FoliumTools.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Folium: Criando mapas interativos com dados reais de forma simples\n",
    "<center><img src='images/Header 16-6.jpg'></center>\n",
    "\n",
    "> Folium é uma poderosa biblioteca Python que combina as a capacidades do ecossistema com a versatilidade da biblioteca Leaflet.js. Com o Folium podemos facilmente buscar, tratar e manipular nossos dados em python e, em seguida, visualiza-los de maneira interativa em um mapa Leaflet.\n",
    "\n",
    "[https://python-visualization.github.io/folium/latest/index.html](https://python-visualization.github.io/folium/latest/index.html)\n",
    "\n",
    "Neste artigo vamos trabalhar exibindo dados com algumas ferramentas do Folium: \n",
    "\n",
    "- Criação do mapa interativo centralizado em uma coordenada geográfica\n",
    "- MarkerCluster: posiciona um marcador na coordenada passada; agrupa marcadores próximos de acordo com o zoom\n",
    "- HeatMap: cria um ponto de calor na coordenada passada; Possibilita identificar onde possui a maior intensidade de pontos pela cor\n",
    "- HeatMapWithTime: Cria uma linha temporal em mapas de calor\n",
    "\n",
    "### Instalação\n",
    "\n",
    "A biblioteca Folium pode ser facilmente instalada usando o comando:\n",
    "\n",
    "`$ pip install folium`\n",
    "\n",
    "Se você está usando o Conda, o equivalente é\n",
    "\n",
    "`$ conda install folium -c conda-forge`\n",
    "\n",
    "### Dependências\n",
    "\n",
    "O Folium tem as seguintes dependências: branca, Jinja2, Numpy e Requests, que serão instaladas automaticamente com o comando de instalação.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Criando um mapa\n",
    "\n",
    "Esse é o exemplo mais simples para a criação de um mapa:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import folium\n",
    "\n",
    "m = folium.Map(location=(-22.9140008, -43.563634))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pronto, está criado! Mas como podemos ver?\n",
    "\n",
    "Se estivermos em um Jupyter Notebook, podemos visualizar facilmente chamando a instancia:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe srcdoc=\"&lt;!DOCTYPE html&gt;\n",
       "&lt;html&gt;\n",
       "&lt;head&gt;\n",
       "    \n",
       "    &lt;meta http-equiv=&quot;content-type&quot; content=&quot;text/html; charset=UTF-8&quot; /&gt;\n",
       "    \n",
       "        &lt;script&gt;\n",
       "            L_NO_TOUCH = false;\n",
       "            L_DISABLE_3D = false;\n",
       "        &lt;/script&gt;\n",
       "    \n",
       "    &lt;style&gt;html, body {width: 100%;height: 100%;margin: 0;padding: 0;}&lt;/style&gt;\n",
       "    &lt;style&gt;#map {position:absolute;top:0;bottom:0;right:0;left:0;}&lt;/style&gt;\n",
       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://code.jquery.com/jquery-1.12.4.min.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/js/bootstrap.bundle.min.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/css/bootstrap.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://netdna.bootstrapcdn.com/bootstrap/3.0.0/css/bootstrap.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/@fortawesome/fontawesome-free@6.2.0/css/all.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css&quot;/&gt;\n",
       "    \n",
       "            &lt;meta name=&quot;viewport&quot; content=&quot;width=device-width,\n",
       "                initial-scale=1.0, maximum-scale=1.0, user-scalable=no&quot; /&gt;\n",
       "            &lt;style&gt;\n",
       "                #map_bb7673dc3df265a44621de24d3f255c2 {\n",
       "                    position: relative;\n",
       "                    width: 100.0%;\n",
       "                    height: 100.0%;\n",
       "                    left: 0.0%;\n",
       "                    top: 0.0%;\n",
       "                }\n",
       "                .leaflet-container { font-size: 1rem; }\n",
       "            &lt;/style&gt;\n",
       "        \n",
       "&lt;/head&gt;\n",
       "&lt;body&gt;\n",
       "    \n",
       "    \n",
       "            &lt;div class=&quot;folium-map&quot; id=&quot;map_bb7673dc3df265a44621de24d3f255c2&quot; &gt;&lt;/div&gt;\n",
       "        \n",
       "&lt;/body&gt;\n",
       "&lt;script&gt;\n",
       "    \n",
       "    \n",
       "            var map_bb7673dc3df265a44621de24d3f255c2 = L.map(\n",
       "                &quot;map_bb7673dc3df265a44621de24d3f255c2&quot;,\n",
       "                {\n",
       "                    center: [-22.9140008, -43.563634],\n",
       "                    crs: L.CRS.EPSG3857,\n",
       "                    zoom: 10,\n",
       "                    zoomControl: true,\n",
       "                    preferCanvas: false,\n",
       "                }\n",
       "            );\n",
       "\n",
       "            \n",
       "\n",
       "        \n",
       "    \n",
       "            var tile_layer_b2985e7d7c44a493aa0747b10430c8ce = L.tileLayer(\n",
       "                &quot;https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png&quot;,\n",
       "                {&quot;attribution&quot;: &quot;Data by \\u0026copy; \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://openstreetmap.org\\&quot;\\u003eOpenStreetMap\\u003c/a\\u003e, under \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://www.openstreetmap.org/copyright\\&quot;\\u003eODbL\\u003c/a\\u003e.&quot;, &quot;detectRetina&quot;: false, &quot;maxNativeZoom&quot;: 18, &quot;maxZoom&quot;: 18, &quot;minZoom&quot;: 0, &quot;noWrap&quot;: false, &quot;opacity&quot;: 1, &quot;subdomains&quot;: &quot;abc&quot;, &quot;tms&quot;: false}\n",
       "            ).addTo(map_bb7673dc3df265a44621de24d3f255c2);\n",
       "        \n",
       "&lt;/script&gt;\n",
       "&lt;/html&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x2a3322f5b90>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ou podemos salvar como HTML:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "m.save(\"html/index.html\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Podemos também mudar o tipo de mapa que é exibido facilmente adicionando o argumento `tiles` e o tipo de mapa. Por padrão é carregado o tileset `OpenStreetMap` porem vamos ver como fica utilizando o `cartodb positron`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe srcdoc=\"&lt;!DOCTYPE html&gt;\n",
       "&lt;html&gt;\n",
       "&lt;head&gt;\n",
       "    \n",
       "    &lt;meta http-equiv=&quot;content-type&quot; content=&quot;text/html; charset=UTF-8&quot; /&gt;\n",
       "    \n",
       "        &lt;script&gt;\n",
       "            L_NO_TOUCH = false;\n",
       "            L_DISABLE_3D = false;\n",
       "        &lt;/script&gt;\n",
       "    \n",
       "    &lt;style&gt;html, body {width: 100%;height: 100%;margin: 0;padding: 0;}&lt;/style&gt;\n",
       "    &lt;style&gt;#map {position:absolute;top:0;bottom:0;right:0;left:0;}&lt;/style&gt;\n",
       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://code.jquery.com/jquery-1.12.4.min.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/js/bootstrap.bundle.min.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/css/bootstrap.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://netdna.bootstrapcdn.com/bootstrap/3.0.0/css/bootstrap.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/@fortawesome/fontawesome-free@6.2.0/css/all.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css&quot;/&gt;\n",
       "    \n",
       "            &lt;meta name=&quot;viewport&quot; content=&quot;width=device-width,\n",
       "                initial-scale=1.0, maximum-scale=1.0, user-scalable=no&quot; /&gt;\n",
       "            &lt;style&gt;\n",
       "                #map_721dbee2ee06cb0337adf1a9355b9863 {\n",
       "                    position: relative;\n",
