "      <td>38368.0</td>\n",
       "      <td>490112.0</td>\n",
       "      <td>196891.0</td>\n",
       "      <td>698442.0</td>\n",
       "      <td>204.140211</td>\n",
       "      <td>249.983926</td>\n",
       "      <td>196.762268</td>\n",
       "      <td>262.036072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>1992_MAINE</td>\n",
       "      <td>MAINE</td>\n",
       "      <td>1992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1206819.0</td>\n",
       "      <td>73160.0</td>\n",
       "      <td>511654.0</td>\n",
       "      <td>622005.0</td>\n",
       "      <td>1228869.0</td>\n",
       "      <td>685350.0</td>\n",
       "      <td>...</td>\n",
       "      <td>17154.0</td>\n",
       "      <td>15969.0</td>\n",
       "      <td>13882.0</td>\n",
       "      <td>135320.0</td>\n",
       "      <td>59289.0</td>\n",
       "      <td>195882.0</td>\n",
       "      <td>231.638840</td>\n",
       "      <td>278.635384</td>\n",
       "      <td>228.380027</td>\n",
       "      <td>262.026859</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>20 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  PRIMARY_KEY                 STATE  YEAR  ENROLL  \\\n",
       "0                1992_ALABAMA               ALABAMA  1992     NaN   \n",
       "1                 1992_ALASKA                ALASKA  1992     NaN   \n",
       "2                1992_ARIZONA               ARIZONA  1992     NaN   \n",
       "3               1992_ARKANSAS              ARKANSAS  1992     NaN   \n",
       "4             1992_CALIFORNIA            CALIFORNIA  1992     NaN   \n",
       "5               1992_COLORADO              COLORADO  1992     NaN   \n",
       "6            1992_CONNECTICUT           CONNECTICUT  1992     NaN   \n",
       "7               1992_DELAWARE              DELAWARE  1992     NaN   \n",
       "8   1992_DISTRICT_OF_COLUMBIA  DISTRICT_OF_COLUMBIA  1992     NaN   \n",
       "9                1992_FLORIDA               FLORIDA  1992     NaN   \n",
       "10               1992_GEORGIA               GEORGIA  1992     NaN   \n",
       "11                1992_HAWAII                HAWAII  1992     NaN   \n",
       "12                 1992_IDAHO                 IDAHO  1992     NaN   \n",
       "13              1992_ILLINOIS              ILLINOIS  1992     NaN   \n",
       "14               1992_INDIANA               INDIANA  1992     NaN   \n",
       "15                  1992_IOWA                  IOWA  1992     NaN   \n",
       "16                1992_KANSAS                KANSAS  1992     NaN   \n",
       "17              1992_KENTUCKY              KENTUCKY  1992     NaN   \n",
       "18             1992_LOUISIANA             LOUISIANA  1992     NaN   \n",
       "19                 1992_MAINE                 MAINE  1992     NaN   \n",
       "\n",
       "    TOTAL_REVENUE  FEDERAL_REVENUE  STATE_REVENUE  LOCAL_REVENUE  \\\n",
       "0       2678885.0         304177.0      1659028.0       715680.0   \n",
       "1       1049591.0         106780.0       720711.0       222100.0   \n",
       "2       3258079.0         297888.0      1369815.0      1590376.0   \n",
       "3       1711959.0         178571.0       958785.0       574603.0   \n",
       "4      26260025.0        2072470.0     16546514.0      7641041.0   \n",
       "5       3185173.0         163253.0      1307986.0      1713934.0   \n",
       "6       3834302.0         143542.0      1342539.0      2348221.0   \n",
       "7        645233.0          45945.0       420942.0       178346.0   \n",
       "8        709480.0          64749.0            0.0       644731.0   \n",
       "9      11506299.0         788420.0      5683949.0      5033930.0   \n",
       "10      5536901.0         398701.0      2798674.0      2339526.0   \n",
       "11       996809.0          71273.0       903443.0        22093.0   \n",
       "12       859329.0          69138.0       531912.0       258279.0   \n",
