special_education.ipynb

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    "# -*- coding: utf-8 -*-\n",
    "%matplotlib inline\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import math\n",
    "import matplotlib as mplstyle\n",
    "import matplotlib.pyplot as plt\n",
    "import locale\n",
    "from locale import atof\n",
    "from dateutil import parser\n",
    "from datetime import datetime\n",
    "\n",
    "plt.style.use('fivethirtyeight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Import data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "df_vouchersBySchool = pd.read_csv('school_choice_data/imported_data/awards_by_school_16.csv')\n",
    "df_specialEdEnrollment = pd.read_csv('school_choice_data/gov_data/EnrollmentEnglishLearnerSpecEdSchls_ALL.csv')\n",
    "df_missingSpecialEdEnrollment = pd.read_csv('school_choice_data/imported_data/updatedEnrollment.csv')\n",
    "df_vouchersByOgSchoolDistrict = pd.read_csv('school_choice_data/imported_data/voucher-students-by-original-school-district.csv')\n",
    "df_publicSpecialEdEnrollment = pd.read_csv('school_choice_data/gov_data/PublicEnrollmentEnglishLearnerSpecEd.csv')\n",
    "df_schoolGrades2015 = pd.read_csv('school_choice_data/imported_data/final-2016-af-school-grades.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true,
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    "editable": true
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   "source": [
    "# replace symbols \n",
    "# use 0 for no school choice students and 9 for schools with less than 10 students\n",
    "def replaceSymbols(id):\n",
    "    if id == '*':\n",
    "        return 9\n",
    "    elif id == '-':\n",
    "        return 0\n",
    "    else:\n",
    "        return id\n",
    "\n",
    "# normalize numbers\n",
    "# if is not a number, return None. if is a number, turn it into an integer\n",
    "def normalizeNums(num):\n",
    "    if (math.isnan(num)):\n",
    "        return None\n",
    "    else:\n",
    "        num = int(math.floor(num))\n",
    "        return num\n",
    "    \n",
    "# multiply by 100 to convert from percent\n",
    "def convertPercent(num):\n",
    "    return num * 100\n",
    "\n",
    "# normalize percent from x% to just a number\n",
    "def normalizePerc(num):\n",
    "    try:\n",
    "        float(num.strip('%'))\n",
    "    except AttributeError:\n",
    "        return num\n",
    "    return float(num.strip('%'))\n",
    "    \n",
    "# get average award amount\n",
    "# divide award amount by award count if they are both numbers\n",
    "def averageAward(awardCount, awardAmount):\n",
    "    if math.isnan(awardAmount) or math.isnan(awardCount):\n",
    "        return None\n",
    "    return round((awardAmount/awardCount),2)\n",
    "\n",
    "# Convert NaN to zeros\n",
    "# the zeros do not always indicate that no students \n",
    "# were in the program. schools with less than ten \n",
    "# students do not have to report \n",
    "def convertInt(num):\n",
    "    if math.isnan(num):\n",
    "        return 0\n",
    "    else:\n",
    "        return int(num)\n",
    "    \n",
    "# calculate percent\n",
    "def calcPerc(num, denom):\n",
    "    if num != 0:\n",
    "        percent = (float(num/denom))*100\n",
    "        return round(percent,2)\n",
    "    else:\n",
    "        return None\n",
    "    \n",
    "# calculate percent change\n",
    "def percentChange(oldVal, newVal):\n",
    "    val1 = float(oldVal)\n",
    "    val2 = float(newVal)\n",
    "    change = (val2-val1)/val1\n",
    "    return float(change)\n",
    "\n",
    "# fill in missing values\n",
    "# compares two values, takes the first if is not null. if it is, takes second.\n",
    "def fillInfo(choiceCell, backupCell):\n",
    "    if pd.isnull(choiceCell):\n",
    "        return backupCell\n",
    "    elif math.isnan(choiceCell):\n",
    "        return backupCell\n",
    "    else:\n",
    "        return choiceCell\n",
    "    \n",
    "# replace with None\n",
    "def fillNone(num):\n",
    "    if num == 1:\n",
    "        return None\n",
    "    else:\n",
    "        return num "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Voucher enrollment data\n",
    "\n",
    "Apply function to replace symbols. Drop data from all but most recent school year. Filter out schools with no voucher enrollment.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true,
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   "outputs": [],
   "source": [
    "df_vouchersBySchool2016_filtered = df_vouchersBySchool\n",
    "df_vouchersBySchool2016_filtered['Voucher enrollment 2016'] = df_vouchersBySchool2016_filtered['2016-2017'].apply(replaceSymbols)\n",
    "\n",
    "# Trim out data from 2011-2015.\n",
    "df_vouchersBySchool2016_trimmed = df_vouchersBySchool.drop(['2011-2012','2012-2013','2013-2014','2014-2015','2015-2016','2016-2017'], axis=1)\n",
    "\n",
    "# Filter out schools with no voucher enrollment in 2016\n",
    "# In the data, 1 == \"-\", and 9 == \"Less than 10 voucher students\"\n",
    "# We want to filter out the \"-\" ones because they're basically zero.\n",
    "df_vouchersBySchool2016_trimmed = df_vouchersBySchool2016_trimmed[df_vouchersBySchool2016_trimmed['Voucher enrollment 2016'] > 0]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Indiana school enrollment (all)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true,
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   "source": [
    "# INDIANA SCHOOL ENROLLMENT (ALL)\n",
    "\n",
    "# Filter out the public schools.\n",
    "# Public school IDs are numbers-only. Private school IDs have letters + numbers.\n",
    "def filterPrivate(id):\n",
    "    if pd.isnull(id):\n",
    "        return True\n",
    "    else:\n",
    "        try:\n",
    "            float(id)\n",
    "        except ValueError:\n",
    "            return False\n",
    "        return True\n",
    "\n",
    "df_specialEdEnrollment_filtered = df_specialEdEnrollment\n",
    "df_specialEdEnrollment_filtered['filter'] = df_specialEdEnrollment_filtered['SCHL_NAME_CODE'].apply(filterPrivate)\n",
