restaurant_recommender.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Install the necessary requirements"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: aitoai==0.4.0 in c:\\users\\lszab\\anaconda3\\lib\\site-packages (0.4.0)\n",
      "Requirement already satisfied: jsonschema~=3.0 in c:\\users\\lszab\\anaconda3\\lib\\site-packages (from aitoai==0.4.0) (3.2.0)\n",
      "Requirement already satisfied: xlrd~=1.1 in c:\\users\\lszab\\anaconda3\\lib\\site-packages (from aitoai==0.4.0) (1.2.0)\n",
      "Requirement already satisfied: requests~=2.22 in c:\\users\\lszab\\anaconda3\\lib\\site-packages (from aitoai==0.4.0) (2.24.0)\n",
      "Requirement already satisfied: ndjson>=0.2.0 in c:\\users\\lszab\\anaconda3\\lib\\site-packages (from aitoai==0.4.0) (0.3.1)\n",
      "Requirement already satisfied: pandas~=1.0; python_full_version > \"3.6.0\" in c:\\users\\lszab\\anaconda3\\lib\\site-packages (from aitoai==0.4.0) (1.0.1)\n",
      "Requirement already satisfied: aiohttp~=3.4; python_version < \"3.8\" in c:\\users\\lszab\\anaconda3\\lib\\site-packages (from aitoai==0.4.0) (3.7.2)\n",
      "Requirement already satisfied: argcomplete<2.0,>=1.11.1 in c:\\users\\lszab\\anaconda3\\lib\\site-packages (from aitoai==0.4.0) (1.12.1)\n",
      "Requirement already satisfied: langdetect<2.0,>=1.0.7 in c:\\users\\lszab\\anaconda3\\lib\\site-packages (from aitoai==0.4.0) (1.0.8)\n",
      "Requirement already satisfied: attrs>=17.4.0 in c:\\users\\lszab\\anaconda3\\lib\\site-packages (from jsonschema~=3.0->aitoai==0.4.0) (20.2.0)\n",
      "Requirement already satisfied: six>=1.11.0 in c:\\users\\lszab\\anaconda3\\lib\\site-packages (from jsonschema~=3.0->aitoai==0.4.0) (1.15.0)\n",
      "Requirement already satisfied: pyrsistent>=0.14.0 in c:\\users\\lszab\\anaconda3\\lib\\site-packages (from jsonschema~=3.0->aitoai==0.4.0) (0.17.3)\n",
      "Requirement already satisfied: setuptools in c:\\users\\lszab\\anaconda3\\lib\\site-packages (from jsonschema~=3.0->aitoai==0.4.0) (50.3.0.post20201006)\n",
      "Requirement already satisfied: importlib-metadata; python_version < \"3.8\" in c:\\users\\lszab\\anaconda3\\lib\\site-packages (from jsonschema~=3.0->aitoai==0.4.0) (1.7.0)\n",
      "Requirement already satisfied: chardet<4,>=3.0.2 in c:\\users\\lszab\\anaconda3\\lib\\site-packages (from requests~=2.22->aitoai==0.4.0) (3.0.4)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\lszab\\anaconda3\\lib\\site-packages (from requests~=2.22->aitoai==0.4.0) (2020.6.20)\n",
      "Requirement already satisfied: idna<3,>=2.5 in c:\\users\\lszab\\anaconda3\\lib\\site-packages (from requests~=2.22->aitoai==0.4.0) (2.10)\n",
      "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in c:\\users\\lszab\\anaconda3\\lib\\site-packages (from requests~=2.22->aitoai==0.4.0) (1.25.10)\n",
      "Requirement already satisfied: pytz>=2017.2 in c:\\users\\lszab\\anaconda3\\lib\\site-packages (from pandas~=1.0; python_full_version > \"3.6.0\"->aitoai==0.4.0) (2020.1)\n",
      "Requirement already satisfied: numpy>=1.13.3 in c:\\users\\lszab\\anaconda3\\lib\\site-packages (from pandas~=1.0; python_full_version > \"3.6.0\"->aitoai==0.4.0) (1.19.1)\n",
      "Requirement already satisfied: python-dateutil>=2.6.1 in c:\\users\\lszab\\anaconda3\\lib\\site-packages (from pandas~=1.0; python_full_version > \"3.6.0\"->aitoai==0.4.0) (2.8.1)\n",
      "Requirement already satisfied: yarl<2.0,>=1.0 in c:\\users\\lszab\\anaconda3\\lib\\site-packages (from aiohttp~=3.4; python_version < \"3.8\"->aitoai==0.4.0) (1.6.2)\n",
      "Requirement already satisfied: typing-extensions>=3.6.5 in c:\\users\\lszab\\anaconda3\\lib\\site-packages (from aiohttp~=3.4; python_version < \"3.8\"->aitoai==0.4.0) (3.7.4.3)\n",
      "Requirement already satisfied: multidict<7.0,>=4.5 in c:\\users\\lszab\\anaconda3\\lib\\site-packages (from aiohttp~=3.4; python_version < \"3.8\"->aitoai==0.4.0) (5.0.0)\n",
      "Requirement already satisfied: async-timeout<4.0,>=3.0 in c:\\users\\lszab\\anaconda3\\lib\\site-packages (from aiohttp~=3.4; python_version < \"3.8\"->aitoai==0.4.0) (3.0.1)\n",
      "Requirement already satisfied: zipp>=0.5 in c:\\users\\lszab\\anaconda3\\lib\\site-packages (from importlib-metadata; python_version < \"3.8\"->jsonschema~=3.0->aitoai==0.4.0) (3.3.0)\n"
     ]
    }
   ],
   "source": [
    "!pip3 install aitoai==0.4.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from aito.schema import AitoStringType, AitoTextType, AitoDelimiterAnalyzerSchema, AitoTableSchema, AitoColumnLinkSchema, AitoDatabaseSchema\n",
    "from aito.client import AitoClient\n",
    "import aito.api as aito_api"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pathlib import Path\n",
    "# Change the data folder to where you have downloaded the original data\n",
    "data_folder = (Path('.') / 'data' / 'original').resolve()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load and process data files"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Places files"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### chefmozaccepts.csv file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>placeID</th>\n",
       "      <th>Rpayment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>135110</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>135110</td>\n",
       "      <td>VISA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>135110</td>\n",
       "      <td>MasterCard-Eurocard</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>135110</td>\n",
       "      <td>American_Express</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>135110</td>\n",
       "      <td>bank_debit_cards</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1309</th>\n",
       "      <td>132012</td>\n",
       "      <td>Diners_Club</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1310</th>\n",
       "      <td>132002</td>\n",
       "      <td>MasterCard-Eurocard</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1311</th>\n",
       "      <td>132002</td>\n",
       "      <td>Visa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1312</th>\n",
       "      <td>132002</td>\n",
       "      <td>American_Express</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1313</th>\n",
       "      <td>132002</td>\n",
       "      <td>Diners_Club</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1314 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      placeID             Rpayment\n",
       "0      135110                 cash\n",
       "1      135110                 VISA\n",
       "2      135110  MasterCard-Eurocard\n",
       "3      135110     American_Express\n",
       "4      135110     bank_debit_cards\n",
       "...       ...                  ...\n",
       "1309   132012          Diners_Club\n",
       "1310   132002  MasterCard-Eurocard\n",
       "1311   132002                 Visa\n",
       "1312   132002     American_Express\n",
       "1313   132002          Diners_Club\n",
       "\n",
       "[1314 rows x 2 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "places_accept_df = pd.read_csv(data_folder / f'chefmozaccepts.csv')\n",
    "places_accept_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Group the restaurant by its placeID since Aito supports multi values in a column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>placeID</th>\n",
       "      <th>payment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>132002</td>\n",
       "      <td>MasterCard-Eurocard;Visa;American_Express;Dine...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>132012</td>\n",
       "      <td>Visa;American_Express;bank_debit_cards;Diners_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>132019</td>\n",
       "      <td>MasterCard-Eurocard;Visa;American_Express;Dine...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>132023</td>\n",
       "      <td>American_Express;Japan_Credit_Bureau;bank_debi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>132024</td>\n",
       "      <td>Visa;American_Express;bank_debit_cards;Diners_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>610</th>\n",
       "      <td>135105</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>611</th>\n",
       "      <td>135106</td>\n",
       "      <td>cash;VISA;MasterCard-Eurocard</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>612</th>\n",
       "      <td>135107</td>\n",
       "      <td>cash;VISA;MasterCard-Eurocard;American_Express...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>613</th>\n",
       "      <td>135109</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>614</th>\n",
       "      <td>135110</td>\n",
       "      <td>cash;VISA;MasterCard-Eurocard;American_Express...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>615 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     placeID                                            payment\n",
       "0     132002  MasterCard-Eurocard;Visa;American_Express;Dine...\n",
       "1     132012  Visa;American_Express;bank_debit_cards;Diners_...\n",
       "2     132019  MasterCard-Eurocard;Visa;American_Express;Dine...\n",
       "3     132023  American_Express;Japan_Credit_Bureau;bank_debi...\n",
       "4     132024  Visa;American_Express;bank_debit_cards;Diners_...\n",
       "..       ...                                                ...\n",
       "610   135105                                               cash\n",
       "611   135106                      cash;VISA;MasterCard-Eurocard\n",
       "612   135107  cash;VISA;MasterCard-Eurocard;American_Express...\n",
       "613   135109                                               cash\n",
       "614   135110  cash;VISA;MasterCard-Eurocard;American_Express...\n",
       "\n",
       "[615 rows x 2 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "places_accept_df.rename(columns={'Rpayment': 'payment'}, inplace=True)\n",
    "places_accept_df = places_accept_df.groupby('placeID').agg({'payment': lambda x: ';'.join(x)}).reset_index()\n",
    "places_accept_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### chefmozparking.csv file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>placeID</th>\n",
       "      <th>parking_lot</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>135111</td>\n",
       "      <td>public</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>135110</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>135109</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>135108</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>135107</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>697</th>\n",
       "      <td>132024</td>\n",
       "      <td>street</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>698</th>\n",
       "      <td>132023</td>\n",
       "      <td>fee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>699</th>\n",
       "      <td>132023</td>\n",
       "      <td>public</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>700</th>\n",
       "      <td>132012</td>\n",
       "      <td>public</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>701</th>\n",
       "      <td>132012</td>\n",
       "      <td>street</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>702 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     placeID parking_lot\n",
       "0     135111      public\n",
       "1     135110        none\n",
       "2     135109        none\n",
       "3     135108        none\n",
       "4     135107        none\n",
       "..       ...         ...\n",
       "697   132024      street\n",
       "698   132023         fee\n",
       "699   132023      public\n",
       "700   132012      public\n",
       "701   132012      street\n",
       "\n",
       "[702 rows x 2 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "places_parking_df = pd.read_csv(data_folder / f'chefmozparking.csv')\n",
    "places_parking_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>placeID</th>\n",
       "      <th>parking_lot</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>132012</td>\n",
       "      <td>public;street</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>132023</td>\n",
       "      <td>fee;public</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>132024</td>\n",
       "      <td>street</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>132026</td>\n",
       "      <td>fee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>132030</td>\n",
       "      <td>street</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>670</th>\n",
       "      <td>135107</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>671</th>\n",
       "      <td>135108</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>672</th>\n",
       "      <td>135109</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>673</th>\n",
       "      <td>135110</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>674</th>\n",
       "      <td>135111</td>\n",
       "      <td>public</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>675 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     placeID    parking_lot\n",
       "0     132012  public;street\n",
       "1     132023     fee;public\n",
       "2     132024         street\n",
       "3     132026            fee\n",
       "4     132030         street\n",
       "..       ...            ...\n",
       "670   135107           none\n",
       "671   135108           none\n",
       "672   135109           none\n",
       "673   135110           none\n",
       "674   135111         public\n",
       "\n",
       "[675 rows x 2 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "places_parking_df = places_parking_df.groupby('placeID').agg({'parking_lot': lambda x: ';'.join(x)}).reset_index()\n",
    "places_parking_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### chefmozcuisine.csv file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>placeID</th>\n",
       "      <th>Rcuisine</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>135110</td>\n",
       "      <td>Spanish</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>135109</td>\n",
       "      <td>Italian</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>135107</td>\n",
       "      <td>Latin_American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>135106</td>\n",
       "      <td>Mexican</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>135105</td>\n",
       "      <td>Fast_Food</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>911</th>\n",
       "      <td>132005</td>\n",
       "      <td>Seafood</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>912</th>\n",
       "      <td>132004</td>\n",
       "      <td>Seafood</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>913</th>\n",
       "      <td>132003</td>\n",
       "      <td>International</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>914</th>\n",
       "      <td>132002</td>\n",
       "      <td>Seafood</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>915</th>\n",
       "      <td>132001</td>\n",
       "      <td>Dutch-Belgian</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>916 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     placeID        Rcuisine\n",
       "0     135110         Spanish\n",
       "1     135109         Italian\n",
       "2     135107  Latin_American\n",
       "3     135106         Mexican\n",
       "4     135105       Fast_Food\n",
       "..       ...             ...\n",
       "911   132005         Seafood\n",
       "912   132004         Seafood\n",
       "913   132003   International\n",
       "914   132002         Seafood\n",
       "915   132001   Dutch-Belgian\n",
       "\n",
       "[916 rows x 2 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "places_cuisine_df = pd.read_csv(data_folder / f'chefmozcuisine.csv')\n",
    "places_cuisine_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>placeID</th>\n",
       "      <th>cuisine</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>132001</td>\n",
