nyc_restaurant_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b3707d83",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import dependencies and load in CSV files\n",
    "import pandas as pd\n",
    "from pathlib import Path \n",
    "\n",
    "nyc_inspection_df = pd.read_csv(\"Resources/nyc_restaurants/DOHMH_New_York_City_Restaurant_Inspection_Results.csv\") # , index_col=0)\n",
    "nyc_income_df = pd.read_csv(\"Resources/nyc_restaurants/Pre_restaurants.csv\") #, index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5e6d2238",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CAMIS</th>\n",
       "      <th>DBA</th>\n",
       "      <th>BORO</th>\n",
       "      <th>BUILDING</th>\n",
       "      <th>STREET</th>\n",
       "      <th>ZIPCODE</th>\n",
       "      <th>PHONE</th>\n",
       "      <th>CUISINE DESCRIPTION</th>\n",
       "      <th>INSPECTION DATE</th>\n",
       "      <th>ACTION</th>\n",
       "      <th>...</th>\n",
       "      <th>RECORD DATE</th>\n",
       "      <th>INSPECTION TYPE</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Community Board</th>\n",
       "      <th>Council District</th>\n",
       "      <th>Census Tract</th>\n",
       "      <th>BIN</th>\n",
       "      <th>BBL</th>\n",
       "      <th>NTA</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>50070654</td>\n",
       "      <td>JOE &amp; THE JUICE</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>801</td>\n",
       "      <td>LEXINGTON AVENUE</td>\n",
       "      <td>10065.0</td>\n",
       "      <td>9179240079</td>\n",
       "      <td>Juice, Smoothies, Fruit Salads</td>\n",
       "      <td>05/03/2022</td>\n",
       "      <td>Violations were cited in the following area(s).</td>\n",
       "      <td>...</td>\n",
       "      <td>05/09/2022</td>\n",
       "      <td>Cycle Inspection / Initial Inspection</td>\n",
       "      <td>40.764001</td>\n",
       "      <td>-73.966872</td>\n",
       "      <td>108.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>11402.0</td>\n",
       "      <td>1041994.0</td>\n",
       "      <td>1.013960e+09</td>\n",
       "      <td>MN40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>50099396</td>\n",
       "      <td>MR LIU'S SPICY CHICKEN</td>\n",
       "      <td>Queens</td>\n",
       "      <td>133-35</td>\n",
       "      <td>ROOSEVELT AVENUE</td>\n",
       "      <td>11354.0</td>\n",
       "      <td>9293536666</td>\n",
       "      <td>Asian/Asian Fusion</td>\n",
       "      <td>11/14/2019</td>\n",
       "      <td>Establishment Closed by DOHMH. Violations were...</td>\n",
       "      <td>...</td>\n",
       "      <td>05/09/2022</td>\n",
       "      <td>Pre-permit (Operational) / Initial Inspection</td>\n",
       "      <td>40.758502</td>\n",
       "      <td>-73.833242</td>\n",
       "      <td>407.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>87100.0</td>\n",
       "      <td>4112276.0</td>\n",
       "      <td>4.049730e+09</td>\n",
       "      <td>QN22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>50043940</td>\n",
       "      <td>SURYA INDIAN CUISINE</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>154</td>\n",
       "      <td>BLEECKER STREET</td>\n",
       "      <td>10012.0</td>\n",
       "      <td>7187374235</td>\n",
       "      <td>Indian</td>\n",
       "      <td>05/24/2019</td>\n",
       "      <td>Violations were cited in the following area(s).</td>\n",
       "      <td>...</td>\n",
       "      <td>05/09/2022</td>\n",
       "      <td>Cycle Inspection / Initial Inspection</td>\n",
       "      <td>40.728354</td>\n",
       "      <td>-73.999571</td>\n",
       "      <td>102.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6500.0</td>\n",
       "      <td>1008266.0</td>\n",
       "      <td>1.005258e+09</td>\n",
       "      <td>MN23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>50067280</td>\n",
       "      <td>LUCKY RESTAURANT</td>\n",
       "      <td>Queens</td>\n",
       "      <td>4521</td>\n",
       "      <td>PARSONS BLVD</td>\n",
       "      <td>11355.0</td>\n",
       "      <td>3478825962</td>\n",
       "      <td>Chinese</td>\n",
       "      <td>05/09/2019</td>\n",
       "      <td>Violations were cited in the following area(s).</td>\n",
       "      <td>...</td>\n",
       "      <td>05/09/2022</td>\n",
       "      <td>Cycle Inspection / Initial Inspection</td>\n",
       "      <td>40.755241</td>\n",
       "      <td>-73.815033</td>\n",
       "      <td>407.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>118900.0</td>\n",
       "      <td>4122841.0</td>\n",
       "      <td>4.054300e+09</td>\n",
       "      <td>QN52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>50108963</td>\n",
       "      <td>TENGRITAGH UYGHUR CUSINE</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>144</td>\n",
       "      <td>WEST   37 STREET</td>\n",
       "      <td>10018.0</td>\n",
       "      <td>3392248555</td>\n",
       "      <td>Chinese</td>\n",
       "      <td>02/23/2022</td>\n",
       "      <td>Violations were cited in the following area(s).</td>\n",
       "      <td>...</td>\n",
       "      <td>05/09/2022</td>\n",
       "      <td>Pre-permit (Operational) / Re-inspection</td>\n",
       "      <td>40.752433</td>\n",
       "      <td>-73.988180</td>\n",
       "      <td>105.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>10900.0</td>\n",
       "      <td>1015248.0</td>\n",
       "      <td>1.008120e+09</td>\n",
       "      <td>MN17</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      CAMIS                       DBA       BORO BUILDING            STREET  \\\n",
       "0  50070654           JOE & THE JUICE  Manhattan      801  LEXINGTON AVENUE   \n",
       "1  50099396    MR LIU'S SPICY CHICKEN     Queens   133-35  ROOSEVELT AVENUE   \n",
       "2  50043940      SURYA INDIAN CUISINE  Manhattan      154   BLEECKER STREET   \n",
       "3  50067280          LUCKY RESTAURANT     Queens     4521      PARSONS BLVD   \n",
       "4  50108963  TENGRITAGH UYGHUR CUSINE  Manhattan      144  WEST   37 STREET   \n",
       "\n",
       "   ZIPCODE       PHONE             CUISINE DESCRIPTION INSPECTION DATE  \\\n",
       "0  10065.0  9179240079  Juice, Smoothies, Fruit Salads      05/03/2022   \n",
       "1  11354.0  9293536666              Asian/Asian Fusion      11/14/2019   \n",
       "2  10012.0  7187374235                          Indian      05/24/2019   \n",