       "                    width: 100.0%;\n",
       "                    height: 100.0%;\n",
       "                    left: 0.0%;\n",
       "                    top: 0.0%;\n",
       "                }\n",
       "                .leaflet-container { font-size: 1rem; }\n",
       "            &lt;/style&gt;\n",
       "        \n",
       "&lt;/head&gt;\n",
       "&lt;body&gt;\n",
       "    \n",
       "    \n",
       "            &lt;div class=&quot;folium-map&quot; id=&quot;map_721dbee2ee06cb0337adf1a9355b9863&quot; &gt;&lt;/div&gt;\n",
       "        \n",
       "&lt;/body&gt;\n",
       "&lt;script&gt;\n",
       "    \n",
       "    \n",
       "            var map_721dbee2ee06cb0337adf1a9355b9863 = L.map(\n",
       "                &quot;map_721dbee2ee06cb0337adf1a9355b9863&quot;,\n",
       "                {\n",
       "                    center: [-22.9140008, -43.563634],\n",
       "                    crs: L.CRS.EPSG3857,\n",
       "                    zoom: 10,\n",
       "                    zoomControl: true,\n",
       "                    preferCanvas: false,\n",
       "                }\n",
       "            );\n",
       "\n",
       "            \n",
       "\n",
       "        \n",
       "    \n",
       "            var tile_layer_3239b6fac637038532c8226c0c50e388 = L.tileLayer(\n",
       "                &quot;https://cartodb-basemaps-{s}.global.ssl.fastly.net/light_all/{z}/{x}/{y}.png&quot;,\n",
       "                {&quot;attribution&quot;: &quot;\\u0026copy; \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://www.openstreetmap.org/copyright\\&quot;\\u003eOpenStreetMap\\u003c/a\\u003e contributors \\u0026copy; \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://cartodb.com/attributions\\&quot;\\u003eCartoDB\\u003c/a\\u003e, CartoDB \\u003ca target=\\&quot;_blank\\&quot; href =\\&quot;http://cartodb.com/attributions\\&quot;\\u003eattributions\\u003c/a\\u003e&quot;, &quot;detectRetina&quot;: false, &quot;maxNativeZoom&quot;: 18, &quot;maxZoom&quot;: 18, &quot;minZoom&quot;: 0, &quot;noWrap&quot;: false, &quot;opacity&quot;: 1, &quot;subdomains&quot;: &quot;abc&quot;, &quot;tms&quot;: false}\n",
       "            ).addTo(map_721dbee2ee06cb0337adf1a9355b9863);\n",
       "        \n",
       "&lt;/script&gt;\n",
       "&lt;/html&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x2a323f42650>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m = folium.Map(location=(-22.9140008, -43.563634), tiles=\"cartodb positron\")\n",
    "m"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Agora que entendemos um pouco sobre a criação do mapa com o Folium, vamos trabalhar com algumas ferramentas que ele disponibiliza para a visualização dos nossos dados!\n",
    "\n",
    "Mas antes de iniciar, vamos carregar todas as libs:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import folium, googlemaps, time\n",
    "from folium.plugins import HeatMap, MarkerCluster, HeatMapWithTime\n",
    "import pandas as pd\n",
    "\n",
    "# carregando a chave api\n",
    "import dotenv, os\n",
    "%load_ext dotenv\n",
    "chave_api = os.getenv(\"API_KEY\")\n",
    "\n",
    "import warnings\n",
    "warnings.simplefilter(action='ignore', category=pd.errors.SettingWithCopyWarning)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MarkerCluster\n",
    "\n",
    "Para utilizar essa primeira ferramenta, pensei em trabalhar com dados reais, como por exemplo: Quais são os Mc Donald’s mais próximos que estão abertos nesse momento?\n",
    "\n",
    "Podemos conseguir esses dados de maneira fácil utilizando a biblioteca `googlemaps`.\n",
    "\n",
    "Instanciando o `googlemaps` com a chave API:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "client = googlemaps.Client(chave_api)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ">Caso não tenha uma chave de api do google clouds, crie uma por aqui [https://cloud.google.com/?hl=pt-BR](https://cloud.google.com/?hl=pt-BR), após criar uma, ative as API’s: Places e Geocoding."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Não tem uma chave mas quer acompanhar o tutorial? Todas as respostas recebidas pela API estão disponíveis no repositório. Carregue-as da seguinte maneira:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "with open(\"responses/01-geocode-response.json\", \"r\") as file:\n",
    "    response = json.load(file)\n",
    "\n",
    "# substitua a requisição à api pelas linhas acima\n",
    "# lembre de alterar o nome do arquivo"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Utilizando o método geocode e passando uma string referente a um endereço, nos é retornado um dicionário repleto de informações. Vamos trabalhar nesse momento somente com as coordenadas."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'lat': -22.9068467, 'lng': -43.1728965}"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "endereco = \"rio de janeiro, rj, brasil\"\n",
    "coords_endereco = client.geocode(endereco)[0][\"geometry\"][\"location\"]\n",
    "\n",
    "coords_endereco\n",
    "# {'lat': -22.9068467, 'lng': -43.1728965}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A partir dessa coordenada, vamos fazer uma busca pelos estabelecimentos próximos definindo uma query que, no nosso caso vai ser \"Mc Donald’s\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[-22.911237, -43.1759081]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lista_coordenadas = []\n",
    "keyword = \"Mc Donalds\"\n",
    "response = client.places(query=keyword, location=coords_endereco, open_now=True)\n",
    "\n",
    "for result in response[\"results\"]:\n",
    "        latitude = result[\"geometry\"][\"location\"][\"lat\"]\n",
    "        longitude = result[\"geometry\"][\"location\"][\"lng\"]\n",
    "        lista_coordenadas.append([latitude, longitude])\n",
    "\n",
    "lista_coordenadas[0]\n",
    "# [-22.9137805, -43.1666602]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Criando o mapa e adicionando os marcadores\n",
    "\n",
    "Com os dados em mãos, podemos inserir em um mapa da seguinte forma:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe srcdoc=\"&lt;!DOCTYPE html&gt;\n",
       "&lt;html&gt;\n",
       "&lt;head&gt;\n",
       "    \n",
       "    &lt;meta http-equiv=&quot;content-type&quot; content=&quot;text/html; charset=UTF-8&quot; /&gt;\n",
       "    \n",
       "        &lt;script&gt;\n",
       "            L_NO_TOUCH = false;\n",
       "            L_DISABLE_3D = false;\n",
       "        &lt;/script&gt;\n",
       "    \n",
       "    &lt;style&gt;html, body {width: 100%;height: 100%;margin: 0;padding: 0;}&lt;/style&gt;\n",
       "    &lt;style&gt;#map {position:absolute;top:0;bottom:0;right:0;left:0;}&lt;/style&gt;\n",
       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://code.jquery.com/jquery-1.12.4.min.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/js/bootstrap.bundle.min.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/css/bootstrap.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://netdna.bootstrapcdn.com/bootstrap/3.0.0/css/bootstrap.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/@fortawesome/fontawesome-free@6.2.0/css/all.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css&quot;/&gt;\n",
       "    \n",
       "            &lt;meta name=&quot;viewport&quot; content=&quot;width=device-width,\n",
       "                initial-scale=1.0, maximum-scale=1.0, user-scalable=no&quot; /&gt;\n",
       "            &lt;style&gt;\n",
       "                #map_de068b448edf7055c1a69a105ca9407b {\n",
       "                    position: relative;\n",
       "                    width: 100.0%;\n",
       "                    height: 100.0%;\n",
       "                    left: 0.0%;\n",
       "                    top: 0.0%;\n",