       "      <td>Dutch-Belgian</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>132002</td>\n",
       "      <td>Seafood</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>132003</td>\n",
       "      <td>International</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>132004</td>\n",
       "      <td>Seafood</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>132005</td>\n",
       "      <td>French;Seafood</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>764</th>\n",
       "      <td>135105</td>\n",
       "      <td>Fast_Food</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>765</th>\n",
       "      <td>135106</td>\n",
       "      <td>Mexican</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>766</th>\n",
       "      <td>135107</td>\n",
       "      <td>Latin_American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>767</th>\n",
       "      <td>135109</td>\n",
       "      <td>Italian</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>768</th>\n",
       "      <td>135110</td>\n",
       "      <td>Spanish</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>769 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     placeID         cuisine\n",
       "0     132001   Dutch-Belgian\n",
       "1     132002         Seafood\n",
       "2     132003   International\n",
       "3     132004         Seafood\n",
       "4     132005  French;Seafood\n",
       "..       ...             ...\n",
       "764   135105       Fast_Food\n",
       "765   135106         Mexican\n",
       "766   135107  Latin_American\n",
       "767   135109         Italian\n",
       "768   135110         Spanish\n",
       "\n",
       "[769 rows x 2 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "places_cuisine_df.rename(columns={'Rcuisine': 'cuisine'}, inplace=True)\n",
    "places_cuisine_df = places_cuisine_df.groupby('placeID').agg({'cuisine': lambda x: ';'.join(x)}).reset_index()\n",
    "places_cuisine_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### geoplaces2.csv file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>placeID</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>the_geom_meter</th>\n",
       "      <th>name</th>\n",
       "      <th>address</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>country</th>\n",
       "      <th>fax</th>\n",
       "      <th>...</th>\n",
       "      <th>alcohol</th>\n",
       "      <th>smoking_area</th>\n",
       "      <th>dress_code</th>\n",
       "      <th>accessibility</th>\n",
       "      <th>price</th>\n",
       "      <th>url</th>\n",
       "      <th>Rambience</th>\n",
       "      <th>franchise</th>\n",
       "      <th>area</th>\n",
       "      <th>other_services</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>134999</td>\n",
       "      <td>18.915421</td>\n",
       "      <td>-99.184871</td>\n",
       "      <td>0101000020957F000088568DE356715AC138C0A525FC46...</td>\n",
       "      <td>Kiku Cuernavaca</td>\n",
       "      <td>Revolucion</td>\n",
       "      <td>Cuernavaca</td>\n",
       "      <td>Morelos</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>?</td>\n",
       "      <td>...</td>\n",
       "      <td>No_Alcohol_Served</td>\n",
       "      <td>none</td>\n",
       "      <td>informal</td>\n",
       "      <td>no_accessibility</td>\n",
       "      <td>medium</td>\n",
       "      <td>kikucuernavaca.com.mx</td>\n",
       "      <td>familiar</td>\n",
       "      <td>f</td>\n",
       "      <td>closed</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>132825</td>\n",
       "      <td>22.147392</td>\n",
       "      <td>-100.983092</td>\n",
       "      <td>0101000020957F00001AD016568C4858C1243261274BA5...</td>\n",
       "      <td>puesto de tacos</td>\n",
       "      <td>esquina santos degollado y leon guzman</td>\n",
       "      <td>s.l.p.</td>\n",
       "      <td>s.l.p.</td>\n",
       "      <td>mexico</td>\n",
       "      <td>?</td>\n",
       "      <td>...</td>\n",
       "      <td>No_Alcohol_Served</td>\n",
       "      <td>none</td>\n",
       "      <td>informal</td>\n",
       "      <td>completely</td>\n",
       "      <td>low</td>\n",
       "      <td>?</td>\n",
       "      <td>familiar</td>\n",
       "      <td>f</td>\n",
       "      <td>open</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>135106</td>\n",
       "      <td>22.149709</td>\n",
       "      <td>-100.976093</td>\n",
       "      <td>0101000020957F0000649D6F21634858C119AE9BF528A3...</td>\n",
       "      <td>El Rincï¿½n de San Francisco</td>\n",
       "      <td>Universidad 169</td>\n",
       "      <td>San Luis Potosi</td>\n",
       "      <td>San Luis Potosi</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>?</td>\n",
       "      <td>...</td>\n",
       "      <td>Wine-Beer</td>\n",
       "      <td>only at bar</td>\n",
       "      <td>informal</td>\n",
       "      <td>partially</td>\n",
       "      <td>medium</td>\n",
       "      <td>?</td>\n",
       "      <td>familiar</td>\n",
       "      <td>f</td>\n",
       "      <td>open</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>132667</td>\n",
       "      <td>23.752697</td>\n",
       "      <td>-99.163359</td>\n",
       "      <td>0101000020957F00005D67BCDDED8157C1222A2DC8D84D...</td>\n",
       "      <td>little pizza Emilio Portes Gil</td>\n",
       "      <td>calle emilio portes gil</td>\n",
       "      <td>victoria</td>\n",
       "      <td>tamaulipas</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>...</td>\n",
       "      <td>No_Alcohol_Served</td>\n",
       "      <td>none</td>\n",
       "      <td>informal</td>\n",
       "      <td>completely</td>\n",
       "      <td>low</td>\n",
       "      <td>?</td>\n",
       "      <td>familiar</td>\n",
       "      <td>t</td>\n",
       "      <td>closed</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>132613</td>\n",
       "      <td>23.752903</td>\n",
       "      <td>-99.165076</td>\n",
       "      <td>0101000020957F00008EBA2D06DC8157C194E03B7B504E...</td>\n",
       "      <td>carnitas_mata</td>\n",
       "      <td>lic. Emilio portes gil</td>\n",
       "      <td>victoria</td>\n",
       "      <td>Tamaulipas</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>?</td>\n",
       "      <td>...</td>\n",
       "      <td>No_Alcohol_Served</td>\n",
       "      <td>permitted</td>\n",
       "      <td>informal</td>\n",
       "      <td>completely</td>\n",
       "      <td>medium</td>\n",
       "      <td>?</td>\n",
       "      <td>familiar</td>\n",
       "      <td>t</td>\n",
       "      <td>closed</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>132866</td>\n",
       "      <td>22.141220</td>\n",
       "      <td>-100.931311</td>\n",
       "      <td>0101000020957F000013871838EC4A58C1B5DF74F8E396...</td>\n",
       "      <td>Chaires</td>\n",
       "      <td>Ricardo B. Anaya</td>\n",
       "      <td>San Luis Potosi</td>\n",
       "      <td>San Luis Potosi</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>?</td>\n",
       "      <td>...</td>\n",
       "      <td>No_Alcohol_Served</td>\n",
       "      <td>not permitted</td>\n",
       "      <td>informal</td>\n",
       "      <td>completely</td>\n",
       "      <td>medium</td>\n",
       "      <td>?</td>\n",
       "      <td>familiar</td>\n",
       "      <td>f</td>\n",
       "      <td>closed</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>135072</td>\n",
       "      <td>22.149192</td>\n",
       "      <td>-101.002936</td>\n",
       "      <td>0101000020957F0000E7B79B1DB94758C1D29BC363D8AA...</td>\n",
       "      <td>Sushi Itto</td>\n",
       "      <td>Venustiano Carranza 1809 C Polanco</td>\n",
       "      <td>San Luis Potosi</td>\n",
       "      <td>SLP</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>?</td>\n",
       "      <td>...</td>\n",
       "      <td>No_Alcohol_Served</td>\n",
       "      <td>none</td>\n",
       "      <td>informal</td>\n",
       "      <td>no_accessibility</td>\n",
       "      <td>medium</td>\n",
       "      <td>sushi-itto.com.mx</td>\n",
       "      <td>familiar</td>\n",
       "      <td>f</td>\n",
       "      <td>closed</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>135109</td>\n",
       "      <td>18.921785</td>\n",
       "      <td>-99.235350</td>\n",
       "      <td>0101000020957F0000A6BF695F136F5AC1DADF87B20556...</td>\n",
       "      <td>Paniroles</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>...</td>\n",
       "      <td>Wine-Beer</td>\n",
       "      <td>not permitted</td>\n",
       "      <td>informal</td>\n",
       "      <td>no_accessibility</td>\n",
       "      <td>medium</td>\n",
       "      <td>?</td>\n",
       "      <td>quiet</td>\n",
       "      <td>f</td>\n",
       "      <td>closed</td>\n",
       "      <td>Internet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>135019</td>\n",
       "      <td>18.875011</td>\n",
       "      <td>-99.159422</td>\n",
       "      <td>0101000020957F0000B49B2E5C6E785AC12F9D58435241...</td>\n",
       "      <td>Restaurant Bar Coty y Pablo</td>\n",
       "      <td>Paseo de Las Fuentes 24 Pedregal de Las Fuentes</td>\n",
       "      <td>Jiutepec</td>\n",
       "      <td>Morelos</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>?</td>\n",
       "      <td>...</td>\n",
       "      <td>No_Alcohol_Served</td>\n",
       "      <td>none</td>\n",
       "      <td>informal</td>\n",
       "      <td>completely</td>\n",
       "      <td>low</td>\n",
       "      <td>?</td>\n",
       "      <td>familiar</td>\n",
       "      <td>f</td>\n",
       "      <td>closed</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>132877</td>\n",
       "      <td>22.135364</td>\n",
       "      <td>-100.934948</td>\n",
       "      <td>0101000020957F000090735015B84B58C1AF0DC0414698...</td>\n",
       "      <td>sirloin stockade</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>...</td>\n",
       "      <td>No_Alcohol_Served</td>\n",
       "      <td>none</td>\n",
       "      <td>informal</td>\n",
       "      <td>completely</td>\n",
       "      <td>low</td>\n",
       "      <td>?</td>\n",
       "      <td>familiar</td>\n",
       "      <td>f</td>\n",
       "      <td>closed</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>130 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     placeID   latitude   longitude  \\\n",
       "0     134999  18.915421  -99.184871   \n",
       "1     132825  22.147392 -100.983092   \n",
       "2     135106  22.149709 -100.976093   \n",
       "3     132667  23.752697  -99.163359   \n",
       "4     132613  23.752903  -99.165076   \n",
       "..       ...        ...         ...   \n",
       "125   132866  22.141220 -100.931311   \n",
       "126   135072  22.149192 -101.002936   \n",
       "127   135109  18.921785  -99.235350   \n",
       "128   135019  18.875011  -99.159422   \n",
       "129   132877  22.135364 -100.934948   \n",
       "\n",
       "                                        the_geom_meter  \\\n",
       "0    0101000020957F000088568DE356715AC138C0A525FC46...   \n",
       "1    0101000020957F00001AD016568C4858C1243261274BA5...   \n",
       "2    0101000020957F0000649D6F21634858C119AE9BF528A3...   \n",
       "3    0101000020957F00005D67BCDDED8157C1222A2DC8D84D...   \n",
       "4    0101000020957F00008EBA2D06DC8157C194E03B7B504E...   \n",
       "..                                                 ...   \n",
       "125  0101000020957F000013871838EC4A58C1B5DF74F8E396...   \n",
       "126  0101000020957F0000E7B79B1DB94758C1D29BC363D8AA...   \n",
       "127  0101000020957F0000A6BF695F136F5AC1DADF87B20556...   \n",
       "128  0101000020957F0000B49B2E5C6E785AC12F9D58435241...   \n",
       "129  0101000020957F000090735015B84B58C1AF0DC0414698...   \n",
       "\n",
       "                               name  \\\n",
       "0                   Kiku Cuernavaca   \n",
       "1                   puesto de tacos   \n",
       "2      El Rincï¿½n de San Francisco   \n",
       "3    little pizza Emilio Portes Gil   \n",
       "4                     carnitas_mata   \n",
       "..                              ...   \n",
       "125                         Chaires   \n",
       "126                      Sushi Itto   \n",
       "127                       Paniroles   \n",
       "128     Restaurant Bar Coty y Pablo   \n",
       "129                sirloin stockade   \n",
       "\n",
       "                                             address             city  \\\n",
       "0                                         Revolucion       Cuernavaca   \n",
       "1             esquina santos degollado y leon guzman           s.l.p.   \n",
       "2                                    Universidad 169  San Luis Potosi   \n",
       "3                            calle emilio portes gil        victoria    \n",
       "4                             lic. Emilio portes gil         victoria   \n",
       "..                                               ...              ...   \n",
       "125                                 Ricardo B. Anaya  San Luis Potosi   \n",
       "126               Venustiano Carranza 1809 C Polanco  San Luis Potosi   \n",
       "127                                                ?                ?   \n",
       "128  Paseo de Las Fuentes 24 Pedregal de Las Fuentes         Jiutepec   \n",
       "129                                                ?                ?   \n",
       "\n",
       "               state country fax  ...            alcohol   smoking_area  \\\n",
       "0            Morelos  Mexico   ?  ...  No_Alcohol_Served           none   \n",
       "1             s.l.p.  mexico   ?  ...  No_Alcohol_Served           none   \n",
       "2    San Luis Potosi  Mexico   ?  ...          Wine-Beer    only at bar   \n",
       "3         tamaulipas       ?   ?  ...  No_Alcohol_Served           none   \n",
       "4         Tamaulipas  Mexico   ?  ...  No_Alcohol_Served      permitted   \n",
       "..               ...     ...  ..  ...                ...            ...   \n",
       "125  San Luis Potosi  Mexico   ?  ...  No_Alcohol_Served  not permitted   \n",
       "126              SLP  Mexico   ?  ...  No_Alcohol_Served           none   \n",
       "127                ?       ?   ?  ...          Wine-Beer  not permitted   \n",
       "128          Morelos  Mexico   ?  ...  No_Alcohol_Served           none   \n",
       "129                ?       ?   ?  ...  No_Alcohol_Served           none   \n",
       "\n",
       "    dress_code     accessibility   price                    url Rambience  \\\n",
       "0     informal  no_accessibility  medium  kikucuernavaca.com.mx  familiar   \n",
       "1     informal        completely     low                      ?  familiar   \n",
       "2     informal         partially  medium                      ?  familiar   \n",
       "3     informal        completely     low                      ?  familiar   \n",
       "4     informal        completely  medium                      ?  familiar   \n",
       "..         ...               ...     ...                    ...       ...   \n",
       "125   informal        completely  medium                      ?  familiar   \n",
       "126   informal  no_accessibility  medium      sushi-itto.com.mx  familiar   \n",
       "127   informal  no_accessibility  medium                      ?     quiet   \n",
       "128   informal        completely     low                      ?  familiar   \n",
       "129   informal        completely     low                      ?  familiar   \n",
       "\n",
       "    franchise    area other_services  \n",
       "0           f  closed           none  \n",
       "1           f    open           none  \n",
       "2           f    open           none  \n",
       "3           t  closed           none  \n",