       "13      9748650.0         597077.0      3073178.0      6078395.0   \n",
       "14      5060274.0         257044.0      2578149.0      2225081.0   \n",
       "15      2663934.0         125665.0      1176205.0      1362064.0   \n",
       "16      2245348.0         121625.0       903199.0      1220524.0   \n",
       "17      2642902.0         289902.0      1643109.0       709891.0   \n",
       "18      3341253.0         367822.0      1848734.0      1124697.0   \n",
       "19      1206819.0          73160.0       511654.0       622005.0   \n",
       "\n",
       "    TOTAL_EXPENDITURE  INSTRUCTION_EXPENDITURE  ...  GRADES_4_G  GRADES_8_G  \\\n",
       "0           2653798.0                1481703.0  ...     57948.0     58025.0   \n",
       "1            972488.0                 498362.0  ...      9748.0      8789.0   \n",
       "2           3401580.0                1435908.0  ...     55433.0     49081.0   \n",
       "3           1743022.0                 964323.0  ...     34632.0     36011.0   \n",
       "4          27138832.0               14358922.0  ...    418418.0    363296.0   \n",
       "5           3264826.0                1642466.0  ...     50648.0     45025.0   \n",
       "6           3721338.0                2148041.0  ...     38058.0     33691.0   \n",
       "7            638784.0                 372722.0  ...      8272.0      8012.0   \n",
       "8            742893.0                 329160.0  ...      5832.0      5000.0   \n",
       "9          11305642.0                5166374.0  ...    164416.0    142372.0   \n",
       "10          5535942.0                3043984.0  ...     99648.0     92374.0   \n",
       "11          1040121.0                 536115.0  ...     13754.0     11750.0   \n",
       "12           886161.0                 473505.0  ...     18607.0     18880.0   \n",
       "13          9850560.0                5010400.0  ...    133120.0    134317.0   \n",
       "14          5182754.0                2598925.0  ...     73760.0     75477.0   \n",
       "15          2795774.0                1446478.0  ...     37692.0     36892.0   \n",
       "16          2234915.0                1165749.0  ...     36013.0     33288.0   \n",
       "17          2518082.0                1343438.0  ...     49666.0     49993.0   \n",
       "18          3362853.0                1888349.0  ...     61125.0     55942.0   \n",
       "19          1228869.0                 685350.0  ...     17154.0     15969.0   \n",
       "\n",
       "    GRADES_12_G  GRADES_1_8_G  GRADES_9_12_G  GRADES_ALL_G  AVG_MATH_4_SCORE  \\\n",
       "0       41167.0      471564.0       196386.0      676174.0        208.327876   \n",
       "1        6714.0       79117.0        30847.0      112335.0        211.790904   \n",
       "2       37410.0      437127.0       175210.0      614881.0        215.253932   \n",
       "3       27651.0      281338.0       123113.0      405259.0        210.206028   \n",
       "4      270675.0     3286034.0      1372011.0     4717112.0        208.398961   \n",
       "5       34533.0      394904.0       160299.0      562613.0        221.023429   \n",
       "6       28366.0      304284.0       126917.0      436932.0        226.798480   \n",
       "7        6129.0       67495.0        28338.0       96296.0        217.899972   \n",
       "8        3433.0       47009.0        18173.0       70000.0        192.600553   \n",
       "9      100835.0     1276685.0       511557.0     1819706.0        213.689751   \n",
       "10      63646.0      787599.0       315539.0     1106441.0        215.594906   \n",
       "11       9051.0      107242.0        43882.0      151649.0        214.056666   \n",
       "12      14593.0      146573.0        66541.0      214345.0        221.562534   \n",
       "13     106475.0     1111167.0       495562.0     1646411.0        221.300138   \n",
       "14      62234.0      601890.0       278161.0      883276.0        221.037742   \n",