       "                }\n",
       "                .leaflet-container { font-size: 1rem; }\n",
       "            &lt;/style&gt;\n",
       "        \n",
       "    &lt;script src=&quot;https://cdnjs.cloudflare.com/ajax/libs/leaflet.markercluster/1.1.0/leaflet.markercluster.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdnjs.cloudflare.com/ajax/libs/leaflet.markercluster/1.1.0/MarkerCluster.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdnjs.cloudflare.com/ajax/libs/leaflet.markercluster/1.1.0/MarkerCluster.Default.css&quot;/&gt;\n",
       "&lt;/head&gt;\n",
       "&lt;body&gt;\n",
       "    \n",
       "    \n",
       "            &lt;div class=&quot;folium-map&quot; id=&quot;map_de068b448edf7055c1a69a105ca9407b&quot; &gt;&lt;/div&gt;\n",
       "        \n",
       "&lt;/body&gt;\n",
       "&lt;script&gt;\n",
       "    \n",
       "    \n",
       "            var map_de068b448edf7055c1a69a105ca9407b = L.map(\n",
       "                &quot;map_de068b448edf7055c1a69a105ca9407b&quot;,\n",
       "                {\n",
       "                    center: [-22.911237, -43.1759081],\n",
       "                    crs: L.CRS.EPSG3857,\n",
       "                    zoom: 13,\n",
       "                    zoomControl: true,\n",
       "                    preferCanvas: false,\n",
       "                }\n",
       "            );\n",
       "\n",
       "            \n",
       "\n",
       "        \n",
       "    \n",
       "            var tile_layer_021eedc767a3dfe31a6303edf2b5d9f7 = L.tileLayer(\n",
       "                &quot;https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png&quot;,\n",
       "                {&quot;attribution&quot;: &quot;Data by \\u0026copy; \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://openstreetmap.org\\&quot;\\u003eOpenStreetMap\\u003c/a\\u003e, under \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://www.openstreetmap.org/copyright\\&quot;\\u003eODbL\\u003c/a\\u003e.&quot;, &quot;detectRetina&quot;: false, &quot;maxNativeZoom&quot;: 18, &quot;maxZoom&quot;: 18, &quot;minZoom&quot;: 0, &quot;noWrap&quot;: false, &quot;opacity&quot;: 1, &quot;subdomains&quot;: &quot;abc&quot;, &quot;tms&quot;: false}\n",
       "            ).addTo(map_de068b448edf7055c1a69a105ca9407b);\n",
       "        \n",
       "    \n",
       "            var marker_cluster_ca2572a16f26ed5f48100d2cc0f6b72e = L.markerClusterGroup(\n",
       "                {}\n",
       "            );\n",
       "            map_de068b448edf7055c1a69a105ca9407b.addLayer(marker_cluster_ca2572a16f26ed5f48100d2cc0f6b72e);\n",
       "        \n",
       "    \n",
       "            var marker_cluster_d6cc83d200e8741f4444b0c0e68d1836 = L.markerClusterGroup(\n",
       "                {}\n",
       "            );\n",
       "            map_de068b448edf7055c1a69a105ca9407b.addLayer(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_6957414a6078262d276f12aaeff59995 = L.marker(\n",
       "                [-22.911237, -43.1759081],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_272983255f93de3e7bddc4aa61b55ff7 = L.marker(\n",
       "                [-22.9144468, -43.1667085],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_ff54004c39d8dce101a8ae58536de261 = L.marker(\n",
       "                [-22.9137805, -43.1666602],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_1c96cfeefb1d6cc608787ed2b402143b = L.marker(\n",
       "                [-22.8975716, -43.180642],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_56a9efe6375efb82f16244f5f5c02ec0 = L.marker(\n",
       "                [-22.9031106, -43.1913556],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_04fcf4881773d0db57945f10f0e5baaa = L.marker(\n",
       "                [-22.9298424, -43.1777513],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_1a5a8fd852693c86278c20bdb4cb04ca = L.marker(\n",
       "                [-22.9145932, -43.2192686],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_56c5962fb219b7e7371a3fd4e8b84f63 = L.marker(\n",
       "                [-22.9474791, -43.1831975],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_61917e89e83b0fe17fb018c421e2c407 = L.marker(\n",
       "                [-22.9537762, -43.19129650000001],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_119137c83c69a58ca8606e2884e062ff = L.marker(\n",
       "                [-22.9574415, -43.176208],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_1be3cf5d3c93f0da66674962e5cedcfc = L.marker(\n",
       "                [-22.8964934, -43.1243923],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_0c935e1be8ec0bdad91692559cb9df1f = L.marker(\n",
       "                [-22.896859, -43.1236835],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_d588e9e91aea47a904912dadf67a9ac7 = L.marker(\n",
       "                [-22.8920359, -43.1240684],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_1538563e51865b1164896b610ee98674 = L.marker(\n",
       "                [-22.9227329, -43.2341956],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_6e14274270dbfcc69d8808c44bf0a05e = L.marker(\n",
       "                [-22.9630126, -43.1742389],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_bcd6b8c733bb180fd2ec81f6db1a3d1f = L.marker(\n",
       "                [-22.9018282, -43.1122963],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_2db7195c8d9933eafd212766c6d5f675 = L.marker(\n",
       "                [-22.9189083, -43.219403],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_62641f34f39820e325fbd4f22086371a = L.marker(\n",
       "                [-22.9219385, -43.2353733],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_2fadd3ffe41e2bde9aac7a1e4c0887ef = L.marker(\n",
       "                [-22.907383, -43.10999820000001],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_0314facff56016297795ee0f476730a5 = L.marker(\n",
       "                [-22.9681457, -43.183966],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "&lt;/script&gt;\n",
       "&lt;/html&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x2a3335e5450>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mapa = folium.Map(location= lista_coordenadas[0], zoom_start= 13)\n",
    "marker = MarkerCluster().add_to(mapa)\n",
    "\n",
    "MarkerCluster(locations=lista_coordenadas).add_to(mapa)\n",
    "mapa.save('mcdonalds_nearby_marker.html')\n",
    "mapa"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Dessa vez definimos um zoom inicial para o nosso mapa com o `zoom_start=13`\n",
    "\n",
    "O argumento `locations` recebe uma lista de coordenadas e para cada uma delas insere um marcador no respectivo local do mapa.\n",
    "\n",
    "Podemos também estilizar o marcador, com os argumentos:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe srcdoc=\"&lt;!DOCTYPE html&gt;\n",
       "&lt;html&gt;\n",
       "&lt;head&gt;\n",
       "    \n",
       "    &lt;meta http-equiv=&quot;content-type&quot; content=&quot;text/html; charset=UTF-8&quot; /&gt;\n",
       "    \n",
       "        &lt;script&gt;\n",
       "            L_NO_TOUCH = false;\n",
       "            L_DISABLE_3D = false;\n",
       "        &lt;/script&gt;\n",
       "    \n",
       "    &lt;style&gt;html, body {width: 100%;height: 100%;margin: 0;padding: 0;}&lt;/style&gt;\n",
       "    &lt;style&gt;#map {position:absolute;top:0;bottom:0;right:0;left:0;}&lt;/style&gt;\n",
       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://code.jquery.com/jquery-1.12.4.min.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/js/bootstrap.bundle.min.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/css/bootstrap.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://netdna.bootstrapcdn.com/bootstrap/3.0.0/css/bootstrap.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/@fortawesome/fontawesome-free@6.2.0/css/all.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css&quot;/&gt;\n",