    "df_specialEdEnrollment_filtered = df_specialEdEnrollment_filtered[df_specialEdEnrollment_filtered['filter'] == False]\n",
    "df_specialEdEnrollment_filtered = df_specialEdEnrollment_filtered.reset_index()\n",
    "\n",
    "# Tidy and rename columns\n",
    "df_specialEdEnrollment_trimmed = df_specialEdEnrollment_filtered.drop(['index','CORP','CORP_NAME','ENR_ELL_N','ENR_ELL_RATIO', 'filter'], axis=1)\n",
    "df_specialEdEnrollment_trimmed = df_specialEdEnrollment_trimmed.rename(columns = {'SCHL_NAME_CODE':'School No.','SCHL_NAME':'School Name','ENR_SPEC_ED_N':'Special ed enrollment 2016','ENR_SPEC_ED_RATIO':'Special ed ratio 2016','ENROLLMENT_N':'Total enrollment 2016'})\n",
    "df_specialEdEnrollment_trimmed['Special ed ratio 2016'] = df_specialEdEnrollment_trimmed['Special ed ratio 2016'].apply(normalizePerc)\n",
    "df_specialEdEnrollment_trimmed\n",
    "\n",
    "# Tidy and rename updated enrollment columns\n",
    "df_missingSpecialEdEnrollment = df_missingSpecialEdEnrollment.rename(columns = {'School ID':'School No.','SpecEd 2016':'Special ed enrollment 2016','SpecEd Perc':'Special ed ratio 2016','Enrollment 2016':'Total enrollment 2016'})\n",
    "df_missingSpecialEdEnrollment['Special ed ratio 2016'] = df_missingSpecialEdEnrollment['Special ed ratio 2016'].apply(normalizePerc)\n",
    "df_missingSpecialEdEnrollment\n",
    "\n",
    "# Merge w/ other special education data\n",
    "df_specialEdEnrollment_merged = df_specialEdEnrollment_trimmed.merge(df_missingSpecialEdEnrollment,on='School No.', how='outer')\n",
    "df_specialEdEnrollment_merged['Special ed enrollment 2016'] = np.vectorize(fillInfo)(df_specialEdEnrollment_merged['Special ed enrollment 2016_x'],df_specialEdEnrollment_merged['Special ed enrollment 2016_y'])\n",
    "df_specialEdEnrollment_merged['Special ed ratio 2016'] = np.vectorize(fillInfo)(df_specialEdEnrollment_merged['Special ed ratio 2016_x'],df_specialEdEnrollment_merged['Special ed ratio 2016_y'])\n",
    "df_specialEdEnrollment_merged['Total enrollment 2016'] = np.vectorize(fillInfo)(df_specialEdEnrollment_merged['Total enrollment 2016_x'],df_specialEdEnrollment_merged['Total enrollment 2016_y'])\n",
    "df_specialEdEnrollment_merged = df_specialEdEnrollment_merged.drop(['Special ed enrollment 2016_x','Special ed enrollment 2016_y','Special ed ratio 2016_x','Special ed ratio 2016_y','Total enrollment 2016_x','Total enrollment 2016_y'], axis=1)\n",
    "df_specialEdEnrollment_merged\n",
    "# df_specialEdEnrollment_merged.to_csv('school_choice_data/exported_data/df_specialEdEnrollment_merged.csv')\n",
    "\n",
    "# Merge w/ voucher school data\n",
    "df_vouchersSpecialEd_merged = df_vouchersBySchool2016_trimmed.merge(df_specialEdEnrollment_merged,on='School No.', how='outer')\n",
    "df_vouchersSpecialEd_merged = df_vouchersSpecialEd_merged.drop(['School Name_y'], axis=1)\n",
    "df_vouchersSpecialEd_merged = df_vouchersSpecialEd_merged.rename(columns = {'School Name_x':'School Name'})\n",
    "# df_vouchersSpecialEd_merged\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### School grades"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
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   "outputs": [],
   "source": [
    "# Associate schools with their current grade by merging grades df and df_vouchersSpecialEd_merged\n",
    "\n",
    "# Tidy and rename columns\n",
    "df_schoolGrades2015_trimmed = df_schoolGrades2015.drop(['IDOE_CORPORATION_ID','CORPORATION_NAME'], axis=1)\n",
    "df_schoolGrades2015_trimmed = df_schoolGrades2015_trimmed.rename(columns = {'IDOE_SCHOOL_ID':'School No.','SCHOOL_NAME':'School Name','2015 Grade':'2015_grade'})\n",
    "df_schoolGrades2015_trimmed\n",
    "\n",
    "# Merge w/ voucher school data\n",
    "df_vouchersSpecialEdGrades_merged = df_vouchersSpecialEd_merged.merge(df_schoolGrades2015_trimmed,on='School No.', how='outer')\n",
    "df_vouchersSpecialEdGrades_merged = df_vouchersSpecialEdGrades_merged.drop(['School Name_y'], axis=1)\n",
    "df_vouchersSpecialEdGrades_merged = df_vouchersSpecialEdGrades_merged.rename(columns = {'School Name_x':'School Name'})\n",
    "df_vouchersSpecialEdGrades_merged\n",
    "\n",
    "# Filter out all schools without vouchers in 2016\n",
    "df_vouchersSpecialEdGrades_merged = df_vouchersSpecialEdGrades_merged[df_vouchersSpecialEdGrades_merged['Voucher enrollment 2016'] > 0]\n",
    "# df_vouchersSpecialEdGrades_merged"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### School districts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true,
    "scrolled": true
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   "outputs": [],
   "source": [
    "# Assign schools to parent school districts\n",
    "\n",
    "# Tidy and rename\n",
    "df_vouchersByOgSchoolDistrict_filtered = df_vouchersByOgSchoolDistrict.rename(columns = {'Corp. No.':'District No.','Corporation Name':'District Name'})\n",
    "df_vouchersByOgSchoolDistrict_filtered = df_vouchersByOgSchoolDistrict_filtered.drop(['Voucher students from this district (2016-2017)'], axis=1)\n",
    "# df_vouchersByOgSchoolDistrict_filtered\n",
    "\n",
    "# Merge w/ school ID\n",
    "df_vouchersSpecialEdGradesDistricts_merged = df_vouchersSpecialEdGrades_merged.merge(df_vouchersByOgSchoolDistrict_filtered,on='School No.', how='outer')\n",
    "df_vouchersSpecialEdGradesDistricts_merged = df_vouchersSpecialEdGradesDistricts_merged.drop(['School Name_y'], axis=1)\n",
    "df_vouchersSpecialEdGradesDistricts_merged = df_vouchersSpecialEdGradesDistricts_merged.rename(columns = {'School Name_x':'School Name'})\n",
    "df_vouchersSpecialEdGradesDistricts_merged\n",
    "\n",
    "df_vouchersSpecialEdGradesDistricts_merged.to_csv('school_choice_data/exported_data/df_vouchersSpecialEdGradesDistricts_merged.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Aggregate by parent school district"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# Drop columns, group by district and reset index. \n",
    "df_districtVoucherSpecialEdAggregate = df_vouchersSpecialEdGradesDistricts_merged.drop(['Special ed ratio 2016'], axis=1)\n",