       "15      33057.0      299253.0       138907.0      442752.0        229.884078   \n",
       "16      26706.0      284143.0       120960.0      407494.0        222.466118   \n",
       "17      38029.0      400849.0       181786.0      597199.0        215.048158   \n",
       "18      38368.0      490112.0       196891.0      698442.0        204.140211   \n",
       "19      13882.0      135320.0        59289.0      195882.0        231.638840   \n",
       "\n",
       "    AVG_MATH_8_SCORE  AVG_READING_4_SCORE  AVG_READING_8_SCORE  \n",
       "0         252.187522           207.963517                  NaN  \n",
       "1         258.776900           207.088116           258.859712  \n",
       "2         265.366278           206.212716           262.169895  \n",
       "3         256.312090           208.634458           264.619665  \n",
       "4         260.892247           196.764414           265.519676  \n",
       "5         272.398433           213.480890           266.419687  \n",
       "6         273.739345           222.417599           264.713904  \n",
       "7         262.868585           206.389052           261.577921  \n",
       "8         234.924621           178.557612           265.976765  \n",
       "9         259.908848           204.882606           262.118986  \n",
       "10        259.359434           206.844175           262.109773  \n",
       "11        257.410887           200.880272           262.100561  \n",
       "12        275.090294           207.174601           262.091348  \n",
       "13        272.594619           213.468929           262.082135  \n",
       "14        270.098944           219.763258           262.072922  \n",
       "15        283.360009           222.852939           262.063710  \n",
       "16        272.800645           217.207623           262.054497  \n",
       "17        262.241282           211.562307           262.045284  \n",
       "18        249.983926           196.762268           262.036072  \n",
       "19        278.635384           228.380027           262.026859  \n",
       "\n",
       "[20 rows x 25 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "useducation4_df = useducation_df.copy()\n",
    "\n",
    "for col in fill_list:\n",
    "    useducation4_df.loc[:, col] = useducation4_df.loc[:, col].interpolate()\n",
    "    \n",
    "useducation4_df.head(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5. Compare your results for the second, third and the fourth questions. Do you find any meaningful differences?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Statistics for columns: ENROLL\n",
      "             ENROLL        ENROLL        ENROLL        ENROLL\n",
      "count  1.229000e+03  1.492000e+03  1.385000e+03  1.456000e+03\n",
      "mean   9.159308e+05  9.159308e+05  9.161654e+05  1.005984e+06\n",
      "std    1.065280e+06  9.667725e+05  1.003532e+06  1.009158e+06\n",
      "min    4.386600e+04  4.386600e+04  4.386600e+04  4.386600e+04\n",
      "25%    2.583140e+05  3.150940e+05  2.867590e+05  2.973995e+05\n",
      "50%    6.483130e+05  8.204140e+05  7.374010e+05  7.540845e+05\n",
      "75%    1.014528e+06  9.211780e+05  9.624880e+05  1.595024e+06\n",
      "max    6.307022e+06  6.307022e+06  6.307022e+06  6.307022e+06\n",
      "Statistics for columns: TOTAL_REVENUE\n",
      "       TOTAL_REVENUE  TOTAL_REVENUE  TOTAL_REVENUE  TOTAL_REVENUE\n",
      "count   1.280000e+03   1.492000e+03   1.441000e+03   1.492000e+03\n",
      "mean    9.092082e+06   9.092082e+06   9.084108e+06   1.111164e+07\n",
      "std     1.174519e+07   1.087818e+07   1.110204e+07   1.200155e+07\n",
      "min     4.656500e+05   4.656500e+05   4.656500e+05   4.656500e+05\n",
      "25%     2.186305e+06   2.546261e+06   2.425600e+06   2.546261e+06\n",
      "50%     5.079546e+06   6.359310e+06   5.778507e+06   6.351760e+06\n",
      "75%     1.085985e+07   9.276958e+06   1.116863e+07   1.803650e+07\n",