       "3  11355.0  3478825962                         Chinese      05/09/2019   \n",
       "4  10018.0  3392248555                         Chinese      02/23/2022   \n",
       "\n",
       "                                              ACTION  ... RECORD DATE  \\\n",
       "0    Violations were cited in the following area(s).  ...  05/09/2022   \n",
       "1  Establishment Closed by DOHMH. Violations were...  ...  05/09/2022   \n",
       "2    Violations were cited in the following area(s).  ...  05/09/2022   \n",
       "3    Violations were cited in the following area(s).  ...  05/09/2022   \n",
       "4    Violations were cited in the following area(s).  ...  05/09/2022   \n",
       "\n",
       "                                 INSPECTION TYPE   Latitude  Longitude  \\\n",
       "0          Cycle Inspection / Initial Inspection  40.764001 -73.966872   \n",
       "1  Pre-permit (Operational) / Initial Inspection  40.758502 -73.833242   \n",
       "2          Cycle Inspection / Initial Inspection  40.728354 -73.999571   \n",
       "3          Cycle Inspection / Initial Inspection  40.755241 -73.815033   \n",
       "4       Pre-permit (Operational) / Re-inspection  40.752433 -73.988180   \n",
       "\n",
       "  Community Board Council District Census Tract        BIN           BBL   NTA  \n",
       "0           108.0              4.0      11402.0  1041994.0  1.013960e+09  MN40  \n",
       "1           407.0             20.0      87100.0  4112276.0  4.049730e+09  QN22  \n",
       "2           102.0              1.0       6500.0  1008266.0  1.005258e+09  MN23  \n",
       "3           407.0             20.0     118900.0  4122841.0  4.054300e+09  QN52  \n",
       "4           105.0              3.0      10900.0  1015248.0  1.008120e+09  MN17  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read the df from the NYC restaurant inspections\n",
    "nyc_inspection_df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f626ee28",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>New York</th>\n",
       "      <th>Borough</th>\n",
       "      <th>income_num_returns(households)</th>\n",
       "      <th>avg income per return(x1000s)</th>\n",
       "      <th>income level</th>\n",
       "      <th>DBA</th>\n",
       "      <th>STREET</th>\n",
       "      <th>GRADE DATE</th>\n",
       "      <th>LATITUDE</th>\n",
       "      <th>LONGITUDE</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>10007</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>3640</td>\n",
       "      <td>693.379945</td>\n",
       "      <td>high income</td>\n",
       "      <td>MARIACHI'S RESTAURANT</td>\n",
       "      <td>CHAMBERS STREET</td>\n",
       "      <td>1/13/2020</td>\n",
       "      <td>40.716432</td>\n",
       "      <td>-74.010472</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>10007</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>3640</td>\n",
       "      <td>693.379945</td>\n",
       "      <td>high income</td>\n",
       "      <td>SPOTIFY - BARISTA BAR</td>\n",
       "      <td>GREENWICH STREET</td>\n",
       "      <td>1/22/2020</td>\n",
       "      <td>40.715553</td>\n",
       "      <td>-74.011021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>10007</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>3640</td>\n",
       "      <td>693.379945</td>\n",
       "      <td>high income</td>\n",
       "      <td>STARBUCKS COFFEE COMPANY #29854</td>\n",
       "      <td>GREENWICH STREET</td>\n",
       "      <td>1/13/2020</td>\n",
       "      <td>40.715553</td>\n",
       "      <td>-74.011021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>10007</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>3640</td>\n",
       "      <td>693.379945</td>\n",
       "      <td>high income</td>\n",
       "      <td>CANTEEN</td>\n",
       "      <td>WORLD TRADE CTR</td>\n",
       "      <td>1/23/2020</td>\n",
       "      <td>40.713941</td>\n",
       "      <td>-74.007401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>10007</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>3640</td>\n",
       "      <td>693.379945</td>\n",
       "      <td>high income</td>\n",
       "      <td>JOE &amp; THE JUICE GREENWICH ST</td>\n",
       "      <td>GREENWICH STREET</td>\n",
       "      <td>12/30/2019</td>\n",
       "      <td>40.715553</td>\n",
       "      <td>-74.011021</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  New York    Borough  income_num_returns(households)  \\\n",
       "0           0     10007  Manhattan                            3640   \n",
       "1           1     10007  Manhattan                            3640   \n",
       "2           2     10007  Manhattan                            3640   \n",
       "3           4     10007  Manhattan                            3640   \n",
       "4           5     10007  Manhattan                            3640   \n",
       "\n",
       "   avg income per return(x1000s) income level  \\\n",
       "0                     693.379945  high income   \n",
       "1                     693.379945  high income   \n",
       "2                     693.379945  high income   \n",
       "3                     693.379945  high income   \n",
       "4                     693.379945  high income   \n",
       "\n",
       "                               DBA            STREET  GRADE DATE   LATITUDE  \\\n",
       "0            MARIACHI'S RESTAURANT   CHAMBERS STREET   1/13/2020  40.716432   \n",
       "1            SPOTIFY - BARISTA BAR  GREENWICH STREET   1/22/2020  40.715553   \n",
       "2  STARBUCKS COFFEE COMPANY #29854  GREENWICH STREET   1/13/2020  40.715553   \n",
       "3                          CANTEEN   WORLD TRADE CTR   1/23/2020  40.713941   \n",
       "4     JOE & THE JUICE GREENWICH ST  GREENWICH STREET  12/30/2019  40.715553   \n",
       "\n",
       "   LONGITUDE  \n",
       "0 -74.010472  \n",
       "1 -74.011021  \n",
       "2 -74.011021  \n",
       "3 -74.007401  \n",
       "4 -74.011021  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read the df from the income levels of the areas around the restaurants\n",
    "nyc_income_df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "336fe5cc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Drop columns\n",
    "clean_inspection_df = nyc_inspection_df.drop(['CAMIS', 'BUILDING', 'PHONE', 'INSPECTION DATE', \n",
    "                                              'ACTION', 'VIOLATION CODE', 'VIOLATION DESCRIPTION', 'CRITICAL FLAG', \n",
