Gestion d'un SIG Web.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Gérez votre SIG Web avec l'API ArcGIS pour Python\n",
    "L'exemple qui suit montre comment vous pouvez créer des utilisateurs, les ajouter à des groupes, gérer les services et d'autres commandes utiles.\n",
    "\n",
    "Commençons par importer les librairies requises."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os, sys, arcpy\n",
    "from arcgis.gis import GIS #ArcGIS API for Python\n",
    "import getpass #Masqueur de mots de passe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "URL du portail: https://esriquebec.maps.arcgis.com\n",
      "Nom d'utilisateur: jgaudreau\n",
      "Mot de passe: ········\n",
      "SUCCÈS: Connecté à https://esriquebec.maps.arcgis.com avec sous jgaudreau\n"
     ]
    }
   ],
   "source": [
    "#Demandons les informations de connexion à l'utilisateur:\n",
    "try:\n",
    "    portalUrl = input(\"URL du portail: \")\n",
    "    username = input(\"Nom d'utilisateur: \")\n",
    "    pwd = getpass.getpass(\"Mot de passe: \")\n",
    "    gis = GIS(portalUrl, username, pwd)\n",
    "    print(\"SUCCÈS: Connecté à \" + portalUrl + \" avec sous \" + username)\n",
    "except:\n",
    "    print(\"ERREUR: Quelque chose n'a pas fonctionné!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div class=\"9item_container\" style=\"height: auto; overflow: hidden; border: 1px solid #cfcfcf; border-radius: 2px; background: #f6fafa; line-height: 1.21429em; padding: 10px;\">\n",
       "                    <div class=\"item_left\" style=\"width: 210px; float: left;\">\n",
       "                       <a href='https://esriQuebec.maps.arcgis.com/home/user.html?user=2fa64aca559a13eeda5016bebc23a846' target='_blank'>\n",
       "                        <img src='data:image/png;base64,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' width='200' height='133' class=\"itemThumbnail\">\n",
       "                       </a>\n",
       "                    </div>\n",
       "\n",
       "                    <div class=\"item_right\" style=\"float: none; width: auto; overflow: hidden;\">\n",
       "                        <a href='https://esriQuebec.maps.arcgis.com/home/user.html?user=2fa64aca559a13eeda5016bebc23a846' target='_blank'><b>Jonathan Gaudreau</b>\n",
       "                        </a>\n",
       "                        <br/><br/><b>Bio</b>: \n",
       "                        <br/><b>First Name</b>: Jonathan\n",
       "                        <br/><b>Last Name</b>: Gaudreau\n",
       "                        <br/><b>Username</b>: jgaudreau\n",
       "                        <br/><b>Joined</b>: May 02, 2016\n",
       "\n",
       "                    </div>\n",
       "                </div>\n",
       "                "
      ],
      "text/plain": [
       "<User username:jgaudreau>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "me = gis.users.me\n",
    "me"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Maintenant, crééons un nouvel utilisateur et ajoutez le dans un groupe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Choisir le nom d'utilisateur: stevesteve123\n",
      "Prénom: Steve\n",
      "Nom: Steeve\n",
      "Courriel: steve@esri.ca\n",
      "Niveau (1 ou 2): 2\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div class=\"9item_container\" style=\"height: auto; overflow: hidden; border: 1px solid #cfcfcf; border-radius: 2px; background: #f6fafa; line-height: 1.21429em; padding: 10px;\">\n",
       "                    <div class=\"item_left\" style=\"width: 210px; float: left;\">\n",
       "                       <a href='https://esriQuebec.maps.arcgis.com/home/user.html?user=dea4111fb4ea4704a01faf3c12691b79' target='_blank'>\n",
       "                        <img src='https://esriQuebec.maps.arcgis.com/home/js/arcgisonline/css/images/no-user-thumb.jpg' class=\"itemThumbnail\">\n",