      "max     8.921726e+07   8.921726e+07   8.921726e+07   8.921726e+07\n",
      "Statistics for columns: FEDERAL_REVENUE\n",
      "       FEDERAL_REVENUE  FEDERAL_REVENUE  FEDERAL_REVENUE  FEDERAL_REVENUE\n",
      "count     1.280000e+03     1.492000e+03     1.441000e+03     1.492000e+03\n",
      "mean      7.663723e+05     7.663723e+05     7.662749e+05     8.922691e+05\n",
      "std       1.145242e+06     1.060702e+06     1.085057e+06     1.106788e+06\n",
      "min       3.102000e+04     3.102000e+04     3.102000e+04     3.102000e+04\n",
      "25%       1.893540e+05     2.170200e+05     2.068530e+05     2.170200e+05\n",
      "50%       4.033765e+05     5.167410e+05     4.461800e+05     5.165190e+05\n",
      "75%       8.289660e+05     7.663723e+05     8.956420e+05     1.411794e+06\n",
      "max       9.990221e+06     9.990221e+06     9.990221e+06     9.990221e+06\n",
      "Statistics for columns: STATE_REVENUE\n",
      "       STATE_REVENUE  STATE_REVENUE  STATE_REVENUE  STATE_REVENUE\n",
      "count   1.280000e+03   1.492000e+03   1.441000e+03   1.492000e+03\n",
      "mean    4.216553e+06   4.216553e+06   4.213597e+06   4.913351e+06\n",
      "std     5.543072e+06   5.133895e+06   5.237195e+06   5.423675e+06\n",
      "min     0.000000e+00   0.000000e+00   0.000000e+00   0.000000e+00\n",
      "25%     1.153097e+06   1.356434e+06   1.319582e+06   1.356434e+06\n",
      "50%     2.537074e+06   3.127639e+06   2.857497e+06   3.119414e+06\n",
      "75%     5.080939e+06   4.269811e+06   5.187230e+06   8.020633e+06\n",
      "max     5.090457e+07   5.090457e+07   5.090457e+07   5.090457e+07\n",
      "Statistics for columns: LOCAL_REVENUE\n",
      "       LOCAL_REVENUE  LOCAL_REVENUE  LOCAL_REVENUE  LOCAL_REVENUE\n",
      "count   1.280000e+03   1.492000e+03   1.441000e+03   1.492000e+03\n",
      "mean    4.109157e+06   4.109157e+06   4.104236e+06   5.306024e+06\n",
      "std     5.482971e+06   5.078230e+06   5.181475e+06   5.900909e+06\n",
      "min     2.209300e+04   2.209300e+04   2.209300e+04   2.209300e+04\n",
      "25%     7.158345e+05   9.447962e+05   8.747060e+05   9.447962e+05\n",
      "50%     2.055780e+06   2.697257e+06   2.398344e+06   2.650904e+06\n",
      "75%     4.768680e+06   4.109157e+06   4.995971e+06   8.584803e+06\n",
      "max     3.610526e+07   3.610526e+07   3.610526e+07   3.610526e+07\n",
      "Statistics for columns: TOTAL_EXPENDITURE\n",
      "       TOTAL_EXPENDITURE  TOTAL_EXPENDITURE  TOTAL_EXPENDITURE  \\\n",
      "count       1.280000e+03       1.492000e+03       1.441000e+03   \n",
      "mean        9.196681e+06       9.196681e+06       9.190557e+06   \n",
      "std         1.197813e+07       1.109393e+07       1.132084e+07   \n",
      "min         4.816650e+05       4.816650e+05       4.816650e+05   \n",
      "25%         2.165404e+06       2.523968e+06       2.427316e+06   \n",
      "50%         5.234506e+06       6.520224e+06       5.858385e+06   \n",
      "75%         1.074519e+07       9.434922e+06       1.116970e+07   \n",
      "max         8.532013e+07       8.532013e+07       8.532013e+07   \n",
      "\n",
      "       TOTAL_EXPENDITURE  \n",
      "count       1.492000e+03  \n",
      "mean        1.114374e+07  \n",
      "std         1.212433e+07  \n",
      "min         4.816650e+05  \n",
      "25%         2.523968e+06  \n",
      "50%         6.499891e+06  \n",
      "75%         1.801704e+07  \n",
      "max         8.532013e+07  \n",
      "Statistics for columns: INSTRUCTION_EXPENDITURE\n",
      "       INSTRUCTION_EXPENDITURE  INSTRUCTION_EXPENDITURE  \\\n",
      "count             1.280000e+03             1.492000e+03   \n",
      "mean              4.762966e+06             4.762966e+06   \n",
      "std               6.293004e+06             5.828468e+06   \n",
      "min               2.655490e+05             2.655490e+05   \n",
      "25%               1.168032e+06             1.343611e+06   \n",
      "50%               2.657452e+06             3.358142e+06   \n",
