{"id":10465,"date":"2019-11-17T21:55:27","date_gmt":"2019-11-17T19:55:27","guid":{"rendered":"https:\/\/www.datanovia.com\/en\/?post_type=dt_lessons&#038;p=10465"},"modified":"2019-11-17T21:55:27","modified_gmt":"2019-11-17T19:55:27","slug":"ggplot-boxplot","status":"publish","type":"dt_lessons","link":"https:\/\/www.datanovia.com\/en\/fr\/lessons\/ggplot-boxplot\/","title":{"rendered":"GGPLOT Boxplot"},"content":{"rendered":"<div id=\"rdoc\">\n<p>Les <strong>boxplots<\/strong> (ou <strong>bo\u00eetes \u00e0 moustaches<\/strong>) sont utilis\u00e9s pour visualiser la distribution d\u2019une variable continue group\u00e9e \u00e0 travers leurs quartiles.<\/p>\n<p>Les boxplots ont l\u2019avantage d\u2019occuper moins d\u2019espace que les diagrammes d\u2019histogramme et de densit\u00e9. Ceci est utile pour comparer les distributions entre plusieurs groupes.<\/p>\n<p>La visualisation des donn\u00e9es \u00e0 l\u2019aide de boxplots permet de:<\/p>\n<ul>\n<li>Inspecter les valeurs cl\u00e9s des donn\u00e9es, y compris : la moyenne, la m\u00e9diane, les premier et troisi\u00e8me quartiles, etc<\/li>\n<li>Identifier les valeurs aberrantes potentielles dans les donn\u00e9es<\/li>\n<li>Voyez si les donn\u00e9es sont \u00e9troitement group\u00e9es, sym\u00e9triques ou asym\u00e9triques, etc<\/li>\n<\/ul>\n<p>Cet article d\u00e9crit comment cr\u00e9er et personnaliser un <strong>boxplot<\/strong> en utilisant le package <strong>ggplot2<\/strong> dans R.<\/p>\n<p>Contents:<\/p>\n<div id=\"TOC\">\n<ul>\n<li><a href=\"#fonctions-r-cles\">Fonctions R cl\u00e9s<\/a><\/li>\n<li><a href=\"#preparation-des-donnees\">Pr\u00e9paration des donn\u00e9es<\/a><\/li>\n<li><a href=\"#chargement-des-packages-r-requis\">Chargement des packages R requis<\/a><\/li>\n<li><a href=\"#boxplots-de-base\">Boxplots de base<\/a><\/li>\n<li><a href=\"#changer-les-couleurs-de-boxplot-par-groupes\">Changer les couleurs de boxplot par groupes:<\/a><\/li>\n<li><a href=\"#creer-un-boxplot-avec-plusieurs-groupes\">Cr\u00e9er un boxplot avec plusieurs groupes<\/a><\/li>\n<li><a href=\"#boxplots-a-panneaux-multiples\">Boxplots \u00e0 panneaux multiples<\/a><\/li>\n<li><a href=\"#conclusion\">Conclusion<\/a><\/li>\n<\/ul>\n<\/div>\n<div class='dt-sc-hr-invisible-medium  '><\/div>\n<div class='dt-sc-ico-content type1'><div class='custom-icon' ><a href='https:\/\/www.datanovia.com\/en\/fr\/produit\/ggplot2-lessentiel-pour-une-visualisation-magnifique-des-donnees-dans-r\/' target='_blank'><span class='fa fa-book'><\/span><\/a><\/div><h4><a href='https:\/\/www.datanovia.com\/en\/fr\/produit\/ggplot2-lessentiel-pour-une-visualisation-magnifique-des-donnees-dans-r\/' target='_blank'> Livre Apparent\u00e9 <\/a><\/h4>GGPLOT2 - L\u2019Essentiel pour une Visualisation Magnifique des Donn\u00e9es dans R<\/div>\n<div class='dt-sc-hr-invisible-medium  '><\/div>\n<div id=\"fonctions-r-cles\" class=\"section level2\">\n<h2>Fonctions R cl\u00e9s<\/h2>\n<ul>\n<li>Fonctions R cl\u00e9s : <code>geom_boxplot()<\/code> [package ggplot2]<\/li>\n<li>Arguments cl\u00e9s pour personnaliser le graphique:\n<ul>\n<li><code>width<\/code>: la largeur du box plot<\/li>\n<li><code>notch<\/code>: logique. Si TRUE, cr\u00e9e un <strong>boxplot avec notch<\/strong>. Le notch affiche un intervalle de confiance autour de la m\u00e9diane, qui est normalement bas\u00e9 sur le <code>median +\/- 1.58*IQR\/sqrt(n)<\/code>. Les \u201cNotches\u201d sont utilis\u00e9es pour comparer les groupes ; si les notches de deux box plots ne se chevauchent pas, c\u2019est une preuve solide que les m\u00e9dianes sont diff\u00e9rentes.