class: center, middle, inverse, title-slide # Données géographiques</br> et cartographie sous R ## Manipulation de données communales en historique et réalisation de cartes ### Kim Antunez ### 06/03/2018 --- background-image: url("img/giphy1.gif") background-size: 100% class: inverse, center, middle # 0. Introduction sur les géographies communales --- # Code Officiel Géographique (COG) Le **Code officiel géographique** (COG) est un document de référence publié par l’**Insee** qui rassemble les **codifications (numérotations et libellés) des communes**, des cantons, des arrondissements, des départements, des régions... Ce code est **révisé annuellement**, en fonction notamment des **fusions et associations** de communes ou de territoires, des **défusions** et des **changements de dénomination**. --- # Types de modifications communales (1/7) <div id="htmlwidget-7ed96402fe74873a10bd" style="width:100%;height:500px;" class="visNetwork html-widget"></div> <script type="application/json" data-for="htmlwidget-7ed96402fe74873a10bd">{"x":{"nodes":{"id":["76095_2011","76108_2011","76108_2013","76095_1968","76095_2014","76108_1968","76108_2012","76108_2014","76095_2017","76108_2017"],"comm":["76095","76108","76108","76095","76095","76108","76108","76108","76095","76108"],"COG":["2011","2011","2013","1968","2014","1968","2012","2014","2017","2017"],"label":["76095\n(2011)","76108\n(2011)","76108\n(2013)","76095\n(1968)","76095\n(2014)","76108\n(1968)","76108\n(2012)","76108\n(2014)","76095\n(2017)","76108\n(2017)"],"level":[2,2,4,1,5,1,3,5,6,6],"pop":["8415","12872","21107","7016","8268","8648","21270","12847","8237","13115"],"libgeo":["Bihorel","Bois-Guillaume","Bois-Guillaume-Bihorel","BIHOREL","Bihorel","BOIS-GUILLAUME","Bois-Guillaume - Bihorel","Bois-Guillaume","Bihorel","Bois-Guillaume"],"ratio":[1,1,0.391569973952167,0.608430026047833,1,1,1,1,1,1],"title":["<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-76095&debut=0>76095<\/a> Bihorel<\/b><br>Population : 8415 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-76108&debut=0>76108<\/a> Bois-Guillaume<\/b><br>Population : 12872 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-76108&debut=0>76108<\/a> Bois-Guillaume-Bihorel<\/b><br>Population : 21107 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-76095&debut=0>76095<\/a> BIHOREL<\/b><br>Population : 7016 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-76095&debut=0>76095<\/a> Bihorel<\/b><br>Population : 8268 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-76108&debut=0>76108<\/a> BOIS-GUILLAUME<\/b><br>Population : 8648 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-76108&debut=0>76108<\/a> Bois-Guillaume - Bihorel<\/b><br>Population : 21270 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-76108&debut=0>76108<\/a> Bois-Guillaume<\/b><br>Population : 12847 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-76095&debut=0>76095<\/a> Bihorel<\/b><br>Population : 8237 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-76108&debut=0>76108<\/a> Bois-Guillaume<\/b><br>Population : 13115 hab."]},"edges":{"from":["76095_2011","76108_2011","76108_2013","76108_2013","76095_1968","76095_2014","76108_1968","76108_2012","76108_2014"],"to":["76108_2012","76108_2012","76095_2014","76108_2014","76095_2011","76095_2017","76108_2011","76108_2013","76108_2017"],"LIBGEO":["Bihorel","Bois-Guillaume","Bois-Guillaume-Bihorel","Bois-Guillaume-Bihorel",null,null,null,null,null],"POP":[8415,12872,21107,21107,null,null,null,null,null],"annee":["2012-01-01","2012-01-01","2014-01-01","2014-01-01",null,null,null,null,null],"typemodif":["f","f","d","d",null,null,null,null,null],"ratio":[1,1,0.391569973952167,0.608430026047833,1,1,1,1,1],"arrows.middle.enabled":[true,true,true,true,false,false,false,false,false],"dashes":[false,false,false,false,true,true,true,true,true],"value":[1,1,0.391569973952167,0.608430026047833,0.2,0.2,0.2,0.2,0.2],"title":["<b>fusion<\/b><br>Date : 01 janv. 2012<br>","<b>fusion<\/b><br>Date : 01 janv. 2012<br>","<b>défusion<\/b> (ratio : 0.39)<br>Date : 01 janv. 2014<br>","<b>défusion<\/b> (ratio : 0.61)<br>Date : 01 janv. 2014<br>",null,null,null,null,null]},"nodesToDataframe":true,"edgesToDataframe":true,"options":{"width":"100%","height":"100%","nodes":{"shape":"ellipse","color":{"border":"black","background":"#000000","highlight":{"border":"#000000","background":"#000000"}},"fixed":{"allowedToMoveX":true,"allowedToMoveY":true},"font":{"face":"verdana","color":"#FFFFFF","size":20}},"manipulation":{"enabled":false},"edges":{"width":10,"arrows":{"middle":{"enabled":true,"scaleFactor":3}},"color":{"color":"#2AA198"},"shadow":false},"layout":{"hierarchical":{"enabled":true,"levelSeparation":500,"direction":"LR"},"randomSeed":12},"interaction":{"hoverConnectedEdges":false,"navigationButtons":true,"selectable":false,"selectConnectedEdges":false},"physics":{"hierarchicalRepulsion":{"centralGravity":0,"springConstant":0,"nodeDistance":0}},"configure":{"enabled":false}},"groups":null,"width":"100%","height":"500px","idselection":{"enabled":false},"byselection":{"enabled":false},"main":null,"submain":null,"footer":null,"tooltipStay":300,"tooltipStyle":"position: fixed;visibility:hidden;padding: 5px;white-space: nowrap;font-family: verdana;font-size:14px;font-color:#000000;background-color: #f5f4ed;-moz-border-radius: 3px;-webkit-border-radius: 3px;border-radius: 3px;border: 1px solid #808074;box-shadow: 3px 3px 10px rgba(0, 0, 0, 0.2);"},"evals":[],"jsHooks":[]}</script> --- # Types de modifications communales (2/7) <div id="htmlwidget-a6436e6d15435f22bdde" style="width:100%;height:500px;" class="visNetwork html-widget"></div> <script