       "    \n",
       "            &lt;meta name=&quot;viewport&quot; content=&quot;width=device-width,\n",
       "                initial-scale=1.0, maximum-scale=1.0, user-scalable=no&quot; /&gt;\n",
       "            &lt;style&gt;\n",
       "                #map_de068b448edf7055c1a69a105ca9407b {\n",
       "                    position: relative;\n",
       "                    width: 100.0%;\n",
       "                    height: 100.0%;\n",
       "                    left: 0.0%;\n",
       "                    top: 0.0%;\n",
       "                }\n",
       "                .leaflet-container { font-size: 1rem; }\n",
       "            &lt;/style&gt;\n",
       "        \n",
       "    &lt;script src=&quot;https://cdnjs.cloudflare.com/ajax/libs/leaflet.markercluster/1.1.0/leaflet.markercluster.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdnjs.cloudflare.com/ajax/libs/leaflet.markercluster/1.1.0/MarkerCluster.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdnjs.cloudflare.com/ajax/libs/leaflet.markercluster/1.1.0/MarkerCluster.Default.css&quot;/&gt;\n",
       "&lt;/head&gt;\n",
       "&lt;body&gt;\n",
       "    \n",
       "    \n",
       "            &lt;div class=&quot;folium-map&quot; id=&quot;map_de068b448edf7055c1a69a105ca9407b&quot; &gt;&lt;/div&gt;\n",
       "        \n",
       "&lt;/body&gt;\n",
       "&lt;script&gt;\n",
       "    \n",
       "    \n",
       "            var map_de068b448edf7055c1a69a105ca9407b = L.map(\n",
       "                &quot;map_de068b448edf7055c1a69a105ca9407b&quot;,\n",
       "                {\n",
       "                    center: [-22.911237, -43.1759081],\n",
       "                    crs: L.CRS.EPSG3857,\n",
       "                    zoom: 13,\n",
       "                    zoomControl: true,\n",
       "                    preferCanvas: false,\n",
       "                }\n",
       "            );\n",
       "\n",
       "            \n",
       "\n",
       "        \n",
       "    \n",
       "            var tile_layer_021eedc767a3dfe31a6303edf2b5d9f7 = L.tileLayer(\n",
       "                &quot;https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png&quot;,\n",
       "                {&quot;attribution&quot;: &quot;Data by \\u0026copy; \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://openstreetmap.org\\&quot;\\u003eOpenStreetMap\\u003c/a\\u003e, under \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://www.openstreetmap.org/copyright\\&quot;\\u003eODbL\\u003c/a\\u003e.&quot;, &quot;detectRetina&quot;: false, &quot;maxNativeZoom&quot;: 18, &quot;maxZoom&quot;: 18, &quot;minZoom&quot;: 0, &quot;noWrap&quot;: false, &quot;opacity&quot;: 1, &quot;subdomains&quot;: &quot;abc&quot;, &quot;tms&quot;: false}\n",
       "            ).addTo(map_de068b448edf7055c1a69a105ca9407b);\n",
       "        \n",
       "    \n",
       "            var marker_cluster_ca2572a16f26ed5f48100d2cc0f6b72e = L.markerClusterGroup(\n",
       "                {}\n",
       "            );\n",
       "            map_de068b448edf7055c1a69a105ca9407b.addLayer(marker_cluster_ca2572a16f26ed5f48100d2cc0f6b72e);\n",
       "        \n",
       "    \n",
       "            var marker_cluster_d6cc83d200e8741f4444b0c0e68d1836 = L.markerClusterGroup(\n",
       "                {}\n",
       "            );\n",
       "            map_de068b448edf7055c1a69a105ca9407b.addLayer(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_6957414a6078262d276f12aaeff59995 = L.marker(\n",
       "                [-22.911237, -43.1759081],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_272983255f93de3e7bddc4aa61b55ff7 = L.marker(\n",
       "                [-22.9144468, -43.1667085],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_ff54004c39d8dce101a8ae58536de261 = L.marker(\n",
       "                [-22.9137805, -43.1666602],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_1c96cfeefb1d6cc608787ed2b402143b = L.marker(\n",
       "                [-22.8975716, -43.180642],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_56a9efe6375efb82f16244f5f5c02ec0 = L.marker(\n",
       "                [-22.9031106, -43.1913556],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_04fcf4881773d0db57945f10f0e5baaa = L.marker(\n",
       "                [-22.9298424, -43.1777513],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_1a5a8fd852693c86278c20bdb4cb04ca = L.marker(\n",
       "                [-22.9145932, -43.2192686],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_56c5962fb219b7e7371a3fd4e8b84f63 = L.marker(\n",
       "                [-22.9474791, -43.1831975],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_61917e89e83b0fe17fb018c421e2c407 = L.marker(\n",
       "                [-22.9537762, -43.19129650000001],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_119137c83c69a58ca8606e2884e062ff = L.marker(\n",
       "                [-22.9574415, -43.176208],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_1be3cf5d3c93f0da66674962e5cedcfc = L.marker(\n",
       "                [-22.8964934, -43.1243923],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_0c935e1be8ec0bdad91692559cb9df1f = L.marker(\n",
       "                [-22.896859, -43.1236835],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_d588e9e91aea47a904912dadf67a9ac7 = L.marker(\n",
       "                [-22.8920359, -43.1240684],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_1538563e51865b1164896b610ee98674 = L.marker(\n",
       "                [-22.9227329, -43.2341956],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_6e14274270dbfcc69d8808c44bf0a05e = L.marker(\n",
       "                [-22.9630126, -43.1742389],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_bcd6b8c733bb180fd2ec81f6db1a3d1f = L.marker(\n",
       "                [-22.9018282, -43.1122963],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_2db7195c8d9933eafd212766c6d5f675 = L.marker(\n",
       "                [-22.9189083, -43.219403],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_62641f34f39820e325fbd4f22086371a = L.marker(\n",
       "                [-22.9219385, -43.2353733],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_2fadd3ffe41e2bde9aac7a1e4c0887ef = L.marker(\n",
       "                [-22.907383, -43.10999820000001],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_0314facff56016297795ee0f476730a5 = L.marker(\n",
       "                [-22.9681457, -43.183966],\n",
       "                {}\n",
       "            ).addTo(marker_cluster_d6cc83d200e8741f4444b0c0e68d1836);\n",
       "        \n",
       "    \n",
       "            var marker_ca6276563a9f3bf3b5cb5a4cfb1da324 = L.marker(\n",
       "                [-22.9068467, -43.1728965],\n",
       "                {}\n",
       "            ).addTo(map_de068b448edf7055c1a69a105ca9407b);\n",
       "        \n",
       "    \n",
       "            var icon_369e88297f6f4d419d1819a54c45e6f6 = L.AwesomeMarkers.icon(\n",
       "                {&quot;extraClasses&quot;: &quot;fa-rotate-0&quot;, &quot;icon&quot;: &quot;user&quot;, &quot;iconColor&quot;: &quot;white&quot;, &quot;markerColor&quot;: &quot;red&quot;, &quot;prefix&quot;: &quot;glyphicon&quot;}\n",
       "            );\n",
       "            marker_ca6276563a9f3bf3b5cb5a4cfb1da324.setIcon(icon_369e88297f6f4d419d1819a54c45e6f6);\n",
       "        \n",
       "    \n",
       "        var popup_2fe44a99a1e47bbdff1d1e716bd82eb4 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_ab2ba5bcb98690f3392e49e1100645ee = $(`&lt;div id=&quot;html_ab2ba5bcb98690f3392e49e1100645ee&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Informações&lt;/div&gt;`)[0];\n",
