updated notebook
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "7acc26cb",
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "c821dd0a",
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"metadata": {},
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"outputs": [],
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"source": [
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"df = pd.read_csv('https://raw.githubusercontent.com/CunyLaguardiaDataAnalytics/datasets/master/2014-15_To_2016-17_School-_Level_NYC_Regents_Report_For_All_Variables.csv')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 71,
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"id": "e080ce64",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(212331, 15)"
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]
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},
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"execution_count": 71,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"df.shape"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 45,
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"id": "57651a37",
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"School DBN object\n",
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"School Name object\n",
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"School Level object\n",
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"Regents Exam object\n",
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"Year int64\n",
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"Total Tested int64\n",
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"Mean Score object\n",
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"Number Scoring Below 65 object\n",
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"Percent Scoring Below 65 object\n",
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"Number Scoring 65 or Above object\n",
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"Percent Scoring 65 or Above object\n",
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"Number Scoring 80 or Above object\n",
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"Percent Scoring 80 or Above object\n",
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"Number Scoring CR object\n",
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"Percent Scoring CR object\n",
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"dtype: object"
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]
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},
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"execution_count": 45,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"df.dtypes"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 63,
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"id": "7147a7d1",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"2015 2017\n"
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]
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}
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],
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"source": [
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"# Time range should be 2014-2015 to 2016-2017 school year. Does the 'Year' column reflect this range?\n",
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"\n",
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"print(df['Year'].min(), df['Year'].max())"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 66,
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"id": "897e335b",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"School DBN 0\n",
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"School Name 0\n",
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"School Level 0\n",
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"Regents Exam 10\n",
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"Year 0\n",
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"Total Tested 0\n",
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"Mean Score 0\n",
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"Number Scoring Below 65 0\n",
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"Percent Scoring Below 65 0\n",
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"Number Scoring 65 or Above 0\n",
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"Percent Scoring 65 or Above 0\n",
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"Number Scoring 80 or Above 0\n",
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"Percent Scoring 80 or Above 0\n",
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"Number Scoring CR 0\n",
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"Percent Scoring CR 0\n",
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"dtype: int64"
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]
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},
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"execution_count": 66,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# Is there any missing data?\n",
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"\n",
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"df.isna().sum()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 79,
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"id": "e0ab351b",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>School DBN</th>\n",
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" <th>School Name</th>\n",
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" <th>School Level</th>\n",
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" <th>Regents Exam</th>\n",
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" <th>Year</th>\n",
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" <th>Total Tested</th>\n",
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" <th>Mean Score</th>\n",
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" <th>Number Scoring Below 65</th>\n",
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" <th>Percent Scoring Below 65</th>\n",