      "75%               5.568028e+06             4.938820e+06   \n",
      "max               4.396452e+07             4.396452e+07   \n",
      "\n",
      "       INSTRUCTION_EXPENDITURE  INSTRUCTION_EXPENDITURE  \n",
      "count             1.441000e+03             1.492000e+03  \n",
      "mean              4.758243e+06             5.792260e+06  \n",
      "std               5.947042e+06             6.376549e+06  \n",
      "min               2.655490e+05             2.655490e+05  \n",
      "25%               1.306105e+06             1.343611e+06  \n",
      "50%               3.033016e+06             3.318778e+06  \n",
      "75%               5.672620e+06             9.130766e+06  \n",
      "max               4.396452e+07             4.396452e+07  \n",
      "Statistics for columns: SUPPORT_SERVICES_EXPENDITURE\n",
      "       SUPPORT_SERVICES_EXPENDITURE  SUPPORT_SERVICES_EXPENDITURE  \\\n",
      "count                  1.280000e+03                  1.492000e+03   \n",
      "mean                   2.680331e+06                  2.680331e+06   \n",
      "std                    3.353349e+06                  3.105812e+06   \n",
      "min                    1.399630e+05                  1.399630e+05   \n",
      "25%                    6.357900e+05                  7.673688e+05   \n",
      "50%                    1.525406e+06                  1.913844e+06   \n",
      "75%                    3.229651e+06                  2.795888e+06   \n",
      "max                    2.605802e+07                  2.605802e+07   \n",
      "\n",
      "       SUPPORT_SERVICES_EXPENDITURE  SUPPORT_SERVICES_EXPENDITURE  \n",
      "count                  1.441000e+03                  1.492000e+03  \n",
      "mean                   2.677770e+06                  3.324275e+06  \n",
      "std                    3.170760e+06                  3.500830e+06  \n",
      "min                    1.399630e+05                  1.399630e+05  \n",
      "25%                    7.350360e+05                  7.673688e+05  \n",
      "50%                    1.720824e+06                  1.910412e+06  \n",
      "75%                    3.333043e+06                  5.435244e+06  \n",
      "max                    2.605802e+07                  2.605802e+07  \n",
      "Statistics for columns: OTHER_EXPENDITURE\n",
      "       OTHER_EXPENDITURE  OTHER_EXPENDITURE  OTHER_EXPENDITURE  \\\n",
      "count       1.229000e+03       1.492000e+03       1.385000e+03   \n",
      "mean        4.292046e+05       4.292046e+05       4.286507e+05   \n",
      "std         5.340693e+05       4.846832e+05       5.041013e+05   \n",
      "min         1.154100e+04       1.154100e+04       1.154100e+04   \n",
      "25%         1.028310e+05       1.354282e+05       1.199340e+05   \n",
      "50%         2.715960e+05       3.672335e+05       3.070220e+05   \n",
      "75%         5.186000e+05       4.568915e+05       5.223475e+05   \n",
      "max         3.995951e+06       3.995951e+06       3.995951e+06   \n",
      "\n",
      "       OTHER_EXPENDITURE  \n",
      "count       1.456000e+03  \n",
      "mean        5.004288e+05  \n",
      "std         5.253843e+05  \n",
      "min         1.154100e+04  \n",
      "25%         1.279618e+05  \n",
      "50%         3.415810e+05  \n",
      "75%         8.490842e+05  \n",
      "max         3.995951e+06  \n",
      "Statistics for columns: CAPITAL_OUTLAY_EXPENDITURE\n",
      "       CAPITAL_OUTLAY_EXPENDITURE  CAPITAL_OUTLAY_EXPENDITURE  \\\n",
      "count                1.280000e+03                1.492000e+03   \n",
      "mean                 9.027693e+05                9.027693e+05   \n",
      "std                  1.327562e+06                1.229564e+06   \n",
      "min                  1.270800e+04                1.270800e+04   \n",
      "25%                  1.815645e+05                2.163398e+05   \n",
      "50%                  5.102595e+05                6.482175e+05   \n",