type="application/json" data-for="htmlwidget-a6436e6d15435f22bdde">{"x":{"nodes":{"id":["14010_1968","14067_1968","14234_1968","14295_1968","14314_1968","14363_1968","14447_1968","14472_1968","14624_1968","14697_1968","14624_1982","14697_2014","14081_2016","14099_2016","14331_2016","14433_2016","14450_2016","14472_2016","14489_2016","14580_2016","14616_2016","14654_2016","14688_2016","14729_2016","14750_2016","14081_1968","14099_1968","14331_1968","14433_1968","14450_1968","14489_1968","14580_1968","14616_1968","14654_1968","14688_1968","14729_1968","14750_1968","14624_1975","14697_1990","14472_2015","14654_2017"],"comm":["14010","14067","14234","14295","14314","14363","14447","14472","14624","14697","14624","14697","14081","14099","14331","14433","14450","14472","14489","14580","14616","14654","14688","14729","14750","14081","14099","14331","14433","14450","14489","14580","14616","14654","14688","14729","14750","14624","14697","14472","14654"],"COG":["1968","1968","1968","1968","1968","1968","1968","1968","1968","1968","1982","2014","2016","2016","2016","2016","2016","2016","2016","2016","2016","2016","2016","2016","2016","1968","1968","1968","1968","1968","1968","1968","1968","1968","1968","1968","1968","1975","1990","2015","2017"],"label":["14010\n(1968)","14067\n(1968)","14234\n(1968)","14295\n(1968)","14314\n(1968)","14363\n(1968)","14447\n(1968)","14472\n(1968)","14624\n(1968)","14697\n(1968)","14624\n(1982)","14697\n(2014)","14081\n(2016)","14099\n(2016)","14331\n(2016)","14433\n(2016)","14450\n(2016)","14472\n(2016)","14489\n(2016)","14580\n(2016)","14616\n(2016)","14654\n(2016)","14688\n(2016)","14729\n(2016)","14750\n(2016)","14081\n(1968)","14099\n(1968)","14331\n(1968)","14433\n(1968)","14450\n(1968)","14489\n(1968)","14580\n(1968)","14616\n(1968)","14654\n(1968)","14688\n(1968)","14729\n(1968)","14750\n(1968)","14624\n(1975)","14697\n(1990)","14472\n(2015)","14654\n(2017)"],"level":[1,1,1,1,1,1,1,1,1,1,3,5,7,7,7,7,7,7,7,7,7,7,7,7,7,1,1,1,1,1,1,1,1,1,1,1,1,2,4,6,8],"pop":["148","136","84","76","108","236","140","172","172","88","1452","1551","233","290","267","152","195","1579","240","102","378","3539","312","212","300","252","312","188","132","268","224","168","284","3644","216","196","304","1510","1372","1574","7799"],"libgeo":["AMMEVILLE","BERVILLE","ECOTS","GARNETOT","GRANDMESNIL","LIEURY","MONTPINCON","NOTRE DAME DE FRESNAY","SAINT-MARTIN-DE-FRESNAY","TÔTES","OUDON","L'Oudon","Boissey","Bretteville-sur-Dives","Hiéville","Mittois","Montviette","L'Oudon","Ouville-la-Bien-Tournée","Saint-Georges-en-Auge","Sainte-Marguerite-de-Viette","Saint-Pierre-sur-Dives","Thiéville","Vaudeloges","Vieux-Pont-en-Auge","BOISSEY","BRETTEVILLE-SUR-DIVES","HIEVILLE","MITTOIS","MONTVIETTE","OUVILLE-LA-BIEN-TOURNEE","SAINT-GEORGES-EN-AUGE","SAINTE-MARGUERITE-DE-VIETTE","SAINT-PIERRE-SUR-DIVES","THIEVILLE","VAUDELOGES","VIEUX-PONT-EN-AUGE","OUDON","OUDON","L'Oudon","Saint-Pierre-en-Auge"],"ratio":[1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1],"title":["<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14010&debut=0>14010<\/a> AMMEVILLE<\/b><br>Population : 148 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14067&debut=0>14067<\/a> BERVILLE<\/b><br>Population : 136 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14234&debut=0>14234<\/a> ECOTS<\/b><br>Population : 84 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14295&debut=0>14295<\/a> GARNETOT<\/b><br>Population : 76 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14314&debut=0>14314<\/a> GRANDMESNIL<\/b><br>Population : 108 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14363&debut=0>14363<\/a> LIEURY<\/b><br>Population : 236 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14447&debut=0>14447<\/a> MONTPINCON<\/b><br>Population : 140 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14472&debut=0>14472<\/a> NOTRE DAME DE FRESNAY<\/b><br>Population : 172 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14624&debut=0>14624<\/a> SAINT-MARTIN-DE-FRESNAY<\/b><br>Population : 172 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14697&debut=0>14697<\/a> TÔTES<\/b><br>Population : 88 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14624&debut=0>14624<\/a> OUDON<\/b><br>Population : 1452 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14697&debut=0>14697<\/a> L'Oudon<\/b><br>Population : 1551 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14081&debut=0>14081<\/a> Boissey<\/b><br>Population : 233 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14099&debut=0>14099<\/a> Bretteville-sur-Dives<\/b><br>Population : 290 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14331&debut=0>14331<\/a> Hiéville<\/b><br>Population : 267 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14433&debut=0>14433<\/a> Mittois<\/b><br>Population : 152 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14450&debut=0>14450<\/a> Montviette<\/b><br>Population : 195 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14472&debut=0>14472<\/a> L'Oudon<\/b><br>Population : 1579 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14489&debut=0>14489<\/a> Ouville-la-Bien-Tournée<\/b><br>Population : 240 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14580&debut=0>14580<\/a> Saint-Georges-en-Auge<\/b><br>Population : 102 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14616&debut=0>14616<\/a> Sainte-Marguerite-de-Viette<\/b><br>Population : 378 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14654&debut=0>14654<\/a> Saint-Pierre-sur-Dives<\/b><br>Population : 3539 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14688&debut=0>14688<\/a> Thiéville<\/b><br>Population : 312 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14729&debut=0>14729<\/a> Vaudeloges<\/b><br>Population : 212 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14750&debut=0>14750<\/a> Vieux-Pont-en-Auge<\/b><br>Population : 300 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14081&debut=0>14081<\/a> BOISSEY<\/b><br>Population : 252 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14099&debut=0>14099<\/a> BRETTEVILLE-SUR-DIVES<\/b><br>Population : 312 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14331&debut=0>14331<\/a> HIEVILLE<\/b><br>Population : 188 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14433&debut=0>14433<\/a> MITTOIS<\/b><br>Population : 132 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14450&debut=0>14450<\/a> MONTVIETTE<\/b><br>Population : 268 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14489&debut=0>14489<\/a> OUVILLE-LA-BIEN-TOURNEE<\/b><br>Population : 224 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14580&debut=0>14580<\/a> SAINT-GEORGES-EN-AUGE<\/b><br>Population : 168 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14616&debut=0>14616<\/a> SAINTE-MARGUERITE-DE-VIETTE<\/b><br>Population : 284 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14654&debut=0>14654<\/a> SAINT-PIERRE-SUR-DIVES<\/b><br>Population : 3644 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14688&debut=0>14688<\/a> THIEVILLE<\/b><br>Population : 216 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14729&debut=0>14729<\/a> VAUDELOGES<\/b><br>Population : 196 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14750&debut=0>14750<\/a> VIEUX-PONT-EN-AUGE<\/b><br>Population : 304 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14624&debut=0>14624<\/a> OUDON<\/b><br>Population : 1510 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14697&debut=0>14697<\/a> OUDON<\/b><br>Population : 1372 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14472&debut=0>14472<\/a> L'Oudon<\/b><br>Population : 1574 hab.","<b><a target=\"_blank\" href=https://www.insee.fr/fr/recherche/recherche-geographique?geo=COM-14654&debut=0>14654<\/a> Saint-Pierre-en-Auge<\/b><br>Population : 7799 hab."]},"edges":{"from":["14010_1968","14067_1968","14234_1968","14295_1968","14314_1968","14363_1968","14447_1968","14472_1968","14624_1968","14697_1968","14624_1982","14697_2014","14081_2016","14099_2016","14331_2016","14433_2016","14450_2016","14472_2016","14489_2016","14580_2016","14616_2016","14654_2016","14688_2016","14729_2016","14750_2016","14081_1968","14099_1968","14331_1968","14433_1968","14450_1968","14489_1968","14580_1968","14616_1968","14654_1968","14688_1968","14729_1968","14750_1968","14624_1975","14697_1990","14472_2015"],"to":["14624_1975","14624_1975","14624_1975","14624_1975","14624_1975","14624_1975","14624_1975","14624_1975","14624_1975","14624_1975","14697_1990","14472_2015","14654_2017","14654_2017","14654_2017","14654_2017","14654_2017","14654_2017","14654_2017","14654_2017","14654_2017","14654_2017","14654_2017","14654_2017","14654_2017","14081_2016","14099_2016","14331_2016","14433_2016","14450_2016","14489_2016","14580_2016","14616_2016","14654_2016","14688_2016","14729_2016","14750_2016","14624_1982","14697_2014","14472_2016"],"LIBGEO":["AMMEVILLE","BERVILLE","ECOTS","GARNETOT","GRANDMESNIL","LIEURY","MONTPINCON","NOTRE 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de noms) qui ont eu lieu entre deux dates : `modifications_communales` - visualiser sur un graphique interactif la trajectoire d'une commune donnée, c'est-à-dire toutes les modifications qui ont eu lieu depuis 1968 : **`trajectoire_commune`** et `trajectoire_commune_shiny` - transformer des tables de données numériques en géographie au premier janvier d'une année souhaitée : **`changement_COG_varNum`** --- # Le package COGugaison (2/2) - transformer des typologies de communes en géographie au premier janvier d'une année souhaitée en ayant le choix entre plusieurs hypothèses de classement en cas de fusion de communes de classes différentes (attribuer une unique classe à toutes les communes fusionnées, attribuer la classe qui contient le plus de population, définir une classe absorbante, une classe absorbée ou une classe spécifique aux regroupements de plusieurs communes de classes différentes) : **`changement_COG_typo`**. Il est également possible d'isoler dans une table les communes fusionnées appartenant à des classes différentes : `changement_COG_typo_details` - permettre d'agréger les tables de données communales à de nombreux échelons supra-communaux administratifs (EPCI, arrondissements, cantons-villes, départements, régions) ou d'étude (bassins de vie, zones d'emploi, unités urbaines, aires urbaines) : **`nivsupra`** - gérer des cas particuliers comme les codes Insee des communes corses (`modification_Corse`) ou des arrondissements municipaux de Paris, Lyon, et Marseille (**`enlever_PLM`**) ou encore l'ancienne commune de l'Oudon (`modification_Oudon`) --- # Les données utiles dans COGugaison (1/4) > - COG ```r head(COG2017) ``` ``` ## CODGEO LIBGEO POP ## 1 01001 L'Abergement-Clémenciat 767 ## 2 01002 L'Abergement-de-Varey 239 ## 3 01004 Ambérieu-en-Bugey 14022 ## 4 01005 Ambérieux-en-Dombes 1627 ## 5 01006 Ambléon 109 ## 6 01007 Ambronay 2570 ``` --- # Les données utiles dans COGugaison (2/4) > - TABLES_PASSAGE ```r head(PASSAGE_2015_2016_insee) ``` ``` ## cod2015 cod2016 annee typemodif ratio ## 1 14697 14472 2016-01-01 c 1 ## 2 01015 01015 2016-01-01 f 1 ## 3 01340 01015 2016-01-01 f 1 ## 4 01080 01080 2016-01-01 f 1 ## 5 01119 01080 2016-01-01 f 1 ## 6 01176 01187 2016-01-01 f 1 ``` --- # Les données utiles dans COGugaison (3/4) ```r head(table_supracom_2017) ``` ``` ## CODGEO LIBGEO DEP REG EPCI NATURE_EPCI ARR CV ## 1 01001 L'Abergement-Clémenciat 01 84 200069193 CC 012 0108 ## 2 01002 L'Abergement-de-Varey 01 84 240100883 CC 011 0101 ## 3 01004 Ambérieu-en-Bugey 01 84 240100883 CC 011 0101 ## 4 01005 Ambérieux-en-Dombes 01 84 200042497 CC 012 0122 ## 5 01006 Ambléon 01 84 200040350 CC 011 0104 ## 6 01007 Ambronay 01 84 240100883 CC 011 0101 ## ZE2010 UU2010 TUU2014 TDUU2014 AU2010 TAU2014 CATAEU2010 BV2012 ## 1 8213 01000 0 05 997 00 120 01093 ## 2 8201 01000 0 04 002 09 112 01004 ## 3 8201 01302 3 32 002 09 112 01004 ## 4 8213 01000 0 06 002 09 112 69123 ## 5 8216 01000 0 03 998 00 300 01034 ## 6 8201 01000 0 07 002 09 112 01004 ``` --- # Les données utiles dans COGugaison (4/4) ```r head(libelles_supracom_2017) ``` ``` ## NIVGEO CODGEO LIBGEO NB_COM ## 1 ARR 011 Belley 115 ## 2 ARR 012 Bourg-en-Bresse 201 ## 3 ARR 013 Gex 27 ## 4 ARR 014 Nantua 65 ## 5 ARR 021 Château-Thierry 108 ## 6 ARR 022 Laon 244 ``` --- # Exemple de fonction COGugaison (1/2) <center><img src="img/typo_fusion2.png" height="120px"></center> **changement_COG_typo** : Transformer des typologies - `methode_classe_fusion` : pour