teabook/data-wrangling.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "broadband-staff",
   "metadata": {},
   "source": [
    "# Obsessed with Boba? Analyzing Bubble Tea Shops in NYC Using the Yelp Fusion API\n",
    "Data Wrangling: Retrieving Bubble Tea Shops in NYC Using Yelp Fusion API"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "behind-apple",
   "metadata": {},
   "source": [
    "In this notebook, we use the Yelp Fusion API to read in data about Bubble Tea Shops in NYC. Additionally, we preview the data, examine the number of rows and columns, and clip only shops that are within NYC's five boroughs. This output data will be the data we use throughout the project."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "casual-harvey",
   "metadata": {},
   "source": [
    "# Importing libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6fd94ed8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# importing libraries\n",
    "import os\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import geopandas as gpd\n",
    "import matplotlib.pyplot as plt\n",
    "import requests\n",
    "# from decouple import AutoConfig"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "democratic-poker",
   "metadata": {},
   "source": [
    "# Retrieving data from Yelp API"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0389b753",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "initial offset number: 0\n",
      "current offset number: 50\n",
      "current offset number: 100\n",
      "current offset number: 150\n",
      "current offset number: 200\n",
      "current offset number: 250\n",
      "current offset number: 300\n",
      "current offset number: 350\n",
      "current offset number: 400\n",
      "current offset number: 450\n",
      "current offset number: 500\n",
      "current offset number: 550\n",
      "current offset number: 600\n",
      "current offset number: 650\n",
      "current offset number: 700\n",
      "current offset number: 750\n",
      "current offset number: 800\n",
      "current offset number: 850\n",
      "current offset number: 900\n",
      "current offset number: 950\n",
      "current offset number: 1000\n",
      "\n",
      "query includes 554 rows and 16 columns.\n",
      "row id is unique: False.\n",
      "\n",
      "duplicates found: ['CoCo Fresh Tea & Juice'].\n",
      "dropping duplicates...\n",
      "\n",
      "row id is unique: True.\n",
      "query includes 553 rows and 16 columns.\n"
     ]
    }
   ],
   "source": [
    "'''API only returns 1,000 results and 50 per request \n",
    "   we use the offset parameter to page through to the next 50 \n",
    "   source: https://www.yelp.com/developers/faq'''\n",
    "\n",
    "# saving yelp api key as an environment variable\n",
    "API_KEY = os.environ.get('yelp_api')\n",
    "if API_KEY is None:\n",
    "    config = AutoConfig(search_path = '.')\n",
    "    API_KEY = config('YELP_API')\n",
    "\n",
    "# empty list to place our data for each page\n",
    "lst = []\n",
    "\n",
    "# our offset parameter - each page 50 rows\n",
    "offset = 0\n",
    "print('initial offset number: {}'.format(offset))\n",
    "\n",
    "# loop through the api 20 times (limit is 1000 rows with each page includes 50 rows)\n",
    "for i in range(20):\n",
    "    \n",
    "    try:\n",
    "        headers = {'Authorization': 'Bearer {}'.format(API_KEY)}\n",
    "        search_api_url = 'https://api.yelp.com/v3/businesses/search'\n",
    "        params = {'term': 'bubble tea', \n",
    "                  'categories': 'bubbletea, boba',\n",
    "                  'location': 'New York City',\n",
    "                  'offset': offset,\n",
    "                  'limit': 50}\n",
    "\n",
    "        response = requests.get(search_api_url, \n",
    "                                headers=headers, \n",
    "                                params=params, \n",
    "                                timeout=10)\n",
    "\n",
    "        # return a dictionary\n",
    "        data_dict = response.json()\n",
    "        \n",
    "        # convert the business dictionary to a pandas dataframe and append to list\n",
    "        data = pd.DataFrame(data_dict['businesses'])\n",
    "        lst.append(data)\n",
    "      \n",
    "        # add 50 to the offset to access a new page\n",
    "        offset += 50\n",
    "        print('current offset number: {}'.format(offset))\n",
    "        \n",
    "    except Exception as ex:\n",
    "        print('exception: {}\\nexit loop.'.format(ex))\n",
    "        break\n",
    "\n",
    "# concatenate all pages to one dataframe and reset index\n",
    "df = pd.concat(lst)\n",
    "df = df.reset_index(drop=True)\n",
    "\n",
    "# review shape of dataframe\n",
    "rows, columns = df.shape\n",
    "print()\n",
    "print('query includes {:,} rows and {} columns.'.format(rows, columns))\n",
    "print('row id is unique: {}.'.format(df['id'].is_unique))\n",
    "\n",
    "# review if dataframe id is unique, if not drop duplicates\n",
    "if df['id'].is_unique == False:\n",
    "    duplicates = df.loc[df.duplicated(subset=['id'])]\n",
    "    vals = list(duplicates.head()['name'].values)\n",
    "    print('\\nduplicates found: {}.'.format(vals))\n",
    "    \n",
    "    df = df.drop_duplicates(subset=['id']).reset_index(drop=True)\n",
    "    print('dropping duplicates...')\n",
    "    \n",
    "    rows, columns = df.shape\n",
    "    print('\\nrow id is unique: {}.'.format(df['id'].is_unique))\n",
    "    print('query includes {:,} rows and {} columns.'.format(rows, columns))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "stretch-policy",
   "metadata": {},
   "source": [
    "# Inspect data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "fossil-smooth",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>alias</th>\n",
       "      <th>name</th>\n",
       "      <th>image_url</th>\n",
       "      <th>is_closed</th>\n",
       "      <th>url</th>\n",
       "      <th>review_count</th>\n",
       "      <th>categories</th>\n",
       "      <th>rating</th>\n",
       "      <th>coordinates</th>\n",
       "      <th>transactions</th>\n",
       "      <th>location</th>\n",
       "      <th>phone</th>\n",
       "      <th>display_phone</th>\n",
       "      <th>distance</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>bVJQEeRNi34-3XN_F1AZEg</td>\n",
       "      <td>xing-fu-tang-new-york</td>\n",
       "      <td>Xing Fu Tang</td>\n",
       "      <td>https://s3-media2.fl.yelpcdn.com/bphoto/cyFHFE...</td>\n",
       "      <td>False</td>\n",
       "      <td>https://www.yelp.com/biz/xing-fu-tang-new-york...</td>\n",
       "      <td>91</td>\n",
       "      <td>[{'alias': 'bubbletea', 'title': 'Bubble Tea'}]</td>\n",
       "      <td>4.5</td>\n",
       "      <td>{'latitude': 40.7288, 'longitude': -73.98775}</td>\n",
       "      <td>[pickup, delivery]</td>\n",
       "      <td>{'address1': '133 2nd Ave', 'address2': '', 'a...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>2656.450427</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3aypSFXLfkAL4dhHVFobKg</td>\n",
       "      <td>lazy-sundaes-new-york-6</td>\n",
       "      <td>Lazy Sundaes</td>\n",
       "      <td>https://s3-media3.fl.yelpcdn.com/bphoto/kEfCYC...</td>\n",
       "      <td>False</td>\n",
       "      <td>https://www.yelp.com/biz/lazy-sundaes-new-york...</td>\n",
       "      <td>32</td>\n",
       "      <td>[{'alias': 'bubbletea', 'title': 'Bubble Tea'}...</td>\n",
       "      <td>4.5</td>\n",
       "      <td>{'latitude': 40.720597, 'longitude': -73.984539}</td>\n",
       "      <td>[pickup, delivery]</td>\n",
       "      <td>{'address1': '23 Clinton St', 'address2': None...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>1877.016204</td>\n",
       "      <td>$$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Q3fmTHT7zilDWtfzLK9lMA</td>\n",
       "      <td>truedan-new-york-3</td>\n",
       "      <td>Truedan</td>\n",
       "      <td>https://s3-media2.fl.yelpcdn.com/bphoto/BmUZXO...</td>\n",
       "      <td>False</td>\n",
       "      <td>https://www.yelp.com/biz/truedan-new-york-3?ad...</td>\n",
       "      <td>99</td>\n",
       "      <td>[{'alias': 'bubbletea', 'title': 'Bubble Tea'}]</td>\n",
       "      <td>4.5</td>\n",
       "      <td>{'latitude': 40.7191742, 'longitude': -73.9962...</td>\n",
       "      <td>[pickup, delivery]</td>\n",
       "      <td>{'address1': '208 Grand St', 'address2': None,...</td>\n",
       "      <td>+16465592886</td>\n",
       "      <td>(646) 559-2886</td>\n",
       "      <td>1535.241614</td>\n",
       "      <td>$$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>nndSS7va9wFlBYzA3zv1nw</td>\n",
       "      <td>ojbk-tea-shop-brooklyn-2</td>\n",
       "      <td>OJBK Tea Shop</td>\n",
       "      <td>https://s3-media1.fl.yelpcdn.com/bphoto/TOjiM7...</td>\n",
       "      <td>False</td>\n",
       "      <td>https://www.yelp.com/biz/ojbk-tea-shop-brookly...</td>\n",
       "      <td>26</td>\n",
       "      <td>[{'alias': 'bubbletea', 'title': 'Bubble Tea'}]</td>\n",
       "      <td>4.5</td>\n",
       "      <td>{'latitude': 40.69395, 'longitude': -73.96369}</td>\n",
       "      <td>[pickup, delivery]</td>\n",
       "      <td>{'address1': '525 Myrtle Ave', 'address2': '',...</td>\n",
       "      <td>+17185763047</td>\n",
       "      <td>(718) 576-3047</td>\n",
       "      <td>2879.927001</td>\n",
       "      <td>$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FKjAriOhhGZJSlkqrk8zWg</td>\n",
       "      <td>i-milky-沐白-new-york-3</td>\n",
       "      <td>I’Milky 沐白</td>\n",
       "      <td>https://s3-media4.fl.yelpcdn.com/bphoto/D04UPg...</td>\n",
       "      <td>False</td>\n",
       "      <td>https://www.yelp.com/biz/i-milky-%E6%B2%90%E7%...</td>\n",
       "      <td>260</td>\n",
       "      <td>[{'alias': 'bubbletea', 'title': 'Bubble Tea'}...</td>\n",
       "      <td>4.5</td>\n",
       "      <td>{'latitude': 40.7513413, 'longitude': -73.9864...</td>\n",
       "      <td>[pickup, delivery]</td>\n",
       "      <td>{'address1': '992 6th Ave', 'address2': '', 'a...</td>\n",
       "      <td>+12122396712</td>\n",
       "      <td>(212) 239-6712</td>\n",
       "      <td>5160.340089</td>\n",
       "      <td>$</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       id                     alias           name  \\\n",
       "0  bVJQEeRNi34-3XN_F1AZEg     xing-fu-tang-new-york   Xing Fu Tang   \n",
       "1  3aypSFXLfkAL4dhHVFobKg   lazy-sundaes-new-york-6   Lazy Sundaes   \n",
       "2  Q3fmTHT7zilDWtfzLK9lMA        truedan-new-york-3        Truedan   \n",
       "3  nndSS7va9wFlBYzA3zv1nw  ojbk-tea-shop-brooklyn-2  OJBK Tea Shop   \n",
       "4  FKjAriOhhGZJSlkqrk8zWg     i-milky-沐白-new-york-3     I’Milky 沐白   \n",
       "\n",
       "                                           image_url  is_closed  \\\n",
       "0  https://s3-media2.fl.yelpcdn.com/bphoto/cyFHFE...      False   \n",
       "1  https://s3-media3.fl.yelpcdn.com/bphoto/kEfCYC...      False   \n",
       "2  https://s3-media2.fl.yelpcdn.com/bphoto/BmUZXO...      False   \n",
