index.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# APIs - Cumulative Lab\n",
    "\n",
    "\n",
    "## Introduction \n",
    "\n",
    "We've seen how the Yelp API works and how to create basic visualizations using Folium. It's time to put those skills to work in order to create a working map! Taking things a step further, you'll also independently explore how to perform pagination in order to retrieve a full results set from the Yelp API.\n",
    "\n",
    "## Objectives\n",
    "\n",
    "You will be able to: \n",
    "\n",
    "* Practice using functions to organize your code\n",
    "* Use pagination to retrieve all results from an API query\n",
    "* Practice parsing data returned from an API query\n",
    "* Practice interpreting visualizations of a dataset\n",
    "* Create maps using Folium"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Your Task: Query Yelp for All Businesses in a Category and Analyze the Results\n",
    "\n",
    "![restaurant counter with pizza](images/restaurant_counter.jpg)\n",
    "\n",
    "Photo by <a href=\"https://unsplash.com/@jordanmadrid?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText\">Jordan Madrid</a> on <a href=\"/s/photos/pizza-restaurant?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText\">Unsplash</a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Overview\n",
    "\n",
    "You've now worked with some API calls, but we have yet to see how to retrieve a more complete dataset in a programmatic manner. In this lab, you will write a query of businesses on Yelp, then use *pagination* to retrieve all possible results for that query. Then you will create a summary of your findings, including a Folium map of the geographic locations of those businesses.\n",
    "\n",
    "### Technical Details\n",
    "\n",
    "Returning to the Yelp API, the [documentation](https://www.yelp.com/developers/documentation/v3/business_search) also provides us details regarding the **API limits**. These often include details about the number of requests a user is allowed to make within a specified time limit and the maximum number of results to be returned. In this case, we are told that any request has a **maximum of 50 results per request** and defaults to 20. Furthermore, any search will be limited to a **total of 1000 results**. To retrieve all 1000 of these results, we would have to page through the results piece by piece, retrieving 50 at a time. Processes such as these are often referred to as pagination.\n",
    "\n",
    "Also, be mindful of the **API** ***rate*** **limits**. You can only make **5000 requests per day** and can make requests too fast. Start prototyping small before running a loop that could be faulty. You can also use `time.sleep(n)` to add delays. For more details see https://www.yelp.com/developers/documentation/v3/rate_limiting.\n",
    "\n",
    "In this lab, you will define a search and then paginate over the results to retrieve all of the results. You'll then parse these responses as a list of dictionaries (for further exploration) and create a map using Folium to visualize the results geographically.\n",
    "\n",
    "### Requirements\n",
    "\n",
    "#### 1. Make the Initial Request\n",
    "\n",
    "Start by filling in your API key to make the initial request to the business search API. Investigate the structure of the response you get back and start figuring out how you will extract the relevant information.\n",
    "\n",
    "#### 2. Add Pagination\n",
    "\n",
    "Using loops and functions, collect the maximum number of results for your query from the API.\n",
    "\n",
    "#### 3. Perform Exploratory Analysis\n",
    "\n",
    "Interpret visualizations related to the price range, average rating, and number of reviews for all query results.\n",
    "\n",
    "#### 4. Create a Folium Map\n",
    "\n",
    "Using latitude and longitude data, plot the query results on an interactive map."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Make the Initial Request\n",
    "\n",
    "### Querying\n",
    "\n",
    "Start by making an initial request to the Yelp API. Your search must include at least 2 parameters: **term** and **location**. For example, you might search for pizza restaurants in NYC. The term and location is up to you but make the request below.\n",
    "\n",
    "Use the `requests` library ([documentation here](https://requests.readthedocs.io/en/master/user/quickstart/#make-a-request)).\n",
    "\n",
    "You'll also need an API key from Yelp. If you haven't done this already, go to the Yelp [Manage App page](https://www.yelp.com/developers/v3/manage_app) and create a new app (after making an account if you haven't already)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Response [200]>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Replace None with appropriate code\n",
    "\n",
    "# Import the requests library\n",
    "import requests\n",
    "\n",
    "# Get this from the \"Manage App\" page. Make sure you set them\n",
    "# back to None before pushing this to GitHub, since otherwise\n",
    "# your credentials will be compromised\n",
    "api_key = None\n",
    "\n",
    "# These can be whatever you want! But the solution uses \"pizza\"\n",
    "# and \"New York NY\" if you want to compare your work directly\n",
    "term = \"pizza\"\n",
    "location = \"New York NY\"\n",
    "\n",
    "# Set up params for request\n",
    "url = \"https://api.yelp.com/v3/businesses/search\"\n",
    "headers = {\n",
    "    \"Authorization\": \"Bearer {}\".format(api_key)\n",
    "}\n",
    "url_params = {\n",
    "    \"term\": term.replace(\" \", \"+\"),\n",
    "    \"location\": location.replace(\" \", \"+\")\n",
    "}\n",
    "\n",
    "# Make the request using requests.get, passing in\n",
    "# url, headers=headers, and params=url_params\n",
    "response = requests.get(url, headers=headers, params=url_params)\n",
    "\n",
    "# Confirm we got a 200 response\n",
    "response"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['businesses', 'total', 'region'])"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Run this cell without changes\n",
    "\n",
    "# Get the response body in JSON format\n",
    "response_json = response.json()\n",
    "# View the keys\n",
    "response_json.keys()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extracting Data\n",
    "\n",
    "Now, retrieve the value associated with the `'businesses'` key, and inspect its contents."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'id': 'zj8Lq1T8KIC5zwFief15jg',\n",
       "  'alias': 'prince-street-pizza-new-york-2',\n",
       "  'name': 'Prince Street Pizza',\n",
       "  'image_url': 'https://s3-media4.fl.yelpcdn.com/bphoto/PfI8oV4ct9ZJZNtUhSS8DQ/o.jpg',\n",
       "  'is_closed': False,\n",
       "  'url': 'https://www.yelp.com/biz/prince-street-pizza-new-york-2?adjust_creative=K0hoWIBukEfJhX5EIWxh-g&utm_campaign=yelp_api_v3&utm_medium=api_v3_business_search&utm_source=K0hoWIBukEfJhX5EIWxh-g',\n",
       "  'review_count': 4970,\n",
       "  'categories': [{'alias': 'pizza', 'title': 'Pizza'},\n",
       "   {'alias': 'italian', 'title': 'Italian'}],\n",
       "  'rating': 4.5,\n",
       "  'coordinates': {'latitude': 40.72308755605564,\n",
       "   'longitude': -73.99453001177575},\n",
       "  'transactions': ['pickup', 'delivery'],\n",
       "  'price': '$',\n",
       "  'location': {'address1': '27 Prince St',\n",
       "   'address2': None,\n",
       "   'address3': '',\n",
       "   'city': 'New York',\n",
       "   'zip_code': '10012',\n",
       "   'country': 'US',\n",
       "   'state': 'NY',\n",
       "   'display_address': ['27 Prince St', 'New York, NY 10012']},\n",
       "  'phone': '+12129664100',\n",
       "  'display_phone': '(212) 966-4100',\n",
       "  'distance': 2209.3116178604555},\n",
       " {'id': 'ysqgdbSrezXgVwER2kQWKA',\n",
       "  'alias': 'julianas-brooklyn-3',\n",
       "  'name': \"Juliana's\",\n",
       "  'image_url': 'https://s3-media2.fl.yelpcdn.com/bphoto/NVoLFle5H-SHNN6piAKIYw/o.jpg',\n",
       "  'is_closed': False,\n",
       "  'url': 'https://www.yelp.com/biz/julianas-brooklyn-3?adjust_creative=K0hoWIBukEfJhX5EIWxh-g&utm_campaign=yelp_api_v3&utm_medium=api_v3_business_search&utm_source=K0hoWIBukEfJhX5EIWxh-g',\n",
       "  'review_count': 2666,\n",
       "  'categories': [{'alias': 'pizza', 'title': 'Pizza'}],\n",
       "  'rating': 4.5,\n",
       "  'coordinates': {'latitude': 40.70274718768062,\n",
       "   'longitude': -73.99343490196397},\n",
       "  'transactions': ['delivery'],\n",
       "  'price': '$$',\n",
       "  'location': {'address1': '19 Old Fulton St',\n",
       "   'address2': '',\n",
       "   'address3': '',\n",
       "   'city': 'Brooklyn',\n",
       "   'zip_code': '11201',\n",
       "   'country': 'US',\n",
       "   'state': 'NY',\n",
       "   'display_address': ['19 Old Fulton St', 'Brooklyn, NY 11201']},\n",
       "  'phone': '+17185966700',\n",
       "  'display_phone': '(718) 596-6700',\n",
       "  'distance': 1289.8572856708206}]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Replace None with appropriate code\n",
    "\n",
    "# Retrieve the value from response_json\n",
    "businesses = response_json['businesses']\n",
    "\n",
    "# View the first 2 records\n",
    "businesses[:2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Preparing Data\n",
    "\n",
    "Write a function `prepare_data` that takes in a list of dictionaries like `businesses` and returns a copy that has been prepared for analysis:\n",
    "\n",
    "1. The `coordinates` key-value pair has been converted into two separate key-value pairs, `latitude` and `longitude`\n",
    "2. All other key-value pairs except for `name`, `review_count`, `rating`, and `price` have been dropped\n",
    "3. All dictionaries missing one of the relevant keys or containing null values have been dropped\n",
    "\n",
    "In other words, the final keys for each dictionary should be `name`, `review_count`, `rating`, `price`, `latitude`, and `longitude`.\n",
    "\n",
    "Complete the function in the cell below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'name': 'Prince Street Pizza',\n",
       "  'review_count': 4970,\n",
       "  'rating': 4.5,\n",
       "  'price': '$',\n",
       "  'latitude': 40.72308755605564,\n",
       "  'longitude': -73.99453001177575},\n",
       " {'name': \"Juliana's\",\n",
       "  'review_count': 2666,\n",
       "  'rating': 4.5,\n",
       "  'price': '$$',\n",
       "  'latitude': 40.70274718768062,\n",
       "  'longitude': -73.99343490196397},\n",
       " {'name': 'Rubirosa',\n",
       "  'review_count': 3077,\n",
       "  'rating': 4.5,\n",
       "  'price': '$$',\n",
       "  'latitude': 40.722766,\n",
       "  'longitude': -73.996233},\n",
       " {'name': \"L'industrie Pizzeria\",\n",
       "  'review_count': 1016,\n",
       "  'rating': 4.5,\n",
       "  'price': '$',\n",
       "  'latitude': 40.71162,\n",
       "  'longitude': -73.95783},\n",
       " {'name': \"Lombardi's Pizza\",\n",
       "  'review_count': 6583,\n",
       "  'rating': 4.0,\n",
       "  'price': '$$',\n",
       "  'latitude': 40.7215934960083,\n",
       "  'longitude': -73.9955956044561},\n",
       " {'name': \"Joe's Pizza\",\n",
       "  'review_count': 3033,\n",
       "  'rating': 4.0,\n",
       "  'price': '$',\n",
       "  'latitude': 40.73060076,\n",
       "  'longitude': -74.00215997},\n",
       " {'name': \"Joe's Pizza\",\n",
       "  'review_count': 1954,\n",
       "  'rating': 4.0,\n",
       "  'price': '$',\n",
       "  'latitude': 40.7547,\n",
       "  'longitude': -73.98696},\n",
       " {'name': \"Grimaldi's Pizzeria\",\n",
       "  'review_count': 4944,\n",
       "  'rating': 3.5,\n",
       "  'price': '$$',\n",
       "  'latitude': 40.7026459,\n",
       "  'longitude': -73.9932413},\n",
       " {'name': \"Rizzo's Fine Pizza\",\n",
       "  'review_count': 659,\n",
       "  'rating': 4.0,\n",
       "  'price': '$',\n",
       "  'latitude': 40.76337,\n",
       "  'longitude': -73.915124},\n",
       " {'name': 'Lucali',\n",
       "  'review_count': 1972,\n",
       "  'rating': 4.0,\n",
       "  'price': '$$',\n",
       "  'latitude': 40.681840746711224,\n",
       "  'longitude': -74.0003327},\n",
       " {'name': \"John's of Bleecker Street\",\n",
       "  'review_count': 2599,\n",
       "  'rating': 4.0,\n",
       "  'price': '$$',\n",
       "  'latitude': 40.73158,\n",
       "  'longitude': -74.00332},\n",
       " {'name': \"Joe's Pizza\",\n",
       "  'review_count': 1059,\n",
       "  'rating': 4.0,\n",
       "  'price': '$',\n",
       "  'latitude': 40.73331,\n",
       "  'longitude': -73.98763},\n",
       " {'name': 'Olio e Più',\n",
       "  'review_count': 4618,\n",
       "  'rating': 4.5,\n",
       "  'price': '$$',\n",
       "  'latitude': 40.733798036104304,\n",
       "  'longitude': -73.99977392649927},\n",
       " {'name': 'Gelso & Grand',\n",
       "  'review_count': 1420,\n",
       "  'rating': 4.5,\n",
       "  'price': '$$',\n",
       "  'latitude': 40.71958,\n",
       "  'longitude': -73.99734},\n",
       " {'name': \"Joe's Pizza\",\n",
       "  'review_count': 450,\n",
       "  'rating': 4.0,\n",
       "  'price': '$',\n",
       "  'latitude': 40.7168952,\n",
       "  'longitude': -73.95892996733771},\n",
       " {'name': \"L'Antica Pizzeria Da Michele NYC\",\n",
       "  'review_count': 88,\n",
       "  'rating': 4.5,\n",
       "  'price': '$$$',\n",
       "  'latitude': 40.73707,\n",
       "  'longitude': -74.00165},\n",
       " {'name': 'Bleecker Street Pizza',\n",
       "  'review_count': 2867,\n",
       "  'rating': 4.0,\n",
       "  'price': '$',\n",
       "  'latitude': 40.7320627016512,\n",
       "  'longitude': -74.0036552270137},\n",
       " {'name': \"Roberta's\",\n",
       "  'review_count': 3297,\n",
       "  'rating': 4.0,\n",
       "  'price': '$$',\n",
       "  'latitude': 40.70493,\n",
       "  'longitude': -73.93399},\n",
       " {'name': \"Mancini's Wood-Fired Pizza\",\n",
       "  'review_count': 153,\n",
       "  'rating': 4.5,\n",
       "  'price': '$',\n",
       "  'latitude': 40.62207,\n",
       "  'longitude': -74.02591}]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Replace None with appropriate code\n",
    "\n",
    "def prepare_data(data_list):\n",
    "    \"\"\"\n",
    "    This function takes in a list of dictionaries and prepares it\n",
    "    for analysis\n",
    "    \"\"\"\n",
    "    \n",
    "    # Make a new list to hold results\n",
    "    results = []\n",
    "    \n",
    "    for business_data in data_list:\n",
    "    \n",