toutes les communes qui ont fusionné entre 2 dates indiquer comme classe la valeur inscrite dans "mot_fusion" y compris pour les fusions de communes de mêmes classes - `methode_difference` : créer une classe spécifique dont le nom est contenu dans mot_difference (par défaut) - `methode_max_pop` : attribuer la classe contenant le maximum de population des communes fusionnées - `methode_classe_absorbante` : attribuer la classe dite absorbante à toute commune fusionnée contenant au moins une ancienne commune appartenant à cette classe absorbante - `methode_classe_absorbee` : ne pas tenir compte de cette classe dite "absorbée" pour toute commune fusionnée contenant au moins une ancienne commune appartenant à cette classe absorbée --- # Exemple de fonction COGugaison (2/2) ```r table_modif_com <- cbind(COG1968, COG1968[, 1])[, c(1,4)] %>% setNames(c("CODGEO", "typo")) table_modif_com[1, ] ``` ``` ## CODGEO typo ## 1 01001 01001 ``` ```r table_modif_com <- changement_COG_typo(table_modif_com, methode_fusion = "methode_classe_fusion", mot_fusion = "communes fusionnées", annees = 1968:2017, codgeo_entree = "CODGEO", typos = "typo", donnees_insee = F) table_modif_com$typo[table_modif_com$typo %in% ( table_modif_com$typo[duplicated(table_modif_com$typo) & table_modif_com$typo != "communes fusionnées"])] <- "communes defusionnées" table_modif_com$typo[which(!table_modif_com$typo %in% c("communes fusionnées", "communes defusionnées"))] <- "communes inchangées" table_modif_com[1, ] ``` ``` ## CODGEO typo ## 1 01001 communes inchangées ``` --- # Modifications communales depuis 1968 <img src="180306_RLadies_COGugaison_carto_files/figure-html/unnamed-chunk-12-1.svg" style="display: block; margin: auto;" /> --- background-image: url("img/fond_carte.png") background-size: 100% # Démarche **Objectif** : Réaliser des cartes du nombre de femmes et nombre de femmes pour 100 hommes de 1968 à aujourd'hui - Récupérer les données sur insee.fr et observer à quoi elles ressemblent - Transformer les données (changements de COG + agrégation à une échelle supra-communale adaptée) - Réaliser les cartes --- background-image: url("img/giphy2.gif") background-size: 100% class: inverse, center, middle # 1. Récupération des données --- # Téléchargeons les données... <center><a href="https://www.insee.fr/fr/statistiques/1893204" target="_self"><img src="img/screenshot_insee.jpg" height="450px"></a></center> --- # Observons à quoi elles ressemblent... <center><img src="img/screenshot_fichier.jpg"></center> --- # Chargement des tables com1968...com2014 ```r library(readxl) recup_bdd <- function(annee) { bdd <- read_excel("data/pop-sexe-age-quinquennal6814.xls", sheet = paste0("COM_", annee), skip = 13, col_names = TRUE, na = "") %>% mutate(codgeo = paste0(substr(DR, 1, 2), CR)) %>% filter(!is.na(get(paste0("ageq_rec01s1rpop", annee)))) %>% mutate(total_s1 = rowSums(select(., contains("s1"))), total_s2 = rowSums(select(., contains("s2")))) %>% select(codgeo, total_s1, total_s2) return(bdd) } bdd_1975 <- recup_bdd(1975) bdd_1999 <- recup_bdd(1999) bdd_2014 <- recup_bdd(2014) c(nrow(bdd_1975), nrow(bdd_1999), nrow(bdd_2014)) ``` ``` ## [1] 36413 36696 35906 ``` --- background-image: url("img/giphy3.gif") background-size: 100% class: inverse, center, middle # 2. Transformation des données --- # En quel COG sont les données ? ```r COG_akinator(bdd_1975$codgeo, donnees_insee = TRUE) ``` ``` # [1] "COG1975" ``` ```r COG_akinator(bdd_1999$codgeo, donnees_insee = TRUE) ``` ``` # [1] "COG1999" ``` ```r COG_akinator(bdd_2014$codgeo, donnees_insee = TRUE) ``` ``` # [1] "COG2016" ``` ```r # REMARQUE :les recensements récents sont en COG n+2 ``` --- # Changements de COG ```r # Transformer les tables en bons COG # idem pour bdd_1999 et bdd_2014 bdd_1975_COG2016 <- bdd_1975 %>% enlever_PLM() %>% changement_COG_varNum(1975:2016, donnees_insee = TRUE) ``` ```r # Fusionner les tables bdd <- plyr::join_all(list(COG2016 %>% rename(codgeo = CODGEO) %>% select(-POP), bdd_1975_COG2016, bdd_1999_COG2016, bdd_2014_COG2016), type = "left", by = "codgeo") %>% setNames(nm = c("CODGEO", "LIBGEO", "total_s1_1975", "total_s2_1975", "total_s1_1999", "total_s2_1999", "total_s1_2014", "total_s2_2014")) # vérifier les totaux. Par exemple... sum(bdd_2014$total_s1, na.rm = TRUE) - sum(bdd$total_s1_2014, na.rm = TRUE) ``` ``` # [1] 0 ``` --- # Echelles géo supra-communales (1/2) <img src="180306_RLadies_COGugaison_carto_files/figure-html/unnamed-chunk-19-1.svg" style="display: block; margin: auto;" /> --- # Echelles géo supra-communales (2/2) <img src="180306_RLadies_COGugaison_carto_files/figure-html/unnamed-chunk-20-1.svg" style="display: block; margin: auto;" /> --- # Agrégation par Zone d'Emploi ```r bdd[1, ] ``` ``` # CODGEO LIBGEO total_s1_1975 total_s2_1975 total_s1_1999 # 1 01001 L'Abergement-Clémenciat 210 240 384 # total_s2_1999 total_s1_2014 total_s2_2014 # 1 332 385 380 ``` ```r bdd_ze <- bdd %>% nivsupra(COG = 2016, nivsupra = "ZE2010") %>% mutate(rapport_FH_1975 = 100 * total_s2_1975/total_s1_1975, rapport_FH_1999 = 100 * total_s2_1999/total_s1_1999, rapport_FH_2014 = 100 * total_s2_2014/total_s1_2014) ``` --- background-image: url("img/giphy4.gif") background-size: 100% class: inverse, center, middle # 3. Cartographie --- # Format des couches cartographiques (1/3) **Avant = spdf (SpatialPolygonsDataFrame)** - {rgdal} : import/export des données et les opérations de projections - {sp} : gestion et l’affichage des données : *coordinates*, *SpatialPolygonsDataFrame* - {rgeos} : géotraitements : *gUnion*, *gSimplify*, *gBuffer* - format : polygons*data.frame imbriqués dans des listes **Maintenant = sf** - un seul package : sf (nov. 2016) - auteur (Edzer Pebesma) = contributeur / maintainer des packages précédents - format : data.frame enrichi d’une « colonne-liste » de géométries - avantage : format considéré plus pratique « tidy » et compatible avec %>% --- # Format des couches cartographiques (2/3) ```r library(rgdal) ``` ```r comm_2016 <- readOGR( dsn = "data/couches_geo", layer = "COM_2016_CARTElette", stringsAsFactors = FALSE, encoding = "UTF-8", verbose = FALSE, ) ``` ```r str(comm_2016) ``` ``` # Formal class 'SpatialPolygonsDataFrame' [package "sp"] with 5 slots # ..