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" <th>Number Scoring 65 or Above</th>\n",
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" <th>Percent Scoring 65 or Above</th>\n",
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" <th>Number Scoring 80 or Above</th>\n",
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" <th>Percent Scoring 80 or Above</th>\n",
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" <th>Number Scoring CR</th>\n",
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" <th>Percent Scoring CR</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>18654</th>\n",
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" <td>84M478</td>\n",
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" <td>Inwood Academy for Leadership Charter School</td>\n",
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" <td>Secondary School</td>\n",
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" <td>NaN</td>\n",
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" <td>2015</td>\n",
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" <td>90</td>\n",
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" <td>55.6</td>\n",
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" <td>61</td>\n",
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" <td>67.8</td>\n",
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" <td>29</td>\n",
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" <td>32.2</td>\n",
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" <td>6</td>\n",
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" <td>6.7</td>\n",
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" <td>0</td>\n",
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" <td>0</td>\n",
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" <td>84M478</td>\n",
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" <td>Inwood Academy for Leadership Charter School</td>\n",
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" <td>Secondary School</td>\n",
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" <td>NaN</td>\n",
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" <td>2015</td>\n",
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" <td>81</td>\n",
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" <td>55.9</td>\n",
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" <td>55</td>\n",
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" <td>67.9</td>\n",
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" <td>26</td>\n",
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" <td>32.1</td>\n",
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" <td>5</td>\n",
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" <td>6.2</td>\n",
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" <td>0</td>\n",
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" <tr>\n",
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" <th>52757</th>\n",
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" <td>84M478</td>\n",
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" <td>Inwood Academy for Leadership Charter School</td>\n",
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" <td>Secondary School</td>\n",
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" <td>NaN</td>\n",
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" <td>2015</td>\n",
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" <td>9</td>\n",
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" <td>53.4</td>\n",
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" <td>6</td>\n",
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" <td>66.7</td>\n",
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" <td>3</td>\n",
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" <td>33.3</td>\n",
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" <td>1</td>\n",
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" <td>11.1</td>\n",
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" <td>0</td>\n",
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" <td>0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>100865</th>\n",
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" <td>84M478</td>\n",
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" <td>Inwood Academy for Leadership Charter School</td>\n",
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" <td>Secondary School</td>\n",
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" <td>NaN</td>\n",
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" <td>2015</td>\n",
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" <td>5</td>\n",
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" <td>s</td>\n",
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" <td>s</td>\n",
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" <td>na</td>\n",
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" <td>na</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>100866</th>\n",
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" <td>84M478</td>\n",
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" <td>Inwood Academy for Leadership Charter School</td>\n",
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" <td>Secondary School</td>\n",
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" <td>NaN</td>\n",
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" <td>2015</td>\n",
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" <td>54</td>\n",
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" <td>57.4</td>\n",
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" <td>34</td>\n",
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" <td>63</td>\n",
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" <td>20</td>\n",
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" <td>37</td>\n",
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" <td>6</td>\n",
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" <td>11.1</td>\n",
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" <td>0</td>\n",
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" <td>0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>100867</th>\n",