    "df_districtVoucherSpecialEdAggregate = df_districtVoucherSpecialEdAggregate.groupby('District No.').sum()\n",
    "df_districtVoucherSpecialEdAggregate = df_districtVoucherSpecialEdAggregate.reset_index()\n",
    "df_districtVoucherSpecialEdAggregate\n",
    "\n",
    "# Recalculate special ed ratio\n",
    "df_districtVoucherSpecialEdAggregate['Special ed ratio 2016'] = np.vectorize(calcPerc)(df_districtVoucherSpecialEdAggregate['Special ed enrollment 2016'],df_districtVoucherSpecialEdAggregate['Total enrollment 2016'])\n",
    "# df_districtVoucherSpecialEdAggregate"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Public school special ed enrollment "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "deletable": true,
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   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>District No.</th>\n",
       "      <th>District Name</th>\n",
       "      <th>Public special ed enrollment 2016</th>\n",
       "      <th>Public special ed ratio 2016</th>\n",
       "      <th>Public total enrollment 2016</th>\n",
       "      <th>Special ed enrollment 2016</th>\n",
       "      <th>Total enrollment 2016</th>\n",
       "      <th>Special ed ratio 2016</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>15</td>\n",
       "      <td>Adams Central Community Schools</td>\n",
       "      <td>132</td>\n",
       "      <td>10.48</td>\n",
       "      <td>1259</td>\n",
       "      <td>25.0</td>\n",
       "      <td>297.0</td>\n",
       "      <td>8.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>25</td>\n",
       "      <td>North Adams Community Schools</td>\n",
       "      <td>260</td>\n",
       "      <td>14.37</td>\n",
       "      <td>1809</td>\n",
       "      <td>75.0</td>\n",
       "      <td>1069.0</td>\n",
       "      <td>7.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>35</td>\n",
       "      <td>South Adams Schools</td>\n",
       "      <td>195</td>\n",
       "      <td>15.02</td>\n",
       "      <td>1298</td>\n",
       "      <td>114.0</td>\n",
       "      <td>1012.0</td>\n",
       "      <td>11.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>125</td>\n",
       "      <td>M S D Southwest Allen County Schls</td>\n",
       "      <td>565</td>\n",
       "      <td>7.86</td>\n",
       "      <td>7190</td>\n",
       "      <td>629.0</td>\n",
       "      <td>9483.0</td>\n",
       "      <td>6.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>225</td>\n",
       "      <td>Northwest Allen County Schools</td>\n",
       "      <td>887</td>\n",
       "      <td>12.05</td>\n",
       "      <td>7362</td>\n",
       "      <td>677.0</td>\n",
       "      <td>10389.0</td>\n",
       "      <td>6.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>235</td>\n",
       "      <td>Fort Wayne Community Schools</td>\n",
       "      <td>4514</td>\n",
       "      <td>15.37</td>\n",
       "      <td>29377</td>\n",
       "      <td>849.0</td>\n",
       "      <td>13046.0</td>\n",
       "      <td>6.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>255</td>\n",
       "      <td>East Allen County Schools</td>\n",
       "      <td>1113</td>\n",
       "      <td>11.63</td>\n",
       "      <td>9569</td>\n",
       "      <td>824.0</td>\n",
       "      <td>12617.0</td>\n",
       "      <td>6.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>365</td>\n",
       "      <td>Bartholomew Con School Corp</td>\n",
       "      <td>1431</td>\n",
       "      <td>12.38</td>\n",
       "      <td>11562</td>\n",
       "      <td>224.0</td>\n",
       "      <td>3058.0</td>\n",
       "      <td>7.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>370</td>\n",
       "      <td>Flat Rock-Hawcreek School Corp</td>\n",
       "      <td>124</td>\n",
       "      <td>14.37</td>\n",
       "      <td>863</td>\n",
       "      <td>60.0</td>\n",
       "      <td>1025.0</td>\n",
       "      <td>5.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>395</td>\n",
       "      <td>Benton Community School Corp</td>\n",
       "      <td>438</td>\n",
       "      <td>23.41</td>\n",
       "      <td>1871</td>\n",
       "      <td>243.0</td>\n",
       "      <td>2362.0</td>\n",
       "      <td>10.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>515</td>\n",
       "      <td>Blackford County Schools</td>\n",
       "      <td>285</td>\n",
       "      <td>16.69</td>\n",
       "      <td>1708</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>615</td>\n",
       "      <td>Western Boone Co Com Sch Dist</td>\n",
       "      <td>279</td>\n",
       "      <td>16.33</td>\n",
       "      <td>1709</td>\n",
       "      <td>51.0</td>\n",
       "      <td>616.0</td>\n",
       "      <td>8.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>630</td>\n",
       "      <td>Zionsville Community Schools</td>\n",
       "      <td>813</td>\n",
       "      <td>11.73</td>\n",
       "      <td>6931</td>\n",
       "      <td>301.0</td>\n",
       "      <td>6048.0</td>\n",
       "      <td>4.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>665</td>\n",
       "      <td>Lebanon Community School Corp</td>\n",
       "      <td>639</td>\n",
       "      <td>18.61</td>\n",
       "      <td>3434</td>\n",
       "      <td>265.0</td>\n",
       "      <td>3406.0</td>\n",
       "      <td>7.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>670</td>\n",
       "      <td>Brown County School Corporation</td>\n",
       "      <td>493</td>\n",
       "      <td>24.64</td>\n",
       "      <td>2001</td>\n",
       "      <td>254.0</td>\n",
       "      <td>3214.0</td>\n",
       "      <td>7.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>750</td>\n",
       "      <td>Carroll Consolidated School Corp</td>\n",
       "      <td>108</td>\n",
       "      <td>9.73</td>\n",
       "      <td>1110</td>\n",
       "      <td>195.0</td>\n",
       "      <td>1877.0</td>\n",
       "      <td>10.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>755</td>\n",
       "      <td>Delphi Community School Corp</td>\n",
       "      <td>154</td>\n",
       "      <td>10.91</td>\n",
       "      <td>1411</td>\n",
