WebScraping_Clenaing_SQL_Import.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# New Opening PopUpStore"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check Connection to fotocasa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import pymysql\n",
    "from sqlalchemy import create_engine\n",
    "from getpass import getpass\n",
    "from sqlalchemy import inspect\n",
    "from bs4 import BeautifulSoup\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import time\n",
    "import os\n",
    "import requests as r\n",
    "import re\n",
    "import geopy "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "url = 'https://api.fotocasa.es/PropertySearch/Search?combinedLocationIds=724,14,28,173,0,28079,0,0,0&culture=es-ES&featureIds=130&hrefLangCultures=ca-ES%3Bes-ES%3Bde-DE%3Ben-GB&isMap=false&isNewConstruction=false&isNewConstructionPromotions=false&latitude=40.4096&longitude=-3.68624&pageNumber=1&platformId=1&sortOrderDesc=true&sortType=bumpdate&transactionTypeId=3&propertyTypeId=2'\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "r.get(url)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Flats for Rent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "headers = \"\"\"accept: application/json, text/plain, */*\n",
    "accept-encoding: gzip, deflate, br\n",
    "accept-language: es-ES,es;q=0.9,fr;q=0.8,en;q=0.7,pl;q=0.6\n",
    "cache-control: no-cache\n",
    "origin: https://www.fotocasa.es\n",
    "pragma: no-cache\n",
    "referer: https://www.fotocasa.es/\n",
    "sec-ch-ua: \"Chromium\";v=\"88\", \"Google Chrome\";v=\"88\", \";Not A Brand\";v=\"99\"\n",
    "sec-ch-ua-mobile: ?0\n",
    "sec-fetch-dest: empty\n",
    "sec-fetch-mode: cors\n",
    "sec-fetch-site: same-site\n",
    "user-agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/88.0.4324.182 Safari/537.36\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "headers=dict(i.split(': ') for i in headers.split('\\n'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "resp = r.get(url, headers=headers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "resp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "resp.json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = resp.json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_test = pd.json_normalize(data['realEstates'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "url = 'https://api.fotocasa.es/PropertySearch/Search?combinedLocationIds=724,14,28,173,0,28079,0,0,0&culture=es-ES&featureIds=130&hrefLangCultures=ca-ES%3Bes-ES%3Bde-DE%3Ben-GB&isMap=false&isNewConstruction=false&isNewConstructionPromotions=false&latitude=40.4096&longitude=-3.68624&pageNumber=1&platformId=1&sortOrderDesc=true&sortType=bumpdate&transactionTypeId=3&propertyTypeId=2'\n",
    "resp = r.get(url, headers=headers)\n",
    "data = resp.json()\n",
    "df = pd.json_normalize(data['realEstates'])\n",
    "number_of_iteration=0\n",
    "time.sleep(2)\n",
    "print('Page number: 1 scanned')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_df():\n",
    "    url = 'https://api.fotocasa.es/PropertySearch/Search?combinedLocationIds=724,14,28,173,0,28079,0,0,0&culture=es-ES&featureIds=130&hrefLangCultures=ca-ES%3Bes-ES%3Bde-DE%3Ben-GB&isMap=false&isNewConstruction=false&isNewConstructionPromotions=false&latitude=40.4096&longitude=-3.68624&pageNumber=1&platformId=1&sortOrderDesc=true&sortType=bumpdate&transactionTypeId=3&propertyTypeId=2'\n",
    "    resp = r.get(url, headers=headers)\n",
    "    data = resp.json()\n",
    "    df = pd.json_normalize(data['realEstates'])\n",
    "    number_of_iteration=0\n",
    "    time.sleep(2)\n",
    "    for i in range(2,80):\n",
    "        number_of_iteration+=1\n",
    "        url = f'https://api.fotocasa.es/PropertySearch/Search?combinedLocationIds=724,14,28,173,0,28079,0,0,0&culture=es-ES&featureIds=130&hrefLangCultures=ca-ES%3Bes-ES%3Bde-DE%3Ben-GB&isMap=false&isNewConstruction=false&isNewConstructionPromotions=false&latitude=40.4096&longitude=-3.68624&pageNumber={i}&platformId=1&sortOrderDesc=true&sortType=bumpdate&transactionTypeId=3&propertyTypeId=2'\n",
    "        resp = r.get(url, headers=headers)\n",
    "        data = resp.json()\n",
    "        df = df.append(pd.json_normalize(data['realEstates']))\n",
    "        if number_of_iteration%10 and number_of_iteration:\n",
    "            time.sleep(5)\n",
    "        time.sleep(2)\n",
    "        print(f'Page number: {i} scanned')\n",
    "    df.to_json('df.json', orient='records')\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#get_df()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "os.getcwd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.read_json('Madrid_rent.json')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Flats for Sale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "url = 'https://api.fotocasa.es/PropertySearch/Search?combinedLocationIds=724,14,28,173,0,28079,0,0,0&culture=es-ES&hrefLangCultures=ca-ES%3Bes-ES%3Bde-DE%3Ben-GB&isMap=false&isNewConstruction=false&isNewConstructionPromotions=false&latitude=40.4096&longitude=-3.68624&pageNumber=1&platformId=1&sortOrderDesc=true&sortType=bumpdate&transactionTypeId=1&propertyTypeId=2'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "r.get(url)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "headers = \"\"\"accept: application/json, text/plain, */*\n",
    "accept-encoding: gzip, deflate, br\n",
    "accept-language: es-ES,es;q=0.9,fr;q=0.8,en;q=0.7,pl;q=0.6\n",
    "cache-control: no-cache\n",
    "origin: https://www.fotocasa.es\n",
    "pragma: no-cache\n",
    "referer: https://www.fotocasa.es/\n",
    "sec-ch-ua: \"Chromium\";v=\"88\", \"Google Chrome\";v=\"88\", \";Not A Brand\";v=\"99\"\n",
    "sec-ch-ua-mobile: ?0\n",
    "sec-fetch-dest: empty\n",
    "sec-fetch-mode: cors\n",
    "sec-fetch-site: same-site\n",
    "user-agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/88.0.4324.182 Safari/537.36\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "headers=dict(i.split(': ') for i in headers.split('\\n'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "resp = r.get(url, headers=headers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "resp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "resp.json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = resp.json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_test = pd.json_normalize(data['realEstates'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "len(df_test.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_df():\n",
    "    url = 'https://api.fotocasa.es/PropertySearch/Search?combinedLocationIds=724,14,28,173,0,28079,0,0,0&culture=es-ES&hrefLangCultures=ca-ES%3Bes-ES%3Bde-DE%3Ben-GB&isMap=false&isNewConstruction=false&isNewConstructionPromotions=false&latitude=40.4096&longitude=-3.68624&pageNumber=1&platformId=1&sortOrderDesc=true&sortType=bumpdate&transactionTypeId=1&propertyTypeId=2'\n",
    "    resp = r.get(url, headers=headers)\n",
    "    data = resp.json()\n",
    "    df = pd.json_normalize(data['realEstates'])\n",
    "    number_of_iteration=0\n",
    "    time.sleep(2)\n",
    "    for i in range(2,556):\n",
    "        number_of_iteration+=1\n",
    "        url = f'https://api.fotocasa.es/PropertySearch/Search?combinedLocationIds=724,14,28,173,0,28079,0,0,0&culture=es-ES&hrefLangCultures=ca-ES%3Bes-ES%3Bde-DE%3Ben-GB&isMap=false&isNewConstruction=false&isNewConstructionPromotions=false&latitude=40.4096&longitude=-3.68624&pageNumber={i}&platformId=1&sortOrderDesc=true&sortType=bumpdate&transactionTypeId=1&propertyTypeId=2'\n",
    "        resp = r.get(url, headers=headers)\n",
    "        data = resp.json()\n",
    "        df = df.append(pd.json_normalize(data['realEstates']))\n",
    "        if number_of_iteration%10 and number_of_iteration:\n",
    "            time.sleep(5)\n",
    "        time.sleep(2)\n",
    "        print(f'Page number: {i} scanned')\n",
    "    df.to_json('Madrid_sale.json', orient='records')\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#get_df()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Start Cleanning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import pymysql\n",
    "from sqlalchemy import create_engine\n",
    "from getpass import getpass\n",
    "from sqlalchemy import inspect\n",
    "from bs4 import BeautifulSoup\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import time\n",
    "import os\n",
    "import requests as r\n",
    "import re\n",
    "import geopy "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['.git',\n",
       " '.gitignore',\n",
       " '.ipynb_checkpoints',\n",
       " 'analysis_and_conclussions.ipynb',\n",
       " 'Madrid Rent.ipynb',\n",
       " 'Madrid_salev1.json',\n",
       " 'mvps',\n",
       " 'New PopUpStore.pptx',\n",
       " 'Outuput',\n",
       " 'PopUpStoreV4.ipynb',\n",
       " 'README.md',\n",
       " 'Rent Apartments sql.ipynb',\n",
       " 'rent_madridv1.json',\n",
       " 'Trello_Miro_Pics',\n",
       " 'Untitled.ipynb']"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.listdir()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "os.chdir('D:\\\\Repositories\\\\NewPoPUpStore\\\\Outuput')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "sale = pd.read_json('Madrid_sale.orginal.json', orient='records')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
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       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>promotionId</th>\n",
       "      <th>typeId</th>\n",
       "      <th>subtypeId</th>\n",
       "      <th>isNew</th>\n",
       "      <th>isPremium</th>\n",
       "      <th>multimedias</th>\n",
       "      <th>features</th>\n",
       "      <th>otherFeatures</th>\n",
       "      <th>transactions</th>\n",
       "      <th>...</th>\n",
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       "      <th>address.coordinates.accuracy</th>\n",
       "      <th>address.coordinates.latitude</th>\n",
       "      <th>address.coordinates.longitude</th>\n",
       "      <th>address.zipCode</th>\n",
       "      <th>address.customZone</th>\n",
       "      <th>advertiser.logo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <td>-3.675195</td>\n",
       "      <td>28002</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <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>16651</th>\n",
       "      <td>158823456</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/85276/27...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [1], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'transactionTypeId': 1, 'value': [115000], '...</td>\n",
       "      <td>...</td>\n",
       "      <td>28079</td>\n",
       "      <td>0</td>\n",
       "      <td>676</td>\n",
       "      <td>79</td>\n",
       "      <td>0</td>\n",
       "      <td>40.42985</td>\n",
       "      <td>-3.613449</td>\n",
       "      <td>28037</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16652</th>\n",
       "      <td>158823310</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/85276/27...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [2], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'transactionTypeId': 1, 'value': [179000], '...</td>\n",
       "      <td>...</td>\n",
       "      <td>28079</td>\n",
       "      <td>0</td>\n",
       "      <td>676</td>\n",
       "      <td>72</td>\n",
       "      <td>0</td>\n",
       "      <td>40.41291</td>\n",
       "      <td>-3.585160</td>\n",
       "      <td>28032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16653</th>\n",
       "      <td>158823307</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/98925/27...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [1], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'transactionTypeId': 1, 'value': [137000], '...</td>\n",
       "      <td>...</td>\n",
       "      <td>28079</td>\n",
       "      <td>0</td>\n",
       "      <td>668</td>\n",
       "      <td>27</td>\n",
       "      <td>0</td>\n",
       "      <td>40.45087</td>\n",
       "      <td>-3.582744</td>\n",
       "      <td>28042</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16654</th>\n",
       "      <td>158823262</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/85276/27...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [1], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'transactionTypeId': 1, 'value': [115000], '...</td>\n",
       "      <td>...</td>\n",
       "      <td>28079</td>\n",
       "      <td>0</td>\n",
       "      <td>676</td>\n",
       "      <td>76</td>\n",
       "      <td>0</td>\n",
       "      <td>40.42963</td>\n",
       "      <td>-3.625728</td>\n",
       "      <td>28037</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16655</th>\n",
       "      <td>158823219</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/88669/27...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [1], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'transactionTypeId': 1, 'value': [380000], '...</td>\n",
       "      <td>...</td>\n",
       "      <td>28079</td>\n",
       "      <td>0</td>\n",
       "      <td>667</td>\n",
       "      <td>18</td>\n",
       "      <td>1</td>\n",
       "      <td>40.42808</td>\n",
       "      <td>-3.675250</td>\n",
       "      <td>28006</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16656 rows × 55 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              id  promotionId  typeId  subtypeId  isNew  isPremium  \\\n",
       "0      150476642            0       2          3  False       True   \n",
       "1      157313689            0       2          1  False       True   \n",
       "2      153519540            0       2         55  False       True   \n",
       "3      154298390            0       2         55  False       True   \n",
       "4      158184418            0       2          1  False       True   \n",
       "...          ...          ...     ...        ...    ...        ...   \n",
       "16651  158823456            0       2          1  False      False   \n",
       "16652  158823310            0       2          8  False      False   \n",
       "16653  158823307            0       2          1  False      False   \n",
       "16654  158823262            0       2          1  False      False   \n",
       "16655  158823219            0       2          1  False      False   \n",
       "\n",
       "                                             multimedias  \\\n",
       "0      [{'url': 'https://d.inmofactory.com/1/100202/1...   \n",
       "1      [{'url': 'https://my.matterport.com/show/?m=fi...   \n",
       "2      [{'url': 'https://d.inmofactory.com/1/100207/1...   \n",
       "3      [{'url': 'https://images.inmofactory.com/inmof...   \n",
       "4      [{'url': 'https://d.inmofactory.com/1/89548/26...   \n",
       "...                                                  ...   \n",
       "16651  [{'url': 'https://d.inmofactory.com/1/85276/27...   \n",
       "16652  [{'url': 'https://d.inmofactory.com/1/85276/27...   \n",
       "16653  [{'url': 'https://d.inmofactory.com/1/98925/27...   \n",
       "16654  [{'url': 'https://d.inmofactory.com/1/85276/27...   \n",
       "16655  [{'url': 'https://d.inmofactory.com/1/88669/27...   \n",
       "\n",
       "                                                features  otherFeatures  \\\n",
       "0      [{'key': 'bathrooms', 'value': [5], 'minValue'...            NaN   \n",
       "1      [{'key': 'bathrooms', 'value': [1], 'minValue'...            NaN   \n",
       "2      [{'key': 'bathrooms', 'value': [6], 'minValue'...            NaN   \n",
       "3      [{'key': 'bathrooms', 'value': [6], 'minValue'...            NaN   \n",
       "4      [{'key': 'bathrooms', 'value': [2], 'minValue'...            NaN   \n",
       "...                                                  ...            ...   \n",
       "16651  [{'key': 'bathrooms', 'value': [1], 'minValue'...            NaN   \n",
       "16652  [{'key': 'bathrooms', 'value': [2], 'minValue'...            NaN   \n",
       "16653  [{'key': 'bathrooms', 'value': [1], 'minValue'...            NaN   \n",
       "16654  [{'key': 'bathrooms', 'value': [1], 'minValue'...            NaN   \n",
       "16655  [{'key': 'bathrooms', 'value': [1], 'minValue'...            NaN   \n",
       "\n",
       "                                            transactions  ...  \\\n",
       "0      [{'transactionTypeId': 1, 'value': [2200000], ...  ...   \n",
       "1      [{'transactionTypeId': 1, 'value': [405000], '...  ...   \n",
       "2      [{'transactionTypeId': 1, 'value': [1930000], ...  ...   \n",
       "3      [{'transactionTypeId': 1, 'value': [1930000], ...  ...   \n",
       "4      [{'transactionTypeId': 1, 'value': [485000], '...  ...   \n",
       "...                                                  ...  ...   \n",
       "16651  [{'transactionTypeId': 1, 'value': [115000], '...  ...   \n",
       "16652  [{'transactionTypeId': 1, 'value': [179000], '...  ...   \n",
       "16653  [{'transactionTypeId': 1, 'value': [137000], '...  ...   \n",
       "16654  [{'transactionTypeId': 1, 'value': [115000], '...  ...   \n",
       "16655  [{'transactionTypeId': 1, 'value': [380000], '...  ...   \n",
       "\n",
       "      address.location.level5Id address.location.level6Id  \\\n",
       "0                         28079                         0   \n",
       "1                         28079                         0   \n",
       "2                         28079                         0   \n",
       "3                         28079                         0   \n",
       "4                         28079                         0   \n",
       "...                         ...                       ...   \n",
       "16651                     28079                         0   \n",
       "16652                     28079                         0   \n",
       "16653                     28079                         0   \n",
       "16654                     28079                         0   \n",
       "16655                     28079                         0   \n",
       "\n",
       "      address.location.level7Id  address.location.level8Id  \\\n",
       "0                           678                         90   \n",
       "1                           176                        116   \n",
       "2                           187                         16   \n",
       "3                           187                         16   \n",
       "4                           176                        113   \n",
       "...                         ...                        ...   \n",
       "16651                       676                         79   \n",
       "16652                       676                         72   \n",
       "16653                       668                         27   \n",
       "16654                       676                         76   \n",
       "16655                       667                         18   \n",
       "\n",
       "       address.coordinates.accuracy  address.coordinates.latitude  \\\n",
       "0                                 0                      40.45485   \n",
       "1                                 0                      40.44738   \n",
       "2                                 0                      40.50451   \n",
       "3                                 0                      40.50597   \n",
       "4                                 0                      40.44738   \n",
       "...                             ...                           ...   \n",
       "16651                             0                      40.42985   \n",
       "16652                             0                      40.41291   \n",
       "16653                             0                      40.45087   \n",
       "16654                             0                      40.42963   \n",
       "16655                             1                      40.42808   \n",
       "\n",
       "       address.coordinates.longitude  address.zipCode  address.customZone  \\\n",
       "0                          -3.630255            28043                 NaN   \n",
       "1                          -3.668194            28002                 NaN   \n",
       "2                          -3.692709            28034                 NaN   \n",
       "3                          -3.692078            28034                 NaN   \n",
       "4                          -3.675195            28002                 NaN   \n",
       "...                              ...              ...                 ...   \n",
       "16651                      -3.613449            28037                 NaN   \n",
       "16652                      -3.585160            28032                 NaN   \n",
       "16653                      -3.582744            28042                 NaN   \n",
       "16654                      -3.625728            28037                 NaN   \n",
       "16655                      -3.675250            28006                 NaN   \n",
       "\n",
       "       advertiser.logo  \n",
       "0                  NaN  \n",
       "1                  NaN  \n",
       "2                  NaN  \n",
       "3                  NaN  \n",
       "4                  NaN  \n",
       "...                ...  \n",
       "16651              NaN  \n",
       "16652              NaN  \n",
       "16653              NaN  \n",
       "16654              NaN  \n",
       "16655              NaN  \n",
       "\n",
       "[16656 rows x 55 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "rent = pd.read_json('Madrid_rent.json', orient='records')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale = pd.DataFrame(sale)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "rent = pd.DataFrame(rent)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Duplicated - Sale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale = sale.set_index(sale['id'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "16656"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(sale)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale = sale.drop_duplicates(subset=['id'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9280"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(sale)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Duplicated - Rent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "rent = rent.set_index(rent['id'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2356"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(rent)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "rent = rent.drop_duplicates(subset=['id'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2277"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(rent)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cleaning Features column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                                                 int64\n",
       "promotionId                                        int64\n",
       "typeId                                             int64\n",
       "subtypeId                                          int64\n",
       "isNew                                               bool\n",
       "isPremium                                           bool\n",
       "multimedias                                       object\n",
       "features                                          object\n",
       "otherFeatures                                    float64\n",
       "transactions                                      object\n",
       "products                                          object\n",
       "date                                 datetime64[ns, UTC]\n",
       "description                                       object\n",
       "isTop                                               bool\n",
       "isPhotoReport                                       bool\n",
       "isMsAdvance                                         bool\n",
       "promotionTypeId                                    int64\n",
       "promotionUrl                                     float64\n",
       "isExternalContact                                   bool\n",
       "isVirtualTour                                       bool\n",
       "advertiser.logo.multimedia.url                    object\n",
       "advertiser.logo.multimedia.typeId                float64\n",
       "advertiser.logo.url.es                            object\n",
       "advertiser.phone                                  object\n",
       "advertiser.typeId                                  int64\n",
       "advertiser.clientId                                int64\n",
       "advertiser.urlAlias                               object\n",
       "advertiser.clientAlias                            object\n",
       "detail.es                                         object\n",
       "address.ubication                                 object\n",
       "address.location.country                          object\n",
       "address.location.level1                           object\n",
       "address.location.level2                           object\n",
       "address.location.level3                           object\n",
       "address.location.level4                           object\n",
       "address.location.level5                           object\n",
       "address.location.level6                           object\n",
       "address.location.level7                           object\n",
       "address.location.level8                           object\n",
       "address.location.upperLevel                       object\n",
       "address.location.countryId                         int64\n",
       "address.location.level1Id                          int64\n",
       "address.location.level2Id                          int64\n",
       "address.location.level3Id                          int64\n",
       "address.location.level4Id                          int64\n",
       "address.location.level5Id                          int64\n",
       "address.location.level6Id                          int64\n",
       "address.location.level7Id                          int64\n",
       "address.location.level8Id                          int64\n",
       "address.coordinates.accuracy                       int64\n",
       "address.coordinates.latitude                     float64\n",
       "address.coordinates.longitude                    float64\n",
       "address.zipCode                                   object\n",
       "address.customZone                               float64\n",
       "advertiser.logo                                  float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sale.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Int64Index([150476642, 157313689, 153519540, 154298390, 158184418, 151395833,\n",
       "            158640294, 158832687, 158859368, 158870851,\n",
       "            ...\n",
       "            157361240, 157924150, 158823492, 158823469, 155208692, 158823456,\n",
       "            158823310, 158823307, 158823262, 158823219],\n",
       "           dtype='int64', name='id', length=9280)"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sale.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(9280, 55)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sale.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "510400"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sale.size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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>id</th>\n",
       "      <th>promotionId</th>\n",
       "      <th>typeId</th>\n",
       "      <th>subtypeId</th>\n",
       "      <th>isNew</th>\n",
       "      <th>isPremium</th>\n",
       "      <th>multimedias</th>\n",
       "      <th>features</th>\n",
       "      <th>otherFeatures</th>\n",