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" <td>84M478</td>\n",
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" <td>Inwood Academy for Leadership Charter School</td>\n",
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" <td>Secondary School</td>\n",
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" <td>NaN</td>\n",
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" <td>2015</td>\n",
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" <td>31</td>\n",
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" <td>s</td>\n",
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" <td>s</td>\n",
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" <td>s</td>\n",
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" <td>s</td>\n",
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||||
" <td>s</td>\n",
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" <td>s</td>\n",
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" <td>na</td>\n",
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" <td>na</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>138300</th>\n",
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" <td>84M478</td>\n",
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" <td>Inwood Academy for Leadership Charter School</td>\n",
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" <td>Secondary School</td>\n",
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" <td>NaN</td>\n",
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" <td>2015</td>\n",
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" <td>54</td>\n",
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" <td>57.3</td>\n",
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" <td>34</td>\n",
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" <td>63</td>\n",
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" <td>20</td>\n",
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" <td>37</td>\n",
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" <td>5</td>\n",
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" <td>9.3</td>\n",
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" <td>0</td>\n",
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" <td>0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>138301</th>\n",
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" <td>84M478</td>\n",
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" <td>Inwood Academy for Leadership Charter School</td>\n",
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" <td>Secondary School</td>\n",
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" <td>NaN</td>\n",
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" <td>2015</td>\n",
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" <td>36</td>\n",
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" <td>53.2</td>\n",
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" <td>27</td>\n",
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" <td>75</td>\n",
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" <td>9</td>\n",
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" <td>25</td>\n",
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" <td>1</td>\n",
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" <td>2.8</td>\n",
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" <td>0</td>\n",
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" <td>0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>209785</th>\n",
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" <td>84M478</td>\n",
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" <td>Inwood Academy for Leadership Charter School</td>\n",
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" <td>Secondary School</td>\n",
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" <td>NaN</td>\n",
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" <td>2015</td>\n",
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" <td>12</td>\n",
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" <td>59</td>\n",
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" <td>9</td>\n",
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" <td>75</td>\n",
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" <td>3</td>\n",
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" <td>25</td>\n",
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" <td>1</td>\n",
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" <td>8.3</td>\n",
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" <td>0</td>\n",
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" <td>0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>209786</th>\n",
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" <td>84M478</td>\n",
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" <td>Inwood Academy for Leadership Charter School</td>\n",
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" <td>Secondary School</td>\n",
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" <td>NaN</td>\n",
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" <td>2015</td>\n",
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" <td>78</td>\n",
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" <td>55.1</td>\n",
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" <td>52</td>\n",
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" <td>66.7</td>\n",
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" <td>26</td>\n",
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" <td>33.3</td>\n",
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" <td>5</td>\n",
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" <td>6.4</td>\n",
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" <td>0</td>\n",
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" <td>0</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" School DBN School Name \\\n",
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"18654 84M478 Inwood Academy for Leadership Charter School \n",