       "      <td>283.0</td>\n",
       "      <td>3035.0</td>\n",
       "      <td>9.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>775</td>\n",
       "      <td>Pioneer Regional School Corp</td>\n",
       "      <td>107</td>\n",
       "      <td>11.75</td>\n",
       "      <td>911</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>815</td>\n",
       "      <td>Southeastern School Corp</td>\n",
       "      <td>143</td>\n",
       "      <td>10.68</td>\n",
       "      <td>1339</td>\n",
       "      <td>38.0</td>\n",
       "      <td>267.0</td>\n",
       "      <td>14.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>875</td>\n",
       "      <td>Logansport Community Sch Corp</td>\n",
       "      <td>499</td>\n",
       "      <td>11.73</td>\n",
       "      <td>4254</td>\n",
       "      <td>1.0</td>\n",
       "      <td>127.0</td>\n",
       "      <td>0.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>940</td>\n",
       "      <td>West Clark Community Schools</td>\n",
       "      <td>670</td>\n",
       "      <td>14.07</td>\n",
       "      <td>4761</td>\n",
       "      <td>208.0</td>\n",
       "      <td>3076.0</td>\n",
       "      <td>6.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1000</td>\n",
       "      <td>Clarksville Community School Corp</td>\n",
       "      <td>236</td>\n",
       "      <td>16.83</td>\n",
       "      <td>1402</td>\n",
       "      <td>187.0</td>\n",
       "      <td>2733.0</td>\n",
       "      <td>6.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1010</td>\n",
       "      <td>Greater Clark County Schools</td>\n",
       "      <td>1718</td>\n",
       "      <td>16.29</td>\n",
       "      <td>10544</td>\n",
       "      <td>208.0</td>\n",
       "      <td>2983.0</td>\n",
       "      <td>6.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1125</td>\n",
       "      <td>Clay Community Schools</td>\n",
       "      <td>865</td>\n",
       "      <td>20.46</td>\n",
       "      <td>4228</td>\n",
       "      <td>4.0</td>\n",
       "      <td>462.0</td>\n",
       "      <td>0.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1150</td>\n",
       "      <td>Clinton Central School Corporation</td>\n",
       "      <td>108</td>\n",
       "      <td>11.66</td>\n",
       "      <td>926</td>\n",
       "      <td>63.0</td>\n",
       "      <td>745.0</td>\n",
       "      <td>8.46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1160</td>\n",
       "      <td>Clinton Prairie School Corporation</td>\n",
       "      <td>161</td>\n",
       "      <td>13.39</td>\n",
       "      <td>1202</td>\n",
       "      <td>212.0</td>\n",
       "      <td>2333.0</td>\n",
       "      <td>9.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1170</td>\n",
       "      <td>Community Schools of Frankfort</td>\n",
       "      <td>408</td>\n",
       "      <td>12.78</td>\n",
       "      <td>3193</td>\n",
       "      <td>164.0</td>\n",
       "      <td>2531.0</td>\n",
       "      <td>6.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1180</td>\n",
       "      <td>Rossville Con School District</td>\n",
       "      <td>108</td>\n",
       "      <td>10.88</td>\n",
       "      <td>993</td>\n",
       "      <td>179.0</td>\n",
       "      <td>2043.0</td>\n",
       "      <td>8.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1300</td>\n",
       "      <td>Crawford County Community Sch Corp</td>\n",
       "      <td>317</td>\n",
       "      <td>20.39</td>\n",
       "      <td>1555</td>\n",
       "      <td>19.0</td>\n",
       "      <td>743.0</td>\n",
       "      <td>2.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1315</td>\n",
       "      <td>Barr-Reeve Community Schools Inc</td>\n",
       "      <td>87</td>\n",
       "      <td>10.61</td>\n",
       "      <td>820</td>\n",
       "      <td>16.0</td>\n",
       "      <td>172.0</td>\n",
       "      <td>9.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361</th>\n",
       "      <td>9840</td>\n",
       "      <td>Excel Center - University Heights</td>\n",
       "      <td>44</td>\n",
       "      <td>11.28</td>\n",
       "      <td>390</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>362</th>\n",
       "      <td>9845</td>\n",
       "      <td>Xavier School of Excellence</td>\n",
       "      <td>38</td>\n",
       "      <td>17.76</td>\n",
       "      <td>214</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>363</th>\n",
       "      <td>9855</td>\n",
       "      <td>Excel Center - Noblesville</td>\n",
       "      <td>26</td>\n",
       "      <td>13.13</td>\n",
       "      <td>198</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>364</th>\n",
       "      <td>9865</td>\n",
       "      <td>Hoosier Acad Virtual Charter</td>\n",
       "      <td>435</td>\n",
       "      <td>13.02</td>\n",
       "      <td>3342</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>365</th>\n",
       "      <td>9870</td>\n",
       "      <td>Discovery Charter School</td>\n",
       "      <td>67</td>\n",
       "      <td>12.93</td>\n",
       "      <td>518</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>366</th>\n",
       "      <td>9875</td>\n",
       "      <td>Rock Creek Community Academy</td>\n",
       "      <td>141</td>\n",
       "      <td>27.81</td>\n",
       "      <td>507</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>367</th>\n",
       "      <td>9880</td>\n",
       "      <td>Career Academy High School</td>\n",
       "      <td>68</td>\n",
       "      <td>25.56</td>\n",
       "      <td>266</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>368</th>\n",
       "      <td>9885</td>\n",
       "      <td>Gary Middle College</td>\n",
       "      <td>20</td>\n",
       "      <td>8.44</td>\n",
       "      <td>237</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>369</th>\n",
       "      <td>9890</td>\n",
       "      <td>Indiana Virtual School</td>\n",
       "      <td>222</td>\n",
       "      <td>7.53</td>\n",
       "      <td>2947</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>370</th>\n",