       "                       </a>\n",
       "                    </div>\n",
       "\n",
       "                    <div class=\"item_right\" style=\"float: none; width: auto; overflow: hidden;\">\n",
       "                        <a href='https://esriQuebec.maps.arcgis.com/home/user.html?user=dea4111fb4ea4704a01faf3c12691b79' target='_blank'><b>Steve Steeve</b>\n",
       "                        </a>\n",
       "                        <br/><br/><b>Bio</b>: None\n",
       "                        <br/><b>First Name</b>: Steve\n",
       "                        <br/><b>Last Name</b>: Steeve\n",
       "                        <br/><b>Username</b>: stevesteve123\n",
       "                        <br/><b>Joined</b>: May 01, 2019\n",
       "\n",
       "                    </div>\n",
       "                </div>\n",
       "                "
      ],
      "text/plain": [
       "<User username:stevesteve123>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "newUsername = input(\"Choisir le nom d'utilisateur: \")\n",
    "newName = input(\"Prénom: \")\n",
    "newLastName = input(\"Nom: \")\n",
    "newEmail = input(\"Courriel: \")\n",
    "newLevel = input(\"Niveau (1 ou 2): \")\n",
    "demo_user1 = gis.users.create(username= newUsername,\n",
    "                             password='Renard123',\n",
    "                             firstname = newName,\n",
    "                             lastname = newLastName,\n",
    "                             email= newEmail,\n",
    "                             level = newLevel,\n",
    "                             provider= 'arcgis')\n",
    "gis.users.get(newUsername)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Enter the name of the group you want to place the user and the services: QuebecUC_SteveGroup\n",
      "Error: The group QuebecUC_SteveGroup does not exist!\n",
      "Would you like to create a group called QuebecUC_SteveGroup? (y or n) y\n"
     ]
    }
   ],
   "source": [
    "groupName = input(\"Enter the name of the group you want to place the user and the services: \")\n",
    "myGroups= gis.groups.search('title:'+groupName)\n",
    "if len(myGroups) == 0:\n",
    "    print(\"Error: The group \" + groupName + \" does not exist!\")\n",
    "    createKey = input(\"Would you like to create a group called \" + groupName + \"? (y or n) \")\n",
    "    if createKey == \"y\" or createKey == \"Y\":\n",
    "        goodGroup = gis.groups.create(groupName,\"python,uc\")\n",
    "        myGroups.append(goodGroup)\n",
    "    else:\n",
    "        print(\"This wizard will end now\")\n",
    "        sys.exit()\n",
    "else:\n",
    "    goodGroup = myGroups[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "L'utilisateur stevesteve123 a été ajouté au groupe QuebecUC_SteveGroup avec succès\n"
     ]
    }
   ],
   "source": [
    "try:\n",
    "    myGroups[0].add_users([newUsername])\n",
    "    print(\"L'utilisateur \" + newUsername + \" a été ajouté au groupe \"+ myGroups[0].title+\" avec succès\")\n",
    "except:\n",
    "    print(\"Erreur: impossible d'ajouter l'utilisateur \" + newUsername + \" au groupe \" + myGroups[0].title)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['stevesteve123']"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "listeMembres= myGroups[0].get_members()\n",
    "listeMembres['users']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Maintenant, créons des utilisateurs en lot et mettons les dans un groupe, à partir d'un fichier CSV\n",
    "\n",
    "On lit un fichier CSV et on crée un utilisateur pour chaque ligne."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ï»¿nom,prenom,email,username,level\n",
      "\n",
      "henri,de la croix,jgaudreau@esri.ca,hdelacroix2,2\n",
      "raoul,duguay,jgaudreau@esri.ca,rduguay232,2\n"
     ]
    }
   ],
   "source": [