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"52756 84M478 Inwood Academy for Leadership Charter School \n",
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"52757 84M478 Inwood Academy for Leadership Charter School \n",
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"100865 84M478 Inwood Academy for Leadership Charter School \n",
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"100866 84M478 Inwood Academy for Leadership Charter School \n",
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"100867 84M478 Inwood Academy for Leadership Charter School \n",
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"138300 84M478 Inwood Academy for Leadership Charter School \n",
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"138301 84M478 Inwood Academy for Leadership Charter School \n",
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"209785 84M478 Inwood Academy for Leadership Charter School \n",
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"209786 84M478 Inwood Academy for Leadership Charter School \n",
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"\n",
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" School Level Regents Exam Year Total Tested Mean Score \\\n",
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"18654 Secondary School NaN 2015 90 55.6 \n",
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"52756 Secondary School NaN 2015 81 55.9 \n",
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"52757 Secondary School NaN 2015 9 53.4 \n",
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"100865 Secondary School NaN 2015 5 s \n",
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"100866 Secondary School NaN 2015 54 57.4 \n",
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"100867 Secondary School NaN 2015 31 s \n",
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"138300 Secondary School NaN 2015 54 57.3 \n",
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"138301 Secondary School NaN 2015 36 53.2 \n",
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"209785 Secondary School NaN 2015 12 59 \n",
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"209786 Secondary School NaN 2015 78 55.1 \n",
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"\n",
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" Number Scoring Below 65 Percent Scoring Below 65 \\\n",
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"18654 61 67.8 \n",
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"52756 55 67.9 \n",
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"52757 6 66.7 \n",
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"100865 s s \n",
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"100866 34 63 \n",
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"100867 s s \n",
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"138300 34 63 \n",
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"138301 27 75 \n",
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"209785 9 75 \n",
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"209786 52 66.7 \n",
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"\n",
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" Number Scoring 65 or Above Percent Scoring 65 or Above \\\n",
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"18654 29 32.2 \n",
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"52756 26 32.1 \n",
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"52757 3 33.3 \n",
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"100865 s s \n",
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"100866 20 37 \n",
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"100867 s s \n",
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"138300 20 37 \n",
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"138301 9 25 \n",
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"209785 3 25 \n",
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"209786 26 33.3 \n",
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"\n",
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" Number Scoring 80 or Above Percent Scoring 80 or Above \\\n",
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"18654 6 6.7 \n",
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"52756 5 6.2 \n",
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"52757 1 11.1 \n",
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"100865 s s \n",
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"100866 6 11.1 \n",
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"100867 s s \n",
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"138300 5 9.3 \n",
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"138301 1 2.8 \n",
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"209785 1 8.3 \n",
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"209786 5 6.4 \n",
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"\n",
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" Number Scoring CR Percent Scoring CR \n",
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"18654 0 0 \n",
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"52756 0 0 \n",
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"52757 0 0 \n",
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"100865 na na \n",
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"100866 0 0 \n",
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"100867 na na \n",
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"138300 0 0 \n",
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"138301 0 0 \n",
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"209785 0 0 \n",
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"209786 0 0 "
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]
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},
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"execution_count": 79,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"df[df['Regents Exam'].isna()]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 83,
