{"id":54002,"date":"2021-04-02T09:10:02","date_gmt":"2021-04-02T08:10:02","guid":{"rendered":"https:\/\/datascientest.com\/?p=54002"},"modified":"2023-11-09T14:09:37","modified_gmt":"2023-11-09T14:09:37","slug":"seaborn-tout-savoir","status":"publish","type":"post","link":"https:\/\/datascientest.com\/seaborn-tout-savoir","title":{"rendered":"Seaborn : tout savoir sur l&rsquo;outil de Data Visualization en Python"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"54002\" class=\"elementor elementor-54002\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-83fb465 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"83fb465\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-6ef4e80\" data-id=\"6ef4e80\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-8f691d5 elementor-widget elementor-widget-heading\" data-id=\"8f691d5\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-heading-title{padding:0;margin:0;line-height:1}.elementor-widget-heading .elementor-heading-title[class*=elementor-size-]>a{color:inherit;font-size:inherit;line-height:inherit}.elementor-widget-heading .elementor-heading-title.elementor-size-small{font-size:15px}.elementor-widget-heading .elementor-heading-title.elementor-size-medium{font-size:19px}.elementor-widget-heading .elementor-heading-title.elementor-size-large{font-size:29px}.elementor-widget-heading .elementor-heading-title.elementor-size-xl{font-size:39px}.elementor-widget-heading .elementor-heading-title.elementor-size-xxl{font-size:59px}<\/style><h2 class=\"elementor-heading-title elementor-size-default\">Seaborn est un outil de Data Visualization en langage Python. D\u00e9couvrez tout ce que vous devez savoir : pr\u00e9sentation, cas d'usage, avantages, formations...<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-4691431 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"4691431\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-5adf3d2\" data-id=\"5adf3d2\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-a5d8ac8 elementor-widget elementor-widget-text-editor\" data-id=\"a5d8ac8\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#69727d;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#69727d;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<p>La <strong><a href=\"https:\/\/datascientest.com\/quest-ce-la-dataviz-le-point-avec-nos-data-experts\">Data Visualization est une technique<\/a><\/strong> permettant aux Data Scientists de transformer des donn\u00e9es brutes en graphiques et en diagrammes. De telles illustrations facilitent la lecture et la compr\u00e9hension des donn\u00e9es, c&rsquo;est la raison pour laquelle la Dataviz est tr\u00e8s utile.<\/p><p>Il existe <strong>de nombreux outils \u00a0\u00bb no-code \u00ab\u00a0<\/strong> permettant de cr\u00e9er des visualisations de donn\u00e9es : Tableau, Power BI, ChartBlocks&#8230; cependant, en guise d&rsquo;alternative, il est aussi possible d&rsquo;opter pour <strong><a href=\"https:\/\/datascientest.com\/python-tout-savoir\">le langage Python<\/a><\/strong>.<\/p><p>Ceci n\u00e9cessite des comp\u00e9tences en programmation, mais offre une libert\u00e9 totale. En utilisant Python, il est possible de manipuler, de transformer et de cr\u00e9er des visualisations de donn\u00e9es. De <strong><a href=\"https:\/\/datascientest.com\/metier-data-scientist\">nombreux Data Scientists<\/a><\/strong> se tournent vers cette solution.<\/p><p>L&rsquo;une des raisons pour lesquelles Python est le meilleur choix pour la Data Science est <strong>son vaste \u00e9cosyst\u00e8me de biblioth\u00e8ques<\/strong>. De nombreuses biblioth\u00e8ques Python permettent de manipuler les donn\u00e9es : numpy, pandas, matplotlib, tensorflow&#8230;<\/p><p>Si Matplotlib est tr\u00e8s populaire pour cr\u00e9er des visualisations de donn\u00e9es, <strong>elle peut \u00eatre complexe d&rsquo;utilisation<\/strong>. Des d\u00e9veloppeurs ont cr\u00e9\u00e9 une nouvelle biblioth\u00e8que bas\u00e9e sur Matplotlib : Seaborn.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-f7ae85b elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"f7ae85b\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-371c709\" data-id=\"371c709\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-0eac3a8 elementor-widget elementor-widget-heading\" data-id=\"0eac3a8\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Qu'est-ce que Seaborn ?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-e38aaf1 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"e38aaf1\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-e4dd78c\" data-id=\"e4dd78c\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-96f4455 elementor-widget elementor-widget-text-editor\" data-id=\"96f4455\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Seaborn est une biblioth\u00e8que permettant de <strong>cr\u00e9er des graphiques statistiques en Python<\/strong>. Elle est bas\u00e9e sur Matplotlib, et s&rsquo;int\u00e8gre avec les structures Pandas.<\/p><p>Cette biblioth\u00e8que est aussi performante que Matplotlib, mais apporte<strong> une simplicit\u00e9 et des fonctionnalit\u00e9s in\u00e9dites<\/strong>. Elle permet d&rsquo;explorer et de comprendre rapidement les donn\u00e9es.<\/p><p>Des<strong> cadres de donn\u00e9es complets<\/strong> peuvent \u00eatre captur\u00e9s, et les fonctions internes permettant la cartographie s\u00e9mantique et l&rsquo;agr\u00e9gation statistique permettent de convertir les donn\u00e9es en visualisations graphiques.<\/p><p>Toute <strong>la complexit\u00e9 de Matplotlib est abstraite par Seaborn<\/strong>. Toutefois, il est possible de cr\u00e9er des graphiques r\u00e9pondant \u00e0 tous vos besoins et vos exigences.