       "      <td>9895</td>\n",
       "      <td>IN Math &amp; Science Academy - North</td>\n",
       "      <td>84</td>\n",
       "      <td>15.14</td>\n",
       "      <td>555</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>371</th>\n",
       "      <td>9900</td>\n",
       "      <td>Excel Center - South Bend</td>\n",
       "      <td>10</td>\n",
       "      <td>2.78</td>\n",
       "      <td>360</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>372</th>\n",
       "      <td>9905</td>\n",
       "      <td>Indiana Connections Academy</td>\n",
       "      <td>631</td>\n",
       "      <td>15.65</td>\n",
       "      <td>4032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>373</th>\n",
       "      <td>9910</td>\n",
       "      <td>Excel Center for Adult Learners</td>\n",
       "      <td>103</td>\n",
       "      <td>9.94</td>\n",
       "      <td>1036</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>374</th>\n",
       "      <td>9915</td>\n",
       "      <td>Marion Academy</td>\n",
       "      <td>47</td>\n",
       "      <td>27.65</td>\n",
       "      <td>170</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>375</th>\n",
       "      <td>9920</td>\n",
       "      <td>Damar Charter Academy</td>\n",
       "      <td>160</td>\n",
       "      <td>97.56</td>\n",
       "      <td>164</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>376</th>\n",
       "      <td>9925</td>\n",
       "      <td>Phalen Leadership Academy - IN Inc</td>\n",
       "      <td>23</td>\n",
       "      <td>7.42</td>\n",
       "      <td>310</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>377</th>\n",
       "      <td>9930</td>\n",
       "      <td>Nexus Academy of Indianapolis</td>\n",
       "      <td>22</td>\n",
       "      <td>16.92</td>\n",
       "      <td>130</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>378</th>\n",
       "      <td>9935</td>\n",
       "      <td>Vision Academy</td>\n",
       "      <td>74</td>\n",
       "      <td>16.86</td>\n",
       "      <td>439</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>379</th>\n",
       "      <td>9940</td>\n",
       "      <td>Tindley Collegiate Academy</td>\n",
       "      <td>34</td>\n",
       "      <td>12.64</td>\n",
       "      <td>269</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>380</th>\n",
       "      <td>9945</td>\n",
       "      <td>Tindley Renaissance Academy</td>\n",
       "      <td>52</td>\n",
       "      <td>9.56</td>\n",
       "      <td>544</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>381</th>\n",
       "      <td>9950</td>\n",
       "      <td>Dugger Union Community School Corp</td>\n",
       "      <td>42</td>\n",
       "      <td>13.73</td>\n",
       "      <td>306</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>382</th>\n",
       "      <td>9955</td>\n",
       "      <td>Mays Community Academy</td>\n",
       "      <td>39</td>\n",
       "      <td>21.67</td>\n",
       "      <td>180</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>383</th>\n",
       "      <td>9960</td>\n",
       "      <td>Success Academy Primary School</td>\n",
       "      <td>83</td>\n",
       "      <td>17.47</td>\n",
       "      <td>475</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>384</th>\n",
       "      <td>9965</td>\n",
       "      <td>Career Academy Middle School</td>\n",
       "      <td>83</td>\n",
       "      <td>20.80</td>\n",
       "      <td>399</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>385</th>\n",
       "      <td>9970</td>\n",
       "      <td>ACE Preparatory Academy</td>\n",
       "      <td>2</td>\n",
       "      <td>5.56</td>\n",
       "      <td>36</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>386</th>\n",
       "      <td>9975</td>\n",
       "      <td>Global Preparatory Academy</td>\n",
       "      <td>22</td>\n",
       "      <td>8.18</td>\n",
       "      <td>269</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>387</th>\n",
       "      <td>9980</td>\n",
       "      <td>Steel City Academy</td>\n",
       "      <td>23</td>\n",
       "      <td>15.13</td>\n",
       "      <td>152</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>388</th>\n",
       "      <td>9985</td>\n",
       "      <td>Seven Oaks Classical School</td>\n",
       "      <td>20</td>\n",
       "      <td>12.42</td>\n",
       "      <td>161</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389</th>\n",
       "      <td>9990</td>\n",
       "      <td>Heritage Institute of Arts &amp; Tech</td>\n",
       "      <td>18</td>\n",
       "      <td>11.76</td>\n",
       "      <td>153</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>390</th>\n",
       "      <td>9995</td>\n",
       "      <td>Excel Center - Shelbyville</td>\n",
       "      <td>3</td>\n",
       "      <td>3.57</td>\n",
       "      <td>84</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>391 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     District No.                       District Name  \\\n",
       "0              15     Adams Central Community Schools   \n",
       "1              25       North Adams Community Schools   \n",
       "2              35                 South Adams Schools   \n",
       "3             125  M S D Southwest Allen County Schls   \n",
       "4             225      Northwest Allen County Schools   \n",
       "5             235        Fort Wayne Community Schools   \n",
       "6             255           East Allen County Schools   \n",
       "7             365         Bartholomew Con School Corp   \n",
       "8             370      Flat Rock-Hawcreek School Corp   \n",
       "9             395        Benton Community School Corp   \n",
       "10            515            Blackford County Schools   \n",
       "11            615       Western Boone Co Com Sch Dist   \n",
       "12            630        Zionsville Community Schools   \n",
       "13            665       Lebanon Community School Corp   \n",
       "14            670     Brown County School Corporation   \n",