       "3  https://s3-media1.fl.yelpcdn.com/bphoto/TOjiM7...      False   \n",
       "4  https://s3-media4.fl.yelpcdn.com/bphoto/D04UPg...      False   \n",
       "\n",
       "                                                 url  review_count  \\\n",
       "0  https://www.yelp.com/biz/xing-fu-tang-new-york...            91   \n",
       "1  https://www.yelp.com/biz/lazy-sundaes-new-york...            32   \n",
       "2  https://www.yelp.com/biz/truedan-new-york-3?ad...            99   \n",
       "3  https://www.yelp.com/biz/ojbk-tea-shop-brookly...            26   \n",
       "4  https://www.yelp.com/biz/i-milky-%E6%B2%90%E7%...           260   \n",
       "\n",
       "                                          categories  rating  \\\n",
       "0    [{'alias': 'bubbletea', 'title': 'Bubble Tea'}]     4.5   \n",
       "1  [{'alias': 'bubbletea', 'title': 'Bubble Tea'}...     4.5   \n",
       "2    [{'alias': 'bubbletea', 'title': 'Bubble Tea'}]     4.5   \n",
       "3    [{'alias': 'bubbletea', 'title': 'Bubble Tea'}]     4.5   \n",
       "4  [{'alias': 'bubbletea', 'title': 'Bubble Tea'}...     4.5   \n",
       "\n",
       "                                         coordinates        transactions  \\\n",
       "0      {'latitude': 40.7288, 'longitude': -73.98775}  [pickup, delivery]   \n",
       "1   {'latitude': 40.720597, 'longitude': -73.984539}  [pickup, delivery]   \n",
       "2  {'latitude': 40.7191742, 'longitude': -73.9962...  [pickup, delivery]   \n",
       "3     {'latitude': 40.69395, 'longitude': -73.96369}  [pickup, delivery]   \n",
       "4  {'latitude': 40.7513413, 'longitude': -73.9864...  [pickup, delivery]   \n",
       "\n",
       "                                            location         phone  \\\n",
       "0  {'address1': '133 2nd Ave', 'address2': '', 'a...                 \n",
       "1  {'address1': '23 Clinton St', 'address2': None...                 \n",
       "2  {'address1': '208 Grand St', 'address2': None,...  +16465592886   \n",
       "3  {'address1': '525 Myrtle Ave', 'address2': '',...  +17185763047   \n",
       "4  {'address1': '992 6th Ave', 'address2': '', 'a...  +12122396712   \n",
       "\n",
       "    display_phone     distance price  \n",
       "0                  2656.450427   NaN  \n",
       "1                  1877.016204    $$  \n",
       "2  (646) 559-2886  1535.241614    $$  \n",
       "3  (718) 576-3047  2879.927001     $  \n",
       "4  (212) 239-6712  5160.340089     $  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# preview first five rows\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8ab37863",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "      <th>alias</th>\n",
       "      <th>name</th>\n",
       "      <th>image_url</th>\n",
       "      <th>is_closed</th>\n",
       "      <th>url</th>\n",
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       "      <th>rating</th>\n",
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       "      <th>548</th>\n",
       "      <td>QBebLBqhiuDlWasPgp6s4Q</td>\n",
       "      <td>tbaar-flushing-5</td>\n",
       "      <td>Tbaar</td>\n",
       "      <td>https://s3-media1.fl.yelpcdn.com/bphoto/bgao-b...</td>\n",
       "      <td>False</td>\n",
       "      <td>https://www.yelp.com/biz/tbaar-flushing-5?adju...</td>\n",
       "      <td>2</td>\n",
       "      <td>[{'alias': 'bubbletea', 'title': 'Bubble Tea'}]</td>\n",
       "      <td>3.5</td>\n",
       "      <td>{'latitude': 40.759357, 'longitude': -73.830396}</td>\n",
       "      <td>[pickup, delivery]</td>\n",
       "      <td>{'address1': '135-52 Roosevelt Ave', 'address2...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
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       "      <th>549</th>\n",
       "      <td>7apqk24GsFC9dptoD5dDZg</td>\n",
       "      <td>uncleman-cafe-new-york</td>\n",
       "      <td>Uncleman Cafe</td>\n",
       "      <td></td>\n",
       "      <td>False</td>\n",
       "      <td>https://www.yelp.com/biz/uncleman-cafe-new-yor...</td>\n",
       "      <td>1</td>\n",
       "      <td>[{'alias': 'desserts', 'title': 'Desserts'}, {...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>{'latitude': 40.71781, 'longitude': -73.99795}</td>\n",
       "      <td>[]</td>\n",
       "      <td>{'address1': '122 Mulberry St', 'address2': No...</td>\n",
       "      <td>+12129666206</td>\n",
       "      <td>(212) 966-6206</td>\n",
       "      <td>1414.238245</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>550</th>\n",
       "      <td>Vz6hbICqQfyMWq9wzAKakw</td>\n",
       "      <td>tbaar-flushing-4</td>\n",
       "      <td>TBaar</td>\n",
       "      <td>https://s3-media1.fl.yelpcdn.com/bphoto/phUYWa...</td>\n",
       "      <td>False</td>\n",
       "      <td>https://www.yelp.com/biz/tbaar-flushing-4?adju...</td>\n",
       "      <td>6</td>\n",
       "      <td>[{'alias': 'bubbletea', 'title': 'Bubble Tea'}...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>{'latitude': 40.7613116, 'longitude': -73.8308...</td>\n",
       "      <td>[]</td>\n",
       "      <td>{'address1': '37-11 Main St', 'address2': '', ...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>15147.410738</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551</th>\n",
       "      <td>YBgAPbviWYtVP2gAUhc7_A</td>\n",
       "      <td>t-baar-flushing</td>\n",
       "      <td>T Baar</td>\n",
       "      <td>https://s3-media4.fl.yelpcdn.com/bphoto/8pk-_Q...</td>\n",
       "      <td>False</td>\n",
       "      <td>https://www.yelp.com/biz/t-baar-flushing?adjus...</td>\n",
       "      <td>8</td>\n",
       "      <td>[{'alias': 'bubbletea', 'title': 'Bubble Tea'}]</td>\n",
       "      <td>3.5</td>\n",
       "      <td>{'latitude': 40.7587509, 'longitude': -73.830162}</td>\n",
       "      <td>[]</td>\n",
       "      <td>{'address1': '135-36 40th Rd', 'address2': '',...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>15045.970192</td>\n",
       "      <td>$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>552</th>\n",
       "      <td>f5UVQXvDpOrrIZdCjsw47w</td>\n",
       "      <td>maxins-cafe-flushing</td>\n",
       "      <td>Maxin's Cafe</td>\n",
       "      <td>https://s3-media1.fl.yelpcdn.com/bphoto/S3vWvD...</td>\n",
       "      <td>False</td>\n",
       "      <td>https://www.yelp.com/biz/maxins-cafe-flushing?...</td>\n",
       "      <td>15</td>\n",
       "      <td>[{'alias': 'bakeries', 'title': 'Bakeries'}, {...</td>\n",
       "      <td>3.5</td>\n",
       "      <td>{'latitude': 40.7585, 'longitude': -73.83064}</td>\n",
       "      <td>[]</td>\n",
       "      <td>{'address1': '135-24 40th Rd', 'address2': '',...</td>\n",
       "      <td>+17188869200</td>\n",
       "      <td>(718) 886-9200</td>\n",
       "      <td>14997.842205</td>\n",
       "      <td>$</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         id                   alias           name  \\\n",
       "548  QBebLBqhiuDlWasPgp6s4Q        tbaar-flushing-5          Tbaar   \n",
       "549  7apqk24GsFC9dptoD5dDZg  uncleman-cafe-new-york  Uncleman Cafe   \n",
       "550  Vz6hbICqQfyMWq9wzAKakw        tbaar-flushing-4          TBaar   \n",
       "551  YBgAPbviWYtVP2gAUhc7_A         t-baar-flushing         T Baar   \n",
       "552  f5UVQXvDpOrrIZdCjsw47w    maxins-cafe-flushing   Maxin's Cafe   \n",
       "\n",
       "                                             image_url  is_closed  \\\n",
       "548  https://s3-media1.fl.yelpcdn.com/bphoto/bgao-b...      False   \n",
       "549                                                         False   \n",
       "550  https://s3-media1.fl.yelpcdn.com/bphoto/phUYWa...      False   \n",
       "551  https://s3-media4.fl.yelpcdn.com/bphoto/8pk-_Q...      False   \n",
       "552  https://s3-media1.fl.yelpcdn.com/bphoto/S3vWvD...      False   \n",
       "\n",
       "                                                   url  review_count  \\\n",
       "548  https://www.yelp.com/biz/tbaar-flushing-5?adju...             2   \n",
       "549  https://www.yelp.com/biz/uncleman-cafe-new-yor...             1   \n",
       "550  https://www.yelp.com/biz/tbaar-flushing-4?adju...             6   \n",
       "551  https://www.yelp.com/biz/t-baar-flushing?adjus...             8   \n",
       "552  https://www.yelp.com/biz/maxins-cafe-flushing?...            15   \n",
       "\n",
       "                                            categories  rating  \\\n",
       "548    [{'alias': 'bubbletea', 'title': 'Bubble Tea'}]     3.5   \n",
       "549  [{'alias': 'desserts', 'title': 'Desserts'}, {...     1.0   \n",
       "550  [{'alias': 'bubbletea', 'title': 'Bubble Tea'}...     4.0   \n",
       "551    [{'alias': 'bubbletea', 'title': 'Bubble Tea'}]     3.5   \n",
       "552  [{'alias': 'bakeries', 'title': 'Bakeries'}, {...     3.5   \n",
       "\n",
       "                                           coordinates        transactions  \\\n",
       "548   {'latitude': 40.759357, 'longitude': -73.830396}  [pickup, delivery]   \n",
       "549     {'latitude': 40.71781, 'longitude': -73.99795}                  []   \n",
       "550  {'latitude': 40.7613116, 'longitude': -73.8308...                  []   \n",
       "551  {'latitude': 40.7587509, 'longitude': -73.830162}                  []   \n",
       "552      {'latitude': 40.7585, 'longitude': -73.83064}                  []   \n",
       "\n",
       "                                              location         phone  \\\n",
       "548  {'address1': '135-52 Roosevelt Ave', 'address2...                 \n",
       "549  {'address1': '122 Mulberry St', 'address2': No...  +12129666206   \n",
       "550  {'address1': '37-11 Main St', 'address2': '', ...                 \n",
       "551  {'address1': '135-36 40th Rd', 'address2': '',...                 \n",
       "552  {'address1': '135-24 40th Rd', 'address2': '',...  +17188869200   \n",
       "\n",
       "      display_phone      distance price  \n",
       "548                  15054.917573   NaN  \n",
       "549  (212) 966-6206   1414.238245   NaN  \n",
       "550                  15147.410738   NaN  \n",
       "551                  15045.970192     $  \n",
       "552  (718) 886-9200  14997.842205     $  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# preview last five rows\n",
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "magnetic-accent",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 553 entries, 0 to 552\n",
      "Data columns (total 16 columns):\n",
      " #   Column         Non-Null Count  Dtype  \n",
      "---  ------         --------------  -----  \n",
      " 0   id             553 non-null    object \n",
      " 1   alias          553 non-null    object \n",
      " 2   name           553 non-null    object \n",
      " 3   image_url      553 non-null    object \n",
      " 4   is_closed      553 non-null    bool   \n",
      " 5   url            553 non-null    object \n",
      " 6   review_count   553 non-null    int64  \n",
      " 7   categories     553 non-null    object \n",
      " 8   rating         553 non-null    float64\n",
      " 9   coordinates    553 non-null    object \n",