@ data :'data.frame': 35885 obs. of 4 variables: # 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[list output truncated] # ..@ plotOrder : int [1:35885] 35838 4348 35823 35839 35859 35854 35866 35856 35863 35828 ... # ..@ bbox : num [1:2, 1:2] 98983 5988966 1242433 7110574 # .. ..- attr(*, "dimnames")=List of 2 # .. .. ..$ : chr [1:2] "x" "y" # .. .. ..$ : chr [1:2] "min" "max" # ..@ proj4string:Formal class 'CRS' [package "sp"] with 1 slot # .. .. ..@ projargs: chr "+proj=lcc +lat_1=49 +lat_2=44 +lat_0=46.5 +lon_0=3 +x_0=700000 +y_0=6600000 +ellps=GRS80 +units=m +no_defs" ``` --- # Format des couches cartographiques (3/3) ```r library(sf) ``` ```r comm_2016 <- st_read(paste0(getwd(), "/data/couches_geo/COM_2016_CARTElette.shp"), stringsAsFactors = FALSE, quiet = TRUE) ``` ```r str(comm_2016) ``` ``` # Classes 'sf' and 'data.frame': 35885 obs. of 5 variables: # $ insee : chr "01001" "01002" "01004" "01005" ... # $ nom : chr "L'Abergement-Clémenciat" "L'Abergement-de-Varey" "Ambérieu-en-Bugey" "Ambérieux-en-Dombes" ... # $ wikipedia: chr "fr:L'Abergement-Clémenciat" "fr:L'Abergement-de-Varey" "fr:Ambérieu-en-Bugey" "fr:Ambérieux-en-Dombes" ... # $ surf_ha : num 1567 909 2449 1602 597 ... # $ geometry :sfc_MULTIPOLYGON of length 35885; first list element: List of 1 # ..$ :List of 1 # .. ..$ : num [1:44, 1:2] 846839 847056 847011 847281 847063 ... # ..- attr(*, "class")= chr "XY" "MULTIPOLYGON" "sfg" # - attr(*, "sf_column")= chr "geometry" # - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA # ..- attr(*, "names")= chr "insee" "nom" "wikipedia" "surf_ha" ``` --- # Créer des couches supra-communales (1/2) <center><img src="img/agreger.png"></center> --- # Créer des couches supra-communales (2/2) ```r # chargement de la couche comm_2016 comm_2016 <- st_read(paste0(getwd(),"/data/couches_geo/COM_2016_CARTElette.shp"), stringsAsFactors = FALSE) %>% merge(table_supracom_2016[, -2], by.x = "insee", by.y = "CODGEO", all.x = T) # fonction pour créer les couches supra-communales creer_couche <- function(maille) { couche <- comm_2016 %>% dplyr::select(maille) %>% group_by(get(maille)) %>% summarize() %>% setNames(nm = c(maille, colnames(.)[-1])) %>% st_simplify(preserveTopology = FALSE, dTolerance = 10) st_write(couche, paste0(getwd(), "/data/couches_geo/", maille, "_2016_CARTElette.shp")) } # appliquer la fonction for (maille in c("DEP", "REG", "CV", "EPCI", "ZE2010", "AU2010", "BV2012", "ARR", "UU2010")) { creer_couche(maille) } ``` --- # Cartes avec cartography (1/4) ```r couche_ze <- st_read(paste0(getwd(), "/data/couches_geo/ZE2010_2016_CARTElette.shp"), stringsAsFactors = FALSE) %>% merge(bdd_ze, by="ZE2010", all.x = TRUE) library(cartography) cartography_rapportHF <- function(annee, breaks, col){ par(mar=c(1,1,1,1)) choroLayer(x = couche_ze, #sf data var = paste0("rapport_FH_", annee), # var in df breaks = breaks, # list of breaks col = col, # colors border = "black", # color of the polygons borders legend.pos = "topleft", # position of the legend legend.title.txt = paste0("Nombre de femmes pour\n100 hommes en ", annee), # title of the legend legend.values.rnd = 0, # number of decimal in the legend values colNA = "#303030", #color of NA values add = FALSE) # add the layer to the current plot ``` --- # Cartes avec cartography (2/4) ```r propSymbolsLayer(x = couche_ze, var = paste0("total_s2_", annee), # population symbols = "circle", # type of symbol border = "grey", # color of the symbols borders col= NA, lwd = 2, # width of the symbols borders legend.pos = "left", legend.title.txt = paste0("Nombre de\nfemmes en ", annee)) layoutLayer(title = paste0("Répartition des femmes en France en ", annee), sources = paste0("Insee, RP",annee,". Fond antuki/CARTElette"), author = "antuki with cartography", scale = 0, #automatic scale bar north = TRUE, frame = TRUE, coltitle = "black", #color of the title col = "#688994" # color of the frame ) } ``` --- # Cartes avec cartography (3/4) ```r cartography_rapportHF(annee = 2014, breaks = quantile(couche_ze$rapport_FH_2014, seq(0, 1, 0.2), na.rm = TRUE) %>% replace(2, 100), col = carto.pal(pal1 = "blue.pal", n1 = 1, pal2 = "red.pal", n2 = 4)) ``` --- # Cartes avec cartography (4/4) <img src="180306_RLadies_COGugaison_carto_files/figure-html/unnamed-chunk-33-1.svg" style="display: block; margin: auto;" /> --- # Cartes avec ggplot2 (1/4) ```r # Créer thème personnalisé theme_map2 <- function() { cowplot::theme_map() %+replace% theme(legend.position = c(0.95, 0.95), legend.justification = c(0, 1), legend.key.width = unit(1, "lines"), legend.text = element_text(size = 10), legend.title = element_text(size = 11), panel.grid.major = element_line(color = "transparent"), plot.title = element_text(size = 12, face = "bold"), plot.caption = element_text(size = 10, colour = "grey20"), plot.margin = unit(c(0, 0, 0, 0), "cm")) } ``` --- # Cartes avec ggplot2 (2/4) ```r ggplot2_rapportHF <- function(annee, breaks, col){ carto <- ggplot( bind_cols(couche_ze %>% mutate(typo = cut(get(paste0("rapport_FH_", annee)), breaks = breaks, dig.lab = 4, include.lowest = TRUE)), couche_ze %>% st_centroid() %>% st_coordinates() %>% as.data.frame() )) + geom_sf(aes(fill = typo), color = "black") + geom_point(aes(x = X, y = Y, size= with(couche_ze, get(paste0("total_s2_", annee)))), shape = 1, fill = NA, color = "grey", stroke = 1.5) + scale_size(name = paste0("Nombre de\nfemmes en ", annee), range = c(0, 18), breaks = c(50000, 100000, 500000),labels = c("50 000", "100 000", "500 000"))+ scale_fill_manual(name = paste0("Nombre de femmes pour\n100 hommes en ", annee), values = col, na.value = "#303030")+ theme_map2() + labs( title = paste0("Répartition des femmes en France en ", annee), caption = paste0("Insee, RP", annee, ". Fond antuki/CARTElette") ) + guides(size = guide_legend(order = 1)) return(carto) } ``` --- # Cartes avec ggplot2 (3/4) ```r ggplot2_rapportHF(annee = 2014, breaks = quantile(couche_ze$rapport_FH_2014, seq(0, 