       "15            750    Carroll Consolidated School Corp   \n",
       "16            755        Delphi Community School Corp   \n",
       "17            775        Pioneer Regional School Corp   \n",
       "18            815            Southeastern School Corp   \n",
       "19            875       Logansport Community Sch Corp   \n",
       "20            940        West Clark Community Schools   \n",
       "21           1000   Clarksville Community School Corp   \n",
       "22           1010        Greater Clark County Schools   \n",
       "23           1125              Clay Community Schools   \n",
       "24           1150  Clinton Central School Corporation   \n",
       "25           1160  Clinton Prairie School Corporation   \n",
       "26           1170      Community Schools of Frankfort   \n",
       "27           1180       Rossville Con School District   \n",
       "28           1300  Crawford County Community Sch Corp   \n",
       "29           1315    Barr-Reeve Community Schools Inc   \n",
       "..            ...                                 ...   \n",
       "361          9840   Excel Center - University Heights   \n",
       "362          9845         Xavier School of Excellence   \n",
       "363          9855          Excel Center - Noblesville   \n",
       "364          9865        Hoosier Acad Virtual Charter   \n",
       "365          9870            Discovery Charter School   \n",
       "366          9875        Rock Creek Community Academy   \n",
       "367          9880          Career Academy High School   \n",
       "368          9885                 Gary Middle College   \n",
       "369          9890              Indiana Virtual School   \n",
       "370          9895   IN Math & Science Academy - North   \n",
       "371          9900           Excel Center - South Bend   \n",
       "372          9905         Indiana Connections Academy   \n",
       "373          9910     Excel Center for Adult Learners   \n",
       "374          9915                      Marion Academy   \n",
       "375          9920               Damar Charter Academy   \n",
       "376          9925  Phalen Leadership Academy - IN Inc   \n",
       "377          9930       Nexus Academy of Indianapolis   \n",
       "378          9935                      Vision Academy   \n",
       "379          9940          Tindley Collegiate Academy   \n",
       "380          9945         Tindley Renaissance Academy   \n",
       "381          9950  Dugger Union Community School Corp   \n",
       "382          9955              Mays Community Academy   \n",
       "383          9960      Success Academy Primary School   \n",
       "384          9965        Career Academy Middle School   \n",
       "385          9970             ACE Preparatory Academy   \n",
       "386          9975          Global Preparatory Academy   \n",
       "387          9980                  Steel City Academy   \n",
       "388          9985         Seven Oaks Classical School   \n",
       "389          9990   Heritage Institute of Arts & Tech   \n",
       "390          9995          Excel Center - Shelbyville   \n",
       "\n",
       "     Public special ed enrollment 2016  Public special ed ratio 2016  \\\n",
       "0                                  132                         10.48   \n",
       "1                                  260                         14.37   \n",
       "2                                  195                         15.02   \n",
       "3                                  565                          7.86   \n",
       "4                                  887                         12.05   \n",
       "5                                 4514                         15.37   \n",
       "6                                 1113                         11.63   \n",
       "7                                 1431                         12.38   \n",
       "8                                  124                         14.37   \n",
       "9                                  438                         23.41   \n",
       "10                                 285                         16.69   \n",
       "11                                 279                         16.33   \n",
       "12                                 813                         11.73   \n",
       "13                                 639                         18.61   \n",
       "14                                 493                         24.64   \n",
       "15                                 108                          9.73   \n",
       "16                                 154                         10.91   \n",
       "17                                 107                         11.75   \n",
       "18                                 143                         10.68   \n",
       "19                                 499                         11.73   \n",
       "20                                 670                         14.07   \n",
       "21                                 236                         16.83   \n",
       "22                                1718                         16.29   \n",
       "23                                 865                         20.46   \n",
       "24                                 108                         11.66   \n",
       "25                                 161                         13.39   \n",
       "26                                 408                         12.78   \n",
       "27                                 108                         10.88   \n",
       "28                                 317                         20.39   \n",
       "29                                  87                         10.61   \n",
       "..                                 ...                           ...   \n",
       "361                                 44                         11.28   \n",
       "362                                 38                         17.76   \n",
       "363                                 26                         13.13   \n",
       "364                                435                         13.02   \n",