      "75%                  9.668515e+05                9.027693e+05   \n",
      "max                  1.022366e+07                1.022366e+07   \n",
      "\n",
      "       CAPITAL_OUTLAY_EXPENDITURE  CAPITAL_OUTLAY_EXPENDITURE  \n",
      "count                1.441000e+03                1.492000e+03  \n",
      "mean                 9.044417e+05                1.033524e+06  \n",
      "std                  1.254176e+06                1.272901e+06  \n",
      "min                  1.270800e+04                1.270800e+04  \n",
      "25%                  2.062410e+05                2.163398e+05  \n",
      "50%                  5.809340e+05                6.436235e+05  \n",
      "75%                  1.024876e+06                1.717212e+06  \n",
      "max                  1.022366e+07                1.022366e+07  \n",
      "Statistics for columns: GRADES_PK_G\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         GRADES_PK_G    GRADES_PK_G    GRADES_PK_G    GRADES_PK_G\n",
      "count    1319.000000    1492.000000    1390.000000    1492.000000\n",
      "mean    17601.614102   17601.614102   17672.581838   15926.059316\n",
      "std     30016.166447   28221.111094   29263.483252   28669.479212\n",
      "min         0.000000       0.000000       0.000000       0.000000\n",
      "25%      2021.000000    2449.000000    2183.250000    1544.000000\n",
      "50%      8106.000000   10505.000000    9066.500000    5910.500000\n",
      "75%     22295.000000   19149.250000   22788.750000   19561.000000\n",
      "max    250911.000000  250911.000000  250911.000000  250911.000000\n",
      "Statistics for columns: GRADES_KG_G\n",
      "         GRADES_KG_G    GRADES_KG_G    GRADES_KG_G    GRADES_KG_G\n",
      "count    1360.000000    1492.000000    1390.000000    1492.000000\n",
      "mean    63746.761029   63746.761029   63810.167724   59021.465818\n",
      "std     80205.138143   76572.547833   79336.993597   78271.025323\n",
      "min       544.000000     544.000000     544.000000     544.000000\n",
      "25%     11745.000000   14016.000000   11928.500000    9926.750000\n",
      "50%     41597.500000   48897.000000   42968.000000   38507.000000\n",
      "75%     73865.250000   70372.750000   72972.250000   70748.750000\n",
      "max    530531.000000  530531.000000  530531.000000  530531.000000\n",
      "Statistics for columns: GRADES_4_G\n",
      "          GRADES_4_G     GRADES_4_G     GRADES_4_G     GRADES_4_G\n",
      "count    1361.000000    1492.000000    1390.000000    1492.000000\n",
      "mean    64538.927259   64538.927259   64590.152441   59797.646113\n",
      "std     80293.387625   76684.998585   79451.944548   78406.899202\n",
      "min       633.000000     633.000000     633.000000     633.000000\n",
      "25%     13739.000000   15195.500000   14190.500000   10117.250000\n",
      "50%     43272.000000   49884.500000   44909.500000   38280.500000\n",
      "75%     75481.000000   71814.250000   75149.750000   72310.250000\n",
      "max    493415.000000  493415.000000  493415.000000  493415.000000\n",
      "Statistics for columns: GRADES_8_G\n",
      "          GRADES_8_G     GRADES_8_G     GRADES_8_G     GRADES_8_G\n",
      "count    1361.000000    1492.000000    1390.000000    1492.000000\n",
      "mean    64271.057311   64271.057311   64331.744106   59511.380027\n",
      "std     78910.545776   75364.301721   78083.976028   77123.573668\n",
      "min       437.000000     437.000000     437.000000     437.000000\n",
      "25%     13342.000000   15682.750000   13698.250000   10252.000000\n",
      "50%     43339.000000   49571.000000   44756.500000   38114.500000\n",
      "75%     76566.000000   72131.000000   75016.250000   72598.250000\n",
      "max    500143.000000  500143.000000  500143.000000  500143.000000\n",
      "Statistics for columns: GRADES_12_G\n",
      "        GRADES_12_G    GRADES_12_G    GRADES_12_G    GRADES_12_G\n",