       "4           t  closed           none  \n",
       "..        ...     ...            ...  \n",
       "125         f  closed           none  \n",
       "126         f  closed           none  \n",
       "127         f  closed       Internet  \n",
       "128         f  closed           none  \n",
       "129         f  closed           none  \n",
       "\n",
       "[130 rows x 21 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "places_geo_df = pd.read_csv(data_folder / f'geoplaces2.csv', encoding='latin-1')\n",
    "places_geo_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>placeID</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>the_geom_meter</th>\n",
       "      <th>name</th>\n",
       "      <th>address</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>country</th>\n",
       "      <th>fax</th>\n",
       "      <th>...</th>\n",
       "      <th>alcohol</th>\n",
       "      <th>smoking_area</th>\n",
       "      <th>dress_code</th>\n",
       "      <th>accessibility</th>\n",
       "      <th>price</th>\n",
       "      <th>url</th>\n",
       "      <th>Rambience</th>\n",
       "      <th>franchise</th>\n",
       "      <th>area</th>\n",
       "      <th>other_services</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>134999</td>\n",
       "      <td>18.915421</td>\n",
       "      <td>-99.184871</td>\n",
       "      <td>0101000020957F000088568DE356715AC138C0A525FC46...</td>\n",
       "      <td>Kiku Cuernavaca</td>\n",
       "      <td>Revolucion</td>\n",
       "      <td>Cuernavaca</td>\n",
       "      <td>Morelos</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>No_Alcohol_Served</td>\n",
       "      <td>none</td>\n",
       "      <td>informal</td>\n",
       "      <td>no_accessibility</td>\n",
       "      <td>medium</td>\n",
       "      <td>kikucuernavaca.com.mx</td>\n",
       "      <td>familiar</td>\n",
       "      <td>f</td>\n",
       "      <td>closed</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>132825</td>\n",
       "      <td>22.147392</td>\n",
       "      <td>-100.983092</td>\n",
       "      <td>0101000020957F00001AD016568C4858C1243261274BA5...</td>\n",
       "      <td>puesto de tacos</td>\n",
       "      <td>esquina santos degollado y leon guzman</td>\n",
       "      <td>s.l.p.</td>\n",
       "      <td>s.l.p.</td>\n",
       "      <td>mexico</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>No_Alcohol_Served</td>\n",
       "      <td>none</td>\n",
       "      <td>informal</td>\n",
       "      <td>completely</td>\n",
       "      <td>low</td>\n",
       "      <td>NaN</td>\n",
       "      <td>familiar</td>\n",
       "      <td>f</td>\n",
       "      <td>open</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>135106</td>\n",
       "      <td>22.149709</td>\n",
       "      <td>-100.976093</td>\n",
       "      <td>0101000020957F0000649D6F21634858C119AE9BF528A3...</td>\n",
       "      <td>El Rincï¿½n de San Francisco</td>\n",
       "      <td>Universidad 169</td>\n",
       "      <td>San Luis Potosi</td>\n",
       "      <td>San Luis Potosi</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>Wine-Beer</td>\n",
       "      <td>only at bar</td>\n",
       "      <td>informal</td>\n",
       "      <td>partially</td>\n",
       "      <td>medium</td>\n",
       "      <td>NaN</td>\n",
       "      <td>familiar</td>\n",
       "      <td>f</td>\n",
       "      <td>open</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>132667</td>\n",
       "      <td>23.752697</td>\n",
       "      <td>-99.163359</td>\n",
       "      <td>0101000020957F00005D67BCDDED8157C1222A2DC8D84D...</td>\n",
       "      <td>little pizza Emilio Portes Gil</td>\n",
       "      <td>calle emilio portes gil</td>\n",
       "      <td>victoria</td>\n",
       "      <td>tamaulipas</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>No_Alcohol_Served</td>\n",
       "      <td>none</td>\n",
       "      <td>informal</td>\n",
       "      <td>completely</td>\n",
       "      <td>low</td>\n",
       "      <td>NaN</td>\n",
       "      <td>familiar</td>\n",
       "      <td>t</td>\n",
       "      <td>closed</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>132613</td>\n",
       "      <td>23.752903</td>\n",
       "      <td>-99.165076</td>\n",
       "      <td>0101000020957F00008EBA2D06DC8157C194E03B7B504E...</td>\n",
       "      <td>carnitas_mata</td>\n",
       "      <td>lic. Emilio portes gil</td>\n",
       "      <td>victoria</td>\n",
       "      <td>Tamaulipas</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>No_Alcohol_Served</td>\n",
       "      <td>permitted</td>\n",
       "      <td>informal</td>\n",
       "      <td>completely</td>\n",
       "      <td>medium</td>\n",
       "      <td>NaN</td>\n",
       "      <td>familiar</td>\n",
       "      <td>t</td>\n",
       "      <td>closed</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>132866</td>\n",
       "      <td>22.141220</td>\n",
       "      <td>-100.931311</td>\n",
       "      <td>0101000020957F000013871838EC4A58C1B5DF74F8E396...</td>\n",
       "      <td>Chaires</td>\n",
       "      <td>Ricardo B. Anaya</td>\n",
       "      <td>San Luis Potosi</td>\n",
       "      <td>San Luis Potosi</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>No_Alcohol_Served</td>\n",
       "      <td>not permitted</td>\n",
       "      <td>informal</td>\n",
       "      <td>completely</td>\n",
       "      <td>medium</td>\n",
       "      <td>NaN</td>\n",
       "      <td>familiar</td>\n",
       "      <td>f</td>\n",
       "      <td>closed</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>135072</td>\n",
       "      <td>22.149192</td>\n",
       "      <td>-101.002936</td>\n",
       "      <td>0101000020957F0000E7B79B1DB94758C1D29BC363D8AA...</td>\n",
       "      <td>Sushi Itto</td>\n",
       "      <td>Venustiano Carranza 1809 C Polanco</td>\n",
       "      <td>San Luis Potosi</td>\n",
       "      <td>SLP</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>No_Alcohol_Served</td>\n",
       "      <td>none</td>\n",
       "      <td>informal</td>\n",
       "      <td>no_accessibility</td>\n",
       "      <td>medium</td>\n",
       "      <td>sushi-itto.com.mx</td>\n",
       "      <td>familiar</td>\n",
       "      <td>f</td>\n",
       "      <td>closed</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>135109</td>\n",
       "      <td>18.921785</td>\n",
       "      <td>-99.235350</td>\n",
       "      <td>0101000020957F0000A6BF695F136F5AC1DADF87B20556...</td>\n",
       "      <td>Paniroles</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>Wine-Beer</td>\n",
       "      <td>not permitted</td>\n",
       "      <td>informal</td>\n",
       "      <td>no_accessibility</td>\n",
       "      <td>medium</td>\n",
       "      <td>NaN</td>\n",
       "      <td>quiet</td>\n",
       "      <td>f</td>\n",
       "      <td>closed</td>\n",
       "      <td>Internet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>135019</td>\n",
       "      <td>18.875011</td>\n",
       "      <td>-99.159422</td>\n",
       "      <td>0101000020957F0000B49B2E5C6E785AC12F9D58435241...</td>\n",
       "      <td>Restaurant Bar Coty y Pablo</td>\n",
       "      <td>Paseo de Las Fuentes 24 Pedregal de Las Fuentes</td>\n",
       "      <td>Jiutepec</td>\n",
       "      <td>Morelos</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>No_Alcohol_Served</td>\n",
       "      <td>none</td>\n",
       "      <td>informal</td>\n",
       "      <td>completely</td>\n",
       "      <td>low</td>\n",
       "      <td>NaN</td>\n",
       "      <td>familiar</td>\n",
       "      <td>f</td>\n",
       "      <td>closed</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>132877</td>\n",
       "      <td>22.135364</td>\n",
       "      <td>-100.934948</td>\n",
       "      <td>0101000020957F000090735015B84B58C1AF0DC0414698...</td>\n",
       "      <td>sirloin stockade</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>No_Alcohol_Served</td>\n",
       "      <td>none</td>\n",
       "      <td>informal</td>\n",
       "      <td>completely</td>\n",
       "      <td>low</td>\n",
       "      <td>NaN</td>\n",
       "      <td>familiar</td>\n",
       "      <td>f</td>\n",
       "      <td>closed</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>130 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     placeID   latitude   longitude  \\\n",
       "0     134999  18.915421  -99.184871   \n",
       "1     132825  22.147392 -100.983092   \n",
       "2     135106  22.149709 -100.976093   \n",
       "3     132667  23.752697  -99.163359   \n",
       "4     132613  23.752903  -99.165076   \n",
       "..       ...        ...         ...   \n",
       "125   132866  22.141220 -100.931311   \n",
       "126   135072  22.149192 -101.002936   \n",
       "127   135109  18.921785  -99.235350   \n",
       "128   135019  18.875011  -99.159422   \n",
       "129   132877  22.135364 -100.934948   \n",
       "\n",
       "                                        the_geom_meter  \\\n",
       "0    0101000020957F000088568DE356715AC138C0A525FC46...   \n",
       "1    0101000020957F00001AD016568C4858C1243261274BA5...   \n",
       "2    0101000020957F0000649D6F21634858C119AE9BF528A3...   \n",
       "3    0101000020957F00005D67BCDDED8157C1222A2DC8D84D...   \n",
       "4    0101000020957F00008EBA2D06DC8157C194E03B7B504E...   \n",
       "..                                                 ...   \n",
       "125  0101000020957F000013871838EC4A58C1B5DF74F8E396...   \n",
       "126  0101000020957F0000E7B79B1DB94758C1D29BC363D8AA...   \n",
       "127  0101000020957F0000A6BF695F136F5AC1DADF87B20556...   \n",
       "128  0101000020957F0000B49B2E5C6E785AC12F9D58435241...   \n",
       "129  0101000020957F000090735015B84B58C1AF0DC0414698...   \n",
       "\n",
       "                               name  \\\n",
       "0                   Kiku Cuernavaca   \n",
       "1                   puesto de tacos   \n",
       "2      El Rincï¿½n de San Francisco   \n",
       "3    little pizza Emilio Portes Gil   \n",
       "4                     carnitas_mata   \n",
       "..                              ...   \n",
       "125                         Chaires   \n",
       "126                      Sushi Itto   \n",
       "127                       Paniroles   \n",
       "128     Restaurant Bar Coty y Pablo   \n",
       "129                sirloin stockade   \n",
       "\n",
       "                                             address             city  \\\n",
       "0                                         Revolucion       Cuernavaca   \n",
       "1             esquina santos degollado y leon guzman           s.l.p.   \n",
       "2                                    Universidad 169  San Luis Potosi   \n",
       "3                            calle emilio portes gil        victoria    \n",
       "4                             lic. Emilio portes gil         victoria   \n",
       "..                                               ...              ...   \n",
       "125                                 Ricardo B. Anaya  San Luis Potosi   \n",
       "126               Venustiano Carranza 1809 C Polanco  San Luis Potosi   \n",
       "127                                              NaN              NaN   \n",
       "128  Paseo de Las Fuentes 24 Pedregal de Las Fuentes         Jiutepec   \n",
       "129                                              NaN              NaN   \n",
       "\n",
       "               state country  fax  ...            alcohol   smoking_area  \\\n",
       "0            Morelos  Mexico  NaN  ...  No_Alcohol_Served           none   \n",
       "1             s.l.p.  mexico  NaN  ...  No_Alcohol_Served           none   \n",
       "2    San Luis Potosi  Mexico  NaN  ...          Wine-Beer    only at bar   \n",
       "3         tamaulipas     NaN  NaN  ...  No_Alcohol_Served           none   \n",
       "4         Tamaulipas  Mexico  NaN  ...  No_Alcohol_Served      permitted   \n",
       "..               ...     ...  ...  ...                ...            ...   \n",
       "125  San Luis Potosi  Mexico  NaN  ...  No_Alcohol_Served  not permitted   \n",
       "126              SLP  Mexico  NaN  ...  No_Alcohol_Served           none   \n",
       "127              NaN     NaN  NaN  ...          Wine-Beer  not permitted   \n",
       "128          Morelos  Mexico  NaN  ...  No_Alcohol_Served           none   \n",
       "129              NaN     NaN  NaN  ...  No_Alcohol_Served           none   \n",
       "\n",
       "    dress_code     accessibility   price                    url Rambience  \\\n",
       "0     informal  no_accessibility  medium  kikucuernavaca.com.mx  familiar   \n",
       "1     informal        completely     low                    NaN  familiar   \n",
       "2     informal         partially  medium                    NaN  familiar   \n",
       "3     informal        completely     low                    NaN  familiar   \n",
       "4     informal        completely  medium                    NaN  familiar   \n",
       "..         ...               ...     ...                    ...       ...   \n",
       "125   informal        completely  medium                    NaN  familiar   \n",
       "126   informal  no_accessibility  medium      sushi-itto.com.mx  familiar   \n",
       "127   informal  no_accessibility  medium                    NaN     quiet   \n",
       "128   informal        completely     low                    NaN  familiar   \n",
       "129   informal        completely     low                    NaN  familiar   \n",
       "\n",
       "    franchise    area other_services  \n",
       "0           f  closed           none  \n",
       "1           f    open           none  \n",
       "2           f    open           none  \n",
       "3           t  closed           none  \n",
       "4           t  closed           none  \n",
       "..        ...     ...            ...  \n",
       "125         f  closed           none  \n",
       "126         f  closed           none  \n",
       "127         f  closed       Internet  \n",
       "128         f  closed           none  \n",
       "129         f  closed           none  \n",
       "\n",
       "[130 rows x 21 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "places_geo_df.replace('?', np.nan, inplace=True)  # replace the unknown value '?' with np.Nan\n",
    "places_geo_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 130 entries, 0 to 129\n",
      "Data columns (total 21 columns):\n",
      " #   Column          Non-Null Count  Dtype  \n",
      "---  ------          --------------  -----  \n",
      " 0   placeID         130 non-null    int64  \n",
      " 1   latitude        130 non-null    float64\n",
      " 2   longitude       130 non-null    float64\n",
      " 3   the_geom_meter  130 non-null    object \n",
      " 4   name            130 non-null    object \n",
      " 5   address         103 non-null    object \n",
      " 6   city            112 non-null    object \n",
      " 7   state           112 non-null    object \n",
      " 8   country         102 non-null    object \n",
      " 9   fax             0 non-null      float64\n",
      " 10  zip             56 non-null     object \n",
      " 11  alcohol         130 non-null    object \n",
      " 12  smoking_area    130 non-null    object \n",
      " 13  dress_code      130 non-null    object \n",
      " 14  accessibility   130 non-null    object \n",
      " 15  price           130 non-null    object \n",
      " 16  url             14 non-null     object \n",
      " 17  Rambience       130 non-null    object \n",
      " 18  franchise       130 non-null    object \n",
      " 19  area            130 non-null    object \n",
      " 20  other_services  130 non-null    object \n",
      "dtypes: float64(3), int64(1), object(17)\n",