<\/li>\n<li><code>color<\/code>, <code>size<\/code>, <code>linetype<\/code>: Couleur, taille et type de ligne de bordure<\/li>\n<li><code>fill<\/code>: couleur de remplissage des zones du box plot<\/li>\n<li><code>outlier.colour<\/code>, <code>outlier.shape<\/code>, <code>outlier.size<\/code>: La couleur, la forme et la taille des points outliers.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/div>\n<div id=\"preparation-des-donnees\" class=\"section level2\">\n<h2>Pr\u00e9paration des donn\u00e9es<\/h2>\n<ul>\n<li>Donn\u00e9es de d\u00e9monstration: <code>ToothGrowth<\/code>\n<ul>\n<li>Variable continue : <code>len<\/code> (longueur des dents). Utilis\u00e9 sur l\u2019axe des y<\/li>\n<li>Variable de regroupement : <code>dose<\/code> (doses de vitamine C : 0,5, 1 et 2 mg\/jour). Utilis\u00e9 sur l\u2019axe des x.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>Tout d\u2019abord, convertir la variable <code>dose<\/code> d\u2019une variable num\u00e9rique en une variable discr\u00e8te de groupes:<\/p>\n<pre class=\"r\"><code>data(&quot;ToothGrowth&quot;)\r\nToothGrowth$dose &lt;- as.factor(ToothGrowth$dose)\r\nhead(ToothGrowth, 4)<\/code><\/pre>\n<pre><code>##    len supp dose\r\n## 1  4.2   VC  0.5\r\n## 2 11.5   VC  0.5\r\n## 3  7.3   VC  0.5\r\n## 4  5.8   VC  0.5<\/code><\/pre>\n<\/div>\n<div id=\"chargement-des-packages-r-requis\" class=\"section level2\">\n<h2>Chargement des packages R requis<\/h2>\n<p>Chargez le package ggplot2 et mettez le th\u00e8me par d\u00e9faut \u00e0 <code>theme_classic()<\/code> avec la l\u00e9gende en haut du graphique:<\/p>\n<pre class=\"r\"><code>library(ggplot2)\r\ntheme_set(\r\n  theme_classic() +\r\n    theme(legend.position = &quot;top&quot;)\r\n  )<\/code><\/pre>\n<\/div>\n<div id=\"boxplots-de-base\" class=\"section level2\">\n<h2>Boxplots de base<\/h2>\n<p>Nous commen\u00e7ons par initier un graphique nomm\u00e9 <code>e<\/code>, puis nous allons ajouter des couches:<\/p>\n<pre class=\"r\"><code># Graphique par d\u00e9faut\r\ne &lt;- ggplot(ToothGrowth, aes(x = dose, y = len))\r\ne + geom_boxplot()\r\n\r\n# Box plot \u00e0 notch avec les points moyens\r\ne + geom_boxplot(notch = TRUE, fill = &quot;lightgray&quot;)+\r\n  stat_summary(fun.y = mean, geom = &quot;point&quot;,\r\n               shape = 18, size = 2.5, color = &quot;#FC4E07&quot;)<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggplot2\/figures\/005-ggplot-boxplot-geom_boxplot-create-basic-boxplots-1.png\" width=\"240\" \/><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggplot2\/figures\/005-ggplot-boxplot-geom_boxplot-create-basic-boxplots-2.png\" width=\"240\" \/><\/p>\n<p>Notez qu\u2019il est possible d\u2019utiliser la fonction <code>scale_x_discrete()<\/code> pour:<\/p>\n<ul>\n<li>choix des \u00e9l\u00e9ments \u00e0 afficher : par exemple c(\u201c0.5\u201d, \u201c2\u201d),<\/li>\n<li>changer l\u2019ordre des \u00e9l\u00e9ments : par exemple de c(\u201c0.5\u201d, \u201c1\u201d, \u201c2\u201d) \u00e0 c(\u201c2\u201d, \u201c0.5\u201d, \u201c1\u201d)<\/li>\n<\/ul>\n<p>Par exemple, tapez ceci:<\/p>\n<pre class=\"r\"><code># Choisir les \u00e9l\u00e9ments \u00e0 afficher : groupe &quot;0.5&quot; et &quot;2&quot;\r\ne + geom_boxplot() + \r\n  scale_x_discrete(limits=c(&quot;0.5&quot;, &quot;2&quot;))\r\n\r\n# Modifier l&#39;ordre par d\u00e9faut des \u00e9l\u00e9ments\r\ne + geom_boxplot() +\r\n  scale_x_discrete(limits=c(&quot;2&quot;, &quot;0.5&quot;, &quot;1&quot;))<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggplot2\/figures\/005-ggplot-boxplot-scale_x_discre_boxplot-change-group-order-1.png\" width=\"192\" \/><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggplot2\/figures\/005-ggplot-boxplot-scale_x_discre_boxplot-change-group-order-2.png\" width=\"192\" \/><\/p>\n<\/div>\n<div id=\"changer-les-couleurs-de-boxplot-par-groupes\" class=\"section level2\">\n<h2>Changer les couleurs de boxplot par groupes:<\/h2>\n<p>Le code R suivant changera la ligne et la couleur de remplissage des boxplot. Les fonctions <code>scale_color_manual()<\/code> et <code>scale_fill_manual()<\/code> sont utilis\u00e9es pour sp\u00e9cifier des couleurs personnalis\u00e9es pour chaque groupe.