    "        # Make a new dictionary to hold prepared data for this business\n",
    "        prepared_data = {}\n",
    "        \n",
    "        # Extract name, review_count, rating, and price key-value pairs\n",
    "        # from business_data and add to prepared_data\n",
    "        # If a key is not present in business_data, add it to prepared_data\n",
    "        # with an associated value of None\n",
    "        prepared_data['name'] = business_data['name']\n",
    "        if not ('name' in business_data):\n",
    "            prepared_data['name'] = None   \n",
    "        prepared_data['review_count'] = business_data['review_count']\n",
    "        if not ('review_count' in business_data):\n",
    "            prepared_data['review_count'] = None   \n",
    "        prepared_data['rating'] = business_data['rating']\n",
    "        if not ('rating' in business_data):\n",
    "            prepared_data['rating'] = None   \n",
    "        if not ('price' in business_data):\n",
    "            prepared_data['price'] = None  \n",
    "        else:\n",
    "            prepared_data['price'] = business_data['price']\n",
    "         \n",
    "    \n",
    "        # Parse and add latitude and longitude columns\n",
    "        prepared_data['latitude'] = business_data['coordinates']['latitude']\n",
    "        if not ('latitude' in business_data['coordinates']):\n",
    "            prepared_data['latitude'] = None\n",
    "        prepared_data['longitude'] = business_data['coordinates']['longitude']\n",
    "        if not ('longitude' in business_data['coordinates']):\n",
    "            prepared_data['longitude'] = None\n",
    "            \n",
    "        # Add to list if all values are present\n",
    "        if all(prepared_data.values()):\n",
    "            results.append(prepared_data)\n",
    "    \n",
    "    return results\n",
    "    \n",
    "# Test out function\n",
    "prepared_businesses = prepare_data(businesses)\n",
    "prepared_businesses"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check that your function created the correct keys:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Run this cell without changes\n",
    "\n",
    "assert sorted(list(prepared_businesses[0].keys())) == ['latitude', 'longitude', 'name', 'price', 'rating', 'review_count']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following code will differ depending on your query, but we expect there to be 20 businesses in the original list, and potentially fewer in the prepared list (if any of them were missing data):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original: 20\n",
      "Prepared: 19\n"
     ]
    }
   ],
   "source": [
    "# Run this cell without changes\n",
    "print(\"Original:\", len(businesses))\n",
    "print(\"Prepared:\", len(prepared_businesses))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Great! We will reuse this function once we have retrieved the full dataset."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Add Pagination\n",
    "\n",
    "Now that you are able to extract information from one page of the response, let's figure out how to request as many pages as possible.\n",
    "\n",
    "### Determining the Total\n",
    "\n",
    "Depending on the number of total results for your query, you will either retrieve all of the results, or just the first 1000 (if there are more than 1000 total).\n",
    "\n",
    "We can find the total number of results using the `\"total\"` key:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "16500"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Run this cell without changes\n",
    "response_json[\"total\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(This is specific to the implementation of the Yelp API. Some APIs will just tell you that there are more pages, or will tell you the number of pages total, rather than the total number of results. If you're not sure, always check the documentation.)\n",
    "\n",
    "In the cell below, assign the variable `total` to either the value shown above (if it is less than 1000), or 1000."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Replace None with appropriate code\n",
    "total = 1000"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calculating the Offsets\n",
    "\n",
    "The documentation states in the parameters section:\n",
    "\n",
    "> **Name**: `limit`, **Type:** int, **Description:** Optional. Number of business results to return. By default, it will return 20. Maximum is 50.\n",
    "\n",
    "> **Name**: `offset`, **Type:** int, **Description:** Optional. Offset the list of returned business results by this amount.\n",
    "\n",
    "So, to get the most results with the fewest API calls we want to set a limit of 50 every time. If, say, we wanted to get 210 total results, that would mean:\n",
    "\n",
    "1. Offset of `0` (first 50 records)\n",
    "2. Offset of `50` (second 50 records)\n",
    "3. Offset of `100` (third 50 records)\n",
    "4. Offset of `150` (fourth 50 records)\n",
    "5. Offset of `200` (final 10 records)\n",
    "\n",
    "In the cell below, create a function `get_offsets` that takes in a total and returns a list of offsets for that total. You can assume that there is a limit of 50 every time.\n",
    "\n",
    "*Hint: you can use `range` ([documentation here](https://docs.python.org/3.3/library/stdtypes.html?highlight=range#range)) to do this in one line of code. Just make the returned result is a list.*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Replace None with appropriate code\n",
    "def get_offsets(total):\n",
    "    \"\"\"\n",
    "    Get a list of offsets needed to get all pages\n",
    "    of data up until the total\n",
    "    \"\"\"\n",
    "    # Initialize an empty list and a counting variable\n",
    "    list = []\n",
    "    count = 0\n",
    "    \n",
    "    # Increment the count by 50 and add it to the list\n",
    "    while count < total:\n",
    "        list.append(count)\n",
    "        count += 50\n",
    "    return list"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check that your function works below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Run this cell without changes\n",
    "\n",
    "assert get_offsets(200) == [0, 50, 100, 150]\n",
    "assert get_offsets(210) == [0, 50, 100, 150, 200]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Putting It All Together\n",
    "\n",
    "Recall that the following variable has already been declared for you:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'term': 'pizza', 'location': 'New+York+NY'}"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Run this cell without changes\n",
    "url_params"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We'll go ahead and also specify that the limit should be 50 every time:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'term': 'pizza', 'location': 'New+York+NY', 'limit': 50}"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Run this cell without changes\n",
    "url_params[\"limit\"] = 50\n",
    "url_params"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In order to modify the offset, you'll need to add it to `url_params` with the key `\"offset\"` and whatever value is needed.\n",
    "\n",
    "In the cell below, write code that:\n",
    "\n",
    "* Creates an empty list for the full prepared dataset\n",
    "* Loops over all of the offsets from `get_offsets` and makes an API call each time with the specified offset\n",
    "* Calls `prepare_data` to get a cleaned version of the result of each API call\n",
    "* Extends the full prepared dataset list with each query's prepared dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "726"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Replace None with appropriate code\n",
    "\n",
    "# Create an empty list for the full prepared dataset\n",
    "full_dataset = []\n",
    "\n",
    "for offset in get_offsets(total):\n",
    "    # Add or update the \"offset\" key-value pair in url_params\n",
    "    url_params[\"offset\"] = offset\n",
    "    \n",
    "    # Make the query and get the response\n",
    "    response = requests.get(url, headers=headers, params=url_params)\n",
    "    \n",
    "    # Get the response body in JSON format\n",
    "    response_json = response.json()\n",
    "    \n",
    "    # Get the list of businesses from the response_json\n",
    "    businesses = response_json ['businesses']\n",
    "    \n",
    "    # Call the prepare_data function to get a list of processed data\n",
    "    prepared_businesses = prepare_data(businesses)\n",
    "    \n",
    "    # Extend full_dataset with this list (don't append, or you'll get\n",
    "    # a list of lists instead of a flat list)\n",
    "    full_dataset.extend(prepared_businesses)\n",
    "\n",
    "# Check the length of the full dataset. It will be up to `total`,\n",
    "# potentially less if there were missing values\n",
    "len(full_dataset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'name': 'Prince Street Pizza',\n",
       "  'review_count': 4970,\n",
       "  'rating': 4.5,\n",
       "  'price': '$',\n",
       "  'latitude': 40.72308755605564,\n",
       "  'longitude': -73.99453001177575},\n",
       " {'name': \"Juliana's\",\n",
       "  'review_count': 2666,\n",
       "  'rating': 4.5,\n",
       "  'price': '$$',\n",
       "  'latitude': 40.70274718768062,\n",
       "  'longitude': -73.99343490196397}]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_dataset[:2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This code may take up to a few minutes to run.\n",
    "\n",
    "If you get an error trying to get the response body in JSON format, try adding `time.sleep(1)` right after the `requests.get` line, so your code will sleep for 1 second between each API call."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Perform Exploratory Analysis\n",
    "\n",
    "Take the businesses from the previous question and do an initial exploratory analysis. We have provided some plots for you to interpret:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA7MAAAFNCAYAAADSGTgvAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/d3fzzAAAACXBIWXMAAAsTAAALEwEAmpwYAABHGElEQVR4nO3deZhkZXn38e+PRVxAERlx2Bw1aAQTUSdEo1GiRnEd9A0Rkxg0JJgEjSYaBd8YMb4kuGE0RiMKARMVR9wQVyTiLjggIAMSR0AZQZioyKJBB+73j/O0FE0vNd1dXV3V38919VWnnjrn1P3UdN9z7jrPeU6qCkmSJEmSRslWww5AkiRJkqQtZTErSZIkSRo5FrOSJEmSpJFjMStJkiRJGjkWs5IkSZKkkWMxK0mSJEkaORazy0iSf0vyymHHsZQl+cMkn1nA/a1Psn9bPirJfy7gvl+R5F0LtT9JUxt27uzNIwuwr9vkuCSV5FcWYt9tfzckue9C7U/SYA3rb3Yh82qSPVs/tm7Pz0zypwux77a/TyY5ZKH2p4UV7zO79CS5HNgFuBm4AfgU8IKqumGYcfUjyR2AVwB/COwKbAL+C/iHqrp8gO+7P/CfVbX7DOucCPwBcFNr+i7wMeCYqvrJFr7ficDGqvq7LdjmKOBXquqPtuS92rb7M0v/JHXmk0OTPBf406p61CBjbO+1CrgMuLE13Qh8HXhzVZ0+x31tW1Wbt2C7Avaqqg1b8n5t2zPp8pJfqklLxKT8dyPwCeCFi3kM2RPD5hbHRcC7geOq6pY57OtPq+qzW7DNmcwxN83nWE3D4ZnZpetpVbU9sC/wEODI4YbTt1OAp9MVjXcDHgycAzxumEH1eF1V7QCsAJ4HPBz4cpK7LOSbJNlmIfcnaYuNUg7dscX6YOB04MOtqF5Q5iVp2ZjIfw8FfgO43Rfvi5APntaOt+4NHAO8HDh+od/EvCaL2SWuqn4AfJrugAyAJA9P8pUk1yY5v2cY68FJ1vVun+Svk5zalk9M8v96XntqkvPafr6S5Ndb+/OSfKxnvQ1J1vY8vyLJvkyS5PHA7wJrqurrVbW5qn5SVf9aVce3dXZNcmqSH7X9/lnP9pPj2z/Jxp7nlyd5aZILkvwkyfuT3LEVop8Edm3DTG5Isussn+v/VtXX6Qrve9AVtiR5bpIvteUkeVOSa9r7XZDkQUkOozvz/LL2Xh/rie/lSS4AbkyyTWt7fM9b37HFfX2Sc5M8uKd/txnuN/F5TNe/ycOWkzy9DUe8tg2xeeBsn91Mn5E0DqbJoUck+U77O7woyTNa+wOBfwMe0f7Orm3tv8xNE3kpyUtabrgqyfN69n2PJB9Lcl2Sr7e/4S/1G2tVvRk4Cnhtkq3aPn+ZR5Lsl2Rd2//VSY5tm3+hPV7bYn9Ey2dfbnnsR8BRvTmux5OTXJrkf5K8vud9J+eYVS1PbZPkaOC3gbe293trW+eXeSzJ3ZK8O8mmJN9N8nc9+35uki8leUOSHye5LMmT+vmcJPWnqr5Pd/zwIPjl3+fhSb4NfLunbeJv9k5J3tj+Xn/S/kbv1F6b8tizjxh+UlWnAs8CDkkyEUtvXt05yWlt3z9K8sUkWyX5D2BP4GMtz7ysJw8dmuR7wH/15qaet75fkrNbPz6aZKf2Xrc5tmxtlyd5fJID6EYXPqu93/nt9V8OW25x/V37jK5pOe5u7bWJOA5J8r2WU//vFv2jaYtZzC5xSXYHngRsaM93Az4O/D9gJ+ClwAeTrABOBR6QZK+eXfwB8N4p9vtQ4ATg+XTF3DuAU5NsB3we+O32B7sS2BZ4ZNvuvsD2wAVThPt44OyqumKGLr0P2Eg3BPn3gH9MsiVnbX8fOAC4D/DrwHOr6ka6z+jKqtq+/VzZz86q6nq6MyG/PcXLTwAeDdwf2JEuEf+wqo4D3kN3lnf7qnpazzbPBp5Cd6ZlqqF+a4AP0P3bvRf4SJJtZ4lx1v4luT/dZ/tiurPOn6BL/nfoWe12n91M7yuNg8k5tPkO3d/83YBXA/+ZZGVVXQz8OfDV9ne24zS7vVfbdjfgUOBfk9y9vfavdEP77gUc0n621IeAewIPmOK1N9MNQ74rcD9g4ovGR7fHHVvsX23PfxO4tO3v6Gne7xnAarqzOGuAP5ktwKr6v8AX6YZvb19VL5hitX+h+5zuCzwG+GPaF4c9sV0C7Ay8Djg+SWZ7b0n9SbIH8GTgGz3NB9L97e09xSZvAB4G/BbdccrLgFtmOfbsS1WdTXf8N9Xx1kvaayvohie/otukngN8j3amuape17PNY4AHAk+c5i3/mC6X7Uo33PktfcT4KeAfgfe393vwFKs9t/38Dl1u2x5466R1HkWXvx8H/H16Ti5o4VnMLl0fSXI9cAVwDfCq1v5HwCeq6hNVdUu7rmod8OSq+inwUbqCilbU/ipdkTvZnwHvqKqzqurmqjqJ7lrSh1fVpcD1dGcyHkN3VuP7SX61Pf/iNNc83AO4aroOtaT6KODl7czoecC7gOf0+6EAb6mqK6vqR3TXu+67BdtO50q65DzZL4Ad6D7DVNXFVTVt/3riu6KqfjbN6+dU1SlV9QvgWOCOdEOd5+tZwMer6vS27zcAd6L7D6k3toX+7KSlarocSlV9oP0t3FJV76c7Q7HfFuz7F3TzAPyiqj5Bd13uA9JNPvJ/gFdV1U+r6iLgpDnEPvFl1XR56VeS7FxVN1TV12bbV1X9SxspM11eem1V/aiqvgf8M+3/kPlon8WzgCOr6vo2Z8IbuW2+/25VvbOqbqb7nFbSHchKmp+PpBtZ8iW6ExT/2PPaP7W/99vkgzZq4k+AF1XV99ux4Veq6iZmOPbcwrhmOt5aCdy75dUv1uyT+hxVVTfOkNf+o6oubCcEXgn8fstL8/WHwLFVdWm7DvlI4OBJZ4VfXVU/q6rzgfPpLiHRgFjMLl0HtmsN9qcrpnZu7fcGDmpDMa5tyepRdEkAurN9EwcifwB8pBW5k90beMmk/exB9w0WdMlvf7pv+z8PnElXyD6mPZ/KD3vimMquwI/a2dAJ36U7u9GvH/Qs/5TuG7H52g340eTGqvovum/b/hW4OslxSe46y75mOit9m9fbFwITZ6nna1e6z7J331dw2892EJ+dtFRNl0NJ8se59RKLa+mG4O085V6m9sNJIy8m/p5WANtw2zwwW06YysTf7e3yEt2Z4PsD30o3jPmps+yrn/fvXee7LExO2hm4Az15idvn+1/mpJ7/p8xL0vwdWFU7VtW9q+ovJxV80+WEnem+YP/OFK/NduzZrymPt4DX042e+Uy6Sx6O6GNffR9v0eWebdmyPD+d2xxvteVtuO0XcR5vLSKL2SWuqj4PnEh3pg26P87/aElq4ucuVXVMe/0zwM7prml9NlMMMe7Zz9GT9nPnqnpfe32imP3ttvx5Zi9mPwvs14b1TeVKYKckO/S07Ql8vy3fCNy557V7TbOfqcxpWu4k29MNj/7ilDutektVPQzYh+4A8m9neb/Z4tij5723Anbn1rMwP2X6/s+23yvp/rOZ2Hfae31/2i2kZWByDk1yb+CdwAuAe7ShxBcCE8Nb5zPF/ya64Wy9OXCPadadyTPoziZfMvmFqvp2VT2bbtjwa4FT0l1XP9ecNDnGPbk1J82Wk2fa9//QnW25d09bb76XNBzT/d3+D/C/dJcvTDbbseeskvwGXTF7uzkE2uiNl1TVfYGnAX/TcwnavI+36HLPL+j6eJu81s7W9g6X3qLjrbbvzcDVs2ynAbGYHQ3/DPxuK1D/E3hakicm2TrdBEj7TxSQ7WzBKXTfcu1Edz3oVN4J/HmS30znLkme0lNofp7ueoA7VdVGumLvALqhxN+YaofVTZs+MRPnw9JNErJDkj9P8ifVXUv7FeCfWty/TneW4T1tF+fRTUSyU5J70V3/2a+rgXtMXIQ/myTbJXkY8BHgx8C/T7HOb7TPZ1u65Pe/dFPMT7zfXO7L9rAkz2zDUV5MN7R7YpjgecAftH/XA+i+OJgwW//WAk9J8rgW70vavr8yhxilcfPP3JpDJwq/TdBNeEebHKW5Gth90vXmfWnDZT9EN9HSndulGX/c7/ZJdknyAroh0UdOdTlHkj9KsqK9dm1rvrn15xbmlpf+Nsnd26UgLwLe39rPAx6d7h6Od+P2M0JPmwfbZ7EWOLr9P3Bv4G/o/g+TtMS0nHICcGy6SSa3TjeR3HbMcuw5kyR3bSNITqa7Xc43p1jnqUl+pX0Rfx1dTpvv8dYfJdk7yZ2BfwBOaXnpv+km43xKO176O2C7nu2uBla1Ew5TeR/w10nu006ITFxj2/ct0bSwLGZHQFVtors/1ytbQbiG7uL4TXTflv0tt/23fC/d2cYPTPfHVVXr6K6bfStdMbeBngmBquq/6a4D+2J7fh3dJCJfbslgOr9HN/nQ+4Gf0J3xWE131ha6s8Wr6L7Z+jDdtWUTBfd/0F1bcDndGeaJA6pZVdW36BLMpW0IzHTD5F7WrqP7Ed1neg7wW+2aisnuSlf0/5huGMkPufUM+fHA3u29PtJvnHTXND+r7fM5wDPbNa7QHUQ+je4A9Q/pCu2++ldVl9Bd0/IvdN88Po1uwoSfb0Fs0lialEMvort286t0By2/Bny5Z/X/AtYDP0jyP3N4uxfQTXr0A7qc9j5uvbf1dK5NciPwTbpr0A6qqhOmWfcAYH2SG+gmgzq4zUHwU7oJnr7ccsSWXIv/UbpceB7dJC/HA7Tc/H66Cf/OAU6btN2bgd9LNxvxVJOrvJDui8BL6c7GvJfuYFnS0vRSujz0dbrjpNcCW/V57DnZx3LrvAX/l26ekOdNs+5edMeJN9Dl5rdV1ZnttX8C/q7ltZduQV/+g25Uzg/ohk//FXSzKwN/STdny/fpclTv7MYfaI8/THLuFPs9oe37C3T39v5fulynIcns11dLkqS5SPJa4F5VNZdZjSVJ0gw8MytJ0gJJ8qtJfr1dvrEf3aUUHx52XJIkjaNtZl9FkiT1aQe6ocW70k3i9Ea6YbySJGmBOcxYkiRJkjRyHGYsSZIkSRo5FrOSJEmSpJEz0tfM7rzzzrVq1aphhyFpiTnnnHP+p6pWzL7maDDXSZrKuOU6MN9Jur2Zct1IF7OrVq1i3bp1ww5D0hKT5LvDjmEhmeskTWXcch2Y7yTd3ky5zmHGkiRJkqSRYzErSZIkSRo5FrOSJEmSpJFjMStJkiRJGjkWs5IkSZKkkWMxK0mSJEkaORazkiRJkqSRYzErSfOQ5I5Jzk5yfpL1SV7d2o9K8v0k57WfJ/dsc2SSDUkuSfLE4UUvSZI0urYZdgCSNOJuAh5bVTck2Rb4UpJPttfeVFVv6F05yd7AwcA+wK7AZ5Pcv6puXtSoJUmSRpxnZiVpHqpzQ3u6bfupGTZZA5xcVTdV1WXABmC/AYcpSZI0dixmJWmekmyd5DzgGuD0qjqrvfSCJBckOSHJ3VvbbsAVPZtvbG2SJEnaAstqmPGqIz4+0P1ffsxTBrp/SUtTGyK8b5IdgQ8neRDwduA1dGdpXwO8EfgTIFPtYnJDksOAwwD23HPPwQSuJWPQ/z8tFf4/qYU0Tn83/m1Ic+OZWUlaIFV1LXAmcEBVXV1VN1fVLcA7uXUo8UZgj57NdgeunGJfx1XV6qpavWLFisEGLkmSNIIsZiVpHpKsaGdkSXIn4PHAt5Ks7FntGcCFbflU4OAk2yW5D7AXcPYihixJkjQWltUwY0kagJXASUm2pvuCcG1VnZbkP5LsSzeE+HLg+QBVtT7JWuAiYDNwuDMZS5IkbTmLWUmah6q6AHjIFO3PmWGbo4GjBxmXJEnSuHOYsSRJkiRp5FjMSpIkSZJGjsWsJEmSJGnkWMxKkiRJkkaOxawkSZIkaeRYzEqSJEmSRo7FrCRJkiRp5FjMSpIkSZJGjsWsJEmSZpTkjknOTnJ+kvVJXt3aj0ry/STntZ8n92xzZJINSS5J8sThRS9pXG0z7AAkSZK05N0EPLaqbkiyLfClJJ9sr72pqt7Qu3KSvYGDgX2AXYHPJrl/Vd28qFFLGmuemZUkSdKMqnNDe7pt+6kZNlkDnFxVN1XVZcAGYL8BhylpmRloMZtkxySnJPlWkouTPCLJTklOT/Lt9nj3nvUdjiJJkrQEJdk6yXnANcDpVXVWe+kFSS5IckLPcd1uwBU9m29sbZK0YAZ9ZvbNwKeq6leBBwMXA0cAZ1TVXsAZ7fnk4SgHAG9LsvWA45MkSVIfqurmqtoX2B3YL8mDgLcD9wP2Ba4C3thWz1S7mGq/SQ5Lsi7Juk2bNi143JLG18CK2SR3BR4NHA9QVT+vqmvphp2c1FY7CTiwLTscRZIkaYlrx3NnAgdU1dWtyL0FeCe3HrttBPbo2Wx34Mpp9ndcVa2uqtUrVqwYXOCSxs4gz8zeF9gE/HuSbyR5V5K7ALtU1VUA7fGebX2Ho0iSJC1BSVYk2bEt3wl4PPCtJCt7VnsGcGFbPhU4OMl2Se4D7AWcvYghS1oGBjmb8TbAQ4EXVtVZSd5MG1I8jb6GoyQ5DDgMYM8991yIOCVJkjSzlcBJ7RKwrYC1VXVakv9Isi/dMdvlwPMBqmp9krXARcBm4HBnMpa00AZZzG4ENvZMDnAKXTF7dZKVVXVV+zbvmp71Zx2OUlXHAccBrF69eqZZ9CRJkrQAquoC4CFTtD9nhm2OBo4eZFySlreBDTOuqh8AVyR5QGt6HN23c6cCh7S2Q4CPtmWHo0iSJEmS+jLIM7MALwTek+QOwKXA82hDU5IcCnwPOAgcjiJJkiRJ6t9Ai9mqOg9YPcVLj5tmfYejSJIkSZJmNej7zEqSJEmStOAsZiVJkiRJI8diVpIkSZI0cixmJUmSJEkjx2JWkiRJkjRyLGYlSZIkSSPHYlaSJEmSNHIsZiVJkiRJI8diVpLmIckdk5yd5Pwk65O8urXvlOT0JN9uj3fv2ebIJBuSXJLkicOLXpIkaXRZzErS/NwEPLaqHgzsCxyQ5OHAEcAZVbUXcEZ7TpK9gYOBfYADgLcl2XoYgUuSJI0yi1lJmofq3NCebtt+ClgDnNTaTwIObMtrgJOr6qaqugzYAOy3eBFLkiSNB4tZSZqnJFsnOQ+4Bji9qs4CdqmqqwDa4z3b6rsBV/RsvrG1SZIkaQtYzErSPFXVzVW1L7A7sF+SB82weqbaxe1WSg5Lsi7Juk2bNi1QpJIkSePDYlaSFkhVXQucSXct7NVJVgK0x2vaahuBPXo22x24cop9HVdVq6tq9YoVKwYZtiRJ0kiymJWkeUiyIsmObflOwOOBbwGnAoe01Q4BPtqWTwUOTrJdkvsAewFnL2rQkiRJY2CbYQcgSSNuJXBSm5F4K2BtVZ2W5KvA2iSHAt8DDgKoqvVJ1gIXAZuBw6vq5iHFLkkaQauO+PiwQ1gwlx/zlGGHoBFmMStJ81BVFwAPmaL9h8DjptnmaODoAYcmSZI01hxmLEmSJEkaORazkiRJkqSRYzErSZIkSRo5FrOSJEmSpJFjMStJkiRJGjkWs5IkSZpRkjsmOTvJ+UnWJ3l1a98pyelJvt0e796zzZFJNiS5JMkThxe9pHFlMStJkqTZ3AQ8tqoeDOwLHJDk4cARwBlVtRdwRntOkr2Bg4F9gAOAt7X7cUvSgrGYlSRJ0oyqc0N7um37KWANcFJrPwk4sC2vAU6uqpuq6jJgA7Df4kUsaTmwmJUkSdKskmyd5DzgGuD0qjoL2KWqrgJoj/dsq+8GXNGz+cbWJkkLxmJWkiRJs6qqm6tqX2B3YL8kD5ph9Uy1iylXTA5Lsi7Juk2bNi1ApJKWC4tZSZIk9a2qrgXOpLsW9uokKwHa4zVttY3AHj2b7Q5cOc3+jquq1VW1esWKFYMKW9IYspiVJEnSjJKsSLJjW74T8HjgW8CpwCFttUOAj7blU4GDk2yX5D7AXsDZixq0pLG3zbADkCRJ0pK3EjipzUi8FbC2qk5L8lVgbZJDge8BBwFU1foka4GLgM3A4VV185BilzSmLGYlSZI0o6q6AHjIFO0/BB43zTZHA0cPODRJy9hAhxknuTzJN5Ocl2Rda/Pm2pIkSZKkeVmMa2Z/p6r2rarV7bk315YkSZIkzcswJoDy5tqSJEmSpHkZdDFbwGeSnJPksNbmzbUlSZIkSfMy6AmgHllVVya5J3B6km/NsG5fN9duRfFhAHvuuefCRClJkiRJGikDPTNbVVe2x2uAD9MNG57XzbW9sbYkSZIkaWDFbJK7JNlhYhl4AnAh3lxbkiRJkjRPgxxmvAvw4SQT7/PeqvpUkq/jzbUlSZIkSfMwsGK2qi4FHjxFuzfXliRJkiTNyzBuzSNJkiRJ0rxYzEqSJEmSRo7FrCRJkiRp5GxRMZtkqyR3HVQwkrQUmOskLQfmOkmjbtZiNsl7k9y13V7nIuCSJH87+NAkafGY6yQtB+Y6SeOknzOze1fVdcCBwCeAPYHnDDIoSRqCOeW6JHsk+VySi5OsT/Ki1n5Uku8nOa/9PLlnmyOTbEhySZInDqg/kjQVj+skjY1+bs2zbZJt6ZLeW6vqF0lqsGFJ0qKba67bDLykqs5NsgNwTpLT22tvqqo39K6cZG/gYGAfYFfgs0nu7321JS0Sj+skjY1+zsy+A7gcuAvwhST3Bq4bZFCSNARzynVVdVVVnduWrwcuBnabYZM1wMlVdVNVXQZsAPabZ+yS1C+P6ySNjVmL2ap6S1XtVlVPrs53gd9ZhNgkadEsRK5Lsgp4CHBWa3pBkguSnJDk7q1tN+CKns02MnPxK0kLxuM6SeOknwmgdklyfJJPtud7A4cMPDJJWkTzzXVJtgc+CLy4XY/2duB+wL7AVcAbJ1adYvPbDfFLcliSdUnWbdq0aYv6IknT8bhO0jjpZ5jxicCn6a7tAvhv4MUDikeShuVE5pjr2vVnHwTeU1UfAqiqq6vq5qq6BXgntw4l3gjs0bP57sCVk/dZVcdV1eqqWr1ixYot740kTe1EPK6TNCb6KWZ3rqq1wC0AVbUZcKISSeNmTrkuSYDjgYur6tie9pU9qz0DuLAtnwocnGS7JPcB9gLOXpguSNKsPK6TNDb6mc34xiT3oA2DS/Jw4CcDjUqSFt9cc90j6W5r8c0k57W2VwDPTrJv29/lwPMBqmp9krV093fcDBzuTMaSFpHHdZLGRj/F7N/QnUm4X5IvAyuA3xtoVJK0+OaU66rqS0x9HewnZtjmaODoOcYpSfPhcZ2ksTFrMdvunfgY4AF0B2yXVNUvBh6ZJC0ic52k5cBcJ2mc9DOb8UHAnapqPd0Ntt+f5KGDDkySFpO5TtJyYK6TNE76mQDqlVV1fZJHAU8ETqK75YQkjRNznaTlwFwnaWz0U8xOTEzyFODtVfVR4A6DC0mShsJcJ2k5mFOuS7JHks8luTjJ+iQvau1HJfl+kvPaz5N7tjkyyYYklyR54kB6I2lZ62cCqO8neQfweOC1SbajvyJYkkaJuU7ScjDXXLcZeEm75nYH4Jwkp7fX3lRVb+hdOcnewMHAPnT3tP1skvs7e7ukhdRP8vp9uptrH1BV1wI7AX87yKAkaQjMdZKWgznluqq6qqrObcvXAxcDu82wyRrg5Kq6qaouAzYA+80zdkm6jX6K2ZXAx6vq20n2Bw4Czh5kUJI0BOY6ScvBvHNdklXAQ4CzWtMLklyQ5IQkd29tuwFX9Gy2kZmLX0naYv0Usx8Ebk7yK8DxwH2A9w40KklafOY6ScvBvHJdku3bPl5cVdfRTR51P2Bf4CrgjROrTrF5TbPPw5KsS7Ju06ZN/YYiSX0Vs7dU1WbgmcA/V9Vf032rJ0njxFwnaTmYc65Lsi1dIfueqvoQQFVdXVU3V9UtwDu5dSjxRmCPns13B66car9VdVxVra6q1StWrJhTpyQtT/0Us79I8mzgj4HTWtu2gwtJkobCXCdpOZhTrksSujO5F1fVsT3tvYXwM4AL2/KpwMFJtktyH2AvvHRD0gLrZzbj5wF/DhxdVZe1hPSfgw1LkhaduU7ScjDXXPdI4DnAN5Oc19peATw7yb50Q4gvB54PUFXrk6wFLqKbCflwZzKWtNBmLWar6qIkLwf2bM8vA44ZdGCStJjMdZKWg7nmuqr6ElNfB/uJGbY5Gjh6jqFK0qxmHWac5GnAecCn2vN9k5w64LgkaVGZ6yQtB+Y6SeOkn2tmj6K7mP9agKo6j27mO0kaJ0dhrpM0/o7CXCdpTPRTzG6uqp9MaptyanVJGmHmOknLgblO0tjoZwKoC5P8AbB1kr2AvwK+MtiwJGnRmeskLQfmOkljo58zsy8E9gFuAt4HXAe8eIAxSdIwmOskLQfmOkljo5/ZjH8K/N/2s8WSbA2sA75fVU9NshPwfmAV3RTuv19VP27rHgkcCtwM/FVVfXou7ylJW2q+uU6SRoG5TtI4mbWYTXJ/4KV0xecv16+qx/b5Hi8CLgbu2p4fAZxRVcckOaI9f3mSvYGD6b4t3BX4bJL7e08ySYthAXKdJC155jpJ46Sfa2Y/APwb8C66M6Z9S7I78BS6e4z9TWteA+zflk8CzgRe3tpPrqqbgMuSbKCbbe+rW/KekjRHc851kjRCzHWSxkY/xezmqnr7HPf/z8DLgB162napqqsAquqqJPds7bsBX+tZb2Nrk6TFMJ9cJ0mjwlwnaWz0MwHUx5L8ZZKVSXaa+JltoyRPBa6pqnP6jCVTtN1uqvgkhyVZl2Tdpk2b+ty1JM1qTrlOkkaMuU7S2OjnzOwh7fFve9oKuO8s2z0SeHqSJwN3BO6a5D+Bq5OsbGdlVwLXtPU3Anv0bL87cOXknVbVccBxAKtXr/a+aJIWylxznSSNEnOdpLHRz2zG95nLjqvqSOBIgCT7Ay+tqj9K8nq6RHpMe/xo2+RU4L1JjqWbAGov4Oy5vLckbam55jpJGiXmOknjZNpiNsljq+q/kjxzqter6kNzfM9jgLVJDgW+BxzU9rc+yVrgImAzcLgzGUsatAHmOklaMsx1ksbRTGdmHwP8F/C0KV4roO+kV1Vn0s1aTFX9EHjcNOsdTTfzsSQtlgXLdZK0hJnrJI2daYvZqnpVe3ze4oUjSYvLXCdpOTDXSRpHs85mnORFSe6azruSnJvkCYsRnCQtFnOdpOXAXCdpnPRza54/qarrgCcA9wSeR3fdqySNkznluiR7JPlckouTrE/yota+U5LTk3y7Pd69Z5sjk2xIckmSJw6qQ5I0BY/rJI2NforZifu/Phn496o6n6nvCStJo2yuuW4z8JKqeiDwcODwJHsDRwBnVNVewBntOe21g4F9gAOAtyXZekF7IknT87hO0tjop5g9J8ln6JLep5PsANwy2LAkadHNKddV1VVVdW5bvh64GNgNWAOc1FY7CTiwLa8BTq6qm6rqMmADsN9CdkSSZuBxnaSxMet9ZoFDgX2BS6vqp0nuQTckRZLGybxzXZJVwEOAs4Bdquoq6AreJPdsq+0GfK1ns42tTZIWg8d1ksZGP8Xso9rjryeOQpE0tuaV65JsD3wQeHFVXTfDPqZ6oabY32HAYQB77rnnFscjSdPwuE7S2OinmP3bnuU70g2HOwd47EAikqThmHOuS7ItXSH7nqqauFfj1UlWtrOyK4FrWvtGYI+ezXcHrpy8z6o6DjgOYPXq1bcrdiVpjjyukzQ2Zi1mq+o2N9dOsgfwuoFFJElDMNdcl+7UxvHAxVV1bM9LpwKH0M0Segjw0Z729yY5FtgV2As4e94dkKQ+eFwnaZz0c2Z2so3AgxY6EElaYvrNdY8EngN8M8l5re0VdEXs2iSHAt8DDgKoqvVJ1gIX0c2EfHhV3bzAsUtSvzyukzSyZi1mk/wLt17PtRXdpAHnDzAmSVp0c811VfUlpr+txeOm2eZo4Ogtj1KS5sfjOknjpJ8zs+t6ljcD76uqLw8oHkkaFnOdpOXAXCdpbPRzzexJs60jSaPOXCdpOZhrrmvX1r4buBfdfWmPq6o3J9kJeD+wCrgc+P2q+nHb5ki6WwHdDPxVVX163h2QpB5bTfdCkr2SnJjk2CS7J/lkkhuSnJ/kNxYzSEkaFHOdpOVgAXLdZuAlVfVA4OHA4Un2Bo4AzqiqvYAz2nPaawcD+wAHAG9LsvUg+iZp+Zq2mAX+HfgK3S0jzgJOAHYGXgq8dfChSdKiMNdJWg7mleuq6qqqOrctXw9cDOwGrAEmzvaeBBzYltcAJ1fVTVV1GbCB7jZAkrRgZipmt6+q46rqDcDPquoDVfW/VXU6sN0ixSdJg2auk7QcLFiuS7IKeAhdUbxLVV0FXcEL3LOtthtwRc9mG1vbVPs7LMm6JOs2bdq0RZ2StLzNVMze0rN83QyvSdIoM9dJWg4WJNcl2R74IPDiqpq8n9usOkVbTdFGK7JXV9XqFStW9BuKJM04AdSvJrmALhndry3Tnt934JFJ0uIw10laDuad65JsS1fIvqeqPtSar06ysqquSrISuKa1bwT26Nl8d7ohzpK0YGYqZh+4aFFI0vCY6yQtB/PKdUkCHA9cXFXH9rx0KnAIcEx7/GhP+3uTHAvsCuwFnD2fGCRpsmmL2ar67mIGIknDYK6TtBwsQK57JPAc4JtJzmttr6ArYtcmORT4HnBQe7/1SdYCF9HNhHx4Vd08zxgk6TZmvc+sJEmSlreq+hJTXwcL8LhptjkaOHpgQUla9maaAEqSJEmSpCVp2mI2yRnt8bWLF44kLS5znaTlwFwnaRzNNMx4ZZLHAE9PcjKThpZM3DhbkkacuU7ScmCukzR2Zipm/x44gm4q9WMnvVbAYwcVlCQtInOdpOXAXCdp7Mw0m/EpwClJXllVr1nEmCRp0ZjrJC0H5jpJ42jW2Yyr6jVJng48ujWdWVWnDTYsSVpc5jpJy4G5TtI4mXU24yT/BLyI7j5hFwEvam2SNDbMdZKWA3OdpHHSz31mnwLsW1W3ACQ5CfgGcOQgA5OkRWauk7QcmOskjY1+7zO7Y8/y3QYQhyQtBTv2LJvrJI2rHXuWzXWSRlY/Z2b/CfhGks/RTeP+aPz2TtL4MddJWg7MdZLGRj8TQL0vyZnAb9AlvZdX1Q9m2y7JHYEvANu19zmlql6VZCfg/cAq4HLg96vqx22bI4FDgZuBv6qqT8+hT5K0xeaa6yT1b9URHx92CLdx+TFPGXYIi85cJ2mc9HNmlqq6Cjh1C/d9E/DYqrohybbAl5J8EngmcEZVHZPkCLp7nr08yd7AwcA+wK7AZ5Pcv6pu3sL3laQ5mWOuk6SRYq6TNC76vWZ2i1XnhvZ02/ZTwBrgpNZ+EnBgW14DnFxVN1XVZcAGYL9BxSdJkiRJGl0DK2YBkmyd5DzgGuD0qjoL2KV9IzjxzeA92+q7AVf0bL6xtU3e52FJ1iVZt2nTpkGGL0mSJElaomYsZpNsleTCue68qm6uqn2B3YH9kjxoprebahdT7PO4qlpdVatXrFgx19Ak6Zfmm+skaRSY6ySNmxmL2XYPsvOT7DmfN6mqa4EzgQOAq5OsBGiP17TVNgJ79Gy2O3DlfN5XkvqxULlOkpYyc52kcdPPBFArgfVJzgZunGisqqfPtFGSFcAvquraJHcCHg+8lm7CgUOAY9rjR9smpwLvTXIs3QRQewFnb1l3JGnO5pTrJGnEmOskjY1+itlXz3HfK4GTkmxNdwZ4bVWdluSrwNokhwLfAw4CqKr1SdYCFwGbgcOdyVjSIpprrpOkUWKukzQ2+rnP7OeT3BvYq6o+m+TOwNZ9bHcB8JAp2n8IPG6abY4Gjp41aklaYHPNdUlOAJ4KXFNVD2ptRwF/BkzMUveKqvpEe837aUsamrnmOklaimadzTjJnwGnAO9oTbsBHxlgTJK06OaR606kmw9gsjdV1b7tZ6KQ7b2f9gHA29roFUlaFB7XSRon/QwzPpzufq9nAVTVt5Pcc+ZNJGnkzCnXVdUXkqzq8z1+eT9t4LIkE/fT/urcQtZcrTri48MOQRoWj+skjY1+7jN7U1X9fOJJkm2Y4pY5kjTiFjrXvSDJBUlOSHL31tbX/bQlaYA8rpM0NvopZj+f5BXAnZL8LvAB4GODDUuSFt1C5rq3A/cD9gWuAt7Y2vu6nzZAksOSrEuybtOmTVOtIklz4XGdpLHRTzF7BN0kJt8Eng98Avi7QQYlSUOwYLmuqq6uqpvbPR3fSTekD7bgftpVdVxVra6q1StWrJhLGJI0FY/rJI2NfmYzviXJSXTXVhRwSVU5HEXSWFnIXJdkZVVd1Z4+A7iwLXs/bUlD5XGdpHHSz2zGTwG+A7wFeCuwIcmTBh2YJC2muea6JO+jm8DpAUk2tntovy7JN5NcAPwO8NfQ3U8bmLif9qfwftqSFtl8juvaHADXJLmwp+2oJN9Pcl77eXLPa0cm2ZDkkiRPXOi+SFI/sxm/EfidqtoAkOR+wMeBTw4yMElaZHPKdVX17Cmaj59hfe+nLWmY5nNcdyJdAfzuSe1vqqo39DZMuhXZrsBnk9zfL/AkLaR+rpm9ZiLhNZcC1wwoHkkaFnOdpOVgzrmuqr4A/KjP9/nlrciq6jJg4lZkkrRgpj0zm+SZbXF9kk/QDY0r4CDg64sQmyQNnLlO0nIw4Fz3giR/DKwDXlJVP6a77djXetbxVmSSFtxMw4yf1rN8NfCYtrwJuPvtV5ekkWSuk7QcDCrXvR14DV1h/Bq6Ycx/whbeigw4DGDPPfecRyiSlptpi9mqet5iBiJJw2Cuk7QcDCrXVdXVE8tJ3gmc1p5u0a3IgOMAVq9e7czKkvo26wRQSe4DvBBY1bt+VT19cGFJ0uIy10laDhY613krMknD1M9sxh+hm5nzY8AtA41GkobnI5jrJI2/jzDHXNduRbY/sHOSjcCrgP2T7Es3hPhy4PnQ3YosycStyDbjrcgkDUA/xez/VtVbBh6JJA2XuU7ScjDnXOetyCQtNf0Us29O8irgM8BNE41Vde7AopKkxWeuk7QcmOskjY1+itlfA54DPJZbh6NUey5J48JcJ2k5MNdJGhv9FLPPAO5bVT8fdDCSNETmOknLgblO0tjYqo91zgd2HHAckjRs5jpJy4G5TtLY6OfM7C7At5J8ndteW+HtKiSNE3OdpOXAXCdpbPRTzL5q4FFI0vCZ6yQtB+Y6SWNj1mK2qj6/GIFI0jCZ6yQtB+Y6SeNk1mI2yfV0s9wB3AHYFrixqu46yMAkaTGZ6yQtB+Y6SeOknzOzO/Q+T3IgsN+gApKkYTDXSVoOzHWSxkk/sxnfRlV9BO9FJmnMmeskLQfmOkmjrJ9hxs/seboVsJpbh6dI0lgw10laDsx1ksZJP7MZP61neTNwObBmINFI0vCY6yQtB+Y6SWOjn2tmn7cYgUjSMJnrJC0H5jpJ42TaYjbJ38+wXVXVawYQjyQtKnOdpOXAXCdpHM10ZvbGKdruAhwK3AMw6UkaB+Y6ScuBuU7S2Jm2mK2qN04sJ9kBeBHwPOBk4I3TbdezzR7Au4F7AbcAx1XVm5PsBLwfWEV3ncbvV9WP2zZH0iXVm4G/qqpPz6lXktSn+eY6SRoF5jpJ42jGW/Mk2SnJ/wMuoCt8H1pVL6+qa/rY92bgJVX1QODhwOFJ9gaOAM6oqr2AM9pz2msHA/sABwBvS7L1HPslSX2bZ66TpJFgrpM0bqYtZpO8Hvg6cD3wa1V11MQZ1H5U1VVVdW5bvh64GNiNbsa8k9pqJwEHtuU1wMlVdVNVXQZswJt4Sxqw+eY6SRoF5jpJ42imM7MvAXYF/g64Msl17ef6JNdtyZskWQU8BDgL2KWqroKu4AXu2VbbDbiiZ7ONrU2SBmnBcp0kLWHmOkljZ6ZrZmccgtyvJNsDHwReXFXXJZl21anCmGJ/hwGHAey5554LEaKkZWyhcp0kLWXmOknjaKCJLcm2dIXse6rqQ6356iQr2+srgYnrNDYCe/Rsvjtw5eR9VtVxVbW6qlavWLFicMFLkiRJkpasgRWz6U7BHg9cXFXH9rx0KnBIWz4E+GhP+8FJtktyH2Av4OxBxSdJCyHJCUmuSXJhT9tOSU5P8u32ePee145MsiHJJUmeOJyoJUmSRt8gz8w+EngO8Ngk57WfJwPHAL+b5NvA77bnVNV6YC1wEfAp4PCqunmA8UnSQjiRbgb2Xs7aLkmSNGDTXjM7X1X1Jaa+DhbgcdNsczRw9KBikqSFVlVfaJPc9VoD7N+WTwLOBF5Oz6ztwGVJJmZt/+qiBCtJkjRGnAxAkhaes7ZLkiQNmMWsJC2evmZth27m9iTrkqzbtGnTgMOSJEkaPRazkrTw5jVrOzhzu6SlxwnvJC01FrOStPCctV3SODoRJ7yTtIRYzErSPCR5H90ETg9IsjHJoThru6QxVFVfAH40qXkN3UR3tMcDe9pPrqqbquoyYGLCO0laMAObzViSloOqevY0Lzlru6Tl4DYT3iXpnfDuaz3rOeGdpAXnmVlJkiQtNCe8kzRwFrOSJEmaKye8kzQ0FrOSJEmaKye8kzQ0XjMrSZKkWbUJ7/YHdk6yEXgV3QR3a9vkd98DDoJuwrskExPebcYJ7yQNgMWsJEmSZuWEd5KWGocZS5IkSZJGjsWsJEmSJGnkWMxKkiRJkkaOxawkSZIkaeRYzEqSJEmSRo7FrCRJkiRp5FjMSpIkSZJGjsWsJEmSJGnkWMxKkiRJkkaOxawkSZIkaeRYzEqSJEmSRo7FrCRJkiRp5FjMSpIkSZJGjsWsJEmSJGnkWMxKkiRJkkaOxawkSZIkaeRYzEqSJEmSRo7FrCRJkiRp5FjMSpIkSZJGjsWsJEmSJGnkDKyYTXJCkmuSXNjTtlOS05N8uz3evee1I5NsSHJJkicOKi5JkiRJ0ugb5JnZE4EDJrUdAZxRVXsBZ7TnJNkbOBjYp23ztiRbDzA2SZIkSdIIG1gxW1VfAH40qXkNcFJbPgk4sKf95Kq6qaouAzYA+w0qNkmSJEnSaFvsa2Z3qaqrANrjPVv7bsAVPettbG2SNLKSXJ7km0nOS7KutU17uYUkSZL6t1QmgMoUbTXlislhSdYlWbdp06YBhyVJ8/Y7VbVvVa1uz6e83EKSJElbZrGL2auTrARoj9e09o3AHj3r7Q5cOdUOquq4qlpdVatXrFgx0GAlaQCmu9xCkkaWI1EkDcNiF7OnAoe05UOAj/a0H5xkuyT3AfYCzl7k2CRpoRXwmSTnJDmstU13uYUkjTpHokhaVNsMasdJ3gfsD+ycZCPwKuAYYG2SQ4HvAQcBVNX6JGuBi4DNwOFVdfOgYpOkRfLIqroyyT2B05N8q98NW/F7GMCee+45qPgkaZDW0B0LQjcS5Uzg5cMKRtL4GVgxW1XPnualx02z/tHA0YOKR5IWW1Vd2R6vSfJhulnar06ysqqumnS5xeRtjwOOA1i9evWUcwhI0hIyMRKlgHe0HHabkSjtiz1JWjBLZQIoSRorSe6SZIeJZeAJwIVMf7mFJI2yR1bVQ4EnAYcneXS/Gzq5p6S5GtiZWUla5nYBPpwEulz73qr6VJKvM8XlFpI0yhyJImkYLGYlaQCq6lLgwVO0/5BpLreQpFHURp9sVVXX94xE+QduHYlyDI5EkTQAFrOSJEmaD0eiSBoKi1lJkiTNmSNRJA2LxawkaeBWHfHxYYcgSZLGjLMZS5IkSZJGjsWsJEmSJGnkWMxKkiRJkkaOxawkSZIkaeRYzEqSJEmSRo6zGUuSJEkaCeMyO/7lxzxl2CGMBc/MSpIkSZJGjsWsJEmSJGnkOMx4AQ162IPDESRJkiSp45lZSZIkSdLIsZiVJEmSJI0ci1lJkiRJ0sixmJUkSZIkjRyLWUmSJEnSyLGYlSRJkiSNHItZSZIkSdLIsZiVJEmSJI0ci1lJkiRJ0sixmJUkSZIkjRyLWUmSJEnSyNlm2AFIkhbWqiM+PuwQJEmSBs4zs5IkSZKkkWMxK0mSJEkaORazkiRJkqSR4zWzkiRpWVpq15dffsxThh2CJI2UJVfMJjkAeDOwNfCuqjpmyCEtGYP+T9f/RKXFY66TtByY6yQN0pIaZpxka+BfgScBewPPTrL3cKOSpIVlrpO0HJjrJA3aUjszux+woaouBUhyMrAGuGioUWnZ86y4Fpi5TtJyYK6TFtBSuzRirhbyuHepFbO7AVf0PN8I/OaQYll2xuUPRIvPYn+LmeskLQfmOkkDtdSK2UzRVrdZITkMOKw9vSHJJVuw/52B/5ljbEvJOPRjHPoAC9SPvHYBIpmfJf3v0efn09uHew8smIWxELluqf2bGc/sllpMxjOzRY9nllw3VTwjn+tg3sd2i2HgvwtL4DhgKovyN7Bc+75E+w1Ls+/T5rqlVsxuBPboeb47cGXvClV1HHDcXHaeZF1VrZ57eEvDOPRjHPoA9mMpGbE+zDvXLbX+Gs/sllpMxjMz41kQs+Y6mN+x3WIY0c9+3pZrv8G+j1Lfl9QEUMDXgb2S3CfJHYCDgVOHHJMkLTRznaTlwFwnaaCW1JnZqtqc5AXAp+mmcD+hqtYPOSxJWlDmOknLgblO0qAtqWIWoKo+AXxiQLtfskNYttA49GMc+gD2YykZqT4sQK5bav01ntkttZiMZ2bGswAGfFy3WEbys18Ay7XfYN9HRqpudx2+JEmSJElL2lK7ZlaSJEmSpFktm2I2yQFJLkmyIckRw46nV5I9knwuycVJ1id5UWvfKcnpSb7dHu/es82RrS+XJHliT/vDknyzvfaWJFNNiz/Ivmyd5BtJThvhPuyY5JQk32r/Jo8Y0X78dft9ujDJ+5LccRT6keSEJNckubCnbcHiTrJdkve39rOSrBpkf+ZjutwwaZ20/m1IckGShw45nv2T/CTJee3n7wcYzx2TnJ3k/BbPq6dYZzE/n37iWbTPp+c9b5OXJ722aJ9Pn/EM4/O5vOWK85Ksm+L1Rf2M+ohn0T8jSVqyqmrsf+gmHfgOcF/gDsD5wN7DjqsnvpXAQ9vyDsB/A3sDrwOOaO1HAK9ty3u3PmwH3Kf1bev22tnAI+ju7fZJ4EmL3Je/Ad4LnNaej2IfTgL+tC3fAdhx1PpBd6P6y4A7tedrgeeOQj+ARwMPBS7saVuwuIG/BP6tLR8MvH8xf7+28LOYMjdMWufJrX8BHg6cNeR49p/4+1+EzyfA9m15W+As4OFD/Hz6iWfRPp+e97xNXh7W59NnPMP4fC4Hdp7h9UX9jPqIZ9E/o+X8A6wCnjvsOIbdX+CoYcc27L6O+u/CQvZ3Kf0+LJczs/sBG6rq0qr6OXAysGbIMf1SVV1VVee25euBi+mKkTV0hRXt8cC2vAY4uapuqqrLgA3AfklWAnetqq9W95v27p5tBi7J7sBTgHf1NI9aH+5KV0wdD1BVP6+qa0etH802wJ2SbAPcme7efku+H1X1BeBHk5oXMu7efZ0CPG7QZ5vnaobc0GsN8O7qfA3YsfV/WPEsmtbnG9rTbdvP5IkgFvPz6SeeRTVNXu61aJ9Pn/EsRYv6GWnpSPIXdDMxvybJmUnuNeyYBmmq/ibZNckngb9sIwH+eshhLogt7euo/y4sVH+X4u/DkpvNeEB2A67oeb4R+M0hxTKjdEMeH0L3jf4uVXUVdAeRSe7ZVtsN+FrPZhtb2y/a8uT2xfLPwMvozthMGLU+3BfYBPx7kgcD5wAvYsT6UVXfT/IG4HvAz4DPVNVnkoxUP3osZNy/zAfV3TbiJ8A9gP8ZXPjzNyk39Joqv+0GXDWkeAAekeR8ui9QXloDvBVHkq3p/k5/BfjXqhrq59NHPLCInw9T5+Vei/37M1s8sLifD3RfOHwmSQHvqKrJM3ku9mc0Wzyw+J/RspNkB+DVwNOABwJnAjcOM6ZBmqG/r6TLaWcBR9PltpG2pX0d9d+FBe7vi6faZpiWy5nZqc66LLlpnJNsD3wQeHFVXTfTqlO01QztA5fkqcA1VXVOv5tM0TbUPjTb0A1xfXtVPYTuj3ema6yXZD/SXVO6hm7o7a7AXZL80UybTNE29H70YS5xL/U+3c4suWHR+zNLPOcC966qBwP/AnxkkLFU1c1VtS+wO91Z+QdNDneqzYYYz6J9Pn3m5UX7fPqMZ1F/f5pHVtVDgScBhyd59KTXF/tvbLZ4hvEZLUe30F1qdFeAqrq8jUgZV9P19+d0X/huW1W/qKqLhxjjQtnSvo7678JC9nfJ/T4sl2J2I7BHz/Pd6b7NXDKSbEt3cPieqvpQa756YihTe7ymtU/Xn41teXL7Yngk8PQkl9MN435skv9ktPowEdfGnrMpp9AVt6PWj8cDl1XVpqr6BfAh4LcYvX5MWMi4f7lNG4J9N24/rHnJmCY39FrU/DZbPFV13cRQ2+ruL7ltkp0HFU/P+15L9+3xAZNeGkr+ny6eRf58psvLvRbz85k1nmH8/lTVle3xGuDDdJcm9VrU36HZ4hnW39hyU1U3An8M/CPdUMs3JLnzkMMamBn6+3q6euH5Sc5Isv/wolwYW9rXUf9dWOD+Lr3fh1oCF+4O+ofubNuldGepJiaA2mfYcfXEF7pr+v55Uvvrue2kN69ry/tw20lvLuXWSW++TjdBxcSkN08eQn/259YJoEauD8AXgQe05aNaH0aqH3TD6NfTXSsbumtEXzgq/aCbdKB3AqgFixs4nNtOALV2sf9GtuBzmDI3TFrnKdx2cpqzhxzPvbj1Hub70Q11z4DiWQHs2Jbv1P52nzrEz6efeBbt85n0vvsz9YRLi/b59BnPon4+wF2AHXqWvwIcMMTfoX7iGcrv0HL9af8fvZDu/9FXDjueYfWX7njoEXRfJt9x2HEOo6+j/ruwkP1dSr8Py+Ka2equi3sB3YXMWwMn1NK6vuSRwHOAbyY5r7W9AjgGWJvkULr/rA4CqKr1SdYCFwGbgcOr6ua23V8AJ9IdSH2y/QzTKPbhhcB7ktyBrjh6Ht23UCPTj6o6K8kpdMPRNgPfAI4Dtl/q/UjyProD3Z2TbARexcL+Hh0P/EeSDXRnZA8eZH/mabrcsCdAVf0b8Am62VY3AD+l+30dZjy/B/xFks1012sfXO1/vgFYCZzUrlPdiu6LidOS/HlPPIv5+fQTz2J+PlMa4ufTTzyL/fnsAnw43Rxw2wDvrapPDfEz6ieeof8OLQftcop7tKcTE97tNLyIBmu6/iZ5IHBJa/8m3RDUbYH/XfQgF8iW9rWN4hrZ34WF7O9S/H2I+U+SJEm6VZt74n3AznQH9t8D/qCqvj/UwAZkuv7SXbv9p3Rf1t1AN7LpX4YV50LY0r6O+u/CQvY3yZ9Otc0id+k2LGYlSZKkKbSZ2/evqhOHHMqimK6/SY6qqqOGEdOgbGlfR/13YSH7u5R+H5bLBFCSJEnSlroWOG/IMSyma5m6v2cuahSL41q2rK/TrT8qrmXh+jvdNovOM7OSJEmSpJHjmVlJkiRJ0sixmJUkSZIkjRyLWf1Skkryxp7nL01y1ALt+8Qkv7cQ+5rlfQ5KcnGSz01qX5XkZ0nOS3JRkncn2XaO7/GuJHsvTMSSlqMkN7d8dGGSjyXZcZb1903y5J7nT09yxMADlbRsTMpLH0hy52nW+8oCvd+Tkqxrx23fSvKGWdbfP8lvLcR7a3xYzKrXTcAzk+w87EB6tXs29utQ4C+r6nemeO07VbUv8GvA7sDvzyWeqvrTqrpoLttKUvOzqtq3qh5Ed7/jw2dZf1+6e50CUFWnVtUxA4xP0vLTm5d+Dvx574sTx2NVNe+CMsmDgLcCf1RVDwQeBFw6y2b7AwMtZtOxPhoh/mOp12bgOOCvJ78w+cxqkhva4/5JPp9kbZL/TnJMkj9McnaSbya5X89uHp/ki229p7btt07y+iRfT3JBkuf37PdzSd5Ld1PmyfE8u+3/wiSvbW1/DzwK+Lckr5+uk1V1M3A2sFvb7mGtD+ck+XSSlUkemOTsnvdbleSCtnxmktVt+QlJvprk3PYt5vZJ9kvyofb6mnZG+A5J7pjk0tb+V+0M8QVJTp79n0bSGPsqt+aj/ZJ8Jck32uMDktwB+AfgWe2sybOSPDfJW9s2JyZ5S1v/0olcnWSrJG9Lsj7JaUk+sRgjZCSNhS8CvzLV8djEMWBbflk7Hjs/yTGt7X5JPtWOq76Y5Fen2P/LgKOr6lsAVbW5qt7Wtn9akrNaHvxskl3S3Sbmz4G/bnnwt5OsSPLBdgz59SSPbNuvSHJ6OzZ7R5LvTpyoSfI37djxwiQvbm2r0p0dfhtwLvDKJG/q6eOfJTl2YT9eLZRthh2Alpx/BS5I8rot2ObBwAPpzi5cCryrqvZL8iLghcCL23qrgMcA9wM+l+RXgD8GflJVv5FkO+DLST7T1t8PeFBVXdb7Zkl2BV4LPAz4MfCZJAdW1T8keSzw0qpaN12wSe4I/CbwonRDjf8FWFNVm5I8iy65/kkrQO9bVZcCzwLWTtrPzsDfAY+vqhuTvBz4G+AfgYe01X4buBD4Dbq/t7Na+xHAfarqpswyvFDS+Ep3puNxwPGt6VvAo6tqc5LHA/9YVf+nfVm3uqpe0LZ77qRdraT7Mu9XgVOBU4Bn0uXdXwPuCVwMnDDQDkkaeUm2AZ4EfKo1TXc89iTgQOA3q+qnSXZqLx0H/HlVfTvJbwJvAx476W0eBLyRqX0JeHhVVZI/BV5WVS9J8m/ADVX1hvb+7wXeVFVfSrIn8Gm649FXAf9VVf+U5ADgsLb+w4Dn0R0DBjgryefpjiUfADyvqv4yyV3ojoVfVlW/aNs8fws+Qi0ii1ndRlVdl+TdwF8BP+tzs69X1VUASb4DTBSj3wR6h/uurapbgG+3M5S/CjwB+PWeswV3A/aiG95y9uTE2fwGcGZVbWrv+R7g0cBHZonzfknOa/s/paouSDfM5UHA6UkAtgaumoiXbijyMXTF7LMm7e/hwN50BTjAHYCvtoPQDUkeSPcfwLEtvq3pvukEuAB4T5KP9BG3pPFzp5aPVgHnAKe39rsBJyXZCyig32v7P9Ly60VJdmltjwI+0Np/kElzCUjSJBN5CbrjlePphvVOdzz2eODfq+qnAFX1oyTbt20+0I6NALbbwjh2B96fZCXdsdVU7z3x/nv3vM9dk+xAl/ue0WL6VJIft9cfBXy4qm4ESDeK7rfpvgD8blV9rW1zY5L/Ap6a5GJg26q63ShBLQ0Ws5rKP9MNs/j3nrbNtGHp6bLGHXpeu6ln+Zae57dw29+xyTc1Lrpvxl5YVZ/ufSHJ/sCN08SXadpn852q2rclxzOTPJ0uQa6vqkdMsf776ZLxh4Cqqm9PEcfpVfXsKbb9It23mr8APgucSFfMvrS9/hS6AvfpdMNZ9qmqzXPsl6TR87OWj+4GnEZ3zexbgNcAn6uqZ7RhdWf2ub/ePJxJj5LUj5+1uUV+qRWKMx2PTT622wq4dvJ+prCeboTd+VO89i/AsVV1ajsePGqafWwFPKKqbnPyJT3V7RTxTmdyH98FvIJutMy/3351LRVeM6vbqaof0Z2VPLSn+XK6pAOwhv7PFvQ6qF3DdT/gvsAldENC/qIN9yXJ/dvwjpmcBTwmyc5tiN6zgc/3G0Q7i3wEcGSLYUWSR7T33zbJPm297wA3A6+kK2wn+xrwyDZcmiR3TnL/9toX6IZXf7WdQb4H3Zno9ekmFtijqj5Hd83IjsD2/cYvaXxU1U/oRsK8tOXBuwHfby8/t2fV64EdtnD3XwL+T8u7u9BNniJJC+UzwJ+kzXqcZKequg64LMlBrS1JHjzFtq8HXjFx3NTy1N+013rz4CE920zOg58BXjDxJMm+bfFLtEk+kzwBuHtr/wJwYDteuwvd2dsvMoWqOgvYA/gD4H0zfQgaLotZTeeNQO+sxu+kKyDPprvWYLpv6WZyCV3R+Um6ayn+l+6br4uAc5NcCLyDWUYMtGL0SOBzdN/onVtVH93CWD4C3JmuL78HvDbJ+cB53HamvPcDf8Sk62VbHJvoDjbfl25yqK/RFazQFdy70CVO6IYVX1BVRXeG9j+TfBP4Bt31HtduYfySxkRVfYMulx0MvA74pyRfpssVEz5HN5zuvHZtfz8+CGyku27/HXR56ScLFrikZa2qPkU3RHddG548MfrsD4FD23HVerqTIJO3vYDuS//3taG8F9Jd+w/dmdgPJPki8D89m30MeEbLg79N90Xg6nSTaV7ErbMvvxp4QpJz6UbJXQVcX1Xn0o2UO5suH76r5d/prAW+XFU/nmEdDVm6Y2tJkjRukmxfVTckuQfdAdwjq+oHw45LkgalTSh6c5vD5BHA2/sY9jzVfk6jO+FwxkLHqIXjNbOSJI2v09qM6XcAXmMhK2kZ2BNY2y7r+jnwZ1uyccuZZwPnW8gufZ6ZlSRJkiSNHK+ZlSRJkiSNHItZSZIkSdLIsZiVJEmSJI0ci1lJkiRJ0sixmJUkSZIkjRyLWUmSJEnSyPn/AmxIvTfvU9cAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1152x360 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Run this cell without changes\n",
    "from collections import Counter\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "fig, (ax1, ax2, ax3) = plt.subplots(ncols=3, figsize=(16, 5))\n",
    "\n",
    "# Plot distribution of number of reviews\n",
    "all_review_counts = [x[\"review_count\"] for x in full_dataset]\n",
    "ax1.hist(all_review_counts)\n",
    "ax1.set_title(\"Review Count Distribution\")\n",
    "ax1.set_xlabel(\"Number of Reviews\")\n",
    "ax1.set_ylabel(\"Number of Businesses\")\n",
    "\n",
    "# Plot rating distribution\n",
    "all_ratings = [x[\"rating\"] for x in full_dataset]\n",
    "rating_counter = Counter(all_ratings)\n",
    "rating_keys = sorted(rating_counter.keys())\n",
    "ax2.bar(rating_keys, [rating_counter[key] for key in rating_keys])\n",
    "ax2.set_title(\"Rating Distribution\")\n",
    "ax2.set_xlabel(\"Rating\")\n",
    "ax2.set_ylabel(\"Number of Businesses\")\n",
    "\n",
    "# Plot price distribution\n",
    "all_prices = [x[\"price\"].replace(\"$\", r\"\\$\") for x in full_dataset]\n",
    "price_counter = Counter(all_prices)\n",
    "price_keys = sorted(price_counter.keys())\n",
    "ax3.bar(price_keys, [price_counter[key] for key in price_keys])\n",
    "ax3.set_title(\"Price Distribution\")\n",
    "ax3.set_xlabel(\"Price Category\")\n",
    "ax3.set_ylabel(\"Number of Businesses\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Describe the distributions displayed above and interpret them in the context of your query. (Your answer may differ from the solution branch depending on your query.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "The distribution of review counts shows that majority of the businesses (about 700 out of 726) in New York \n",
      "have between 0 and 1,000 reviews. There are very few outliers with more than 5,000 reviews.\n",
      "\n",
      "From the distribution of review counts, we can see that about half of the businesses (about 350 out of 726) \n",
      "have a review count of 4.0. This appears to be a relatively normal distribution of reviews.\n",
      "\n",
      "From the distribution of price category, we can see that majority of the businesses (more than 650 out of 726) \n",
      "are in the lower price categories of $ and $$.\n",
      "\n",
      "However, there is no way to establish the relationships between and amongst the variables, such as the relationship \n",
      "between the price category and the number of reviews, or the relationship between the price category and the review rating.\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Replace None with appropriate text\n",
    "print(\"\"\"\n",
    "The distribution of review counts shows that majority of the businesses (about 700 out of 726) in New York \n",
    "have between 0 and 1,000 reviews. There are very few outliers with more than 5,000 reviews.\n",
    "\n",
    "From the distribution of review counts, we can see that about half of the businesses (about 350 out of 726) \n",
    "have a review count of 4.0. This appears to be a relatively normal distribution of reviews.\n",
    "\n",
    "From the distribution of price category, we can see that majority of the businesses (more than 650 out of 726) \n",
    "are in the lower price categories of $ and $$.\n",
    "\n",
    "However, there is no way to establish the relationships between and amongst the variables, such as the relationship \n",
    "between the price category and the number of reviews, or the relationship between the price category and the review rating.\n",
    "\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the cell below, we also plot the rating distributions by price. In this setup, a price of one dollar sign is \"lower price\" and everything else is \"higher price\"."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Run this cell without changes\n",
    "\n",
    "higher_price = []\n",
    "lower_price = []\n",
    "for row in full_dataset:\n",
    "    if row[\"price\"] == \"$\":\n",
    "        lower_price.append(row[\"rating\"])\n",
    "    else:\n",
    "        higher_price.append(row[\"rating\"])\n",
    "        \n",
    "fig, ax = plt.subplots()\n",
    "\n",
    "ax.hist([higher_price, lower_price], label=[\"higher price\", \"lower price\"])\n",
    "\n",
    "ax.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Is a higher price associated with a higher rating? (No need for any additional math/statistics, just interpret what you see in the plot.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "The histogram shows that the distribution of ratings is closely similar between the lower priced and higher-priced businesses.\n",
      "Majority of the businesses in both categories have a rating of 4.0 and both distributions appear relatively normal.\n",
      "\n",
      "However, between a rating of 2.5 and 3.5, lower-priced businesses have about twice the number of ratings of higher-priced businesses.\n",
      "Between a rating of 4.0 and 5.0, lower-priced businesses have slighly lower numbers of ratings than higher-priced businesses.\n",
      "This could indicate that lower-price customers are more impressed by the price while higher-price customers are more \n",
      "impressed by the quality of service.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Replace None with appropriate text\n",
    "print(\"\"\"\n",
    "The histogram shows that the distribution of ratings is closely similar between the lower priced and higher-priced businesses.\n",
    "Majority of the businesses in both categories have a rating of 4.0 and both distributions appear relatively normal.\n",
    "\n",
    "However, between a rating of 2.5 and 3.5, lower-priced businesses have about twice the number of ratings of higher-priced businesses.\n",
    "Between a rating of 4.0 and 5.0, lower-priced businesses have slighly lower numbers of ratings than higher-priced businesses.\n",
    "This could indicate that lower-price customers are more impressed by the price while higher-price customers are more \n",
    "impressed by the quality of service.\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, let's look at ratings vs. review counts:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Run this cell without changes\n",
    "fig, ax = plt.subplots(figsize=(16,5))\n",
    "\n",
    "ax.scatter(all_review_counts, all_ratings, alpha=0.2)\n",
    "ax.set_xlabel(\"Number of Reviews\")\n",
    "ax.set_ylabel(\"Rating\")\n",
    "# \"zoom in\" to a subset of review counts\n",
    "ax.set_xlim(left=0, right=1000);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Is a higher number of reviews associated with a higher rating?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "The scatter plot of rating against number of reviews shows a low density of reviews in the lower ratings of 2.5 and 3.5.\n",
      "\n",
      "The plot has a higher density of reviews between the ratings of 3.5 and 4.5, with 4.0 having the highest density of ratings.\n",
      "\n",
      "There are only a handful of reviews for businesses that were rated 5.0.\n",
      "\n",
      "The general trend is that reviewers are intentional, and thus a higher number of reviews is associated with a higher rating. \n",
      "This means that most of those who leave a low rating of between 2.5 and 3.0 are so disappointed with the business that they don't \n",
      "bother reviewing it.\n",
      "On the other hand, those who leave a higher rating of between 3.5 and 4.5 have been impressed or satisfied with the \n",
      "quality of service, and therefore, they're intentional and thoughful in leaving a review and a rating.\n",
      "\n",
      "Those who leave a rating of 5.0 may be satisfied with the business but most of them are not intentional enough to take \n",
      "the time to write a review.\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Replace None with appropriate text\n",
    "\n",
    "print(\"\"\"\n",
    "The scatter plot of rating against number of reviews shows a low density of reviews in the lower ratings of 2.5 and 3.5.\n",
    "\n",
    "The plot has a higher density of reviews between the ratings of 3.5 and 4.5, with 4.0 having the highest density of ratings.\n",
    "\n",
    "There are only a handful of reviews for businesses that were rated 5.0.\n",
    "\n",
    "The general trend is that reviewers are intentional, and thus a higher number of reviews is associated with a higher rating. \n",
    "This means that most of those who leave a low rating of between 2.5 and 3.0 are so disappointed with the business that they don't \n",
    "bother reviewing it.\n",
    "On the other hand, those who leave a higher rating of between 3.5 and 4.5 have been impressed or satisfied with the \n",
    "quality of service, and therefore, they're intentional and thoughful in leaving a review and a rating.\n",
    "\n",
    "Those who leave a rating of 5.0 may be satisfied with the business but most of them are not intentional enough to take \n",
    "the time to write a review.\n",
    "\n",
    "\"\"\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Create a Folium Map\n",
    "\n",
    "Make a map using Folium of the businesses you retrieved. Be sure to also add popups to the markers giving some basic information such as name, rating and price.\n",
    "\n",
    "You can center the map around the latitude and longitude of the first item in `full_dataset`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe src=\"about:blank\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" data-html=<!DOCTYPE html>
<head>    
    <meta http-equiv="content-type" content="text/html; charset=UTF-8" />
    