       "      <th>transactions</th>\n",
       "      <th>...</th>\n",
       "      <th>address.location.level5Id</th>\n",
       "      <th>address.location.level6Id</th>\n",
       "      <th>address.location.level7Id</th>\n",
       "      <th>address.location.level8Id</th>\n",
       "      <th>address.coordinates.accuracy</th>\n",
       "      <th>address.coordinates.latitude</th>\n",
       "      <th>address.coordinates.longitude</th>\n",
       "      <th>address.zipCode</th>\n",
       "      <th>address.customZone</th>\n",
       "      <th>advertiser.logo</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>150476642</th>\n",
       "      <td>150476642</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/100202/1...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [5], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'transactionTypeId': 1, 'value': [2200000], ...</td>\n",
       "      <td>...</td>\n",
       "      <td>28079</td>\n",
       "      <td>0</td>\n",
       "      <td>678</td>\n",
       "      <td>90</td>\n",
       "      <td>0</td>\n",
       "      <td>40.45485</td>\n",
       "      <td>-3.630255</td>\n",
       "      <td>28043</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157313689</th>\n",
       "      <td>157313689</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>[{'url': 'https://my.matterport.com/show/?m=fi...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [1], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'transactionTypeId': 1, 'value': [405000], '...</td>\n",
       "      <td>...</td>\n",
       "      <td>28079</td>\n",
       "      <td>0</td>\n",
       "      <td>176</td>\n",
       "      <td>116</td>\n",
       "      <td>0</td>\n",
       "      <td>40.44738</td>\n",
       "      <td>-3.668194</td>\n",
       "      <td>28002</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153519540</th>\n",
       "      <td>153519540</td>\n",
       "      <td>0</td>\n",
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       "      <td>55</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/100207/1...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [6], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'transactionTypeId': 1, 'value': [1930000], ...</td>\n",
       "      <td>...</td>\n",
       "      <td>28079</td>\n",
       "      <td>0</td>\n",
       "      <td>187</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>40.50451</td>\n",
       "      <td>-3.692709</td>\n",
       "      <td>28034</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154298390</th>\n",
       "      <td>154298390</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>55</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>[{'url': 'https://images.inmofactory.com/inmof...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [6], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'transactionTypeId': 1, 'value': [1930000], ...</td>\n",
       "      <td>...</td>\n",
       "      <td>28079</td>\n",
       "      <td>0</td>\n",
       "      <td>187</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>40.50597</td>\n",
       "      <td>-3.692078</td>\n",
       "      <td>28034</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158184418</th>\n",
       "      <td>158184418</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/89548/26...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [2], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'transactionTypeId': 1, 'value': [485000], '...</td>\n",
       "      <td>...</td>\n",
       "      <td>28079</td>\n",
       "      <td>0</td>\n",
       "      <td>176</td>\n",
       "      <td>113</td>\n",
       "      <td>0</td>\n",
       "      <td>40.44738</td>\n",
       "      <td>-3.675195</td>\n",
       "      <td>28002</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 55 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  id  promotionId  typeId  subtypeId  isNew  isPremium  \\\n",
       "id                                                                       \n",
       "150476642  150476642            0       2          3  False       True   \n",
       "157313689  157313689            0       2          1  False       True   \n",
       "153519540  153519540            0       2         55  False       True   \n",
       "154298390  154298390            0       2         55  False       True   \n",
       "158184418  158184418            0       2          1  False       True   \n",
       "\n",
       "                                                 multimedias  \\\n",
       "id                                                             \n",
       "150476642  [{'url': 'https://d.inmofactory.com/1/100202/1...   \n",
       "157313689  [{'url': 'https://my.matterport.com/show/?m=fi...   \n",
       "153519540  [{'url': 'https://d.inmofactory.com/1/100207/1...   \n",
       "154298390  [{'url': 'https://images.inmofactory.com/inmof...   \n",
       "158184418  [{'url': 'https://d.inmofactory.com/1/89548/26...   \n",
       "\n",
       "                                                    features  otherFeatures  \\\n",
       "id                                                                            \n",
       "150476642  [{'key': 'bathrooms', 'value': [5], 'minValue'...            NaN   \n",
       "157313689  [{'key': 'bathrooms', 'value': [1], 'minValue'...            NaN   \n",
       "153519540  [{'key': 'bathrooms', 'value': [6], 'minValue'...            NaN   \n",
       "154298390  [{'key': 'bathrooms', 'value': [6], 'minValue'...            NaN   \n",
       "158184418  [{'key': 'bathrooms', 'value': [2], 'minValue'...            NaN   \n",
       "\n",
       "                                                transactions  ...  \\\n",
       "id                                                            ...   \n",
       "150476642  [{'transactionTypeId': 1, 'value': [2200000], ...  ...   \n",
       "157313689  [{'transactionTypeId': 1, 'value': [405000], '...  ...   \n",
       "153519540  [{'transactionTypeId': 1, 'value': [1930000], ...  ...   \n",
       "154298390  [{'transactionTypeId': 1, 'value': [1930000], ...  ...   \n",
       "158184418  [{'transactionTypeId': 1, 'value': [485000], '...  ...   \n",
       "\n",
       "          address.location.level5Id address.location.level6Id  \\\n",
       "id                                                              \n",
       "150476642                     28079                         0   \n",
       "157313689                     28079                         0   \n",
       "153519540                     28079                         0   \n",
       "154298390                     28079                         0   \n",
       "158184418                     28079                         0   \n",
       "\n",
       "          address.location.level7Id  address.location.level8Id  \\\n",
       "id                                                               \n",
       "150476642                       678                         90   \n",
       "157313689                       176                        116   \n",
       "153519540                       187                         16   \n",
       "154298390                       187                         16   \n",
       "158184418                       176                        113   \n",
       "\n",
       "           address.coordinates.accuracy  address.coordinates.latitude  \\\n",
       "id                                                                      \n",
       "150476642                             0                      40.45485   \n",
       "157313689                             0                      40.44738   \n",
       "153519540                             0                      40.50451   \n",
       "154298390                             0                      40.50597   \n",
       "158184418                             0                      40.44738   \n",
       "\n",
       "           address.coordinates.longitude  address.zipCode  address.customZone  \\\n",
       "id                                                                              \n",
       "150476642                      -3.630255            28043                 NaN   \n",
       "157313689                      -3.668194            28002                 NaN   \n",
       "153519540                      -3.692709            28034                 NaN   \n",
       "154298390                      -3.692078            28034                 NaN   \n",
       "158184418                      -3.675195            28002                 NaN   \n",
       "\n",
       "           advertiser.logo  \n",
       "id                          \n",
       "150476642              NaN  \n",
       "157313689              NaN  \n",
       "153519540              NaN  \n",
       "154298390              NaN  \n",
       "158184418              NaN  \n",
       "\n",
       "[5 rows x 55 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sale.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>158823307</th>\n",
       "      <td>[{'key': 'bathrooms', 'value': [1], 'minValue'...</td>\n",
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       "      <th>158823262</th>\n",
       "      <td>[{'key': 'bathrooms', 'value': [1], 'minValue'...</td>\n",
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       "    <tr>\n",
       "      <th>158823219</th>\n",
       "      <td>[{'key': 'bathrooms', 'value': [1], 'minValue'...</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>9280 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    features\n",
       "id                                                          \n",
       "150476642  [{'key': 'bathrooms', 'value': [5], 'minValue'...\n",
       "157313689  [{'key': 'bathrooms', 'value': [1], 'minValue'...\n",
       "153519540  [{'key': 'bathrooms', 'value': [6], 'minValue'...\n",
       "154298390  [{'key': 'bathrooms', 'value': [6], 'minValue'...\n",
       "158184418  [{'key': 'bathrooms', 'value': [2], 'minValue'...\n",
       "...                                                      ...\n",
       "158823456  [{'key': 'bathrooms', 'value': [1], 'minValue'...\n",
       "158823310  [{'key': 'bathrooms', 'value': [2], 'minValue'...\n",
       "158823307  [{'key': 'bathrooms', 'value': [1], 'minValue'...\n",
       "158823262  [{'key': 'bathrooms', 'value': [1], 'minValue'...\n",
       "158823219  [{'key': 'bathrooms', 'value': [1], 'minValue'...\n",
       "\n",
       "[9280 rows x 1 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(sale['features'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "features = pd.DataFrame(sale['features'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "features = features.apply(pd.Series)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
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       "      <td>{'key': 'bathrooms', 'value': [1], 'minValue':...</td>\n",
       "      <td>{'key': 'conservationState', 'value': [3], 'mi...</td>\n",
       "      <td>{'key': 'floor', 'value': [6], 'minValue': 0, ...</td>\n",
       "      <td>{'key': 'rooms', 'value': [1], 'minValue': 0, ...</td>\n",
       "      <td>{'key': 'surface', 'value': [56], 'minValue': ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158823262</th>\n",
       "      <td>{'key': 'bathrooms', 'value': [1], 'minValue':...</td>\n",
       "      <td>{'key': 'conservationState', 'value': [1], 'mi...</td>\n",
       "      <td>{'key': 'rooms', 'value': [2], 'minValue': 0, ...</td>\n",
       "      <td>{'key': 'surface', 'value': [48], 'minValue': ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158823219</th>\n",
       "      <td>{'key': 'bathrooms', 'value': [1], 'minValue':...</td>\n",
       "      <td>{'key': 'conservationState', 'value': [2], 'mi...</td>\n",
       "      <td>{'key': 'floor', 'value': [6], 'minValue': 0, ...</td>\n",
       "      <td>{'key': 'elevator', 'value': [1], 'minValue': ...</td>\n",
       "      <td>{'key': 'rooms', 'value': [2], 'minValue': 0, ...</td>\n",
       "      <td>{'key': 'surface', 'value': [90], 'minValue': ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9280 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                           0  \\\n",
       "id                                                             \n",
       "150476642  {'key': 'bathrooms', 'value': [5], 'minValue':...   \n",
       "157313689  {'key': 'bathrooms', 'value': [1], 'minValue':...   \n",
       "153519540  {'key': 'bathrooms', 'value': [6], 'minValue':...   \n",
       "154298390  {'key': 'bathrooms', 'value': [6], 'minValue':...   \n",
       "158184418  {'key': 'bathrooms', 'value': [2], 'minValue':...   \n",
       "...                                                      ...   \n",
       "158823456  {'key': 'bathrooms', 'value': [1], 'minValue':...   \n",
       "158823310  {'key': 'bathrooms', 'value': [2], 'minValue':...   \n",
       "158823307  {'key': 'bathrooms', 'value': [1], 'minValue':...   \n",
       "158823262  {'key': 'bathrooms', 'value': [1], 'minValue':...   \n",
       "158823219  {'key': 'bathrooms', 'value': [1], 'minValue':...   \n",
       "\n",
       "                                                           1  \\\n",
       "id                                                             \n",
       "150476642  {'key': 'conservationState', 'value': [2], 'mi...   \n",
       "157313689  {'key': 'conservationState', 'value': [3], 'mi...   \n",
       "153519540  {'key': 'conservationState', 'value': [1], 'mi...   \n",
       "154298390  {'key': 'conservationState', 'value': [1], 'mi...   \n",
       "158184418  {'key': 'conservationState', 'value': [4], 'mi...   \n",
       "...                                                      ...   \n",
       "158823456  {'key': 'conservationState', 'value': [4], 'mi...   \n",
       "158823310  {'key': 'floor', 'value': [6], 'minValue': 0, ...   \n",
       "158823307  {'key': 'conservationState', 'value': [3], 'mi...   \n",
       "158823262  {'key': 'conservationState', 'value': [1], 'mi...   \n",
       "158823219  {'key': 'conservationState', 'value': [2], 'mi...   \n",
       "\n",
       "                                                           2  \\\n",
       "id                                                             \n",
       "150476642  {'key': 'terrace', 'value': [1], 'minValue': 0...   \n",
       "157313689  {'key': 'floor', 'value': [7], 'minValue': 0, ...   \n",
       "153519540  {'key': 'terrace', 'value': [1], 'minValue': 0...   \n",
       "154298390  {'key': 'terrace', 'value': [1], 'minValue': 0...   \n",
       "158184418  {'key': 'floor', 'value': [8], 'minValue': 0, ...   \n",
       "...                                                      ...   \n",
       "158823456  {'key': 'floor', 'value': [6], 'minValue': 0, ...   \n",
       "158823310  {'key': 'terrace', 'value': [1], 'minValue': 0...   \n",
       "158823307  {'key': 'floor', 'value': [6], 'minValue': 0, ...   \n",
       "158823262  {'key': 'rooms', 'value': [2], 'minValue': 0, ...   \n",
       "158823219  {'key': 'floor', 'value': [6], 'minValue': 0, ...   \n",
       "\n",
       "                                                           3  \\\n",
       "id                                                             \n",
       "150476642  {'key': 'rooms', 'value': [5], 'minValue': 0, ...   \n",
       "157313689  {'key': 'elevator', 'value': [1], 'minValue': ...   \n",
       "153519540  {'key': 'rooms', 'value': [5], 'minValue': 0, ...   \n",
       "154298390  {'key': 'rooms', 'value': [5], 'minValue': 0, ...   \n",
       "158184418  {'key': 'elevator', 'value': [1], 'minValue': ...   \n",
       "...                                                      ...   \n",
       "158823456  {'key': 'rooms', 'value': [3], 'minValue': 0, ...   \n",
       "158823310  {'key': 'elevator', 'value': [1], 'minValue': ...   \n",
       "158823307  {'key': 'rooms', 'value': [1], 'minValue': 0, ...   \n",
       "158823262  {'key': 'surface', 'value': [48], 'minValue': ...   \n",
       "158823219  {'key': 'elevator', 'value': [1], 'minValue': ...   \n",
       "\n",
       "                                                           4  \\\n",
       "id                                                             \n",
       "150476642  {'key': 'surface', 'value': [554], 'minValue':...   \n",
       "157313689  {'key': 'rooms', 'value': [3], 'minValue': 0, ...   \n",
       "153519540  {'key': 'surface', 'value': [547], 'minValue':...   \n",
       "154298390  {'key': 'surface', 'value': [547], 'minValue':...   \n",
       "158184418  {'key': 'rooms', 'value': [4], 'minValue': 0, ...   \n",
       "...                                                      ...   \n",
       "158823456  {'key': 'surface', 'value': [62], 'minValue': ...   \n",
       "158823310  {'key': 'rooms', 'value': [2], 'minValue': 0, ...   \n",
       "158823307  {'key': 'surface', 'value': [56], 'minValue': ...   \n",
       "158823262                                                NaN   \n",
       "158823219  {'key': 'rooms', 'value': [2], 'minValue': 0, ...   \n",
       "\n",
       "                                                           5    6    7  \n",
       "id                                                                      \n",
       "150476642                                                NaN  NaN  NaN  \n",
       "157313689  {'key': 'surface', 'value': [80], 'minValue': ...  NaN  NaN  \n",
       "153519540                                                NaN  NaN  NaN  \n",
       "154298390                                                NaN  NaN  NaN  \n",
       "158184418  {'key': 'surface', 'value': [133], 'minValue':...  NaN  NaN  \n",
       "...                                                      ...  ...  ...  \n",
       "158823456                                                NaN  NaN  NaN  \n",
       "158823310  {'key': 'surface', 'value': [83], 'minValue': ...  NaN  NaN  \n",
       "158823307                                                NaN  NaN  NaN  \n",
       "158823262                                                NaN  NaN  NaN  \n",
       "158823219  {'key': 'surface', 'value': [90], 'minValue': ...  NaN  NaN  \n",
       "\n",
       "[9280 rows x 8 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features['features'].apply(pd.Series)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "features = features['features'].apply(pd.Series)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#feats0 = features[0].apply(pd.Series)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "feats0 = features[0].apply(pd.Series)\n",
    "feats1 = features[1].apply(pd.Series)\n",
    "feats2 = features[2].apply(pd.Series)\n",
    "feats3 = features[3].apply(pd.Series)\n",
    "feats4 = features[4].apply(pd.Series)\n",
    "feats5 = features[5].apply(pd.Series)\n",
    "feats6 = features[6].apply(pd.Series)\n",
    "feats7 = features[7].apply(pd.Series)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>key</th>\n",
       "      <th>maxValue</th>\n",
       "      <th>minValue</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>150476642</th>\n",
       "      <td>NaN</td>\n",
       "      <td>bathrooms</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>[5]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157313689</th>\n",
       "      <td>NaN</td>\n",
       "      <td>bathrooms</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>[1]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153519540</th>\n",
       "      <td>NaN</td>\n",
       "      <td>bathrooms</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>[6]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154298390</th>\n",
       "      <td>NaN</td>\n",
       "      <td>bathrooms</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>[6]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158184418</th>\n",
       "      <td>NaN</td>\n",
       "      <td>bathrooms</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</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>158823456</th>\n",
       "      <td>NaN</td>\n",
       "      <td>bathrooms</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>[1]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158823310</th>\n",
       "      <td>NaN</td>\n",
       "      <td>bathrooms</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>[2]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158823307</th>\n",
       "      <td>NaN</td>\n",
       "      <td>bathrooms</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>[1]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158823262</th>\n",
       "      <td>NaN</td>\n",
       "      <td>bathrooms</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>[1]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158823219</th>\n",
       "      <td>NaN</td>\n",
       "      <td>bathrooms</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>[1]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9280 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            0        key  maxValue  minValue value\n",
       "id                                                \n",
       "150476642 NaN  bathrooms       0.0       0.0   [5]\n",
       "157313689 NaN  bathrooms       0.0       0.0   [1]\n",
       "153519540 NaN  bathrooms       0.0       0.0   [6]\n",
       "154298390 NaN  bathrooms       0.0       0.0   [6]\n",
       "158184418 NaN  bathrooms       0.0       0.0   [2]\n",
       "...        ..        ...       ...       ...   ...\n",
       "158823456 NaN  bathrooms       0.0       0.0   [1]\n",
       "158823310 NaN  bathrooms       0.0       0.0   [2]\n",
       "158823307 NaN  bathrooms       0.0       0.0   [1]\n",
       "158823262 NaN  bathrooms       0.0       0.0   [1]\n",
       "158823219 NaN  bathrooms       0.0       0.0   [1]\n",
       "\n",
       "[9280 rows x 5 columns]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feats0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(9280, 5)"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feats0.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index([0, 'key', 'maxValue', 'minValue', 'value'], dtype='object')"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feats0.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "feats0 = feats0.drop([0, 'maxValue', 'minValue'], axis=1)\n",
    "feats1 = feats1.drop([0, 'maxValue', 'minValue'], axis=1)\n",
    "feats2 = feats2.drop([0, 'maxValue', 'minValue'], axis=1)\n",
    "feats3 = feats3.drop([0, 'maxValue', 'minValue'], axis=1)\n",
    "feats4 = feats4.drop([0, 'maxValue', 'minValue'], axis=1)\n",
    "feats5 = feats5.drop([0, 'maxValue', 'minValue'], axis=1)\n",
    "feats6 = feats6.drop([0, 'maxValue', 'minValue'], axis=1)\n",
    "feats7 = feats7.drop([0, 'maxValue', 'minValue'], axis=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(9280, 2)"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feats0.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#feats['value'] = feats['value'].map(lambda x: str(x).strip('[]'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "feats0['value'] = feats0['value'].map(lambda x: str(x).strip('[]'))\n",
    "feats1['value'] = feats1['value'].map(lambda x: str(x).strip('[]'))\n",
    "feats2['value'] = feats2['value'].map(lambda x: str(x).strip('[]'))\n",
    "feats3['value'] = feats3['value'].map(lambda x: str(x).strip('[]'))\n",
    "feats4['value'] = feats4['value'].map(lambda x: str(x).strip('[]'))\n",
    "feats5['value'] = feats5['value'].map(lambda x: str(x).strip('[]'))\n",
    "feats6['value'] = feats6['value'].map(lambda x: str(x).strip('[]'))\n",
    "feats7['value'] = feats7['value'].map(lambda x: str(x).strip('[]'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "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>key</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>150476642</th>\n",
       "      <td>bathrooms</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157313689</th>\n",
       "      <td>bathrooms</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153519540</th>\n",
       "      <td>bathrooms</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154298390</th>\n",
       "      <td>bathrooms</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158184418</th>\n",
       "      <td>bathrooms</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158823456</th>\n",
       "      <td>bathrooms</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158823310</th>\n",
       "      <td>bathrooms</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158823307</th>\n",
       "      <td>bathrooms</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158823262</th>\n",
       "      <td>bathrooms</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158823219</th>\n",
       "      <td>bathrooms</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9280 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 key value\n",
       "id                        \n",
       "150476642  bathrooms     5\n",
       "157313689  bathrooms     1\n",
       "153519540  bathrooms     6\n",
       "154298390  bathrooms     6\n",
       "158184418  bathrooms     2\n",
       "...              ...   ...\n",
       "158823456  bathrooms     1\n",
       "158823310  bathrooms     2\n",
       "158823307  bathrooms     1\n",
       "158823262  bathrooms     1\n",
       "158823219  bathrooms     1\n",
       "\n",
       "[9280 rows x 2 columns]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feats0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feats0['value'].isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# feats['value'] = feats['value'].astype('float')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "feats0['value'] = feats0['value'].astype('float')\n",
    "feats1['value'] = feats1['value'].astype('float')\n",
    "feats2['value'] = feats2['value'].astype('float')\n",
    "feats3['value'] = feats3['value'].astype('float')\n",
    "feats4['value'] = feats4['value'].astype('float')\n",
    "feats5['value'] = feats5['value'].astype('float')\n",
    "feats6['value'] = feats6['value'].astype('float')\n",
    "feats7['value'] = feats7['value'].astype('float')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#feats['value'] = feats['value'].fillna(value=0)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "feats0['value'] = feats0['value'].fillna(value=0)\n",
    "feats1['value'] = feats1['value'].fillna(value=0)\n",
    "feats2['value'] = feats2['value'].fillna(value=0)\n",
    "feats3['value'] = feats3['value'].fillna(value=0)\n",
    "feats4['value'] = feats4['value'].fillna(value=0)\n",
    "feats5['value'] = feats5['value'].fillna(value=0)\n",
    "feats6['value'] = feats6['value'].fillna(value=0)\n",
    "feats7['value'] = feats7['value'].fillna(value=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#feats['value'] = feats['value'].astype('int64')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "feats0['value'] = feats0['value'].astype('int64')\n",
    "feats1['value'] = feats1['value'].astype('int64')\n",
    "feats2['value'] = feats2['value'].astype('int64')\n",
    "feats3['value'] = feats3['value'].astype('int64')\n",
    "feats4['value'] = feats4['value'].astype('int64')\n",
    "feats5['value'] = feats5['value'].astype('int64')\n",
    "feats6['value'] = feats6['value'].astype('int64')\n",
    "feats7['value'] = feats7['value'].astype('int64')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#feats.drop([158149988], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#feats = pd.pivot_table(feats, index=['id'], columns=feats['key'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "feats0 = pd.pivot_table(feats0, index=['id'], columns=feats0['key'])\n",
    "feats1 = pd.pivot_table(feats1, index=['id'], columns=feats1['key'])\n",