    "                                              'RECORD DATE', 'INSPECTION TYPE', 'GRADE DATE', 'Latitude', 'Longitude', 'Community Board', 'Council District', 'Census Tract', 'BIN', 'BBL', 'NTA'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f06a54be",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DBA</th>\n",
       "      <th>BORO</th>\n",
       "      <th>STREET</th>\n",
       "      <th>ZIPCODE</th>\n",
       "      <th>CUISINE DESCRIPTION</th>\n",
       "      <th>SCORE</th>\n",
       "      <th>GRADE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>JOE &amp; THE JUICE</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>LEXINGTON AVENUE</td>\n",
       "      <td>10065.0</td>\n",
       "      <td>Juice, Smoothies, Fruit Salads</td>\n",
       "      <td>18.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MR LIU'S SPICY CHICKEN</td>\n",
       "      <td>Queens</td>\n",
       "      <td>ROOSEVELT AVENUE</td>\n",
       "      <td>11354.0</td>\n",
       "      <td>Asian/Asian Fusion</td>\n",
       "      <td>47.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SURYA INDIAN CUISINE</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>BLEECKER STREET</td>\n",
       "      <td>10012.0</td>\n",
       "      <td>Indian</td>\n",
       "      <td>24.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>LUCKY RESTAURANT</td>\n",
       "      <td>Queens</td>\n",
       "      <td>PARSONS BLVD</td>\n",
       "      <td>11355.0</td>\n",
       "      <td>Chinese</td>\n",
       "      <td>20.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>TENGRITAGH UYGHUR CUSINE</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>WEST   37 STREET</td>\n",
       "      <td>10018.0</td>\n",
       "      <td>Chinese</td>\n",
       "      <td>13.0</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        DBA       BORO            STREET  ZIPCODE  \\\n",
       "0           JOE & THE JUICE  Manhattan  LEXINGTON AVENUE  10065.0   \n",
       "1    MR LIU'S SPICY CHICKEN     Queens  ROOSEVELT AVENUE  11354.0   \n",
       "2      SURYA INDIAN CUISINE  Manhattan   BLEECKER STREET  10012.0   \n",
       "3          LUCKY RESTAURANT     Queens      PARSONS BLVD  11355.0   \n",
       "4  TENGRITAGH UYGHUR CUSINE  Manhattan  WEST   37 STREET  10018.0   \n",
       "\n",
       "              CUISINE DESCRIPTION  SCORE GRADE  \n",
       "0  Juice, Smoothies, Fruit Salads   18.0   NaN  \n",
       "1              Asian/Asian Fusion   47.0   NaN  \n",
       "2                          Indian   24.0   NaN  \n",
       "3                         Chinese   20.0   NaN  \n",
       "4                         Chinese   13.0     A  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check cleaned dataframe\n",
    "clean_inspection_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "b7e11860",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Change column name to match the other dataset\n",
    "clean_inspection_df.rename(columns = {'BORO':'BOROUGH'}, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "3027cf98",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Drop null values\n",
    "clean_inspection_df2 = clean_inspection_df.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "6ff96579",
   "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>DBA</th>\n",
       "      <th>BOROUGH</th>\n",
       "      <th>STREET</th>\n",
       "      <th>ZIPCODE</th>\n",
       "      <th>CUISINE DESCRIPTION</th>\n",
       "      <th>SCORE</th>\n",
       "      <th>GRADE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>TENGRITAGH UYGHUR CUSINE</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>WEST   37 STREET</td>\n",
       "      <td>10018.0</td>\n",
       "      <td>Chinese</td>\n",
       "      <td>13.0</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>KORILLA</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>METROTECH CTR</td>\n",
       "      <td>11201.0</td>\n",
       "      <td>Korean</td>\n",
       "      <td>9.0</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>FANTASY BAR AND RESTAURANT</td>\n",
       "      <td>Bronx</td>\n",
       "      <td>EAST TREMONT AVENUE</td>\n",
       "      <td>10453.0</td>\n",
       "      <td>Spanish</td>\n",
       "      <td>11.0</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>INTERNATIONAL CATERERS</td>\n",
       "      <td>Bronx</td>\n",
       "      <td>AMPERE AVENUE</td>\n",
       "      <td>10465.0</td>\n",
       "      <td>American</td>\n",
       "      <td>11.0</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>FRESH CITY DELI</td>\n",
       "      <td>Bronx</td>\n",
       "      <td>HUNTS POINT AVENUE</td>\n",
       "      <td>10459.0</td>\n",
       "      <td>American</td>\n",
       "      <td>65.0</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           DBA    BOROUGH               STREET  ZIPCODE  \\\n",
       "4     TENGRITAGH UYGHUR CUSINE  Manhattan     WEST   37 STREET  10018.0   \n",
       "5                      KORILLA   Brooklyn        METROTECH CTR  11201.0   \n",
       "7   FANTASY BAR AND RESTAURANT      Bronx  EAST TREMONT AVENUE  10453.0   \n",
       "9       INTERNATIONAL CATERERS      Bronx        AMPERE AVENUE  10465.0   \n",
       "14             FRESH CITY DELI      Bronx   HUNTS POINT AVENUE  10459.0   \n",
       "\n",
       "   CUISINE DESCRIPTION  SCORE GRADE  \n",
       "4              Chinese   13.0     A  \n",
       "5               Korean    9.0     A  \n",
       "7              Spanish   11.0     A  \n",
       "9             American   11.0     A  \n",
       "14            American   65.0     N  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check new df with no null values\n",
    "clean_inspection_df2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "32b8b4e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DBA                    0\n",
       "BOROUGH                0\n",
       "STREET                 0\n",
       "ZIPCODE                0\n",
       "CUISINE DESCRIPTION    0\n",
       "SCORE                  0\n",
       "GRADE                  0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check if we dropped all null values\n",
    "clean_inspection_df2.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "2120126e",
   "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>DBA</th>\n",
       "      <th>BOROUGH</th>\n",
       "      <th>STREET</th>\n",
       "      <th>ZIPCODE</th>\n",
       "      <th>CUISINE DESCRIPTION</th>\n",
       "      <th>SCORE</th>\n",