        <script>
            L_NO_TOUCH = false;
            L_DISABLE_3D = false;
        </script>
    
    <script src="https://cdn.jsdelivr.net/npm/leaflet@1.6.0/dist/leaflet.js"></script>
    <script src="https://code.jquery.com/jquery-1.12.4.min.js"></script>
    <script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/js/bootstrap.min.js"></script>
    <script src="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js"></script>
    <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/leaflet@1.6.0/dist/leaflet.css"/>
    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap.min.css"/>
    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap-theme.min.css"/>
    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/font-awesome/4.6.3/css/font-awesome.min.css"/>
    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css"/>
    <link rel="stylesheet" href="https://rawcdn.githack.com/python-visualization/folium/master/folium/templates/leaflet.awesome.rotate.css"/>
    <style>html, body {width: 100%;height: 100%;margin: 0;padding: 0;}</style>
    <style>#map {position:absolute;top:0;bottom:0;right:0;left:0;}</style>
    
            <meta name="viewport" content="width=device-width,
                initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />
            <style>
                #map_ea7523b0f91c4818ab5cf54c96c5f31a {
                    position: relative;
                    width: 100.0%;
                    height: 100.0%;
                    left: 0.0%;
                    top: 0.0%;
                }
            </style>
        
</head>
<body>    
    
            <div class="folium-map" id="map_ea7523b0f91c4818ab5cf54c96c5f31a" ></div>
        
</body>
<script>    
    
            var map_ea7523b0f91c4818ab5cf54c96c5f31a = L.map(
                "map_ea7523b0f91c4818ab5cf54c96c5f31a",
                {
                    center: [40.72308755605564, -73.99453001177575],
                    crs: L.CRS.EPSG3857,
                    zoom: 13,
                    zoomControl: true,
                    preferCanvas: false,
                }
            );

            

        
    
            var tile_layer_ac35791627a64b4c9e99ab877e5a78da = L.tileLayer(
                "https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png",
                {"attribution": "Data by \u0026copy; \u003ca href=\"http://openstreetmap.org\"\u003eOpenStreetMap\u003c/a\u003e, under \u003ca href=\"http://www.openstreetmap.org/copyright\"\u003eODbL\u003c/a\u003e.", "detectRetina": false, "maxNativeZoom": 18, "maxZoom": 18, "minZoom": 0, "noWrap": false, "opacity": 1, "subdomains": "abc", "tms": false}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
            var marker_27dda51f5522495592c2e36dba52f831 = L.marker(
                [40.72308755605564, -73.99453001177575],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_e425063dc0e14b57878711d33a0c613e = L.popup({"maxWidth": "100%"});

        
            var html_bbb0553fe85a44b9899a9e8238007ae2 = $(`<div id="html_bbb0553fe85a44b9899a9e8238007ae2" style="width: 100.0%; height: 100.0%;">Prince Street Pizza Price: $ Rating:4.5</div>`)[0];
            popup_e425063dc0e14b57878711d33a0c613e.setContent(html_bbb0553fe85a44b9899a9e8238007ae2);
        

        marker_27dda51f5522495592c2e36dba52f831.bindPopup(popup_e425063dc0e14b57878711d33a0c613e)
        ;

        
    
    
            var marker_aac8ba96e738467799208d884ba8ea25 = L.marker(
                [40.70274718768062, -73.99343490196397],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_243d4b655e7f4571a06d9bcbb3d2d37e = L.popup({"maxWidth": "100%"});

        
            var html_a3bab6a7232040a8a07a9fd13a434eab = $(`<div id="html_a3bab6a7232040a8a07a9fd13a434eab" style="width: 100.0%; height: 100.0%;">Juliana&#39;s Price: $$ Rating:4.5</div>`)[0];
            popup_243d4b655e7f4571a06d9bcbb3d2d37e.setContent(html_a3bab6a7232040a8a07a9fd13a434eab);
        

        marker_aac8ba96e738467799208d884ba8ea25.bindPopup(popup_243d4b655e7f4571a06d9bcbb3d2d37e)
        ;

        
    
    
            var marker_c6ca2831243840dab59d55e55efd3fcf = L.marker(
                [40.722766, -73.996233],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_f892b3cd7264418faaf87827792a6403 = L.popup({"maxWidth": "100%"});

        
            var html_d1943ce8966e4cbeb1c86a3270dd0bb8 = $(`<div id="html_d1943ce8966e4cbeb1c86a3270dd0bb8" style="width: 100.0%; height: 100.0%;">Rubirosa Price: $$ Rating:4.5</div>`)[0];
            popup_f892b3cd7264418faaf87827792a6403.setContent(html_d1943ce8966e4cbeb1c86a3270dd0bb8);
        

        marker_c6ca2831243840dab59d55e55efd3fcf.bindPopup(popup_f892b3cd7264418faaf87827792a6403)
        ;

        
    
    
            var marker_44f8612465b84dc7aaa49e451b39807a = L.marker(
                [40.71162, -73.95783],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_5a1e7994700a4e1cb79fc2774b7f86d6 = L.popup({"maxWidth": "100%"});

        
            var html_638acc1ec2384fb5847c363c38c92e81 = $(`<div id="html_638acc1ec2384fb5847c363c38c92e81" style="width: 100.0%; height: 100.0%;">L&#39;industrie Pizzeria Price: $ Rating:4.5</div>`)[0];
            popup_5a1e7994700a4e1cb79fc2774b7f86d6.setContent(html_638acc1ec2384fb5847c363c38c92e81);
        

        marker_44f8612465b84dc7aaa49e451b39807a.bindPopup(popup_5a1e7994700a4e1cb79fc2774b7f86d6)
        ;

        
    
    
            var marker_472cd8e639d24849b6ab91ff28782139 = L.marker(
                [40.7215934960083, -73.9955956044561],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_4823af24911b4af1aba444c35a21ef91 = L.popup({"maxWidth": "100%"});

        
            var html_76e1827637164855831c591b9821f717 = $(`<div id="html_76e1827637164855831c591b9821f717" style="width: 100.0%; height: 100.0%;">Lombardi&#39;s Pizza Price: $$ Rating:4.0</div>`)[0];
            popup_4823af24911b4af1aba444c35a21ef91.setContent(html_76e1827637164855831c591b9821f717);
        

        marker_472cd8e639d24849b6ab91ff28782139.bindPopup(popup_4823af24911b4af1aba444c35a21ef91)
        ;

        
    
    
            var marker_bac09aeb01b04da78a97d2011cbf2513 = L.marker(
                [40.73060076, -74.00215997],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_c5cabf3cdb0647cfbbbb32bfc3f3f355 = L.popup({"maxWidth": "100%"});

        
            var html_8699e7a5944649a7b168d3311d4f78e0 = $(`<div id="html_8699e7a5944649a7b168d3311d4f78e0" style="width: 100.0%; height: 100.0%;">Joe&#39;s Pizza Price: $ Rating:4.0</div>`)[0];
            popup_c5cabf3cdb0647cfbbbb32bfc3f3f355.setContent(html_8699e7a5944649a7b168d3311d4f78e0);
        

        marker_bac09aeb01b04da78a97d2011cbf2513.bindPopup(popup_c5cabf3cdb0647cfbbbb32bfc3f3f355)
        ;

        
    
    
            var marker_d554dcef79de404996489e8af6ecb9ed = L.marker(
                [40.7547, -73.98696],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_a7f39a1748864511a095ad137a5bccc7 = L.popup({"maxWidth": "100%"});

        
            var html_dbeedc687de04679a1477cc31f8e7bb5 = $(`<div id="html_dbeedc687de04679a1477cc31f8e7bb5" style="width: 100.0%; height: 100.0%;">Joe&#39;s Pizza Price: $ Rating:4.0</div>`)[0];
            popup_a7f39a1748864511a095ad137a5bccc7.setContent(html_dbeedc687de04679a1477cc31f8e7bb5);
        

        marker_d554dcef79de404996489e8af6ecb9ed.bindPopup(popup_a7f39a1748864511a095ad137a5bccc7)
        ;

        
    
    
            var marker_8365413bfcc641768ae183260029fc09 = L.marker(
                [40.73331, -73.98763],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_0e296f3ad2ae43099c55c4b3ee918540 = L.popup({"maxWidth": "100%"});

        
            var html_51e878892a524c49a626784a23c2ce3f = $(`<div id="html_51e878892a524c49a626784a23c2ce3f" style="width: 100.0%; height: 100.0%;">Joe&#39;s Pizza Price: $ Rating:4.0</div>`)[0];
            popup_0e296f3ad2ae43099c55c4b3ee918540.setContent(html_51e878892a524c49a626784a23c2ce3f);
        

        marker_8365413bfcc641768ae183260029fc09.bindPopup(popup_0e296f3ad2ae43099c55c4b3ee918540)
        ;

        
    
    
            var marker_5f3bb28302b74bf38aa872ede7b64075 = L.marker(
                [40.7026459, -73.9932413],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_68741d5c12254f08ad3cdf53d7c644e1 = L.popup({"maxWidth": "100%"});

        
            var html_c0317960cfe34e76ade6e33a01f915d3 = $(`<div id="html_c0317960cfe34e76ade6e33a01f915d3" style="width: 100.0%; height: 100.0%;">Grimaldi&#39;s Pizzeria Price: $$ Rating:3.5</div>`)[0];
            popup_68741d5c12254f08ad3cdf53d7c644e1.setContent(html_c0317960cfe34e76ade6e33a01f915d3);
        

        marker_5f3bb28302b74bf38aa872ede7b64075.bindPopup(popup_68741d5c12254f08ad3cdf53d7c644e1)
        ;

        
    
    
            var marker_8fc973e5e4fc40458de3bb5af759db03 = L.marker(
                [40.76337, -73.915124],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_18cfe7b2163a41a8b2700f7f0c79662d = L.popup({"maxWidth": "100%"});

        
            var html_b69513203b8d403ea06d4a0a82aa9aff = $(`<div id="html_b69513203b8d403ea06d4a0a82aa9aff" style="width: 100.0%; height: 100.0%;">Rizzo&#39;s Fine Pizza Price: $ Rating:4.0</div>`)[0];
            popup_18cfe7b2163a41a8b2700f7f0c79662d.setContent(html_b69513203b8d403ea06d4a0a82aa9aff);
        

        marker_8fc973e5e4fc40458de3bb5af759db03.bindPopup(popup_18cfe7b2163a41a8b2700f7f0c79662d)
        ;

        
    
    
            var marker_4c7d1418a3fc4314903e8442c5fe8b6c = L.marker(
                [40.681840746711224, -74.0003327],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_fb8ea1dc137d41f2bbc7854e797cbb1b = L.popup({"maxWidth": "100%"});

        
            var html_633de44036184af086290244fa4e3c1e = $(`<div id="html_633de44036184af086290244fa4e3c1e" style="width: 100.0%; height: 100.0%;">Lucali Price: $$ Rating:4.0</div>`)[0];
            popup_fb8ea1dc137d41f2bbc7854e797cbb1b.setContent(html_633de44036184af086290244fa4e3c1e);
        

        marker_4c7d1418a3fc4314903e8442c5fe8b6c.bindPopup(popup_fb8ea1dc137d41f2bbc7854e797cbb1b)
        ;

        
    
    
            var marker_75a3948ea498401eb396f78e3a39022c = L.marker(
                [40.7101297729083, -74.0077206864953],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_7a8a22fc30dc47739134d991d3f8660e = L.popup({"maxWidth": "100%"});

        
            var html_8c8a3c2e073a49c08de0bde04706f4ba = $(`<div id="html_8c8a3c2e073a49c08de0bde04706f4ba" style="width: 100.0%; height: 100.0%;">Joe&#39;s Pizza Price: $ Rating:4.0</div>`)[0];
            popup_7a8a22fc30dc47739134d991d3f8660e.setContent(html_8c8a3c2e073a49c08de0bde04706f4ba);
        

        marker_75a3948ea498401eb396f78e3a39022c.bindPopup(popup_7a8a22fc30dc47739134d991d3f8660e)
        ;

        
    
    
            var marker_d8a5be6f72624727938a6f3038ca516f = L.marker(
                [40.73158, -74.00332],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_4b3fc70e4aab4b25a5f37992e0dc9bc2 = L.popup({"maxWidth": "100%"});

        
            var html_b111bcaae62044b7a7def39555166738 = $(`<div id="html_b111bcaae62044b7a7def39555166738" style="width: 100.0%; height: 100.0%;">John&#39;s of Bleecker Street Price: $$ Rating:4.0</div>`)[0];
            popup_4b3fc70e4aab4b25a5f37992e0dc9bc2.setContent(html_b111bcaae62044b7a7def39555166738);
        

        marker_d8a5be6f72624727938a6f3038ca516f.bindPopup(popup_4b3fc70e4aab4b25a5f37992e0dc9bc2)
        ;

        
    
    
            var marker_c974b35a3a7d432bbb11fe1100453383 = L.marker(
                [40.7320627016512, -74.0036552270137],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_8d214c5a2a5948a59035fff2936e4330 = L.popup({"maxWidth": "100%"});

        
            var html_1f41c0bb17f545cbb766d9c19d52c175 = $(`<div id="html_1f41c0bb17f545cbb766d9c19d52c175" style="width: 100.0%; height: 100.0%;">Bleecker Street Pizza Price: $ Rating:4.0</div>`)[0];
            popup_8d214c5a2a5948a59035fff2936e4330.setContent(html_1f41c0bb17f545cbb766d9c19d52c175);
        

        marker_c974b35a3a7d432bbb11fe1100453383.bindPopup(popup_8d214c5a2a5948a59035fff2936e4330)
        ;

        
    
    
            var marker_1166ead1640f4024b81764ebf7784f63 = L.marker(
                [40.733798036104304, -73.99977392649927],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_ba9263fbb44d45cf814b64acfd54fd33 = L.popup({"maxWidth": "100%"});

        
            var html_0ec08c6a1c9048a0bcb85289ec5083cc = $(`<div id="html_0ec08c6a1c9048a0bcb85289ec5083cc" style="width: 100.0%; height: 100.0%;">Olio e Più Price: $$ Rating:4.5</div>`)[0];
            popup_ba9263fbb44d45cf814b64acfd54fd33.setContent(html_0ec08c6a1c9048a0bcb85289ec5083cc);
        

        marker_1166ead1640f4024b81764ebf7784f63.bindPopup(popup_ba9263fbb44d45cf814b64acfd54fd33)
        ;

        
    
    
            var marker_ae7334f332f64b16b959fdccafa50106 = L.marker(
                [40.71958, -73.99734],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_3cc31322e2d7457d9448c0068e37be1f = L.popup({"maxWidth": "100%"});

        
            var html_58219ac97db344f7874aff333d3eec63 = $(`<div id="html_58219ac97db344f7874aff333d3eec63" style="width: 100.0%; height: 100.0%;">Gelso &amp; Grand Price: $$ Rating:4.5</div>`)[0];
            popup_3cc31322e2d7457d9448c0068e37be1f.setContent(html_58219ac97db344f7874aff333d3eec63);
        

        marker_ae7334f332f64b16b959fdccafa50106.bindPopup(popup_3cc31322e2d7457d9448c0068e37be1f)
        ;

        
    
    
            var marker_92849027ebb24c0aaeb4de471a13a76c = L.marker(
                [40.70244, -73.98943],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_1b9a9f1ac9794063a15719a46ca3bd99 = L.popup({"maxWidth": "100%"});

        
            var html_c7c9d2b93317480993bd62243cfe67ff = $(`<div id="html_c7c9d2b93317480993bd62243cfe67ff" style="width: 100.0%; height: 100.0%;">Front Street Pizza Price: $ Rating:4.0</div>`)[0];
            popup_1b9a9f1ac9794063a15719a46ca3bd99.setContent(html_c7c9d2b93317480993bd62243cfe67ff);
        

        marker_92849027ebb24c0aaeb4de471a13a76c.bindPopup(popup_1b9a9f1ac9794063a15719a46ca3bd99)
        ;

        
    
    
            var marker_bc9db17a68044917b191ba99ae669aef = L.marker(
                [40.7168952, -73.95892996733771],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_4052aca4f58146eabcf71610d1e5f12f = L.popup({"maxWidth": "100%"});

        
            var html_e6ef7ed4042947548842dd485de5a011 = $(`<div id="html_e6ef7ed4042947548842dd485de5a011" style="width: 100.0%; height: 100.0%;">Joe&#39;s Pizza Price: $ Rating:4.0</div>`)[0];
            popup_4052aca4f58146eabcf71610d1e5f12f.setContent(html_e6ef7ed4042947548842dd485de5a011);
        

        marker_bc9db17a68044917b191ba99ae669aef.bindPopup(popup_4052aca4f58146eabcf71610d1e5f12f)
        ;

        
    
    
            var marker_279239efebab46588cc683dbc4787cd9 = L.marker(
                [40.70493, -73.93399],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_a479b15ffe7a47929c0857850958882a = L.popup({"maxWidth": "100%"});

        
            var html_4bea8ce43b54412eb8c023de70466c2c = $(`<div id="html_4bea8ce43b54412eb8c023de70466c2c" style="width: 100.0%; height: 100.0%;">Roberta&#39;s Price: $$ Rating:4.0</div>`)[0];
            popup_a479b15ffe7a47929c0857850958882a.setContent(html_4bea8ce43b54412eb8c023de70466c2c);
        

        marker_279239efebab46588cc683dbc4787cd9.bindPopup(popup_a479b15ffe7a47929c0857850958882a)
        ;

        
    
    
            var marker_4e53f54225914dd293619f6242be0951 = L.marker(
                [40.62207, -74.02591],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_5c77ee9acb13464ba9f70bd5611240b6 = L.popup({"maxWidth": "100%"});

        
            var html_23910eec0a1c419094e4da8005017c71 = $(`<div id="html_23910eec0a1c419094e4da8005017c71" style="width: 100.0%; height: 100.0%;">Mancini&#39;s Wood-Fired Pizza Price: $ Rating:4.5</div>`)[0];
            popup_5c77ee9acb13464ba9f70bd5611240b6.setContent(html_23910eec0a1c419094e4da8005017c71);
        

        marker_4e53f54225914dd293619f6242be0951.bindPopup(popup_5c77ee9acb13464ba9f70bd5611240b6)
        ;

        
    
    
            var marker_df8d356456f04e14842995350b0b3bf1 = L.marker(
                [40.729546, -73.958568],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_cdefabaceb5a403bacb705a8763f19cd = L.popup({"maxWidth": "100%"});

        
            var html_3fde0b3d132243b5976672c9da91a7f8 = $(`<div id="html_3fde0b3d132243b5976672c9da91a7f8" style="width: 100.0%; height: 100.0%;">Paulie Gee&#39;s Price: $$ Rating:4.5</div>`)[0];
            popup_cdefabaceb5a403bacb705a8763f19cd.setContent(html_3fde0b3d132243b5976672c9da91a7f8);
        

        marker_df8d356456f04e14842995350b0b3bf1.bindPopup(popup_cdefabaceb5a403bacb705a8763f19cd)
        ;

        
    
    
            var marker_1600124ebb3a4d258e6cfbd24574d34c = L.marker(
                [40.76458, -73.98247],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_eeb7081788b54637bf8e883aede85b08 = L.popup({"maxWidth": "100%"});

        
            var html_15f8044e0c85476fbbc0a61ca5622455 = $(`<div id="html_15f8044e0c85476fbbc0a61ca5622455" style="width: 100.0%; height: 100.0%;">99 Cent Fresh Pizza Price: $ Rating:4.0</div>`)[0];
            popup_eeb7081788b54637bf8e883aede85b08.setContent(html_15f8044e0c85476fbbc0a61ca5622455);
        

        marker_1600124ebb3a4d258e6cfbd24574d34c.bindPopup(popup_eeb7081788b54637bf8e883aede85b08)
        ;