      "memory usage: 21.5+ KB\n"
     ]
    }
   ],
   "source": [
    "places_geo_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# remove the \"fax\" and \"url\" column since they are mostly null\n",
    "places_geo_df.drop(columns=['fax', 'url'], inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Concatenate the restaurant dfs into a single df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>placeID</th>\n",
       "      <th>payment</th>\n",
       "      <th>cuisine</th>\n",
       "      <th>parking_lot</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>the_geom_meter</th>\n",
       "      <th>name</th>\n",
       "      <th>address</th>\n",
       "      <th>city</th>\n",
       "      <th>...</th>\n",
       "      <th>zip</th>\n",
       "      <th>alcohol</th>\n",
       "      <th>smoking_area</th>\n",
       "      <th>dress_code</th>\n",
       "      <th>accessibility</th>\n",
       "      <th>price</th>\n",
       "      <th>Rambience</th>\n",
       "      <th>franchise</th>\n",
       "      <th>area</th>\n",
       "      <th>other_services</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>132002</td>\n",
       "      <td>MasterCard-Eurocard;Visa;American_Express;Dine...</td>\n",
       "      <td>Seafood</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>132012</td>\n",
       "      <td>Visa;American_Express;bank_debit_cards;Diners_...</td>\n",
       "      <td>French;Dutch-Belgian</td>\n",
       "      <td>public;street</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>132019</td>\n",
       "      <td>MasterCard-Eurocard;Visa;American_Express;Dine...</td>\n",
       "      <td>Dutch-Belgian</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>132023</td>\n",
       "      <td>American_Express;Japan_Credit_Bureau;bank_debi...</td>\n",
       "      <td>French;Dutch-Belgian</td>\n",
       "      <td>fee;public</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>132024</td>\n",
       "      <td>Visa;American_Express;bank_debit_cards;Diners_...</td>\n",
       "      <td>Seafood;Continental-European</td>\n",
       "      <td>street</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>929</th>\n",
       "      <td>133041</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>none</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>930</th>\n",
       "      <td>133042</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>none</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>931</th>\n",
       "      <td>134979</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>none</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>932</th>\n",
       "      <td>135108</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>none</td>\n",
       "      <td>22.1363</td>\n",
       "      <td>-100.934</td>\n",
       "      <td>0101000020957F00008FAE40D59E4B58C112C66046D597...</td>\n",
       "      <td>Potzocalli</td>\n",
       "      <td>Carretera Central Sn</td>\n",
       "      <td>San Luis Potosi</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>No_Alcohol_Served</td>\n",
       "      <td>none</td>\n",
       "      <td>informal</td>\n",
       "      <td>completely</td>\n",
       "      <td>low</td>\n",
       "      <td>familiar</td>\n",
       "      <td>f</td>\n",
       "      <td>closed</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>933</th>\n",
       "      <td>135111</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>public</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>934 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    placeID                                            payment  \\\n",
       "0    132002  MasterCard-Eurocard;Visa;American_Express;Dine...   \n",
       "1    132012  Visa;American_Express;bank_debit_cards;Diners_...   \n",
       "2    132019  MasterCard-Eurocard;Visa;American_Express;Dine...   \n",
       "3    132023  American_Express;Japan_Credit_Bureau;bank_debi...   \n",
       "4    132024  Visa;American_Express;bank_debit_cards;Diners_...   \n",
       "..      ...                                                ...   \n",
       "929  133041                                               None   \n",
       "930  133042                                               None   \n",
       "931  134979                                               None   \n",
       "932  135108                                               None   \n",
       "933  135111                                               None   \n",
       "\n",
       "                          cuisine    parking_lot latitude longitude  \\\n",
       "0                         Seafood           None     None      None   \n",
       "1            French;Dutch-Belgian  public;street     None      None   \n",
       "2                   Dutch-Belgian           None     None      None   \n",
       "3            French;Dutch-Belgian     fee;public     None      None   \n",
       "4    Seafood;Continental-European         street     None      None   \n",
       "..                            ...            ...      ...       ...   \n",
       "929                          None           none     None      None   \n",
       "930                          None           none     None      None   \n",
       "931                          None           none     None      None   \n",
       "932                          None           none  22.1363  -100.934   \n",
       "933                          None         public     None      None   \n",
       "\n",
       "                                        the_geom_meter        name  \\\n",
       "0                                                 None        None   \n",
       "1                                                 None        None   \n",
       "2                                                 None        None   \n",
       "3                                                 None        None   \n",
       "4                                                 None        None   \n",
       "..                                                 ...         ...   \n",
       "929                                               None        None   \n",
       "930                                               None        None   \n",
       "931                                               None        None   \n",
       "932  0101000020957F00008FAE40D59E4B58C112C66046D597...  Potzocalli   \n",
       "933                                               None        None   \n",
       "\n",
       "                  address             city  ...   zip            alcohol  \\\n",
       "0                    None             None  ...  None               None   \n",
       "1                    None             None  ...  None               None   \n",
       "2                    None             None  ...  None               None   \n",
       "3                    None             None  ...  None               None   \n",
       "4                    None             None  ...  None               None   \n",
       "..                    ...              ...  ...   ...                ...   \n",
       "929                  None             None  ...  None               None   \n",
       "930                  None             None  ...  None               None   \n",
       "931                  None             None  ...  None               None   \n",
       "932  Carretera Central Sn  San Luis Potosi  ...  None  No_Alcohol_Served   \n",
       "933                  None             None  ...  None               None   \n",
       "\n",
       "    smoking_area dress_code accessibility price Rambience franchise    area  \\\n",
       "0           None       None          None  None      None      None    None   \n",
       "1           None       None          None  None      None      None    None   \n",
       "2           None       None          None  None      None      None    None   \n",
       "3           None       None          None  None      None      None    None   \n",
       "4           None       None          None  None      None      None    None   \n",
       "..           ...        ...           ...   ...       ...       ...     ...   \n",
       "929         None       None          None  None      None      None    None   \n",
       "930         None       None          None  None      None      None    None   \n",
       "931         None       None          None  None      None      None    None   \n",
       "932         none   informal    completely   low  familiar         f  closed   \n",
       "933         None       None          None  None      None      None    None   \n",
       "\n",
       "    other_services  \n",
       "0             None  \n",
       "1             None  \n",
       "2             None  \n",
       "3             None  \n",
       "4             None  \n",
       "..             ...  \n",
       "929           None  \n",
       "930           None  \n",
       "931           None  \n",
       "932           none  \n",
       "933           None  \n",
       "\n",
       "[934 rows x 22 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from functools import reduce\n",
    "places_df = reduce(lambda left,right: pd.merge(left, right, on='placeID', how='outer'), [places_accept_df, places_cuisine_df, places_parking_df, places_geo_df])\n",
    "places_df.placeID = places_df.placeID.astype(str)\n",
    "places_df.replace({np.nan: None}, inplace=True)\n",
    "places_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## User files"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### usercuisine file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>userID</th>\n",
       "      <th>Rcuisine</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>U1001</td>\n",
       "      <td>American</td>\n",
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       "      <th>1</th>\n",
       "      <td>U1002</td>\n",
       "      <td>Mexican</td>\n",
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       "      <th>2</th>\n",
       "      <td>U1003</td>\n",
       "      <td>Mexican</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>U1004</td>\n",
       "      <td>Bakery</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>U1004</td>\n",
       "      <td>Breakfast-Brunch</td>\n",
       "    </tr>\n",
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       "      <th>...</th>\n",
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       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>325</th>\n",
       "      <td>U1135</td>\n",
       "      <td>Southern</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>326</th>\n",
       "      <td>U1135</td>\n",
       "      <td>Dessert-Ice_Cream</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>327</th>\n",
       "      <td>U1136</td>\n",
       "      <td>Mexican</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>328</th>\n",
       "      <td>U1137</td>\n",
       "      <td>Mexican</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>329</th>\n",
       "      <td>U1138</td>\n",
       "      <td>Pizzeria</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>330 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    userID           Rcuisine\n",
       "0    U1001           American\n",
       "1    U1002            Mexican\n",
       "2    U1003            Mexican\n",
       "3    U1004             Bakery\n",
       "4    U1004   Breakfast-Brunch\n",
       "..     ...                ...\n",
       "325  U1135           Southern\n",
       "326  U1135  Dessert-Ice_Cream\n",
       "327  U1136            Mexican\n",
       "328  U1137            Mexican\n",
       "329  U1138           Pizzeria\n",
       "\n",
       "[330 rows x 2 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "users_cuisine_df = pd.read_csv(data_folder / 'usercuisine.csv')\n",
    "users_cuisine_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>userID</th>\n",
       "      <th>cuisine</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>U1001</td>\n",
       "      <td>American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>U1002</td>\n",
       "      <td>Mexican</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>U1003</td>\n",
       "      <td>Mexican</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>U1004</td>\n",
       "      <td>Bakery; Breakfast-Brunch; Japanese; Contempora...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>U1005</td>\n",
       "      <td>American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>U1134</td>\n",
       "      <td>Mexican</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>U1135</td>\n",
       "      <td>Organic-Healthy; Steaks; Middle_Eastern; Medit...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>U1136</td>\n",
       "      <td>Mexican</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>U1137</td>\n",
       "      <td>Mexican</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>U1138</td>\n",
       "      <td>Pizzeria</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>138 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    userID                                            cuisine\n",
       "0    U1001                                           American\n",
       "1    U1002                                            Mexican\n",
       "2    U1003                                            Mexican\n",
       "3    U1004  Bakery; Breakfast-Brunch; Japanese; Contempora...\n",
       "4    U1005                                           American\n",
       "..     ...                                                ...\n",
       "133  U1134                                            Mexican\n",
       "134  U1135  Organic-Healthy; Steaks; Middle_Eastern; Medit...\n",
       "135  U1136                                            Mexican\n",
       "136  U1137                                            Mexican\n",
       "137  U1138                                           Pizzeria\n",
       "\n",
       "[138 rows x 2 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "users_cuisine_df.rename(columns={'Rcuisine': 'cuisine'}, inplace=True)\n",
    "users_cuisine_df = users_cuisine_df.groupby('userID').agg({'cuisine': lambda x: '; '.join(x)}).reset_index()\n",
    "users_cuisine_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### userpayment file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>userID</th>\n",
       "      <th>Upayment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>U1001</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>U1002</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>U1003</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>U1004</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>U1004</td>\n",
       "      <td>bank_debit_cards</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>U1134</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>U1135</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>U1136</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>U1137</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>U1138</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>177 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    userID          Upayment\n",
       "0    U1001              cash\n",
       "1    U1002              cash\n",
       "2    U1003              cash\n",
       "3    U1004              cash\n",
       "4    U1004  bank_debit_cards\n",
       "..     ...               ...\n",
       "172  U1134              cash\n",
       "173  U1135              cash\n",
       "174  U1136              cash\n",
       "175  U1137              cash\n",
       "176  U1138              cash\n",
       "\n",
       "[177 rows x 2 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "users_payment_df = pd.read_csv(data_folder / 'userpayment.csv')\n",
    "users_payment_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>userID</th>\n",