    "#Ouverture d'un explorateur de fichier\n",
    "from tkinter import filedialog #Librairie pour les interfaces graphiques\n",
    "from tkinter import Tk #Librairie pour les interfaces graphiques\n",
    "import csv\n",
    "root = Tk()\n",
    "root.withdraw()\n",
    "filename = filedialog.askopenfilename()\n",
    "filename2 = open(filename,\"r\")\n",
    "head = filename2.readline()\n",
    "lignes = filename2.read()\n",
    "print(head)\n",
    "print(lignes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Utilisateur hdelacroix2 créé avec succès!!\n",
      "Utilisateur hdelacroix2 ajouté au groupe QuebecUC_SteveGroup avec succès!\n",
      "Utilisateur rduguay232 créé avec succès!!\n",
      "Utilisateur rduguay232 ajouté au groupe QuebecUC_SteveGroup avec succès!\n"
     ]
    }
   ],
   "source": [
    "from arcgis.gis import GIS #ArcGIS API for Python\n",
    "lignes2 = lignes.split(\"\\n\")\n",
    "nbLignes = len(lignes.split(\"\\n\"))\n",
    "for i in range(0, nbLignes):\n",
    "    gis.users.create(username=lignes2[i].split(\",\")[3],password='Renard123',firstname=lignes2[i].split(\",\")[0],lastname=lignes2[i].split(\",\")[1],email=lignes2[i].split(\",\")[2],level=lignes2[i].split(\",\")[4],provider='arcgis')\n",
    "    newUser = gis.users.get(lignes2[i].split(\",\")[3])\n",
    "    myGroups[0]\n",
    "    print(\"Utilisateur \" + newUser.username + \" créé avec succès!!\")\n",
    "    try:\n",
    "        myGroups[0].add_users([newUser.username])\n",
    "        print(\"Utilisateur \" + newUser.username + \" ajouté au groupe \"+ myGroups[0].title+\" avec succès!\")\n",
    "    except:\n",
    "        print(\"Error: Impossible d'ajouter l'utilisateur \" + newUser.username + \" au groupe \" + myGroups[0].title)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div class=\"9item_container\" style=\"height: auto; overflow: hidden; border: 1px solid #cfcfcf; border-radius: 2px; background: #f6fafa; line-height: 1.21429em; padding: 10px;\">\n",
       "                    <div class=\"item_left\" style=\"width: 210px; float: left;\">\n",
       "                       <a href='https://esriQuebec.maps.arcgis.com/home/user.html?user=96cb31f596fd482281ecae9ca15eb662' target='_blank'>\n",
       "                        <img src='https://esriQuebec.maps.arcgis.com/home/js/arcgisonline/css/images/no-user-thumb.jpg' class=\"itemThumbnail\">\n",
       "                       </a>\n",
       "                    </div>\n",
       "\n",
       "                    <div class=\"item_right\" style=\"float: none; width: auto; overflow: hidden;\">\n",
       "                        <a href='https://esriQuebec.maps.arcgis.com/home/user.html?user=96cb31f596fd482281ecae9ca15eb662' target='_blank'><b>henri de la croix</b>\n",
       "                        </a>\n",
       "                        <br/><br/><b>Bio</b>: None\n",
       "                        <br/><b>First Name</b>: henri\n",
       "                        <br/><b>Last Name</b>: de la croix\n",
       "                        <br/><b>Username</b>: hdelacroix2\n",
       "                        <br/><b>Joined</b>: May 01, 2019\n",
       "\n",
       "                    </div>\n",
       "                </div>\n",
       "                "
      ],
      "text/plain": [
       "<User username:hdelacroix2>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "henri = gis.users.get(lignes2[0].split(\",\")[3])\n",
    "henri"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'username': 'jgaudreau',\n",
       " 'id': 'a3be5aaece0948fa91dd684556b2fb98',\n",