1, 0.2), na.rm = TRUE) %>% replace(2, 100), col = carto.pal(pal1 = "blue.pal", n1 = 1, pal2 = "red.pal", n2 = 4)) ``` --- # Cartes avec ggplot2 (4/4) <img src="180306_RLadies_COGugaison_carto_files/figure-html/unnamed-chunk-37-1.svg" style="display: block; margin: auto;" /> --- # Cartes animées avec magick (1/2) ```r library(magick) img <- image_graph(800, 500, res = 96) out <- lapply(c(1975, 1999, 2014), function(annee) { p <- ggplot2_rapportHF(annee = annee, breaks = quantile(c(couche_ze$rapport_FH_1975, couche_ze$rapport_FH_1999, couche_ze$rapport_FH_2014), seq(0, 1, 0.2), na.rm = TRUE) %>% replace(2, 100), col = carto.pal(pal1 = "blue.pal", n1 = 1, pal2 = "red.pal", n2 = 4)) print(p) }) animation <- image_animate(img, fps = 0.5) print(animation) image_write(animation, "carte_animee.gif") ``` --- # Cartes animées avec magick (2/2) <center><img src="img/carte_animee.gif"></center> --- # Cartes interactives avec ggiraph (1/4) ```r library(rgdal) library(ggiraph) couche_ze_rgdal <- merge(fortify( rgeos::gBuffer(readOGR(dsn = "data/couches_geo", layer = "ZE2010_2016_CARTElette", stringsAsFactors = FALSE), width = 0, byid = TRUE), region = "ZE2010"), bdd_ze, by.x = "id", by.y = "ZE2010", all.x = TRUE) couche_ze_rgdal <- couche_ze_rgdal %>% mutate(typo = cut(get( paste0("rapport_FH_", 2014)), breaks = quantile(couche_ze$rapport_FH_2014, seq(0, 1, 0.2), na.rm = TRUE) %>% replace(2, 100), dig.lab = 4, include.lowest = TRUE)) ``` --- # Cartes interactives avec ggiraph (2/4) ```r ggiraph_rapportHF <- function(annee, breaks, col) { carto <- ggplot(couche_ze_rgdal, aes(x = long, y = lat)) + geom_map_interactive(map = couche_ze_rgdal, mapping = aes(map_id = id, tooltip = paste0("Ratio : ", round(get(paste0("rapport_FH_", annee)), 0)), fill = typo), color = NA) + coord_fixed() + scale_fill_manual(name = paste0("Nombre de femmes pour\n100 hommes en ", annee), values = col, na.value = "#303030") + cowplot::theme_map() + labs(title = paste0("Répartition des femmes en France en ", annee), caption = paste0("Insee, RP", annee, ". 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160.46,297.52 160.35,297.58 160.22,297.58 160.07,297.56 159.83,297.38 160.35,297.38 159.83,297.38 159.67,297.29 159.60,297.18 159.61,297.03 159.47,296.85 159.41,296.37 159.43,296.30 159.70,296.53 159.87,296.55 159.92,296.60 160.05,296.54 160.09,296.63 160.39,296.74 160.41,296.67 160.54,296.88 160.49,296.77 160.49,296.77 160.54,296.65 160.65,296.61 160.68,296.52 160.65,296.00 160.56,295.76 160.57,295.44 160.77,295.62 160.98,295.65 161.05,295.71 161.13,295.72 161.22,295.63 161.30,295.90 161.42,295.93 161.41,296.07 161.48,296.09 161.47,296.16 161.65,296.31 161.56,296.37 161.66,296.34 161.79,296.48 161.81,296.58 162.02,296.49 162.10,296.65 162.17,296.57 162.27,296.58 162.33,296.48 162.51,296.51 162.76,296.65 162.73,296.40 162.79,296.22 162.88,296.08 163.03,296.12 163.10,295.91 163.25,295.94 163.51,296.12 164.07,296.28 163.93,296.55 163.84,296.61 163.86,296.65 163.74,296.68 163.77,296.74 163.67,296.71 163.77,296.74 163.66,296.94 163.51,297.01 163.45,297.15 163.51,297.20 163.49,297.30 163.41,297.25 163.42,297.31 163.37,297.36 163.45,297.47 163.43,297.55 163.36,297.54 163.29,297.60 163.28,297.95 163.30,297.79 163.31,297.86 163.47,297.98 163.59,297.83 163.66,297.94 163.78,297.95 163.99,297.65 164.16,297.82 164.35,297.68 164.61,297.70 164.74,297.87 164.70,297.96 164.80,297.79 164.80,297.79 164.84,297.75 164.77,297.59 164.62,297.50 164.48,297.19 164.49,297.13 164.61,297.17 164.73,297.00 164.83,297.08 165.00,297.07 165.03,296.97 165.36,296.90 165.37,296.79 165.60,296.79 165.65,296.84 165.79,296.77 166.03,296.83 166.25,296.73 166.33,296.78 166.13,296.60 166.13,296.37 165.97,296.12 165.96,295.94 165.75,295.83 165.70,295.73 165.73,295.59 165.95,295.69 166.01,295.56 165.99,295.46 166.35,295.27 166.42,295.47 166.39,295.53 166.56,295.72 166.66,295.99 166.91,295.99 167.16,296.12 167.57,295.88 167.92,295.91 167.73,295.89 167.76,295.71 167.68,295.68 167.62,295.57 167.66,295.47 167.83,295.52 167.89,295.34 168.08,295.32 167.70,295.21 167.53,294.99 168.06,294.25 168.38,293.62 168.65,293.46 168.78,293.28 169.00,293.18 169.11,293.01 169.27,292.95 169.35,292.83 169.69,292.80 169.80,292.71 169.89,293.07 170.01,293.12 169.99,293.27 170.07,293.30 170.07,293.30 170.28,293.19 170.47,293.13 170.55,293.17 170.56,293.04 170.84,292.99 170.84,292.99 170.96,292.98 171.05,293.01 171.09,293.13 171.29,293.26 171.44,293.22 171.48,293.31 171.66,293.26 171.64,293.21 171.69,293.16 171.78,293.14 171.79,293.22 172.11,293.15 172.11,293.40 172.33,293.44 172.35,293.52 172.41,293.52 172.58,293.92 172.48,293.94 172.39,293.84 172.49,293.95 172.50,294.16 172.50,294.07 172.73,294.07 172.97,293.95 173.51,294.19 173.85,294.19 173.88,294.12 173.95,294.13 174.11,294.04 174.13,293.96 174.31,293.92 174.39,293.83 174.48,293.89 174.44,293.96 174.83,294.23 175.12,294.18 175.19,294.21 175.27,294.38 175.40,294.14 175.51,294.12 175.60,294.03 175.60,293.89 175.83,293.56 176.15,293.62 176.43,293.74 176.78,293.76 177.07,293.85 177.59,294.03 177.18,293.89 177.26,293.75 177.14,293.79 176.97,293.64 177.18,293.26 177.04,293.15 177.08,293.12 177.03,292.95 177.09,292.78 177.30,292.64 177.51,292.65 177.62,292.75 177.67,292.86 177.89,293.03 177.89,293.00 178.02,292.96 178.10,292.82 178.17,292.87 178.28,292.73 178.39,292.85 178.76,293.01 178.91,293.01 178.91,293.21 179.04,293.25 178.97,293.50 179.18,293.93 179.19,294.01 179.37,294.08 179.50,293.86 179.62,293.77 179.63,293.46 179.91,293.52 180.04,293.63 180.20,293.57 180.21,293.61 180.21,293.60 180.49,293.64 180.56,293.57 180.57,293.59 180.66,293.65 180.69,293.59 180.70,293.35 180.62,293.20 180.68,293.09 180.69,293.09 180.65,292.97 180.79,292.86 180.83,292.59 181.07,292.68 181.32,292.61 181.39,292.50 181.47,292.55 181.56,292.45 181.68,292.57 182.10,292.75 182.05,292.80 182.09,293.01 182.26,293.11 182.23,293.35 182.28,292.98 182.43,292.77 182.52,292.54 182.66,292.42 182.65,292.38 182.49,292.23 182.42,292.10 181.95,292.12 181.96,292.04 181.87,291.95 181.84,291.77 181.91,291.45 182.07,291.32 182.09,291.38 