      " 10  transactions   553 non-null    object \n",
      " 11  location       553 non-null    object \n",
      " 12  phone          553 non-null    object \n",
      " 13  display_phone  553 non-null    object \n",
      " 14  distance       553 non-null    float64\n",
      " 15  price          334 non-null    object \n",
      "dtypes: bool(1), float64(2), int64(1), object(12)\n",
      "memory usage: 65.5+ KB\n"
     ]
    }
   ],
   "source": [
    "# preview column datatypes and non-null counts\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "4a1a2b8e",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Gong Cha                  37\n",
       "Kung Fu Tea               34\n",
       "ViVi Bubble Tea           20\n",
       "Möge Tee                  10\n",
       "CoCo Fresh Tea & Juice     8\n",
       "                          ..\n",
       "Brew Memories              1\n",
       "Dragon Bing                1\n",
       "Hug a Mug Coffee & Tea     1\n",
       "Yummy Boba Desserts        1\n",
       "Zai's Dessertery           1\n",
       "Name: name, Length: 368, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# return count of unique values of bubble tea shops\n",
    "df['name'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d37534c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Gong Cha                       37\n",
       "Kung Fu Tea                    34\n",
       "ViVi Bubble Tea                20\n",
       "Möge Tee                       10\n",
       "CoCo Fresh Tea & Juice          8\n",
       "Vivi Bubble Tea                 6\n",
       "Coco Fresh Tea & Juice          6\n",
       "Tiger Sugar                     5\n",
       "Real Fruit Bubble Tea           5\n",
       "Meet Fresh                      4\n",
       "Banhmigos                       4\n",
       "Chun Yang Tea                   4\n",
       "Hawa Smoothies & Bubble Tea     4\n",
       "TBaar                           4\n",
       "Hanco's                         3\n",
       "Yi Fang Taiwan Fruit Tea        3\n",
       "Lazy Sundaes                    3\n",
       "Mi Tea                          3\n",
       "Tbaar                           3\n",
       "Waffle & Bubble                 3\n",
       "Name: name, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# return top 20 count of unique values of bubble tea shops\n",
    "df['name'].value_counts().head(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "broken-suite",
   "metadata": {},
   "source": [
    "# Inspect categories"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "upset-telescope",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      [{'alias': 'bubbletea', 'title': 'Bubble Tea'}]\n",
       "1    [{'alias': 'bubbletea', 'title': 'Bubble Tea'}...\n",
       "2      [{'alias': 'bubbletea', 'title': 'Bubble Tea'}]\n",
       "3      [{'alias': 'bubbletea', 'title': 'Bubble Tea'}]\n",
       "4    [{'alias': 'bubbletea', 'title': 'Bubble Tea'}...\n",
       "Name: categories, dtype: object"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['categories'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "dimensional-dietary",
   "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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "      <td>{'alias': 'desserts', 'title': 'Desserts'}</td>\n",
       "      <td>{'alias': 'shavedice', 'title': 'Shaved Ice'}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "      <td>{'alias': 'taiwanese', 'title': 'Taiwanese'}</td>\n",
       "      <td>{'alias': 'juicebars', 'title': 'Juice Bars &amp; ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>548</th>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>549</th>\n",
       "      <td>{'alias': 'desserts', 'title': 'Desserts'}</td>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "      <td>{'alias': 'cafes', 'title': 'Cafes'}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>550</th>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "      <td>{'alias': 'juicebars', 'title': 'Juice Bars &amp; ...</td>\n",
       "      <td>{'alias': 'coffee', 'title': 'Coffee &amp; Tea'}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551</th>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>552</th>\n",
       "      <td>{'alias': 'bakeries', 'title': 'Bakeries'}</td>\n",
       "      <td>{'alias': 'chinese', 'title': 'Chinese'}</td>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>553 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 0  \\\n",
       "0    {'alias': 'bubbletea', 'title': 'Bubble Tea'}   \n",
       "1    {'alias': 'bubbletea', 'title': 'Bubble Tea'}   \n",
       "2    {'alias': 'bubbletea', 'title': 'Bubble Tea'}   \n",
       "3    {'alias': 'bubbletea', 'title': 'Bubble Tea'}   \n",
       "4    {'alias': 'bubbletea', 'title': 'Bubble Tea'}   \n",
       "..                                             ...   \n",
       "548  {'alias': 'bubbletea', 'title': 'Bubble Tea'}   \n",
       "549     {'alias': 'desserts', 'title': 'Desserts'}   \n",
       "550  {'alias': 'bubbletea', 'title': 'Bubble Tea'}   \n",
       "551  {'alias': 'bubbletea', 'title': 'Bubble Tea'}   \n",
       "552     {'alias': 'bakeries', 'title': 'Bakeries'}   \n",
       "\n",
       "                                                     1  \\\n",
       "0                                                  NaN   \n",
       "1           {'alias': 'desserts', 'title': 'Desserts'}   \n",
       "2                                                  NaN   \n",
       "3                                                  NaN   \n",
       "4         {'alias': 'taiwanese', 'title': 'Taiwanese'}   \n",
       "..                                                 ...   \n",
       "548                                                NaN   \n",
       "549      {'alias': 'bubbletea', 'title': 'Bubble Tea'}   \n",
       "550  {'alias': 'juicebars', 'title': 'Juice Bars & ...   \n",
       "551                                                NaN   \n",
       "552           {'alias': 'chinese', 'title': 'Chinese'}   \n",
       "\n",
       "                                                     2  \n",
       "0                                                  NaN  \n",
       "1        {'alias': 'shavedice', 'title': 'Shaved Ice'}  \n",
       "2                                                  NaN  \n",
       "3                                                  NaN  \n",
       "4    {'alias': 'juicebars', 'title': 'Juice Bars & ...  \n",
       "..                                                 ...  \n",
       "548                                                NaN  \n",
       "549               {'alias': 'cafes', 'title': 'Cafes'}  \n",
       "550       {'alias': 'coffee', 'title': 'Coffee & Tea'}  \n",
       "551                                                NaN  \n",
       "552      {'alias': 'bubbletea', 'title': 'Bubble Tea'}  \n",
       "\n",
       "[553 rows x 3 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['categories'].apply(pd.Series)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "spectacular-liberia",
   "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>cat_1</th>\n",
       "      <th>cat_2</th>\n",
       "      <th>cat_3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "      <td>{'alias': 'desserts', 'title': 'Desserts'}</td>\n",
       "      <td>{'alias': 'shavedice', 'title': 'Shaved Ice'}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "      <td>{'alias': 'taiwanese', 'title': 'Taiwanese'}</td>\n",
       "      <td>{'alias': 'juicebars', 'title': 'Juice Bars &amp; ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>548</th>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>549</th>\n",
       "      <td>{'alias': 'desserts', 'title': 'Desserts'}</td>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "      <td>{'alias': 'cafes', 'title': 'Cafes'}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>550</th>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "      <td>{'alias': 'juicebars', 'title': 'Juice Bars &amp; ...</td>\n",
       "      <td>{'alias': 'coffee', 'title': 'Coffee &amp; Tea'}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551</th>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>552</th>\n",
       "      <td>{'alias': 'bakeries', 'title': 'Bakeries'}</td>\n",
       "      <td>{'alias': 'chinese', 'title': 'Chinese'}</td>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>553 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             cat_1  \\\n",
       "0    {'alias': 'bubbletea', 'title': 'Bubble Tea'}   \n",
       "1    {'alias': 'bubbletea', 'title': 'Bubble Tea'}   \n",
       "2    {'alias': 'bubbletea', 'title': 'Bubble Tea'}   \n",
       "3    {'alias': 'bubbletea', 'title': 'Bubble Tea'}   \n",
       "4    {'alias': 'bubbletea', 'title': 'Bubble Tea'}   \n",
       "..                                             ...   \n",
       "548  {'alias': 'bubbletea', 'title': 'Bubble Tea'}   \n",
       "549     {'alias': 'desserts', 'title': 'Desserts'}   \n",
       "550  {'alias': 'bubbletea', 'title': 'Bubble Tea'}   \n",
       "551  {'alias': 'bubbletea', 'title': 'Bubble Tea'}   \n",
       "552     {'alias': 'bakeries', 'title': 'Bakeries'}   \n",
       "\n",
       "                                                 cat_2  \\\n",
       "0                                                  NaN   \n",
       "1           {'alias': 'desserts', 'title': 'Desserts'}   \n",
       "2                                                  NaN   \n",
       "3                                                  NaN   \n",
       "4         {'alias': 'taiwanese', 'title': 'Taiwanese'}   \n",
       "..                                                 ...   \n",
       "548                                                NaN   \n",
       "549      {'alias': 'bubbletea', 'title': 'Bubble Tea'}   \n",
       "550  {'alias': 'juicebars', 'title': 'Juice Bars & ...   \n",
       "551                                                NaN   \n",
       "552           {'alias': 'chinese', 'title': 'Chinese'}   \n",
       "\n",
       "                                                 cat_3  \n",
       "0                                                  NaN  \n",
       "1        {'alias': 'shavedice', 'title': 'Shaved Ice'}  \n",
       "2                                                  NaN  \n",
       "3                                                  NaN  \n",
       "4    {'alias': 'juicebars', 'title': 'Juice Bars & ...  \n",
       "..                                                 ...  \n",
       "548                                                NaN  \n",
       "549               {'alias': 'cafes', 'title': 'Cafes'}  \n",
       "550       {'alias': 'coffee', 'title': 'Coffee & Tea'}  \n",
       "551                                                NaN  \n",
       "552      {'alias': 'bubbletea', 'title': 'Bubble Tea'}  \n",
       "\n",
       "[553 rows x 3 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "categories_df = df['categories'].apply(pd.Series)\n",
    "categories_df.columns = ['cat_1', 'cat_2', 'cat_3']\n",
    "\n",
    "categories_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "received-blade",