       "      <th>payment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>U1001</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>U1002</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>U1003</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>U1004</td>\n",
       "      <td>cash; bank_debit_cards</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>U1005</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>U1134</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>U1135</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>U1136</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>U1137</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>U1138</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>133 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    userID                 payment\n",
       "0    U1001                    cash\n",
       "1    U1002                    cash\n",
       "2    U1003                    cash\n",
       "3    U1004  cash; bank_debit_cards\n",
       "4    U1005                    cash\n",
       "..     ...                     ...\n",
       "128  U1134                    cash\n",
       "129  U1135                    cash\n",
       "130  U1136                    cash\n",
       "131  U1137                    cash\n",
       "132  U1138                    cash\n",
       "\n",
       "[133 rows x 2 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "users_payment_df.rename(columns={'Upayment': 'payment'}, inplace=True)\n",
    "users_payment_df = users_payment_df.groupby('userID').agg({'payment': lambda x: '; '.join(x)}).reset_index()\n",
    "users_payment_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### userprofile file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>userID</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>smoker</th>\n",
       "      <th>drink_level</th>\n",
       "      <th>dress_preference</th>\n",
       "      <th>ambience</th>\n",
       "      <th>transport</th>\n",
       "      <th>marital_status</th>\n",
       "      <th>hijos</th>\n",
       "      <th>birth_year</th>\n",
       "      <th>interest</th>\n",
       "      <th>personality</th>\n",
       "      <th>religion</th>\n",
       "      <th>activity</th>\n",
       "      <th>color</th>\n",
       "      <th>weight</th>\n",
       "      <th>budget</th>\n",
       "      <th>height</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>U1001</td>\n",
       "      <td>22.139997</td>\n",
       "      <td>-100.978803</td>\n",
       "      <td>false</td>\n",
       "      <td>abstemious</td>\n",
       "      <td>informal</td>\n",
       "      <td>family</td>\n",
       "      <td>on foot</td>\n",
       "      <td>single</td>\n",
       "      <td>independent</td>\n",
       "      <td>1989</td>\n",
       "      <td>variety</td>\n",
       "      <td>thrifty-protector</td>\n",
       "      <td>none</td>\n",
       "      <td>student</td>\n",
       "      <td>black</td>\n",
       "      <td>69</td>\n",
       "      <td>medium</td>\n",
       "      <td>1.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>U1002</td>\n",
       "      <td>22.150087</td>\n",
       "      <td>-100.983325</td>\n",
       "      <td>false</td>\n",
       "      <td>abstemious</td>\n",
       "      <td>informal</td>\n",
       "      <td>family</td>\n",
       "      <td>public</td>\n",
       "      <td>single</td>\n",
       "      <td>independent</td>\n",
       "      <td>1990</td>\n",
       "      <td>technology</td>\n",
       "      <td>hunter-ostentatious</td>\n",
       "      <td>Catholic</td>\n",
       "      <td>student</td>\n",
       "      <td>red</td>\n",
       "      <td>40</td>\n",
       "      <td>low</td>\n",
       "      <td>1.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>U1003</td>\n",
       "      <td>22.119847</td>\n",
       "      <td>-100.946527</td>\n",
       "      <td>false</td>\n",
       "      <td>social drinker</td>\n",
       "      <td>formal</td>\n",
       "      <td>family</td>\n",
       "      <td>public</td>\n",
       "      <td>single</td>\n",
       "      <td>independent</td>\n",
       "      <td>1989</td>\n",
       "      <td>none</td>\n",
       "      <td>hard-worker</td>\n",
       "      <td>Catholic</td>\n",
       "      <td>student</td>\n",
       "      <td>blue</td>\n",
       "      <td>60</td>\n",
       "      <td>low</td>\n",
       "      <td>1.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>U1004</td>\n",
       "      <td>18.867000</td>\n",
       "      <td>-99.183000</td>\n",
       "      <td>false</td>\n",
       "      <td>abstemious</td>\n",
       "      <td>informal</td>\n",
       "      <td>family</td>\n",
       "      <td>public</td>\n",
       "      <td>single</td>\n",
       "      <td>independent</td>\n",
       "      <td>1940</td>\n",
       "      <td>variety</td>\n",
       "      <td>hard-worker</td>\n",
       "      <td>none</td>\n",
       "      <td>professional</td>\n",
       "      <td>green</td>\n",
       "      <td>44</td>\n",
       "      <td>medium</td>\n",
       "      <td>1.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>U1005</td>\n",
       "      <td>22.183477</td>\n",
       "      <td>-100.959891</td>\n",
       "      <td>false</td>\n",
       "      <td>abstemious</td>\n",
       "      <td>no preference</td>\n",
       "      <td>family</td>\n",
       "      <td>public</td>\n",
       "      <td>single</td>\n",
       "      <td>independent</td>\n",
       "      <td>1992</td>\n",
       "      <td>none</td>\n",
       "      <td>thrifty-protector</td>\n",
       "      <td>Catholic</td>\n",
       "      <td>student</td>\n",
       "      <td>black</td>\n",
       "      <td>65</td>\n",
       "      <td>medium</td>\n",
       "      <td>1.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>U1134</td>\n",
       "      <td>22.149654</td>\n",
       "      <td>-100.998610</td>\n",
       "      <td>false</td>\n",
       "      <td>casual drinker</td>\n",
       "      <td>no preference</td>\n",
       "      <td>family</td>\n",
       "      <td>public</td>\n",
       "      <td>single</td>\n",
       "      <td>independent</td>\n",
       "      <td>1991</td>\n",
       "      <td>variety</td>\n",
       "      <td>hard-worker</td>\n",
       "      <td>Catholic</td>\n",
       "      <td>student</td>\n",
       "      <td>black</td>\n",
       "      <td>52</td>\n",
       "      <td>medium</td>\n",
       "      <td>1.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>U1135</td>\n",
       "      <td>22.170396</td>\n",
       "      <td>-100.949936</td>\n",
       "      <td>false</td>\n",
       "      <td>casual drinker</td>\n",
       "      <td>informal</td>\n",
       "      <td>family</td>\n",
       "      <td>on foot</td>\n",
       "      <td>single</td>\n",
       "      <td>kids</td>\n",
       "      <td>1988</td>\n",
       "      <td>variety</td>\n",
       "      <td>hunter-ostentatious</td>\n",
       "      <td>Catholic</td>\n",
       "      <td>student</td>\n",
       "      <td>purple</td>\n",
       "      <td>66</td>\n",
       "      <td>low</td>\n",
       "      <td>1.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>U1136</td>\n",
       "      <td>22.149607</td>\n",
       "      <td>-100.997235</td>\n",
       "      <td>true</td>\n",
       "      <td>social drinker</td>\n",
       "      <td>no preference</td>\n",
       "      <td>friends</td>\n",
       "      <td>car owner</td>\n",
       "      <td>single</td>\n",
       "      <td>independent</td>\n",
       "      <td>1990</td>\n",
       "      <td>retro</td>\n",
       "      <td>thrifty-protector</td>\n",
       "      <td>Catholic</td>\n",
       "      <td>student</td>\n",
       "      <td>black</td>\n",
       "      <td>50</td>\n",
       "      <td>low</td>\n",
       "      <td>1.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>U1137</td>\n",
       "      <td>22.144803</td>\n",
       "      <td>-100.944623</td>\n",
       "      <td>false</td>\n",
       "      <td>social drinker</td>\n",
       "      <td>formal</td>\n",
       "      <td>family</td>\n",
       "      <td>public</td>\n",
       "      <td>single</td>\n",
       "      <td>independent</td>\n",
       "      <td>1989</td>\n",
       "      <td>eco-friendly</td>\n",
       "      <td>hard-worker</td>\n",
       "      <td>Catholic</td>\n",
       "      <td>student</td>\n",
       "      <td>blue</td>\n",
       "      <td>72</td>\n",
       "      <td>low</td>\n",
       "      <td>1.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>U1138</td>\n",
       "      <td>22.152884</td>\n",
       "      <td>-100.939663</td>\n",
       "      <td>false</td>\n",
       "      <td>social drinker</td>\n",
       "      <td>formal</td>\n",
       "      <td>friends</td>\n",
       "      <td>public</td>\n",
       "      <td>single</td>\n",
       "      <td>independent</td>\n",
       "      <td>1991</td>\n",
       "      <td>variety</td>\n",
       "      <td>thrifty-protector</td>\n",
       "      <td>none</td>\n",
       "      <td>student</td>\n",
       "      <td>blue</td>\n",
       "      <td>54</td>\n",
       "      <td>medium</td>\n",
       "      <td>1.55</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>138 rows × 19 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    userID   latitude   longitude smoker     drink_level dress_preference  \\\n",
       "0    U1001  22.139997 -100.978803  false      abstemious         informal   \n",
       "1    U1002  22.150087 -100.983325  false      abstemious         informal   \n",
       "2    U1003  22.119847 -100.946527  false  social drinker           formal   \n",
       "3    U1004  18.867000  -99.183000  false      abstemious         informal   \n",
       "4    U1005  22.183477 -100.959891  false      abstemious    no preference   \n",
       "..     ...        ...         ...    ...             ...              ...   \n",
       "133  U1134  22.149654 -100.998610  false  casual drinker    no preference   \n",
       "134  U1135  22.170396 -100.949936  false  casual drinker         informal   \n",
       "135  U1136  22.149607 -100.997235   true  social drinker    no preference   \n",
       "136  U1137  22.144803 -100.944623  false  social drinker           formal   \n",
       "137  U1138  22.152884 -100.939663  false  social drinker           formal   \n",
       "\n",
       "    ambience  transport marital_status        hijos  birth_year      interest  \\\n",
       "0     family    on foot         single  independent        1989       variety   \n",
       "1     family     public         single  independent        1990    technology   \n",
       "2     family     public         single  independent        1989          none   \n",
       "3     family     public         single  independent        1940       variety   \n",
       "4     family     public         single  independent        1992          none   \n",
       "..       ...        ...            ...          ...         ...           ...   \n",
       "133   family     public         single  independent        1991       variety   \n",
       "134   family    on foot         single         kids        1988       variety   \n",
       "135  friends  car owner         single  independent        1990         retro   \n",
       "136   family     public         single  independent        1989  eco-friendly   \n",
       "137  friends     public         single  independent        1991       variety   \n",
       "\n",
       "             personality  religion      activity   color  weight  budget  \\\n",
       "0      thrifty-protector      none       student   black      69  medium   \n",
       "1    hunter-ostentatious  Catholic       student     red      40     low   \n",
       "2            hard-worker  Catholic       student    blue      60     low   \n",
       "3            hard-worker      none  professional   green      44  medium   \n",
       "4      thrifty-protector  Catholic       student   black      65  medium   \n",
       "..                   ...       ...           ...     ...     ...     ...   \n",
       "133          hard-worker  Catholic       student   black      52  medium   \n",
       "134  hunter-ostentatious  Catholic       student  purple      66     low   \n",
       "135    thrifty-protector  Catholic       student   black      50     low   \n",
       "136          hard-worker  Catholic       student    blue      72     low   \n",
       "137    thrifty-protector      none       student    blue      54  medium   \n",
       "\n",
       "     height  \n",
       "0      1.77  \n",
       "1      1.87  \n",
       "2      1.69  \n",
       "3      1.53  \n",
       "4      1.69  \n",
       "..      ...  \n",
       "133    1.65  \n",
       "134    1.54  \n",
       "135    1.60  \n",
       "136    1.78  \n",
       "137    1.55  \n",
       "\n",
       "[138 rows x 19 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "users_profile_df = pd.read_csv(data_folder / 'userprofile.csv')\n",
    "users_profile_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>userID</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>smoker</th>\n",
       "      <th>drink_level</th>\n",
       "      <th>dress_preference</th>\n",
       "      <th>ambience</th>\n",
       "      <th>transport</th>\n",
       "      <th>marital_status</th>\n",
       "      <th>hijos</th>\n",
       "      <th>...</th>\n",
       "      <th>interest</th>\n",
       "      <th>personality</th>\n",
       "      <th>religion</th>\n",
       "      <th>activity</th>\n",
       "      <th>color</th>\n",
       "      <th>weight</th>\n",
       "      <th>budget</th>\n",
       "      <th>height</th>\n",
       "      <th>cuisine</th>\n",
       "      <th>payment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>U1001</td>\n",
       "      <td>22.139997</td>\n",
       "      <td>-100.978803</td>\n",
       "      <td>false</td>\n",
       "      <td>abstemious</td>\n",
       "      <td>informal</td>\n",
       "      <td>family</td>\n",
       "      <td>on foot</td>\n",
       "      <td>single</td>\n",
       "      <td>independent</td>\n",
       "      <td>...</td>\n",
       "      <td>variety</td>\n",
       "      <td>thrifty-protector</td>\n",
       "      <td>none</td>\n",
       "      <td>student</td>\n",
       "      <td>black</td>\n",
       "      <td>69</td>\n",
       "      <td>medium</td>\n",
       "      <td>1.77</td>\n",
       "      <td>American</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>U1002</td>\n",
       "      <td>22.150087</td>\n",
       "      <td>-100.983325</td>\n",
       "      <td>false</td>\n",
       "      <td>abstemious</td>\n",
       "      <td>informal</td>\n",
       "      <td>family</td>\n",
       "      <td>public</td>\n",
       "      <td>single</td>\n",
       "      <td>independent</td>\n",
       "      <td>...</td>\n",
       "      <td>technology</td>\n",
       "      <td>hunter-ostentatious</td>\n",
       "      <td>Catholic</td>\n",
       "      <td>student</td>\n",
       "      <td>red</td>\n",
       "      <td>40</td>\n",
       "      <td>low</td>\n",
       "      <td>1.87</td>\n",
       "      <td>Mexican</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>U1003</td>\n",
       "      <td>22.119847</td>\n",
       "      <td>-100.946527</td>\n",
       "      <td>false</td>\n",
       "      <td>social drinker</td>\n",
       "      <td>formal</td>\n",
       "      <td>family</td>\n",
       "      <td>public</td>\n",
       "      <td>single</td>\n",
       "      <td>independent</td>\n",
       "      <td>...</td>\n",
       "      <td>none</td>\n",
       "      <td>hard-worker</td>\n",
       "      <td>Catholic</td>\n",
       "      <td>student</td>\n",
       "      <td>blue</td>\n",
       "      <td>60</td>\n",
       "      <td>low</td>\n",
       "      <td>1.69</td>\n",