       "365                                 67                         12.93   \n",
       "366                                141                         27.81   \n",
       "367                                 68                         25.56   \n",
       "368                                 20                          8.44   \n",
       "369                                222                          7.53   \n",
       "370                                 84                         15.14   \n",
       "371                                 10                          2.78   \n",
       "372                                631                         15.65   \n",
       "373                                103                          9.94   \n",
       "374                                 47                         27.65   \n",
       "375                                160                         97.56   \n",
       "376                                 23                          7.42   \n",
       "377                                 22                         16.92   \n",
       "378                                 74                         16.86   \n",
       "379                                 34                         12.64   \n",
       "380                                 52                          9.56   \n",
       "381                                 42                         13.73   \n",
       "382                                 39                         21.67   \n",
       "383                                 83                         17.47   \n",
       "384                                 83                         20.80   \n",
       "385                                  2                          5.56   \n",
       "386                                 22                          8.18   \n",
       "387                                 23                         15.13   \n",
       "388                                 20                         12.42   \n",
       "389                                 18                         11.76   \n",
       "390                                  3                          3.57   \n",
       "\n",
       "     Public total enrollment 2016  Special ed enrollment 2016  \\\n",
       "0                            1259                        25.0   \n",
       "1                            1809                        75.0   \n",
       "2                            1298                       114.0   \n",
       "3                            7190                       629.0   \n",
       "4                            7362                       677.0   \n",
       "5                           29377                       849.0   \n",
       "6                            9569                       824.0   \n",
       "7                           11562                       224.0   \n",
       "8                             863                        60.0   \n",
       "9                            1871                       243.0   \n",
       "10                           1708                         NaN   \n",
       "11                           1709                        51.0   \n",
       "12                           6931                       301.0   \n",
       "13                           3434                       265.0   \n",
       "14                           2001                       254.0   \n",
       "15                           1110                       195.0   \n",
       "16                           1411                       283.0   \n",
       "17                            911                         NaN   \n",
       "18                           1339                        38.0   \n",
       "19                           4254                         1.0   \n",
       "20                           4761                       208.0   \n",
       "21                           1402                       187.0   \n",
       "22                          10544                       208.0   \n",
       "23                           4228                         4.0   \n",
       "24                            926                        63.0   \n",
       "25                           1202                       212.0   \n",
       "26                           3193                       164.0   \n",
       "27                            993                       179.0   \n",
       "28                           1555                        19.0   \n",
       "29                            820                        16.0   \n",
       "..                            ...                         ...   \n",
       "361                           390                         NaN   \n",
       "362                           214                         NaN   \n",
       "363                           198                         NaN   \n",
       "364                          3342                         NaN   \n",
       "365                           518                         NaN   \n",
       "366                           507                         NaN   \n",
       "367                           266                         NaN   \n",
       "368                           237                         NaN   \n",
       "369                          2947                         NaN   \n",
       "370                           555                         NaN   \n",
       "371                           360                         NaN   \n",
       "372                          4032                         NaN   \n",
       "373                          1036                         NaN   \n",
       "374                           170                         NaN   \n",
       "375                           164                         NaN   \n",
       "376                           310                         NaN   \n",
       "377                           130                         NaN   \n",
       "378                           439                         NaN   \n",
       "379                           269                         NaN   \n",
       "380                           544                         NaN   \n",