      "count    1361.00000    1492.000000    1390.000000    1492.000000\n",
      "mean    54268.92432   54268.924320   54418.075582   50207.239276\n",
      "std     67889.27623   64838.328605   67187.337112   66309.867155\n",
      "min       311.00000     311.000000     311.000000     311.000000\n",
      "25%     10919.00000   13437.000000   11161.750000    8951.000000\n",
      "50%     36735.00000   39566.000000   37541.500000   33279.000000\n",
      "75%     67460.00000   64616.250000   67026.000000   64920.500000\n",
      "max    498403.00000  498403.000000  498403.000000  498403.000000\n",
      "Statistics for columns: GRADES_1_8_G\n",
      "       GRADES_1_8_G  GRADES_1_8_G  GRADES_1_8_G  GRADES_1_8_G\n",
      "count  1.361000e+03  1.492000e+03  1.390000e+03  1.492000e+03\n",
      "mean   5.192140e+05  5.192140e+05  5.196200e+05  4.810102e+05\n",
      "std    6.436384e+05  6.147133e+05  6.368932e+05  6.286622e+05\n",
      "min    4.878000e+03  4.878000e+03  4.878000e+03  4.878000e+03\n",
      "25%    1.106260e+05  1.211522e+05  1.129712e+05  8.127325e+04\n",
      "50%    3.457750e+05  4.015865e+05  3.611705e+05  3.097340e+05\n",
      "75%    6.119050e+05  5.749118e+05  6.052242e+05  5.783400e+05\n",
      "max    3.929869e+06  3.929869e+06  3.929869e+06  3.929869e+06\n",
      "Statistics for columns: GRADES_9_12_G\n",
      "       GRADES_9_12_G  GRADES_9_12_G  GRADES_9_12_G  GRADES_9_12_G\n",
      "count   1.361000e+03   1.492000e+03   1.390000e+03   1.492000e+03\n",
      "mean    2.470714e+05   2.470714e+05   2.474932e+05   2.286678e+05\n",
      "std     3.077056e+05   2.938773e+05   3.044943e+05   3.005815e+05\n",
      "min     1.808000e+03   1.808000e+03   1.808000e+03   1.808000e+03\n",
      "25%     5.147100e+04   5.919750e+04   5.270300e+04   3.950675e+04\n",
      "50%     1.642600e+05   1.817010e+05   1.706525e+05   1.472355e+05\n",
      "75%     2.905020e+05   2.825390e+05   2.888522e+05   2.843505e+05\n",
      "max     2.013687e+06   2.013687e+06   2.013687e+06   2.013687e+06\n",
      "Statistics for columns: GRADES_ALL_G\n",
      "       GRADES_ALL_G  GRADES_ALL_G  GRADES_ALL_G  GRADES_ALL_G\n",
      "count  1.319000e+03  1.492000e+03  1.390000e+03  1.492000e+03\n",
      "mean   8.024415e+05  8.024415e+05  8.029178e+05  7.478782e+05\n",
      "std    9.707031e+05  9.126522e+05  9.456162e+05  9.291585e+05\n",
      "min    7.254000e+03  7.254000e+03  7.254000e+03  7.254000e+03\n",
      "25%    1.810650e+05  2.293578e+05  1.939785e+05  1.718665e+05\n",
      "50%    5.503420e+05  6.473260e+05  5.983920e+05  4.591248e+05\n",
      "75%    9.282755e+05  8.724220e+05  9.045562e+05  8.860948e+05\n",
      "max    5.944746e+06  5.944746e+06  5.944746e+06  5.944746e+06\n",
      "Statistics for columns: AVG_MATH_4_SCORE\n",
      "       AVG_MATH_4_SCORE  AVG_MATH_4_SCORE  AVG_MATH_4_SCORE  AVG_MATH_4_SCORE\n",
      "count        536.000000       1492.000000        632.000000       1492.000000\n",
      "mean         234.768293        234.768293        234.164118        232.723472\n",
      "std           10.221511          6.122843         10.117544          9.405215\n",
      "min          187.134670        187.134670        187.134670        187.134670\n",
      "25%          229.694352        234.768293        227.719378        226.267129\n",
      "50%          237.238552        234.768293        236.867138        234.226904\n",
      "75%          241.995486        234.768293        241.590257        240.163315\n",
      "max          253.420961        253.420961        253.420961        253.420961\n",
      "Statistics for columns: AVG_MATH_8_SCORE\n",
      "       AVG_MATH_8_SCORE  AVG_MATH_8_SCORE  AVG_MATH_8_SCORE  AVG_MATH_8_SCORE\n",
      "count        532.000000       1492.000000        632.000000       1492.000000\n",
      "mean         278.414711        278.414711        277.962776        275.734024\n",