   "metadata": {},
   "source": [
    "# Check for duplicates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "infrared-growing",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "number of unique bubble tea shops: 368\n"
     ]
    },
    {
     "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>name</th>\n",
       "      <th>counts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Gong Cha</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Kung Fu Tea</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ViVi Bubble Tea</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Möge Tee</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CoCo Fresh Tea &amp; Juice</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>363</th>\n",
       "      <td>Brew Memories</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>364</th>\n",
       "      <td>Dragon Bing</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>365</th>\n",
       "      <td>Hug a Mug Coffee &amp; Tea</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>366</th>\n",
       "      <td>Yummy Boba Desserts</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>367</th>\n",
       "      <td>Zai's Dessertery</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>368 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       name  counts\n",
       "0                  Gong Cha      37\n",
       "1               Kung Fu Tea      34\n",
       "2           ViVi Bubble Tea      20\n",
       "3                  Möge Tee      10\n",
       "4    CoCo Fresh Tea & Juice       8\n",
       "..                      ...     ...\n",
       "363           Brew Memories       1\n",
       "364             Dragon Bing       1\n",
       "365  Hug a Mug Coffee & Tea       1\n",
       "366     Yummy Boba Desserts       1\n",
       "367        Zai's Dessertery       1\n",
       "\n",
       "[368 rows x 2 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# identify number of unique bubble tea shop entries\n",
    "names_counts = df['name'].value_counts().reset_index()\n",
    "names_counts = names_counts.rename(columns={'index':'name', 'name':'counts'})\n",
    "\n",
    "print('number of unique bubble tea shops: {}'.format(len(names_counts)))\n",
    "names_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "interior-activity",
   "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>name</th>\n",
       "      <th>counts</th>\n",
       "      <th>name_lower</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Gong Cha</td>\n",
       "      <td>37</td>\n",
       "      <td>gongcha</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Kung Fu Tea</td>\n",
       "      <td>34</td>\n",
       "      <td>kungfutea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ViVi Bubble Tea</td>\n",
       "      <td>20</td>\n",
       "      <td>vivibubbletea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Möge Tee</td>\n",
       "      <td>10</td>\n",
       "      <td>mögetee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CoCo Fresh Tea &amp; Juice</td>\n",
       "      <td>8</td>\n",
       "      <td>cocofreshtea&amp;juice</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     name  counts          name_lower\n",
       "0                Gong Cha      37             gongcha\n",
       "1             Kung Fu Tea      34           kungfutea\n",
       "2         ViVi Bubble Tea      20       vivibubbletea\n",
       "3                Möge Tee      10             mögetee\n",
       "4  CoCo Fresh Tea & Juice       8  cocofreshtea&juice"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check for duplicates - white spaces, mispellings, etc\n",
    "lst = []\n",
    "for row in range(len(names_counts)):\n",
    "    value = names_counts['name'][row].replace(' ', '').lower()\n",
    "    lst.append(value)  \n",
    "    \n",
    "names_counts = pd.concat([names_counts, pd.Series(lst).rename('name_lower')], axis=1)\n",
    "names_counts.head()    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "pending-asbestos",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "yifangtaiwanfruittea    3\n",
       "jooyteashoppe           3\n",
       "tbaar                   3\n",
       "vivibubbletea           3\n",
       "cocofreshtea&juice      2\n",
       "pokébowlstation         2\n",
       "yomie'sricexyogurt      2\n",
       "mr.wish                 2\n",
       "tigersugar              2\n",
       "corndogunion            1\n",
       "Name: name_lower, dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# there are duplicate entries\n",
    "names_counts['name_lower'].value_counts().head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "regional-reverse",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "these places have dulicate entries:\n",
      "\n",
      "yifangtaiwanfruittea\n",
      "jooyteashoppe\n",
      "tbaar\n",
      "vivibubbletea\n",
      "cocofreshtea&juice\n",
      "pokébowlstation\n",
      "yomie'sricexyogurt\n",
      "mr.wish\n",
      "tigersugar\n"
     ]
    }
   ],
   "source": [
    "# return list of duplicate entries that need to be replaced\n",
    "duplicates_ser = names_counts['name_lower'].value_counts() > 1\n",
    "duplicates = duplicates_ser.loc[duplicates_ser].index\n",
    "\n",
    "print('these places have dulicate entries:\\n')\n",
    "for dup in duplicates.to_list():\n",
    "    print(dup)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "exciting-smith",
   "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>name</th>\n",
       "      <th>counts</th>\n",
       "      <th>name_lower</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CoCo Fresh Tea &amp; Juice</td>\n",
       "      <td>8</td>\n",
       "      <td>cocofreshtea&amp;juice</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Coco Fresh Tea &amp; Juice</td>\n",
       "      <td>6</td>\n",
       "      <td>cocofreshtea&amp;juice</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>354</th>\n",
       "      <td>JOOY Tea Shoppe</td>\n",
       "      <td>1</td>\n",
       "      <td>jooyteashoppe</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>227</th>\n",
       "      <td>Jooy Tea Shoppe</td>\n",
       "      <td>1</td>\n",
       "      <td>jooyteashoppe</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>JOOY TEA SHOPPE</td>\n",
       "      <td>1</td>\n",
       "      <td>jooyteashoppe</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Mr. Wish</td>\n",
       "      <td>3</td>\n",
       "      <td>mr.wish</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>Mr.Wish</td>\n",
       "      <td>1</td>\n",
       "      <td>mr.wish</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>320</th>\n",
       "      <td>Pokébowl Station</td>\n",
       "      <td>1</td>\n",
       "      <td>pokébowlstation</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>PokéBowl Station</td>\n",
       "      <td>2</td>\n",
       "      <td>pokébowlstation</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>TBaar</td>\n",
       "      <td>4</td>\n",
       "      <td>tbaar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Tbaar</td>\n",
       "      <td>3</td>\n",
       "      <td>tbaar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>T Baar</td>\n",
       "      <td>1</td>\n",
       "      <td>tbaar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Tiger Sugar</td>\n",
       "      <td>5</td>\n",
       "      <td>tigersugar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>TIGER SUGAR</td>\n",
       "      <td>1</td>\n",
       "      <td>tigersugar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ViVi Bubble Tea</td>\n",
       "      <td>20</td>\n",
       "      <td>vivibubbletea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Vivi Bubble Tea</td>\n",
       "      <td>6</td>\n",
       "      <td>vivibubbletea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>ViVi Bubble tea</td>\n",
       "      <td>1</td>\n",
       "      <td>vivibubbletea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Yifang Taiwan Fruit Tea</td>\n",
       "      <td>3</td>\n",
       "      <td>yifangtaiwanfruittea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Yi Fang Taiwan Fruit Tea</td>\n",
       "      <td>3</td>\n",
       "      <td>yifangtaiwanfruittea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>YiFang Taiwan Fruit Tea</td>\n",
       "      <td>2</td>\n",
       "      <td>yifangtaiwanfruittea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>340</th>\n",
       "      <td>Yomie's Rice x Yogurt</td>\n",
       "      <td>1</td>\n",
       "      <td>yomie'sricexyogurt</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>328</th>\n",
       "      <td>Yomie's Rice X Yogurt</td>\n",
       "      <td>1</td>\n",
       "      <td>yomie'sricexyogurt</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         name  counts            name_lower\n",
       "4      CoCo Fresh Tea & Juice       8    cocofreshtea&juice\n",
       "6      Coco Fresh Tea & Juice       6    cocofreshtea&juice\n",
       "354           JOOY Tea Shoppe       1         jooyteashoppe\n",
       "227           Jooy Tea Shoppe       1         jooyteashoppe\n",
       "99            JOOY TEA SHOPPE       1         jooyteashoppe\n",
       "21                   Mr. Wish       3               mr.wish\n",
       "64                    Mr.Wish       1               mr.wish\n",
       "320          Pokébowl Station       1       pokébowlstation\n",
       "49           PokéBowl Station       2       pokébowlstation\n",
       "13                      TBaar       4                 tbaar\n",
       "18                      Tbaar       3                 tbaar\n",
       "130                    T Baar       1                 tbaar\n",
       "7                 Tiger Sugar       5            tigersugar\n",
       "81                TIGER SUGAR       1            tigersugar\n",
       "2             ViVi Bubble Tea      20         vivibubbletea\n",
       "5             Vivi Bubble Tea       6         vivibubbletea\n",
       "97            ViVi Bubble tea       1         vivibubbletea\n",
       "24    Yifang Taiwan Fruit Tea       3  yifangtaiwanfruittea\n",
       "15   Yi Fang Taiwan Fruit Tea       3  yifangtaiwanfruittea\n",
       "29    YiFang Taiwan Fruit Tea       2  yifangtaiwanfruittea\n",
       "340     Yomie's Rice x Yogurt       1    yomie'sricexyogurt\n",
       "328     Yomie's Rice X Yogurt       1    yomie'sricexyogurt"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "names_counts = (names_counts.loc[names_counts['name_lower'].isin(duplicates.to_list())]\n",
    "                .sort_values(by='name_lower'))\n",
    "\n",
    "names_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "south-nickel",
   "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>name</th>\n",
       "      <th>counts</th>\n",
       "      <th>name_lower</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CoCo Fresh Tea &amp; Juice</td>\n",
       "      <td>8</td>\n",
       "      <td>CoCo Fresh Tea &amp; Juice</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Coco Fresh Tea &amp; Juice</td>\n",