       "      <th>GRADE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>JOE &amp; THE JUICE</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>LEXINGTON AVENUE</td>\n",
       "      <td>10065</td>\n",
       "      <td>Juice, Smoothies, Fruit Salads</td>\n",
       "      <td>18.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MR LIU'S SPICY CHICKEN</td>\n",
       "      <td>Queens</td>\n",
       "      <td>ROOSEVELT AVENUE</td>\n",
       "      <td>11354</td>\n",
       "      <td>Asian/Asian Fusion</td>\n",
       "      <td>47.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SURYA INDIAN CUISINE</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>BLEECKER STREET</td>\n",
       "      <td>10012</td>\n",
       "      <td>Indian</td>\n",
       "      <td>24.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>LUCKY RESTAURANT</td>\n",
       "      <td>Queens</td>\n",
       "      <td>PARSONS BLVD</td>\n",
       "      <td>11355</td>\n",
       "      <td>Chinese</td>\n",
       "      <td>20.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>TENGRITAGH UYGHUR CUSINE</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>WEST   37 STREET</td>\n",
       "      <td>10018</td>\n",
       "      <td>Chinese</td>\n",
       "      <td>13.0</td>\n",
       "      <td>A</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>297943</th>\n",
       "      <td>SILVER STAR CR</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>18 AVENUE</td>\n",
       "      <td>11204</td>\n",
       "      <td>Chinese</td>\n",
       "      <td>28.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>297944</th>\n",
       "      <td>CALEXICO</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>2 AVENUE</td>\n",
       "      <td>10075</td>\n",
       "      <td>Mexican</td>\n",
       "      <td>11.0</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>297945</th>\n",
       "      <td>NIKKO HIBACHI STEAKHOUSE &amp; LOUNGE</td>\n",
       "      <td>Queens</td>\n",
       "      <td>UNION TPKE</td>\n",
       "      <td>nan</td>\n",
       "      <td>Japanese</td>\n",
       "      <td>19.0</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>297946</th>\n",
       "      <td>HAPPY WOK</td>\n",
       "      <td>Queens</td>\n",
       "      <td>BEACH CHANNEL DR</td>\n",
       "      <td>11692</td>\n",
       "      <td>Chinese</td>\n",
       "      <td>13.0</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>297947</th>\n",
       "      <td>CROWN FRIED CHICKEN</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>MARCUS GARVEY BOULEVARD</td>\n",
       "      <td>11221</td>\n",
       "      <td>Chicken</td>\n",
       "      <td>4.0</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>297948 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      DBA    BOROUGH                   STREET  \\\n",
       "0                         JOE & THE JUICE  Manhattan         LEXINGTON AVENUE   \n",
       "1                  MR LIU'S SPICY CHICKEN     Queens         ROOSEVELT AVENUE   \n",
       "2                    SURYA INDIAN CUISINE  Manhattan          BLEECKER STREET   \n",
       "3                        LUCKY RESTAURANT     Queens             PARSONS BLVD   \n",
       "4                TENGRITAGH UYGHUR CUSINE  Manhattan         WEST   37 STREET   \n",
       "...                                   ...        ...                      ...   \n",
       "297943                     SILVER STAR CR   Brooklyn                18 AVENUE   \n",
       "297944                           CALEXICO  Manhattan                 2 AVENUE   \n",
       "297945  NIKKO HIBACHI STEAKHOUSE & LOUNGE     Queens               UNION TPKE   \n",
       "297946                          HAPPY WOK     Queens         BEACH CHANNEL DR   \n",
       "297947                CROWN FRIED CHICKEN   Brooklyn  MARCUS GARVEY BOULEVARD   \n",
       "\n",
       "       ZIPCODE             CUISINE DESCRIPTION  SCORE GRADE  \n",
       "0        10065  Juice, Smoothies, Fruit Salads   18.0   NaN  \n",
       "1        11354              Asian/Asian Fusion   47.0   NaN  \n",
       "2        10012                          Indian   24.0   NaN  \n",
       "3        11355                         Chinese   20.0   NaN  \n",
       "4        10018                         Chinese   13.0     A  \n",
       "...        ...                             ...    ...   ...  \n",
       "297943   11204                         Chinese   28.0   NaN  \n",
       "297944   10075                         Mexican   11.0     A  \n",
       "297945     nan                        Japanese   19.0     B  \n",
       "297946   11692                         Chinese   13.0     A  \n",
       "297947   11221                         Chicken    4.0     A  \n",
       "\n",
       "[297948 rows x 7 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remove decimal point from ZIPCODE\n",
    "clean_inspection_df['ZIPCODE'] = clean_inspection_df['ZIPCODE'].astype(str).apply(lambda x: x.replace('.0',''))\n",
    "\n",
    "clean_inspection_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fbcc6c3c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "a54b30fb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Drop columns\n",
    "clean_income_df = nyc_income_df.drop(['Unnamed: 0', 'New York', 'income_num_returns(households)', \n",
    "                                      'avg income per return(x1000s)'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "53f64894",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Rename to all capital for consistent column names\n",
    "clean_income_df.rename(columns = {'income level':'INCOME LEVEL'}, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "8c9afd65",
   "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>Borough</th>\n",
       "      <th>INCOME LEVEL</th>\n",
       "      <th>DBA</th>\n",
       "      <th>STREET</th>\n",
       "      <th>GRADE DATE</th>\n",
       "      <th>LATITUDE</th>\n",
       "      <th>LONGITUDE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>high income</td>\n",
       "      <td>MARIACHI'S RESTAURANT</td>\n",
       "      <td>CHAMBERS STREET</td>\n",
       "      <td>1/13/2020</td>\n",
       "      <td>40.716432</td>\n",
       "      <td>-74.010472</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>high income</td>\n",
       "      <td>SPOTIFY - BARISTA BAR</td>\n",
       "      <td>GREENWICH STREET</td>\n",
       "      <td>1/22/2020</td>\n",
       "      <td>40.715553</td>\n",