    "feats2 = pd.pivot_table(feats2, index=['id'], columns=feats2['key'])\n",
    "feats3 = pd.pivot_table(feats3, index=['id'], columns=feats3['key'])\n",
    "feats4 = pd.pivot_table(feats4, index=['id'], columns=feats4['key'])\n",
    "feats5 = pd.pivot_table(feats5, index=['id'], columns=feats5['key'])\n",
    "feats6 = pd.pivot_table(feats6, index=['id'], columns=feats6['key'])\n",
    "feats7 = pd.pivot_table(feats7, index=['id'], columns=feats7['key'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "right0 = feats0.add(feats1, fill_value=0)\n",
    "right1 = feats2.add(feats3, fill_value=0)\n",
    "right2 = feats4.add(feats5, fill_value=0)\n",
    "right3 = feats6.add(feats7, fill_value=0)\n",
    "right4 = right0.add(right1, fill_value=0)\n",
    "right5 = right2.add(right3, fill_value=0)\n",
    "features_d = right4.add(right5, fill_value=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"8\" halign=\"left\">value</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>key</th>\n",
       "      <th>bathrooms</th>\n",
       "      <th>conservationState</th>\n",
       "      <th>elevator</th>\n",
       "      <th>floor</th>\n",
       "      <th>parking</th>\n",
       "      <th>rooms</th>\n",
       "      <th>surface</th>\n",
       "      <th>terrace</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>126502387</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126510669</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129014252</th>\n",
       "      <td>9.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1300.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129864463</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>80.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129864591</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>93.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158984488</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158984518</th>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158984533</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158984567</th>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>307.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158984617</th>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>191.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9279 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              value                                                         \\\n",
       "key       bathrooms conservationState elevator floor parking rooms surface   \n",
       "id                                                                           \n",
       "126502387       2.0               NaN      1.0   9.0     NaN   2.0    95.0   \n",
       "126510669       1.0               NaN      1.0   6.0     NaN   1.0    80.0   \n",
       "129014252       9.0               2.0      NaN   3.0     NaN   7.0  1300.0   \n",
       "129864463       1.0               NaN      1.0   8.0     1.0   NaN    80.0   \n",
       "129864591       2.0               NaN      1.0   3.0     1.0   NaN    93.0   \n",
       "...             ...               ...      ...   ...     ...   ...     ...   \n",
       "158984488       1.0               1.0      NaN   3.0     NaN   1.0    50.0   \n",
       "158984518       2.0               1.0      1.0   NaN     1.0   3.0    93.0   \n",
       "158984533       1.0               3.0      1.0   8.0     NaN   3.0    93.0   \n",
       "158984567       3.0               NaN      NaN   NaN     NaN   NaN   307.0   \n",
       "158984617       2.0               4.0      1.0   6.0     NaN   5.0   191.0   \n",
       "\n",
       "                   \n",
       "key       terrace  \n",
       "id                 \n",
       "126502387     1.0  \n",
       "126510669     NaN  \n",
       "129014252     NaN  \n",
       "129864463     1.0  \n",
       "129864591     1.0  \n",
       "...           ...  \n",
       "158984488     NaN  \n",
       "158984518     NaN  \n",
       "158984533     NaN  \n",
       "158984567     1.0  \n",
       "158984617     NaN  \n",
       "\n",
       "[9279 rows x 8 columns]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features_d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale['bathrooms']=features_d.value['bathrooms']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale['conservationState'] = features_d.value['conservationState']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale['elevator'] = features_d.value['elevator']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale['floor'] = features_d.value['floor']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale['parking'] = features_d.value['parking']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale['rooms'] = features_d.value['rooms']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale['surface'] = features_d.value['surface']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale['terrace'] = features_d.value['terrace']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale.to_json('Madrid_sale.json', orient='records')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale.to_json('Madrid_salev1.json', orient='records')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Droping some Columns isna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import pymysql\n",
    "from sqlalchemy import create_engine\n",
    "from getpass import getpass\n",
    "from sqlalchemy import inspect\n",
    "from bs4 import BeautifulSoup\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import time\n",
    "import os\n",
    "import requests as r\n",
    "import re\n",
    "import geopy "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Expected object or value",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-72-9221d60502fa>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0msale\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread_json\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Madrid_salev1.json'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0morient\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'records'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m~\\miniconda3\\lib\\site-packages\\pandas\\util\\_decorators.py\u001b[0m in \u001b[0;36mwrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    197\u001b[0m                 \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    198\u001b[0m                     \u001b[0mkwargs\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mnew_arg_name\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnew_arg_value\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 199\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    200\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    201\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mcast\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mF\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mwrapper\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\miniconda3\\lib\\site-packages\\pandas\\util\\_decorators.py\u001b[0m in \u001b[0;36mwrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    297\u001b[0m                 )\n\u001b[0;32m    298\u001b[0m                 \u001b[0mwarnings\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwarn\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mFutureWarning\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstacklevel\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mstacklevel\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 299\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    300\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    301\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mwrapper\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\miniconda3\\lib\\site-packages\\pandas\\io\\json\\_json.py\u001b[0m in \u001b[0;36mread_json\u001b[1;34m(path_or_buf, orient, typ, dtype, convert_axes, convert_dates, keep_default_dates, numpy, precise_float, date_unit, encoding, lines, chunksize, compression, nrows, storage_options)\u001b[0m\n\u001b[0;32m    561\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    562\u001b[0m     \u001b[1;32mwith\u001b[0m \u001b[0mjson_reader\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 563\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mjson_reader\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    564\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    565\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\miniconda3\\lib\\site-packages\\pandas\\io\\json\\_json.py\u001b[0m in \u001b[0;36mread\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    692\u001b[0m                 \u001b[0mobj\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_object_parser\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_combine_lines\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata_lines\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    693\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 694\u001b[1;33m             \u001b[0mobj\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_object_parser\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    695\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mclose\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    696\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mobj\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\miniconda3\\lib\\site-packages\\pandas\\io\\json\\_json.py\u001b[0m in \u001b[0;36m_get_object_parser\u001b[1;34m(self, json)\u001b[0m\n\u001b[0;32m    714\u001b[0m         \u001b[0mobj\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    715\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mtyp\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m\"frame\"\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 716\u001b[1;33m             \u001b[0mobj\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mFrameParser\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mjson\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mparse\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    717\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    718\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mtyp\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m\"series\"\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0mobj\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\miniconda3\\lib\\site-packages\\pandas\\io\\json\\_json.py\u001b[0m in \u001b[0;36mparse\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    829\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    830\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 831\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_parse_no_numpy\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    832\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    833\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mobj\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\miniconda3\\lib\\site-packages\\pandas\\io\\json\\_json.py\u001b[0m in \u001b[0;36m_parse_no_numpy\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m   1096\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1097\u001b[0m             self.obj = DataFrame(\n\u001b[1;32m-> 1098\u001b[1;33m                 \u001b[0mloads\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mjson\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mprecise_float\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mprecise_float\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1099\u001b[0m             )\n\u001b[0;32m   1100\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mValueError\u001b[0m: Expected object or value"
     ]
    }
   ],
   "source": [
    "sale = pd.read_json('Madrid_salev1.json', orient='records')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['id', 'multimedias', 'transactions', 'products', 'date', 'description',\n",
       "       'advertiser.logo.multimedia.typeId', 'detail.es', 'address.ubication',\n",
       "       'address.location.country', 'address.location.level1',\n",
       "       'address.location.level2', 'address.location.level3',\n",
       "       'address.location.level5', 'address.location.level7',\n",
       "       'address.location.level8', 'address.location.upperLevel',\n",
       "       'address.location.countryId', 'address.location.level1Id',\n",
       "       'address.location.level2Id', 'address.location.level3Id',\n",
       "       'address.location.level4Id', 'address.location.level5Id',\n",
       "       'address.location.level6Id', 'address.location.level7Id',\n",
       "       'address.location.level8Id', 'address.coordinates.accuracy',\n",
       "       'address.coordinates.latitude', 'address.coordinates.longitude',\n",
       "       'address.zipCode', 'bathrooms', 'conservationState', 'elevator',\n",
       "       'floor', 'parking', 'rooms', 'surface', 'terrace'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sale.columns\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale = sale.drop(['advertiser.phone', 'advertiser.typeId', 'advertiser.clientId','advertiser.urlAlias', 'advertiser.clientAlias','address.location.level4', 'address.location.level6','promotionId','typeId','subtypeId', 'isNew', 'isTop', 'isPhotoReport', 'isMsAdvance', 'isExternalContact','promotionId'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale.to_json('Madrid_salev1.json', orient='records')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 298,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale = sale.drop(['products', 'advertiser.logo.multimedia.typeId'], axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Lets attack multimedia column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 299,
   "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>id</th>\n",
       "      <th>multimedias</th>\n",
       "      <th>transactions</th>\n",
       "      <th>date</th>\n",
       "      <th>description</th>\n",
       "      <th>detail.es</th>\n",
       "      <th>address.ubication</th>\n",
       "      <th>address.location.country</th>\n",
       "      <th>address.location.level1</th>\n",
       "      <th>address.location.level2</th>\n",
       "      <th>...</th>\n",
       "      <th>address.zipCode</th>\n",
       "      <th>bathrooms</th>\n",
       "      <th>conservationState</th>\n",
       "      <th>elevator</th>\n",
       "      <th>floor</th>\n",
       "      <th>parking</th>\n",
       "      <th>rooms</th>\n",
       "      <th>surface</th>\n",
       "      <th>terrace</th>\n",
       "      <th>multimedia</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>150476642</th>\n",
       "      <td>150476642</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/100202/1...</td>\n",
       "      <td>2200000</td>\n",
       "      <td>2021-02-19 15:40:40.138</td>\n",
       "      <td>GILMAR Consulting Inmobiliario Madrid, Conde O...</td>\n",
       "      <td>/es/comprar/vivienda/madrid-capital/calefaccio...</td>\n",
       "      <td>Andarrios, Hortaleza</td>\n",
       "      <td>España</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>...</td>\n",
       "      <td>28043</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>554.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/100202/1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157313689</th>\n",
       "      <td>157313689</td>\n",
       "      <td>[{'url': 'https://my.matterport.com/show/?m=fi...</td>\n",
       "      <td>405000</td>\n",
       "      <td>2021-02-19 15:40:40.138</td>\n",
       "      <td>Gilmar ofrece, magnifica Vivienda, Ubicada en ...</td>\n",
       "      <td>/es/comprar/vivienda/madrid-capital/aire-acond...</td>\n",
       "      <td>Chamartín</td>\n",
       "      <td>España</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>...</td>\n",
       "      <td>28002</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'url': 'https://my.matterport.com/show/?m=fi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153519540</th>\n",
       "      <td>153519540</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/100207/1...</td>\n",
       "      <td>1930000</td>\n",
       "      <td>2021-02-19 15:40:40.138</td>\n",
       "      <td>Gilmar Mirasierra - Puerta de Hierro (91771777...</td>\n",
       "      <td>/es/comprar/vivienda/madrid-capital/aire-acond...</td>\n",
       "      <td>Fuencarral</td>\n",
       "      <td>España</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>...</td>\n",
       "      <td>28034</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>547.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/100207/1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154298390</th>\n",
       "      <td>154298390</td>\n",
       "      <td>[{'url': 'https://images.inmofactory.com/inmof...</td>\n",
       "      <td>1930000</td>\n",
       "      <td>2021-02-19 15:40:40.138</td>\n",
       "      <td>Gilmar Mirasierra - Puerta de Hierro (91771777...</td>\n",
       "      <td>/es/comprar/vivienda/madrid-capital/aire-acond...</td>\n",
       "      <td>Fuencarral</td>\n",
       "      <td>España</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>...</td>\n",
       "      <td>28034</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>547.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[{'url': 'https://images.inmofactory.com/inmof...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158184418</th>\n",
       "      <td>158184418</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/89548/26...</td>\n",
       "      <td>485000</td>\n",
       "      <td>2021-02-19 15:40:40.138</td>\n",
       "      <td>Magnifica vivienda en Ciudad Jardín, \\r\\n\\r\\nP...</td>\n",
       "      <td>/es/comprar/vivienda/madrid-capital/calefaccio...</td>\n",
       "      <td>Chamartín</td>\n",
       "      <td>España</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>...</td>\n",
       "      <td>28002</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>133.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/89548/26...</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>158823456</th>\n",
       "      <td>158823456</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/85276/27...</td>\n",
       "      <td>115000</td>\n",
       "      <td>2021-02-05 11:43:44.497</td>\n",
       "      <td>Piso para actualizar en Zona Hellín.\\r\\n\\r\\nFa...</td>\n",
       "      <td>/es/comprar/vivienda/madrid-capital/aire-acond...</td>\n",
       "      <td>Calle de Hinojosa del Duque, San Blas</td>\n",
       "      <td>España</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>...</td>\n",
       "      <td>28037</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/85276/27...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158823310</th>\n",
       "      <td>158823310</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/85276/27...</td>\n",
       "      <td>179000</td>\n",
       "      <td>2021-02-05 11:35:14.360</td>\n",
       "      <td>Magnífico dúplex loft a dos alturas, totalment...</td>\n",
       "      <td>/es/comprar/vivienda/madrid-capital/aire-acond...</td>\n",
       "      <td>Carretera de Vicálvaro a la Estac. O'donnell, ...</td>\n",
       "      <td>España</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>...</td>\n",
       "      <td>28032</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/85276/27...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158823307</th>\n",
       "      <td>158823307</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/98925/27...</td>\n",
       "      <td>137000</td>\n",
       "      <td>2021-02-05 11:34:53.280</td>\n",
       "      <td>Luminosa vivienda de 56 m2, amplio salón con c...</td>\n",
       "      <td>/es/comprar/vivienda/madrid-capital/aire-acond...</td>\n",
       "      <td>Calle Garganchón, Barajas</td>\n",
       "      <td>España</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>...</td>\n",
       "      <td>28042</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/98925/27...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158823262</th>\n",
       "      <td>158823262</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/85276/27...</td>\n",
       "      <td>115000</td>\n",
       "      <td>2021-02-05 11:31:41.277</td>\n",
       "      <td>Fantástico Piso en zona Simancas, Impecable, t...</td>\n",
       "      <td>/es/comprar/vivienda/madrid-capital/aire-acond...</td>\n",
       "      <td>Calle de Zubieta, San Blas</td>\n",
       "      <td>España</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>...</td>\n",
       "      <td>28037</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/85276/27...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158823219</th>\n",
       "      <td>158823219</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/88669/27...</td>\n",
       "      <td>380000</td>\n",
       "      <td>2021-02-05 11:29:45.217</td>\n",
       "      <td>\"Piso inteio, muy tranquilo en el corazón del ...</td>\n",
       "      <td>/es/comprar/vivienda/madrid-capital/aire-acond...</td>\n",
       "      <td>Calle del Conde de Peñalver, 30, Salamanca</td>\n",
       "      <td>España</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>...</td>\n",
       "      <td>28006</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/88669/27...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9280 rows × 37 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  id                                        multimedias  \\\n",
       "id                                                                        \n",
       "150476642  150476642  [{'url': 'https://d.inmofactory.com/1/100202/1...   \n",
       "157313689  157313689  [{'url': 'https://my.matterport.com/show/?m=fi...   \n",
       "153519540  153519540  [{'url': 'https://d.inmofactory.com/1/100207/1...   \n",
       "154298390  154298390  [{'url': 'https://images.inmofactory.com/inmof...   \n",
       "158184418  158184418  [{'url': 'https://d.inmofactory.com/1/89548/26...   \n",
       "...              ...                                                ...   \n",
       "158823456  158823456  [{'url': 'https://d.inmofactory.com/1/85276/27...   \n",
       "158823310  158823310  [{'url': 'https://d.inmofactory.com/1/85276/27...   \n",
       "158823307  158823307  [{'url': 'https://d.inmofactory.com/1/98925/27...   \n",
       "158823262  158823262  [{'url': 'https://d.inmofactory.com/1/85276/27...   \n",
       "158823219  158823219  [{'url': 'https://d.inmofactory.com/1/88669/27...   \n",
       "\n",
       "           transactions                    date  \\\n",
       "id                                                \n",
       "150476642       2200000 2021-02-19 15:40:40.138   \n",
       "157313689        405000 2021-02-19 15:40:40.138   \n",
       "153519540       1930000 2021-02-19 15:40:40.138   \n",
       "154298390       1930000 2021-02-19 15:40:40.138   \n",
       "158184418        485000 2021-02-19 15:40:40.138   \n",
       "...                 ...                     ...   \n",
       "158823456        115000 2021-02-05 11:43:44.497   \n",
       "158823310        179000 2021-02-05 11:35:14.360   \n",
       "158823307        137000 2021-02-05 11:34:53.280   \n",
       "158823262        115000 2021-02-05 11:31:41.277   \n",
       "158823219        380000 2021-02-05 11:29:45.217   \n",
       "\n",
       "                                                 description  \\\n",
       "id                                                             \n",
       "150476642  GILMAR Consulting Inmobiliario Madrid, Conde O...   \n",
       "157313689  Gilmar ofrece, magnifica Vivienda, Ubicada en ...   \n",
       "153519540  Gilmar Mirasierra - Puerta de Hierro (91771777...   \n",
       "154298390  Gilmar Mirasierra - Puerta de Hierro (91771777...   \n",
       "158184418  Magnifica vivienda en Ciudad Jardín, \\r\\n\\r\\nP...   \n",
       "...                                                      ...   \n",
       "158823456  Piso para actualizar en Zona Hellín.\\r\\n\\r\\nFa...   \n",
       "158823310  Magnífico dúplex loft a dos alturas, totalment...   \n",
       "158823307  Luminosa vivienda de 56 m2, amplio salón con c...   \n",
       "158823262  Fantástico Piso en zona Simancas, Impecable, t...   \n",
       "158823219  \"Piso inteio, muy tranquilo en el corazón del ...   \n",
       "\n",
       "                                                   detail.es  \\\n",
       "id                                                             \n",
       "150476642  /es/comprar/vivienda/madrid-capital/calefaccio...   \n",
       "157313689  /es/comprar/vivienda/madrid-capital/aire-acond...   \n",
       "153519540  /es/comprar/vivienda/madrid-capital/aire-acond...   \n",
       "154298390  /es/comprar/vivienda/madrid-capital/aire-acond...   \n",
       "158184418  /es/comprar/vivienda/madrid-capital/calefaccio...   \n",
       "...                                                      ...   \n",
       "158823456  /es/comprar/vivienda/madrid-capital/aire-acond...   \n",
       "158823310  /es/comprar/vivienda/madrid-capital/aire-acond...   \n",
       "158823307  /es/comprar/vivienda/madrid-capital/aire-acond...   \n",
       "158823262  /es/comprar/vivienda/madrid-capital/aire-acond...   \n",
       "158823219  /es/comprar/vivienda/madrid-capital/aire-acond...   \n",
       "\n",
       "                                           address.ubication  \\\n",
       "id                                                             \n",
       "150476642                               Andarrios, Hortaleza   \n",
       "157313689                                          Chamartín   \n",
       "153519540                                         Fuencarral   \n",
       "154298390                                         Fuencarral   \n",
       "158184418                                          Chamartín   \n",
       "...                                                      ...   \n",
       "158823456              Calle de Hinojosa del Duque, San Blas   \n",
       "158823310  Carretera de Vicálvaro a la Estac. O'donnell, ...   \n",
       "158823307                          Calle Garganchón, Barajas   \n",
       "158823262                         Calle de Zubieta, San Blas   \n",
       "158823219         Calle del Conde de Peñalver, 30, Salamanca   \n",
       "\n",
       "          address.location.country address.location.level1  \\\n",
       "id                                                           \n",
       "150476642                   España                  Madrid   \n",
       "157313689                   España                  Madrid   \n",
       "153519540                   España                  Madrid   \n",
       "154298390                   España                  Madrid   \n",
       "158184418                   España                  Madrid   \n",
       "...                            ...                     ...   \n",
       "158823456                   España                  Madrid   \n",
       "158823310                   España                  Madrid   \n",
       "158823307                   España                  Madrid   \n",
       "158823262                   España                  Madrid   \n",
       "158823219                   España                  Madrid   \n",
       "\n",
       "          address.location.level2  ... address.zipCode bathrooms  \\\n",
       "id                                 ...                             \n",
       "150476642                  Madrid  ...           28043       5.0   \n",
       "157313689                  Madrid  ...           28002       1.0   \n",
       "153519540                  Madrid  ...           28034       6.0   \n",
       "154298390                  Madrid  ...           28034       6.0   \n",