       "      <td>6</td>\n",
       "      <td>CoCo Fresh Tea &amp; Juice</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>354</th>\n",
       "      <td>JOOY Tea Shoppe</td>\n",
       "      <td>1</td>\n",
       "      <td>JOOY Tea Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>227</th>\n",
       "      <td>Jooy Tea Shoppe</td>\n",
       "      <td>1</td>\n",
       "      <td>JOOY Tea Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>JOOY TEA SHOPPE</td>\n",
       "      <td>1</td>\n",
       "      <td>JOOY Tea Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Mr. Wish</td>\n",
       "      <td>3</td>\n",
       "      <td>mr.wish</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>Mr.Wish</td>\n",
       "      <td>1</td>\n",
       "      <td>mr.wish</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>320</th>\n",
       "      <td>Pokébowl Station</td>\n",
       "      <td>1</td>\n",
       "      <td>PokéBowl Station</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>PokéBowl Station</td>\n",
       "      <td>2</td>\n",
       "      <td>PokéBowl Station</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>TBaar</td>\n",
       "      <td>4</td>\n",
       "      <td>TBaar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Tbaar</td>\n",
       "      <td>3</td>\n",
       "      <td>TBaar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>T Baar</td>\n",
       "      <td>1</td>\n",
       "      <td>TBaar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Tiger Sugar</td>\n",
       "      <td>5</td>\n",
       "      <td>tigersugar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>TIGER SUGAR</td>\n",
       "      <td>1</td>\n",
       "      <td>tigersugar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ViVi Bubble Tea</td>\n",
       "      <td>20</td>\n",
       "      <td>Vivi Bubble Tea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Vivi Bubble Tea</td>\n",
       "      <td>6</td>\n",
       "      <td>Vivi Bubble Tea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>ViVi Bubble tea</td>\n",
       "      <td>1</td>\n",
       "      <td>Vivi Bubble Tea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Yifang Taiwan Fruit Tea</td>\n",
       "      <td>3</td>\n",
       "      <td>Yi Fang Taiwan Fruit Tea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Yi Fang Taiwan Fruit Tea</td>\n",
       "      <td>3</td>\n",
       "      <td>Yi Fang Taiwan Fruit Tea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>YiFang Taiwan Fruit Tea</td>\n",
       "      <td>2</td>\n",
       "      <td>Yi Fang Taiwan Fruit Tea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>340</th>\n",
       "      <td>Yomie's Rice x Yogurt</td>\n",
       "      <td>1</td>\n",
       "      <td>Yomie's Rice X Yogurt</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>328</th>\n",
       "      <td>Yomie's Rice X Yogurt</td>\n",
       "      <td>1</td>\n",
       "      <td>Yomie's Rice X Yogurt</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         name  counts                name_lower\n",
       "4      CoCo Fresh Tea & Juice       8    CoCo Fresh Tea & Juice\n",
       "6      Coco Fresh Tea & Juice       6    CoCo Fresh Tea & Juice\n",
       "354           JOOY Tea Shoppe       1             JOOY Tea Shop\n",
       "227           Jooy Tea Shoppe       1             JOOY Tea Shop\n",
       "99            JOOY TEA SHOPPE       1             JOOY Tea Shop\n",
       "21                   Mr. Wish       3                   mr.wish\n",
       "64                    Mr.Wish       1                   mr.wish\n",
       "320          Pokébowl Station       1          PokéBowl Station\n",
       "49           PokéBowl Station       2          PokéBowl Station\n",
       "13                      TBaar       4                     TBaar\n",
       "18                      Tbaar       3                     TBaar\n",
       "130                    T Baar       1                     TBaar\n",
       "7                 Tiger Sugar       5                tigersugar\n",
       "81                TIGER SUGAR       1                tigersugar\n",
       "2             ViVi Bubble Tea      20           Vivi Bubble Tea\n",
       "5             Vivi Bubble Tea       6           Vivi Bubble Tea\n",
       "97            ViVi Bubble tea       1           Vivi Bubble Tea\n",
       "24    Yifang Taiwan Fruit Tea       3  Yi Fang Taiwan Fruit Tea\n",
       "15   Yi Fang Taiwan Fruit Tea       3  Yi Fang Taiwan Fruit Tea\n",
       "29    YiFang Taiwan Fruit Tea       2  Yi Fang Taiwan Fruit Tea\n",
       "340     Yomie's Rice x Yogurt       1     Yomie's Rice X Yogurt\n",
       "328     Yomie's Rice X Yogurt       1     Yomie's Rice X Yogurt"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# a dictionary of formatted names (lower & remove white spice) and new names to be returned\n",
    "new_names = {'yifangtaiwanfruittea':'Yi Fang Taiwan Fruit Tea',\n",
    "             'vivibubbletea':'Vivi Bubble Tea',\n",
    "             'jooyteashoppe':'JOOY Tea Shop',\n",
    "             'tbaar':'TBaar',\n",
    "             'cocofreshtea&juice':'CoCo Fresh Tea & Juice',\n",
    "             \"yomie'sricexyogurt\":\"Yomie's Rice X Yogurt\",\n",
    "             'pokébowlstation':'PokéBowl Station'}\n",
    "\n",
    "names_counts['name_lower'] = names_counts['name_lower'].replace(new_names)\n",
    "\n",
    "names_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "diverse-bleeding",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'CoCo Fresh Tea & Juice': 'CoCo Fresh Tea & Juice',\n",
       " 'Coco Fresh Tea & Juice': 'CoCo Fresh Tea & Juice',\n",
       " 'JOOY Tea Shoppe': 'JOOY Tea Shop',\n",
       " 'Jooy Tea Shoppe': 'JOOY Tea Shop',\n",
       " 'JOOY TEA SHOPPE': 'JOOY Tea Shop',\n",
       " 'Mr. Wish': 'mr.wish',\n",
       " 'Mr.Wish': 'mr.wish',\n",
       " 'Pokébowl Station': 'PokéBowl Station',\n",
       " 'PokéBowl Station': 'PokéBowl Station',\n",
       " 'TBaar': 'TBaar',\n",
       " 'Tbaar': 'TBaar',\n",
       " 'T Baar': 'TBaar',\n",
       " 'Tiger Sugar': 'tigersugar',\n",
       " 'TIGER SUGAR': 'tigersugar',\n",
       " 'ViVi Bubble Tea': 'Vivi Bubble Tea',\n",
       " 'Vivi Bubble Tea': 'Vivi Bubble Tea',\n",
       " 'ViVi Bubble tea': 'Vivi Bubble Tea',\n",
       " 'Yifang Taiwan Fruit Tea': 'Yi Fang Taiwan Fruit Tea',\n",
       " 'Yi Fang Taiwan Fruit Tea': 'Yi Fang Taiwan Fruit Tea',\n",
       " 'YiFang Taiwan Fruit Tea': 'Yi Fang Taiwan Fruit Tea',\n",
       " \"Yomie's Rice x Yogurt\": \"Yomie's Rice X Yogurt\",\n",
       " \"Yomie's Rice X Yogurt\": \"Yomie's Rice X Yogurt\"}"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# a dictionary of old and new names to be returned\n",
    "replace_duplicates = dict(zip(names_counts['name'], names_counts['name_lower']))\n",
    "\n",
    "replace_duplicates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "surprising-contributor",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
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       "        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>id</th>\n",
       "      <th>alias</th>\n",
       "      <th>name</th>\n",
       "      <th>image_url</th>\n",
       "      <th>is_closed</th>\n",
       "      <th>url</th>\n",
       "      <th>review_count</th>\n",
       "      <th>categories</th>\n",
       "      <th>rating</th>\n",
       "      <th>coordinates</th>\n",
       "      <th>transactions</th>\n",
       "      <th>location</th>\n",
       "      <th>phone</th>\n",
       "      <th>display_phone</th>\n",
       "      <th>distance</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>bVJQEeRNi34-3XN_F1AZEg</td>\n",
       "      <td>xing-fu-tang-new-york</td>\n",
       "      <td>Xing Fu Tang</td>\n",
       "      <td>https://s3-media2.fl.yelpcdn.com/bphoto/cyFHFE...</td>\n",
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       "      <td>https://www.yelp.com/biz/xing-fu-tang-new-york...</td>\n",
       "      <td>91</td>\n",
       "      <td>[{'alias': 'bubbletea', 'title': 'Bubble Tea'}]</td>\n",
       "      <td>4.5</td>\n",
       "      <td>{'latitude': 40.7288, 'longitude': -73.98775}</td>\n",
       "      <td>[pickup, delivery]</td>\n",
       "      <td>{'address1': '133 2nd Ave', 'address2': '', 'a...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>2656.450427</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3aypSFXLfkAL4dhHVFobKg</td>\n",
       "      <td>lazy-sundaes-new-york-6</td>\n",
       "      <td>Lazy Sundaes</td>\n",
       "      <td>https://s3-media3.fl.yelpcdn.com/bphoto/kEfCYC...</td>\n",
       "      <td>False</td>\n",
       "      <td>https://www.yelp.com/biz/lazy-sundaes-new-york...</td>\n",
       "      <td>32</td>\n",
       "      <td>[{'alias': 'bubbletea', 'title': 'Bubble Tea'}...</td>\n",
       "      <td>4.5</td>\n",
       "      <td>{'latitude': 40.720597, 'longitude': -73.984539}</td>\n",
       "      <td>[pickup, delivery]</td>\n",
       "      <td>{'address1': '23 Clinton St', 'address2': None...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>1877.016204</td>\n",
       "      <td>$$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Q3fmTHT7zilDWtfzLK9lMA</td>\n",
       "      <td>truedan-new-york-3</td>\n",
       "      <td>Truedan</td>\n",
       "      <td>https://s3-media2.fl.yelpcdn.com/bphoto/BmUZXO...</td>\n",
       "      <td>False</td>\n",
       "      <td>https://www.yelp.com/biz/truedan-new-york-3?ad...</td>\n",
       "      <td>99</td>\n",
       "      <td>[{'alias': 'bubbletea', 'title': 'Bubble Tea'}]</td>\n",
       "      <td>4.5</td>\n",
       "      <td>{'latitude': 40.7191742, 'longitude': -73.9962...</td>\n",
       "      <td>[pickup, delivery]</td>\n",
       "      <td>{'address1': '208 Grand St', 'address2': None,...</td>\n",
       "      <td>+16465592886</td>\n",
       "      <td>(646) 559-2886</td>\n",
       "      <td>1535.241614</td>\n",
       "      <td>$$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>nndSS7va9wFlBYzA3zv1nw</td>\n",
       "      <td>ojbk-tea-shop-brooklyn-2</td>\n",
       "      <td>OJBK Tea Shop</td>\n",
       "      <td>https://s3-media1.fl.yelpcdn.com/bphoto/TOjiM7...</td>\n",
       "      <td>False</td>\n",
       "      <td>https://www.yelp.com/biz/ojbk-tea-shop-brookly...</td>\n",
       "      <td>26</td>\n",
       "      <td>[{'alias': 'bubbletea', 'title': 'Bubble Tea'}]</td>\n",
       "      <td>4.5</td>\n",
       "      <td>{'latitude': 40.69395, 'longitude': -73.96369}</td>\n",
       "      <td>[pickup, delivery]</td>\n",
       "      <td>{'address1': '525 Myrtle Ave', 'address2': '',...</td>\n",
       "      <td>+17185763047</td>\n",
       "      <td>(718) 576-3047</td>\n",
       "      <td>2879.927001</td>\n",
       "      <td>$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FKjAriOhhGZJSlkqrk8zWg</td>\n",
       "      <td>i-milky-沐白-new-york-3</td>\n",
       "      <td>I’Milky 沐白</td>\n",
       "      <td>https://s3-media4.fl.yelpcdn.com/bphoto/D04UPg...</td>\n",
       "      <td>False</td>\n",
       "      <td>https://www.yelp.com/biz/i-milky-%E6%B2%90%E7%...</td>\n",