       "381                           306                         NaN   \n",
       "382                           180                         NaN   \n",
       "383                           475                         NaN   \n",
       "384                           399                         NaN   \n",
       "385                            36                         NaN   \n",
       "386                           269                         NaN   \n",
       "387                           152                         NaN   \n",
       "388                           161                         NaN   \n",
       "389                           153                         NaN   \n",
       "390                            84                         NaN   \n",
       "\n",
       "     Total enrollment 2016  Special ed ratio 2016  \n",
       "0                    297.0                   8.42  \n",
       "1                   1069.0                   7.02  \n",
       "2                   1012.0                  11.26  \n",
       "3                   9483.0                   6.63  \n",
       "4                  10389.0                   6.52  \n",
       "5                  13046.0                   6.51  \n",
       "6                  12617.0                   6.53  \n",
       "7                   3058.0                   7.33  \n",
       "8                   1025.0                   5.85  \n",
       "9                   2362.0                  10.29  \n",
       "10                     NaN                    NaN  \n",
       "11                   616.0                   8.28  \n",
       "12                  6048.0                   4.98  \n",
       "13                  3406.0                   7.78  \n",
       "14                  3214.0                   7.90  \n",
       "15                  1877.0                  10.39  \n",
       "16                  3035.0                   9.32  \n",
       "17                     NaN                    NaN  \n",
       "18                   267.0                  14.23  \n",
       "19                   127.0                   0.79  \n",
       "20                  3076.0                   6.76  \n",
       "21                  2733.0                   6.84  \n",
       "22                  2983.0                   6.97  \n",
       "23                   462.0                   0.87  \n",
       "24                   745.0                   8.46  \n",
       "25                  2333.0                   9.09  \n",
       "26                  2531.0                   6.48  \n",
       "27                  2043.0                   8.76  \n",
       "28                   743.0                   2.56  \n",
       "29                   172.0                   9.30  \n",
       "..                     ...                    ...  \n",
       "361                    NaN                    NaN  \n",
       "362                    NaN                    NaN  \n",
       "363                    NaN                    NaN  \n",
       "364                    NaN                    NaN  \n",
       "365                    NaN                    NaN  \n",
       "366                    NaN                    NaN  \n",
       "367                    NaN                    NaN  \n",
       "368                    NaN                    NaN  \n",
       "369                    NaN                    NaN  \n",
       "370                    NaN                    NaN  \n",
       "371                    NaN                    NaN  \n",
       "372                    NaN                    NaN  \n",
       "373                    NaN                    NaN  \n",
       "374                    NaN                    NaN  \n",
       "375                    NaN                    NaN  \n",
       "376                    NaN                    NaN  \n",
       "377                    NaN                    NaN  \n",
       "378                    NaN                    NaN  \n",
       "379                    NaN                    NaN  \n",
       "380                    NaN                    NaN  \n",
       "381                    NaN                    NaN  \n",
       "382                    NaN                    NaN  \n",
       "383                    NaN                    NaN  \n",
       "384                    NaN                    NaN  \n",
       "385                    NaN                    NaN  \n",
       "386                    NaN                    NaN  \n",
       "387                    NaN                    NaN  \n",
       "388                    NaN                    NaN  \n",
       "389                    NaN                    NaN  \n",
       "390                    NaN                    NaN  \n",
       "\n",
       "[391 rows x 8 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Merge in public school special ed enrollment data\n",
    "\n",
    "# Tidy and clean columns\n",
    "df_publicSpecialEdEnrollment_trimmed = df_publicSpecialEdEnrollment\n",
    "df_publicSpecialEdEnrollment_trimmed = df_publicSpecialEdEnrollment_trimmed.drop(['ENR_ELL_N','ENR_ELL_RATIO'], axis=1)\n",
    "df_publicSpecialEdEnrollment_trimmed = df_publicSpecialEdEnrollment_trimmed.rename(columns = {'CORP':'District No.','CORP_NAME':'District Name','ENR_SPEC_ED_N':'Public special ed enrollment 2016','ENR_SPEC_ED_RATIO':'Public special ed ratio 2016','ENROLLMENT_N':'Public total enrollment 2016'})\n",
    "df_publicSpecialEdEnrollment_trimmed['Public special ed ratio 2016'] = df_publicSpecialEdEnrollment_trimmed['Public special ed ratio 2016'].apply(normalizePerc)\n",
    "df_publicSpecialEdEnrollment_trimmed\n",
    "\n",
    "# Merge\n",
    "df_districtVoucherSpecialEdAggregate_merged = df_publicSpecialEdEnrollment_trimmed.merge(df_districtVoucherSpecialEdAggregate,on='District No.', how='outer')\n",
    "df_districtVoucherSpecialEdAggregate_merged\n",
    "\n",
    "# df_districtVoucherSpecialEdAggregate_merged.to_csv('school_choice_data/exported_data/df_districtVoucherSpecialEdAggregate_merged.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": []
  }
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