       "158184418                  Madrid  ...           28002       2.0   \n",
       "...                           ...  ...             ...       ...   \n",
       "158823456                  Madrid  ...           28037       1.0   \n",
       "158823310                  Madrid  ...           28032       2.0   \n",
       "158823307                  Madrid  ...           28042       1.0   \n",
       "158823262                  Madrid  ...           28037       1.0   \n",
       "158823219                  Madrid  ...           28006       1.0   \n",
       "\n",
       "          conservationState elevator floor  parking  rooms  surface  terrace  \\\n",
       "id                                                                             \n",
       "150476642               2.0      NaN   NaN      NaN    5.0    554.0      1.0   \n",
       "157313689               3.0      1.0   7.0      NaN    3.0     80.0      NaN   \n",
       "153519540               1.0      NaN   NaN      NaN    5.0    547.0      1.0   \n",
       "154298390               1.0      NaN   NaN      NaN    5.0    547.0      1.0   \n",
       "158184418               4.0      1.0   8.0      NaN    4.0    133.0      NaN   \n",
       "...                     ...      ...   ...      ...    ...      ...      ...   \n",
       "158823456               4.0      NaN   6.0      NaN    3.0     62.0      NaN   \n",
       "158823310               NaN      1.0   6.0      NaN    2.0     83.0      1.0   \n",
       "158823307               3.0      NaN   6.0      NaN    1.0     56.0      NaN   \n",
       "158823262               1.0      NaN   NaN      NaN    2.0     48.0      NaN   \n",
       "158823219               2.0      1.0   6.0      NaN    2.0     90.0      NaN   \n",
       "\n",
       "                                                  multimedia  \n",
       "id                                                            \n",
       "150476642  [{'url': 'https://d.inmofactory.com/1/100202/1...  \n",
       "157313689  [{'url': 'https://my.matterport.com/show/?m=fi...  \n",
       "153519540  [{'url': 'https://d.inmofactory.com/1/100207/1...  \n",
       "154298390  [{'url': 'https://images.inmofactory.com/inmof...  \n",
       "158184418  [{'url': 'https://d.inmofactory.com/1/89548/26...  \n",
       "...                                                      ...  \n",
       "158823456  [{'url': 'https://d.inmofactory.com/1/85276/27...  \n",
       "158823310  [{'url': 'https://d.inmofactory.com/1/85276/27...  \n",
       "158823307  [{'url': 'https://d.inmofactory.com/1/98925/27...  \n",
       "158823262  [{'url': 'https://d.inmofactory.com/1/85276/27...  \n",
       "158823219  [{'url': 'https://d.inmofactory.com/1/88669/27...  \n",
       "\n",
       "[9280 rows x 37 columns]"
      ]
     },
     "execution_count": 299,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale = sale.set_index(sale['id'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 252,
   "metadata": {},
   "outputs": [],
   "source": [
    "multimedia = pd.DataFrame(sale['multimedias'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 253,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale['multimedia']=multimedia['multimedias']\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Let's go for the price of the flat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 269,
   "metadata": {},
   "outputs": [],
   "source": [
    "price = pd.DataFrame(sale['transactions'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 273,
   "metadata": {},
   "outputs": [],
   "source": [
    "price = price['transactions'].apply(pd.Series)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 286,
   "metadata": {},
   "outputs": [],
   "source": [
    "price = price[0].apply(pd.Series)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 288,
   "metadata": {},
   "outputs": [],
   "source": [
    "price['value'] = price['value'].map(lambda x: str(x).strip('[]'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 290,
   "metadata": {},
   "outputs": [],
   "source": [
    "price['value'] = price['value'].astype('int64')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 291,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale['transactions'] = price['value']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 292,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>multimedias</th>\n",
       "      <th>transactions</th>\n",
       "      <th>products</th>\n",
       "      <th>date</th>\n",
       "      <th>description</th>\n",
       "      <th>advertiser.logo.multimedia.typeId</th>\n",
       "      <th>detail.es</th>\n",
       "      <th>address.ubication</th>\n",
       "      <th>address.location.country</th>\n",
       "      <th>...</th>\n",
       "      <th>address.zipCode</th>\n",
       "      <th>bathrooms</th>\n",
       "      <th>conservationState</th>\n",
       "      <th>elevator</th>\n",
       "      <th>floor</th>\n",
       "      <th>parking</th>\n",
       "      <th>rooms</th>\n",
       "      <th>surface</th>\n",
       "      <th>terrace</th>\n",
       "      <th>multimedia</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>150476642</th>\n",
       "      <td>150476642</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/100202/1...</td>\n",
       "      <td>2200000</td>\n",
       "      <td>[{'id': 56}]</td>\n",
       "      <td>2021-02-19 15:40:40.138</td>\n",
       "      <td>GILMAR Consulting Inmobiliario Madrid, Conde O...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>/es/comprar/vivienda/madrid-capital/calefaccio...</td>\n",
       "      <td>Andarrios, Hortaleza</td>\n",
       "      <td>España</td>\n",
       "      <td>...</td>\n",
       "      <td>28043</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>554.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/100202/1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157313689</th>\n",
       "      <td>157313689</td>\n",
       "      <td>[{'url': 'https://my.matterport.com/show/?m=fi...</td>\n",
       "      <td>405000</td>\n",
       "      <td>[{'id': 56}]</td>\n",
       "      <td>2021-02-19 15:40:40.138</td>\n",
       "      <td>Gilmar ofrece, magnifica Vivienda, Ubicada en ...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>/es/comprar/vivienda/madrid-capital/aire-acond...</td>\n",
       "      <td>Chamartín</td>\n",
       "      <td>España</td>\n",
       "      <td>...</td>\n",
       "      <td>28002</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'url': 'https://my.matterport.com/show/?m=fi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153519540</th>\n",
       "      <td>153519540</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/100207/1...</td>\n",
       "      <td>1930000</td>\n",
       "      <td>[{'id': 3}, {'id': 56}]</td>\n",
       "      <td>2021-02-19 15:40:40.138</td>\n",
       "      <td>Gilmar Mirasierra - Puerta de Hierro (91771777...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>/es/comprar/vivienda/madrid-capital/aire-acond...</td>\n",
       "      <td>Fuencarral</td>\n",
       "      <td>España</td>\n",
       "      <td>...</td>\n",
       "      <td>28034</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>547.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/100207/1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154298390</th>\n",
       "      <td>154298390</td>\n",
       "      <td>[{'url': 'https://images.inmofactory.com/inmof...</td>\n",
       "      <td>1930000</td>\n",
       "      <td>[{'id': 56}]</td>\n",
       "      <td>2021-02-19 15:40:40.138</td>\n",
       "      <td>Gilmar Mirasierra - Puerta de Hierro (91771777...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>/es/comprar/vivienda/madrid-capital/aire-acond...</td>\n",
       "      <td>Fuencarral</td>\n",
       "      <td>España</td>\n",
       "      <td>...</td>\n",
       "      <td>28034</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>547.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[{'url': 'https://images.inmofactory.com/inmof...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158184418</th>\n",
       "      <td>158184418</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/89548/26...</td>\n",
       "      <td>485000</td>\n",
       "      <td>[{'id': 56}]</td>\n",
       "      <td>2021-02-19 15:40:40.138</td>\n",
       "      <td>Magnifica vivienda en Ciudad Jardín, \\r\\n\\r\\nP...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>/es/comprar/vivienda/madrid-capital/calefaccio...</td>\n",
       "      <td>Chamartín</td>\n",
       "      <td>España</td>\n",
       "      <td>...</td>\n",
       "      <td>28002</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>133.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/89548/26...</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>158823456</th>\n",
       "      <td>158823456</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/85276/27...</td>\n",
       "      <td>115000</td>\n",
       "      <td>[{'id': 62}]</td>\n",
       "      <td>2021-02-05 11:43:44.497</td>\n",
       "      <td>Piso para actualizar en Zona Hellín.\\r\\n\\r\\nFa...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>/es/comprar/vivienda/madrid-capital/aire-acond...</td>\n",
       "      <td>Calle de Hinojosa del Duque, San Blas</td>\n",
       "      <td>España</td>\n",
       "      <td>...</td>\n",
       "      <td>28037</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/85276/27...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158823310</th>\n",
       "      <td>158823310</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/85276/27...</td>\n",
       "      <td>179000</td>\n",
       "      <td>[{'id': 62}, {'id': 56}]</td>\n",
       "      <td>2021-02-05 11:35:14.360</td>\n",
       "      <td>Magnífico dúplex loft a dos alturas, totalment...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>/es/comprar/vivienda/madrid-capital/aire-acond...</td>\n",
       "      <td>Carretera de Vicálvaro a la Estac. O'donnell, ...</td>\n",
       "      <td>España</td>\n",
       "      <td>...</td>\n",
       "      <td>28032</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/85276/27...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158823307</th>\n",
       "      <td>158823307</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/98925/27...</td>\n",
       "      <td>137000</td>\n",
       "      <td>[]</td>\n",
       "      <td>2021-02-05 11:34:53.280</td>\n",
       "      <td>Luminosa vivienda de 56 m2, amplio salón con c...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>/es/comprar/vivienda/madrid-capital/aire-acond...</td>\n",
       "      <td>Calle Garganchón, Barajas</td>\n",
       "      <td>España</td>\n",
       "      <td>...</td>\n",
       "      <td>28042</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/98925/27...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158823262</th>\n",
       "      <td>158823262</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/85276/27...</td>\n",
       "      <td>115000</td>\n",
       "      <td>[{'id': 62}]</td>\n",
       "      <td>2021-02-05 11:31:41.277</td>\n",
       "      <td>Fantástico Piso en zona Simancas, Impecable, t...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>/es/comprar/vivienda/madrid-capital/aire-acond...</td>\n",
       "      <td>Calle de Zubieta, San Blas</td>\n",
       "      <td>España</td>\n",
       "      <td>...</td>\n",
       "      <td>28037</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/85276/27...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158823219</th>\n",
       "      <td>158823219</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/88669/27...</td>\n",
       "      <td>380000</td>\n",
       "      <td>[{'id': 3}]</td>\n",
       "      <td>2021-02-05 11:29:45.217</td>\n",
       "      <td>\"Piso inteio, muy tranquilo en el corazón del ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/es/comprar/vivienda/madrid-capital/aire-acond...</td>\n",
       "      <td>Calle del Conde de Peñalver, 30, Salamanca</td>\n",
       "      <td>España</td>\n",
       "      <td>...</td>\n",
       "      <td>28006</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/88669/27...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9280 rows × 39 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  id                                        multimedias  \\\n",
       "id                                                                        \n",
       "150476642  150476642  [{'url': 'https://d.inmofactory.com/1/100202/1...   \n",
       "157313689  157313689  [{'url': 'https://my.matterport.com/show/?m=fi...   \n",
       "153519540  153519540  [{'url': 'https://d.inmofactory.com/1/100207/1...   \n",
       "154298390  154298390  [{'url': 'https://images.inmofactory.com/inmof...   \n",
       "158184418  158184418  [{'url': 'https://d.inmofactory.com/1/89548/26...   \n",
       "...              ...                                                ...   \n",
       "158823456  158823456  [{'url': 'https://d.inmofactory.com/1/85276/27...   \n",
       "158823310  158823310  [{'url': 'https://d.inmofactory.com/1/85276/27...   \n",
       "158823307  158823307  [{'url': 'https://d.inmofactory.com/1/98925/27...   \n",
       "158823262  158823262  [{'url': 'https://d.inmofactory.com/1/85276/27...   \n",
       "158823219  158823219  [{'url': 'https://d.inmofactory.com/1/88669/27...   \n",
       "\n",
       "           transactions                  products                    date  \\\n",
       "id                                                                          \n",
       "150476642       2200000              [{'id': 56}] 2021-02-19 15:40:40.138   \n",
       "157313689        405000              [{'id': 56}] 2021-02-19 15:40:40.138   \n",
       "153519540       1930000   [{'id': 3}, {'id': 56}] 2021-02-19 15:40:40.138   \n",
       "154298390       1930000              [{'id': 56}] 2021-02-19 15:40:40.138   \n",
       "158184418        485000              [{'id': 56}] 2021-02-19 15:40:40.138   \n",
       "...                 ...                       ...                     ...   \n",
       "158823456        115000              [{'id': 62}] 2021-02-05 11:43:44.497   \n",
       "158823310        179000  [{'id': 62}, {'id': 56}] 2021-02-05 11:35:14.360   \n",
       "158823307        137000                        [] 2021-02-05 11:34:53.280   \n",
       "158823262        115000              [{'id': 62}] 2021-02-05 11:31:41.277   \n",
       "158823219        380000               [{'id': 3}] 2021-02-05 11:29:45.217   \n",
       "\n",
       "                                                 description  \\\n",
       "id                                                             \n",
       "150476642  GILMAR Consulting Inmobiliario Madrid, Conde O...   \n",
       "157313689  Gilmar ofrece, magnifica Vivienda, Ubicada en ...   \n",
       "153519540  Gilmar Mirasierra - Puerta de Hierro (91771777...   \n",
       "154298390  Gilmar Mirasierra - Puerta de Hierro (91771777...   \n",
       "158184418  Magnifica vivienda en Ciudad Jardín, \\r\\n\\r\\nP...   \n",
       "...                                                      ...   \n",
       "158823456  Piso para actualizar en Zona Hellín.\\r\\n\\r\\nFa...   \n",
       "158823310  Magnífico dúplex loft a dos alturas, totalment...   \n",
       "158823307  Luminosa vivienda de 56 m2, amplio salón con c...   \n",
       "158823262  Fantástico Piso en zona Simancas, Impecable, t...   \n",
       "158823219  \"Piso inteio, muy tranquilo en el corazón del ...   \n",
       "\n",
       "           advertiser.logo.multimedia.typeId  \\\n",
       "id                                             \n",
       "150476642                                8.0   \n",
       "157313689                                8.0   \n",
       "153519540                                8.0   \n",
       "154298390                                8.0   \n",
       "158184418                                8.0   \n",
       "...                                      ...   \n",
       "158823456                                8.0   \n",
       "158823310                                8.0   \n",
       "158823307                                8.0   \n",
       "158823262                                8.0   \n",
       "158823219                                NaN   \n",
       "\n",
       "                                                   detail.es  \\\n",
       "id                                                             \n",
       "150476642  /es/comprar/vivienda/madrid-capital/calefaccio...   \n",
       "157313689  /es/comprar/vivienda/madrid-capital/aire-acond...   \n",
       "153519540  /es/comprar/vivienda/madrid-capital/aire-acond...   \n",
       "154298390  /es/comprar/vivienda/madrid-capital/aire-acond...   \n",
       "158184418  /es/comprar/vivienda/madrid-capital/calefaccio...   \n",
       "...                                                      ...   \n",
       "158823456  /es/comprar/vivienda/madrid-capital/aire-acond...   \n",
       "158823310  /es/comprar/vivienda/madrid-capital/aire-acond...   \n",
       "158823307  /es/comprar/vivienda/madrid-capital/aire-acond...   \n",
       "158823262  /es/comprar/vivienda/madrid-capital/aire-acond...   \n",
       "158823219  /es/comprar/vivienda/madrid-capital/aire-acond...   \n",
       "\n",
       "                                           address.ubication  \\\n",
       "id                                                             \n",
       "150476642                               Andarrios, Hortaleza   \n",
       "157313689                                          Chamartín   \n",
       "153519540                                         Fuencarral   \n",
       "154298390                                         Fuencarral   \n",
       "158184418                                          Chamartín   \n",
       "...                                                      ...   \n",
       "158823456              Calle de Hinojosa del Duque, San Blas   \n",
       "158823310  Carretera de Vicálvaro a la Estac. O'donnell, ...   \n",
       "158823307                          Calle Garganchón, Barajas   \n",
       "158823262                         Calle de Zubieta, San Blas   \n",
       "158823219         Calle del Conde de Peñalver, 30, Salamanca   \n",
       "\n",
       "          address.location.country  ... address.zipCode bathrooms  \\\n",
       "id                                  ...                             \n",
       "150476642                   España  ...           28043       5.0   \n",
       "157313689                   España  ...           28002       1.0   \n",
       "153519540                   España  ...           28034       6.0   \n",
       "154298390                   España  ...           28034       6.0   \n",
       "158184418                   España  ...           28002       2.0   \n",
       "...                            ...  ...             ...       ...   \n",
       "158823456                   España  ...           28037       1.0   \n",
       "158823310                   España  ...           28032       2.0   \n",
       "158823307                   España  ...           28042       1.0   \n",
       "158823262                   España  ...           28037       1.0   \n",
       "158823219                   España  ...           28006       1.0   \n",
       "\n",
       "          conservationState elevator floor parking rooms  surface  terrace  \\\n",
       "id                                                                           \n",
       "150476642               2.0      NaN   NaN     NaN   5.0    554.0      1.0   \n",
       "157313689               3.0      1.0   7.0     NaN   3.0     80.0      NaN   \n",
       "153519540               1.0      NaN   NaN     NaN   5.0    547.0      1.0   \n",
       "154298390               1.0      NaN   NaN     NaN   5.0    547.0      1.0   \n",
       "158184418               4.0      1.0   8.0     NaN   4.0    133.0      NaN   \n",
       "...                     ...      ...   ...     ...   ...      ...      ...   \n",
       "158823456               4.0      NaN   6.0     NaN   3.0     62.0      NaN   \n",
       "158823310               NaN      1.0   6.0     NaN   2.0     83.0      1.0   \n",
       "158823307               3.0      NaN   6.0     NaN   1.0     56.0      NaN   \n",
       "158823262               1.0      NaN   NaN     NaN   2.0     48.0      NaN   \n",
       "158823219               2.0      1.0   6.0     NaN   2.0     90.0      NaN   \n",
       "\n",
       "                                                  multimedia  \n",
       "id                                                            \n",
       "150476642  [{'url': 'https://d.inmofactory.com/1/100202/1...  \n",
       "157313689  [{'url': 'https://my.matterport.com/show/?m=fi...  \n",
       "153519540  [{'url': 'https://d.inmofactory.com/1/100207/1...  \n",
       "154298390  [{'url': 'https://images.inmofactory.com/inmof...  \n",
       "158184418  [{'url': 'https://d.inmofactory.com/1/89548/26...  \n",
       "...                                                      ...  \n",
       "158823456  [{'url': 'https://d.inmofactory.com/1/85276/27...  \n",
       "158823310  [{'url': 'https://d.inmofactory.com/1/85276/27...  \n",
       "158823307  [{'url': 'https://d.inmofactory.com/1/98925/27...  \n",
       "158823262  [{'url': 'https://d.inmofactory.com/1/85276/27...  \n",
       "158823219  [{'url': 'https://d.inmofactory.com/1/88669/27...  \n",
       "\n",
       "[9280 rows x 39 columns]"
      ]
     },
     "execution_count": 292,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 293,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale.to_json('Madrid_salev1.json', orient='records')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 303,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale.rename(columns={'transactions':'price'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 305,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale.to_json('Madrid_salev1.json', orient='records')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 304,
   "metadata": {},
   "outputs": [
    {
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       "      <td>Gilmar ofrece, magnifica Vivienda, Ubicada en ...</td>\n",
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       "      <td>Madrid</td>\n",
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       "      <td>[{'url': 'https://d.inmofactory.com/1/100207/1...</td>\n",
       "      <td>1930000</td>\n",
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       "      <td>Gilmar Mirasierra - Puerta de Hierro (91771777...</td>\n",
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       "      <td>[{'url': 'https://d.inmofactory.com/1/85276/27...</td>\n",
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       "      <td>179000</td>\n",
       "      <td>2021-02-05 11:35:14.360</td>\n",
       "      <td>Magnífico dúplex loft a dos alturas, totalment...</td>\n",
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       "      <td>NaN</td>\n",
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       "      <th>158823262</th>\n",
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       "      <td>[{'url': 'https://d.inmofactory.com/1/85276/27...</td>\n",
       "      <td>115000</td>\n",
       "      <td>2021-02-05 11:31:41.277</td>\n",
       "      <td>Fantástico Piso en zona Simancas, Impecable, t...</td>\n",
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       "      <td>Madrid</td>\n",
       "      <td>Madrid</td>\n",
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       "      <td>28037</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>380000</td>\n",
       "      <td>2021-02-05 11:29:45.217</td>\n",
       "      <td>\"Piso inteio, muy tranquilo en el corazón del ...</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/88669/27...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9280 rows × 37 columns</p>\n",
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       "                  id                                        multimedias  \\\n",
       "id                                                                        \n",
       "150476642  150476642  [{'url': 'https://d.inmofactory.com/1/100202/1...   \n",
       "157313689  157313689  [{'url': 'https://my.matterport.com/show/?m=fi...   \n",
       "153519540  153519540  [{'url': 'https://d.inmofactory.com/1/100207/1...   \n",
       "154298390  154298390  [{'url': 'https://images.inmofactory.com/inmof...   \n",
       "158184418  158184418  [{'url': 'https://d.inmofactory.com/1/89548/26...   \n",
       "...              ...                                                ...   \n",
       "158823456  158823456  [{'url': 'https://d.inmofactory.com/1/85276/27...   \n",
       "158823310  158823310  [{'url': 'https://d.inmofactory.com/1/85276/27...   \n",
       "158823307  158823307  [{'url': 'https://d.inmofactory.com/1/98925/27...   \n",
       "158823262  158823262  [{'url': 'https://d.inmofactory.com/1/85276/27...   \n",
       "158823219  158823219  [{'url': 'https://d.inmofactory.com/1/88669/27...   \n",
       "\n",
       "             price                    date  \\\n",
       "id                                           \n",
       "150476642  2200000 2021-02-19 15:40:40.138   \n",
       "157313689   405000 2021-02-19 15:40:40.138   \n",
       "153519540  1930000 2021-02-19 15:40:40.138   \n",
       "154298390  1930000 2021-02-19 15:40:40.138   \n",
       "158184418   485000 2021-02-19 15:40:40.138   \n",
       "...            ...                     ...   \n",
       "158823456   115000 2021-02-05 11:43:44.497   \n",
       "158823310   179000 2021-02-05 11:35:14.360   \n",
       "158823307   137000 2021-02-05 11:34:53.280   \n",
       "158823262   115000 2021-02-05 11:31:41.277   \n",
       "158823219   380000 2021-02-05 11:29:45.217   \n",
       "\n",
       "                                                 description  \\\n",
       "id                                                             \n",
       "150476642  GILMAR Consulting Inmobiliario Madrid, Conde O...   \n",
       "157313689  Gilmar ofrece, magnifica Vivienda, Ubicada en ...   \n",
       "153519540  Gilmar Mirasierra - Puerta de Hierro (91771777...   \n",
       "154298390  Gilmar Mirasierra - Puerta de Hierro (91771777...   \n",
       "158184418  Magnifica vivienda en Ciudad Jardín, \\r\\n\\r\\nP...   \n",
       "...                                                      ...   \n",
       "158823456  Piso para actualizar en Zona Hellín.\\r\\n\\r\\nFa...   \n",
       "158823310  Magnífico dúplex loft a dos alturas, totalment...   \n",
       "158823307  Luminosa vivienda de 56 m2, amplio salón con c...   \n",
       "158823262  Fantástico Piso en zona Simancas, Impecable, t...   \n",
       "158823219  \"Piso inteio, muy tranquilo en el corazón del ...   \n",
       "\n",
       "                                                   detail.es  \\\n",
       "id                                                             \n",
       "150476642  /es/comprar/vivienda/madrid-capital/calefaccio...   \n",
       "157313689  /es/comprar/vivienda/madrid-capital/aire-acond...   \n",
       "153519540  /es/comprar/vivienda/madrid-capital/aire-acond...   \n",
       "154298390  /es/comprar/vivienda/madrid-capital/aire-acond...   \n",
       "158184418  /es/comprar/vivienda/madrid-capital/calefaccio...   \n",
       "...                                                      ...   \n",
       "158823456  /es/comprar/vivienda/madrid-capital/aire-acond...   \n",
       "158823310  /es/comprar/vivienda/madrid-capital/aire-acond...   \n",