       " 'title': 'packages2'}"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gis.content.create_folder('packages2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "lpk_item = gis.content.add({'title':\"Mon gabarit de service\",'description':'Ceci est un service','tags':'arcgis,python','type':'File Geodatabase'},data= r\"D:\\OneDrive - Esri Canada\\Presentations\\TOR_UC_2018\\data\\AutomateYourGIS.zip\",folder='packages2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "myServiceTemplate = lpk_item.publish()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'notSharedWith': [''], 'itemId': '44945d8329b04b1dbae408ccf737e23d'}"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "myServiceTemplate.share(groups=[myGroups[0]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "from arcgis.features import FeatureLayer\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "wifiLayer = FeatureLayer(\"https://services.arcgis.com/3MrgBYsx9oKZpmLl/arcgis/rest/services/BornesWIFI/FeatureServer/0\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Nombre de points dans la couche de Wifi: \n",
      "320\n"
     ]
    }
   ],
   "source": [
    "#On fait une requête dans la couche de wifi\n",
    "wifi_features = wifiLayer.query()\n",
    "print('Nombre de points dans la couche de Wifi: ')\n",
    "print(len(wifi_features.features))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>Arrondisse</th>\n",
       "      <th>GlobalID</th>\n",
       "      <th>ID</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Lieu</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>OBJECTID</th>\n",
       "      <th>Type</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>SHAPE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ville-Marie</td>\n",
       "      <td>67617e92-ba27-4f82-b7d8-826a98c2ffa9</td>\n",
       "      <td>4HA01</td>\n",
       "      <td>45.50472</td>\n",
       "      <td>Rue Saint Jacques / Place d'Armes</td>\n",
       "      <td>-73.55792</td>\n",
       "      <td>1</td>\n",
       "      <td>Intersection</td>\n",
       "      <td>300273.915871</td>\n",
       "      <td>5.040535e+06</td>\n",
       "      <td>{'x': 300273.9159000004, 'y': 5040534.8258, 's...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ville-Marie</td>\n",
       "      <td>824bc51f-aee2-4393-997d-9655f75a397c</td>\n",
       "      <td>4HA02</td>\n",
       "      <td>45.50486</td>\n",
       "      <td>Rue Notre-Dames/ Place d'Armes</td>\n",
       "      <td>-73.55660</td>\n",
       "      <td>2</td>\n",
       "      <td>Intersection</td>\n",
       "      <td>300377.076541</td>\n",
       "      <td>5.040550e+06</td>\n",
       "      <td>{'x': 300377.07650000043, 'y': 5040550.3105999...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ville-Marie</td>\n",
       "      <td>175cec06-7f80-4087-b8c0-477ac159bc6e</td>\n",
       "      <td>4HA04</td>\n",
       "      <td>45.50578</td>\n",
       "      <td>Rue Le Royer / boul. Saint-Laurent</td>\n",
       "      <td>-73.55467</td>\n",
       "      <td>3</td>\n",
       "      <td>Intersection</td>\n",
       "      <td>300527.963129</td>\n",
       "      <td>5.040652e+06</td>\n",
       "      <td>{'x': 300527.9631000003, 'y': 5040652.4462, 's...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Outremont</td>\n",
       "      <td>7d6ae455-14dd-4a72-a812-c3d68d24336f</td>\n",
       "      <td>4HA05</td>\n",
       "      <td>45.50393</td>\n",
       "      <td>Rue Saint-Suplice / rue de la Commune</td>\n",
       "      <td>-73.55381</td>\n",
       "      <td>4</td>\n",
       "      <td>Intersection</td>\n",
       "      <td>300595.027736</td>\n",
       "      <td>5.040447e+06</td>\n",
       "      <td>{'x': 300595.02770000044, 'y': 5040446.8093, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ville-Marie</td>\n",
       "      <td>911483e2-74b5-4a9d-9c18-61b4909e7fbc</td>\n",
       "      <td>4HA06</td>\n",
       "      <td>45.50321</td>\n",
       "      <td>Place Royale/rue de la Commune</td>\n",
       "      <td>-73.55398</td>\n",
       "      <td>5</td>\n",
       "      <td>Intersection</td>\n",
       "      <td>300581.689347</td>\n",