182.47,291.68 182.55,291.50 182.76,291.59 182.93,291.57 182.98,291.47 183.12,291.61 183.12,291.83 183.01,292.01 182.98,292.24 183.30,292.39 183.27,292.51 183.31,292.44 183.59,292.51 183.64,292.28 183.74,292.20 184.33,292.53 184.41,292.84 184.50,292.97 184.41,292.83 184.55,292.81 184.75,292.90 184.85,292.88 185.41,292.98 185.64,293.13 185.80,293.05 185.95,292.83 186.20,292.97 186.28,293.08 186.45,293.02 186.47,293.12 186.58,293.19 186.60,293.27 186.83,293.13 187.19,293.39 187.61,293.41 187.58,293.62 187.44,293.72 187.37,293.87 187.63,294.73 187.90,295.22 187.59,295.41 187.23,295.47 186.82,295.79 186.73,296.10 186.77,296.20 186.92,296.32 186.89,296.40 186.58,296.54 186.58,296.54 186.69,296.73 186.78,296.72 186.88,296.77 187.04,296.66 187.45,296.73 187.79,296.96 187.87,296.95 187.89,297.00 187.99,296.87 187.86,296.75 187.72,296.49 187.71,296.31 188.04,296.28 188.16,296.34 188.38,296.79 188.66,297.03 189.00,296.95 189.04,296.81 189.19,296.78 189.41,297.03 189.50,297.31 189.71,297.41 189.94,297.64 189.96,297.55 190.03,297.91 190.63,298.03 190.61,298.08 190.72,297.91 190.91,297.80 190.91,297.64 191.08,297.52 191.03,297.32 191.22,297.14 191.31,297.18 191.39,297.14 191.57,297.25 191.73,297.16 191.89,297.34 192.15,297.40 192.42,297.76 192.72,297.74 193.14,297.47 193.18,297.58 193.34,297.63 193.27,297.82 193.55,298.22 193.51,298.33 193.51,298.33 193.60,298.13 193.91,298.29 194.11,298.49 194.26,298.80 194.48,298.71 194.68,298.55 194.72,298.62 194.82,298.61 194.83,298.67 194.77,298.68 194.88,298.90 194.62,299.05 194.55,299.34 194.49,299.37 194.51,299.50 194.55,299.69 194.57,299.99 194.39,300.08 194.34,300.06 194.12,300.37 193.89,300.21 193.54,300.30 193.43,300.17 193.59,300.40 193.60,300.56 193.67,300.60 193.71,300.55 193.78,300.56 193.90,300.84 193.84,300.90 193.80,300.86 193.71,300.87 193.69,301.06 193.62,301.08 193.69,301.16 193.68,301.24 193.44,301.29 193.51,301.46 193.45,301.50 193.21,301.35 193.14,301.35 193.15,301.45 192.96,301.45 192.88,301.26 192.68,301.28 192.66,301.26 192.75,301.43 192.71,301.61 192.80,301.75 192.48,301.74 192.43,301.87 192.31,302.02 192.17,302.06 191.96,302.05 191.80,302.49 191.71,302.56 191.74,302.69 191.41,303.05 191.47,303.07 191.47,303.17 191.42,303.19 191.56,303.29 191.78,303.25 191.86,303.30 191.93,303.23 191.88,303.12 191.92,303.01 192.05,302.94 192.17,302.98 192.09,303.48 191.98,303.52 191.99,303.60 191.82,303.78 191.83,303.90 191.67,304.04 191.65,304.13 191.40,304.32 191.31,304.51 190.96,304.60 191.15,304.75 191.04,304.85 191.03,304.96 190.92,305.08 190.65,304.87 190.41,304.90 190.34,304.70 190.34,304.76 190.07,304.64 190.04,304.66 190.17,304.93 190.09,304.99 190.00,305.20 190.07,305.30 190.30,305.46 190.63,305.60 190.69,305.66 190.70,305.86 190.59,305.83 190.49,305.92 190.37,305.88 190.32,305.97 190.14,305.88 190.07,306.12 189.93,306.10 189.70,306.09 189.68,306.25 189.55,306.22 189.51,306.26 189.51,306.15 189.47,306.29 189.50,306.38 189.35,306.44 189.42,306.50 189.57,306.51 189.59,306.46 189.74,306.55 189.82,306.51 189.93,306.53 189.97,306.60 190.06,306.53 190.16,306.55 190.27,306.50 190.36,306.56 190.47,306.64 190.48,306.71 190.32,306.99 190.46,307.07 190.35,307.26 190.39,307.41 190.46,307.47 190.32,307.56 190.13,307.76 190.35,307.58 190.43,307.70 190.42,307.69 190.53,307.60 190.52,307.53 190.76,307.31 190.84,307.39 190.86,307.35 191.07,307.30 191.14,307.20 191.27,307.20 191.26,307.38 191.31,307.48 191.36,307.27 191.57,307.34 191.65,307.07 191.75,307.05 191.97,307.16 191.94,307.19 192.02,307.28 192.10,307.29 192.29,307.53 192.29,307.65 192.38,307.67 192.37,307.71 192.44,307.70 192.53,307.83 192.61,307.73 192.65,307.85 192.62,308.02 192.75,308.01 192.83,308.14 192.82,308.38 192.75,308.40 192.74,308.47 192.67,308.49 192.93,308.51 193.01,308.46 193.20,308.89 193.34,308.97 193.45,308.95 193.44,309.06 193.67,308.88 193.74,309.04 194.03,309.25 194.03,309.25 193.79,309.07 194.09,308.76 194.45,309.23 194.32,309.35 194.38,309.42 194.34,309.47 194.45,309.71 194.56,309.86 194.40,310.07 194.70,310.44 194.98,310.55 195.13,310.77 195.08,311.06 194.92,311.19 194.89,311.40 194.76,311.59 194.77,311.67 194.69,311.89 194.75,311.97 194.64,312.10 194.23,312.12 194.17,312.22 194.14,312.21 194.12,312.28 194.08,312.28 194.11,312.41 194.30,312.72 194.28,312.79 194.43,312.88 194.61,313.14 194.61,313.30 194.54,313.40 194.56,313.67 194.51,313.75 194.44,313.70 194.35,314.13 194.47,314.13 194.76,314.25 194.73,314.57 194.77,314.67 195.04,314.80 195.00,314.92 195.03,315.04 195.23,315.17 195.25,315.28 195.07,315.36 194.83,315.58 194.87,315.62 194.75,315.59 194.48,315.94 194.30,315.97 194.51,316.09 194.50,316.45 194.56,316.63 194.29,316.55 194.20,316.74 193.98,316.64 193.95,316.69 193.80,316.58 193.72,316.63 193.65,316.76 193.52,316.82 193.57,316.87 193.57,316.98 193.37,317.03 193.32,317.23 193.30,317.22 193.31,317.22 193.22,317.94 193.05,318.05 192.95,318.24 192.94,318.51 192.77,318.65 192.71,318.97 192.48,319.09 192.43,319.00 192.04,318.86 191.92,318.89 191.82,318.81 191.62,318.83 191.56,318.90 191.30,318.74 191.68,318.98 191.66,319.05 191.74,319.08 191.65,319.22 191.49,319.21 191.54,319.39 191.28,319.80 191.16,319.85 191.04,319.99 190.71,320.03 190.71,320.03 191.04,320.02 191.20,320.19 190.99,320.44 191.17,320.43 191.20,320.51 191.12,320.69 191.07,320.67 191.01,320.76 191.10,320.99 191.05,321.06 190.88,321.05 190.98,321.17 191.01,321.35 190.95,321.26 190.80,321.23 190.79,321.36 190.83,321.43 190.72,321.47 190.66,321.63 190.70,321.66 190.70,321.78 190.77,321.80 190.83,321.90 190.96,321.91 190.92,322.01 190.87,322.00 190.68,322.18 190.67,322.27 190.50,322.33 189.94,322.23 189.97,322.18 189.91,322.00 189.87,322.00 189.88,321.89 189.56,321.76 189.34,321.77 189.32,321.59 189.31,321.59 189.06,321.44 188.79,321.46 188.66,321.56 188.65,321.79 188.56,321.85 188.43,322.06 188.31,321.92 188.37,321.82 188.37,321.70 188.10,321.65 188.10,321.42 188.16,321.35 188.10,321.04 188.14,320.89 188.01,321.09 187.75,321.08 187.56,321.00 187.49,321.02 187.43,320.49 187.34,320.33 187.38,320.46 187.32,320.58 187.25,320.60 187.14,320.53 187.11,320.63 187.28,320.72 187.39,320.90 187.36,320.94 187.26,320.97 