       "158823307  /es/comprar/vivienda/madrid-capital/aire-acond...   \n",
       "158823262  /es/comprar/vivienda/madrid-capital/aire-acond...   \n",
       "158823219  /es/comprar/vivienda/madrid-capital/aire-acond...   \n",
       "\n",
       "                                           address.ubication  \\\n",
       "id                                                             \n",
       "150476642                               Andarrios, Hortaleza   \n",
       "157313689                                          Chamartín   \n",
       "153519540                                         Fuencarral   \n",
       "154298390                                         Fuencarral   \n",
       "158184418                                          Chamartín   \n",
       "...                                                      ...   \n",
       "158823456              Calle de Hinojosa del Duque, San Blas   \n",
       "158823310  Carretera de Vicálvaro a la Estac. O'donnell, ...   \n",
       "158823307                          Calle Garganchón, Barajas   \n",
       "158823262                         Calle de Zubieta, San Blas   \n",
       "158823219         Calle del Conde de Peñalver, 30, Salamanca   \n",
       "\n",
       "          address.location.country address.location.level1  \\\n",
       "id                                                           \n",
       "150476642                   España                  Madrid   \n",
       "157313689                   España                  Madrid   \n",
       "153519540                   España                  Madrid   \n",
       "154298390                   España                  Madrid   \n",
       "158184418                   España                  Madrid   \n",
       "...                            ...                     ...   \n",
       "158823456                   España                  Madrid   \n",
       "158823310                   España                  Madrid   \n",
       "158823307                   España                  Madrid   \n",
       "158823262                   España                  Madrid   \n",
       "158823219                   España                  Madrid   \n",
       "\n",
       "          address.location.level2  ... address.zipCode bathrooms  \\\n",
       "id                                 ...                             \n",
       "150476642                  Madrid  ...           28043       5.0   \n",
       "157313689                  Madrid  ...           28002       1.0   \n",
       "153519540                  Madrid  ...           28034       6.0   \n",
       "154298390                  Madrid  ...           28034       6.0   \n",
       "158184418                  Madrid  ...           28002       2.0   \n",
       "...                           ...  ...             ...       ...   \n",
       "158823456                  Madrid  ...           28037       1.0   \n",
       "158823310                  Madrid  ...           28032       2.0   \n",
       "158823307                  Madrid  ...           28042       1.0   \n",
       "158823262                  Madrid  ...           28037       1.0   \n",
       "158823219                  Madrid  ...           28006       1.0   \n",
       "\n",
       "          conservationState elevator floor  parking  rooms  surface  terrace  \\\n",
       "id                                                                             \n",
       "150476642               2.0      NaN   NaN      NaN    5.0    554.0      1.0   \n",
       "157313689               3.0      1.0   7.0      NaN    3.0     80.0      NaN   \n",
       "153519540               1.0      NaN   NaN      NaN    5.0    547.0      1.0   \n",
       "154298390               1.0      NaN   NaN      NaN    5.0    547.0      1.0   \n",
       "158184418               4.0      1.0   8.0      NaN    4.0    133.0      NaN   \n",
       "...                     ...      ...   ...      ...    ...      ...      ...   \n",
       "158823456               4.0      NaN   6.0      NaN    3.0     62.0      NaN   \n",
       "158823310               NaN      1.0   6.0      NaN    2.0     83.0      1.0   \n",
       "158823307               3.0      NaN   6.0      NaN    1.0     56.0      NaN   \n",
       "158823262               1.0      NaN   NaN      NaN    2.0     48.0      NaN   \n",
       "158823219               2.0      1.0   6.0      NaN    2.0     90.0      NaN   \n",
       "\n",
       "                                                  multimedia  \n",
       "id                                                            \n",
       "150476642  [{'url': 'https://d.inmofactory.com/1/100202/1...  \n",
       "157313689  [{'url': 'https://my.matterport.com/show/?m=fi...  \n",
       "153519540  [{'url': 'https://d.inmofactory.com/1/100207/1...  \n",
       "154298390  [{'url': 'https://images.inmofactory.com/inmof...  \n",
       "158184418  [{'url': 'https://d.inmofactory.com/1/89548/26...  \n",
       "...                                                      ...  \n",
       "158823456  [{'url': 'https://d.inmofactory.com/1/85276/27...  \n",
       "158823310  [{'url': 'https://d.inmofactory.com/1/85276/27...  \n",
       "158823307  [{'url': 'https://d.inmofactory.com/1/98925/27...  \n",
       "158823262  [{'url': 'https://d.inmofactory.com/1/85276/27...  \n",
       "158823219  [{'url': 'https://d.inmofactory.com/1/88669/27...  \n",
       "\n",
       "[9280 rows x 37 columns]"
      ]
     },
     "execution_count": 304,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sale"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Column - Detail.es"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 306,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale.to_json('Madrid_salev1.json', orient='records')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "price['value'] = price['value'].map(lambda x: str(x).strip('[]'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 311,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale['detail.es'] = sale['detail.es'].map(lambda x: x.strip('/es/comprar/vivienda/madrid-capital/'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 313,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>multimedias</th>\n",
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       "      <td>405000</td>\n",
       "      <td>2021-02-19 15:40:40.138</td>\n",
       "      <td>Gilmar ofrece, magnifica Vivienda, Ubicada en ...</td>\n",
       "      <td>faccion-parking-ascensor/157313689</td>\n",
       "      <td>Chamartín</td>\n",
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       "      <td>Madrid</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>...</td>\n",
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       "      <td>[{'url': 'https://d.inmofactory.com/1/100207/1...</td>\n",
       "      <td>1930000</td>\n",
       "      <td>2021-02-19 15:40:40.138</td>\n",
       "      <td>Gilmar Mirasierra - Puerta de Hierro (91771777...</td>\n",
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       "      <td>1930000</td>\n",
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       "      <td>Gilmar Mirasierra - Puerta de Hierro (91771777...</td>\n",
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       "      <th>158184418</th>\n",
       "      <td>158184418</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/89548/26...</td>\n",
       "      <td>485000</td>\n",
       "      <td>2021-02-19 15:40:40.138</td>\n",
       "      <td>Magnifica vivienda en Ciudad Jardín, \\r\\n\\r\\nP...</td>\n",
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       "      <th>158823456</th>\n",
       "      <td>158823456</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/85276/27...</td>\n",
       "      <td>115000</td>\n",
       "      <td>2021-02-05 11:43:44.497</td>\n",
       "      <td>Piso para actualizar en Zona Hellín.\\r\\n\\r\\nFa...</td>\n",
       "      <td>faccion/158823456</td>\n",
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       "      <td>Madrid</td>\n",
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       "      <td>NaN</td>\n",
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       "      <th>158823310</th>\n",
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       "      <td>179000</td>\n",
       "      <td>2021-02-05 11:35:14.360</td>\n",
       "      <td>Magnífico dúplex loft a dos alturas, totalment...</td>\n",
       "      <td>faccion-parking-terraza-ascensor-amueblado/158...</td>\n",
       "      <td>Carretera de Vicálvaro a la Estac. O'donnell, ...</td>\n",
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       "      <td>Madrid</td>\n",
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       "      <td>28032</td>\n",
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       "      <td>83.0</td>\n",
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       "    <tr>\n",
       "      <th>158823307</th>\n",
       "      <td>158823307</td>\n",
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       "      <td>137000</td>\n",
       "      <td>2021-02-05 11:34:53.280</td>\n",
       "      <td>Luminosa vivienda de 56 m2, amplio salón con c...</td>\n",
       "      <td>faccion-amueblado/158823307</td>\n",
       "      <td>Calle Garganchón, Barajas</td>\n",
       "      <td>España</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>...</td>\n",
       "      <td>28042</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/98925/27...</td>\n",
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       "    <tr>\n",
       "      <th>158823262</th>\n",
       "      <td>158823262</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/85276/27...</td>\n",
       "      <td>115000</td>\n",
       "      <td>2021-02-05 11:31:41.277</td>\n",
       "      <td>Fantástico Piso en zona Simancas, Impecable, t...</td>\n",
       "      <td>faccion-no-amueblado/158823262</td>\n",
       "      <td>Calle de Zubieta, San Blas</td>\n",
       "      <td>España</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>...</td>\n",
       "      <td>28037</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/85276/27...</td>\n",
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       "      <td>380000</td>\n",
       "      <td>2021-02-05 11:29:45.217</td>\n",
       "      <td>\"Piso inteio, muy tranquilo en el corazón del ...</td>\n",
       "      <td>faccion-ascensor-patio-amueblado/158823219</td>\n",
       "      <td>Calle del Conde de Peñalver, 30, Salamanca</td>\n",
       "      <td>España</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>...</td>\n",
       "      <td>28006</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/88669/27...</td>\n",
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       "  </tbody>\n",
       "</table>\n",
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       "                  id                                        multimedias  \\\n",
       "id                                                                        \n",
       "150476642  150476642  [{'url': 'https://d.inmofactory.com/1/100202/1...   \n",
       "157313689  157313689  [{'url': 'https://my.matterport.com/show/?m=fi...   \n",
       "153519540  153519540  [{'url': 'https://d.inmofactory.com/1/100207/1...   \n",
       "154298390  154298390  [{'url': 'https://images.inmofactory.com/inmof...   \n",
       "158184418  158184418  [{'url': 'https://d.inmofactory.com/1/89548/26...   \n",
       "...              ...                                                ...   \n",
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       "158823310  158823310  [{'url': 'https://d.inmofactory.com/1/85276/27...   \n",
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       "158823262  158823262  [{'url': 'https://d.inmofactory.com/1/85276/27...   \n",
       "158823219  158823219  [{'url': 'https://d.inmofactory.com/1/88669/27...   \n",
       "\n",
       "             price                    date  \\\n",
       "id                                           \n",
       "150476642  2200000 2021-02-19 15:40:40.138   \n",
       "157313689   405000 2021-02-19 15:40:40.138   \n",
       "153519540  1930000 2021-02-19 15:40:40.138   \n",
       "154298390  1930000 2021-02-19 15:40:40.138   \n",
       "158184418   485000 2021-02-19 15:40:40.138   \n",
       "...            ...                     ...   \n",
       "158823456   115000 2021-02-05 11:43:44.497   \n",
       "158823310   179000 2021-02-05 11:35:14.360   \n",
       "158823307   137000 2021-02-05 11:34:53.280   \n",
       "158823262   115000 2021-02-05 11:31:41.277   \n",
       "158823219   380000 2021-02-05 11:29:45.217   \n",
       "\n",
       "                                                 description  \\\n",
       "id                                                             \n",
       "150476642  GILMAR Consulting Inmobiliario Madrid, Conde O...   \n",
       "157313689  Gilmar ofrece, magnifica Vivienda, Ubicada en ...   \n",
       "153519540  Gilmar Mirasierra - Puerta de Hierro (91771777...   \n",
       "154298390  Gilmar Mirasierra - Puerta de Hierro (91771777...   \n",
       "158184418  Magnifica vivienda en Ciudad Jardín, \\r\\n\\r\\nP...   \n",
       "...                                                      ...   \n",
       "158823456  Piso para actualizar en Zona Hellín.\\r\\n\\r\\nFa...   \n",
       "158823310  Magnífico dúplex loft a dos alturas, totalment...   \n",
       "158823307  Luminosa vivienda de 56 m2, amplio salón con c...   \n",
       "158823262  Fantástico Piso en zona Simancas, Impecable, t...   \n",
       "158823219  \"Piso inteio, muy tranquilo en el corazón del ...   \n",
       "\n",
       "                                                   detail.es  \\\n",
       "id                                                             \n",
       "150476642  faccion-jardin-terraza-trastero-patio-piscina/...   \n",
       "157313689                 faccion-parking-ascensor/157313689   \n",
       "153519540     king-jardin-terraza-trastero-piscina/153519540   \n",
       "154298390     king-jardin-terraza-trastero-piscina/154298390   \n",
       "158184418                         faccion-ascensor/158184418   \n",
       "...                                                      ...   \n",
       "158823456                                  faccion/158823456   \n",
       "158823310  faccion-parking-terraza-ascensor-amueblado/158...   \n",
       "158823307                        faccion-amueblado/158823307   \n",
       "158823262                     faccion-no-amueblado/158823262   \n",
       "158823219         faccion-ascensor-patio-amueblado/158823219   \n",
       "\n",
       "                                           address.ubication  \\\n",
       "id                                                             \n",
       "150476642                               Andarrios, Hortaleza   \n",
       "157313689                                          Chamartín   \n",
       "153519540                                         Fuencarral   \n",
       "154298390                                         Fuencarral   \n",
       "158184418                                          Chamartín   \n",
       "...                                                      ...   \n",
       "158823456              Calle de Hinojosa del Duque, San Blas   \n",
       "158823310  Carretera de Vicálvaro a la Estac. O'donnell, ...   \n",
       "158823307                          Calle Garganchón, Barajas   \n",
       "158823262                         Calle de Zubieta, San Blas   \n",
       "158823219         Calle del Conde de Peñalver, 30, Salamanca   \n",
       "\n",
       "          address.location.country address.location.level1  \\\n",
       "id                                                           \n",
       "150476642                   España                  Madrid   \n",
       "157313689                   España                  Madrid   \n",
       "153519540                   España                  Madrid   \n",
       "154298390                   España                  Madrid   \n",
       "158184418                   España                  Madrid   \n",
       "...                            ...                     ...   \n",
       "158823456                   España                  Madrid   \n",
       "158823310                   España                  Madrid   \n",
       "158823307                   España                  Madrid   \n",
       "158823262                   España                  Madrid   \n",
       "158823219                   España                  Madrid   \n",
       "\n",
       "          address.location.level2  ... address.zipCode bathrooms  \\\n",
       "id                                 ...                             \n",
       "150476642                  Madrid  ...           28043       5.0   \n",
       "157313689                  Madrid  ...           28002       1.0   \n",
       "153519540                  Madrid  ...           28034       6.0   \n",
       "154298390                  Madrid  ...           28034       6.0   \n",
       "158184418                  Madrid  ...           28002       2.0   \n",
       "...                           ...  ...             ...       ...   \n",
       "158823456                  Madrid  ...           28037       1.0   \n",
       "158823310                  Madrid  ...           28032       2.0   \n",
       "158823307                  Madrid  ...           28042       1.0   \n",
       "158823262                  Madrid  ...           28037       1.0   \n",
       "158823219                  Madrid  ...           28006       1.0   \n",
       "\n",
       "          conservationState elevator floor  parking  rooms  surface  terrace  \\\n",
       "id                                                                             \n",
       "150476642               2.0      NaN   NaN      NaN    5.0    554.0      1.0   \n",
       "157313689               3.0      1.0   7.0      NaN    3.0     80.0      NaN   \n",
       "153519540               1.0      NaN   NaN      NaN    5.0    547.0      1.0   \n",
       "154298390               1.0      NaN   NaN      NaN    5.0    547.0      1.0   \n",
       "158184418               4.0      1.0   8.0      NaN    4.0    133.0      NaN   \n",
       "...                     ...      ...   ...      ...    ...      ...      ...   \n",
       "158823456               4.0      NaN   6.0      NaN    3.0     62.0      NaN   \n",
       "158823310               NaN      1.0   6.0      NaN    2.0     83.0      1.0   \n",
       "158823307               3.0      NaN   6.0      NaN    1.0     56.0      NaN   \n",
       "158823262               1.0      NaN   NaN      NaN    2.0     48.0      NaN   \n",
       "158823219               2.0      1.0   6.0      NaN    2.0     90.0      NaN   \n",
       "\n",
       "                                                  multimedia  \n",
       "id                                                            \n",
       "150476642  [{'url': 'https://d.inmofactory.com/1/100202/1...  \n",
       "157313689  [{'url': 'https://my.matterport.com/show/?m=fi...  \n",
       "153519540  [{'url': 'https://d.inmofactory.com/1/100207/1...  \n",
       "154298390  [{'url': 'https://images.inmofactory.com/inmof...  \n",
       "158184418  [{'url': 'https://d.inmofactory.com/1/89548/26...  \n",
       "...                                                      ...  \n",
       "158823456  [{'url': 'https://d.inmofactory.com/1/85276/27...  \n",
       "158823310  [{'url': 'https://d.inmofactory.com/1/85276/27...  \n",
       "158823307  [{'url': 'https://d.inmofactory.com/1/98925/27...  \n",
       "158823262  [{'url': 'https://d.inmofactory.com/1/85276/27...  \n",
       "158823219  [{'url': 'https://d.inmofactory.com/1/88669/27...  \n",
       "\n",
       "[9280 rows x 37 columns]"
      ]
     },
     "execution_count": 313,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 315,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale = sale.drop(['multimedias'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 343,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale = sale.drop(['address.location.level2'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 330,
   "metadata": {},
   "outputs": [],
   "source": [
    "zona = sale['address.location.level3'].apply(pd.Series)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 396,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale = sale.drop(['address.location.level8Id'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 382,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['id', 'price', 'date', 'customer_description', 'short_detail',\n",
       "       'address', 'country', 'neighborhood', 'district',\n",
       "       'address.location.level5Id', 'address.location.level7Id',\n",
       "       'address.location.level8Id', 'address.coordinates.accuracy',\n",
       "       'address.coordinates.latitude', 'address.coordinates.longitude',\n",
       "       'address.zipCode', 'bathrooms', 'conservationState', 'elevator',\n",
       "       'floor', 'parking', 'rooms', 'surface', 'terrace', 'multimedia'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 382,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sale.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 410,
   "metadata": {},
   "outputs": [],
   "source": [
    "cols = ['id', 'price', 'publish_date', 'customer_description', 'short_detail',\n",
    "       'address', 'country', 'neighborhood', 'district',\n",
    "       'coordinates.accuracy', 'coordinates.latitude',\n",
    "       'coordinates.longitude', 'zipCode', 'bathrooms', 'conservationState',\n",
    "       'elevator', 'floor', 'parking', 'rooms', 'surface', 'terrace',\n",
    "       'multimedia']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 411,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['id', 'price', 'date', 'customer_description', 'short_detail',\n",
       "       'address', 'country', 'neighborhood', 'district',\n",
       "       'address.coordinates.accuracy', 'coordinates.latitude',\n",
       "       'coordinates.longitude', 'zipCode', 'bathrooms', 'conservationState',\n",
       "       'elevator', 'floor', 'parking', 'rooms', 'surface', 'terrace',\n",
       "       'multimedia'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 411,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sale.columns "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 412,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>price</th>\n",
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       "      <th>customer_description</th>\n",
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       "      <th>multimedia</th>\n",
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       "    <tr>\n",
       "      <th>id</th>\n",
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       "    <tr>\n",
       "      <th>150476642</th>\n",
       "      <td>150476642</td>\n",
       "      <td>2200000</td>\n",
       "      <td>2021-02-19 15:40:40.138</td>\n",
       "      <td>GILMAR Consulting Inmobiliario Madrid, Conde O...</td>\n",
       "      <td>faccion-jardin-terraza-trastero-patio-piscina/...</td>\n",
       "      <td>Andarrios, Hortaleza</td>\n",
       "      <td>España</td>\n",
       "      <td>Hortaleza</td>\n",
       "      <td>Conde Orgaz - Piovera</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>28043</td>\n",
       "      <td>5.0</td>\n",
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       "    <tr>\n",
       "      <th>157313689</th>\n",
       "      <td>157313689</td>\n",
       "      <td>405000</td>\n",
       "      <td>2021-02-19 15:40:40.138</td>\n",
       "      <td>Gilmar ofrece, magnifica Vivienda, Ubicada en ...</td>\n",
       "      <td>faccion-parking-ascensor/157313689</td>\n",
       "      <td>Chamartín</td>\n",
       "      <td>España</td>\n",
       "      <td>Chamartín</td>\n",
       "      <td>Prosperidad</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>28002</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'url': 'https://my.matterport.com/show/?m=fi...</td>\n",
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       "      <th>153519540</th>\n",
       "      <td>153519540</td>\n",
       "      <td>1930000</td>\n",
       "      <td>2021-02-19 15:40:40.138</td>\n",
       "      <td>Gilmar Mirasierra - Puerta de Hierro (91771777...</td>\n",
       "      <td>king-jardin-terraza-trastero-piscina/153519540</td>\n",
       "      <td>Fuencarral</td>\n",
       "      <td>España</td>\n",
       "      <td>Fuencarral</td>\n",
       "      <td>Tres Olivos - Valverde</td>\n",
       "      <td>0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>547.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/100207/1...</td>\n",
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       "    <tr>\n",
       "      <th>154298390</th>\n",
       "      <td>154298390</td>\n",
       "      <td>1930000</td>\n",
       "      <td>2021-02-19 15:40:40.138</td>\n",
       "      <td>Gilmar Mirasierra - Puerta de Hierro (91771777...</td>\n",
       "      <td>king-jardin-terraza-trastero-piscina/154298390</td>\n",
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       "      <th>158184418</th>\n",
       "      <td>158184418</td>\n",
       "      <td>485000</td>\n",
       "      <td>2021-02-19 15:40:40.138</td>\n",
       "      <td>Magnifica vivienda en Ciudad Jardín, \\r\\n\\r\\nP...</td>\n",
       "      <td>faccion-ascensor/158184418</td>\n",
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       "      <td>Ciudad Jardín</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>4.0</td>\n",
       "      <td>133.0</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>158823456</th>\n",
       "      <td>158823456</td>\n",
       "      <td>115000</td>\n",
       "      <td>2021-02-05 11:43:44.497</td>\n",
       "      <td>Piso para actualizar en Zona Hellín.\\r\\n\\r\\nFa...</td>\n",
       "      <td>faccion/158823456</td>\n",
       "      <td>Calle de Hinojosa del Duque, San Blas</td>\n",
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       "      <td>62.0</td>\n",
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       "      <td>179000</td>\n",
       "      <td>2021-02-05 11:35:14.360</td>\n",
       "      <td>Magnífico dúplex loft a dos alturas, totalment...</td>\n",
       "      <td>faccion-parking-terraza-ascensor-amueblado/158...</td>\n",
       "      <td>Carretera de Vicálvaro a la Estac. O'donnell, ...</td>\n",
       "      <td>España</td>\n",
       "      <td>San Blas</td>\n",
       "      <td>Rosas - Musas</td>\n",
       "      <td>0</td>\n",
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       "      <td>83.0</td>\n",
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       "      <td>158823307</td>\n",
       "      <td>137000</td>\n",
       "      <td>2021-02-05 11:34:53.280</td>\n",
       "      <td>Luminosa vivienda de 56 m2, amplio salón con c...</td>\n",
       "      <td>faccion-amueblado/158823307</td>\n",
       "      <td>Calle Garganchón, Barajas</td>\n",
       "      <td>España</td>\n",
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       "      <td>Aeropuerto</td>\n",
       "      <td>0</td>\n",
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       "      <td>28042</td>\n",
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       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/98925/27...</td>\n",
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       "    <tr>\n",
       "      <th>158823262</th>\n",
       "      <td>158823262</td>\n",
       "      <td>115000</td>\n",
       "      <td>2021-02-05 11:31:41.277</td>\n",
       "      <td>Fantástico Piso en zona Simancas, Impecable, t...</td>\n",