       "      <td>260</td>\n",
       "      <td>[{'alias': 'bubbletea', 'title': 'Bubble Tea'}...</td>\n",
       "      <td>4.5</td>\n",
       "      <td>{'latitude': 40.7513413, 'longitude': -73.9864...</td>\n",
       "      <td>[pickup, delivery]</td>\n",
       "      <td>{'address1': '992 6th Ave', 'address2': '', 'a...</td>\n",
       "      <td>+12122396712</td>\n",
       "      <td>(212) 239-6712</td>\n",
       "      <td>5160.340089</td>\n",
       "      <td>$</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       id                     alias           name  \\\n",
       "0  bVJQEeRNi34-3XN_F1AZEg     xing-fu-tang-new-york   Xing Fu Tang   \n",
       "1  3aypSFXLfkAL4dhHVFobKg   lazy-sundaes-new-york-6   Lazy Sundaes   \n",
       "2  Q3fmTHT7zilDWtfzLK9lMA        truedan-new-york-3        Truedan   \n",
       "3  nndSS7va9wFlBYzA3zv1nw  ojbk-tea-shop-brooklyn-2  OJBK Tea Shop   \n",
       "4  FKjAriOhhGZJSlkqrk8zWg     i-milky-沐白-new-york-3     I’Milky 沐白   \n",
       "\n",
       "                                           image_url  is_closed  \\\n",
       "0  https://s3-media2.fl.yelpcdn.com/bphoto/cyFHFE...      False   \n",
       "1  https://s3-media3.fl.yelpcdn.com/bphoto/kEfCYC...      False   \n",
       "2  https://s3-media2.fl.yelpcdn.com/bphoto/BmUZXO...      False   \n",
       "3  https://s3-media1.fl.yelpcdn.com/bphoto/TOjiM7...      False   \n",
       "4  https://s3-media4.fl.yelpcdn.com/bphoto/D04UPg...      False   \n",
       "\n",
       "                                                 url  review_count  \\\n",
       "0  https://www.yelp.com/biz/xing-fu-tang-new-york...            91   \n",
       "1  https://www.yelp.com/biz/lazy-sundaes-new-york...            32   \n",
       "2  https://www.yelp.com/biz/truedan-new-york-3?ad...            99   \n",
       "3  https://www.yelp.com/biz/ojbk-tea-shop-brookly...            26   \n",
       "4  https://www.yelp.com/biz/i-milky-%E6%B2%90%E7%...           260   \n",
       "\n",
       "                                          categories  rating  \\\n",
       "0    [{'alias': 'bubbletea', 'title': 'Bubble Tea'}]     4.5   \n",
       "1  [{'alias': 'bubbletea', 'title': 'Bubble Tea'}...     4.5   \n",
       "2    [{'alias': 'bubbletea', 'title': 'Bubble Tea'}]     4.5   \n",
       "3    [{'alias': 'bubbletea', 'title': 'Bubble Tea'}]     4.5   \n",
       "4  [{'alias': 'bubbletea', 'title': 'Bubble Tea'}...     4.5   \n",
       "\n",
       "                                         coordinates        transactions  \\\n",
       "0      {'latitude': 40.7288, 'longitude': -73.98775}  [pickup, delivery]   \n",
       "1   {'latitude': 40.720597, 'longitude': -73.984539}  [pickup, delivery]   \n",
       "2  {'latitude': 40.7191742, 'longitude': -73.9962...  [pickup, delivery]   \n",
       "3     {'latitude': 40.69395, 'longitude': -73.96369}  [pickup, delivery]   \n",
       "4  {'latitude': 40.7513413, 'longitude': -73.9864...  [pickup, delivery]   \n",
       "\n",
       "                                            location         phone  \\\n",
       "0  {'address1': '133 2nd Ave', 'address2': '', 'a...                 \n",
       "1  {'address1': '23 Clinton St', 'address2': None...                 \n",
       "2  {'address1': '208 Grand St', 'address2': None,...  +16465592886   \n",
       "3  {'address1': '525 Myrtle Ave', 'address2': '',...  +17185763047   \n",
       "4  {'address1': '992 6th Ave', 'address2': '', 'a...  +12122396712   \n",
       "\n",
       "    display_phone     distance price  \n",
       "0                  2656.450427   NaN  \n",
       "1                  1877.016204    $$  \n",
       "2  (646) 559-2886  1535.241614    $$  \n",
       "3  (718) 576-3047  2879.927001     $  \n",
       "4  (212) 239-6712  5160.340089     $  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# replace old and new names to original dataframe\n",
    "df['name'] = df['name'].replace(replace_duplicates)\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "foster-vampire",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Gong Cha                       37\n",
       "Kung Fu Tea                    34\n",
       "Vivi Bubble Tea                27\n",
       "CoCo Fresh Tea & Juice         14\n",
       "Möge Tee                       10\n",
       "TBaar                           8\n",
       "Yi Fang Taiwan Fruit Tea        8\n",
       "tigersugar                      6\n",
       "Real Fruit Bubble Tea           5\n",
       "Banhmigos                       4\n",
       "Meet Fresh                      4\n",
       "mr.wish                         4\n",
       "Chun Yang Tea                   4\n",
       "Hawa Smoothies & Bubble Tea     4\n",
       "Waffle & Bubble                 3\n",
       "Lazy Sundaes                    3\n",
       "Mi Tea                          3\n",
       "Jupioca                         3\n",
       "Hanco's                         3\n",
       "JOOY Tea Shop                   3\n",
       "Name: name, dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['name'].value_counts().head(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dominant-copper",
   "metadata": {},
   "source": [
    "# Inspecting categories"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "educational-responsibility",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        [{'alias': 'bubbletea', 'title': 'Bubble Tea'}]\n",
       "1      [{'alias': 'bubbletea', 'title': 'Bubble Tea'}...\n",
       "2        [{'alias': 'bubbletea', 'title': 'Bubble Tea'}]\n",
       "3        [{'alias': 'bubbletea', 'title': 'Bubble Tea'}]\n",
       "4      [{'alias': 'bubbletea', 'title': 'Bubble Tea'}...\n",
       "                             ...                        \n",
       "548      [{'alias': 'bubbletea', 'title': 'Bubble Tea'}]\n",
       "549    [{'alias': 'desserts', 'title': 'Desserts'}, {...\n",
       "550    [{'alias': 'bubbletea', 'title': 'Bubble Tea'}...\n",
       "551      [{'alias': 'bubbletea', 'title': 'Bubble Tea'}]\n",
       "552    [{'alias': 'bakeries', 'title': 'Bakeries'}, {...\n",
       "Name: categories, Length: 553, dtype: object"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['categories']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "indonesian-moderator",
   "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>0</th>\n",
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       "      <th>2</th>\n",
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       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "      <td>{'alias': 'desserts', 'title': 'Desserts'}</td>\n",
       "      <td>{'alias': 'shavedice', 'title': 'Shaved Ice'}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "      <td>{'alias': 'taiwanese', 'title': 'Taiwanese'}</td>\n",
       "      <td>{'alias': 'juicebars', 'title': 'Juice Bars &amp; ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>548</th>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>549</th>\n",
       "      <td>{'alias': 'desserts', 'title': 'Desserts'}</td>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "      <td>{'alias': 'cafes', 'title': 'Cafes'}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>550</th>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "      <td>{'alias': 'juicebars', 'title': 'Juice Bars &amp; ...</td>\n",
       "      <td>{'alias': 'coffee', 'title': 'Coffee &amp; Tea'}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551</th>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>552</th>\n",
       "      <td>{'alias': 'bakeries', 'title': 'Bakeries'}</td>\n",
       "      <td>{'alias': 'chinese', 'title': 'Chinese'}</td>\n",
       "      <td>{'alias': 'bubbletea', 'title': 'Bubble Tea'}</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>553 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 0  \\\n",
       "0    {'alias': 'bubbletea', 'title': 'Bubble Tea'}   \n",
       "1    {'alias': 'bubbletea', 'title': 'Bubble Tea'}   \n",
       "2    {'alias': 'bubbletea', 'title': 'Bubble Tea'}   \n",
       "3    {'alias': 'bubbletea', 'title': 'Bubble Tea'}   \n",
       "4    {'alias': 'bubbletea', 'title': 'Bubble Tea'}   \n",
       "..                                             ...   \n",
       "548  {'alias': 'bubbletea', 'title': 'Bubble Tea'}   \n",
       "549     {'alias': 'desserts', 'title': 'Desserts'}   \n",
       "550  {'alias': 'bubbletea', 'title': 'Bubble Tea'}   \n",
       "551  {'alias': 'bubbletea', 'title': 'Bubble Tea'}   \n",
       "552     {'alias': 'bakeries', 'title': 'Bakeries'}   \n",
       "\n",
       "                                                     1  \\\n",
       "0                                                  NaN   \n",
       "1           {'alias': 'desserts', 'title': 'Desserts'}   \n",
       "2                                                  NaN   \n",
       "3                                                  NaN   \n",
       "4         {'alias': 'taiwanese', 'title': 'Taiwanese'}   \n",
       "..                                                 ...   \n",
       "548                                                NaN   \n",
       "549      {'alias': 'bubbletea', 'title': 'Bubble Tea'}   \n",
       "550  {'alias': 'juicebars', 'title': 'Juice Bars & ...   \n",
       "551                                                NaN   \n",
       "552           {'alias': 'chinese', 'title': 'Chinese'}   \n",
       "\n",
       "                                                     2  \n",
       "0                                                  NaN  \n",
       "1        {'alias': 'shavedice', 'title': 'Shaved Ice'}  \n",
       "2                                                  NaN  \n",
       "3                                                  NaN  \n",
       "4    {'alias': 'juicebars', 'title': 'Juice Bars & ...  \n",
       "..                                                 ...  \n",
       "548                                                NaN  \n",
       "549               {'alias': 'cafes', 'title': 'Cafes'}  \n",
       "550       {'alias': 'coffee', 'title': 'Coffee & Tea'}  \n",
       "551                                                NaN  \n",
       "552      {'alias': 'bubbletea', 'title': 'Bubble Tea'}  \n",
       "\n",
       "[553 rows x 3 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['categories'].apply(pd.Series)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "favorite-tenant",
   "metadata": {},
   "source": [
    "# Clip shops within NYC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "4b8f5d72",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>alias</th>\n",
       "      <th>name</th>\n",
       "      <th>image_url</th>\n",
       "      <th>is_closed</th>\n",
       "      <th>url</th>\n",
       "      <th>review_count</th>\n",
       "      <th>categories</th>\n",
       "      <th>rating</th>\n",
       "      <th>coordinates</th>\n",
       "      <th>transactions</th>\n",
       "      <th>location</th>\n",
       "      <th>phone</th>\n",
       "      <th>display_phone</th>\n",
       "      <th>distance</th>\n",
       "      <th>price</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>bVJQEeRNi34-3XN_F1AZEg</td>\n",