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"id": "c9a49215",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Cleaning the data\n",
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"\n",
|
||||
"# There are ten missing values. One school is responsible. We'll drop that school from the dataset\n",
|
||||
"\n",
|
||||
"df.dropna(inplace = True)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 137,
|
||||
"id": "1f05cd97",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"<class 'pandas.core.frame.DataFrame'>\n",
|
||||
"Int64Index: 137101 entries, 1 to 212325\n",
|
||||
"Data columns (total 15 columns):\n",
|
||||
" # Column Non-Null Count Dtype \n",
|
||||
"--- ------ -------------- ----- \n",
|
||||
" 0 School DBN 137101 non-null object \n",
|
||||
" 1 School Name 137101 non-null object \n",
|
||||
" 2 School Level 137101 non-null object \n",
|
||||
" 3 Regents Exam 137101 non-null object \n",
|
||||
" 4 Year 137101 non-null int64 \n",
|
||||
" 5 Total Tested 137101 non-null int64 \n",
|
||||
" 6 Mean Score 137101 non-null float64\n",
|
||||
" 7 Number Scoring Below 65 137101 non-null object \n",
|
||||
" 8 Percent Scoring Below 65 137101 non-null object \n",
|
||||
" 9 Number Scoring 65 or Above 137101 non-null object \n",
|
||||
" 10 Percent Scoring 65 or Above 137101 non-null object \n",
|
||||
" 11 Number Scoring 80 or Above 137101 non-null object \n",
|
||||
" 12 Percent Scoring 80 or Above 137101 non-null object \n",
|
||||
" 13 Number Scoring CR 137101 non-null object \n",
|
||||
" 14 Percent Scoring CR 137101 non-null object \n",
|
||||
"dtypes: float64(1), int64(2), object(12)\n",
|
||||
"memory usage: 16.7+ MB\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# 'Mean Score'\n",
|
||||
"\n",
|
||||
"# We expect integers or floats. Instead we have objects.\n",
|
||||
"# Can we convert them to floats?\n",
|
||||
"\n",
|
||||
"# Yes, but first we have to deal with the nonsense value 's'.\n",
|
||||
"# We don't know what 's' means so let's make a subset then\n",
|
||||
"# convert the mean scores to floats.\n",
|
||||
"\n",
|
||||
"df = df[df['Mean Score'] != 's']\n",
|
||||
"df['Mean Score'] = pd.to_numeric(df['Mean Score'])\n",
|
||||
"df.info()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 142,
|
||||
"id": "f62fbc11",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"dtype('O')"
|
||||
]
|
||||
},
|
||||
"execution_count": 142,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# 'Percent Scoring 80 or Above': an interesting column.\n",
|
||||
"# This column's data type also needs to be recast.\n",
|
||||
"\n",
|
||||
"df['Percent Scoring 80 or Above'].dtype"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 146,
|
||||
"id": "e3550ecb",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"dtype('float64')"
|
||||
]
|
||||
},
|
||||
"execution_count": 146,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"df['Percent Scoring 80 or Above'] = pd.to_numeric(df['Percent Scoring 80 or Above'])\n",
|
||||
"df['Percent Scoring 80 or Above'].dtype"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 148,
|
||||
"id": "138ebba4",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<div>\n",
|
||||
"<style scoped>\n",
|
||||
" .dataframe tbody tr th:only-of-type {\n",
|
||||
" vertical-align: middle;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe tbody tr th {\n",
|
||||
" vertical-align: top;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe thead th {\n",
|
||||
" text-align: right;\n",
|
||||
" }\n",
|
||||
"</style>\n",
|
||||
"<table border=\"1\" class=\"dataframe\">\n",
|
||||
" <thead>\n",
|
||||
" <tr style=\"text-align: right;\">\n",
|
||||
" <th></th>\n",
|
||||
" <th>School DBN</th>\n",
|
||||
" <th>School Name</th>\n",
|
||||
" <th>School Level</th>\n",
|
||||
" <th>Regents Exam</th>\n",
|
||||
" <th>Year</th>\n",
|
||||
" <th>Total Tested</th>\n",
|
||||
" <th>Mean Score</th>\n",
|
||||
" <th>Number Scoring Below 65</th>\n",
|
||||
" <th>Percent Scoring Below 65</th>\n",
|
||||
" <th>Number Scoring 65 or Above</th>\n",
|
||||
" <th>Percent Scoring 65 or Above</th>\n",
|
||||
" <th>Number Scoring 80 or Above</th>\n",
|
||||
" <th>Percent Scoring 80 or Above</th>\n",
|
||||
" <th>Number Scoring CR</th>\n",
|
||||
" <th>Percent Scoring CR</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>1</th>\n",
|
||||
" <td>01M034</td>\n",
|
||||
" <td>P.S. 034 Franklin D. Roosevelt</td>\n",
|
||||
" <td>K-8</td>\n",
|
||||
" <td>Living Environment</td>\n",
|
||||
" <td>2015</td>\n",
|
||||
" <td>16</td>\n",
|
||||
" <td>77.9</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>6.3</td>\n",
|
||||
" <td>15</td>\n",
|
||||
" <td>93.8</td>\n",
|
||||
" <td>7</td>\n",
|
||||
" <td>43.8</td>\n",
|
||||
" <td>na</td>\n",
|
||||
" <td>na</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2</th>\n",
|
||||
" <td>01M034</td>\n",
|
||||
" <td>P.S. 034 Franklin D. Roosevelt</td>\n",
|
||||
" <td>K-8</td>\n",
|
||||
" <td>Living Environment</td>\n",
|
||||
" <td>2016</td>\n",
|
||||
" <td>9</td>\n",
|
||||
" <td>74.0</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>11.1</td>\n",
|
||||
" <td>8</td>\n",
|
||||
" <td>88.9</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>22.2</td>\n",
|
||||
" <td>na</td>\n",
|
||||
" <td>na</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>5</th>\n",
|
||||
" <td>01M140</td>\n",
|
||||
" <td>P.S. 140 Nathan Straus</td>\n",
|
||||
" <td>K-8</td>\n",
|
||||
" <td>Living Environment</td>\n",
|
||||
" <td>2015</td>\n",
|
||||
" <td>9</td>\n",
|
||||
" <td>67.4</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>33.3</td>\n",
|
||||
" <td>6</td>\n",
|
||||
" <td>66.7</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>na</td>\n",
|
||||
" <td>na</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>6</th>\n",
|
||||
" <td>01M140</td>\n",
|
||||
" <td>P.S. 140 Nathan Straus</td>\n",
|
||||
" <td>K-8</td>\n",
|
||||
" <td>Living Environment</td>\n",
|
||||
" <td>2016</td>\n",
|
||||
" <td>15</td>\n",
|
||||
" <td>72.6</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>13.3</td>\n",
|
||||
" <td>13</td>\n",
|