       "      <td>-74.011021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>high income</td>\n",
       "      <td>STARBUCKS COFFEE COMPANY #29854</td>\n",
       "      <td>GREENWICH STREET</td>\n",
       "      <td>1/13/2020</td>\n",
       "      <td>40.715553</td>\n",
       "      <td>-74.011021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>high income</td>\n",
       "      <td>CANTEEN</td>\n",
       "      <td>WORLD TRADE CTR</td>\n",
       "      <td>1/23/2020</td>\n",
       "      <td>40.713941</td>\n",
       "      <td>-74.007401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>high income</td>\n",
       "      <td>JOE &amp; THE JUICE GREENWICH ST</td>\n",
       "      <td>GREENWICH STREET</td>\n",
       "      <td>12/30/2019</td>\n",
       "      <td>40.715553</td>\n",
       "      <td>-74.011021</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Borough INCOME LEVEL                              DBA            STREET  \\\n",
       "0  Manhattan  high income            MARIACHI'S RESTAURANT   CHAMBERS STREET   \n",
       "1  Manhattan  high income            SPOTIFY - BARISTA BAR  GREENWICH STREET   \n",
       "2  Manhattan  high income  STARBUCKS COFFEE COMPANY #29854  GREENWICH STREET   \n",
       "3  Manhattan  high income                          CANTEEN   WORLD TRADE CTR   \n",
       "4  Manhattan  high income     JOE & THE JUICE GREENWICH ST  GREENWICH STREET   \n",
       "\n",
       "   GRADE DATE   LATITUDE  LONGITUDE  \n",
       "0   1/13/2020  40.716432 -74.010472  \n",
       "1   1/22/2020  40.715553 -74.011021  \n",
       "2   1/13/2020  40.715553 -74.011021  \n",
       "3   1/23/2020  40.713941 -74.007401  \n",
       "4  12/30/2019  40.715553 -74.011021  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check cleaned up df\n",
    "clean_income_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "717aa8ca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Borough         0\n",
       "INCOME LEVEL    0\n",
       "DBA             0\n",
       "STREET          0\n",
       "GRADE DATE      0\n",
       "LATITUDE        0\n",
       "LONGITUDE       0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check for null values\n",
    "clean_income_df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "8f6950e3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Exporting df as new CSV file\n",
    "clean_inspection_df2.to_csv('Resources/clean_inspection_df2.csv', index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "3718fea8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Exporting df as new CSV file\n",
    "clean_income_df.to_csv('Resources/clean_income_df.csv', index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "a9ea483c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Drop columns for the purpose of joining cleanly on postgress\n",
    "clean_income_df2 = clean_income_df.drop(['Borough', 'GRADE DATE', 'LATITUDE', 'LONGITUDE'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "2d2f9f7e",
   "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>INCOME LEVEL</th>\n",
       "      <th>DBA</th>\n",
       "      <th>STREET</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>high income</td>\n",
       "      <td>MARIACHI'S RESTAURANT</td>\n",
       "      <td>CHAMBERS STREET</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>high income</td>\n",
       "      <td>SPOTIFY - BARISTA BAR</td>\n",
       "      <td>GREENWICH STREET</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>high income</td>\n",
       "      <td>STARBUCKS COFFEE COMPANY #29854</td>\n",
       "      <td>GREENWICH STREET</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>high income</td>\n",
       "      <td>CANTEEN</td>\n",
       "      <td>WORLD TRADE CTR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>high income</td>\n",
       "      <td>JOE &amp; THE JUICE GREENWICH ST</td>\n",
       "      <td>GREENWICH STREET</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  INCOME LEVEL                              DBA            STREET\n",
       "0  high income            MARIACHI'S RESTAURANT   CHAMBERS STREET\n",
       "1  high income            SPOTIFY - BARISTA BAR  GREENWICH STREET\n",
       "2  high income  STARBUCKS COFFEE COMPANY #29854  GREENWICH STREET\n",
       "3  high income                          CANTEEN   WORLD TRADE CTR\n",
       "4  high income     JOE & THE JUICE GREENWICH ST  GREENWICH STREET"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clean_income_df2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "ea3e8cae",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Exporting df as new CSV file\n",
    "clean_income_df2.to_csv('Resources/clean_income_df2.csv', index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "f9381801",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DBA</th>\n",
       "      <th>Borough</th>\n",
       "      <th>STREET</th>\n",
       "      <th>CUISINE DESCRIPTION</th>\n",
       "      <th>SCORE</th>\n",
       "      <th>GRADE</th>\n",
       "      <th>GRADE DATE</th>\n",
       "      <th>INCOME LEVEL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HENRI'S BACKYARD</td>\n",
       "      <td>BROOKLYN</td>\n",
       "      <td>4TH AVE</td>\n",
       "      <td>American</td>\n",
       "      <td>39.0</td>\n",
       "      <td>C</td>\n",
       "      <td>06/22/2017</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RICHMOND COUNTY COUNTRY CLUB</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "      <td>TODT HILL ROAD</td>\n",
       "      <td>American</td>\n",
       "      <td>12.0</td>\n",
       "      <td>A</td>\n",
       "      <td>06/14/2017</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>TOMOE SUSHI</td>\n",
       "      <td>MANHATTAN</td>\n",
       "      <td>THOMPSON STREET</td>\n",
       "      <td>Japanese</td>\n",
       "      <td>13.0</td>\n",
       "      <td>A</td>\n",
       "      <td>10/06/2015</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CRAB SPOT RESTAURANT</td>\n",
       "      <td>BROOKLYN</td>\n",
       "      <td>UNION STREET</td>\n",
       "      <td>Seafood</td>\n",
       "      <td>12.0</td>\n",
       "      <td>A</td>\n",
       "      <td>07/28/2016</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>M NOODLE SHOP</td>\n",
       "      <td>BROOKLYN</td>\n",
       "      <td>METROPOLITAN AVENUE</td>\n",
       "      <td>Chinese</td>\n",
       "      <td>10.0</td>\n",
       "      <td>A</td>\n",