       "      <td>xing-fu-tang-new-york</td>\n",
       "      <td>Xing Fu Tang</td>\n",
       "      <td>https://s3-media2.fl.yelpcdn.com/bphoto/cyFHFE...</td>\n",
       "      <td>False</td>\n",
       "      <td>https://www.yelp.com/biz/xing-fu-tang-new-york...</td>\n",
       "      <td>91</td>\n",
       "      <td>[{'alias': 'bubbletea', 'title': 'Bubble Tea'}]</td>\n",
       "      <td>4.5</td>\n",
       "      <td>{'latitude': 40.7288, 'longitude': -73.98775}</td>\n",
       "      <td>[pickup, delivery]</td>\n",
       "      <td>{'address1': '133 2nd Ave', 'address2': '', 'a...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>2656.450427</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.728800</td>\n",
       "      <td>-73.987750</td>\n",
       "      <td>POINT (-73.98775 40.72880)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3aypSFXLfkAL4dhHVFobKg</td>\n",
       "      <td>lazy-sundaes-new-york-6</td>\n",
       "      <td>Lazy Sundaes</td>\n",
       "      <td>https://s3-media3.fl.yelpcdn.com/bphoto/kEfCYC...</td>\n",
       "      <td>False</td>\n",
       "      <td>https://www.yelp.com/biz/lazy-sundaes-new-york...</td>\n",
       "      <td>32</td>\n",
       "      <td>[{'alias': 'bubbletea', 'title': 'Bubble Tea'}...</td>\n",
       "      <td>4.5</td>\n",
       "      <td>{'latitude': 40.720597, 'longitude': -73.984539}</td>\n",
       "      <td>[pickup, delivery]</td>\n",
       "      <td>{'address1': '23 Clinton St', 'address2': None...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>1877.016204</td>\n",
       "      <td>$$</td>\n",
       "      <td>40.720597</td>\n",
       "      <td>-73.984539</td>\n",
       "      <td>POINT (-73.98454 40.72060)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Q3fmTHT7zilDWtfzLK9lMA</td>\n",
       "      <td>truedan-new-york-3</td>\n",
       "      <td>Truedan</td>\n",
       "      <td>https://s3-media2.fl.yelpcdn.com/bphoto/BmUZXO...</td>\n",
       "      <td>False</td>\n",
       "      <td>https://www.yelp.com/biz/truedan-new-york-3?ad...</td>\n",
       "      <td>99</td>\n",
       "      <td>[{'alias': 'bubbletea', 'title': 'Bubble Tea'}]</td>\n",
       "      <td>4.5</td>\n",
       "      <td>{'latitude': 40.7191742, 'longitude': -73.9962...</td>\n",
       "      <td>[pickup, delivery]</td>\n",
       "      <td>{'address1': '208 Grand St', 'address2': None,...</td>\n",
       "      <td>+16465592886</td>\n",
       "      <td>(646) 559-2886</td>\n",
       "      <td>1535.241614</td>\n",
       "      <td>$$</td>\n",
       "      <td>40.719174</td>\n",
       "      <td>-73.996220</td>\n",
       "      <td>POINT (-73.99622 40.71917)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>nndSS7va9wFlBYzA3zv1nw</td>\n",
       "      <td>ojbk-tea-shop-brooklyn-2</td>\n",
       "      <td>OJBK Tea Shop</td>\n",
       "      <td>https://s3-media1.fl.yelpcdn.com/bphoto/TOjiM7...</td>\n",
       "      <td>False</td>\n",
       "      <td>https://www.yelp.com/biz/ojbk-tea-shop-brookly...</td>\n",
       "      <td>26</td>\n",
       "      <td>[{'alias': 'bubbletea', 'title': 'Bubble Tea'}]</td>\n",
       "      <td>4.5</td>\n",
       "      <td>{'latitude': 40.69395, 'longitude': -73.96369}</td>\n",
       "      <td>[pickup, delivery]</td>\n",
       "      <td>{'address1': '525 Myrtle Ave', 'address2': '',...</td>\n",
       "      <td>+17185763047</td>\n",
       "      <td>(718) 576-3047</td>\n",
       "      <td>2879.927001</td>\n",
       "      <td>$</td>\n",
       "      <td>40.693950</td>\n",
       "      <td>-73.963690</td>\n",
       "      <td>POINT (-73.96369 40.69395)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FKjAriOhhGZJSlkqrk8zWg</td>\n",
       "      <td>i-milky-沐白-new-york-3</td>\n",
       "      <td>I’Milky 沐白</td>\n",
       "      <td>https://s3-media4.fl.yelpcdn.com/bphoto/D04UPg...</td>\n",
       "      <td>False</td>\n",
       "      <td>https://www.yelp.com/biz/i-milky-%E6%B2%90%E7%...</td>\n",
       "      <td>260</td>\n",
       "      <td>[{'alias': 'bubbletea', 'title': 'Bubble Tea'}...</td>\n",
       "      <td>4.5</td>\n",
       "      <td>{'latitude': 40.7513413, 'longitude': -73.9864...</td>\n",
       "      <td>[pickup, delivery]</td>\n",
       "      <td>{'address1': '992 6th Ave', 'address2': '', 'a...</td>\n",
       "      <td>+12122396712</td>\n",
       "      <td>(212) 239-6712</td>\n",
       "      <td>5160.340089</td>\n",
       "      <td>$</td>\n",
       "      <td>40.751341</td>\n",
       "      <td>-73.986447</td>\n",
       "      <td>POINT (-73.98645 40.75134)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       id                     alias           name  \\\n",
       "0  bVJQEeRNi34-3XN_F1AZEg     xing-fu-tang-new-york   Xing Fu Tang   \n",
       "1  3aypSFXLfkAL4dhHVFobKg   lazy-sundaes-new-york-6   Lazy Sundaes   \n",
       "2  Q3fmTHT7zilDWtfzLK9lMA        truedan-new-york-3        Truedan   \n",
       "3  nndSS7va9wFlBYzA3zv1nw  ojbk-tea-shop-brooklyn-2  OJBK Tea Shop   \n",
       "4  FKjAriOhhGZJSlkqrk8zWg     i-milky-沐白-new-york-3     I’Milky 沐白   \n",
       "\n",
       "                                           image_url  is_closed  \\\n",
       "0  https://s3-media2.fl.yelpcdn.com/bphoto/cyFHFE...      False   \n",
       "1  https://s3-media3.fl.yelpcdn.com/bphoto/kEfCYC...      False   \n",
       "2  https://s3-media2.fl.yelpcdn.com/bphoto/BmUZXO...      False   \n",
       "3  https://s3-media1.fl.yelpcdn.com/bphoto/TOjiM7...      False   \n",
       "4  https://s3-media4.fl.yelpcdn.com/bphoto/D04UPg...      False   \n",
       "\n",
       "                                                 url  review_count  \\\n",
       "0  https://www.yelp.com/biz/xing-fu-tang-new-york...            91   \n",
       "1  https://www.yelp.com/biz/lazy-sundaes-new-york...            32   \n",
       "2  https://www.yelp.com/biz/truedan-new-york-3?ad...            99   \n",
       "3  https://www.yelp.com/biz/ojbk-tea-shop-brookly...            26   \n",
       "4  https://www.yelp.com/biz/i-milky-%E6%B2%90%E7%...           260   \n",
       "\n",
       "                                          categories  rating  \\\n",
       "0    [{'alias': 'bubbletea', 'title': 'Bubble Tea'}]     4.5   \n",
       "1  [{'alias': 'bubbletea', 'title': 'Bubble Tea'}...     4.5   \n",
       "2    [{'alias': 'bubbletea', 'title': 'Bubble Tea'}]     4.5   \n",
       "3    [{'alias': 'bubbletea', 'title': 'Bubble Tea'}]     4.5   \n",
       "4  [{'alias': 'bubbletea', 'title': 'Bubble Tea'}...     4.5   \n",
       "\n",
       "                                         coordinates        transactions  \\\n",
       "0      {'latitude': 40.7288, 'longitude': -73.98775}  [pickup, delivery]   \n",
       "1   {'latitude': 40.720597, 'longitude': -73.984539}  [pickup, delivery]   \n",
       "2  {'latitude': 40.7191742, 'longitude': -73.9962...  [pickup, delivery]   \n",
       "3     {'latitude': 40.69395, 'longitude': -73.96369}  [pickup, delivery]   \n",
       "4  {'latitude': 40.7513413, 'longitude': -73.9864...  [pickup, delivery]   \n",
       "\n",
       "                                            location         phone  \\\n",
       "0  {'address1': '133 2nd Ave', 'address2': '', 'a...                 \n",
       "1  {'address1': '23 Clinton St', 'address2': None...                 \n",
       "2  {'address1': '208 Grand St', 'address2': None,...  +16465592886   \n",
       "3  {'address1': '525 Myrtle Ave', 'address2': '',...  +17185763047   \n",
       "4  {'address1': '992 6th Ave', 'address2': '', 'a...  +12122396712   \n",
       "\n",
       "    display_phone     distance price   latitude  longitude  \\\n",
       "0                  2656.450427   NaN  40.728800 -73.987750   \n",
       "1                  1877.016204    $$  40.720597 -73.984539   \n",
       "2  (646) 559-2886  1535.241614    $$  40.719174 -73.996220   \n",
       "3  (718) 576-3047  2879.927001     $  40.693950 -73.963690   \n",
       "4  (212) 239-6712  5160.340089     $  40.751341 -73.986447   \n",
       "\n",
       "                     geometry  \n",
       "0  POINT (-73.98775 40.72880)  \n",
       "1  POINT (-73.98454 40.72060)  \n",
       "2  POINT (-73.99622 40.71917)  \n",
       "3  POINT (-73.96369 40.69395)  \n",
       "4  POINT (-73.98645 40.75134)  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# explode coordinates to create an individual column\n",
    "gdf = pd.concat([df, df['coordinates'].apply(pd.Series)], axis=1)\n",
    "\n",
    "# retrieve lat, lon values and return a geodataframe\n",
    "gdf = gpd.GeoDataFrame(gdf, crs=4326, \n",
    "      geometry=gpd.points_from_xy(gdf.longitude, gdf.latitude))\n",
    "\n",
    "gdf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "incoming-bidder",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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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>boro_code</th>\n",
       "      <th>boro_name</th>\n",
       "      <th>shape_area</th>\n",
       "      <th>shape_leng</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>6.366208e+08</td>\n",
       "      <td>359993.127161</td>\n",
       "      <td>MULTIPOLYGON (((-74.01093 40.68449, -74.01193 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.0</td>\n",
       "      <td>Bronx</td>\n",
       "      <td>1.187194e+09</td>\n",
       "      <td>463868.935588</td>\n",
       "      <td>MULTIPOLYGON (((-73.89681 40.79581, -73.89694 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.0</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>1.934174e+09</td>\n",
       "      <td>728195.194837</td>\n",
       "      <td>MULTIPOLYGON (((-73.86327 40.58388, -73.86381 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5.0</td>\n",
       "      <td>Staten Island</td>\n",
       "      <td>1.623631e+09</td>\n",
       "      <td>325924.002252</td>\n",
       "      <td>MULTIPOLYGON (((-74.05051 40.56642, -74.05047 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4.0</td>\n",
       "      <td>Queens</td>\n",
       "      <td>3.040206e+09</td>\n",
       "      <td>900269.281914</td>\n",
       "      <td>MULTIPOLYGON (((-73.82645 40.59053, -73.82642 ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   boro_code      boro_name    shape_area     shape_leng  \\\n",
       "0        1.0      Manhattan  6.366208e+08  359993.127161   \n",
       "1        2.0          Bronx  1.187194e+09  463868.935588   \n",
       "2        3.0       Brooklyn  1.934174e+09  728195.194837   \n",
       "3        5.0  Staten Island  1.623631e+09  325924.002252   \n",
       "4        4.0         Queens  3.040206e+09  900269.281914   \n",
       "\n",
       "                                            geometry  \n",
       "0  MULTIPOLYGON (((-74.01093 40.68449, -74.01193 ...  \n",
       "1  MULTIPOLYGON (((-73.89681 40.79581, -73.89694 ...  \n",
       "2  MULTIPOLYGON (((-73.86327 40.58388, -73.86381 ...  \n",
       "3  MULTIPOLYGON (((-74.05051 40.56642, -74.05047 ...  \n",
       "4  MULTIPOLYGON (((-73.82645 40.59053, -73.82642 ...  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# read in boroughs shapefile to return only bubble tea shops within nyc\n",