||||
" <td>86.7</td>\n",
|
||||
" <td>5</td>\n",
|
||||
" <td>33.3</td>\n",
|
||||
" <td>na</td>\n",
|
||||
" <td>na</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>7</th>\n",
|
||||
" <td>01M140</td>\n",
|
||||
" <td>P.S. 140 Nathan Straus</td>\n",
|
||||
" <td>K-8</td>\n",
|
||||
" <td>Living Environment</td>\n",
|
||||
" <td>2017</td>\n",
|
||||
" <td>9</td>\n",
|
||||
" <td>64.4</td>\n",
|
||||
" <td>5</td>\n",
|
||||
" <td>55.6</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>44.4</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>11.1</td>\n",
|
||||
" <td>na</td>\n",
|
||||
" <td>na</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>...</th>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>212321</th>\n",
|
||||
" <td>84X717</td>\n",
|
||||
" <td>Icahn Charter School</td>\n",
|
||||
" <td>K-8</td>\n",
|
||||
" <td>Common Core Algebra</td>\n",
|
||||
" <td>2016</td>\n",
|
||||
" <td>6</td>\n",
|
||||
" <td>87.2</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>6</td>\n",
|
||||
" <td>100</td>\n",
|
||||
" <td>6</td>\n",
|
||||
" <td>100.0</td>\n",
|
||||
" <td>6</td>\n",
|
||||
" <td>100</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>212322</th>\n",
|
||||
" <td>84X717</td>\n",
|
||||
" <td>Icahn Charter School</td>\n",
|
||||
" <td>K-8</td>\n",
|
||||
" <td>Common Core Algebra</td>\n",
|
||||
" <td>2017</td>\n",
|
||||
" <td>6</td>\n",
|
||||
" <td>87.0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>6</td>\n",
|
||||
" <td>100</td>\n",
|
||||
" <td>6</td>\n",
|
||||
" <td>100.0</td>\n",
|
||||
" <td>6</td>\n",
|
||||
" <td>100</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>212323</th>\n",
|
||||
" <td>84X717</td>\n",
|
||||
" <td>Icahn Charter School</td>\n",
|
||||
" <td>K-8</td>\n",
|
||||
" <td>Common Core Algebra</td>\n",
|
||||
" <td>2017</td>\n",
|
||||
" <td>6</td>\n",
|
||||
" <td>88.3</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>6</td>\n",
|
||||
" <td>100</td>\n",
|
||||
" <td>5</td>\n",
|
||||
" <td>83.3</td>\n",
|
||||
" <td>6</td>\n",
|
||||
" <td>100</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>212324</th>\n",
|
||||
" <td>84X717</td>\n",
|
||||
" <td>Icahn Charter School</td>\n",
|
||||
" <td>K-8</td>\n",
|
||||
" <td>Living Environment</td>\n",
|
||||
" <td>2015</td>\n",
|
||||
" <td>8</td>\n",
|
||||
" <td>76.5</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>12.5</td>\n",
|
||||
" <td>7</td>\n",
|
||||
" <td>87.5</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>25.0</td>\n",
|
||||
" <td>na</td>\n",
|
||||
" <td>na</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>212325</th>\n",
|
||||
" <td>84X717</td>\n",
|
||||
" <td>Icahn Charter School</td>\n",
|
||||
" <td>K-8</td>\n",
|
||||
" <td>Living Environment</td>\n",
|
||||
" <td>2015</td>\n",
|
||||
" <td>6</td>\n",
|
||||
" <td>79.8</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>6</td>\n",
|
||||
" <td>100</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>33.3</td>\n",
|
||||
" <td>na</td>\n",
|
||||
" <td>na</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"<p>137101 rows × 15 columns</p>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" School DBN School Name School Level \\\n",
|
||||
"1 01M034 P.S. 034 Franklin D. Roosevelt K-8 \n",
|
||||
"2 01M034 P.S. 034 Franklin D. Roosevelt K-8 \n",
|
||||
"5 01M140 P.S. 140 Nathan Straus K-8 \n",
|
||||
"6 01M140 P.S. 140 Nathan Straus K-8 \n",
|
||||
"7 01M140 P.S. 140 Nathan Straus K-8 \n",
|
||||
"... ... ... ... \n",
|
||||
"212321 84X717 Icahn Charter School K-8 \n",
|
||||
"212322 84X717 Icahn Charter School K-8 \n",
|
||||
"212323 84X717 Icahn Charter School K-8 \n",
|
||||
"212324 84X717 Icahn Charter School K-8 \n",
|
||||
"212325 84X717 Icahn Charter School K-8 \n",
|
||||
"\n",
|
||||
" Regents Exam Year Total Tested Mean Score \\\n",
|
||||
"1 Living Environment 2015 16 77.9 \n",
|
||||
"2 Living Environment 2016 9 74.0 \n",
|
||||
"5 Living Environment 2015 9 67.4 \n",
|
||||
"6 Living Environment 2016 15 72.6 \n",
|
||||
"7 Living Environment 2017 9 64.4 \n",
|
||||
"... ... ... ... ... \n",
|
||||
"212321 Common Core Algebra 2016 6 87.2 \n",
|
||||
"212322 Common Core Algebra 2017 6 87.0 \n",
|
||||
"212323 Common Core Algebra 2017 6 88.3 \n",
|
||||
"212324 Living Environment 2015 8 76.5 \n",
|
||||
"212325 Living Environment 2015 6 79.8 \n",
|
||||
"\n",
|
||||
" Number Scoring Below 65 Percent Scoring Below 65 \\\n",
|
||||
"1 1 6.3 \n",
|
||||
"2 1 11.1 \n",
|
||||
"5 3 33.3 \n",
|
||||
"6 2 13.3 \n",
|
||||
"7 5 55.6 \n",
|
||||
"... ... ... \n",
|
||||
"212321 0 0 \n",
|
||||
"212322 0 0 \n",
|
||||
"212323 0 0 \n",
|
||||
"212324 1 12.5 \n",
|
||||
"212325 0 0 \n",
|
||||
"\n",
|
||||
" Number Scoring 65 or Above Percent Scoring 65 or Above \\\n",
|
||||
"1 15 93.8 \n",
|
||||
"2 8 88.9 \n",
|
||||
"5 6 66.7 \n",
|
||||
"6 13 86.7 \n",
|
||||
"7 4 44.4 \n",
|
||||
"... ... ... \n",
|
||||
"212321 6 100 \n",
|
||||
"212322 6 100 \n",
|
||||
"212323 6 100 \n",
|
||||
"212324 7 87.5 \n",
|
||||
"212325 6 100 \n",
|
||||
"\n",
|
||||
" Number Scoring 80 or Above Percent Scoring 80 or Above \\\n",
|
||||
"1 7 43.8 \n",
|
||||
"2 2 22.2 \n",
|
||||
"5 0 0.0 \n",
|
||||
"6 5 33.3 \n",
|
||||
"7 1 11.1 \n",
|
||||
"... ... ... \n",
|
||||
"212321 6 100.0 \n",
|
||||
"212322 6 100.0 \n",
|
||||
"212323 5 83.3 \n",
|
||||
"212324 2 25.0 \n",
|
||||
"212325 2 33.3 \n",
|
||||
"\n",
|
||||
" Number Scoring CR Percent Scoring CR \n",
|
||||
"1 na na \n",
|
||||
"2 na na \n",
|
||||
"5 na na \n",
|
||||
"6 na na \n",
|
||||
"7 na na \n",
|
||||
"... ... ... \n",
|
||||
"212321 6 100 \n",
|
||||
"212322 6 100 \n",
|
||||
"212323 6 100 \n",
|
||||
"212324 na na \n",
|
||||
"212325 na na \n",
|
||||
"\n",
|
||||
"[137101 rows x 15 columns]"
|
||||
]
|
||||
},
|
||||
"execution_count": 148,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"df"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"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": "3.10.4"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
Loading…
Reference in New Issue