       "      <td>01/19/2017</td>\n",
       "      <td>NaN</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>95</th>\n",
       "      <td>MR TONG</td>\n",
       "      <td>BROOKLYN</td>\n",
       "      <td>FORT HAMILTON PARKWAY</td>\n",
       "      <td>Chinese</td>\n",
       "      <td>10.0</td>\n",
       "      <td>A</td>\n",
       "      <td>09/11/2014</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>ELEGANT CHINESE RESTAURANT</td>\n",
       "      <td>QUEENS</td>\n",
       "      <td>HILLSIDE AVENUE</td>\n",
       "      <td>Chinese</td>\n",
       "      <td>9.0</td>\n",
       "      <td>A</td>\n",
       "      <td>05/20/2015</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>EAST 86 CINEMAS</td>\n",
       "      <td>MANHATTAN</td>\n",
       "      <td>EAST   86 STREET</td>\n",
       "      <td>American</td>\n",
       "      <td>7.0</td>\n",
       "      <td>A</td>\n",
       "      <td>09/08/2015</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>GOLDEN KRUST CARIBBEAN BAKERY &amp; GRILL</td>\n",
       "      <td>BROOKLYN</td>\n",
       "      <td>FLATBUSH AVENUE</td>\n",
       "      <td>Caribbean</td>\n",
       "      <td>11.0</td>\n",
       "      <td>P</td>\n",
       "      <td>09/09/2016</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>VB BAKERY</td>\n",
       "      <td>QUEENS</td>\n",
       "      <td>97TH ST</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>9.0</td>\n",
       "      <td>A</td>\n",
       "      <td>05/04/2017</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      DBA        Borough  \\\n",
       "0                        HENRI'S BACKYARD       BROOKLYN   \n",
       "1            RICHMOND COUNTY COUNTRY CLUB  STATEN ISLAND   \n",
       "2                             TOMOE SUSHI      MANHATTAN   \n",
       "3                    CRAB SPOT RESTAURANT       BROOKLYN   \n",
       "4                           M NOODLE SHOP       BROOKLYN   \n",
       "..                                    ...            ...   \n",
       "95                                MR TONG       BROOKLYN   \n",
       "96             ELEGANT CHINESE RESTAURANT         QUEENS   \n",
       "97                        EAST 86 CINEMAS      MANHATTAN   \n",
       "98  GOLDEN KRUST CARIBBEAN BAKERY & GRILL       BROOKLYN   \n",
       "99                              VB BAKERY         QUEENS   \n",
       "\n",
       "                   STREET CUISINE DESCRIPTION  SCORE GRADE  GRADE DATE  \\\n",
       "0                 4TH AVE            American   39.0     C  06/22/2017   \n",
       "1          TODT HILL ROAD            American   12.0     A  06/14/2017   \n",
       "2         THOMPSON STREET            Japanese   13.0     A  10/06/2015   \n",
       "3            UNION STREET             Seafood   12.0     A  07/28/2016   \n",
       "4     METROPOLITAN AVENUE             Chinese   10.0     A  01/19/2017   \n",
       "..                    ...                 ...    ...   ...         ...   \n",
       "95  FORT HAMILTON PARKWAY             Chinese   10.0     A  09/11/2014   \n",
       "96        HILLSIDE AVENUE             Chinese    9.0     A  05/20/2015   \n",
       "97       EAST   86 STREET            American    7.0     A  09/08/2015   \n",
       "98        FLATBUSH AVENUE           Caribbean   11.0     P  09/09/2016   \n",
       "99                97TH ST              Bakery    9.0     A  05/04/2017   \n",
       "\n",
       "   INCOME LEVEL  \n",
       "0           NaN  \n",
       "1           NaN  \n",
       "2           NaN  \n",
       "3           NaN  \n",
       "4           NaN  \n",
       "..          ...  \n",
       "95          NaN  \n",
       "96          NaN  \n",
       "97          NaN  \n",
       "98          NaN  \n",
       "99          NaN  \n",
       "\n",
       "[100 rows x 8 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# See how datasets look when joined\n",
    "joined_inspection_df = pd.merge(clean_inspection_df2, clean_income_df2, how='left', on=[\"STREET\", \"DBA\"])\n",
    "joined_inspection_df.head(100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "ae05b790",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DBA</th>\n",
       "      <th>Borough</th>\n",
       "      <th>STREET</th>\n",
       "      <th>CUISINE DESCRIPTION</th>\n",
       "      <th>SCORE</th>\n",
       "      <th>GRADE</th>\n",
       "      <th>GRADE DATE</th>\n",
       "      <th>INCOME LEVEL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>208063</th>\n",
       "      <td>AMBROSE HALL</td>\n",
       "      <td>MANHATTAN</td>\n",
       "      <td>FULTON ST</td>\n",
       "      <td>Seafood</td>\n",
       "      <td>9.0</td>\n",
       "      <td>A</td>\n",
       "      <td>05/13/2015</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208064</th>\n",
       "      <td>UNTAMED SANDWICHES</td>\n",
       "      <td>MANHATTAN</td>\n",
       "      <td>W 39TH ST</td>\n",
       "      <td>American</td>\n",
       "      <td>11.0</td>\n",
       "      <td>A</td>\n",
       "      <td>06/22/2016</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208065</th>\n",
       "      <td>CANTON LOUNGE</td>\n",
       "      <td>MANHATTAN</td>\n",
       "      <td>MOTT ST</td>\n",
       "      <td>Chinese</td>\n",
       "      <td>2.0</td>\n",
       "      <td>C</td>\n",
       "      <td>12/23/2015</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208066</th>\n",
       "      <td>TORINO PIZZA</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "      <td>RICHMOND ROAD</td>\n",
       "      <td>Pizza/Italian</td>\n",
       "      <td>22.0</td>\n",
       "      <td>Z</td>\n",
       "      <td>01/19/2017</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208067</th>\n",
       "      <td>CARIBBEAN STYLE CUISINE</td>\n",
       "      <td>QUEENS</td>\n",
       "      <td>ROCKAWAY BOULEVARD</td>\n",
       "      <td>Caribbean</td>\n",
       "      <td>24.0</td>\n",
       "      <td>B</td>\n",
       "      <td>12/11/2013</td>\n",
       "      <td>NaN</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>208158</th>\n",
       "      <td>RICHNESS  RESTAURANT</td>\n",
       "      <td>BROOKLYN</td>\n",
       "      <td>RUTLAND RD</td>\n",
       "      <td>Caribbean</td>\n",
       "      <td>11.0</td>\n",
       "      <td>A</td>\n",
       "      <td>03/14/2016</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208159</th>\n",
       "      <td>DUNKIN' DONUTS</td>\n",
       "      <td>QUEENS</td>\n",