       "                popup_2fe44a99a1e47bbdff1d1e716bd82eb4.setContent(html_ab2ba5bcb98690f3392e49e1100645ee);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_ca6276563a9f3bf3b5cb5a4cfb1da324.bindPopup(popup_2fe44a99a1e47bbdff1d1e716bd82eb4)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            marker_ca6276563a9f3bf3b5cb5a4cfb1da324.bindTooltip(\n",
       "                `&lt;div&gt;\n",
       "                     Rio de Janeiro\n",
       "                 &lt;/div&gt;`,\n",
       "                {&quot;sticky&quot;: true}\n",
       "            );\n",
       "        \n",
       "&lt;/script&gt;\n",
       "&lt;/html&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x2a3335e5450>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "folium.Marker(\n",
    "    location=[-22.9068467, -43.1728965],\n",
    "    tooltip=\"Rio de Janeiro\",\n",
    "    popup=\"Informações\",\n",
    "    icon=folium.Icon(icon=\"user\", color=\"red\"),\n",
    ").add_to(mapa)\n",
    "mapa\n",
    "# Veja mais opções em: https://github.com/lennardv2/Leaflet.awesome-markers e \n",
    "# https://fontawesome.com/search?s=solid&f=classic&o=r"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Podemos então concluir que é bem simples apresentar esses dados em um mapa, permitindo uma exploração interativa para análises e insights geográficos. Mas vamos explorar mais algumas ferramentas. Dessa vez vamos tentar com um mapa de calor."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## HeatMap\n",
    "\n",
    "Um gráfico de calor em um mapa, pode nos ajudar a obter informações valiosas. O mapa de calor facilita a identificação de repetições e padrões em coordenadas geoespaciais.\n",
    "\n",
    "Para exemplificar com dados reais um mapa de calor, vamos buscar as coordenadas de todos os *Mc Donald’s* de uma cidade. Vamos fazer uma busca parecida com a anterior, porém com um raio maior. Também vamos coletar um pouco mais de dados da resposta, para limpar e refinar os resultados. E para isso, nada melhor que usar o amigo do analista de dados, sim, estou falando do `Pandas`. 🐼\n",
    "\n",
    "Vamos começar fazendo uma nova requisição, utilizando agora o `places_nearby()` para definir um raio maior de busca."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>nome</th>\n",
       "      <th>endereco</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>McDonald's</td>\n",
       "      <td>Av. Jorn. Roberto Marinho, 231 - box 301/302 -...</td>\n",
       "      <td>-22.826635</td>\n",
       "      <td>-43.015602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>McDonald's</td>\n",
       "      <td>Praça Floriano, 19 - Centro, Rio de Janeiro</td>\n",
       "      <td>-22.911237</td>\n",
       "      <td>-43.175908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>McDonald's</td>\n",
       "      <td>R. Dr. Felíciano Sodré, 260 - Centro, São Gonçalo</td>\n",
       "      <td>-22.823476</td>\n",
       "      <td>-43.046556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>McDonald's</td>\n",
       "      <td>Av. das Américas, 14801 - Recreio dos Bandeira...</td>\n",
       "      <td>-23.012553</td>\n",
       "      <td>-43.457515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>McDonald's</td>\n",
       "      <td>R. Mariz e Barros, 525 - Maracanã, Rio de Janeiro</td>\n",
       "      <td>-22.914593</td>\n",
       "      <td>-43.219269</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          nome                                           endereco   latitude  \\\n",
       "50  McDonald's  Av. Jorn. Roberto Marinho, 231 - box 301/302 -... -22.826635   \n",
       "18  McDonald's        Praça Floriano, 19 - Centro, Rio de Janeiro -22.911237   \n",
       "1   McDonald's  R. Dr. Felíciano Sodré, 260 - Centro, São Gonçalo -22.823476   \n",
       "54  McDonald's  Av. das Américas, 14801 - Recreio dos Bandeira... -23.012553   \n",
       "2   McDonald's  R. Mariz e Barros, 525 - Maracanã, Rio de Janeiro -22.914593   \n",
       "\n",
       "    longitude  \n",
       "50 -43.015602  \n",
       "18 -43.175908  \n",
       "1  -43.046556  \n",
       "54 -43.457515  \n",
       "2  -43.219269  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lista_dfs = []\n",
    "keyword = \"Mc Donalds\"\n",
    "response = client.places_nearby(location=coords_endereco, keyword=keyword, radius=50000)\n",
    "\n",
    "while True:\n",
    "    time.sleep(0.1)\n",
    "\n",
    "    for store in response[\"results\"]:\n",
    "        df = pd.DataFrame(\n",
    "            {\n",
    "                \"nome\": store[\"name\"],\n",
    "                \"endereco\": store[\"vicinity\"],\n",
    "                \"latitude\": store[\"geometry\"][\"location\"][\"lat\"],\n",
    "                \"longitude\": store[\"geometry\"][\"location\"][\"lng\"],\n",
    "            },\n",
    "            index=[0],\n",
    "        )\n",
    "        lista_dfs.append(df)\n",
    "\n",
    "    if \"next_page_token\" in response:\n",
    "        next_page_token = response[\"next_page_token\"]\n",
    "        time.sleep(2.3)\n",
    "        response = client.places_nearby(\n",
    "            location=coords_endereco,\n",
    "            keyword=keyword,\n",
    "            radius=50000,\n",
    "            page_token=next_page_token,\n",
    "        )\n",
    "\n",
    "    else:\n",
    "        break\n",
    "\n",
    "df_resultados = pd.concat(lista_dfs, ignore_index=True)\n",
    "df_resultados.sample(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Como são muitos resultados, a API divide-os em páginas e envia na resposta um token para a próxima.\n",
    "- Após a primeira requisição é iniciado um loop infinito, que é interrompido quando não tem mais páginas. Dentro do loop é iniciado um for loop que itera por cada resultado da página, criando um dataframe para cada um.\n",
    "- Caso a página tenha um token para a próxima página, é feito uma nova requisição incluindo esse token como argumento.\n",
    "- Por fim, fazemos uma concatenação de DataFrames com `pd.concat()`\n",
    "\n",
    "> Importante: Evite utilizar o método concat() dentro de loops, isso pode resultar em uma grande perca de eficiência. Para casos como esse, guarde os DataFrames em uma lista temporária e, ao final do loop, utilize o pd.concat() para unir todos os DataFrames da lista.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Tratando os dados\n",
    "\n",
    "Após criar o DataFrame com todos os resultados, podemos trata-los para remover possíveis resultados indesejados ou duplicados.\n",
    "\n",
    "E com os dados limpos, podemos salvar apenas o que nos interessa: as coordenadas."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Quantidade de resultados: 60\n",
      "Exemplo de resultado: [-22.9056077 -43.1761831]\n"
     ]
    }
   ],
   "source": [
    "lojas_mc_filtrado = df_resultados[\n",
    "    (df_resultados[\"nome\"].str.lower().str.contains(\"mcdonald\"))\n",
    "    | df_resultados[\"nome\"].str.lower().str.contains(\"mc donald\")\n",
    "]\n",
    "lojas_mc_filtrado = lojas_mc_filtrado.drop_duplicates(subset=\"endereco\")\n",
    "\n",
    "lista_coordenadas = lojas_mc_filtrado[['latitude', 'longitude']].values\n",
    "\n",
    "print('Quantidade de resultados:', len(lista_coordenadas))\n",
    "# Quantidade de resultados: 60\n",
    "print('Exemplo de resultado:', lista_coordenadas[0])\n",
    "# Exemplo de resultado: [-22.9056077 -43.1761831]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plotando os dados no mapa\n",
    "\n",
    "Agora vamos utilizar o plugin HeatMap para criar os pontos de calor e em seguida adicionar no mapa com a função `add_to()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe srcdoc=\"&lt;!DOCTYPE html&gt;\n",
       "&lt;html&gt;\n",
       "&lt;head&gt;\n",
       "    \n",