<\/p>\n<pre class=\"r\"><code># Couleur par groupe (dose)\r\ne + geom_boxplot(aes(color = dose))+\r\n  scale_color_manual(values = c(&quot;#00AFBB&quot;, &quot;#E7B800&quot;, &quot;#FC4E07&quot;))\r\n\r\n# Changer la couleur de remplissage par groupe (dose)\r\ne + geom_boxplot(aes(fill = dose)) +\r\n  scale_fill_manual(values = c(&quot;#00AFBB&quot;, &quot;#E7B800&quot;, &quot;#FC4E07&quot;))<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggplot2\/figures\/005-ggplot-boxplot-geom_boxplot-color-by-groups-1.png\" width=\"288\" \/><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggplot2\/figures\/005-ggplot-boxplot-geom_boxplot-color-by-groups-2.png\" width=\"288\" \/><\/p>\n<\/div>\n<div id=\"creer-un-boxplot-avec-plusieurs-groupes\" class=\"section level2\">\n<h2>Cr\u00e9er un boxplot avec plusieurs groupes<\/h2>\n<p>Deux variables de regroupement diff\u00e9rentes sont utilis\u00e9es : <code>dose<\/code> sur l\u2019axe des abscisses et <code>supp<\/code> comme couleur de remplissage (variable de la l\u00e9gende).<\/p>\n<p>L\u2019espace entre les boxplots group\u00e9s est ajust\u00e9 \u00e0 l\u2019aide de la fonction <code>position_dodge()<\/code>.<\/p>\n<pre class=\"r\"><code>e2 &lt;- e + \r\n  geom_boxplot(aes(fill = supp), position = position_dodge(0.9) ) +\r\n  scale_fill_manual(values = c(&quot;#999999&quot;, &quot;#E69F00&quot;))\r\ne2<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggplot2\/figures\/005-ggplot-boxplot-boxplot-multiple-groups-1.png\" width=\"288\" \/><\/p>\n<\/div>\n<div id=\"boxplots-a-panneaux-multiples\" class=\"section level2\">\n<h2>Boxplots \u00e0 panneaux multiples<\/h2>\n<p>Vous pouvez diviser le graphique en plusieurs panneaux \u00e0 l\u2019aide de la fonction <code>facet_wrap()<\/code>:<\/p>\n<pre class=\"r\"><code>e2 + facet_wrap(~supp)<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggplot2\/figures\/005-ggplot-boxplot-multiple-panel-boxplot-1.png\" width=\"576\" \/><\/p>\n<\/div>\n<div id=\"conclusion\" class=\"section level2\">\n<h2>Conclusion<\/h2>\n<p>Cet article d\u00e9crit comment cr\u00e9er un boxplot en utilisant le package ggplot2.<\/p>\n<\/div>\n<\/div>\n<p><!--end rdoc--><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Les boxplots sont utilis\u00e9s pour visualiser la distribution d&rsquo;une variable continue group\u00e9e \u00e0 travers leurs quartiles. Vous apprendrez comment cr\u00e9er et personnaliser des boxplots en utilisant le package R ggplot2.<\/p>\n","protected":false},"author":1,"featured_media":10220,"parent":0,"menu_order":4,"comment_status":"open","ping_status":"closed","template":"","class_list":["post-10465","dt_lessons","type-dt_lessons","status-publish","has-post-thumbnail","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>GGPLOT Boxplot : Meilleure R\u00e9f\u00e9rence - Datanovia<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.datanovia.com\/en\/fr\/lessons\/ggplot-boxplot\/\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"GGPLOT Boxplot : Meilleure R\u00e9f\u00e9rence - Datanovia\" \/>\n<meta property=\"og:description\" content=\"Les boxplots sont utilis\u00e9s pour visualiser la distribution d&#039;une variable continue group\u00e9e \u00e0 travers leurs quartiles. 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