    "url = 'https://data.cityofnewyork.us/api/geospatial/tqmj-j8zm?method=export&format=Shapefile'\n",
    "boro_gdf = gpd.read_file(url)\n",
    "\n",
    "boro_gdf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "sitting-special",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot bubble tea shops and boroughs\n",
    "fig, ax = plt.subplots(figsize=(8, 8))\n",
    "\n",
    "gdf.plot(ax=ax)\n",
    "boro_gdf.plot(ax=ax, facecolor='None', edgecolor='black', zorder=0)\n",
    "\n",
    "plt.title('bubble tea shops in NYC area')\n",
    "plt.xlabel('lon')\n",
    "plt.ylabel('lat')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "unable-upgrade",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "number of rows: 414\n",
      "number of columns: 19\n"
     ]
    }
   ],
   "source": [
    "# clip bubble tea shops that are within the five boroughs\n",
    "gdf = gpd.clip(gdf, boro_gdf)\n",
    "gdf = gdf.reset_index(drop=True)\n",
    "\n",
    "rows, columns = gdf.shape\n",
    "print('number of rows: {}\\n\\\n",
    "number of columns: {}'.format(rows, columns))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "boolean-conditions",
   "metadata": {
    "scrolled": false
   },
   "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>id</th>\n",
       "      <th>alias</th>\n",
       "      <th>name</th>\n",
       "      <th>image_url</th>\n",
       "      <th>is_closed</th>\n",
       "      <th>url</th>\n",
       "      <th>review_count</th>\n",
       "      <th>categories</th>\n",
       "      <th>rating</th>\n",
       "      <th>coordinates</th>\n",
       "      <th>transactions</th>\n",
       "      <th>location</th>\n",
       "      <th>phone</th>\n",
       "      <th>display_phone</th>\n",
       "      <th>distance</th>\n",
       "      <th>price</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>bVJQEeRNi34-3XN_F1AZEg</td>\n",
       "      <td>xing-fu-tang-new-york</td>\n",
       "      <td>Xing Fu Tang</td>\n",
       "      <td>https://s3-media2.fl.yelpcdn.com/bphoto/cyFHFE...</td>\n",
       "      <td>False</td>\n",
       "      <td>https://www.yelp.com/biz/xing-fu-tang-new-york...</td>\n",
       "      <td>91</td>\n",
       "      <td>[{'alias': 'bubbletea', 'title': 'Bubble Tea'}]</td>\n",
       "      <td>4.5</td>\n",
       "      <td>{'latitude': 40.7288, 'longitude': -73.98775}</td>\n",
       "      <td>[pickup, delivery]</td>\n",
       "      <td>{'address1': '133 2nd Ave', 'address2': '', 'a...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>2656.450427</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.728800</td>\n",
       "      <td>-73.987750</td>\n",
       "      <td>POINT (-73.98775 40.72880)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3aypSFXLfkAL4dhHVFobKg</td>\n",
       "      <td>lazy-sundaes-new-york-6</td>\n",
       "      <td>Lazy Sundaes</td>\n",
       "      <td>https://s3-media3.fl.yelpcdn.com/bphoto/kEfCYC...</td>\n",
       "      <td>False</td>\n",
       "      <td>https://www.yelp.com/biz/lazy-sundaes-new-york...</td>\n",
       "      <td>32</td>\n",
       "      <td>[{'alias': 'bubbletea', 'title': 'Bubble Tea'}...</td>\n",
       "      <td>4.5</td>\n",
       "      <td>{'latitude': 40.720597, 'longitude': -73.984539}</td>\n",
       "      <td>[pickup, delivery]</td>\n",
       "      <td>{'address1': '23 Clinton St', 'address2': None...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>1877.016204</td>\n",
       "      <td>$$</td>\n",
       "      <td>40.720597</td>\n",
       "      <td>-73.984539</td>\n",
       "      <td>POINT (-73.98454 40.72060)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Q3fmTHT7zilDWtfzLK9lMA</td>\n",
       "      <td>truedan-new-york-3</td>\n",
       "      <td>Truedan</td>\n",
       "      <td>https://s3-media2.fl.yelpcdn.com/bphoto/BmUZXO...</td>\n",
       "      <td>False</td>\n",
       "      <td>https://www.yelp.com/biz/truedan-new-york-3?ad...</td>\n",
       "      <td>99</td>\n",
       "      <td>[{'alias': 'bubbletea', 'title': 'Bubble Tea'}]</td>\n",
       "      <td>4.5</td>\n",
       "      <td>{'latitude': 40.7191742, 'longitude': -73.9962...</td>\n",
       "      <td>[pickup, delivery]</td>\n",
       "      <td>{'address1': '208 Grand St', 'address2': None,...</td>\n",
       "      <td>+16465592886</td>\n",
       "      <td>(646) 559-2886</td>\n",
       "      <td>1535.241614</td>\n",
       "      <td>$$</td>\n",
       "      <td>40.719174</td>\n",
       "      <td>-73.996220</td>\n",
       "      <td>POINT (-73.99622 40.71917)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>nndSS7va9wFlBYzA3zv1nw</td>\n",
       "      <td>ojbk-tea-shop-brooklyn-2</td>\n",
       "      <td>OJBK Tea Shop</td>\n",
       "      <td>https://s3-media1.fl.yelpcdn.com/bphoto/TOjiM7...</td>\n",
       "      <td>False</td>\n",
       "      <td>https://www.yelp.com/biz/ojbk-tea-shop-brookly...</td>\n",
       "      <td>26</td>\n",
       "      <td>[{'alias': 'bubbletea', 'title': 'Bubble Tea'}]</td>\n",
       "      <td>4.5</td>\n",
       "      <td>{'latitude': 40.69395, 'longitude': -73.96369}</td>\n",
       "      <td>[pickup, delivery]</td>\n",
       "      <td>{'address1': '525 Myrtle Ave', 'address2': '',...</td>\n",
       "      <td>+17185763047</td>\n",
       "      <td>(718) 576-3047</td>\n",
       "      <td>2879.927001</td>\n",
       "      <td>$</td>\n",
       "      <td>40.693950</td>\n",
       "      <td>-73.963690</td>\n",
       "      <td>POINT (-73.96369 40.69395)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FKjAriOhhGZJSlkqrk8zWg</td>\n",
       "      <td>i-milky-沐白-new-york-3</td>\n",
       "      <td>I’Milky 沐白</td>\n",
       "      <td>https://s3-media4.fl.yelpcdn.com/bphoto/D04UPg...</td>\n",
       "      <td>False</td>\n",
       "      <td>https://www.yelp.com/biz/i-milky-%E6%B2%90%E7%...</td>\n",
       "      <td>260</td>\n",
       "      <td>[{'alias': 'bubbletea', 'title': 'Bubble Tea'}...</td>\n",
       "      <td>4.5</td>\n",
       "      <td>{'latitude': 40.7513413, 'longitude': -73.9864...</td>\n",
       "      <td>[pickup, delivery]</td>\n",
       "      <td>{'address1': '992 6th Ave', 'address2': '', 'a...</td>\n",
       "      <td>+12122396712</td>\n",
       "      <td>(212) 239-6712</td>\n",
       "      <td>5160.340089</td>\n",
       "      <td>$</td>\n",
       "      <td>40.751341</td>\n",
       "      <td>-73.986447</td>\n",
       "      <td>POINT (-73.98645 40.75134)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       id                     alias           name  \\\n",
       "0  bVJQEeRNi34-3XN_F1AZEg     xing-fu-tang-new-york   Xing Fu Tang   \n",
       "1  3aypSFXLfkAL4dhHVFobKg   lazy-sundaes-new-york-6   Lazy Sundaes   \n",
       "2  Q3fmTHT7zilDWtfzLK9lMA        truedan-new-york-3        Truedan   \n",
       "3  nndSS7va9wFlBYzA3zv1nw  ojbk-tea-shop-brooklyn-2  OJBK Tea Shop   \n",
       "4  FKjAriOhhGZJSlkqrk8zWg     i-milky-沐白-new-york-3     I’Milky 沐白   \n",
       "\n",
       "                                           image_url  is_closed  \\\n",
       "0  https://s3-media2.fl.yelpcdn.com/bphoto/cyFHFE...      False   \n",
       "1  https://s3-media3.fl.yelpcdn.com/bphoto/kEfCYC...      False   \n",
       "2  https://s3-media2.fl.yelpcdn.com/bphoto/BmUZXO...      False   \n",
       "3  https://s3-media1.fl.yelpcdn.com/bphoto/TOjiM7...      False   \n",
       "4  https://s3-media4.fl.yelpcdn.com/bphoto/D04UPg...      False   \n",
       "\n",
       "                                                 url  review_count  \\\n",
       "0  https://www.yelp.com/biz/xing-fu-tang-new-york...            91   \n",
       "1  https://www.yelp.com/biz/lazy-sundaes-new-york...            32   \n",
       "2  https://www.yelp.com/biz/truedan-new-york-3?ad...            99   \n",
       "3  https://www.yelp.com/biz/ojbk-tea-shop-brookly...            26   \n",
       "4  https://www.yelp.com/biz/i-milky-%E6%B2%90%E7%...           260   \n",
       "\n",
       "                                          categories  rating  \\\n",
       "0    [{'alias': 'bubbletea', 'title': 'Bubble Tea'}]     4.5   \n",
       "1  [{'alias': 'bubbletea', 'title': 'Bubble Tea'}...     4.5   \n",
       "2    [{'alias': 'bubbletea', 'title': 'Bubble Tea'}]     4.5   \n",
       "3    [{'alias': 'bubbletea', 'title': 'Bubble Tea'}]     4.5   \n",
       "4  [{'alias': 'bubbletea', 'title': 'Bubble Tea'}...     4.5   \n",
       "\n",
       "                                         coordinates        transactions  \\\n",
       "0      {'latitude': 40.7288, 'longitude': -73.98775}  [pickup, delivery]   \n",
       "1   {'latitude': 40.720597, 'longitude': -73.984539}  [pickup, delivery]   \n",
       "2  {'latitude': 40.7191742, 'longitude': -73.9962...  [pickup, delivery]   \n",
       "3     {'latitude': 40.69395, 'longitude': -73.96369}  [pickup, delivery]   \n",
       "4  {'latitude': 40.7513413, 'longitude': -73.9864...  [pickup, delivery]   \n",
       "\n",
       "                                            location         phone  \\\n",
       "0  {'address1': '133 2nd Ave', 'address2': '', 'a...                 \n",
       "1  {'address1': '23 Clinton St', 'address2': None...                 \n",
       "2  {'address1': '208 Grand St', 'address2': None,...  +16465592886   \n",
       "3  {'address1': '525 Myrtle Ave', 'address2': '',...  +17185763047   \n",
       "4  {'address1': '992 6th Ave', 'address2': '', 'a...  +12122396712   \n",
       "\n",
       "    display_phone     distance price   latitude  longitude  \\\n",
       "0                  2656.450427   NaN  40.728800 -73.987750   \n",
       "1                  1877.016204    $$  40.720597 -73.984539   \n",
       "2  (646) 559-2886  1535.241614    $$  40.719174 -73.996220   \n",
       "3  (718) 576-3047  2879.927001     $  40.693950 -73.963690   \n",
       "4  (212) 239-6712  5160.340089     $  40.751341 -73.986447   \n",
       "\n",
       "                     geometry  \n",
       "0  POINT (-73.98775 40.72880)  \n",
       "1  POINT (-73.98454 40.72060)  \n",
       "2  POINT (-73.99622 40.71917)  \n",
       "3  POINT (-73.96369 40.69395)  \n",
       "4  POINT (-73.98645 40.75134)  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# preview dataframe\n",
    "gdf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "enclosed-shipping",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8, 8))\n",
    "\n",
    "gdf.plot(ax=ax)\n",
    "boro_gdf.plot(ax=ax, facecolor='None', edgecolor='black', zorder=0)\n",
    "\n",
    "plt.title('bubble tea shops in NYC')\n",
    "plt.xlabel('lon')\n",
    "plt.ylabel('lat')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "f6173aa6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # save file\n",
    "# gdf.to_csv('boba-nyc.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "quick-binary",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # sanity check\n",
    "# pd.read_csv('boba-nyc.csv').head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "collaborative-wiring",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}