       "      <td>GRAND CENTRAL PARKWAY</td>\n",
       "      <td>Donuts</td>\n",
       "      <td>9.0</td>\n",
       "      <td>A</td>\n",
       "      <td>05/02/2017</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208160</th>\n",
       "      <td>MAGGIES PLACE</td>\n",
       "      <td>MANHATTAN</td>\n",
       "      <td>EAST   47 STREET</td>\n",
       "      <td>American</td>\n",
       "      <td>11.0</td>\n",
       "      <td>A</td>\n",
       "      <td>02/29/2016</td>\n",
       "      <td>high income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208161</th>\n",
       "      <td>RUBY FALLS NIGHTLIFE CAFE</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "      <td>PAGE AVENUE</td>\n",
       "      <td>American</td>\n",
       "      <td>12.0</td>\n",
       "      <td>A</td>\n",
       "      <td>09/19/2014</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208162</th>\n",
       "      <td>DUNKIN' DONUTS</td>\n",
       "      <td>BROOKLYN</td>\n",
       "      <td>NEPTUNE AVE</td>\n",
       "      <td>Donuts</td>\n",
       "      <td>9.0</td>\n",
       "      <td>A</td>\n",
       "      <td>11/15/2016</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                              DBA        Borough                 STREET  \\\n",
       "208063               AMBROSE HALL      MANHATTAN              FULTON ST   \n",
       "208064         UNTAMED SANDWICHES      MANHATTAN              W 39TH ST   \n",
       "208065              CANTON LOUNGE      MANHATTAN                MOTT ST   \n",
       "208066               TORINO PIZZA  STATEN ISLAND          RICHMOND ROAD   \n",
       "208067    CARIBBEAN STYLE CUISINE         QUEENS     ROCKAWAY BOULEVARD   \n",
       "...                           ...            ...                    ...   \n",
       "208158       RICHNESS  RESTAURANT       BROOKLYN             RUTLAND RD   \n",
       "208159             DUNKIN' DONUTS         QUEENS  GRAND CENTRAL PARKWAY   \n",
       "208160              MAGGIES PLACE      MANHATTAN       EAST   47 STREET   \n",
       "208161  RUBY FALLS NIGHTLIFE CAFE  STATEN ISLAND            PAGE AVENUE   \n",
       "208162             DUNKIN' DONUTS       BROOKLYN            NEPTUNE AVE   \n",
       "\n",
       "       CUISINE DESCRIPTION  SCORE GRADE  GRADE DATE INCOME LEVEL  \n",
       "208063             Seafood    9.0     A  05/13/2015          NaN  \n",
       "208064            American   11.0     A  06/22/2016          NaN  \n",
       "208065             Chinese    2.0     C  12/23/2015          NaN  \n",
       "208066       Pizza/Italian   22.0     Z  01/19/2017          NaN  \n",
       "208067           Caribbean   24.0     B  12/11/2013          NaN  \n",
       "...                    ...    ...   ...         ...          ...  \n",
       "208158           Caribbean   11.0     A  03/14/2016          NaN  \n",
       "208159              Donuts    9.0     A  05/02/2017          NaN  \n",
       "208160            American   11.0     A  02/29/2016  high income  \n",
       "208161            American   12.0     A  09/19/2014          NaN  \n",
       "208162              Donuts    9.0     A  11/15/2016          NaN  \n",
       "\n",
       "[100 rows x 8 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joined_inspection_df.tail(100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "4dc11996",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DBA</th>\n",
       "      <th>Borough</th>\n",
       "      <th>STREET</th>\n",
       "      <th>CUISINE DESCRIPTION</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>208153</th>\n",
       "      <td>SUBWAY</td>\n",
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       "      <td>Sandwiches</td>\n",
       "      <td>13.0</td>\n",
       "      <td>A</td>\n",
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       "      <th>208154</th>\n",
       "      <td>SUBWAY</td>\n",
       "      <td>MANHATTAN</td>\n",
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       "      <td>Sandwiches</td>\n",
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       "      <td>A</td>\n",
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       "      <td>high income</td>\n",
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       "    <tr>\n",
       "      <th>208155</th>\n",
       "      <td>SUBWAY</td>\n",
       "      <td>MANHATTAN</td>\n",
       "      <td>3 AVENUE</td>\n",
       "      <td>Sandwiches</td>\n",
       "      <td>13.0</td>\n",
       "      <td>A</td>\n",
       "      <td>01/16/2015</td>\n",
       "      <td>high income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208156</th>\n",
       "      <td>STARBUCKS</td>\n",
       "      <td>MANHATTAN</td>\n",
       "      <td>YORK AVENUE</td>\n",
       "      <td>CafÃ©/Coffee/Tea</td>\n",
       "      <td>9.0</td>\n",
       "      <td>A</td>\n",
       "      <td>12/01/2014</td>\n",
       "      <td>high income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208160</th>\n",
       "      <td>MAGGIES PLACE</td>\n",
       "      <td>MANHATTAN</td>\n",
       "      <td>EAST   47 STREET</td>\n",
       "      <td>American</td>\n",
       "      <td>11.0</td>\n",
       "      <td>A</td>\n",
       "      <td>02/29/2016</td>\n",
       "      <td>high income</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  DBA    Borough            STREET CUISINE DESCRIPTION  SCORE  \\\n",
       "208153         SUBWAY  MANHATTAN          3 AVENUE          Sandwiches   13.0   \n",
       "208154         SUBWAY  MANHATTAN          3 AVENUE          Sandwiches   13.0   \n",
       "208155         SUBWAY  MANHATTAN          3 AVENUE          Sandwiches   13.0   \n",
       "208156      STARBUCKS  MANHATTAN       YORK AVENUE    CafÃ©/Coffee/Tea    9.0   \n",
       "208160  MAGGIES PLACE  MANHATTAN  EAST   47 STREET            American   11.0   \n",
       "\n",
       "       GRADE  GRADE DATE INCOME LEVEL  \n",
       "208153     A  01/16/2015  high income  \n",
       "208154     A  01/16/2015  high income  \n",
       "208155     A  01/16/2015  high income  \n",
       "208156     A  12/01/2014  high income  \n",
       "208160     A  02/29/2016  high income  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joined_inspection_df2 = joined_inspection_df.dropna()\n",
    "joined_inspection_df2.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "a313f95e",
   "metadata": {},
   "outputs": [],
   "source": [