      "std           10.159722          6.063038          9.666190          8.754805\n",
      "min          232.831510        232.831510        232.831510        232.831510\n",
      "25%          272.761598        278.414711        272.306655        270.096001\n",
      "50%          280.618803        278.414711        279.735763        275.711254\n",
      "75%          285.347428        278.414711        284.198883        282.702092\n",
      "max          300.568235        300.568235        300.568235        300.568235\n",
      "Statistics for columns: AVG_READING_4_SCORE\n",
      "       AVG_READING_4_SCORE  AVG_READING_4_SCORE  AVG_READING_4_SCORE  \\\n",
      "count           533.000000          1492.000000           632.000000   \n",
      "mean            218.866154           218.866154           218.636919   \n",
      "std               7.769616             4.641053             7.251228   \n",
      "min             178.557612           178.557612           178.557612   \n",
      "25%             214.663401           218.866154           214.587049   \n",
      "50%             220.416034           218.866154           219.799644   \n",
      "75%             223.999337           218.866154           223.441918   \n",
      "max             236.773867           236.773867           236.773867   \n",
      "\n",
      "       AVG_READING_4_SCORE  \n",
      "count          1492.000000  \n",
      "mean            218.971553  \n",
      "std               5.959927  \n",
      "min             178.557612  \n",
      "25%             216.126818  \n",
      "50%             219.771325  \n",
      "75%             222.684611  \n",
      "max             236.773867  \n",
      "Statistics for columns: AVG_READING_8_SCORE\n",
      "       AVG_READING_8_SCORE  AVG_READING_8_SCORE  AVG_READING_8_SCORE  \\\n",
      "count           498.000000          1492.000000           632.000000   \n",
      "mean            263.661132           263.661132           263.539168   \n",
      "std               6.803725             3.928132             6.071020   \n",
      "min             236.379102           236.379102           236.379102   \n",
      "25%             259.533171           263.661132           261.117268   \n",
      "50%             265.010912           263.661132           263.363933   \n",
      "75%             268.190121           263.661132           267.451963   \n",
      "max             280.499130           280.499130           280.499130   \n",
      "\n",
      "       AVG_READING_8_SCORE  \n",
      "count          1491.000000  \n",
      "mean            263.267799  \n",
      "std               4.978792  \n",
      "min             236.379102  \n",
      "25%             260.490023  \n",
      "50%             262.617766  \n",
      "75%             266.849675  \n",
      "max             280.499130  \n"
     ]
    }
   ],
   "source": [
    "for col in fill_list:\n",
    "    print(\"Statistics for columns: {}\".format(col))\n",
    "    print(pd.concat([useducation_df[col], useducation2_df[col], useducation3_df[col], useducation4_df[col]], axis = 1).describe())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<function matplotlib.pyplot.show(*args, **kw)>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x7200 with 22 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(20, 100))\n",
    "\n",
    "for i, col in enumerate(fill_list):\n",
    "    df = pd.concat([useducation_df[col],useducation2_df[col],useducation3_df[col],useducation4_df[col]], axis = 1)\n",
    "      \n",
    "    plt.subplot(len(fill_list), 4, i+1)\n",
    "    plt.bar([\"original\", \"overall\", \"year-by-year\", \"interpolation\"], df.median())\n",
    "    plt.xticks(rotation = \"vertical\")\n",
    "    plt.title(\"Mod of {}\".format(col))\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show"
   ]
  },
  {
   "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": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}