        
    
    
            var marker_41c74d2552cf4742b86e61c58b522a50 = L.marker(
                [40.6897, -73.965369],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_b6bc40878c354367a475326259e3eb04 = L.popup({"maxWidth": "100%"});

        
            var html_afdb575f0f764bcf9da31a65e9c4fc57 = $(`<div id="html_afdb575f0f764bcf9da31a65e9c4fc57" style="width: 100.0%; height: 100.0%;">Luigi&#39;s Pizzeria Price: $ Rating:4.5</div>`)[0];
            popup_b6bc40878c354367a475326259e3eb04.setContent(html_afdb575f0f764bcf9da31a65e9c4fc57);
        

        marker_41c74d2552cf4742b86e61c58b522a50.bindPopup(popup_b6bc40878c354367a475326259e3eb04)
        ;

        
    
    
            var marker_d4a7441ac5754400ab59397ddc52243a = L.marker(
                [40.723625, -73.988555],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_ae6689f00246470bb4277f72e2c0e2a9 = L.popup({"maxWidth": "100%"});

        
            var html_af611c6654be4cd5a1d925e7bf0c8c3f = $(`<div id="html_af611c6654be4cd5a1d925e7bf0c8c3f" style="width: 100.0%; height: 100.0%;">Lil Frankie&#39;s Price: $$ Rating:4.0</div>`)[0];
            popup_ae6689f00246470bb4277f72e2c0e2a9.setContent(html_af611c6654be4cd5a1d925e7bf0c8c3f);
        

        marker_d4a7441ac5754400ab59397ddc52243a.bindPopup(popup_ae6689f00246470bb4277f72e2c0e2a9)
        ;

        
    
    
            var marker_8e5a59a2e1a044478e3146067b73eab5 = L.marker(
                [40.7157238, -73.99161149999999],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_37f94acfdbf04e7bab53f222f8143d04 = L.popup({"maxWidth": "100%"});

        
            var html_69170b327a14412a82111209a1279c2d = $(`<div id="html_69170b327a14412a82111209a1279c2d" style="width: 100.0%; height: 100.0%;">Scarr&#39;s Pizza Price: $ Rating:4.0</div>`)[0];
            popup_37f94acfdbf04e7bab53f222f8143d04.setContent(html_69170b327a14412a82111209a1279c2d);
        

        marker_8e5a59a2e1a044478e3146067b73eab5.bindPopup(popup_37f94acfdbf04e7bab53f222f8143d04)
        ;

        
    
    
            var marker_0af6fb4f686846618ab987a943361cc6 = L.marker(
                [40.6854737, -73.9203186],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_e58e64dfe93f4405b24962e2a9768f97 = L.popup({"maxWidth": "100%"});

        
            var html_08cb3b133f574cfb8d49b1ba7185bb89 = $(`<div id="html_08cb3b133f574cfb8d49b1ba7185bb89" style="width: 100.0%; height: 100.0%;">Cuts &amp; Slices Price: $$ Rating:4.0</div>`)[0];
            popup_e58e64dfe93f4405b24962e2a9768f97.setContent(html_08cb3b133f574cfb8d49b1ba7185bb89);
        

        marker_0af6fb4f686846618ab987a943361cc6.bindPopup(popup_e58e64dfe93f4405b24962e2a9768f97)
        ;

        
    
    
            var marker_642d8cc2d0b04f2c94c1dc04d98df17a = L.marker(
                [40.69116658201196, -73.99065911521895],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_7ad0186f2c8b44618ecf44ff518a0830 = L.popup({"maxWidth": "100%"});

        
            var html_fc51469f6b08430f8ca27583fa53dca0 = $(`<div id="html_fc51469f6b08430f8ca27583fa53dca0" style="width: 100.0%; height: 100.0%;">Piz-zetta Price: $ Rating:4.5</div>`)[0];
            popup_7ad0186f2c8b44618ecf44ff518a0830.setContent(html_fc51469f6b08430f8ca27583fa53dca0);
        

        marker_642d8cc2d0b04f2c94c1dc04d98df17a.bindPopup(popup_7ad0186f2c8b44618ecf44ff518a0830)
        ;

        
    
    
            var marker_f5754ecd8ad8440f93b17d73461fa618 = L.marker(
                [40.7608512, -73.9694809],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_7496595e73814c1f8c1954847aa332c5 = L.popup({"maxWidth": "100%"});

        
            var html_b438c968baf643f7934d5be4953d6ae8 = $(`<div id="html_b438c968baf643f7934d5be4953d6ae8" style="width: 100.0%; height: 100.0%;">My Pie Pizzeria Romana Price: $ Rating:4.5</div>`)[0];
            popup_7496595e73814c1f8c1954847aa332c5.setContent(html_b438c968baf643f7934d5be4953d6ae8);
        

        marker_f5754ecd8ad8440f93b17d73461fa618.bindPopup(popup_7496595e73814c1f8c1954847aa332c5)
        ;

        
    
    
            var marker_0920726a6d0143b4b9367d6a3e420148 = L.marker(
                [40.72836, -73.9572],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_d2f3de30fb334271993e3a685c7dc097 = L.popup({"maxWidth": "100%"});

        
            var html_fbeaa7410d2c41e3af5954fe380a659a = $(`<div id="html_fbeaa7410d2c41e3af5954fe380a659a" style="width: 100.0%; height: 100.0%;">Paulie Gee&#39;s Slice Shop Price: $ Rating:4.0</div>`)[0];
            popup_d2f3de30fb334271993e3a685c7dc097.setContent(html_fbeaa7410d2c41e3af5954fe380a659a);
        

        marker_0920726a6d0143b4b9367d6a3e420148.bindPopup(popup_d2f3de30fb334271993e3a685c7dc097)
        ;

        
    
    
            var marker_3aea4e9aabd343fc91f997061000b594 = L.marker(
                [40.7502059936523, -73.9953231811523],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_8de24f1cb37847a4b69a09a33ab26a1f = L.popup({"maxWidth": "100%"});

        
            var html_be2914c0544d424f80aff8e5d60b04af = $(`<div id="html_be2914c0544d424f80aff8e5d60b04af" style="width: 100.0%; height: 100.0%;">NY Pizza Suprema Price: $ Rating:4.5</div>`)[0];
            popup_8de24f1cb37847a4b69a09a33ab26a1f.setContent(html_be2914c0544d424f80aff8e5d60b04af);
        

        marker_3aea4e9aabd343fc91f997061000b594.bindPopup(popup_8de24f1cb37847a4b69a09a33ab26a1f)
        ;

        
    
    
            var marker_86f3ec7e059d45fba44062b3316f11cc = L.marker(
                [40.7215270996094, -73.9970855712891],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_5c52df55c9794f918d1a8b106cad351b = L.popup({"maxWidth": "100%"});

        
            var html_1e842c6481bc4ef38ce2d49500b3e5d8 = $(`<div id="html_1e842c6481bc4ef38ce2d49500b3e5d8" style="width: 100.0%; height: 100.0%;">Champion Pizza Price: $ Rating:4.5</div>`)[0];
            popup_5c52df55c9794f918d1a8b106cad351b.setContent(html_1e842c6481bc4ef38ce2d49500b3e5d8);
        

        marker_86f3ec7e059d45fba44062b3316f11cc.bindPopup(popup_5c52df55c9794f918d1a8b106cad351b)
        ;

        
    
    
            var marker_a20363ed7d3b40f5b2fa0dde91281d86 = L.marker(
                [40.72813, -74.00188],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_3966beb4b7484502b01e35d2b4df0441 = L.popup({"maxWidth": "100%"});

        
            var html_941413e2bdf746458fe0116760546f68 = $(`<div id="html_941413e2bdf746458fe0116760546f68" style="width: 100.0%; height: 100.0%;">Song E Napule Price: $$ Rating:4.5</div>`)[0];
            popup_3966beb4b7484502b01e35d2b4df0441.setContent(html_941413e2bdf746458fe0116760546f68);
        

        marker_a20363ed7d3b40f5b2fa0dde91281d86.bindPopup(popup_3966beb4b7484502b01e35d2b4df0441)
        ;

        
    
    
            var marker_f9252ffe9de046fcb738c018e6846690 = L.marker(
                [40.73216, -73.983877],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_10a3ecef6aab4144ad5de4a429731fbe = L.popup({"maxWidth": "100%"});

        
            var html_21c5f363a09c4e4ea23d5c81d07052b9 = $(`<div id="html_21c5f363a09c4e4ea23d5c81d07052b9" style="width: 100.0%; height: 100.0%;">Artichoke Basille&#39;s Pizza Price: $ Rating:4.0</div>`)[0];
            popup_10a3ecef6aab4144ad5de4a429731fbe.setContent(html_21c5f363a09c4e4ea23d5c81d07052b9);
        

        marker_f9252ffe9de046fcb738c018e6846690.bindPopup(popup_10a3ecef6aab4144ad5de4a429731fbe)
        ;

        
    
    
            var marker_2be296751e0d4d889f20be9eebe07616 = L.marker(
                [40.743553, -73.980026],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_38490ec870294f5e90ea78bdf2a6698e = L.popup({"maxWidth": "100%"});

        
            var html_a70bd2c0037e44bd8b7f2c9c96c24edf = $(`<div id="html_a70bd2c0037e44bd8b7f2c9c96c24edf" style="width: 100.0%; height: 100.0%;">Norma Price: $$ Rating:4.5</div>`)[0];
            popup_38490ec870294f5e90ea78bdf2a6698e.setContent(html_a70bd2c0037e44bd8b7f2c9c96c24edf);
        

        marker_2be296751e0d4d889f20be9eebe07616.bindPopup(popup_38490ec870294f5e90ea78bdf2a6698e)
        ;

        
    
    
            var marker_3c4c4fba96714610a3cd7348920e7b8f = L.marker(
                [40.6950309, -73.9961252],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_73aa80f6e6664adf9efe1be383936bb7 = L.popup({"maxWidth": "100%"});

        
            var html_8e1716a3afe84daabbfc683964dc0d01 = $(`<div id="html_8e1716a3afe84daabbfc683964dc0d01" style="width: 100.0%; height: 100.0%;">Dellarocco&#39;s Brick Oven Pizza Price: $$ Rating:4.0</div>`)[0];
            popup_73aa80f6e6664adf9efe1be383936bb7.setContent(html_8e1716a3afe84daabbfc683964dc0d01);
        

        marker_3c4c4fba96714610a3cd7348920e7b8f.bindPopup(popup_73aa80f6e6664adf9efe1be383936bb7)
        ;

        
    
    
            var marker_074775aa03d14335b018cbfb278beb17 = L.marker(
                [40.6627403949909, -73.8403776268684],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_7c11ce76492c4e719b32044ffe7e11f2 = L.popup({"maxWidth": "100%"});

        
            var html_6997e478eb414c898fe495a4f4705711 = $(`<div id="html_6997e478eb414c898fe495a4f4705711" style="width: 100.0%; height: 100.0%;">New Park Pizza Price: $ Rating:4.0</div>`)[0];
            popup_7c11ce76492c4e719b32044ffe7e11f2.setContent(html_6997e478eb414c898fe495a4f4705711);
        

        marker_074775aa03d14335b018cbfb278beb17.bindPopup(popup_7c11ce76492c4e719b32044ffe7e11f2)
        ;

        
    
    
            var marker_5c47b6bc6fc54678b0482fd4411addbe = L.marker(
                [40.717953, -73.9637027],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_c6a820f7fc2c4a6eacdfbc9d1e6da059 = L.popup({"maxWidth": "100%"});

        
            var html_9d354ccf98c448f5bcc0abf8d467be33 = $(`<div id="html_9d354ccf98c448f5bcc0abf8d467be33" style="width: 100.0%; height: 100.0%;">La Nonna Krispy Krust Pizza Price: $$ Rating:4.0</div>`)[0];
            popup_c6a820f7fc2c4a6eacdfbc9d1e6da059.setContent(html_9d354ccf98c448f5bcc0abf8d467be33);
        

        marker_5c47b6bc6fc54678b0482fd4411addbe.bindPopup(popup_c6a820f7fc2c4a6eacdfbc9d1e6da059)
        ;

        
    
    
            var marker_fe0ea959f80e437c95feb0ffb38d8571 = L.marker(
                [40.71505, -73.958365],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_be63f3a113654a31809bb8d9eb26bdf4 = L.popup({"maxWidth": "100%"});

        
            var html_f43e61eb4b034bc9b7a697d5e7521ceb = $(`<div id="html_f43e61eb4b034bc9b7a697d5e7521ceb" style="width: 100.0%; height: 100.0%;">Ace&#39;s Pizza Price: $$ Rating:4.5</div>`)[0];
            popup_be63f3a113654a31809bb8d9eb26bdf4.setContent(html_f43e61eb4b034bc9b7a697d5e7521ceb);
        

        marker_fe0ea959f80e437c95feb0ffb38d8571.bindPopup(popup_be63f3a113654a31809bb8d9eb26bdf4)
        ;

        
    
    
            var marker_25ac2ad723ff44c8b1480ebd2cd87d1e = L.marker(
                [40.70424819999999, -74.0101127],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_86932a81360847bc91b8d17bb59c5de2 = L.popup({"maxWidth": "100%"});

        
            var html_255846aa4a71411083e89f27d6cc43da = $(`<div id="html_255846aa4a71411083e89f27d6cc43da" style="width: 100.0%; height: 100.0%;">Adrienne&#39;s Pizzabar Price: $$ Rating:4.0</div>`)[0];
            popup_86932a81360847bc91b8d17bb59c5de2.setContent(html_255846aa4a71411083e89f27d6cc43da);
        

        marker_25ac2ad723ff44c8b1480ebd2cd87d1e.bindPopup(popup_86932a81360847bc91b8d17bb59c5de2)
        ;

        
    
    
            var marker_c286cc3273f34d52afc47280664cee8f = L.marker(
                [40.80084, -73.96766],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_1e5f6649e5df45b5b9840e1bbc1c43d7 = L.popup({"maxWidth": "100%"});

        
            var html_76826d5f74e944b69176eccfb59b8437 = $(`<div id="html_76826d5f74e944b69176eccfb59b8437" style="width: 100.0%; height: 100.0%;">MAMA&#39;S TOO! Price: $$ Rating:3.5</div>`)[0];
            popup_1e5f6649e5df45b5b9840e1bbc1c43d7.setContent(html_76826d5f74e944b69176eccfb59b8437);
        

        marker_c286cc3273f34d52afc47280664cee8f.bindPopup(popup_1e5f6649e5df45b5b9840e1bbc1c43d7)
        ;

        
    
    
            var marker_4d50f5a1ef5c456fa2bace70e8c0cec2 = L.marker(
                [40.7826, -73.95351],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_9ffab4822d1b40de8c7db30353832e43 = L.popup({"maxWidth": "100%"});

        
            var html_4c7e70a4dd56460a950a420644862019 = $(`<div id="html_4c7e70a4dd56460a950a420644862019" style="width: 100.0%; height: 100.0%;">Marinara Pizza Price: $ Rating:4.0</div>`)[0];
            popup_9ffab4822d1b40de8c7db30353832e43.setContent(html_4c7e70a4dd56460a950a420644862019);
        

        marker_4d50f5a1ef5c456fa2bace70e8c0cec2.bindPopup(popup_9ffab4822d1b40de8c7db30353832e43)
        ;

        
    
    
            var marker_d57d3c6af38040f58fab7690ee7af6f7 = L.marker(
                [40.8280452239988, -73.9489363226845],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_b12c966b486a4447954c15f7e41ba9e5 = L.popup({"maxWidth": "100%"});

        
            var html_856ec5e4c0f24e67bc2a8454b01bbc06 = $(`<div id="html_856ec5e4c0f24e67bc2a8454b01bbc06" style="width: 100.0%; height: 100.0%;">Jumbo Pizza Coffee Shop Price: $ Rating:3.5</div>`)[0];
            popup_b12c966b486a4447954c15f7e41ba9e5.setContent(html_856ec5e4c0f24e67bc2a8454b01bbc06);
        

        marker_d57d3c6af38040f58fab7690ee7af6f7.bindPopup(popup_b12c966b486a4447954c15f7e41ba9e5)
        ;

        
    
    
            var marker_48763d8f1f49488ab68e78e794011547 = L.marker(
                [40.6941108703613, -73.8500289916992],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_5926ef3bfe1242b48fafa5e779f9b84c = L.popup({"maxWidth": "100%"});

        
            var html_4bfcef8bd8b1419181ae3956d8520ae1 = $(`<div id="html_4bfcef8bd8b1419181ae3956d8520ae1" style="width: 100.0%; height: 100.0%;">Joe&#39;s Pizza Price: $$$ Rating:4.0</div>`)[0];
            popup_5926ef3bfe1242b48fafa5e779f9b84c.setContent(html_4bfcef8bd8b1419181ae3956d8520ae1);
        

        marker_48763d8f1f49488ab68e78e794011547.bindPopup(popup_5926ef3bfe1242b48fafa5e779f9b84c)
        ;

        
    
    
            var marker_5aeffe72b9b842afa28df333624f1503 = L.marker(
                [40.7634285660493, -73.81413158435902],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_2cfdd89570864c819d22e354d1e6bc4e = L.popup({"maxWidth": "100%"});

        
            var html_fc86dcc725844caa8bdbd1a9b05933fc = $(`<div id="html_fc86dcc725844caa8bdbd1a9b05933fc" style="width: 100.0%; height: 100.0%;">Mahsil Price: $$ Rating:4.0</div>`)[0];
            popup_2cfdd89570864c819d22e354d1e6bc4e.setContent(html_fc86dcc725844caa8bdbd1a9b05933fc);
        

        marker_5aeffe72b9b842afa28df333624f1503.bindPopup(popup_2cfdd89570864c819d22e354d1e6bc4e)
        ;

        
    
    
            var marker_3bf24b9f2d0c4801bf2e1211446b25ba = L.marker(
                [40.7302, -73.98069],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_4fac503933aa4ea397a6e2d0b56aa0dd = L.popup({"maxWidth": "100%"});

        
            var html_c648580b7a224c2986ab3f561f591ee5 = $(`<div id="html_c648580b7a224c2986ab3f561f591ee5" style="width: 100.0%; height: 100.0%;">Burrata Pizza Price: $ Rating:4.0</div>`)[0];
            popup_4fac503933aa4ea397a6e2d0b56aa0dd.setContent(html_c648580b7a224c2986ab3f561f591ee5);
        

        marker_3bf24b9f2d0c4801bf2e1211446b25ba.bindPopup(popup_4fac503933aa4ea397a6e2d0b56aa0dd)
        ;

        
    
    
            var marker_1e1a0a5cda5d4ea7b7a29cce4d33765d = L.marker(
                [40.7177776, -74.0442612],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_b5b9ea6bddc0469f9905434af172934a = L.popup({"maxWidth": "100%"});

        
            var html_af0acef62a5e45e2860aa34a4a3874ab = $(`<div id="html_af0acef62a5e45e2860aa34a4a3874ab" style="width: 100.0%; height: 100.0%;">Razza Price: $$ Rating:4.0</div>`)[0];
            popup_b5b9ea6bddc0469f9905434af172934a.setContent(html_af0acef62a5e45e2860aa34a4a3874ab);
        

        marker_1e1a0a5cda5d4ea7b7a29cce4d33765d.bindPopup(popup_b5b9ea6bddc0469f9905434af172934a)
        ;

        
    
    
            var marker_ee869960144e4e2abb2a3fa6b6c3275a = L.marker(
                [40.728212, -73.985182],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_b8916367ffd945dd8e9e3072c11e8138 = L.popup({"maxWidth": "100%"});

        
            var html_5108a4a25b094d30a7320f0dda1206f7 = $(`<div id="html_5108a4a25b094d30a7320f0dda1206f7" style="width: 100.0%; height: 100.0%;">East Village Pizza Price: $ Rating:4.0</div>`)[0];
            popup_b8916367ffd945dd8e9e3072c11e8138.setContent(html_5108a4a25b094d30a7320f0dda1206f7);
        

        marker_ee869960144e4e2abb2a3fa6b6c3275a.bindPopup(popup_b8916367ffd945dd8e9e3072c11e8138)
        ;

        
    
    
            var marker_07a47b18333542178d6be5c99aa8f681 = L.marker(
                [40.688285, -73.989006],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_ea49a9372b4b49ec9af5fc5d52e924da = L.popup({"maxWidth": "100%"});

        
            var html_cac8d774e3924dd7bed130793108c6f5 = $(`<div id="html_cac8d774e3924dd7bed130793108c6f5" style="width: 100.0%; height: 100.0%;">Sottocasa Pizzeria Price: $$ Rating:4.5</div>`)[0];
            popup_ea49a9372b4b49ec9af5fc5d52e924da.setContent(html_cac8d774e3924dd7bed130793108c6f5);
        

        marker_07a47b18333542178d6be5c99aa8f681.bindPopup(popup_ea49a9372b4b49ec9af5fc5d52e924da)
        ;

        
    
    
            var marker_98083f243ae7448a8e01826159e93a72 = L.marker(
                [40.697516, -73.967514],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_28806dce525743548892a555744957d0 = L.popup({"maxWidth": "100%"});

        
            var html_3b64329c38824efcb42b610245696034 = $(`<div id="html_3b64329c38824efcb42b610245696034" style="width: 100.0%; height: 100.0%;">Il Porto Price: $$ Rating:4.0</div>`)[0];
            popup_28806dce525743548892a555744957d0.setContent(html_3b64329c38824efcb42b610245696034);
        

        marker_98083f243ae7448a8e01826159e93a72.bindPopup(popup_28806dce525743548892a555744957d0)
        ;