       "    &lt;meta http-equiv=&quot;content-type&quot; content=&quot;text/html; charset=UTF-8&quot; /&gt;\n",
       "    \n",
       "        &lt;script&gt;\n",
       "            L_NO_TOUCH = false;\n",
       "            L_DISABLE_3D = false;\n",
       "        &lt;/script&gt;\n",
       "    \n",
       "    &lt;style&gt;html, body {width: 100%;height: 100%;margin: 0;padding: 0;}&lt;/style&gt;\n",
       "    &lt;style&gt;#map {position:absolute;top:0;bottom:0;right:0;left:0;}&lt;/style&gt;\n",
       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://code.jquery.com/jquery-1.12.4.min.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/js/bootstrap.bundle.min.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/css/bootstrap.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://netdna.bootstrapcdn.com/bootstrap/3.0.0/css/bootstrap.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/@fortawesome/fontawesome-free@6.2.0/css/all.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css&quot;/&gt;\n",
       "    \n",
       "            &lt;meta name=&quot;viewport&quot; content=&quot;width=device-width,\n",
       "                initial-scale=1.0, maximum-scale=1.0, user-scalable=no&quot; /&gt;\n",
       "            &lt;style&gt;\n",
       "                #map_aa15ba022f454917764ae9938d01af2e {\n",
       "                    position: relative;\n",
       "                    width: 100.0%;\n",
       "                    height: 100.0%;\n",
       "                    left: 0.0%;\n",
       "                    top: 0.0%;\n",
       "                }\n",
       "                .leaflet-container { font-size: 1rem; }\n",
       "            &lt;/style&gt;\n",
       "        \n",
       "    &lt;script src=&quot;https://cdn.jsdelivr.net/gh/python-visualization/folium@main/folium/templates/leaflet_heat.min.js&quot;&gt;&lt;/script&gt;\n",
       "&lt;/head&gt;\n",
       "&lt;body&gt;\n",
       "    \n",
       "    \n",
       "            &lt;div class=&quot;folium-map&quot; id=&quot;map_aa15ba022f454917764ae9938d01af2e&quot; &gt;&lt;/div&gt;\n",
       "        \n",
       "&lt;/body&gt;\n",
       "&lt;script&gt;\n",
       "    \n",
       "    \n",
       "            var map_aa15ba022f454917764ae9938d01af2e = L.map(\n",
       "                &quot;map_aa15ba022f454917764ae9938d01af2e&quot;,\n",
       "                {\n",
       "                    center: [-22.9068467, -43.1728965],\n",
       "                    crs: L.CRS.EPSG3857,\n",
       "                    zoom: 11,\n",
       "                    zoomControl: true,\n",
       "                    preferCanvas: false,\n",
       "                }\n",
       "            );\n",
       "\n",
       "            \n",
       "\n",
       "        \n",
       "    \n",
       "            var tile_layer_d85d08d49dbd693ef5be27c45e9f4a10 = L.tileLayer(\n",
       "                &quot;https://cartodb-basemaps-{s}.global.ssl.fastly.net/dark_all/{z}/{x}/{y}.png&quot;,\n",
       "                {&quot;attribution&quot;: &quot;\\u0026copy; \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://www.openstreetmap.org/copyright\\&quot;\\u003eOpenStreetMap\\u003c/a\\u003e contributors \\u0026copy; \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://cartodb.com/attributions\\&quot;\\u003eCartoDB\\u003c/a\\u003e, CartoDB \\u003ca target=\\&quot;_blank\\&quot; href =\\&quot;http://cartodb.com/attributions\\&quot;\\u003eattributions\\u003c/a\\u003e&quot;, &quot;detectRetina&quot;: false, &quot;maxNativeZoom&quot;: 18, &quot;maxZoom&quot;: 18, &quot;minZoom&quot;: 0, &quot;noWrap&quot;: false, &quot;opacity&quot;: 1, &quot;subdomains&quot;: &quot;abc&quot;, &quot;tms&quot;: false}\n",
       "            ).addTo(map_aa15ba022f454917764ae9938d01af2e);\n",
       "        \n",
       "    \n",
       "            var heat_map_fb9dbefb721b5fc2fb74a3da21b318ad = L.heatLayer(\n",
       "                [[-22.9056077, -43.1761831], [-22.8234761, -43.046556], [-22.9145932, -43.2192686], [-22.9227329, -43.2341956], [-22.9766704, -43.1901489], [-22.9836616, -43.2198192], [-22.9708847, -43.1864104], [-22.9044687, -43.1771804], [-22.8867701, -43.2884083], [-22.9829281, -43.3623799], [-23.021557, -43.48862], [-22.7613374, -43.45578949999999], [-22.9233385, -43.2492723], [-22.9033773, -43.1784808], [-22.9681457, -43.183966], [-23.0140988, -43.4675742], [-22.9537762, -43.19129650000001], [-22.9992305, -43.40508519999999], [-22.911237, -43.1759081], [-22.9219385, -43.2353733], [-22.9124164, -43.1666883], [-22.9031303, -43.2830114], [-22.9474791, -43.1831975], [-22.9024087, -43.1811066], [-22.9298424, -43.1777513], [-22.9574415, -43.176208], [-22.9845734, -43.2026622], [-22.870455, -43.3410831], [-22.9412594, -43.34463119999999], [-22.9890673, -43.3614967], [-22.8975716, -43.180642], [-22.8215742, -43.408192], [-22.9250863, -43.3609062], [-22.9271647, -43.34326189999999], [-22.9149532, -43.09479140000001], [-23.0011775, -43.33365690000001], [-22.8739388, -43.3372739], [-23.0180754, -43.4788726], [-22.8393943, -43.3108028], [-23.0102629, -43.4606111], [-22.8764928, -43.370831], [-22.8057239, -43.2103308], [-22.9844728, -43.3665311], [-22.8836914, -43.2845608], [-22.9144468, -43.1667085], [-22.7887249, -43.3108831], [-22.8786423, -43.4682068], [-22.8860505, -43.4027717], [-22.7894959, -43.2861486], [-22.9014988, -43.2799205], [-22.8266354, -43.0156016], [-22.8249268, -43.3127757], [-22.9274502, -43.5748104], [-22.9745703, -43.4142342], [-23.0125527, -43.4575148], [-22.9630126, -43.1742389], [-22.798007, -43.351973], [-22.9140008, -43.563634], [-22.8660554, -43.2552268], [-22.8329122, -43.32723]],\n",
       "                {&quot;blur&quot;: 15, &quot;maxZoom&quot;: 18, &quot;minOpacity&quot;: 0.5, &quot;radius&quot;: 30}\n",
       "            ).addTo(map_aa15ba022f454917764ae9938d01af2e);\n",
       "        \n",
       "&lt;/script&gt;\n",
       "&lt;/html&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x2a333640750>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "map_calor = folium.Map(location=list(coords_endereco.values()), zoom_start=11, tiles=\"Cartodb dark_matter\",)\n",
    "HeatMap(lista_coordenadas, radius= 30).add_to(map_calor)\n",
    "map_calor.save('mcdonalds_heatmap.html')\n",
    "map_calor"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Com dados parecidos aos anteriores porém em maior escala podemos identificar facilmente pontos de maior cobertura dos restaurantes."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## HeatmapWithTime\n",
    "\n",
    "O mapa de calor com tempo possibilita visualizar de uma forma dinâmica como os pontos do mapa evoluem ao longo do tempo. Esse recurso é amplamente utilizado em diversas áreas, como na analise de tráfego de veículos ao longo do dia ou mapeamento de jogadores em esportes ao longo das partidas, entre muitos outros exemplos.\n",
    "\n",
    "Para exemplificar essa ferramenta vamos trabalhar usando a data de abertura das lojas da empresa renner (disponibilizadas publicamente em seu site: https://lojasrenner.mzweb.com.br/) e analisar o avanço da cobertura da empresa pelo país ao longo do tempo.\n",
    "\n",
    "### Carregando e tratando dados\n",
    "\n",
    "Partindo do zero: vamos puxar todos os dados da planilha com a função `pd.read_excel()`. \n",
    "\n",
    "- Com o argumento `sheet_name` devemos passar o nome referente a aba que contem a lista de lojas.\n",
    "- Em `skiprows` vamos passar quantas linhas devemos pular de cabeçalho\n",
    "- E finalmente em `usecols`, selecionaremos as colunas que vamos começar a trabalhar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>Opening date</th>\n",
       "      <th>Country</th>\n",
       "      <th>UF</th>\n",
       "      <th>State</th>\n",
       "      <th>City</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2023-10-17 00:00:00</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>MG</td>\n",