187.10,320.92 187.00,321.01 186.84,320.93 186.70,320.98 186.61,320.87 186.23,320.65 186.16,320.56 185.95,320.57 185.85,320.49 185.73,320.55 185.60,320.75 185.60,320.62 185.51,320.43 185.38,320.39 185.31,320.28 185.03,320.17 184.89,320.07 184.81,319.95 184.61,319.86 184.63,319.76 184.57,319.73 184.60,319.62 184.09,319.42 183.85,319.51 183.76,319.47 183.70,319.32 183.75,319.19 183.70,319.07 183.82,318.96 183.85,318.82 184.14,318.59 184.04,318.38 184.02,318.19 184.09,318.13 184.18,318.26 184.09,318.13 183.89,318.02 183.93,317.99 183.73,317.78 183.73,317.68 183.56,317.60 183.56,317.52 183.68,317.40 183.52,317.43 183.38,317.35 183.48,317.28 183.57,317.01 183.51,316.78 183.23,316.39 183.22,316.40 182.85,316.11 182.83,315.92 182.82,316.21 182.74,316.22 182.75,316.29 182.62,316.35 182.37,316.70 182.22,316.83 182.25,317.09 182.38,317.21 182.34,317.44 182.05,317.66 181.82,317.66 181.80,317.51 181.89,317.01 181.12,316.83 180.93,316.61 180.47,316.52 180.48,316.44 180.39,316.29 180.41,316.05 180.36,316.39 180.31,316.38 180.24,316.24 180.14,316.42 180.14,316.52 180.27,316.60 180.29,316.67 180.18,316.86 180.18,317.00 180.04,317.07 179.58,316.18 179.43,316.28 179.41,316.17 178.82,316.45 178.76,316.12 178.82,316.08 178.81,315.98 178.75,315.88 178.83,315.77 178.70,315.61 178.61,315.67 178.62,315.79 178.53,315.87 178.45,315.84 178.23,315.53 178.28,315.61 178.19,316.04 178.27,316.24 178.13,316.32 178.03,316.46 178.16,316.67 178.08,316.83 178.13,316.98 178.28,316.97 178.46,317.17 178.33,317.32 178.29,317.51 178.16,317.59 178.45,317.75 178.40,318.02 178.57,318.13 178.42,318.19 178.29,318.14 177.99,317.92 177.75,318.09 177.69,318.30 177.77,318.75 177.95,318.87 178.18,318.87 178.25,318.95 178.09,319.14 178.09,319.21 178.00,319.25 177.94,319.20 177.70,319.22 177.67,319.29 177.54,319.35 177.49,319.50 177.34,319.63 177.08,319.73 177.15,319.90 177.37,320.31 177.58,320.39 177.53,320.52 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<rect x=\"413.83\" y=\"186.65\" width=\"15.86\" height=\"15.86\" id=\"744\" clip-path=\"url(#cl2_3)\" fill=\"#9AD3EB\" fill-opacity=\"1\" stroke=\"none\"/>\n <rect x=\"413.83\" y=\"203.93\" width=\"15.86\" height=\"15.86\" id=\"745\" clip-path=\"url(#cl2_3)\" fill=\"#FCDACA\" fill-opacity=\"1\" stroke=\"none\"/>\n <rect x=\"413.83\" y=\"221.21\" width=\"15.86\" height=\"15.86\" id=\"746\" clip-path=\"url(#cl2_3)\" fill=\"#F28278\" fill-opacity=\"1\" stroke=\"none\"/>\n <rect x=\"413.83\" y=\"238.49\" width=\"15.86\" height=\"15.86\" id=\"747\" clip-path=\"url(#cl2_3)\" fill=\"#E71312\" fill-opacity=\"1\" stroke=\"none\"/>\n <rect x=\"413.83\" y=\"255.77\" width=\"15.86\" height=\"15.86\" id=\"748\" clip-path=\"url(#cl2_3)\" fill=\"#7C000C\" fill-opacity=\"1\" stroke=\"none\"/>\n <rect x=\"413.83\" y=\"273.05\" width=\"15.86\" height=\"15.86\" id=\"749\" clip-path=\"url(#cl2_3)\" fill=\"#303030\" fill-opacity=\"1\" stroke=\"none\"/>\n <g clip-path=\"url(#cl2_3)\">\n <text x=\"432.56\" y=\"198.51\" id=\"750\" font-size=\"8.40pt\" font-family=\"Arial\">[93.72,100]<\/text>\n <\/g>\n <g clip-path=\"url(#cl2_3)\">\n <text x=\"432.56\" y=\"215.79\" id=\"751\" font-size=\"8.40pt\" font-family=\"Arial\">(100,105.1]<\/text>\n <\/g>\n <g clip-path=\"url(#cl2_3)\">\n <text x=\"432.56\" y=\"233.07\" id=\"752\" font-size=\"8.40pt\" font-family=\"Arial\">(105.1,106.4]<\/text>\n <\/g>\n <g clip-path=\"url(#cl2_3)\">\n <text x=\"432.56\" y=\"250.35\" id=\"753\" font-size=\"8.40pt\" font-family=\"Arial\">(106.4,108]<\/text>\n <\/g>\n <g clip-path=\"url(#cl2_3)\">\n <text x=\"432.56\" y=\"267.63\" id=\"754\" font-size=\"8.40pt\" font-family=\"Arial\">(108,123.5]<\/text>\n <\/g>\n <g clip-path=\"url(#cl2_3)\">\n <text x=\"432.56\" y=\"284.91\" id=\"755\" font-size=\"8.40pt\" font-family=\"Arial\">NA<\/text>\n <\/g>\n <g clip-path=\"url(#cl2_3)\">\n <text x=\"8.04\" y=\"20.54\" id=\"756\" font-size=\"12.60pt\" font-family=\"Arial\">Répartition des femmes en France en 2014<\/text>\n 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addTiles('http://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png') %>% addCircles(lng = ~X, lat = ~Y, weight = 1, radius = ~sqrt(total_s2_2014)*50, popup = ~paste(nom," : ", round(total_s2_2014, 0)), color = ~colorQuantile(carto.pal(pal1 = "blue.pal", n1 = 1, pal2 = "red.pal", n2 = 4), domain=couche_ze$rapport_FH_2014, n = 5) (rapport_FH_2014), fillOpacity = 0.7) ``` --- # Cartes interactives avec leaflet (2/3) ```r carto <- carto %>% addLegend("topright", colors = carto.pal(pal1 = "blue.pal", n1 = 1, pal2 = "red.pal", n2 = 4), labels = paste0("[", round(quantile(couche_ze$rapport_FH_2014, seq(0,1,0.20),na.rm=TRUE), 1), ";", c(round(quantile( couche_ze$rapport_FH_2014,seq(0, 1, 0.20),na.rm=TRUE), 1)[-1], NA),")")[-6], title = "Nombre de<br>femmes pour<br>100 hommes<br>en 2014", opacity = 1) return(carto) } ``` --- # Cartes interactives avec leaflet (3/3) <div id="htmlwidget-f3d8f28709d3332d6439" style="width:504px;height:504px;" class="leaflet html-widget"></div> <script 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legend"}]}],"limits":{"lat":[41.5191964629222,50.9467924543705],"lng":[-4.33150316422561,9.34459782176858]}},"evals":[],"jsHooks":[]}</script> --- class: center, middle <center><img src="img/avatar.gif" height="300px"></center> <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/4.7.0/css/font-awesome.min.css"> <a href="http://twitter.com/antuki13" class="social"><i class="fa fa-twitter fa-2x" title="Mon twitter"></i>@antuki13</a> <a href="http://github.com/antuki" class="social"><i class="fa fa-github fa-2x" title="Mon github"></i>antuki</a> <a href="http://antuki.github.io" class="social"><i class="fa fa-bold fa-2x" title="Mon blog"></i>antuki.github.io</a> Diaporama créé avec le package R [**xaringan**](https://github.com/yihui/xaringan) avec le thème [rladies](https://alison.rbind.io/post/r-ladies-slides/) et quelques gifs rigolos de [giphy](https://giphy.com/). Avec également l'utilisation de [remark.js](https://remarkjs.com), [knitr](http://yihui.name/knitr), et [R Markdown](https://rmarkdown.rstudio.com).