        
    
    
            var marker_53da4815f3ef4aaaabf339e8bd78bfae = L.marker(
                [40.72693, -73.99319],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_d50d8f79598b4aadb3d5a5b5bb29b84e = L.popup({"maxWidth": "100%"});

        
            var html_f4578a2ea6594a838f2d021b06b0c424 = $(`<div id="html_f4578a2ea6594a838f2d021b06b0c424" style="width: 100.0%; height: 100.0%;">Vic&#39;s Price: $$ Rating:4.5</div>`)[0];
            popup_d50d8f79598b4aadb3d5a5b5bb29b84e.setContent(html_f4578a2ea6594a838f2d021b06b0c424);
        

        marker_53da4815f3ef4aaaabf339e8bd78bfae.bindPopup(popup_d50d8f79598b4aadb3d5a5b5bb29b84e)
        ;

        
    
    
            var marker_5d4ad2ff407c4aafa6361d8a38b60184 = L.marker(
                [40.7156, -73.95352],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_920b35f5bfd04ce39e14fb972c101204 = L.popup({"maxWidth": "100%"});

        
            var html_8ce4465ab17b446bb92a89f0e38d4605 = $(`<div id="html_8ce4465ab17b446bb92a89f0e38d4605" style="width: 100.0%; height: 100.0%;">Best Pizza Price: $ Rating:3.5</div>`)[0];
            popup_920b35f5bfd04ce39e14fb972c101204.setContent(html_8ce4465ab17b446bb92a89f0e38d4605);
        

        marker_5d4ad2ff407c4aafa6361d8a38b60184.bindPopup(popup_920b35f5bfd04ce39e14fb972c101204)
        ;

        
    
    
            var marker_edd700233c1d453e9fe89a87f8661ac3 = L.marker(
                [40.712121, -74.009704],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_ffd425989ec1474a8eebdb74dcb68655 = L.popup({"maxWidth": "100%"});

        
            var html_4c91793ee79b41879abd3a3b93595599 = $(`<div id="html_4c91793ee79b41879abd3a3b93595599" style="width: 100.0%; height: 100.0%;">Stage Door Pizzeria Price: $ Rating:4.0</div>`)[0];
            popup_ffd425989ec1474a8eebdb74dcb68655.setContent(html_4c91793ee79b41879abd3a3b93595599);
        

        marker_edd700233c1d453e9fe89a87f8661ac3.bindPopup(popup_ffd425989ec1474a8eebdb74dcb68655)
        ;

        
    
    
            var marker_956db517c2eb40bb9c1ee0d7e03ead32 = L.marker(
                [40.7334346, -73.9916923],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_c64a55bbd4d84298bcfb1e91bfb59b5d = L.popup({"maxWidth": "100%"});

        
            var html_7cced63b87704260ae81b2711d39d1e7 = $(`<div id="html_7cced63b87704260ae81b2711d39d1e7" style="width: 100.0%; height: 100.0%;">Ribalta Pizza Price: $$ Rating:4.0</div>`)[0];
            popup_c64a55bbd4d84298bcfb1e91bfb59b5d.setContent(html_7cced63b87704260ae81b2711d39d1e7);
        

        marker_956db517c2eb40bb9c1ee0d7e03ead32.bindPopup(popup_c64a55bbd4d84298bcfb1e91bfb59b5d)
        ;

        
    
    
            var marker_ac0550563b314c5d8e59959b91c51955 = L.marker(
                [40.718554, -73.997447],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_0df922a2641743d69acd6624de759e0f = L.popup({"maxWidth": "100%"});

        
            var html_94c84b1e89a04a2b8e4717d4b6ecc49d = $(`<div id="html_94c84b1e89a04a2b8e4717d4b6ecc49d" style="width: 100.0%; height: 100.0%;">Paesano of Mulberry Street Price: $$ Rating:4.0</div>`)[0];
            popup_0df922a2641743d69acd6624de759e0f.setContent(html_94c84b1e89a04a2b8e4717d4b6ecc49d);
        

        marker_ac0550563b314c5d8e59959b91c51955.bindPopup(popup_0df922a2641743d69acd6624de759e0f)
        ;

        
    
    
            var marker_dbc995e0f44a4642a581d1cbcb6e25d5 = L.marker(
                [40.76492, -73.97794],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_95fdedc8e74147a6b2b797740ca13352 = L.popup({"maxWidth": "100%"});

        
            var html_21603d14f7d44d49909360b93194ca13 = $(`<div id="html_21603d14f7d44d49909360b93194ca13" style="width: 100.0%; height: 100.0%;">Angelo&#39;s Coal Oven Pizzeria Price: $$ Rating:4.0</div>`)[0];
            popup_95fdedc8e74147a6b2b797740ca13352.setContent(html_21603d14f7d44d49909360b93194ca13);
        

        marker_dbc995e0f44a4642a581d1cbcb6e25d5.bindPopup(popup_95fdedc8e74147a6b2b797740ca13352)
        ;

        
    
    
            var marker_ddb461a8c7334efa85ec9180b73aa7c7 = L.marker(
                [40.73069, -74.00015],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_f77b7857728449ae985e1e758c4d10fe = L.popup({"maxWidth": "100%"});

        
            var html_9a40f6a6b91f491fb5a2867532ea068a = $(`<div id="html_9a40f6a6b91f491fb5a2867532ea068a" style="width: 100.0%; height: 100.0%;">La Lanterna Di Vittorio Price: $$ Rating:4.0</div>`)[0];
            popup_f77b7857728449ae985e1e758c4d10fe.setContent(html_9a40f6a6b91f491fb5a2867532ea068a);
        

        marker_ddb461a8c7334efa85ec9180b73aa7c7.bindPopup(popup_f77b7857728449ae985e1e758c4d10fe)
        ;

        
    
    
            var marker_26c292d4ae4e463e80331b204dedef64 = L.marker(
                [40.6985, -73.99273],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_b7b9855935884950add41000e02bfc8a = L.popup({"maxWidth": "100%"});

        
            var html_5653fc928b984f2bae1acaec0678d0b8 = $(`<div id="html_5653fc928b984f2bae1acaec0678d0b8" style="width: 100.0%; height: 100.0%;">Fascati Pizza Price: $ Rating:3.5</div>`)[0];
            popup_b7b9855935884950add41000e02bfc8a.setContent(html_5653fc928b984f2bae1acaec0678d0b8);
        

        marker_26c292d4ae4e463e80331b204dedef64.bindPopup(popup_b7b9855935884950add41000e02bfc8a)
        ;

        
    
    
            var marker_9e1af2a71dd043b1bfc03aab4da6f0b7 = L.marker(
                [40.7509380299598, -73.9767879766344],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_b61c91ee68a347e8852b4410d3117241 = L.popup({"maxWidth": "100%"});

        
            var html_434a18668ade4b9cbb1116eacaffc1e9 = $(`<div id="html_434a18668ade4b9cbb1116eacaffc1e9" style="width: 100.0%; height: 100.0%;">Previti Pizza Price: $ Rating:4.0</div>`)[0];
            popup_b61c91ee68a347e8852b4410d3117241.setContent(html_434a18668ade4b9cbb1116eacaffc1e9);
        

        marker_9e1af2a71dd043b1bfc03aab4da6f0b7.bindPopup(popup_b61c91ee68a347e8852b4410d3117241)
        ;

        
    
    
            var marker_8dca35e1f2444981a3bac7c1fc04f26f = L.marker(
                [40.7273563342024, -74.0004944801331],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_c6eed42dbd0d419fae123fe3352102aa = L.popup({"maxWidth": "100%"});

        
            var html_24003b9ffd40435f89d06dc069d076db = $(`<div id="html_24003b9ffd40435f89d06dc069d076db" style="width: 100.0%; height: 100.0%;">Arturo&#39;s Price: $$ Rating:4.0</div>`)[0];
            popup_c6eed42dbd0d419fae123fe3352102aa.setContent(html_24003b9ffd40435f89d06dc069d076db);
        

        marker_8dca35e1f2444981a3bac7c1fc04f26f.bindPopup(popup_c6eed42dbd0d419fae123fe3352102aa)
        ;

        
    
    
            var marker_71a20f9f90874fac81ff9a898b5a760b = L.marker(
                [40.73039, -73.98381],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_4399ae61b0e543bfb91b475b9786fb7c = L.popup({"maxWidth": "100%"});

        
            var html_47f465a8dbcf4a3a8a42f05d7e73b320 = $(`<div id="html_47f465a8dbcf4a3a8a42f05d7e73b320" style="width: 100.0%; height: 100.0%;">Motorino Price: $$ Rating:4.0</div>`)[0];
            popup_4399ae61b0e543bfb91b475b9786fb7c.setContent(html_47f465a8dbcf4a3a8a42f05d7e73b320);
        

        marker_71a20f9f90874fac81ff9a898b5a760b.bindPopup(popup_4399ae61b0e543bfb91b475b9786fb7c)
        ;

        
    
    
            var marker_207a79ba6cfe4d2da1625251dce407e6 = L.marker(
                [40.7189, -73.956843],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_e9d206e910ed4e01b07933d86f3d8091 = L.popup({"maxWidth": "100%"});

        
            var html_f67cbecf7cf841dfbc8411b3324d92a6 = $(`<div id="html_f67cbecf7cf841dfbc8411b3324d92a6" style="width: 100.0%; height: 100.0%;">Vinnie&#39;s Pizzeria Price: $ Rating:4.0</div>`)[0];
            popup_e9d206e910ed4e01b07933d86f3d8091.setContent(html_f67cbecf7cf841dfbc8411b3324d92a6);
        

        marker_207a79ba6cfe4d2da1625251dce407e6.bindPopup(popup_e9d206e910ed4e01b07933d86f3d8091)
        ;

        
    
    
            var marker_5c26b38acf60421db3592b3fc7f02abd = L.marker(
                [40.708152, -74.013864],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_c711fb331d33421c8c3dc73d2fdf95b8 = L.popup({"maxWidth": "100%"});

        
            var html_3d789520d2f447be9419b611930acaa7 = $(`<div id="html_3d789520d2f447be9419b611930acaa7" style="width: 100.0%; height: 100.0%;">Siena Pizza &amp; Cannoli Price: $ Rating:4.5</div>`)[0];
            popup_c711fb331d33421c8c3dc73d2fdf95b8.setContent(html_3d789520d2f447be9419b611930acaa7);
        

        marker_5c26b38acf60421db3592b3fc7f02abd.bindPopup(popup_c711fb331d33421c8c3dc73d2fdf95b8)
        ;

        
    
    
            var marker_eaa549b724164d12a354228f41f2434c = L.marker(
                [40.692930215177675, -74.00165153160219],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_ff34c7781fe54b2ca4ef33d37c6605be = L.popup({"maxWidth": "100%"});

        
            var html_77f855a3338b458f906f8fcb9556089b = $(`<div id="html_77f855a3338b458f906f8fcb9556089b" style="width: 100.0%; height: 100.0%;">Fornino Price: $$ Rating:4.0</div>`)[0];
            popup_ff34c7781fe54b2ca4ef33d37c6605be.setContent(html_77f855a3338b458f906f8fcb9556089b);
        

        marker_eaa549b724164d12a354228f41f2434c.bindPopup(popup_ff34c7781fe54b2ca4ef33d37c6605be)
        ;

        
    
    
            var marker_0dca7607089a452185e3f551dd81f1d3 = L.marker(
                [40.699286, -73.918724],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_117e1a8e028a4a0bb464a1fb82337fdf = L.popup({"maxWidth": "100%"});

        
            var html_d19f4ce2d05144b0b72faea892fc219b = $(`<div id="html_d19f4ce2d05144b0b72faea892fc219b" style="width: 100.0%; height: 100.0%;">Tony&#39;s Pizzeria &amp; Restaurant Price: $ Rating:4.5</div>`)[0];
            popup_117e1a8e028a4a0bb464a1fb82337fdf.setContent(html_d19f4ce2d05144b0b72faea892fc219b);
        

        marker_0dca7607089a452185e3f551dd81f1d3.bindPopup(popup_117e1a8e028a4a0bb464a1fb82337fdf)
        ;

        
    
    
            var marker_f51025b013174ab88d2df0a8bcb23a8c = L.marker(
                [40.76032, -73.82813],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_2f1d0d5527f243629de70f34fc3e4344 = L.popup({"maxWidth": "100%"});

        
            var html_3845df4ea3214d8c8585426311890553 = $(`<div id="html_3845df4ea3214d8c8585426311890553" style="width: 100.0%; height: 100.0%;">Lucia Pizza Price: $ Rating:4.5</div>`)[0];
            popup_2f1d0d5527f243629de70f34fc3e4344.setContent(html_3845df4ea3214d8c8585426311890553);
        

        marker_f51025b013174ab88d2df0a8bcb23a8c.bindPopup(popup_2f1d0d5527f243629de70f34fc3e4344)
        ;

        
    
    
            var marker_2f9b7d5a92bf485a8e7fe32ab8af8333 = L.marker(
                [40.742101, -73.989922],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_a901c59082734fbeb72cfdce6cc9e478 = L.popup({"maxWidth": "100%"});

        
            var html_7867fc0db0504a8a9a17a30d59f18d91 = $(`<div id="html_7867fc0db0504a8a9a17a30d59f18d91" style="width: 100.0%; height: 100.0%;">Eataly NYC Flatiron Price: $$ Rating:4.0</div>`)[0];
            popup_a901c59082734fbeb72cfdce6cc9e478.setContent(html_7867fc0db0504a8a9a17a30d59f18d91);
        

        marker_2f9b7d5a92bf485a8e7fe32ab8af8333.bindPopup(popup_a901c59082734fbeb72cfdce6cc9e478)
        ;

        
    
    
            var marker_4eb01a4e7c544ed39010a8fa3666b130 = L.marker(
                [40.67206, -73.95717],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_79e2e52b41b443e8943b956eda908faa = L.popup({"maxWidth": "100%"});

        
            var html_6df7947cbbb84924835d33c6b3486ef8 = $(`<div id="html_6df7947cbbb84924835d33c6b3486ef8" style="width: 100.0%; height: 100.0%;">Barboncino Pizza &amp; Bar Price: $$ Rating:4.5</div>`)[0];
            popup_79e2e52b41b443e8943b956eda908faa.setContent(html_6df7947cbbb84924835d33c6b3486ef8);
        

        marker_4eb01a4e7c544ed39010a8fa3666b130.bindPopup(popup_79e2e52b41b443e8943b956eda908faa)
        ;

        
    
    
            var marker_de5246a954404f50b0a4679a049139c0 = L.marker(
                [40.722121, -73.956678],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_d10bc785b8184d4bad4da7fc4a66de6e = L.popup({"maxWidth": "100%"});

        
            var html_b3ed2ca3293a4efcb6b499b0b01a68c2 = $(`<div id="html_b3ed2ca3293a4efcb6b499b0b01a68c2" style="width: 100.0%; height: 100.0%;">Leuca Price: $$$ Rating:4.0</div>`)[0];
            popup_d10bc785b8184d4bad4da7fc4a66de6e.setContent(html_b3ed2ca3293a4efcb6b499b0b01a68c2);
        

        marker_de5246a954404f50b0a4679a049139c0.bindPopup(popup_d10bc785b8184d4bad4da7fc4a66de6e)
        ;

        
    
    
            var marker_2d24f30673f2448fbfa945554d87bbae = L.marker(
                [40.703137, -73.993608],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_f4714d999a7d4390a7ffbb69b0e09bc3 = L.popup({"maxWidth": "100%"});

        
            var html_1440d056af474f4aa51198228bf435af = $(`<div id="html_1440d056af474f4aa51198228bf435af" style="width: 100.0%; height: 100.0%;">Ignazio&#39;s Price: $$ Rating:3.5</div>`)[0];
            popup_f4714d999a7d4390a7ffbb69b0e09bc3.setContent(html_1440d056af474f4aa51198228bf435af);
        

        marker_2d24f30673f2448fbfa945554d87bbae.bindPopup(popup_f4714d999a7d4390a7ffbb69b0e09bc3)
        ;

        
    
    
            var marker_b1e27fdba52d4f1583177b72771c1746 = L.marker(
                [40.75225, -73.98061],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_186b79cb344642d890e6751fada0fcdc = L.popup({"maxWidth": "100%"});

        
            var html_9b240ca6e869421f84bf66fa1c1c42f8 = $(`<div id="html_9b240ca6e869421f84bf66fa1c1c42f8" style="width: 100.0%; height: 100.0%;">Stone Bridge Pizza &amp; Salad Price: $$ Rating:4.5</div>`)[0];
            popup_186b79cb344642d890e6751fada0fcdc.setContent(html_9b240ca6e869421f84bf66fa1c1c42f8);
        

        marker_b1e27fdba52d4f1583177b72771c1746.bindPopup(popup_186b79cb344642d890e6751fada0fcdc)
        ;

        
    
    
            var marker_38d8d8d8165d454d9b89dc6d64f9e0f8 = L.marker(
                [40.68097, -73.97723],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_387577bd77084e90b7d965a0455b08ef = L.popup({"maxWidth": "100%"});

        
            var html_fd384dd5009d4e94996271470cab5f7c = $(`<div id="html_fd384dd5009d4e94996271470cab5f7c" style="width: 100.0%; height: 100.0%;">Artichoke Basille&#39;s Pizza Price: $ Rating:3.5</div>`)[0];
            popup_387577bd77084e90b7d965a0455b08ef.setContent(html_fd384dd5009d4e94996271470cab5f7c);
        

        marker_38d8d8d8165d454d9b89dc6d64f9e0f8.bindPopup(popup_387577bd77084e90b7d965a0455b08ef)
        ;

        
    
    
            var marker_c1cdf1e0a6a64ce89291753e20c1d462 = L.marker(
                [40.62236, -74.0055],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_31f44a0c0577441cbe3f0dbca9d6df2d = L.popup({"maxWidth": "100%"});

        
            var html_98b408e44a5d4a9ca9248405f5c06de9 = $(`<div id="html_98b408e44a5d4a9ca9248405f5c06de9" style="width: 100.0%; height: 100.0%;">Krispy Pizza  Price: $ Rating:4.0</div>`)[0];
            popup_31f44a0c0577441cbe3f0dbca9d6df2d.setContent(html_98b408e44a5d4a9ca9248405f5c06de9);
        

        marker_c1cdf1e0a6a64ce89291753e20c1d462.bindPopup(popup_31f44a0c0577441cbe3f0dbca9d6df2d)
        ;

        
    
    
            var marker_a0d45a0e8e934b0faedec6db8a21d7af = L.marker(
                [40.92033366683442, -73.86751644723435],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_0fe209ccc7f64325a076b614b557fc69 = L.popup({"maxWidth": "100%"});

        
            var html_b82703fcbdb647c1b5880d03006b2dfd = $(`<div id="html_b82703fcbdb647c1b5880d03006b2dfd" style="width: 100.0%; height: 100.0%;">Pizza Barn Price: $$ Rating:4.0</div>`)[0];
            popup_0fe209ccc7f64325a076b614b557fc69.setContent(html_b82703fcbdb647c1b5880d03006b2dfd);
        

        marker_a0d45a0e8e934b0faedec6db8a21d7af.bindPopup(popup_0fe209ccc7f64325a076b614b557fc69)
        ;

        
    
    
            var marker_18de0937d06d4c86ad6fe986f773adb3 = L.marker(
                [40.719742, -73.9872791],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_fd6c769f23b54ba18f688a89d2b319c1 = L.popup({"maxWidth": "100%"});

        
            var html_66d3e9ebbd684784a1445a79a3020176 = $(`<div id="html_66d3e9ebbd684784a1445a79a3020176" style="width: 100.0%; height: 100.0%;">Champion Pizza Price: $ Rating:4.0</div>`)[0];
            popup_fd6c769f23b54ba18f688a89d2b319c1.setContent(html_66d3e9ebbd684784a1445a79a3020176);
        

        marker_18de0937d06d4c86ad6fe986f773adb3.bindPopup(popup_fd6c769f23b54ba18f688a89d2b319c1)
        ;

        
    
    
            var marker_8e413f543d8f411eb2161b8b37c16704 = L.marker(
                [40.750244140625, -73.9970245361328],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_5066996e329a4ac99142dc7f7087c89e = L.popup({"maxWidth": "100%"});

        
            var html_27a2ff492716405fa510da5b637f2dfe = $(`<div id="html_27a2ff492716405fa510da5b637f2dfe" style="width: 100.0%; height: 100.0%;">Scott&#39;s Pizza Tours Price: $$ Rating:5.0</div>`)[0];
            popup_5066996e329a4ac99142dc7f7087c89e.setContent(html_27a2ff492716405fa510da5b637f2dfe);
        

        marker_8e413f543d8f411eb2161b8b37c16704.bindPopup(popup_5066996e329a4ac99142dc7f7087c89e)
        ;

        
    
    
            var marker_cab2cd687f124136a25d87526ba61a43 = L.marker(
                [40.7081041823001, -74.0046897976739],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_a733f8df796943aea99c9e5be2217606 = L.popup({"maxWidth": "100%"});

        
            var html_974f0b3f8d374f708dfab740d143cbac = $(`<div id="html_974f0b3f8d374f708dfab740d143cbac" style="width: 100.0%; height: 100.0%;">Little Italy Pizza Price: $ Rating:3.5</div>`)[0];
            popup_a733f8df796943aea99c9e5be2217606.setContent(html_974f0b3f8d374f708dfab740d143cbac);
        

        marker_cab2cd687f124136a25d87526ba61a43.bindPopup(popup_a733f8df796943aea99c9e5be2217606)
        ;