       "      <td>Minas Gerais</td>\n",
       "      <td>Ituiutaba</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2023-10-11 00:00:00</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>SC</td>\n",
       "      <td>Santa Catarina</td>\n",
       "      <td>Videira</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2023-09-20 00:00:00</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>ES</td>\n",
       "      <td>Espírito Santo</td>\n",
       "      <td>Vitória</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2023-09-15 00:00:00</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>PB</td>\n",
       "      <td>Paraíba</td>\n",
       "      <td>João Pessoa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2023-09-09 00:00:00</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>GO</td>\n",
       "      <td>Goiás</td>\n",
       "      <td>Goiânia</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>764</th>\n",
       "      <td>41</td>\n",
       "      <td>4</td>\n",
       "      <td>57</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>765</th>\n",
       "      <td>118</td>\n",
       "      <td>46</td>\n",
       "      <td>205</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>766</th>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>767</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>768</th>\n",
       "      <td>423</td>\n",
       "      <td>118</td>\n",
       "      <td>665</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>769 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Opening date Country   UF           State         City\n",
       "0    2023-10-17 00:00:00  Brazil   MG    Minas Gerais    Ituiutaba\n",
       "1    2023-10-11 00:00:00  Brazil   SC  Santa Catarina      Videira\n",
       "2    2023-09-20 00:00:00  Brazil   ES  Espírito Santo      Vitória\n",
       "3    2023-09-15 00:00:00  Brazil   PB         Paraíba  João Pessoa\n",
       "4    2023-09-09 00:00:00  Brazil   GO           Goiás      Goiânia\n",
       "..                   ...     ...  ...             ...          ...\n",
       "764                   41       4   57             NaN          NaN\n",
       "765                  118      46  205             NaN          NaN\n",
       "766                   10       0   10             NaN          NaN\n",
       "767                    4       0    4             NaN          NaN\n",
       "768                  423     118  665             NaN          NaN\n",
       "\n",
       "[769 rows x 5 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_excel(\n",
    "    \"Planilhas e Fundamentos .xlsm\", \n",
    "    sheet_name= 'Lista de Lojas | Stores List', \n",
    "    skiprows= 5,\n",
    "    usecols = ['Opening date', 'Country', 'UF', 'State', 'City'])\n",
    "\n",
    "df_renner = df.copy()\n",
    "df_renner"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ">Pessoalmente gosto de criar copias de requisições ou de dataframes carregados de arquivos para não precisar executar a operação novamente caso faça algo errado durante a analise."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>Opening date</th>\n",
       "      <th>Country</th>\n",
       "      <th>UF</th>\n",
       "      <th>State</th>\n",
       "      <th>City</th>\n",
       "      <th>Address</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2023-10-17</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>MG</td>\n",
       "      <td>Minas Gerais</td>\n",
       "      <td>Ituiutaba</td>\n",
       "      <td>Ituiutaba - Minas Gerais - Brazil</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2023-10-11</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>SC</td>\n",
       "      <td>Santa Catarina</td>\n",
       "      <td>Videira</td>\n",
       "      <td>Videira - Santa Catarina - Brazil</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2023-09-20</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>ES</td>\n",
       "      <td>Espírito Santo</td>\n",
       "      <td>Vitória</td>\n",
       "      <td>Vitória - Espírito Santo - Brazil</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2023-09-15</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>PB</td>\n",
       "      <td>Paraíba</td>\n",
       "      <td>João Pessoa</td>\n",
       "      <td>João Pessoa - Paraíba - Brazil</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2023-09-09</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>GO</td>\n",
       "      <td>Goiás</td>\n",
       "      <td>Goiânia</td>\n",
       "      <td>Goiânia - Goiás - Brazil</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Opening date Country  UF           State         City  \\\n",
       "0   2023-10-17  Brazil  MG    Minas Gerais    Ituiutaba   \n",
       "1   2023-10-11  Brazil  SC  Santa Catarina      Videira   \n",
       "2   2023-09-20  Brazil  ES  Espírito Santo      Vitória   \n",
       "3   2023-09-15  Brazil  PB         Paraíba  João Pessoa   \n",
       "4   2023-09-09  Brazil  GO           Goiás      Goiânia   \n",
       "\n",
       "                             Address  \n",
       "0  Ituiutaba - Minas Gerais - Brazil  \n",
       "1  Videira - Santa Catarina - Brazil  \n",
       "2  Vitória - Espírito Santo - Brazil  \n",
       "3     João Pessoa - Paraíba - Brazil  \n",
       "4           Goiânia - Goiás - Brazil  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# removendo dados faltantes\n",
    "df_renner.dropna(inplace= True)\n",
    "\n",
    "# tratando a data de abertura\n",
    "df_renner['Opening date'] = pd.to_datetime(df_renner['Opening date']) \n",
    "\n",
    "# filtrando o pais\n",
    "df_renner = df_renner[df_renner['Country'] == 'Brazil']\n",
    "\n",
    "# criando uma coluna com endereco\n",
    "df_renner['Address'] = df_renner.apply(lambda row: f\"{row['City']} - {row['State']} - {row['Country']}\", axis= 1)\n",
    "\n",
    "df_renner.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Com os dados do endereço agora podemos fazer uma requisição ao geocode para obter as coordenadas do local e salvar em uma nova coluna."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>Opening date</th>\n",
       "      <th>Country</th>\n",
       "      <th>UF</th>\n",
       "      <th>State</th>\n",
       "      <th>City</th>\n",
       "      <th>Address</th>\n",
       "      <th>Coords</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2023-10-17</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>MG</td>\n",
       "      <td>Minas Gerais</td>\n",
       "      <td>Ituiutaba</td>\n",
       "      <td>Ituiutaba - Minas Gerais - Brazil</td>\n",
       "      <td>(-18.9745738, -49.4600885)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2023-10-11</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>SC</td>\n",
       "      <td>Santa Catarina</td>\n",
       "      <td>Videira</td>\n",
       "      <td>Videira - Santa Catarina - Brazil</td>\n",
       "      <td>(-27.0052075, -51.15439500000001)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2023-09-20</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>ES</td>\n",
       "      <td>Espírito Santo</td>\n",
       "      <td>Vitória</td>\n",
       "      <td>Vitória - Espírito Santo - Brazil</td>\n",
       "      <td>(-20.3196644, -40.3384748)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2023-09-15</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>PB</td>\n",
       "      <td>Paraíba</td>\n",
       "      <td>João Pessoa</td>\n",
       "      <td>João Pessoa - Paraíba - Brazil</td>\n",
       "      <td>(-7.118835199999999, -34.8814339)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Opening date Country  UF           State         City  \\\n",