       "      <td>5.040367e+06</td>\n",
       "      <td>{'x': 300581.68929999974, 'y': 5040366.8043000...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Arrondisse                              GlobalID     ID  Latitude  \\\n",
       "0  Ville-Marie  67617e92-ba27-4f82-b7d8-826a98c2ffa9  4HA01  45.50472   \n",
       "1  Ville-Marie  824bc51f-aee2-4393-997d-9655f75a397c  4HA02  45.50486   \n",
       "2  Ville-Marie  175cec06-7f80-4087-b8c0-477ac159bc6e  4HA04  45.50578   \n",
       "3    Outremont  7d6ae455-14dd-4a72-a812-c3d68d24336f  4HA05  45.50393   \n",
       "4  Ville-Marie  911483e2-74b5-4a9d-9c18-61b4909e7fbc  4HA06  45.50321   \n",
       "\n",
       "                                    Lieu  Longitude  OBJECTID          Type  \\\n",
       "0      Rue Saint Jacques / Place d'Armes  -73.55792         1  Intersection   \n",
       "1         Rue Notre-Dames/ Place d'Armes  -73.55660         2  Intersection   \n",
       "2     Rue Le Royer / boul. Saint-Laurent  -73.55467         3  Intersection   \n",
       "3  Rue Saint-Suplice / rue de la Commune  -73.55381         4  Intersection   \n",
       "4         Place Royale/rue de la Commune  -73.55398         5  Intersection   \n",
       "\n",
       "               X             Y  \\\n",
       "0  300273.915871  5.040535e+06   \n",
       "1  300377.076541  5.040550e+06   \n",
       "2  300527.963129  5.040652e+06   \n",
       "3  300595.027736  5.040447e+06   \n",
       "4  300581.689347  5.040367e+06   \n",
       "\n",
       "                                               SHAPE  \n",
       "0  {'x': 300273.9159000004, 'y': 5040534.8258, 's...  \n",
       "1  {'x': 300377.07650000043, 'y': 5040550.3105999...  \n",
       "2  {'x': 300527.9631000003, 'y': 5040652.4462, 's...  \n",
       "3  {'x': 300595.02770000044, 'y': 5040446.8093, '...  \n",
       "4  {'x': 300581.68929999974, 'y': 5040366.8043000...  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wifi_features.df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "wifi_features.df.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Maintenant, jouons avec matplotlib, la librairie de graphiques.\n",
    "\n",
    "Tout ce que vous avez besoin est de fournir des données et les étiquettes pour les x, y et le titre"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# Data for plotting\n",
    "t = np.arange(0.0, 2.0, 0.01)\n",
    "s = 1 + np.sin(2 * np.pi * t)\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "ax.plot(t, s)\n",
    "\n",
    "ax.set(xlabel='temps (s)', ylabel='voltage (mV)',\n",
    "       title='Ceci est un graphique!')\n",
    "ax.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Maintenant, jouons avec des cartes!\n",
    "Souvenez vous, on a qu'à ajouter une carte avec gis.map(adresse, échelle)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "df6cfec8b4ee4c1c863ae25f2595263e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "MapView(layout=Layout(height='400px', width='100%'), zoom=10.0)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "MyMap = gis.map(\"Montreal\",10)\n",
    "MyMap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "MyMap.add_layer(wifiLayer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "MyMap2 = gis.map(\"1425 René-Lévesque O, Montréal\",5)\n",
    "MyMap2.add_layer(wifiLayer)\n",
    "MyMap2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "366b5bd6c2424609ae5f805fc2c449b6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "MapView(hide_mode_switch=True, layout=Layout(height='400px', width='100%'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from arcgis.mapping import WebMap\n",
    "wm_item = gis.content.get('b74d3d6b7cf345f5bcab192d5f940732')\n",
    "\n",
    "# create a WebMap object from the existing web map item\n",
    "wm = WebMap(wm_item)\n",
    "wm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}