        
    
    
            var marker_1d157a57a47a49b891cf7cb1c89b9135 = L.marker(
                [40.6904563903809, -73.9696273803711],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_1dc5626fb2c8438fa9c70d4eb015c8fe = L.popup({"maxWidth": "100%"});

        
            var html_89c7d650a3c944ecbe6a3dc616b0b93f = $(`<div id="html_89c7d650a3c944ecbe6a3dc616b0b93f" style="width: 100.0%; height: 100.0%;">Graziella&#39;s Price: $$ Rating:4.0</div>`)[0];
            popup_1dc5626fb2c8438fa9c70d4eb015c8fe.setContent(html_89c7d650a3c944ecbe6a3dc616b0b93f);
        

        marker_1d157a57a47a49b891cf7cb1c89b9135.bindPopup(popup_1dc5626fb2c8438fa9c70d4eb015c8fe)
        ;

        
    
    
            var marker_76a8bbb2cfca4dca9627a33f3342164a = L.marker(
                [40.66163, -73.99334],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_301393176f474f55a6bac1d351b48d82 = L.popup({"maxWidth": "100%"});

        
            var html_45f1f87bc6ba481da5f5f14570b0f6dd = $(`<div id="html_45f1f87bc6ba481da5f5f14570b0f6dd" style="width: 100.0%; height: 100.0%;">Luigi&#39;s Pizza Price: $ Rating:4.5</div>`)[0];
            popup_301393176f474f55a6bac1d351b48d82.setContent(html_45f1f87bc6ba481da5f5f14570b0f6dd);
        

        marker_76a8bbb2cfca4dca9627a33f3342164a.bindPopup(popup_301393176f474f55a6bac1d351b48d82)
        ;

        
    
    
            var marker_267cbf5036ac4579907e8eb0a1b58c57 = L.marker(
                [40.6302266718896, -74.1402754933448],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_197171dc40914a31a806738ce9fd6f84 = L.popup({"maxWidth": "100%"});

        
            var html_709ebd4c82c84fb09d51b2929a1b499a = $(`<div id="html_709ebd4c82c84fb09d51b2929a1b499a" style="width: 100.0%; height: 100.0%;">Denino&#39;s Pizzeria &amp; Tavern Price: $$ Rating:4.0</div>`)[0];
            popup_197171dc40914a31a806738ce9fd6f84.setContent(html_709ebd4c82c84fb09d51b2929a1b499a);
        

        marker_267cbf5036ac4579907e8eb0a1b58c57.bindPopup(popup_197171dc40914a31a806738ce9fd6f84)
        ;

        
    
    
            var marker_ca3b879db2594bbfa4300ae28151e1b4 = L.marker(
                [40.75949451155184, -73.98673451962638],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_9cb0a4e7b72f4568a559f0cbf4c1e9f5 = L.popup({"maxWidth": "100%"});

        
            var html_6049072aa2ec4c48b4835add05f6386b = $(`<div id="html_6049072aa2ec4c48b4835add05f6386b" style="width: 100.0%; height: 100.0%;">Patzeria Perfect Pizza Price: $ Rating:4.0</div>`)[0];
            popup_9cb0a4e7b72f4568a559f0cbf4c1e9f5.setContent(html_6049072aa2ec4c48b4835add05f6386b);
        

        marker_ca3b879db2594bbfa4300ae28151e1b4.bindPopup(popup_9cb0a4e7b72f4568a559f0cbf4c1e9f5)
        ;

        
    
    
            var marker_9404c7ea9dbe43bf8cc18a87c0336131 = L.marker(
                [40.789283, -73.9487429],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_81379fb06d054df49680544759c04bab = L.popup({"maxWidth": "100%"});

        
            var html_b3f2838404914f8ebc660a3a07872c7f = $(`<div id="html_b3f2838404914f8ebc660a3a07872c7f" style="width: 100.0%; height: 100.0%;">Lexington Pizza Parlour Price: $$ Rating:4.0</div>`)[0];
            popup_81379fb06d054df49680544759c04bab.setContent(html_b3f2838404914f8ebc660a3a07872c7f);
        

        marker_9404c7ea9dbe43bf8cc18a87c0336131.bindPopup(popup_81379fb06d054df49680544759c04bab)
        ;

        
    
    
            var marker_d430c5a1df0c4eca90f6958689c7dce2 = L.marker(
                [40.71822, -73.99123],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_1f26332ee4a94171b8d9a9e728879031 = L.popup({"maxWidth": "100%"});

        
            var html_ff72041a59e64acaaa62908f32a31a1d = $(`<div id="html_ff72041a59e64acaaa62908f32a31a1d" style="width: 100.0%; height: 100.0%;">Williamsburg Pizza Price: $ Rating:4.0</div>`)[0];
            popup_1f26332ee4a94171b8d9a9e728879031.setContent(html_ff72041a59e64acaaa62908f32a31a1d);
        

        marker_d430c5a1df0c4eca90f6958689c7dce2.bindPopup(popup_1f26332ee4a94171b8d9a9e728879031)
        ;

        
    
    
            var marker_ec0bcf416deb4a90a8e24afe1f6021ea = L.marker(
                [40.756482, -73.981484],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_0a56578fb6b94f47b4fc71e9a822d18d = L.popup({"maxWidth": "100%"});

        
            var html_aaa04eeb38ca463f90f89bb5a4485464 = $(`<div id="html_aaa04eeb38ca463f90f89bb5a4485464" style="width: 100.0%; height: 100.0%;">Little Italy Pizza Price: $ Rating:4.0</div>`)[0];
            popup_0a56578fb6b94f47b4fc71e9a822d18d.setContent(html_aaa04eeb38ca463f90f89bb5a4485464);
        

        marker_ec0bcf416deb4a90a8e24afe1f6021ea.bindPopup(popup_0a56578fb6b94f47b4fc71e9a822d18d)
        ;

        
    
    
            var marker_39501beb55ee48ab855272d04baeaec2 = L.marker(
                [40.7084890714263, -73.9610940711639],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_790ed870d2ef49479cc5bb7d2f140f74 = L.popup({"maxWidth": "100%"});

        
            var html_011b41addf714bc8bc8e0545812ce53c = $(`<div id="html_011b41addf714bc8bc8e0545812ce53c" style="width: 100.0%; height: 100.0%;">Roebling Pizza Price: $ Rating:4.5</div>`)[0];
            popup_790ed870d2ef49479cc5bb7d2f140f74.setContent(html_011b41addf714bc8bc8e0545812ce53c);
        

        marker_39501beb55ee48ab855272d04baeaec2.bindPopup(popup_790ed870d2ef49479cc5bb7d2f140f74)
        ;

        
    
    
            var marker_55edebe3212b4601be59f7c44c8c1bdf = L.marker(
                [40.7445882, -73.9847936],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_9093aee856d44adfa54c52bc456f521e = L.popup({"maxWidth": "100%"});

        
            var html_d1f3a8a4b95d4a2783a12147944d19ad = $(`<div id="html_d1f3a8a4b95d4a2783a12147944d19ad" style="width: 100.0%; height: 100.0%;">Marta Price: $$$ Rating:4.0</div>`)[0];
            popup_9093aee856d44adfa54c52bc456f521e.setContent(html_d1f3a8a4b95d4a2783a12147944d19ad);
        

        marker_55edebe3212b4601be59f7c44c8c1bdf.bindPopup(popup_9093aee856d44adfa54c52bc456f521e)
        ;

        
    
    
            var marker_ae54839b6eee4361914fb7fc11755522 = L.marker(
                [40.842018, -74.000809],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_3380a39049484d0b9f2e39c1c14a0ee0 = L.popup({"maxWidth": "100%"});

        
            var html_24fb5d50f0c74c8ea1a480b4013330f2 = $(`<div id="html_24fb5d50f0c74c8ea1a480b4013330f2" style="width: 100.0%; height: 100.0%;">K Pizza Price: $$ Rating:3.5</div>`)[0];
            popup_3380a39049484d0b9f2e39c1c14a0ee0.setContent(html_24fb5d50f0c74c8ea1a480b4013330f2);
        

        marker_ae54839b6eee4361914fb7fc11755522.bindPopup(popup_3380a39049484d0b9f2e39c1c14a0ee0)
        ;

        
    
    
            var marker_73587dfdb0db4d82b529ec026b72e882 = L.marker(
                [40.797157, -73.93488],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_7d633dca008544aca21c2e98c29fe291 = L.popup({"maxWidth": "100%"});

        
            var html_5a97a9d2ddbe43fda07c7928842e02ff = $(`<div id="html_5a97a9d2ddbe43fda07c7928842e02ff" style="width: 100.0%; height: 100.0%;">Patsy&#39;s Pizzeria Price: $$ Rating:4.0</div>`)[0];
            popup_7d633dca008544aca21c2e98c29fe291.setContent(html_5a97a9d2ddbe43fda07c7928842e02ff);
        

        marker_73587dfdb0db4d82b529ec026b72e882.bindPopup(popup_7d633dca008544aca21c2e98c29fe291)
        ;

        
    
    
            var marker_6169d2922b8d469bac8207668f42f790 = L.marker(
                [40.73068, -74.00042],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_b09c703acb484bff9d47f3fc7dbf85ef = L.popup({"maxWidth": "100%"});

        
            var html_aa3f51cd45404f82a785580a3b666fc3 = $(`<div id="html_aa3f51cd45404f82a785580a3b666fc3" style="width: 100.0%; height: 100.0%;">Artistic Pizza Price: $ Rating:4.5</div>`)[0];
            popup_b09c703acb484bff9d47f3fc7dbf85ef.setContent(html_aa3f51cd45404f82a785580a3b666fc3);
        

        marker_6169d2922b8d469bac8207668f42f790.bindPopup(popup_b09c703acb484bff9d47f3fc7dbf85ef)
        ;

        
    
    
            var marker_a47ece2d7a3442fbac8b74c05f02b217 = L.marker(
                [40.7604321973079, -73.9839891042824],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_f3a07ed0eb1448208e3266d552ff96f6 = L.popup({"maxWidth": "100%"});

        
            var html_0ac4b5dcdc1c44d78920beb56a914c9d = $(`<div id="html_0ac4b5dcdc1c44d78920beb56a914c9d" style="width: 100.0%; height: 100.0%;">Ray&#39;s Pizza Price: $ Rating:3.0</div>`)[0];
            popup_f3a07ed0eb1448208e3266d552ff96f6.setContent(html_0ac4b5dcdc1c44d78920beb56a914c9d);
        

        marker_a47ece2d7a3442fbac8b74c05f02b217.bindPopup(popup_f3a07ed0eb1448208e3266d552ff96f6)
        ;

        
    
    
            var marker_5f894561df244a7d8065584dc0f55274 = L.marker(
                [40.691219329834, -73.9973449707031],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_70eea0f457ba43cca3ea9e725d2b2b61 = L.popup({"maxWidth": "100%"});

        
            var html_ea86fceb3c0c44f4bb27b85401bf8d27 = $(`<div id="html_ea86fceb3c0c44f4bb27b85401bf8d27" style="width: 100.0%; height: 100.0%;">Table 87 - Brooklyn Heights Price: $$ Rating:4.0</div>`)[0];
            popup_70eea0f457ba43cca3ea9e725d2b2b61.setContent(html_ea86fceb3c0c44f4bb27b85401bf8d27);
        

        marker_5f894561df244a7d8065584dc0f55274.bindPopup(popup_70eea0f457ba43cca3ea9e725d2b2b61)
        ;

        
    
    
            var marker_bb9de768e9304ab293db10c991fe9f8c = L.marker(
                [40.7204716, -73.9893263],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_730db9a3905a42219bcd200b0a46e500 = L.popup({"maxWidth": "100%"});

        
            var html_838cb6ed04eb48c383b61a1b35d3f892 = $(`<div id="html_838cb6ed04eb48c383b61a1b35d3f892" style="width: 100.0%; height: 100.0%;">Sauce Price: $$ Rating:4.0</div>`)[0];
            popup_730db9a3905a42219bcd200b0a46e500.setContent(html_838cb6ed04eb48c383b61a1b35d3f892);
        

        marker_bb9de768e9304ab293db10c991fe9f8c.bindPopup(popup_730db9a3905a42219bcd200b0a46e500)
        ;

        
    
    
            var marker_a9ff98e1f9b04fdea9123c5d28ee9a03 = L.marker(
                [40.7632745057344, -73.9815969765186],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_f9868622efbf449b8592de416bfa39a9 = L.popup({"maxWidth": "100%"});

        
            var html_519964f7048b4439839d6e0e899ce4b6 = $(`<div id="html_519964f7048b4439839d6e0e899ce4b6" style="width: 100.0%; height: 100.0%;">Famous Original Ray&#39;s Pizza Price: $ Rating:2.5</div>`)[0];
            popup_f9868622efbf449b8592de416bfa39a9.setContent(html_519964f7048b4439839d6e0e899ce4b6);
        

        marker_a9ff98e1f9b04fdea9123c5d28ee9a03.bindPopup(popup_f9868622efbf449b8592de416bfa39a9)
        ;

        
    
    
            var marker_9f50800a7e30477eb6f2c76447ce8250 = L.marker(
                [40.76388, -73.98821],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_2fcec72fd02e4b9b894b37935aa74af4 = L.popup({"maxWidth": "100%"});

        
            var html_96c4c005071f43f3b91b25dd370ed5bd = $(`<div id="html_96c4c005071f43f3b91b25dd370ed5bd" style="width: 100.0%; height: 100.0%;">B Side Pizza &amp; Wine Bar Price: $$ Rating:4.5</div>`)[0];
            popup_2fcec72fd02e4b9b894b37935aa74af4.setContent(html_96c4c005071f43f3b91b25dd370ed5bd);
        

        marker_9f50800a7e30477eb6f2c76447ce8250.bindPopup(popup_2fcec72fd02e4b9b894b37935aa74af4)
        ;

        
    
    
            var marker_e6d9ce48126f401d9a3dd4ba7425fc19 = L.marker(
                [40.7089474315161, -73.83051320334309],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_cb5df4578e2742e389eadb2293c760ee = L.popup({"maxWidth": "100%"});

        
            var html_80f0e22c1f904a23a68c4096bf9a5193 = $(`<div id="html_80f0e22c1f904a23a68c4096bf9a5193" style="width: 100.0%; height: 100.0%;">Dani&#39;s House of Pizza Price: $ Rating:3.5</div>`)[0];
            popup_cb5df4578e2742e389eadb2293c760ee.setContent(html_80f0e22c1f904a23a68c4096bf9a5193);
        

        marker_e6d9ce48126f401d9a3dd4ba7425fc19.bindPopup(popup_cb5df4578e2742e389eadb2293c760ee)
        ;

        
    
    
            var marker_1683b9e9c22a4c53b5e0ad99ac53c1eb = L.marker(
                [40.727303, -74.00243],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_faf4bdd4a4be4a07adfc7822ea6cb167 = L.popup({"maxWidth": "100%"});

        
            var html_1c5d96f393bd4c66b95a160299395d88 = $(`<div id="html_1c5d96f393bd4c66b95a160299395d88" style="width: 100.0%; height: 100.0%;">Emmett&#39;s Price: $$ Rating:4.0</div>`)[0];
            popup_faf4bdd4a4be4a07adfc7822ea6cb167.setContent(html_1c5d96f393bd4c66b95a160299395d88);
        

        marker_1683b9e9c22a4c53b5e0ad99ac53c1eb.bindPopup(popup_faf4bdd4a4be4a07adfc7822ea6cb167)
        ;

        
    
    
            var marker_1d07b6b4aa6b407ea033ed8481caefc6 = L.marker(
                [40.75334, -73.93716],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_be2f80bc5352410096b169373b53dbfa = L.popup({"maxWidth": "100%"});

        
            var html_825c6085c9cd4c9990bb46a936cdd473 = $(`<div id="html_825c6085c9cd4c9990bb46a936cdd473" style="width: 100.0%; height: 100.0%;">Goodfellas Pizzeria of LIC Price: $ Rating:4.5</div>`)[0];
            popup_be2f80bc5352410096b169373b53dbfa.setContent(html_825c6085c9cd4c9990bb46a936cdd473);
        

        marker_1d07b6b4aa6b407ea033ed8481caefc6.bindPopup(popup_be2f80bc5352410096b169373b53dbfa)
        ;

        
    
    
            var marker_6d48042980be4579862eb0f9eaa5c5b7 = L.marker(
                [40.73293764919451, -73.99758608256435],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_51c74628b04a432bb30e274ae49bacd6 = L.popup({"maxWidth": "100%"});

        
            var html_4671f7426d26404083c9e615279b0274 = $(`<div id="html_4671f7426d26404083c9e615279b0274" style="width: 100.0%; height: 100.0%;">Loring Place Price: $$$ Rating:4.5</div>`)[0];
            popup_51c74628b04a432bb30e274ae49bacd6.setContent(html_4671f7426d26404083c9e615279b0274);
        

        marker_6d48042980be4579862eb0f9eaa5c5b7.bindPopup(popup_51c74628b04a432bb30e274ae49bacd6)
        ;

        
    
    
            var marker_ee7d7a26a83e400fbe8fd442271d91cd = L.marker(
                [40.72892, -73.98411],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_1cf115d0a2b548059698fc9a6a36e6e9 = L.popup({"maxWidth": "100%"});

        
            var html_b497d544b4894e7da14d39eb959b9993 = $(`<div id="html_b497d544b4894e7da14d39eb959b9993" style="width: 100.0%; height: 100.0%;">Joe &amp; Pat&#39;s Pizzeria Price: $$ Rating:4.0</div>`)[0];
            popup_1cf115d0a2b548059698fc9a6a36e6e9.setContent(html_b497d544b4894e7da14d39eb959b9993);
        

        marker_ee7d7a26a83e400fbe8fd442271d91cd.bindPopup(popup_1cf115d0a2b548059698fc9a6a36e6e9)
        ;

        
    
    
            var marker_0b63e3ff256c46ff9f66351556ecdea9 = L.marker(
                [40.7190165, -73.9586248],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_c544d60dce0f4c838868ddb5cddf0e5f = L.popup({"maxWidth": "100%"});

        
            var html_947e7b57c00d4aa99e1e9ce9e0fb515e = $(`<div id="html_947e7b57c00d4aa99e1e9ce9e0fb515e" style="width: 100.0%; height: 100.0%;">Oregano Price: $$ Rating:4.0</div>`)[0];
            popup_c544d60dce0f4c838868ddb5cddf0e5f.setContent(html_947e7b57c00d4aa99e1e9ce9e0fb515e);
        

        marker_0b63e3ff256c46ff9f66351556ecdea9.bindPopup(popup_c544d60dce0f4c838868ddb5cddf0e5f)
        ;

        
    
    
            var marker_9f3b613778b441678ea43fb5be6cf360 = L.marker(
                [40.76436969988826, -73.9164369],
                {}
            ).addTo(map_ea7523b0f91c4818ab5cf54c96c5f31a);
        
    
        var popup_b7d731cad0d4446fa0f8bc332b8e63c6 = L.popup({"maxWidth": "100%"});

        
            var html_fa8765f732054c5f90a733f39c388547 = $(`<div id="html_fa8765f732054c5f90a733f39c388547" style="width: 100.0%; height: 100.0%;">Andrew Bellucci&#39;s Pizzeria Price: $$ Rating:4.5</div>`)[0];
            popup_b7d731cad0d4446fa0f8bc332b8e63c6.setContent(html_fa8765f732054c5f90a733f39c388547);
        

        marker_9f3b613778b441678ea43fb5be6cf360.bindPopup(popup_b7d731cad0d4446fa0f8bc332b8e63c6)
        ;

        
    
</script> onload=\"this.contentDocument.open();this.contentDocument.write(atob(this.getAttribute('data-html')));this.contentDocument.close();\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x22aeedddb50>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Replace None with appropriate code\n",
    "\n",
    "# Import the library\n",
    "import folium\n",
    "\n",
    "# Set up center latitude and longitude\n",
    "center_lat = full_dataset[0]['latitude']\n",
    "center_long = full_dataset[0]['longitude']\n",
    "\n",
    "# Initialize map with center lat and long\n",
    "yelp_map = folium.Map([center_lat, center_long], zoom_start=13)\n",
    "\n",
    "# Adjust this limit to see more or fewer businesses\n",
    "limit=100\n",
    "\n",
    "for business in full_dataset[:limit]:\n",
    "    # Extract information about business\n",
    "    lat = business['latitude']\n",
    "    long = business['longitude']\n",
    "    name = business['name']\n",
    "    rating = business['rating']\n",
    "    price = business['price']\n",
    "    details = \"{}\\nPrice: {} Rating:{}\".format(name,price,rating)\n",
    "    \n",
    "    # Create popup with relevant details\n",
    "    popup = folium.Popup(details, parse_html=True)\n",
    "    \n",
    "    # Create marker with relevant lat/long and popup\n",
    "    marker = folium.Marker(location=[lat, long], popup=popup)\n",
    "    \n",
    "    marker.add_to(yelp_map)\n",
    "    \n",
    "yelp_map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Summary\n",
    "\n",
    "Nice work! In this lab, you've made multiple API calls to Yelp in order to paginate through a results set, performing some basic exploratory analysis and then creating a nice interactive map to display the results using Folium! Well done!"
   ]
  }
 ],
 "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": "3.8.5"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}