       "      <td>Mexican</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>U1004</td>\n",
       "      <td>18.867000</td>\n",
       "      <td>-99.183000</td>\n",
       "      <td>false</td>\n",
       "      <td>abstemious</td>\n",
       "      <td>informal</td>\n",
       "      <td>family</td>\n",
       "      <td>public</td>\n",
       "      <td>single</td>\n",
       "      <td>independent</td>\n",
       "      <td>...</td>\n",
       "      <td>variety</td>\n",
       "      <td>hard-worker</td>\n",
       "      <td>none</td>\n",
       "      <td>professional</td>\n",
       "      <td>green</td>\n",
       "      <td>44</td>\n",
       "      <td>medium</td>\n",
       "      <td>1.53</td>\n",
       "      <td>Bakery; Breakfast-Brunch; Japanese; Contempora...</td>\n",
       "      <td>cash; bank_debit_cards</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>U1005</td>\n",
       "      <td>22.183477</td>\n",
       "      <td>-100.959891</td>\n",
       "      <td>false</td>\n",
       "      <td>abstemious</td>\n",
       "      <td>no preference</td>\n",
       "      <td>family</td>\n",
       "      <td>public</td>\n",
       "      <td>single</td>\n",
       "      <td>independent</td>\n",
       "      <td>...</td>\n",
       "      <td>none</td>\n",
       "      <td>thrifty-protector</td>\n",
       "      <td>Catholic</td>\n",
       "      <td>student</td>\n",
       "      <td>black</td>\n",
       "      <td>65</td>\n",
       "      <td>medium</td>\n",
       "      <td>1.69</td>\n",
       "      <td>American</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>U1134</td>\n",
       "      <td>22.149654</td>\n",
       "      <td>-100.998610</td>\n",
       "      <td>false</td>\n",
       "      <td>casual drinker</td>\n",
       "      <td>no preference</td>\n",
       "      <td>family</td>\n",
       "      <td>public</td>\n",
       "      <td>single</td>\n",
       "      <td>independent</td>\n",
       "      <td>...</td>\n",
       "      <td>variety</td>\n",
       "      <td>hard-worker</td>\n",
       "      <td>Catholic</td>\n",
       "      <td>student</td>\n",
       "      <td>black</td>\n",
       "      <td>52</td>\n",
       "      <td>medium</td>\n",
       "      <td>1.65</td>\n",
       "      <td>Mexican</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>U1135</td>\n",
       "      <td>22.170396</td>\n",
       "      <td>-100.949936</td>\n",
       "      <td>false</td>\n",
       "      <td>casual drinker</td>\n",
       "      <td>informal</td>\n",
       "      <td>family</td>\n",
       "      <td>on foot</td>\n",
       "      <td>single</td>\n",
       "      <td>kids</td>\n",
       "      <td>...</td>\n",
       "      <td>variety</td>\n",
       "      <td>hunter-ostentatious</td>\n",
       "      <td>Catholic</td>\n",
       "      <td>student</td>\n",
       "      <td>purple</td>\n",
       "      <td>66</td>\n",
       "      <td>low</td>\n",
       "      <td>1.54</td>\n",
       "      <td>Organic-Healthy; Steaks; Middle_Eastern; Medit...</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>U1136</td>\n",
       "      <td>22.149607</td>\n",
       "      <td>-100.997235</td>\n",
       "      <td>true</td>\n",
       "      <td>social drinker</td>\n",
       "      <td>no preference</td>\n",
       "      <td>friends</td>\n",
       "      <td>car owner</td>\n",
       "      <td>single</td>\n",
       "      <td>independent</td>\n",
       "      <td>...</td>\n",
       "      <td>retro</td>\n",
       "      <td>thrifty-protector</td>\n",
       "      <td>Catholic</td>\n",
       "      <td>student</td>\n",
       "      <td>black</td>\n",
       "      <td>50</td>\n",
       "      <td>low</td>\n",
       "      <td>1.60</td>\n",
       "      <td>Mexican</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>U1137</td>\n",
       "      <td>22.144803</td>\n",
       "      <td>-100.944623</td>\n",
       "      <td>false</td>\n",
       "      <td>social drinker</td>\n",
       "      <td>formal</td>\n",
       "      <td>family</td>\n",
       "      <td>public</td>\n",
       "      <td>single</td>\n",
       "      <td>independent</td>\n",
       "      <td>...</td>\n",
       "      <td>eco-friendly</td>\n",
       "      <td>hard-worker</td>\n",
       "      <td>Catholic</td>\n",
       "      <td>student</td>\n",
       "      <td>blue</td>\n",
       "      <td>72</td>\n",
       "      <td>low</td>\n",
       "      <td>1.78</td>\n",
       "      <td>Mexican</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>U1138</td>\n",
       "      <td>22.152884</td>\n",
       "      <td>-100.939663</td>\n",
       "      <td>false</td>\n",
       "      <td>social drinker</td>\n",
       "      <td>formal</td>\n",
       "      <td>friends</td>\n",
       "      <td>public</td>\n",
       "      <td>single</td>\n",
       "      <td>independent</td>\n",
       "      <td>...</td>\n",
       "      <td>variety</td>\n",
       "      <td>thrifty-protector</td>\n",
       "      <td>none</td>\n",
       "      <td>student</td>\n",
       "      <td>blue</td>\n",
       "      <td>54</td>\n",
       "      <td>medium</td>\n",
       "      <td>1.55</td>\n",
       "      <td>Pizzeria</td>\n",
       "      <td>cash</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>138 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    userID   latitude   longitude smoker     drink_level dress_preference  \\\n",
       "0    U1001  22.139997 -100.978803  false      abstemious         informal   \n",
       "1    U1002  22.150087 -100.983325  false      abstemious         informal   \n",
       "2    U1003  22.119847 -100.946527  false  social drinker           formal   \n",
       "3    U1004  18.867000  -99.183000  false      abstemious         informal   \n",
       "4    U1005  22.183477 -100.959891  false      abstemious    no preference   \n",
       "..     ...        ...         ...    ...             ...              ...   \n",
       "133  U1134  22.149654 -100.998610  false  casual drinker    no preference   \n",
       "134  U1135  22.170396 -100.949936  false  casual drinker         informal   \n",
       "135  U1136  22.149607 -100.997235   true  social drinker    no preference   \n",
       "136  U1137  22.144803 -100.944623  false  social drinker           formal   \n",
       "137  U1138  22.152884 -100.939663  false  social drinker           formal   \n",
       "\n",
       "    ambience  transport marital_status        hijos  ...      interest  \\\n",
       "0     family    on foot         single  independent  ...       variety   \n",
       "1     family     public         single  independent  ...    technology   \n",
       "2     family     public         single  independent  ...          none   \n",
       "3     family     public         single  independent  ...       variety   \n",
       "4     family     public         single  independent  ...          none   \n",
       "..       ...        ...            ...          ...  ...           ...   \n",
       "133   family     public         single  independent  ...       variety   \n",
       "134   family    on foot         single         kids  ...       variety   \n",
       "135  friends  car owner         single  independent  ...         retro   \n",
       "136   family     public         single  independent  ...  eco-friendly   \n",
       "137  friends     public         single  independent  ...       variety   \n",
       "\n",
       "             personality  religion      activity   color weight  budget  \\\n",
       "0      thrifty-protector      none       student   black     69  medium   \n",
       "1    hunter-ostentatious  Catholic       student     red     40     low   \n",
       "2            hard-worker  Catholic       student    blue     60     low   \n",
       "3            hard-worker      none  professional   green     44  medium   \n",
       "4      thrifty-protector  Catholic       student   black     65  medium   \n",
       "..                   ...       ...           ...     ...    ...     ...   \n",
       "133          hard-worker  Catholic       student   black     52  medium   \n",
       "134  hunter-ostentatious  Catholic       student  purple     66     low   \n",
       "135    thrifty-protector  Catholic       student   black     50     low   \n",
       "136          hard-worker  Catholic       student    blue     72     low   \n",
       "137    thrifty-protector      none       student    blue     54  medium   \n",
       "\n",
       "    height                                            cuisine  \\\n",
       "0     1.77                                           American   \n",
       "1     1.87                                            Mexican   \n",
       "2     1.69                                            Mexican   \n",
       "3     1.53  Bakery; Breakfast-Brunch; Japanese; Contempora...   \n",
       "4     1.69                                           American   \n",
       "..     ...                                                ...   \n",
       "133   1.65                                            Mexican   \n",
       "134   1.54  Organic-Healthy; Steaks; Middle_Eastern; Medit...   \n",
       "135   1.60                                            Mexican   \n",
       "136   1.78                                            Mexican   \n",
       "137   1.55                                           Pizzeria   \n",
       "\n",
       "                    payment  \n",
       "0                      cash  \n",
       "1                      cash  \n",
       "2                      cash  \n",
       "3    cash; bank_debit_cards  \n",
       "4                      cash  \n",
       "..                      ...  \n",
       "133                    cash  \n",
       "134                    cash  \n",
       "135                    cash  \n",
       "136                    cash  \n",
       "137                    cash  \n",
       "\n",
       "[138 rows x 21 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "users_df = reduce(lambda left,right: pd.merge(left, right, on='userID', how='outer'), [users_profile_df, users_cuisine_df, users_payment_df])\n",
    "users_df.replace({np.nan: None}, inplace=True)\n",
    "users_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Ratings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>userID</th>\n",
       "      <th>placeID</th>\n",
       "      <th>rating</th>\n",
       "      <th>food_rating</th>\n",
       "      <th>service_rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>U1077</td>\n",
       "      <td>135085</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>U1077</td>\n",
       "      <td>135038</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>U1077</td>\n",
       "      <td>132825</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>U1077</td>\n",
       "      <td>135060</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>U1068</td>\n",
       "      <td>135104</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1156</th>\n",
       "      <td>U1043</td>\n",
       "      <td>132630</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1157</th>\n",
       "      <td>U1011</td>\n",
       "      <td>132715</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1158</th>\n",
       "      <td>U1068</td>\n",
       "      <td>132733</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1159</th>\n",
       "      <td>U1068</td>\n",
       "      <td>132594</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1160</th>\n",
       "      <td>U1068</td>\n",
       "      <td>132660</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1161 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     userID placeID  rating  food_rating  service_rating\n",
       "0     U1077  135085       2            2               2\n",
       "1     U1077  135038       2            2               1\n",
       "2     U1077  132825       2            2               2\n",
       "3     U1077  135060       1            2               2\n",
       "4     U1068  135104       1            1               2\n",
       "...     ...     ...     ...          ...             ...\n",
       "1156  U1043  132630       1            1               1\n",
       "1157  U1011  132715       1            1               0\n",
       "1158  U1068  132733       1            1               0\n",
       "1159  U1068  132594       1            1               1\n",
       "1160  U1068  132660       0            0               0\n",
       "\n",
       "[1161 rows x 5 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings_df = pd.read_csv(data_folder / 'rating_final.csv')\n",
    "ratings_df.placeID = ratings_df.placeID.astype(str)\n",
    "ratings_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Populate data into Aito\n",
    "Now that we have all the data loaded and processed, we will upload it to your Aito instance"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## First, let's start with creating table schemas for each of the places, users, and ratings tables from their respective dataframes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Infer the Aito Table schema from the places data frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      "  \"type\": \"table\",\n",
      "  \"columns\": {\n",
      "    \"placeID\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": false\n",
      "    },\n",
      "    \"payment\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"cuisine\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"parking_lot\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"latitude\": {\n",
      "      \"type\": \"Decimal\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"longitude\": {\n",
      "      \"type\": \"Decimal\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"the_geom_meter\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"name\": {\n",
      "      \"type\": \"Text\",\n",
      "      \"nullable\": true,\n",
      "      \"analyzer\": {\n",
      "        \"type\": \"language\",\n",
      "        \"language\": \"spanish\",\n",
      "        \"useDefaultStopWords\": false,\n",
      "        \"customStopWords\": [],\n",
      "        \"customKeyWords\": []\n",
      "      }\n",
      "    },\n",
      "    \"address\": {\n",
      "      \"type\": \"Text\",\n",
      "      \"nullable\": true,\n",
      "      \"analyzer\": {\n",
      "        \"type\": \"language\",\n",
      "        \"language\": \"spanish\",\n",
      "        \"useDefaultStopWords\": false,\n",
      "        \"customStopWords\": [],\n",
      "        \"customKeyWords\": []\n",
      "      }\n",
      "    },\n",
      "    \"city\": {\n",
      "      \"type\": \"Text\",\n",
      "      \"nullable\": true,\n",
      "      \"analyzer\": \"whitespace\"\n",
      "    },\n",
      "    \"state\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"country\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"zip\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"alcohol\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"smoking_area\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"dress_code\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"accessibility\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"price\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"Rambience\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"franchise\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"area\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"other_services\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    }\n",
      "  }\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "places_schema = AitoTableSchema.infer_from_pandas_data_frame(places_df)\n",
    "print(places_schema.to_json_string(indent=2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Aito didn't do well to detect some fields to be semicolon delimited. Let's adjust a bit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      "  \"type\": \"table\",\n",