    "joined_inspection_df3 = joined_inspection_df2.drop_duplicates()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "fa221ac2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>DBA</th>\n",
       "      <th>Borough</th>\n",
       "      <th>STREET</th>\n",
       "      <th>CUISINE DESCRIPTION</th>\n",
       "      <th>SCORE</th>\n",
       "      <th>GRADE</th>\n",
       "      <th>GRADE DATE</th>\n",
       "      <th>INCOME LEVEL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>TROPICAL REVIVAL RESTAURANT &amp; CATERING</td>\n",
       "      <td>QUEENS</td>\n",
       "      <td>CLINTONVILLE ST</td>\n",
       "      <td>Caribbean</td>\n",
       "      <td>2.0</td>\n",
       "      <td>A</td>\n",
       "      <td>11/15/2016</td>\n",
       "      <td>medium income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>WOLF AND LAMB</td>\n",
       "      <td>MANHATTAN</td>\n",
       "      <td>EAST   48 STREET</td>\n",
       "      <td>Steak</td>\n",
       "      <td>12.0</td>\n",
       "      <td>A</td>\n",
       "      <td>12/16/2014</td>\n",
       "      <td>high income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>BROOK AVENUE DELI &amp; PIZZA</td>\n",
       "      <td>BRONX</td>\n",
       "      <td>BROOK AVENUE</td>\n",
       "      <td>Pizza</td>\n",
       "      <td>12.0</td>\n",
       "      <td>A</td>\n",
       "      <td>08/02/2017</td>\n",
       "      <td>low income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>PLAZA TULCINGO RESTAURANT</td>\n",
       "      <td>BRONX</td>\n",
       "      <td>EAST CLARKE PLACE</td>\n",
       "      <td>Mexican</td>\n",
       "      <td>33.0</td>\n",
       "      <td>C</td>\n",
       "      <td>09/08/2016</td>\n",
       "      <td>low income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>GOOD ENOUGH TO EAT (A.G. BISTRO)</td>\n",
       "      <td>MANHATTAN</td>\n",
       "      <td>COLUMBUS AVENUE</td>\n",
       "      <td>American</td>\n",
       "      <td>33.0</td>\n",
       "      <td>C</td>\n",
       "      <td>01/30/2015</td>\n",
       "      <td>high income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>BAREBURGER</td>\n",
       "      <td>QUEENS</td>\n",
       "      <td>VERNON BLVD</td>\n",
       "      <td>Hamburgers</td>\n",
       "      <td>10.0</td>\n",
       "      <td>A</td>\n",
       "      <td>03/25/2015</td>\n",
       "      <td>medium income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>PANCHO VILLA RESTAURANT</td>\n",
       "      <td>BRONX</td>\n",
       "      <td>JEROME AVENUE</td>\n",
       "      <td>Mexican</td>\n",
       "      <td>42.0</td>\n",
       "      <td>C</td>\n",
       "      <td>12/01/2016</td>\n",
       "      <td>low income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>GIRELLO</td>\n",
       "      <td>MANHATTAN</td>\n",
       "      <td>NORTH MOORE STREET</td>\n",
       "      <td>Italian</td>\n",
       "      <td>12.0</td>\n",
       "      <td>A</td>\n",
       "      <td>03/04/2015</td>\n",
       "      <td>high income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>DOCKS RESTAURANT</td>\n",
       "      <td>MANHATTAN</td>\n",
       "      <td>3 AVENUE</td>\n",
       "      <td>Seafood</td>\n",
       "      <td>9.0</td>\n",
       "      <td>A</td>\n",
       "      <td>09/02/2014</td>\n",
       "      <td>high income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>CAFE CORTADITO</td>\n",
       "      <td>MANHATTAN</td>\n",
       "      <td>EAST    3 STREET</td>\n",
       "      <td>Latin (Cuban, Dominican, Puerto Rican, South &amp;...</td>\n",
       "      <td>11.0</td>\n",
       "      <td>A</td>\n",
       "      <td>09/29/2015</td>\n",
       "      <td>medium income</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        DBA    Borough              STREET  \\\n",
       "10   TROPICAL REVIVAL RESTAURANT & CATERING     QUEENS     CLINTONVILLE ST   \n",
       "15                            WOLF AND LAMB  MANHATTAN    EAST   48 STREET   \n",
       "24                BROOK AVENUE DELI & PIZZA      BRONX        BROOK AVENUE   \n",
       "32                PLAZA TULCINGO RESTAURANT      BRONX   EAST CLARKE PLACE   \n",
       "49         GOOD ENOUGH TO EAT (A.G. BISTRO)  MANHATTAN     COLUMBUS AVENUE   \n",
       "76                               BAREBURGER     QUEENS         VERNON BLVD   \n",
       "78                  PANCHO VILLA RESTAURANT      BRONX       JEROME AVENUE   \n",
       "102                                 GIRELLO  MANHATTAN  NORTH MOORE STREET   \n",
       "108                        DOCKS RESTAURANT  MANHATTAN            3 AVENUE   \n",
       "123                          CAFE CORTADITO  MANHATTAN    EAST    3 STREET   \n",
       "\n",
       "                                   CUISINE DESCRIPTION  SCORE GRADE  \\\n",
       "10                                           Caribbean    2.0     A   \n",
       "15                                               Steak   12.0     A   \n",
       "24                                               Pizza   12.0     A   \n",
       "32                                             Mexican   33.0     C   \n",
       "49                                            American   33.0     C   \n",
       "76                                          Hamburgers   10.0     A   \n",
       "78                                             Mexican   42.0     C   \n",
       "102                                            Italian   12.0     A   \n",
       "108                                            Seafood    9.0     A   \n",
       "123  Latin (Cuban, Dominican, Puerto Rican, South &...   11.0     A   \n",
       "\n",
       "     GRADE DATE   INCOME LEVEL  \n",
       "10   11/15/2016  medium income  \n",
       "15   12/16/2014    high income  \n",
       "24   08/02/2017     low income  \n",
       "32   09/08/2016     low income  \n",
       "49   01/30/2015    high income  \n",
       "76   03/25/2015  medium income  \n",
       "78   12/01/2016     low income  \n",
       "102  03/04/2015    high income  \n",
       "108  09/02/2014    high income  \n",
       "123  09/29/2015  medium income  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joined_inspection_df3.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "b411f720",
   "metadata": {},
   "outputs": [],
   "source": [
    "joined_inspection_df3.to_csv('Resources/joined_inspection_df3.csv', index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f00c62a3",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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