       "0   2023-10-17  Brazil  MG    Minas Gerais    Ituiutaba   \n",
       "1   2023-10-11  Brazil  SC  Santa Catarina      Videira   \n",
       "2   2023-09-20  Brazil  ES  Espírito Santo      Vitória   \n",
       "3   2023-09-15  Brazil  PB         Paraíba  João Pessoa   \n",
       "\n",
       "                             Address                             Coords  \n",
       "0  Ituiutaba - Minas Gerais - Brazil         (-18.9745738, -49.4600885)  \n",
       "1  Videira - Santa Catarina - Brazil  (-27.0052075, -51.15439500000001)  \n",
       "2  Vitória - Espírito Santo - Brazil         (-20.3196644, -40.3384748)  \n",
       "3     João Pessoa - Paraíba - Brazil  (-7.118835199999999, -34.8814339)  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def get_coords(address): return client.geocode(address)[0]['geometry']['location']\n",
    "df_renner['Coords'] = df_renner['Address'].apply(lambda coords: tuple(get_coords(coords).values()))\n",
    "\n",
    "df_renner_copia = df_renner.copy()\n",
    "df_renner.head(4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A partir desse df, deixaremos somente o que vamos precisar para criar os marcadores no mapa: as coordenadas e o ano de abertura da loja."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>Coords</th>\n",
       "      <th>Opening Year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>728</th>\n",
       "      <td>(-31.7699685, -52.3312971)</td>\n",
       "      <td>1967</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>727</th>\n",
       "      <td>(-30.0368176, -51.2089887)</td>\n",
       "      <td>1970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>726</th>\n",
       "      <td>(-29.9077898, -51.1847036)</td>\n",
       "      <td>1976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>725</th>\n",
       "      <td>(-30.0368176, -51.2089887)</td>\n",
       "      <td>1977</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>724</th>\n",
       "      <td>(-29.68949839999999, -53.7923441)</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                Coords  Opening Year\n",
       "728         (-31.7699685, -52.3312971)          1967\n",
       "727         (-30.0368176, -51.2089887)          1970\n",
       "726         (-29.9077898, -51.1847036)          1976\n",
       "725         (-30.0368176, -51.2089887)          1977\n",
       "724  (-29.68949839999999, -53.7923441)          1980"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# criando uma coluna com o ano\n",
    "df_renner['Opening Year'] = df_renner['Opening date'].dt.year\n",
    "\n",
    "# removendo dados desnecessários\n",
    "df_renner = df_renner.drop(['Country', 'UF', 'State', 'City', 'Opening date', 'Address'], axis=1)\n",
    "\n",
    "# Ordenando pelo ano\n",
    "df_renner = df_renner.sort_values(by='Opening Year')\n",
    "\n",
    "df_renner.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Estamos quase lá, para criarmos o mapa de calor com linha do tempo precisamos criar uma `data` e um `index`. O `index` é uma lista com marcadores, para o nosso caso usaremos uma lista com todos os anos passados da abertura da primeira loja até o ano atual. Para a `data`, precisamos criar uma lista do mesmo tamanho do index, com coordenadas ou listas de coordenadas. \n",
    "\n",
    "Vamos fazer alguns loops percorrendo o `index` e identificar qual loja está aberta e qual está fechada. Também podemos atribuir uma intensidade, de 0 à 1 junto com a coordenada. Criaremos uma definição de quanto mais tempo a loja está aberta, maior será a força."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# criando o index de anos\n",
    "primeiro_ano = df_renner[\"Opening Year\"].min()\n",
    "ultimo_ano = df_renner[\"Opening Year\"].max()\n",
    "year_index = list(range(primeiro_ano, ultimo_ano))\n",
    "year_index.append(ultimo_ano)\n",
    "\n",
    "coords_time_line = []\n",
    "for year in year_index:\n",
    "    lojas_coordenadas_por_ano = []\n",
    "    for index, row in df_renner.iterrows():\n",
    "        # calcula o tempo que a loja está aberta\n",
    "        year_diff = year - row[\"Opening Year\"]\n",
    "\n",
    "        # caso seja menor que zero, não é adicionada ao mapa\n",
    "        if year_diff < 0:\n",
    "            pass\n",
    "        else:\n",
    "            # adicionando uma lista com as cordenadas e a intensidade\n",
    "            coord = [row[\"Coords\"][0], row[\"Coords\"][1]]\n",
    "\n",
    "            # para ilustrar, podemos criar uma definição de força de acordo com\n",
    "            # a idade da loja\n",
    "            if year_diff == 0:\n",
    "                coord.append(0.5)\n",
    "            elif year_diff == 1:\n",
    "                coord.append(0.7)\n",
    "            elif year_diff > 1:\n",
    "                coord.append(1)\n",
    "\n",
    "            lojas_coordenadas_por_ano.append(coord)\n",
    "\n",
    "    coords_time_line.append(lojas_coordenadas_por_ano)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Por fim, estamos com duas variáveis: year_index e coords_time_line, as duas com o mesmo tamanho. Agora basta criar o mapa:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "                {heatmapOptions: {\n",
       "                        radius: 15,\n",
       "                        blur: 1,\n",
       "                        minOpacity: 0,\n",
       "                        maxOpacity: 0.3,\n",
       "                        scaleRadius: false,\n",
       "                        useLocalExtrema: false,\n",
       "                        defaultWeight: 1,\n",
       "                        \n",
       "                    }\n",
       "                })\n",
       "                .addTo(map_4791f915ca099b1936d71e2933ad845a);\n",
       "\n",
       "        \n",
       "&lt;/script&gt;\n",
       "&lt;/html&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x2a336fec890>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mapa_renner = folium.Map(location=[-17, -50], zoom_start=4)\n",
    "HeatMap = HeatMapWithTime(\n",
    "    data=coords_time_line,\n",
    "    index=year_index,\n",
    "    auto_play=True,\n",
    "    max_opacity=0.3,\n",
    "    name=\"Datas\",\n",
    "    blur=1,\n",
    "    min_speed=1,\n",
    ").add_to(mapa_renner)\n",
    "mapa_renner.save('renner_heatmap-time.html')\n",
    "mapa_renner"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Com o HeatMapWithTime, também configuramos mais algumas coisas, como opacidade máxima, blur e velocidade mínima. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusão\n",
    "\n",
    "O folium ainda oferece outras funcionalidades além das abordadas nesse artigo. Mas com uma exemplificação breve de algumas de suas ferramentas podemos perceber o potencial da biblioteca para análise e geração de insights a partir de dados geoespaciais. \n",
    "\n",
    "Aliado a outras ferramentas para obtenção e manipulação de dados, o Folium se torna peça chave em um conjunto para a análise e visualização de dados. Sua leveza e baixa dificuldade para gerar mapas interativos possibilitam uma análise exploratória e explanatória eficaz."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Referências\n",
    "\n",
    "https://python-visualization.github.io/folium/latest/\n",
    "\n",
    "https://lojasrenner.mzweb.com.br/\n",
    "\n",
    "\n",
    "Repositório do projeto:\n",
    "\n",
    "https://github.com/Moscarde/FoliumTools\n",
    "\n",
    "Se você leu até esse ponto, muito obrigado. Esta é minha primeira publicação, Fique à vontade para me seguir em outras redes sociais e, se possível me conte o que achou do conteúdo. =)\n",
    "\n",
    "https://www.linkedin.com/in/moscarde/\n",
    "\n",
    "https://github.com/Moscarde/"
   ]
  }
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