       "      <td>faccion-no-amueblado/158823262</td>\n",
       "      <td>Calle de Zubieta, San Blas</td>\n",
       "      <td>España</td>\n",
       "      <td>San Blas</td>\n",
       "      <td>Simancas</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>28037</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/85276/27...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158823219</th>\n",
       "      <td>158823219</td>\n",
       "      <td>380000</td>\n",
       "      <td>2021-02-05 11:29:45.217</td>\n",
       "      <td>\"Piso inteio, muy tranquilo en el corazón del ...</td>\n",
       "      <td>faccion-ascensor-patio-amueblado/158823219</td>\n",
       "      <td>Calle del Conde de Peñalver, 30, Salamanca</td>\n",
       "      <td>España</td>\n",
       "      <td>Salamanca</td>\n",
       "      <td>Goya</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>28006</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/88669/27...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9280 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  id    price                    date  \\\n",
       "id                                                      \n",
       "150476642  150476642  2200000 2021-02-19 15:40:40.138   \n",
       "157313689  157313689   405000 2021-02-19 15:40:40.138   \n",
       "153519540  153519540  1930000 2021-02-19 15:40:40.138   \n",
       "154298390  154298390  1930000 2021-02-19 15:40:40.138   \n",
       "158184418  158184418   485000 2021-02-19 15:40:40.138   \n",
       "...              ...      ...                     ...   \n",
       "158823456  158823456   115000 2021-02-05 11:43:44.497   \n",
       "158823310  158823310   179000 2021-02-05 11:35:14.360   \n",
       "158823307  158823307   137000 2021-02-05 11:34:53.280   \n",
       "158823262  158823262   115000 2021-02-05 11:31:41.277   \n",
       "158823219  158823219   380000 2021-02-05 11:29:45.217   \n",
       "\n",
       "                                        customer_description  \\\n",
       "id                                                             \n",
       "150476642  GILMAR Consulting Inmobiliario Madrid, Conde O...   \n",
       "157313689  Gilmar ofrece, magnifica Vivienda, Ubicada en ...   \n",
       "153519540  Gilmar Mirasierra - Puerta de Hierro (91771777...   \n",
       "154298390  Gilmar Mirasierra - Puerta de Hierro (91771777...   \n",
       "158184418  Magnifica vivienda en Ciudad Jardín, \\r\\n\\r\\nP...   \n",
       "...                                                      ...   \n",
       "158823456  Piso para actualizar en Zona Hellín.\\r\\n\\r\\nFa...   \n",
       "158823310  Magnífico dúplex loft a dos alturas, totalment...   \n",
       "158823307  Luminosa vivienda de 56 m2, amplio salón con c...   \n",
       "158823262  Fantástico Piso en zona Simancas, Impecable, t...   \n",
       "158823219  \"Piso inteio, muy tranquilo en el corazón del ...   \n",
       "\n",
       "                                                short_detail  \\\n",
       "id                                                             \n",
       "150476642  faccion-jardin-terraza-trastero-patio-piscina/...   \n",
       "157313689                 faccion-parking-ascensor/157313689   \n",
       "153519540     king-jardin-terraza-trastero-piscina/153519540   \n",
       "154298390     king-jardin-terraza-trastero-piscina/154298390   \n",
       "158184418                         faccion-ascensor/158184418   \n",
       "...                                                      ...   \n",
       "158823456                                  faccion/158823456   \n",
       "158823310  faccion-parking-terraza-ascensor-amueblado/158...   \n",
       "158823307                        faccion-amueblado/158823307   \n",
       "158823262                     faccion-no-amueblado/158823262   \n",
       "158823219         faccion-ascensor-patio-amueblado/158823219   \n",
       "\n",
       "                                                     address country  \\\n",
       "id                                                                     \n",
       "150476642                               Andarrios, Hortaleza  España   \n",
       "157313689                                          Chamartín  España   \n",
       "153519540                                         Fuencarral  España   \n",
       "154298390                                         Fuencarral  España   \n",
       "158184418                                          Chamartín  España   \n",
       "...                                                      ...     ...   \n",
       "158823456              Calle de Hinojosa del Duque, San Blas  España   \n",
       "158823310  Carretera de Vicálvaro a la Estac. O'donnell, ...  España   \n",
       "158823307                          Calle Garganchón, Barajas  España   \n",
       "158823262                         Calle de Zubieta, San Blas  España   \n",
       "158823219         Calle del Conde de Peñalver, 30, Salamanca  España   \n",
       "\n",
       "          neighborhood                district  address.coordinates.accuracy  \\\n",
       "id                                                                             \n",
       "150476642    Hortaleza   Conde Orgaz - Piovera                             0   \n",
       "157313689    Chamartín             Prosperidad                             0   \n",
       "153519540   Fuencarral  Tres Olivos - Valverde                             0   \n",
       "154298390   Fuencarral  Tres Olivos - Valverde                             0   \n",
       "158184418    Chamartín           Ciudad Jardín                             0   \n",
       "...                ...                     ...                           ...   \n",
       "158823456     San Blas                  Hellín                             0   \n",
       "158823310     San Blas           Rosas - Musas                             0   \n",
       "158823307      Barajas              Aeropuerto                             0   \n",
       "158823262     San Blas                Simancas                             0   \n",
       "158823219    Salamanca                    Goya                             1   \n",
       "\n",
       "           ...  zipCode  bathrooms conservationState  elevator  floor  \\\n",
       "id         ...                                                          \n",
       "150476642  ...    28043        5.0               2.0       NaN    NaN   \n",
       "157313689  ...    28002        1.0               3.0       1.0    7.0   \n",
       "153519540  ...    28034        6.0               1.0       NaN    NaN   \n",
       "154298390  ...    28034        6.0               1.0       NaN    NaN   \n",
       "158184418  ...    28002        2.0               4.0       1.0    8.0   \n",
       "...        ...      ...        ...               ...       ...    ...   \n",
       "158823456  ...    28037        1.0               4.0       NaN    6.0   \n",
       "158823310  ...    28032        2.0               NaN       1.0    6.0   \n",
       "158823307  ...    28042        1.0               3.0       NaN    6.0   \n",
       "158823262  ...    28037        1.0               1.0       NaN    NaN   \n",
       "158823219  ...    28006        1.0               2.0       1.0    6.0   \n",
       "\n",
       "           parking  rooms  surface  terrace  \\\n",
       "id                                            \n",
       "150476642      NaN    5.0    554.0      1.0   \n",
       "157313689      NaN    3.0     80.0      NaN   \n",
       "153519540      NaN    5.0    547.0      1.0   \n",
       "154298390      NaN    5.0    547.0      1.0   \n",
       "158184418      NaN    4.0    133.0      NaN   \n",
       "...            ...    ...      ...      ...   \n",
       "158823456      NaN    3.0     62.0      NaN   \n",
       "158823310      NaN    2.0     83.0      1.0   \n",
       "158823307      NaN    1.0     56.0      NaN   \n",
       "158823262      NaN    2.0     48.0      NaN   \n",
       "158823219      NaN    2.0     90.0      NaN   \n",
       "\n",
       "                                                  multimedia  \n",
       "id                                                            \n",
       "150476642  [{'url': 'https://d.inmofactory.com/1/100202/1...  \n",
       "157313689  [{'url': 'https://my.matterport.com/show/?m=fi...  \n",
       "153519540  [{'url': 'https://d.inmofactory.com/1/100207/1...  \n",
       "154298390  [{'url': 'https://images.inmofactory.com/inmof...  \n",
       "158184418  [{'url': 'https://d.inmofactory.com/1/89548/26...  \n",
       "...                                                      ...  \n",
       "158823456  [{'url': 'https://d.inmofactory.com/1/85276/27...  \n",
       "158823310  [{'url': 'https://d.inmofactory.com/1/85276/27...  \n",
       "158823307  [{'url': 'https://d.inmofactory.com/1/98925/27...  \n",
       "158823262  [{'url': 'https://d.inmofactory.com/1/85276/27...  \n",
       "158823219  [{'url': 'https://d.inmofactory.com/1/88669/27...  \n",
       "\n",
       "[9280 rows x 22 columns]"
      ]
     },
     "execution_count": 412,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 405,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(9280,)"
      ]
     },
     "execution_count": 405,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sale['address.coordinates.accuracy']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 366,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale.to_json('Madrid_salev1.json', orient='records')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## New_Column Price m2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 419,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale['Price_m2'] = round(sale['price']/sale['surface'], 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 426,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale.Price_m2.colanme"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 428,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale.rename(columns={'Price_m2':'price_m2'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 430,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 9280 entries, 150476642 to 158823219\n",
      "Data columns (total 23 columns):\n",
      " #   Column                        Non-Null Count  Dtype         \n",
      "---  ------                        --------------  -----         \n",
      " 0   id                            9280 non-null   int64         \n",
      " 1   price                         9280 non-null   int64         \n",
      " 2   date                          9280 non-null   datetime64[ns]\n",
      " 3   customer_description          9233 non-null   object        \n",
      " 4   short_detail                  9280 non-null   object        \n",
      " 5   address                       9280 non-null   object        \n",
      " 6   country                       9280 non-null   object        \n",
      " 7   neighborhood                  9280 non-null   object        \n",
      " 8   district                      9280 non-null   object        \n",
      " 9   address.coordinates.accuracy  9280 non-null   int64         \n",
      " 10  coordinates.latitude          9280 non-null   float64       \n",
      " 11  coordinates.longitude         9280 non-null   float64       \n",
      " 12  zipCode                       9280 non-null   object        \n",
      " 13  bathrooms                     9134 non-null   float64       \n",
      " 14  conservationState             4820 non-null   float64       \n",
      " 15  elevator                      5632 non-null   float64       \n",
      " 16  floor                         6507 non-null   float64       \n",
      " 17  parking                       887 non-null    float64       \n",
      " 18  rooms                         8995 non-null   float64       \n",
      " 19  surface                       9257 non-null   float64       \n",
      " 20  terrace                       3181 non-null   float64       \n",
      " 21  multimedia                    9280 non-null   object        \n",
      " 22  price_m2                      9257 non-null   float64       \n",
      "dtypes: datetime64[ns](1), float64(11), int64(3), object(8)\n",
      "memory usage: 2.0+ MB\n"
     ]
    }
   ],
   "source": [
    "sale.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 434,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale.to_json('Madrid_salev1.json', orient='records')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 445,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale['customer_description'] = sale['customer_description'].apply(lambda x : str(x).strip('\\r\\n\\r\\n'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 447,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Gilmar ofrece, magnifica Vivienda, Ubicada en Prosperidad, zona norte de Madrid. Piso exterior, con una superficie construida de 80 m2 catastrales, 71 m2 útiles, distribuidos en: Hall de entrada espacioso, 3 buenos Dormitorios, 1 Cuarto de baño completo, salón-comedor, cocina independiente y equipada. Dispone de Calefacción Central, suelos de Tarima. 4 armarios empotrados, puerta de seguridad.\\r\\n\\r\\nLa finca dispone de portero físico, acceso a personas con movilidad reducida.\\r\\n\\r\\nEl barrio ya consolidado y excelentemente comunicado cuenta con zonas deportivas, colegios, iglesias, guarderías, gran oferta de restaurantes, terrazas, pequeño comercio y supermercados, así como parques y amplias zonas verdes. Con acceso directo a la M-30, que comunica tanto al resto de la red arterial como al aeropuerto, Igualmente cercano se encuentra el intercambiador de autobuses de la Avda. de América y las líneas de autobuses de la EMT números: 9, 40, 72, 73, 120,43 y cercana la estación de metro Alfonso XIII.\"\\r\\n\\r\\nComercializa Consulting Inmobiliario Gilmar Avenida America 91 771 77 99.\\r\\n\\r\\nEl Barrio de Prosperidad, Chamartín es una de las zonas más demandadas del distrito por su gran ambiente familiar y multitud de servicios, sin abandonar el entorno de zonas verdes por el que se caracteriza este distinguido distrito. Chamartín. Dispone de una gran variedad de zonas de ocio como el Auditorio Nacional de Música o el Parque de Berlín. Las necesidades básicas familiares, están totalmente cubiertas por diversidad de comercios, tiendas tradicionales, galerías comerciales con los productos más frescos e incluso famosos supermercados de grandes superficies. La arquitectura por la que se rodea la zona ronda desde edificios clásicos hasta algunos de los edificios más modernos de la capital como el IBM o el Hotel Silken Puerta de América. \\r\\n\\r\\nLa zona es conocida también por sus centros educativos. Colegios públicos dentro de los mejores catalogados, así como gran variedad de colegios privados bilingües y de gran relevancia. Todo, sin olvidarse de universidades tan conocidas como la escuela universitaria de diseño, innovación y tecnología ESNE.\\r\\n\\r\\nExiste también en la zona, el polideportivo municipal “El Pradillo”, para practicar todo tipo de deportes, en cualquier época del año.\\r\\n\\r\\nLa red de transporte público de la zona garantiza gran comodidad al contar con las paradas de metro de Prosperidad, Cartagena, Alfonso XIII y a un paseo del intercambiador de Avenida de América que cuenta con multitud de conexiones con líneas de autobús (40,43,72,9) Asimismo, dispone de un rápido acceso a algunas de las carreteras más destacadas de Madrid como la M30 y A2, que le conducirán en pocos minutos al aeropuerto.'"
      ]
     },
     "execution_count": 447,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sale['customer_description'].values[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 449,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale.to_json('Madrid_salev1.json', orient='records')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## To SQL >>>>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale = pd.read_json('Madrid_salev1.json', orient='records')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>id</th>\n",
       "      <th>price</th>\n",
       "      <th>date</th>\n",
       "      <th>customer_description</th>\n",
       "      <th>short_detail</th>\n",
       "      <th>address</th>\n",
       "      <th>country</th>\n",
       "      <th>neighborhood</th>\n",
       "      <th>district</th>\n",
       "      <th>address.coordinates.accuracy</th>\n",
       "      <th>...</th>\n",
       "      <th>bathrooms</th>\n",
       "      <th>conservationState</th>\n",
       "      <th>elevator</th>\n",
       "      <th>floor</th>\n",
       "      <th>parking</th>\n",
       "      <th>rooms</th>\n",
       "      <th>surface</th>\n",
       "      <th>terrace</th>\n",
       "      <th>multimedia</th>\n",
       "      <th>price_m2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>150476642</td>\n",
       "      <td>2200000</td>\n",
       "      <td>2021-02-19 15:40:40.138</td>\n",
       "      <td>GILMAR Consulting Inmobiliario Madrid, Conde O...</td>\n",
       "      <td>faccion-jardin-terraza-trastero-patio-piscina/...</td>\n",
       "      <td>Andarrios, Hortaleza</td>\n",
       "      <td>España</td>\n",
       "      <td>Hortaleza</td>\n",
       "      <td>Conde Orgaz - Piovera</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>554.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/100202/1...</td>\n",
       "      <td>3971.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>157313689</td>\n",
       "      <td>405000</td>\n",
       "      <td>2021-02-19 15:40:40.138</td>\n",
       "      <td>Gilmar ofrece, magnifica Vivienda, Ubicada en ...</td>\n",
       "      <td>faccion-parking-ascensor/157313689</td>\n",
       "      <td>Chamartín</td>\n",
       "      <td>España</td>\n",
       "      <td>Chamartín</td>\n",
       "      <td>Prosperidad</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'url': 'https://my.matterport.com/show/?m=fi...</td>\n",
       "      <td>5062.0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>153519540</td>\n",
       "      <td>1930000</td>\n",
       "      <td>2021-02-19 15:40:40.138</td>\n",
       "      <td>Gilmar Mirasierra - Puerta de Hierro (91771777...</td>\n",
       "      <td>king-jardin-terraza-trastero-piscina/153519540</td>\n",
       "      <td>Fuencarral</td>\n",
       "      <td>España</td>\n",
       "      <td>Fuencarral</td>\n",
       "      <td>Tres Olivos - Valverde</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>547.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/100207/1...</td>\n",
       "      <td>3528.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>154298390</td>\n",
       "      <td>1930000</td>\n",
       "      <td>2021-02-19 15:40:40.138</td>\n",
       "      <td>Gilmar Mirasierra - Puerta de Hierro (91771777...</td>\n",
       "      <td>king-jardin-terraza-trastero-piscina/154298390</td>\n",
       "      <td>Fuencarral</td>\n",
       "      <td>España</td>\n",
       "      <td>Fuencarral</td>\n",
       "      <td>Tres Olivos - Valverde</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>547.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[{'url': 'https://images.inmofactory.com/inmof...</td>\n",
       "      <td>3528.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>158184418</td>\n",
       "      <td>485000</td>\n",
       "      <td>2021-02-19 15:40:40.138</td>\n",
       "      <td>Magnifica vivienda en Ciudad Jardín, \\r\\n\\r\\nP...</td>\n",
       "      <td>faccion-ascensor/158184418</td>\n",
       "      <td>Chamartín</td>\n",
       "      <td>España</td>\n",
       "      <td>Chamartín</td>\n",
       "      <td>Ciudad Jardín</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>133.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/89548/26...</td>\n",
       "      <td>3647.0</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>9275</th>\n",
       "      <td>158823456</td>\n",
       "      <td>115000</td>\n",
       "      <td>2021-02-05 11:43:44.497</td>\n",
       "      <td>Piso para actualizar en Zona Hellín.\\r\\n\\r\\nFa...</td>\n",
       "      <td>faccion/158823456</td>\n",
       "      <td>Calle de Hinojosa del Duque, San Blas</td>\n",
       "      <td>España</td>\n",
       "      <td>San Blas</td>\n",
       "      <td>Hellín</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/85276/27...</td>\n",
       "      <td>1855.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9276</th>\n",
       "      <td>158823310</td>\n",
       "      <td>179000</td>\n",
       "      <td>2021-02-05 11:35:14.360</td>\n",
       "      <td>Magnífico dúplex loft a dos alturas, totalment...</td>\n",
       "      <td>faccion-parking-terraza-ascensor-amueblado/158...</td>\n",
       "      <td>Carretera de Vicálvaro a la Estac. O'donnell, ...</td>\n",
       "      <td>España</td>\n",
       "      <td>San Blas</td>\n",
       "      <td>Rosas - Musas</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/85276/27...</td>\n",
       "      <td>2157.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9277</th>\n",
       "      <td>158823307</td>\n",
       "      <td>137000</td>\n",
       "      <td>2021-02-05 11:34:53.280</td>\n",
       "      <td>Luminosa vivienda de 56 m2, amplio salón con c...</td>\n",
       "      <td>faccion-amueblado/158823307</td>\n",
       "      <td>Calle Garganchón, Barajas</td>\n",
       "      <td>España</td>\n",
       "      <td>Barajas</td>\n",
       "      <td>Aeropuerto</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/98925/27...</td>\n",
       "      <td>2446.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9278</th>\n",
       "      <td>158823262</td>\n",
       "      <td>115000</td>\n",
       "      <td>2021-02-05 11:31:41.277</td>\n",
       "      <td>Fantástico Piso en zona Simancas, Impecable, t...</td>\n",
       "      <td>faccion-no-amueblado/158823262</td>\n",
       "      <td>Calle de Zubieta, San Blas</td>\n",
       "      <td>España</td>\n",
       "      <td>San Blas</td>\n",
       "      <td>Simancas</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/85276/27...</td>\n",
       "      <td>2396.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9279</th>\n",
       "      <td>158823219</td>\n",
       "      <td>380000</td>\n",
       "      <td>2021-02-05 11:29:45.217</td>\n",
       "      <td>\"Piso inteio, muy tranquilo en el corazón del ...</td>\n",
       "      <td>faccion-ascensor-patio-amueblado/158823219</td>\n",
       "      <td>Calle del Conde de Peñalver, 30, Salamanca</td>\n",
       "      <td>España</td>\n",
       "      <td>Salamanca</td>\n",
       "      <td>Goya</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/88669/27...</td>\n",
       "      <td>4222.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9280 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             id    price                    date  \\\n",
       "0     150476642  2200000 2021-02-19 15:40:40.138   \n",
       "1     157313689   405000 2021-02-19 15:40:40.138   \n",
       "2     153519540  1930000 2021-02-19 15:40:40.138   \n",
       "3     154298390  1930000 2021-02-19 15:40:40.138   \n",
       "4     158184418   485000 2021-02-19 15:40:40.138   \n",
       "...         ...      ...                     ...   \n",
       "9275  158823456   115000 2021-02-05 11:43:44.497   \n",
       "9276  158823310   179000 2021-02-05 11:35:14.360   \n",
       "9277  158823307   137000 2021-02-05 11:34:53.280   \n",
       "9278  158823262   115000 2021-02-05 11:31:41.277   \n",
       "9279  158823219   380000 2021-02-05 11:29:45.217   \n",
       "\n",
       "                                   customer_description  \\\n",
       "0     GILMAR Consulting Inmobiliario Madrid, Conde O...   \n",
       "1     Gilmar ofrece, magnifica Vivienda, Ubicada en ...   \n",
       "2     Gilmar Mirasierra - Puerta de Hierro (91771777...   \n",
       "3     Gilmar Mirasierra - Puerta de Hierro (91771777...   \n",
       "4     Magnifica vivienda en Ciudad Jardín, \\r\\n\\r\\nP...   \n",
       "...                                                 ...   \n",
       "9275  Piso para actualizar en Zona Hellín.\\r\\n\\r\\nFa...   \n",
       "9276  Magnífico dúplex loft a dos alturas, totalment...   \n",
       "9277  Luminosa vivienda de 56 m2, amplio salón con c...   \n",
       "9278  Fantástico Piso en zona Simancas, Impecable, t...   \n",
       "9279  \"Piso inteio, muy tranquilo en el corazón del ...   \n",
       "\n",
       "                                           short_detail  \\\n",
       "0     faccion-jardin-terraza-trastero-patio-piscina/...   \n",
       "1                    faccion-parking-ascensor/157313689   \n",
       "2        king-jardin-terraza-trastero-piscina/153519540   \n",
       "3        king-jardin-terraza-trastero-piscina/154298390   \n",
       "4                            faccion-ascensor/158184418   \n",
       "...                                                 ...   \n",
       "9275                                  faccion/158823456   \n",
       "9276  faccion-parking-terraza-ascensor-amueblado/158...   \n",
       "9277                        faccion-amueblado/158823307   \n",
       "9278                     faccion-no-amueblado/158823262   \n",
       "9279         faccion-ascensor-patio-amueblado/158823219   \n",
       "\n",
       "                                                address country neighborhood  \\\n",
       "0                                  Andarrios, Hortaleza  España    Hortaleza   \n",
       "1                                             Chamartín  España    Chamartín   \n",
       "2                                            Fuencarral  España   Fuencarral   \n",
       "3                                            Fuencarral  España   Fuencarral   \n",
       "4                                             Chamartín  España    Chamartín   \n",
       "...                                                 ...     ...          ...   \n",
       "9275              Calle de Hinojosa del Duque, San Blas  España     San Blas   \n",
       "9276  Carretera de Vicálvaro a la Estac. O'donnell, ...  España     San Blas   \n",
       "9277                          Calle Garganchón, Barajas  España      Barajas   \n",
       "9278                         Calle de Zubieta, San Blas  España     San Blas   \n",
       "9279         Calle del Conde de Peñalver, 30, Salamanca  España    Salamanca   \n",
       "\n",
       "                    district  address.coordinates.accuracy  ...  bathrooms  \\\n",
       "0      Conde Orgaz - Piovera                             0  ...        5.0   \n",
       "1                Prosperidad                             0  ...        1.0   \n",
       "2     Tres Olivos - Valverde                             0  ...        6.0   \n",
       "3     Tres Olivos - Valverde                             0  ...        6.0   \n",
       "4              Ciudad Jardín                             0  ...        2.0   \n",
       "...                      ...                           ...  ...        ...   \n",
       "9275                  Hellín                             0  ...        1.0   \n",
       "9276           Rosas - Musas                             0  ...        2.0   \n",
       "9277              Aeropuerto                             0  ...        1.0   \n",
       "9278                Simancas                             0  ...        1.0   \n",
       "9279                    Goya                             1  ...        1.0   \n",
       "\n",
       "      conservationState elevator  floor  parking  rooms  surface  terrace  \\\n",
       "0                   2.0      NaN    NaN      NaN    5.0    554.0      1.0   \n",
       "1                   3.0      1.0    7.0      NaN    3.0     80.0      NaN   \n",