      "  \"columns\": {\n",
      "    \"placeID\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": false\n",
      "    },\n",
      "    \"payment\": {\n",
      "      \"type\": \"Text\",\n",
      "      \"nullable\": true,\n",
      "      \"analyzer\": {\n",
      "        \"type\": \"delimiter\",\n",
      "        \"delimiter\": \";\",\n",
      "        \"trimWhitespace\": true\n",
      "      }\n",
      "    },\n",
      "    \"cuisine\": {\n",
      "      \"type\": \"Text\",\n",
      "      \"nullable\": true,\n",
      "      \"analyzer\": {\n",
      "        \"type\": \"delimiter\",\n",
      "        \"delimiter\": \";\",\n",
      "        \"trimWhitespace\": true\n",
      "      }\n",
      "    },\n",
      "    \"parking_lot\": {\n",
      "      \"type\": \"Text\",\n",
      "      \"nullable\": true,\n",
      "      \"analyzer\": {\n",
      "        \"type\": \"delimiter\",\n",
      "        \"delimiter\": \";\",\n",
      "        \"trimWhitespace\": true\n",
      "      }\n",
      "    },\n",
      "    \"latitude\": {\n",
      "      \"type\": \"Decimal\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"longitude\": {\n",
      "      \"type\": \"Decimal\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"the_geom_meter\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"name\": {\n",
      "      \"type\": \"Text\",\n",
      "      \"nullable\": true,\n",
      "      \"analyzer\": {\n",
      "        \"type\": \"language\",\n",
      "        \"language\": \"spanish\",\n",
      "        \"useDefaultStopWords\": false,\n",
      "        \"customStopWords\": [],\n",
      "        \"customKeyWords\": []\n",
      "      }\n",
      "    },\n",
      "    \"address\": {\n",
      "      \"type\": \"Text\",\n",
      "      \"nullable\": true,\n",
      "      \"analyzer\": {\n",
      "        \"type\": \"language\",\n",
      "        \"language\": \"spanish\",\n",
      "        \"useDefaultStopWords\": false,\n",
      "        \"customStopWords\": [],\n",
      "        \"customKeyWords\": []\n",
      "      }\n",
      "    },\n",
      "    \"city\": {\n",
      "      \"type\": \"Text\",\n",
      "      \"nullable\": true,\n",
      "      \"analyzer\": \"whitespace\"\n",
      "    },\n",
      "    \"state\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"country\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"zip\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"alcohol\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"smoking_area\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"dress_code\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"accessibility\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"price\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"Rambience\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"franchise\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"area\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"other_services\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    }\n",
      "  }\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "for field in ('payment', 'cuisine', 'parking_lot'):\n",
    "    places_schema[field].data_type = AitoTextType()\n",
    "    places_schema[field].analyzer = AitoDelimiterAnalyzerSchema(delimiter=';')\n",
    "print(places_schema.to_json_string(indent=2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      "  \"type\": \"table\",\n",
      "  \"columns\": {\n",
      "    \"placeID\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": false\n",
      "    },\n",
      "    \"payment\": {\n",
      "      \"type\": \"Text\",\n",
      "      \"nullable\": true,\n",
      "      \"analyzer\": {\n",
      "        \"type\": \"delimiter\",\n",
      "        \"delimiter\": \";\",\n",
      "        \"trimWhitespace\": true\n",
      "      }\n",
      "    },\n",
      "    \"cuisine\": {\n",
      "      \"type\": \"Text\",\n",
      "      \"nullable\": true,\n",
      "      \"analyzer\": {\n",
      "        \"type\": \"delimiter\",\n",
      "        \"delimiter\": \";\",\n",
      "        \"trimWhitespace\": true\n",
      "      }\n",
      "    },\n",
      "    \"parking_lot\": {\n",
      "      \"type\": \"Text\",\n",
      "      \"nullable\": true,\n",
      "      \"analyzer\": {\n",
      "        \"type\": \"delimiter\",\n",
      "        \"delimiter\": \";\",\n",
      "        \"trimWhitespace\": true\n",
      "      }\n",
      "    },\n",
      "    \"latitude\": {\n",
      "      \"type\": \"Decimal\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"longitude\": {\n",
      "      \"type\": \"Decimal\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"the_geom_meter\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"name\": {\n",
      "      \"type\": \"Text\",\n",
      "      \"nullable\": true,\n",
      "      \"analyzer\": {\n",
      "        \"type\": \"language\",\n",
      "        \"language\": \"spanish\",\n",
      "        \"useDefaultStopWords\": false,\n",
      "        \"customStopWords\": [],\n",
      "        \"customKeyWords\": []\n",
      "      }\n",
      "    },\n",
      "    \"address\": {\n",
      "      \"type\": \"Text\",\n",
      "      \"nullable\": true,\n",
      "      \"analyzer\": {\n",
      "        \"type\": \"language\",\n",
      "        \"language\": \"spanish\",\n",
      "        \"useDefaultStopWords\": false,\n",
      "        \"customStopWords\": [],\n",
      "        \"customKeyWords\": []\n",
      "      }\n",
      "    },\n",
      "    \"city\": {\n",
      "      \"type\": \"Text\",\n",
      "      \"nullable\": true,\n",
      "      \"analyzer\": \"whitespace\"\n",
      "    },\n",
      "    \"state\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"country\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"zip\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"alcohol\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"smoking_area\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"dress_code\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"accessibility\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"price\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"Rambience\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"franchise\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"area\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    },\n",
      "    \"other_services\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    }\n",
      "  }\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "print(places_schema.to_json_string(indent=2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Infer the Aito Table schema from the user data frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      "  \"type\": \"table\",\n",
      "  \"columns\": {\n",
      "    \"userID\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": false\n",
      "    },\n",
      "    \"latitude\": {\n",
      "      \"type\": \"Decimal\",\n",
      "      \"nullable\": false\n",
      "    },\n",
      "    \"longitude\": {\n",
      "      \"type\": \"Decimal\",\n",
      "      \"nullable\": false\n",
      "    },\n",
      "    \"smoker\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": false\n",
      "    },\n",
      "    \"drink_level\": {\n",
      "      \"type\": \"Text\",\n",
      "      \"nullable\": false,\n",
      "      \"analyzer\": \"whitespace\"\n",
      "    },\n",
      "    \"dress_preference\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": false\n",
      "    },\n",
      "    \"ambience\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": false\n",
      "    },\n",
      "    \"transport\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": false\n",
      "    },\n",
      "    \"marital_status\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": false\n",
      "    },\n",
      "    \"hijos\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": false\n",
      "    },\n",
      "    \"birth_year\": {\n",
      "      \"type\": \"Int\",\n",
      "      \"nullable\": false\n",
      "    },\n",
      "    \"interest\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": false\n",
      "    },\n",
      "    \"personality\": {\n",
      "      \"type\": \"Text\",\n",
      "      \"nullable\": false,\n",
      "      \"analyzer\": {\n",
      "        \"type\": \"delimiter\",\n",
      "        \"delimiter\": \"-\",\n",
      "        \"trimWhitespace\": true\n",
      "      }\n",
      "    },\n",
      "    \"religion\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": false\n",
      "    },\n",
      "    \"activity\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": false\n",
      "    },\n",
      "    \"color\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": false\n",
      "    },\n",
      "    \"weight\": {\n",
      "      \"type\": \"Int\",\n",
      "      \"nullable\": false\n",
      "    },\n",
      "    \"budget\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": false\n",
      "    },\n",
      "    \"height\": {\n",
      "      \"type\": \"Decimal\",\n",
      "      \"nullable\": false\n",
      "    },\n",
      "    \"cuisine\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": false\n",
      "    },\n",
      "    \"payment\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": true\n",
      "    }\n",
      "  }\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "users_schema = AitoTableSchema.infer_from_pandas_data_frame(users_df)\n",
    "print(users_schema.to_json_string(indent=2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Similarly, the users' cuisine and parking should be semicolon delimited"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "for field in ('payment', 'cuisine'):\n",
    "    users_schema[field].data_type = AitoTextType()\n",
    "    users_schema[field].analyzer = AitoDelimiterAnalyzerSchema(delimiter=';')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Infer the Aito Table Schema from the ratings data frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      "  \"type\": \"table\",\n",
      "  \"columns\": {\n",
      "    \"userID\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": false\n",
      "    },\n",
      "    \"placeID\": {\n",
      "      \"type\": \"String\",\n",
      "      \"nullable\": false\n",
      "    },\n",
      "    \"rating\": {\n",
      "      \"type\": \"Int\",\n",
      "      \"nullable\": false\n",
      "    },\n",
      "    \"food_rating\": {\n",
      "      \"type\": \"Int\",\n",
      "      \"nullable\": false\n",
      "    },\n",
      "    \"service_rating\": {\n",
      "      \"type\": \"Int\",\n",
      "      \"nullable\": false\n",
      "    }\n",
      "  }\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "ratings_schema = AitoTableSchema.infer_from_pandas_data_frame(ratings_df)\n",
    "print(ratings_schema.to_json_string(indent=2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Link the ratings to the places and the users table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "ratings_schema['placeID'].link = AitoColumnLinkSchema('places', 'placeID')\n",
    "ratings_schema['userID'].link = AitoColumnLinkSchema('users', 'userID')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### We now have our db schema:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "db_schema = AitoDatabaseSchema(tables={'users': users_schema, 'places': places_schema, 'ratings': ratings_schema})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      "  \"schema\": {\n",
      "    \"users\": {\n",
      "      \"type\": \"table\",\n",
      "      \"columns\": {\n",
      "        \"userID\": {\n",
      "          \"type\": \"String\",\n",
      "          \"nullable\": false\n",
      "        },\n",
      "        \"latitude\": {\n",
      "          \"type\": \"Decimal\",\n",
      "          \"nullable\": false\n",
      "        },\n",
      "        \"longitude\": {\n",
      "          \"type\": \"Decimal\",\n",
      "          \"nullable\": false\n",
      "        },\n",
      "        \"smoker\": {\n",
      "          \"type\": \"String\",\n",
      "          \"nullable\": false\n",
      "        },\n",
      "        \"drink_level\": {\n",
      "          \"type\": \"Text\",\n",
      "          \"nullable\": false,\n",
      "          \"analyzer\": \"whitespace\"\n",
      "        },\n",
      "        \"dress_preference\": {\n",
      "          \"type\": \"String\",\n",
      "          \"nullable\": false\n",
      "        },\n",
      "        \"ambience\": {\n",
      "          \"type\": \"String\",\n",
      "          \"nullable\": false\n",
      "        },\n",
      "        \"transport\": {\n",
      "          \"type\": \"String\",\n",
      "          \"nullable\": false\n",
      "        },\n",
      "        \"marital_status\": {\n",
      "          \"type\": \"String\",\n",
      "          \"nullable\": false\n",
      "        },\n",
      "        \"hijos\": {\n",
      "          \"type\": \"String\",\n",
      "          \"nullable\": false\n",
      "        },\n",
      "        \"birth_year\": {\n",
      "          \"type\": \"Int\",\n",
      "          \"nullable\": false\n",
      "        },\n",
      "        \"interest\": {\n",
      "          \"type\": \"String\",\n",
      "          \"nullable\": false\n",
      "        },\n",
      "        \"personality\": {\n",
      "          \"type\": \"Text\",\n",
      "          \"nullable\": false,\n",
      "          \"analyzer\": {\n",
      "            \"type\": \"delimiter\",\n",
      "            \"delimiter\": \"-\",\n",
      "            \"trimWhitespace\": true\n",
      "          }\n",
      "        },\n",
      "        \"religion\": {\n",
      "          \"type\": \"String\",\n",
      "          \"nullable\": false\n",
      "        },\n",
      "        \"activity\": {\n",
      "          \"type\": \"String\",\n",
      "          \"nullable\": false\n",
      "        },\n",
      "        \"color\": {\n",
      "          \"type\": \"String\",\n",
      "          \"nullable\": false\n",
      "        },\n",
      "        \"weight\": {\n",
      "          \"type\": \"Int\",\n",
      "          \"nullable\": false\n",
      "        },\n",
      "        \"budget\": {\n",
      "          \"type\": \"String\",\n",
      "          \"nullable\": false\n",
      "        },\n",
      "        \"height\": {\n",
      "          \"type\": \"Decimal\",\n",
      "          \"nullable\": false\n",
      "        },\n",
      "        \"cuisine\": {\n",
      "          \"type\": \"Text\",\n",
      "          \"nullable\": false,\n",
      "          \"analyzer\": {\n",
      "            \"type\": \"delimiter\",\n",
      "            \"delimiter\": \";\",\n",
      "            \"trimWhitespace\": true\n",
      "          }\n",
      "        },\n",
      "        \"payment\": {\n",
      "          \"type\": \"Text\",\n",
      "          \"nullable\": true,\n",
      "          \"analyzer\": {\n",
      "            \"type\": \"delimiter\",\n",
      "            \"delimiter\": \";\",\n",
      "            \"trimWhitespace\": true\n",
      "          }\n",
      "        }\n",
      "      }\n",
      "    },\n",
      "    \"places\": {\n",
      "      \"type\": \"table\",\n",
      "      \"columns\": {\n",
      "        \"placeID\": {\n",
      "          \"type\": \"String\",\n",
      "          \"nullable\": false\n",
      "        },\n",
      "        \"payment\": {\n",
      "          \"type\": \"Text\",\n",
      "          \"nullable\": true,\n",
      "          \"analyzer\": {\n",
      "            \"type\": \"delimiter\",\n",
      "            \"delimiter\": \";\",\n",
      "            \"trimWhitespace\": true\n",
      "          }\n",
      "        },\n",