       "2                   1.0      NaN    NaN      NaN    5.0    547.0      1.0   \n",
       "3                   1.0      NaN    NaN      NaN    5.0    547.0      1.0   \n",
       "4                   4.0      1.0    8.0      NaN    4.0    133.0      NaN   \n",
       "...                 ...      ...    ...      ...    ...      ...      ...   \n",
       "9275                4.0      NaN    6.0      NaN    3.0     62.0      NaN   \n",
       "9276                NaN      1.0    6.0      NaN    2.0     83.0      1.0   \n",
       "9277                3.0      NaN    6.0      NaN    1.0     56.0      NaN   \n",
       "9278                1.0      NaN    NaN      NaN    2.0     48.0      NaN   \n",
       "9279                2.0      1.0    6.0      NaN    2.0     90.0      NaN   \n",
       "\n",
       "                                             multimedia  price_m2  \n",
       "0     [{'url': 'https://d.inmofactory.com/1/100202/1...    3971.0  \n",
       "1     [{'url': 'https://my.matterport.com/show/?m=fi...    5062.0  \n",
       "2     [{'url': 'https://d.inmofactory.com/1/100207/1...    3528.0  \n",
       "3     [{'url': 'https://images.inmofactory.com/inmof...    3528.0  \n",
       "4     [{'url': 'https://d.inmofactory.com/1/89548/26...    3647.0  \n",
       "...                                                 ...       ...  \n",
       "9275  [{'url': 'https://d.inmofactory.com/1/85276/27...    1855.0  \n",
       "9276  [{'url': 'https://d.inmofactory.com/1/85276/27...    2157.0  \n",
       "9277  [{'url': 'https://d.inmofactory.com/1/98925/27...    2446.0  \n",
       "9278  [{'url': 'https://d.inmofactory.com/1/85276/27...    2396.0  \n",
       "9279  [{'url': 'https://d.inmofactory.com/1/88669/27...    4222.0  \n",
       "\n",
       "[9280 rows x 23 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "sale.to_csv('Madrid_salev1.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "········\n"
     ]
    }
   ],
   "source": [
    "username='root'\n",
    "password='password'\n",
    "server='localhost'\n",
    "database='madrid'\n",
    "password=getpass()\n",
    "engine = create_engine(f'mysql+pymysql://{username}:{password}@{server}/{database}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "inspector = inspect(engine)\n",
    "inspector.get_table_names()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "for_sale = pd.read_csv('Madrid_salev1.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import table to SQL Madrid Schema"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "for_sale.to_sql('sale', con=engine,index=False,if_exists='append')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['sale']"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "inspector = inspect(engine)\n",
    "inspector.get_table_names()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['id', 'price', 'date', 'customer_description', 'short_detail',\n",
       "       'address', 'country', 'neighborhood', 'district',\n",
       "       'address.coordinates.accuracy', 'coordinates.latitude',\n",
       "       'coordinates.longitude', 'zipCode', 'bathrooms', 'conservationState',\n",
       "       'elevator', 'floor', 'parking', 'rooms', 'surface', 'terrace',\n",
       "       'multimedia', 'price_m2'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sale.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Start Cleanning Flats for Rent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "rent = pd.read_json('Madrid_rent.json', orient='records')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>promotionId</th>\n",
       "      <th>typeId</th>\n",
       "      <th>subtypeId</th>\n",
       "      <th>isNew</th>\n",
       "      <th>isPremium</th>\n",
       "      <th>multimedias</th>\n",
       "      <th>features</th>\n",
       "      <th>otherFeatures</th>\n",
       "      <th>transactions</th>\n",
       "      <th>...</th>\n",
       "      <th>address.location.level5Id</th>\n",
       "      <th>address.location.level6Id</th>\n",
       "      <th>address.location.level7Id</th>\n",
       "      <th>address.location.level8Id</th>\n",
       "      <th>address.coordinates.accuracy</th>\n",
       "      <th>address.coordinates.latitude</th>\n",
       "      <th>address.coordinates.longitude</th>\n",
       "      <th>address.zipCode</th>\n",
       "      <th>address.customZone</th>\n",
       "      <th>advertiser.logo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>True</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/86845/22...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [2], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'transactionTypeId': 3, 'value': [1400], 're...</td>\n",
       "      <td>...</td>\n",
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       "      <td>-3.674870</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>156275511</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/97827/97...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [2], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'transactionTypeId': 3, 'value': [1100], 're...</td>\n",
       "      <td>...</td>\n",
       "      <td>28079</td>\n",
       "      <td>0</td>\n",
       "      <td>676</td>\n",
       "      <td>78</td>\n",
       "      <td>0</td>\n",
       "      <td>40.44377</td>\n",
       "      <td>-3.633442</td>\n",
       "      <td>28027</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>157447223</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/86864/48...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [1], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'transactionTypeId': 3, 'value': [780], 'red...</td>\n",
       "      <td>...</td>\n",
       "      <td>28079</td>\n",
       "      <td>0</td>\n",
       "      <td>667</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>40.43719</td>\n",
       "      <td>-3.674235</td>\n",
       "      <td>28028</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>156282920</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/86864/22...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [2], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'transactionTypeId': 3, 'value': [1700], 're...</td>\n",
       "      <td>...</td>\n",
       "      <td>28079</td>\n",
       "      <td>0</td>\n",
       "      <td>667</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>40.43322</td>\n",
       "      <td>-3.670206</td>\n",
       "      <td>28028</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>158073481</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/97827/26...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [2], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'transactionTypeId': 3, 'value': [1500], 're...</td>\n",
       "      <td>...</td>\n",
       "      <td>28079</td>\n",
       "      <td>0</td>\n",
       "      <td>676</td>\n",
       "      <td>78</td>\n",
       "      <td>0</td>\n",
       "      <td>40.44605</td>\n",
       "      <td>-3.625998</td>\n",
       "      <td>28027</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <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>2351</th>\n",
       "      <td>158656257</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/107685/2...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [1], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'transactionTypeId': 3, 'value': [950], 'red...</td>\n",
       "      <td>...</td>\n",
       "      <td>28079</td>\n",
       "      <td>0</td>\n",
       "      <td>176</td>\n",
       "      <td>114</td>\n",
       "      <td>0</td>\n",
       "      <td>40.45871</td>\n",
       "      <td>-3.674893</td>\n",
       "      <td>28016</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2352</th>\n",
       "      <td>158245390</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/118430/2...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [2], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'transactionTypeId': 3, 'value': [1250], 're...</td>\n",
       "      <td>...</td>\n",
       "      <td>28079</td>\n",
       "      <td>0</td>\n",
       "      <td>671</td>\n",
       "      <td>42</td>\n",
       "      <td>0</td>\n",
       "      <td>40.40918</td>\n",
       "      <td>-3.721197</td>\n",
       "      <td>28005</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2353</th>\n",
       "      <td>156156495</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/86593/22...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [2], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'transactionTypeId': 3, 'value': [2000], 're...</td>\n",
       "      <td>...</td>\n",
       "      <td>28079</td>\n",
       "      <td>0</td>\n",
       "      <td>177</td>\n",
       "      <td>142</td>\n",
       "      <td>0</td>\n",
       "      <td>40.44104</td>\n",
       "      <td>-3.695068</td>\n",
       "      <td>28003</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2354</th>\n",
       "      <td>158619379</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/86593/53...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [1], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'transactionTypeId': 3, 'value': [600], 'red...</td>\n",
       "      <td>...</td>\n",
       "      <td>28079</td>\n",
       "      <td>0</td>\n",
       "      <td>177</td>\n",
       "      <td>142</td>\n",
       "      <td>1</td>\n",
       "      <td>40.44130</td>\n",
       "      <td>-3.694986</td>\n",
       "      <td>28003</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2355</th>\n",
       "      <td>157175919</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/85553/15...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [1], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'transactionTypeId': 3, 'value': [1500], 're...</td>\n",
       "      <td>...</td>\n",
       "      <td>28079</td>\n",
       "      <td>0</td>\n",
       "      <td>669</td>\n",
       "      <td>33</td>\n",
       "      <td>0</td>\n",
       "      <td>40.42593</td>\n",
       "      <td>-3.712181</td>\n",
       "      <td>28003</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2356 rows × 55 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             id  promotionId  typeId  subtypeId  isNew  isPremium  \\\n",
       "0     157612297            0       2          1  False       True   \n",
       "1     156275511            0       2          1  False       True   \n",
       "2     157447223            0       2          2  False       True   \n",
       "3     156282920            0       2          1  False       True   \n",
       "4     158073481            0       2          1  False       True   \n",
       "...         ...          ...     ...        ...    ...        ...   \n",
       "2351  158656257            0       2          6  False      False   \n",
       "2352  158245390            0       2          1  False      False   \n",
       "2353  156156495            0       2          1  False      False   \n",
       "2354  158619379            0       2          1  False      False   \n",
       "2355  157175919            0       2          1  False      False   \n",
       "\n",
       "                                            multimedias  \\\n",
       "0     [{'url': 'https://d.inmofactory.com/1/86845/22...   \n",
       "1     [{'url': 'https://d.inmofactory.com/1/97827/97...   \n",
       "2     [{'url': 'https://d.inmofactory.com/1/86864/48...   \n",
       "3     [{'url': 'https://d.inmofactory.com/1/86864/22...   \n",
       "4     [{'url': 'https://d.inmofactory.com/1/97827/26...   \n",
       "...                                                 ...   \n",
       "2351  [{'url': 'https://d.inmofactory.com/1/107685/2...   \n",
       "2352  [{'url': 'https://d.inmofactory.com/1/118430/2...   \n",
       "2353  [{'url': 'https://d.inmofactory.com/1/86593/22...   \n",
       "2354  [{'url': 'https://d.inmofactory.com/1/86593/53...   \n",
       "2355  [{'url': 'https://d.inmofactory.com/1/85553/15...   \n",
       "\n",
       "                                               features  otherFeatures  \\\n",
       "0     [{'key': 'bathrooms', 'value': [2], 'minValue'...            NaN   \n",
       "1     [{'key': 'bathrooms', 'value': [2], 'minValue'...            NaN   \n",
       "2     [{'key': 'bathrooms', 'value': [1], 'minValue'...            NaN   \n",
       "3     [{'key': 'bathrooms', 'value': [2], 'minValue'...            NaN   \n",
       "4     [{'key': 'bathrooms', 'value': [2], 'minValue'...            NaN   \n",
       "...                                                 ...            ...   \n",
       "2351  [{'key': 'bathrooms', 'value': [1], 'minValue'...            NaN   \n",
       "2352  [{'key': 'bathrooms', 'value': [2], 'minValue'...            NaN   \n",
       "2353  [{'key': 'bathrooms', 'value': [2], 'minValue'...            NaN   \n",
       "2354  [{'key': 'bathrooms', 'value': [1], 'minValue'...            NaN   \n",
       "2355  [{'key': 'bathrooms', 'value': [1], 'minValue'...            NaN   \n",
       "\n",
       "                                           transactions  ...  \\\n",
       "0     [{'transactionTypeId': 3, 'value': [1400], 're...  ...   \n",
       "1     [{'transactionTypeId': 3, 'value': [1100], 're...  ...   \n",
       "2     [{'transactionTypeId': 3, 'value': [780], 'red...  ...   \n",
       "3     [{'transactionTypeId': 3, 'value': [1700], 're...  ...   \n",
       "4     [{'transactionTypeId': 3, 'value': [1500], 're...  ...   \n",
       "...                                                 ...  ...   \n",
       "2351  [{'transactionTypeId': 3, 'value': [950], 'red...  ...   \n",
       "2352  [{'transactionTypeId': 3, 'value': [1250], 're...  ...   \n",
       "2353  [{'transactionTypeId': 3, 'value': [2000], 're...  ...   \n",
       "2354  [{'transactionTypeId': 3, 'value': [600], 'red...  ...   \n",
       "2355  [{'transactionTypeId': 3, 'value': [1500], 're...  ...   \n",
       "\n",
       "     address.location.level5Id address.location.level6Id  \\\n",
       "0                        28079                         0   \n",
       "1                        28079                         0   \n",
       "2                        28079                         0   \n",
       "3                        28079                         0   \n",
       "4                        28079                         0   \n",
       "...                        ...                       ...   \n",
       "2351                     28079                         0   \n",
       "2352                     28079                         0   \n",
       "2353                     28079                         0   \n",
       "2354                     28079                         0   \n",
       "2355                     28079                         0   \n",
       "\n",
       "     address.location.level7Id  address.location.level8Id  \\\n",
       "0                          199                        122   \n",
       "1                          676                         78   \n",
       "2                          667                         20   \n",
       "3                          667                         20   \n",
       "4                          676                         78   \n",
       "...                        ...                        ...   \n",
       "2351                       176                        114   \n",
       "2352                       671                         42   \n",
       "2353                       177                        142   \n",
       "2354                       177                        142   \n",
       "2355                       669                         33   \n",
       "\n",
       "      address.coordinates.accuracy  address.coordinates.latitude  \\\n",
       "0                                1                      40.41804   \n",
       "1                                0                      40.44377   \n",
       "2                                0                      40.43719   \n",
       "3                                0                      40.43322   \n",
       "4                                0                      40.44605   \n",
       "...                            ...                           ...   \n",
       "2351                             0                      40.45871   \n",
       "2352                             0                      40.40918   \n",
       "2353                             0                      40.44104   \n",
       "2354                             1                      40.44130   \n",
       "2355                             0                      40.42593   \n",
       "\n",
       "      address.coordinates.longitude  address.zipCode  address.customZone  \\\n",
       "0                         -3.674870            28009                 NaN   \n",
       "1                         -3.633442            28027                 NaN   \n",
       "2                         -3.674235            28028                 NaN   \n",
       "3                         -3.670206            28028                 NaN   \n",
       "4                         -3.625998            28027                 NaN   \n",
       "...                             ...              ...                 ...   \n",
       "2351                      -3.674893            28016                 NaN   \n",
       "2352                      -3.721197            28005                 NaN   \n",
       "2353                      -3.695068            28003                 NaN   \n",
       "2354                      -3.694986            28003                 NaN   \n",
       "2355                      -3.712181            28003                 NaN   \n",
       "\n",
       "      advertiser.logo  \n",
       "0                 NaN  \n",
       "1                 NaN  \n",
       "2                 NaN  \n",
       "3                 NaN  \n",
       "4                 NaN  \n",
       "...               ...  \n",
       "2351              NaN  \n",
       "2352              NaN  \n",
       "2353              NaN  \n",
       "2354              NaN  \n",
       "2355              NaN  \n",
       "\n",
       "[2356 rows x 55 columns]"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rent"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Duplicated - Rent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "rent = rent.set_index(rent['id'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2356"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(rent)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "rent = rent.drop_duplicates(subset=['id'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2277"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(rent)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cleaning Features columm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                                                 int64\n",
       "promotionId                                        int64\n",
       "typeId                                             int64\n",
       "subtypeId                                          int64\n",
       "isNew                                               bool\n",
       "isPremium                                           bool\n",
       "multimedias                                       object\n",
       "features                                          object\n",
       "otherFeatures                                    float64\n",
       "transactions                                      object\n",
       "products                                          object\n",
       "date                                 datetime64[ns, UTC]\n",
       "description                                       object\n",
       "isTop                                               bool\n",
       "isPhotoReport                                       bool\n",
       "isMsAdvance                                         bool\n",
       "promotionTypeId                                    int64\n",
       "promotionUrl                                     float64\n",
       "isExternalContact                                   bool\n",
       "isVirtualTour                                       bool\n",
       "advertiser.logo.multimedia.url                    object\n",
       "advertiser.logo.multimedia.typeId                float64\n",
       "advertiser.logo.url.es                            object\n",
       "advertiser.phone                                  object\n",
       "advertiser.typeId                                  int64\n",
       "advertiser.clientId                                int64\n",
       "advertiser.urlAlias                               object\n",
       "advertiser.clientAlias                            object\n",
       "detail.es                                         object\n",
       "address.ubication                                 object\n",
       "address.location.country                          object\n",
       "address.location.level1                           object\n",
       "address.location.level2                           object\n",
       "address.location.level3                           object\n",
       "address.location.level4                           object\n",
       "address.location.level5                           object\n",
       "address.location.level6                           object\n",
       "address.location.level7                           object\n",
       "address.location.level8                           object\n",
       "address.location.upperLevel                       object\n",
       "address.location.countryId                         int64\n",
       "address.location.level1Id                          int64\n",
       "address.location.level2Id                          int64\n",
       "address.location.level3Id                          int64\n",
       "address.location.level4Id                          int64\n",
       "address.location.level5Id                          int64\n",
       "address.location.level6Id                          int64\n",
       "address.location.level7Id                          int64\n",
       "address.location.level8Id                          int64\n",
       "address.coordinates.accuracy                       int64\n",
       "address.coordinates.latitude                     float64\n",
       "address.coordinates.longitude                    float64\n",
       "address.zipCode                                    int64\n",
       "address.customZone                               float64\n",
       "advertiser.logo                                  float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rent.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Int64Index([157612297, 156275511, 157447223, 156282920, 158073481, 157233057,\n",
       "            158890770, 158898445, 158885578, 158637151,\n",
       "            ...\n",
       "            155469142, 156153373, 157308889, 157861410, 158668998, 158656257,\n",
       "            158245390, 156156495, 158619379, 157175919],\n",
       "           dtype='int64', name='id', length=2277)"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rent.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "125235"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rent.size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>promotionId</th>\n",
       "      <th>typeId</th>\n",
       "      <th>subtypeId</th>\n",
       "      <th>isNew</th>\n",
       "      <th>isPremium</th>\n",
       "      <th>multimedias</th>\n",
       "      <th>features</th>\n",
       "      <th>otherFeatures</th>\n",
       "      <th>transactions</th>\n",
       "      <th>...</th>\n",
       "      <th>address.location.level5Id</th>\n",
       "      <th>address.location.level6Id</th>\n",
       "      <th>address.location.level7Id</th>\n",
       "      <th>address.location.level8Id</th>\n",
       "      <th>address.coordinates.accuracy</th>\n",
       "      <th>address.coordinates.latitude</th>\n",
       "      <th>address.coordinates.longitude</th>\n",
       "      <th>address.zipCode</th>\n",
       "      <th>address.customZone</th>\n",
       "      <th>advertiser.logo</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>157612297</th>\n",
       "      <td>157612297</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/86845/22...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [2], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'transactionTypeId': 3, 'value': [1400], 're...</td>\n",
       "      <td>...</td>\n",
       "      <td>28079</td>\n",
       "      <td>0</td>\n",
       "      <td>199</td>\n",
       "      <td>122</td>\n",
       "      <td>1</td>\n",
       "      <td>40.41804</td>\n",
       "      <td>-3.674870</td>\n",
       "      <td>28009</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156275511</th>\n",
       "      <td>156275511</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/97827/97...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [2], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'transactionTypeId': 3, 'value': [1100], 're...</td>\n",
       "      <td>...</td>\n",
       "      <td>28079</td>\n",
       "      <td>0</td>\n",
       "      <td>676</td>\n",
       "      <td>78</td>\n",
       "      <td>0</td>\n",
       "      <td>40.44377</td>\n",
       "      <td>-3.633442</td>\n",
       "      <td>28027</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157447223</th>\n",
       "      <td>157447223</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/86864/48...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [1], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'transactionTypeId': 3, 'value': [780], 'red...</td>\n",
       "      <td>...</td>\n",
       "      <td>28079</td>\n",
       "      <td>0</td>\n",
       "      <td>667</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>40.43719</td>\n",
       "      <td>-3.674235</td>\n",
       "      <td>28028</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156282920</th>\n",
       "      <td>156282920</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/86864/22...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [2], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'transactionTypeId': 3, 'value': [1700], 're...</td>\n",
       "      <td>...</td>\n",
       "      <td>28079</td>\n",
       "      <td>0</td>\n",
       "      <td>667</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>40.43322</td>\n",
       "      <td>-3.670206</td>\n",
       "      <td>28028</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158073481</th>\n",
       "      <td>158073481</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/97827/26...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [2], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'transactionTypeId': 3, 'value': [1500], 're...</td>\n",
       "      <td>...</td>\n",
       "      <td>28079</td>\n",
       "      <td>0</td>\n",
       "      <td>676</td>\n",
       "      <td>78</td>\n",
       "      <td>0</td>\n",
       "      <td>40.44605</td>\n",
       "      <td>-3.625998</td>\n",
       "      <td>28027</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 55 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  id  promotionId  typeId  subtypeId  isNew  isPremium  \\\n",
       "id                                                                       \n",
       "157612297  157612297            0       2          1  False       True   \n",
       "156275511  156275511            0       2          1  False       True   \n",
       "157447223  157447223            0       2          2  False       True   \n",
       "156282920  156282920            0       2          1  False       True   \n",
       "158073481  158073481            0       2          1  False       True   \n",
       "\n",
       "                                                 multimedias  \\\n",
       "id                                                             \n",
       "157612297  [{'url': 'https://d.inmofactory.com/1/86845/22...   \n",
       "156275511  [{'url': 'https://d.inmofactory.com/1/97827/97...   \n",
       "157447223  [{'url': 'https://d.inmofactory.com/1/86864/48...   \n",
       "156282920  [{'url': 'https://d.inmofactory.com/1/86864/22...   \n",
       "158073481  [{'url': 'https://d.inmofactory.com/1/97827/26...   \n",
       "\n",
       "                                                    features  otherFeatures  \\\n",
       "id                                                                            \n",
       "157612297  [{'key': 'bathrooms', 'value': [2], 'minValue'...            NaN   \n",
       "156275511  [{'key': 'bathrooms', 'value': [2], 'minValue'...            NaN   \n",
       "157447223  [{'key': 'bathrooms', 'value': [1], 'minValue'...            NaN   \n",
       "156282920  [{'key': 'bathrooms', 'value': [2], 'minValue'...            NaN   \n",
       "158073481  [{'key': 'bathrooms', 'value': [2], 'minValue'...            NaN   \n",
       "\n",
       "                                                transactions  ...  \\\n",
       "id                                                            ...   \n",
       "157612297  [{'transactionTypeId': 3, 'value': [1400], 're...  ...   \n",
       "156275511  [{'transactionTypeId': 3, 'value': [1100], 're...  ...   \n",
       "157447223  [{'transactionTypeId': 3, 'value': [780], 'red...  ...   \n",
       "156282920  [{'transactionTypeId': 3, 'value': [1700], 're...  ...   \n",
       "158073481  [{'transactionTypeId': 3, 'value': [1500], 're...  ...   \n",
       "\n",
       "          address.location.level5Id address.location.level6Id  \\\n",
       "id                                                              \n",
       "157612297                     28079                         0   \n",
       "156275511                     28079                         0   \n",
       "157447223                     28079                         0   \n",
       "156282920                     28079                         0   \n",
       "158073481                     28079                         0   \n",
       "\n",
       "          address.location.level7Id  address.location.level8Id  \\\n",
       "id                                                               \n",
       "157612297                       199                        122   \n",
       "156275511                       676                         78   \n",
       "157447223                       667                         20   \n",
       "156282920                       667                         20   \n",
       "158073481                       676                         78   \n",
       "\n",
       "           address.coordinates.accuracy  address.coordinates.latitude  \\\n",
       "id                                                                      \n",
       "157612297                             1                      40.41804   \n",
       "156275511                             0                      40.44377   \n",
       "157447223                             0                      40.43719   \n",
       "156282920                             0                      40.43322   \n",
       "158073481                             0                      40.44605   \n",
       "\n",
       "           address.coordinates.longitude  address.zipCode  address.customZone  \\\n",
       "id                                                                              \n",
       "157612297                      -3.674870            28009                 NaN   \n",
       "156275511                      -3.633442            28027                 NaN   \n",
       "157447223                      -3.674235            28028                 NaN   \n",
       "156282920                      -3.670206            28028                 NaN   \n",
       "158073481                      -3.625998            28027                 NaN   \n",
       "\n",
       "           advertiser.logo  \n",
       "id                          \n",
       "157612297              NaN  \n",
       "156275511              NaN  \n",
       "157447223              NaN  \n",
       "156282920              NaN  \n",
       "158073481              NaN  \n",
       "\n",
       "[5 rows x 55 columns]"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rent.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cleannning Features Rent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "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 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>features</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>157612297</th>\n",
       "      <td>[{'key': 'bathrooms', 'value': [2], 'minValue'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156275511</th>\n",
       "      <td>[{'key': 'bathrooms', 'value': [2], 'minValue'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157447223</th>\n",
       "      <td>[{'key': 'bathrooms', 'value': [1], 'minValue'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156282920</th>\n",
       "      <td>[{'key': 'bathrooms', 'value': [2], 'minValue'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158073481</th>\n",
       "      <td>[{'key': 'bathrooms', 'value': [2], 'minValue'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158656257</th>\n",
       "      <td>[{'key': 'bathrooms', 'value': [1], 'minValue'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158245390</th>\n",
       "      <td>[{'key': 'bathrooms', 'value': [2], 'minValue'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156156495</th>\n",
       "      <td>[{'key': 'bathrooms', 'value': [2], 'minValue'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158619379</th>\n",
       "      <td>[{'key': 'bathrooms', 'value': [1], 'minValue'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157175919</th>\n",
       "      <td>[{'key': 'bathrooms', 'value': [1], 'minValue'...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2277 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    features\n",
       "id                                                          \n",
       "157612297  [{'key': 'bathrooms', 'value': [2], 'minValue'...\n",
       "156275511  [{'key': 'bathrooms', 'value': [2], 'minValue'...\n",
       "157447223  [{'key': 'bathrooms', 'value': [1], 'minValue'...\n",
       "156282920  [{'key': 'bathrooms', 'value': [2], 'minValue'...\n",
       "158073481  [{'key': 'bathrooms', 'value': [2], 'minValue'...\n",
       "...                                                      ...\n",
       "158656257  [{'key': 'bathrooms', 'value': [1], 'minValue'...\n",
       "158245390  [{'key': 'bathrooms', 'value': [2], 'minValue'...\n",
       "156156495  [{'key': 'bathrooms', 'value': [2], 'minValue'...\n",
       "158619379  [{'key': 'bathrooms', 'value': [1], 'minValue'...\n",
       "157175919  [{'key': 'bathrooms', 'value': [1], 'minValue'...\n",
       "\n",
       "[2277 rows x 1 columns]"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(rent['features'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "features = pd.DataFrame(rent['features'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "features = features['features'].apply(pd.Series)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "feats0 = features[0].apply(pd.Series)\n",
    "feats1 = features[1].apply(pd.Series)\n",
    "feats2 = features[2].apply(pd.Series)\n",
    "feats3 = features[3].apply(pd.Series)\n",
    "feats4 = features[4].apply(pd.Series)\n",
    "feats5 = features[5].apply(pd.Series)\n",
    "feats6 = features[6].apply(pd.Series)\n",
    "feats7 = features[7].apply(pd.Series)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "feats0 = features[0].apply(pd.Series)\n",
    "feats1 = features[1].apply(pd.Series)\n",
    "feats2 = features[2].apply(pd.Series)\n",
    "feats3 = features[3].apply(pd.Series)\n",
    "feats4 = features[4].apply(pd.Series)\n",
    "feats5 = features[5].apply(pd.Series)\n",
    "feats6 = features[6].apply(pd.Series)\n",
    "feats7 = features[7].apply(pd.Series)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "feats0['value'] = feats0['value'].map(lambda x: str(x).strip('[]'))\n",
    "feats1['value'] = feats1['value'].map(lambda x: str(x).strip('[]'))\n",
    "feats2['value'] = feats2['value'].map(lambda x: str(x).strip('[]'))\n",
    "feats3['value'] = feats3['value'].map(lambda x: str(x).strip('[]'))\n",
    "feats4['value'] = feats4['value'].map(lambda x: str(x).strip('[]'))\n",
    "feats5['value'] = feats5['value'].map(lambda x: str(x).strip('[]'))\n",
    "feats6['value'] = feats6['value'].map(lambda x: str(x).strip('[]'))\n",
    "feats7['value'] = feats7['value'].map(lambda x: str(x).strip('[]'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "feats0['value'] = feats0['value'].astype('float')\n",
    "feats1['value'] = feats1['value'].astype('float')\n",
    "feats2['value'] = feats2['value'].astype('float')\n",
    "feats3['value'] = feats3['value'].astype('float')\n",
    "feats4['value'] = feats4['value'].astype('float')\n",
    "feats5['value'] = feats5['value'].astype('float')\n",
    "feats6['value'] = feats6['value'].astype('float')\n",
    "feats7['value'] = feats7['value'].astype('float')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "feats0['value'] = feats0['value'].fillna(value=0)\n",
    "feats1['value'] = feats1['value'].fillna(value=0)\n",
    "feats2['value'] = feats2['value'].fillna(value=0)\n",
    "feats3['value'] = feats3['value'].fillna(value=0)\n",
    "feats4['value'] = feats4['value'].fillna(value=0)\n",
    "feats5['value'] = feats5['value'].fillna(value=0)\n",
    "feats6['value'] = feats6['value'].fillna(value=0)\n",
    "feats7['value'] = feats7['value'].fillna(value=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "feats0['value'] = feats0['value'].astype('int64')\n",
    "feats1['value'] = feats1['value'].astype('int64')\n",
    "feats2['value'] = feats2['value'].astype('int64')\n",
    "feats3['value'] = feats3['value'].astype('int64')\n",
    "feats4['value'] = feats4['value'].astype('int64')\n",
    "feats5['value'] = feats5['value'].astype('int64')\n",
    "feats6['value'] = feats6['value'].astype('int64')\n",
    "feats7['value'] = feats7['value'].astype('int64')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "feats0 = pd.pivot_table(feats0, index=['id'], columns=feats0['key'])\n",
    "feats1 = pd.pivot_table(feats1, index=['id'], columns=feats1['key'])\n",
    "feats2 = pd.pivot_table(feats2, index=['id'], columns=feats2['key'])\n",
    "feats3 = pd.pivot_table(feats3, index=['id'], columns=feats3['key'])\n",
    "feats4 = pd.pivot_table(feats4, index=['id'], columns=feats4['key'])\n",
    "feats5 = pd.pivot_table(feats5, index=['id'], columns=feats5['key'])\n",
    "feats6 = pd.pivot_table(feats6, index=['id'], columns=feats6['key'])\n",
    "feats7 = pd.pivot_table(feats7, index=['id'], columns=feats7['key'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "right0 = feats0.add(feats1, fill_value=0)\n",
    "right1 = feats2.add(feats3, fill_value=0)\n",
    "right2 = feats4.add(feats5, fill_value=0)\n",
    "right3 = feats6.add(feats7, fill_value=0)\n",
    "right4 = right0.add(right1, fill_value=0)\n",
    "right5 = right2.add(right3, fill_value=0)\n",
    "features_d = right4.add(right5, fill_value=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
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       "      <td>6.0</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>2277 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           maxValue                                                         \\\n",
       "key       bathrooms conservationState elevator floor parking rooms surface   \n",
       "id                                                                           \n",
       "136071016       0.0               0.0      0.0   0.0     NaN   0.0     0.0   \n",
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       "...             ...               ...      ...   ...     ...   ...     ...   \n",
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       "158984424       0.0               0.0      0.0   0.0     0.0   0.0     0.0   \n",
       "\n",
       "                   minValue                    ...                     value  \\\n",
       "key       terrace bathrooms conservationState  ... surface terrace bathrooms   \n",
       "id                                             ...                             \n",
       "136071016     0.0       0.0               0.0  ...     0.0     0.0       2.0   \n",
       "136914670     NaN       0.0               0.0  ...     0.0     NaN       3.0   \n",
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       "146842265     0.0       0.0               0.0  ...     0.0     0.0       3.0   \n",
       "...           ...       ...               ...  ...     ...     ...       ...   \n",
       "158983628     NaN       0.0               0.0  ...     0.0     NaN       2.0   \n",
       "158983629     NaN       0.0               NaN  ...     0.0     NaN       2.0   \n",
       "158983631     0.0       0.0               NaN  ...     0.0     0.0       2.0   \n",
       "158984314     NaN       0.0               0.0  ...     0.0     NaN       3.0   \n",
       "158984424     0.0       0.0               0.0  ...     0.0     0.0       5.0   \n",
       "\n",
       "                                                                          \n",
       "key       conservationState elevator floor parking rooms surface terrace  \n",
       "id                                                                        \n",
       "136071016               1.0      1.0   3.0     NaN   2.0   100.0     1.0  \n",
       "136914670               1.0      1.0  11.0     NaN   3.0   258.0     NaN  \n",
       "145255644               8.0      1.0   NaN     1.0   2.0   157.0     NaN  \n",
       "146204865               NaN      1.0   3.0     NaN   3.0   220.0     NaN  \n",
       "146842265               1.0      1.0   NaN     NaN   4.0   180.0     1.0  \n",
       "...                     ...      ...   ...     ...   ...     ...     ...  \n",
       "158983628               2.0      1.0   8.0     NaN   3.0   130.0     NaN  \n",
       "158983629               NaN      1.0  10.0     NaN   3.0   110.0     NaN  \n",
       "158983631               NaN      1.0   8.0     NaN   3.0   110.0     1.0  \n",
       "158984314               2.0      1.0   3.0     1.0   3.0   135.0     NaN  \n",
       "158984424               2.0      1.0   9.0     1.0   6.0   301.0     1.0  \n",
       "\n",
       "[2277 rows x 24 columns]"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features_d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "rent['bathrooms']=features_d.value['bathrooms']\n",
    "rent['conservationState'] = features_d.value['conservationState']\n",
    "rent['elevator'] = features_d.value['elevator']\n",
    "rent['floor'] = features_d.value['floor']\n",
    "rent['parking'] = features_d.value['parking']\n",
    "rent['rooms'] = features_d.value['rooms']\n",
    "rent['surface'] = features_d.value['surface']\n",
    "rent['terrace'] = features_d.value['terrace']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "rent.to_json('Madrid_rentv1.json', orient='records')ºb"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Let's go for the price of the fl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "price = pd.DataFrame(rent['transactions'])\n",
    "price = price['transactions'].apply(pd.Series)\n",
    "price = price[0].apply(pd.Series)\n",
    "price['value'] = price['value'].map(lambda x: str(x).strip('[]'))\n",
    "price['value'] = price['value'].astype('int64')\n",
    "rent['transactions'] = price['value']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
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       "      <th>...</th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>157612297</th>\n",
       "      <td>157612297</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/86845/22...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [2], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1400</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>105.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156275511</th>\n",
       "      <td>156275511</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/97827/97...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [2], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1100</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157447223</th>\n",
       "      <td>157447223</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/86864/48...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [1], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>780</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156282920</th>\n",
       "      <td>156282920</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/86864/22...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [2], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1700</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158073481</th>\n",
       "      <td>158073481</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/97827/26...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [2], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1500</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>1.0</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>158656257</th>\n",
       "      <td>158656257</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/107685/2...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [1], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>950</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158245390</th>\n",
       "      <td>158245390</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/118430/2...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [2], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1250</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>117.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156156495</th>\n",
       "      <td>156156495</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/86593/22...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [2], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2000</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>158.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158619379</th>\n",
       "      <td>158619379</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/86593/53...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [1], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>600</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157175919</th>\n",
       "      <td>157175919</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>[{'url': 'https://d.inmofactory.com/1/85553/15...</td>\n",
       "      <td>[{'key': 'bathrooms', 'value': [1], 'minValue'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1500</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2277 rows × 63 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  id  promotionId  typeId  subtypeId  isNew  isPremium  \\\n",
       "id                                                                       \n",
       "157612297  157612297            0       2          1  False       True   \n",
       "156275511  156275511            0       2          1  False       True   \n",
       "157447223  157447223            0       2          2  False       True   \n",
       "156282920  156282920            0       2          1  False       True   \n",
       "158073481  158073481            0       2          1  False       True   \n",
       "...              ...          ...     ...        ...    ...        ...   \n",
       "158656257  158656257            0       2          6  False      False   \n",
       "158245390  158245390            0       2          1  False      False   \n",
       "156156495  156156495            0       2          1  False      False   \n",
       "158619379  158619379            0       2          1  False      False   \n",
       "157175919  157175919            0       2          1  False      False   \n",
       "\n",
       "                                                 multimedias  \\\n",
       "id                                                             \n",
       "157612297  [{'url': 'https://d.inmofactory.com/1/86845/22...   \n",
       "156275511  [{'url': 'https://d.inmofactory.com/1/97827/97...   \n",
       "157447223  [{'url': 'https://d.inmofactory.com/1/86864/48...   \n",
       "156282920  [{'url': 'https://d.inmofactory.com/1/86864/22...   \n",
       "158073481  [{'url': 'https://d.inmofactory.com/1/97827/26...   \n",
       "...                                                      ...   \n",
       "158656257  [{'url': 'https://d.inmofactory.com/1/107685/2...   \n",
       "158245390  [{'url': 'https://d.inmofactory.com/1/118430/2...   \n",
       "156156495  [{'url': 'https://d.inmofactory.com/1/86593/22...   \n",
       "158619379  [{'url': 'https://d.inmofactory.com/1/86593/53...   \n",
       "157175919  [{'url': 'https://d.inmofactory.com/1/85553/15...   \n",
       "\n",
       "                                                    features  otherFeatures  \\\n",
       "id                                                                            \n",
       "157612297  [{'key': 'bathrooms', 'value': [2], 'minValue'...            NaN   \n",
       "156275511  [{'key': 'bathrooms', 'value': [2], 'minValue'...            NaN   \n",
       "157447223  [{'key': 'bathrooms', 'value': [1], 'minValue'...            NaN   \n",
       "156282920  [{'key': 'bathrooms', 'value': [2], 'minValue'...            NaN   \n",
       "158073481  [{'key': 'bathrooms', 'value': [2], 'minValue'...            NaN   \n",
       "...                                                      ...            ...   \n",
       "158656257  [{'key': 'bathrooms', 'value': [1], 'minValue'...            NaN   \n",
       "158245390  [{'key': 'bathrooms', 'value': [2], 'minValue'...            NaN   \n",
       "156156495  [{'key': 'bathrooms', 'value': [2], 'minValue'...            NaN   \n",
       "158619379  [{'key': 'bathrooms', 'value': [1], 'minValue'...            NaN   \n",
       "157175919  [{'key': 'bathrooms', 'value': [1], 'minValue'...            NaN   \n",
       "\n",
       "           transactions  ... address.customZone advertiser.logo bathrooms  \\\n",
       "id                       ...                                                \n",
       "157612297          1400  ...                NaN             NaN       2.0   \n",
       "156275511          1100  ...                NaN             NaN       2.0   \n",
       "157447223           780  ...                NaN             NaN       1.0   \n",
       "156282920          1700  ...                NaN             NaN       2.0   \n",
       "158073481          1500  ...                NaN             NaN       2.0   \n",
       "...                 ...  ...                ...             ...       ...   \n",
       "158656257           950  ...                NaN             NaN       1.0   \n",
       "158245390          1250  ...                NaN             NaN       2.0   \n",
       "156156495          2000  ...                NaN             NaN       2.0   \n",
       "158619379           600  ...                NaN             NaN       1.0   \n",
       "157175919          1500  ...                NaN             NaN       1.0   \n",
       "\n",
       "           conservationState  elevator  floor  parking  rooms  surface  \\\n",
       "id                                                                       \n",
       "157612297                3.0       1.0    8.0      NaN    3.0    105.0   \n",
       "156275511                NaN       1.0    7.0      1.0    2.0     90.0   \n",
       "157447223                NaN       1.0    5.0      NaN    1.0     45.0   \n",
       "156282920                2.0       1.0    NaN      1.0    4.0    103.0   \n",
       "158073481                2.0       1.0   11.0      1.0    4.0    138.0   \n",
       "...                      ...       ...    ...      ...    ...      ...   \n",
       "158656257                NaN       1.0    9.0      NaN    1.0     55.0   \n",
       "158245390                NaN       1.0    6.0      NaN    4.0    117.0   \n",
       "156156495                NaN       1.0   11.0      NaN    3.0    158.0   \n",
       "158619379                3.0       1.0   14.0      NaN    NaN     39.0   \n",
       "157175919                2.0       1.0   19.0      NaN    2.0     70.0   \n",
       "\n",
       "           terrace  \n",
       "id                  \n",
       "157612297      NaN  \n",
       "156275511      NaN  \n",
       "157447223      1.0  \n",
       "156282920      1.0  \n",
       "158073481      1.0  \n",
       "...            ...  \n",
       "158656257      1.0  \n",
       "158245390      NaN  \n",
       "156156495      NaN  \n",
       "158619379      NaN  \n",
       "157175919      NaN  \n",
       "\n",
       "[2277 rows x 63 columns]"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rent"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Column - Detail.es"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [],
   "source": [
    "rent['detail.es'] = rent['detail.es'].map(lambda x: x.strip('/es/comprar/vivienda/madrid-capital/'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Drop unnecesary columns "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "rent = rent.drop(['promotionId', 'typeId', 'subtypeId', 'isNew', 'isPremium', 'otherFeatures', 'isTop', 'isPhotoReport', 'isMsAdvance', 'promotionTypeId', 'promotionUrl', 'isExternalContact', 'isVirtualTour',\n",
    "       'advertiser.logo.multimedia.url', 'advertiser.logo.multimedia.typeId',\n",
    "       'advertiser.logo.url.es', 'advertiser.phone', 'advertiser.typeId',\n",
    "       'advertiser.clientId', 'advertiser.urlAlias', 'advertiser.clientAlias', 'advertiser.logo'], axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Rename Cols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "col = ['id', 'multimedias', 'price', 'date', 'description', 'short_detail',\n",
    "       'address', 'country',\n",
    "       'city', 'neighborhood',\n",
    "       'district',\n",
    "       'address.coordinates.accuracy', 'coordinates.latitude',\n",
    "       'coordinates.longitude', 'zipCode', 'bathrooms', 'conservationState', 'elevator',\n",
    "       'floor', 'parking', 'rooms', 'surface', 'terrace']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## New_Column Price m2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "rent['price_m2'] = round(rent['price']/rent['surface'], 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Rent to SQL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "········\n"
     ]
    }
   ],
   "source": [
    "username='root'\n",
    "password='password'\n",
    "server='localhost'\n",
    "database='madrid'\n",
    "password=getpass()\n",
    "engine = create_engine(f'mysql+pymysql://{username}:{password}@{server}/{database}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['rent', 'sale']"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "inspector = inspect(engine)\n",
    "inspector.get_table_names()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for_rent.to_sql('rent', con=engine,index=False,if_exists='append')"
   ]
  }
 ],
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    "name": "ipython",
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