      "        \"cuisine\": {\n",
      "          \"type\": \"Text\",\n",
      "          \"nullable\": true,\n",
      "          \"analyzer\": {\n",
      "            \"type\": \"delimiter\",\n",
      "            \"delimiter\": \";\",\n",
      "            \"trimWhitespace\": true\n",
      "          }\n",
      "        },\n",
      "        \"parking_lot\": {\n",
      "          \"type\": \"Text\",\n",
      "          \"nullable\": true,\n",
      "          \"analyzer\": {\n",
      "            \"type\": \"delimiter\",\n",
      "            \"delimiter\": \";\",\n",
      "            \"trimWhitespace\": true\n",
      "          }\n",
      "        },\n",
      "        \"latitude\": {\n",
      "          \"type\": \"Decimal\",\n",
      "          \"nullable\": true\n",
      "        },\n",
      "        \"longitude\": {\n",
      "          \"type\": \"Decimal\",\n",
      "          \"nullable\": true\n",
      "        },\n",
      "        \"the_geom_meter\": {\n",
      "          \"type\": \"String\",\n",
      "          \"nullable\": true\n",
      "        },\n",
      "        \"name\": {\n",
      "          \"type\": \"Text\",\n",
      "          \"nullable\": true,\n",
      "          \"analyzer\": {\n",
      "            \"type\": \"language\",\n",
      "            \"language\": \"spanish\",\n",
      "            \"useDefaultStopWords\": false,\n",
      "            \"customStopWords\": [],\n",
      "            \"customKeyWords\": []\n",
      "          }\n",
      "        },\n",
      "        \"address\": {\n",
      "          \"type\": \"Text\",\n",
      "          \"nullable\": true,\n",
      "          \"analyzer\": {\n",
      "            \"type\": \"language\",\n",
      "            \"language\": \"spanish\",\n",
      "            \"useDefaultStopWords\": false,\n",
      "            \"customStopWords\": [],\n",
      "            \"customKeyWords\": []\n",
      "          }\n",
      "        },\n",
      "        \"city\": {\n",
      "          \"type\": \"Text\",\n",
      "          \"nullable\": true,\n",
      "          \"analyzer\": \"whitespace\"\n",
      "        },\n",
      "        \"state\": {\n",
      "          \"type\": \"String\",\n",
      "          \"nullable\": true\n",
      "        },\n",
      "        \"country\": {\n",
      "          \"type\": \"String\",\n",
      "          \"nullable\": true\n",
      "        },\n",
      "        \"zip\": {\n",
      "          \"type\": \"String\",\n",
      "          \"nullable\": true\n",
      "        },\n",
      "        \"alcohol\": {\n",
      "          \"type\": \"String\",\n",
      "          \"nullable\": true\n",
      "        },\n",
      "        \"smoking_area\": {\n",
      "          \"type\": \"String\",\n",
      "          \"nullable\": true\n",
      "        },\n",
      "        \"dress_code\": {\n",
      "          \"type\": \"String\",\n",
      "          \"nullable\": true\n",
      "        },\n",
      "        \"accessibility\": {\n",
      "          \"type\": \"String\",\n",
      "          \"nullable\": true\n",
      "        },\n",
      "        \"price\": {\n",
      "          \"type\": \"String\",\n",
      "          \"nullable\": true\n",
      "        },\n",
      "        \"Rambience\": {\n",
      "          \"type\": \"String\",\n",
      "          \"nullable\": true\n",
      "        },\n",
      "        \"franchise\": {\n",
      "          \"type\": \"String\",\n",
      "          \"nullable\": true\n",
      "        },\n",
      "        \"area\": {\n",
      "          \"type\": \"String\",\n",
      "          \"nullable\": true\n",
      "        },\n",
      "        \"other_services\": {\n",
      "          \"type\": \"String\",\n",
      "          \"nullable\": true\n",
      "        }\n",
      "      }\n",
      "    },\n",
      "    \"ratings\": {\n",
      "      \"type\": \"table\",\n",
      "      \"columns\": {\n",
      "        \"userID\": {\n",
      "          \"type\": \"String\",\n",
      "          \"nullable\": false,\n",
      "          \"link\": \"users.userID\"\n",
      "        },\n",
      "        \"placeID\": {\n",
      "          \"type\": \"String\",\n",
      "          \"nullable\": false,\n",
      "          \"link\": \"places.placeID\"\n",
      "        },\n",
      "        \"rating\": {\n",
      "          \"type\": \"Int\",\n",
      "          \"nullable\": false\n",
      "        },\n",
      "        \"food_rating\": {\n",
      "          \"type\": \"Int\",\n",
      "          \"nullable\": false\n",
      "        },\n",
      "        \"service_rating\": {\n",
      "          \"type\": \"Int\",\n",
      "          \"nullable\": false\n",
      "        }\n",
      "      }\n",
      "    }\n",
      "  }\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "print(db_schema.to_json_string(indent=2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Finally, set up the credentials and upload the data into Aito"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fill in your Aito instance credentials\n",
    "AITO_INSTANCE_URL = 'https://team1junction.aito.app'\n",
    "AITO_API_KEY = 'l9uG4dc5ha7BoqBcgT58S2Z7G7uq75ES9w6scxTM'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "client = AitoClient(instance_url=AITO_INSTANCE_URL, api_key=AITO_API_KEY)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "aito_api.create_database(client=client, schema=db_schema)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "aito_api.upload_entries(client=client, table_name='places', entries=places_df.to_dict(orient='records'))\n",
    "aito_api.upload_entries(client=client, table_name='users', entries=users_df.to_dict(orient='records'))\n",
    "aito_api.upload_entries(client=client, table_name='ratings', entries=ratings_df.to_dict(orient='records'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Now, lets try some queries"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Search for places that match an user's criteria\n",
    "\n",
    "Let's assumme that this user like Mexican cuisine and would like to pay by cash"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      "  \"offset\": 0,\n",
      "  \"total\": 147,\n",
      "  \"hits\": [\n",
      "    {\n",
      "      \"cuisine\": \"Mexican\",\n",
      "      \"parking_lot\": \"none\",\n",
      "      \"payment\": \"cash\",\n",
      "      \"placeID\": \"132578\"\n",
      "    },\n",
      "    {\n",
      "      \"cuisine\": \"Mexican\",\n",
      "      \"parking_lot\": \"none\",\n",
      "      \"payment\": \"cash\",\n",
      "      \"placeID\": \"132580\"\n",
      "    },\n",
      "    {\n",
      "      \"Rambience\": \"familiar\",\n",
      "      \"accessibility\": \"completely\",\n",
      "      \"alcohol\": \"No_Alcohol_Served\",\n",
      "      \"area\": \"closed\",\n",
      "      \"cuisine\": \"Mexican\",\n",
      "      \"dress_code\": \"informal\",\n",
      "      \"franchise\": \"t\",\n",
      "      \"latitude\": 23.752364800000002,\n",
      "      \"longitude\": -99.16528790000001,\n",
      "      \"name\": \"Gorditas Dona Tota\",\n",
      "      \"other_services\": \"none\",\n",
      "      \"parking_lot\": \"yes\",\n",
      "      \"payment\": \"cash\",\n",
      "      \"placeID\": \"132584\",\n",
      "      \"price\": \"medium\",\n",
      "      \"smoking_area\": \"not permitted\",\n",
      "      \"the_geom_meter\": \"0101000020957F000048C65BA7EF8157C177F2344D664E4941\"\n",
      "    },\n",
      "    {\n",
      "      \"cuisine\": \"Mexican\",\n",
      "      \"parking_lot\": \"public\",\n",
      "      \"payment\": \"cash\",\n",
      "      \"placeID\": \"132588\"\n",
      "    },\n",
      "    {\n",
      "      \"cuisine\": \"Mexican\",\n",
      "      \"parking_lot\": \"public\",\n",
      "      \"payment\": \"cash\",\n",
      "      \"placeID\": \"132593\"\n",
      "    },\n",
      "    {\n",
      "      \"Rambience\": \"familiar\",\n",
      "      \"accessibility\": \"completely\",\n",
      "      \"alcohol\": \"No_Alcohol_Served\",\n",
      "      \"area\": \"open\",\n",
      "      \"cuisine\": \"Mexican\",\n",
      "      \"dress_code\": \"informal\",\n",
      "      \"franchise\": \"f\",\n",
      "      \"latitude\": 23.7521677,\n",
      "      \"longitude\": -99.16570899999999,\n",
      "      \"name\": \"tacos de barbacoa enfrente del Tec\",\n",
      "      \"other_services\": \"none\",\n",
      "      \"parking_lot\": \"public\",\n",
      "      \"payment\": \"cash\",\n",
      "      \"placeID\": \"132594\",\n",
      "      \"price\": \"low\",\n",
      "      \"smoking_area\": \"not permitted\",\n",
      "      \"the_geom_meter\": \"0101000020957F00003AE4C6DBF48157C1CE38ECC1864E4941\"\n",
      "    },\n",
      "    {\n",
      "      \"cuisine\": \"Mexican\",\n",
      "      \"parking_lot\": \"none\",\n",
      "      \"payment\": \"cash\",\n",
      "      \"placeID\": \"132595\"\n",
      "    },\n",
      "    {\n",
      "      \"cuisine\": \"Mexican\",\n",
      "      \"parking_lot\": \"none\",\n",
      "      \"payment\": \"cash\",\n",
      "      \"placeID\": \"132596\"\n",
      "    },\n",
      "    {\n",
      "      \"cuisine\": \"Mexican\",\n",
      "      \"parking_lot\": \"public\",\n",
      "      \"payment\": \"cash\",\n",
      "      \"placeID\": \"132599\"\n",
      "    },\n",
      "    {\n",
      "      \"cuisine\": \"Mexican\",\n",
      "      \"parking_lot\": \"public\",\n",
      "      \"payment\": \"cash\",\n",
      "      \"placeID\": \"132602\"\n",
      "    }\n",
      "  ]\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "query = {\n",
    "    \"from\": \"places\",\n",
    "    \"where\": {\n",
    "        \"cuisine\": \"Mexican\",\n",
    "        \"payment\": \"cash\"\n",
    "    }\n",
    "}\n",
    "res = aito_api.generic_query(client=client, query=query)\n",
    "print(res.to_json_string(indent=2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Pretty good but we want to return better results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## This time, we would like to suggest a restaurant to an user based on the previous ratings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "rec_query = {\n",
    "    \"from\": \"ratings\",\n",
    "    \"where\": {\n",
    "        \"userID\": {\n",
    "            \"$and\": [\n",
    "                {\"userID\": \"U1022\"},\n",
    "                {\"userID\": \"U1026\"}\n",
    "            ]\n",
    "        },\n",
    "        \"placeID\": {\n",
    "            \"price\": \"high\"\n",
    "        }\n",
    "    },\n",
    "    \"recommend\": \"placeID\",\n",
    "    \"goal\": {\"rating\": 2},\n",
    "    \"limit\": 5\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'offset': 0,\n",
       " 'total': 25,\n",
       " 'hits': [{'$p': 0.9244336662379592,\n",
       "   'Rambience': 'familiar',\n",
       "   'accessibility': 'no_accessibility',\n",
       "   'address': 'Ricardo Linares 107',\n",
       "   'alcohol': 'Wine-Beer',\n",
       "   'area': 'closed',\n",
       "   'city': 'Cuernavaca',\n",
       "   'country': 'Mexico',\n",
       "   'cuisine': 'International',\n",
       "   'dress_code': 'formal',\n",
       "   'franchise': 'f',\n",
       "   'latitude': 18.928798,\n",
       "   'longitude': -99.239513,\n",
       "   'name': 'Restaurant Las Mananitas',\n",
       "   'other_services': 'none',\n",
       "   'parking_lot': 'yes',\n",
       "   'placeID': '134986',\n",
       "   'price': 'high',\n",
       "   'smoking_area': 'none',\n",
       "   'state': 'Morelos',\n",
       "   'the_geom_meter': '0101000020957F00002A0D05E2D96D5AC1AB058CB1EC564A41'},\n",
       "  {'$p': 0.8847367370604847,\n",
       "   'Rambience': 'familiar',\n",
       "   'accessibility': 'no_accessibility',\n",
       "   'address': 'Venustiano Carranza 560 Centro',\n",
       "   'alcohol': 'Wine-Beer',\n",
       "   'area': 'closed',\n",
       "   'city': 'San Luis Potosi',\n",
       "   'country': 'Mexico',\n",
       "   'dress_code': 'casual',\n",
       "   'franchise': 'f',\n",
       "   'latitude': 22.151189000000002,\n",
       "   'longitude': -100.98179,\n",
       "   'name': 'Restaurante la Gran Via',\n",
       "   'other_services': 'none',\n",
       "   'parking_lot': 'yes',\n",
       "   'payment': 'cash;VISA;MasterCard-Eurocard;American_Express',\n",
       "   'placeID': '135045',\n",
       "   'price': 'high',\n",
       "   'smoking_area': 'none',\n",
       "   'state': 'SLP',\n",
       "   'the_geom_meter': '0101000020957F00000B6735CA004858C108FD525CB2A44B41',\n",
       "   'zip': '78000'},\n",
       "  {'$p': 0.8565059788045788,\n",
       "   'Rambience': 'familiar',\n",
       "   'accessibility': 'no_accessibility',\n",
       "   'address': 'Venustiano Carranza 2175 Jardin',\n",
       "   'alcohol': 'No_Alcohol_Served',\n",
       "   'area': 'closed',\n",
       "   'city': 'San Luis Potosi',\n",
       "   'country': 'Mexico',\n",
       "   'cuisine': 'Mexican',\n",
       "   'dress_code': 'informal',\n",
       "   'franchise': 'f',\n",
       "   'latitude': 22.148854,\n",
       "   'longitude': -101.008472,\n",
       "   'name': 'la Cochinita Pibil Restaurante Yucateco',\n",
       "   'other_services': 'none',\n",
       "   'parking_lot': 'yes',\n",
       "   'payment': 'cash;VISA;MasterCard-Eurocard;American_Express',\n",
       "   'placeID': '135055',\n",
       "   'price': 'high',\n",
       "   'smoking_area': 'section',\n",
       "   'state': 'SLP',\n",
       "   'the_geom_meter': '0101000020957F00006610DA0F9F4758C12ED00BA771AC4B41',\n",
       "   'zip': '78270'},\n",
       "  {'$p': 0.7992038844679102,\n",
       "   'Rambience': 'familiar',\n",
       "   'accessibility': 'no_accessibility',\n",
       "   'address': 'Ignacio Aldama 300 Centro',\n",
       "   'alcohol': 'Full_Bar',\n",
       "   'area': 'closed',\n",
       "   'city': 'San Luis Potosi',\n",
       "   'country': 'Mexico',\n",
       "   'cuisine': 'Bar;Bar_Pub_Brewery',\n",
       "   'dress_code': 'informal',\n",
       "   'franchise': 'f',\n",
       "   'latitude': 22.150980999999998,\n",
       "   'longitude': -100.977412,\n",
       "   'name': 'La Cantina Restaurante',\n",
       "   'other_services': 'none',\n",
       "   'parking_lot': 'none',\n",
       "   'payment': 'cash;VISA;MasterCard-Eurocard',\n",
       "   'placeID': '135052',\n",
       "   'price': 'high',\n",
       "   'smoking_area': 'none',\n",
       "   'state': 'SLP',\n",
       "   'the_geom_meter': '0101000020957F0000B72147F1274858C189A406ED75A34B41',\n",
       "   'zip': '78000'},\n",
       "  {'$p': 0.6993052173166198,\n",
       "   'Rambience': 'familiar',\n",
       "   'accessibility': 'no_accessibility',\n",
       "   'address': 'Capitan Caldera No. 420 Tequisqueapan',\n",
       "   'alcohol': 'Full_Bar',\n",
       "   'area': 'closed',\n",
       "   'city': 'San Luis Potosi',\n",
       "   'country': 'Mexico',\n",
       "   'cuisine': 'Bar;Bar_Pub_Brewery',\n",
       "   'dress_code': 'informal',\n",
       "   'franchise': 'f',\n",
       "   'latitude': 22.148665,\n",
       "   'longitude': -101.001273,\n",
       "   'name': 'la Cantina',\n",
       "   'other_services': 'none',\n",
       "   'parking_lot': 'none',\n",
       "   'placeID': '135026',\n",
       "   'price': 'high',\n",
       "   'smoking_area': 'none',\n",
       "   'state': 'SLP',\n",
       "   'the_geom_meter': '0101000020957F0000C75F8790D94758C1FF8BCA0567AA4B41',\n",
       "   'zip': '78250'}]}"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res = aito_api.recommend(client=client, query=rec_query)\n",
    "res.json"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## This is just a scratch on the surface. Now it's your turn to explore Aito's capabilities and make the best restaurant recommendation app"
   ]
  }
 ],
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