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-274baf2 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"274baf2\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-eceea34\" data-id=\"eceea34\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-64209c1 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"64209c1\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-grow\" href=\"\/formation-data-scientist\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Apprendre \u00e0 utiliser Seaborn<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-918267c elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"918267c\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-09c812b\" data-id=\"09c812b\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-94eaf4e elementor-widget elementor-widget-heading\" data-id=\"94eaf4e\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Seaborn et les diff\u00e9rents types de Dataviz<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-585de53 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"585de53\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-184933f\" data-id=\"184933f\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-534507f elementor-widget elementor-widget-text-editor\" data-id=\"534507f\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Seaborn fournit <strong>diff\u00e9rents styles et palettes de couleur par d\u00e9faut<\/strong> permettant de cr\u00e9er des graphismes plus attrayants. Les diff\u00e9rents types de visualisations permettent de mettre en lumi\u00e8re les relations entre les donn\u00e9es. Il peut s&rsquo;agir de variables num\u00e9riques ou de groupes, de classes, de divisions.<\/p><p>Les graphiques relationnels sont utilis\u00e9s pour <strong>comprendre les relations entre deux variables<\/strong>, tandis que les graphiques cat\u00e9goriques permettent de visualiser des variables class\u00e9es par cat\u00e9gorie.<\/p><p>Les graphiques de distribution sont utilis\u00e9s pour examiner les distributions univari\u00e9es ou bivari\u00e9es. Les graphiques de r\u00e9gression permettent d&rsquo;ajouter un guide visuel pour <strong>mettre en lumi\u00e8re les motifs<\/strong> dans un ensemble de donn\u00e9es pour les analyses exploratoires.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-506d856 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"506d856\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-8860991\" data-id=\"8860991\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-8ff5a28 elementor-widget elementor-widget-image\" data-id=\"8ff5a28\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-image{text-align:center}.elementor-widget-image a{display:inline-block}.elementor-widget-image a img[src$=\".svg\"]{width:48px}.elementor-widget-image img{vertical-align:middle;display:inline-block}<\/style>\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"370\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/03\/seaborn-graphique.png\" class=\"attachment-large size-large wp-image-54006\" alt=\"exemple seaborn\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/03\/seaborn-graphique.png 960w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/03\/seaborn-graphique-300x139.png 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/03\/seaborn-graphique-768x355.png 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-6309a3e elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"6309a3e\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-8363437\" data-id=\"8363437\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-282f09b elementor-widget elementor-widget-heading\" data-id=\"282f09b\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Quels sont les avantages de Seaborn ?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-abeb90b elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"abeb90b\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-5aae45d\" data-id=\"5aae45d\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-08c89be elementor-widget elementor-widget-text-editor\" data-id=\"08c89be\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>La biblioth\u00e8que Seaborn offre plusieurs avantages majeurs. Elle fournit diff\u00e9rents types de visualisations. Sa<strong> syntaxe est r\u00e9duite<\/strong>, et elle propose des th\u00e8mes par d\u00e9faut tr\u00e8s attrayants.<\/p><p>Il s&rsquo;agit d&rsquo;un <strong>outil id\u00e9al pour la visualisation statistique<\/strong>. On l&rsquo;utilise pour r\u00e9sumer les donn\u00e9es dans les visualisations et la distribution des donn\u00e9es.<\/p><p>En outre,<strong> Seaborn est mieux int\u00e9gr\u00e9 que Matplotlib<\/strong> pour travailler avec les data frames de Pandas. Enfin, il s&rsquo;agit d&rsquo;une extension de Matplotlib pour cr\u00e9er de beaux graphiques \u00e0 l&rsquo;aide de Python gr\u00e2ce \u00e0 un ensemble de m\u00e9thodes plus directes.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-41990ef elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"41990ef\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-e6fa785\" data-id=\"e6fa785\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-1fd97d6 elementor-widget elementor-widget-heading\" data-id=\"1fd97d6\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Seaborn vs Matplotlib : lequel utiliser ?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-2b5f096 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"2b5f096\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-11b38f0\" data-id=\"11b38f0\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-58a595d elementor-widget elementor-widget-text-editor\" data-id=\"58a595d\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Matplotlib et Seaborn sont <strong>les deux outils Python les plus populaires<\/strong> pour la Data Visualization. Chacun pr\u00e9sente des avantages et des inconv\u00e9nients.<\/p><p>On utilise principalement <strong>Matplotlib pour les trac\u00e9s de graphiques basiques<\/strong>, tandis que Seaborn propose de nombreux th\u00e8mes par d\u00e9faut et une vaste vari\u00e9t\u00e9 de sch\u00e9mas pour la visualisation de statistiques.<\/p><p>En outre, <strong>Seaborn automatise la cr\u00e9ation de figures multiples<\/strong>. C&rsquo;est un avantage, m\u00eame si cela peut mener \u00e0 des probl\u00e8mes d&rsquo;utilisation de m\u00e9moire vie. Un autre atout de Seaborn est l&rsquo;int\u00e9gration renforc\u00e9e avec Pandas et ses Data Frames, m\u00eame si Matplotlib est aussi int\u00e9gr\u00e9 avec Pandas et NumPy.<\/p><p>En revanche, <strong>Matplotlib offre une flexibilit\u00e9 accrue<\/strong> en termes de customisation et des performances parfois sup\u00e9rieures. Il peut donc s&rsquo;agir d&rsquo;une meilleure option dans certaines situations.<\/p><p>De mani\u00e8re g\u00e9n\u00e9rale, Seaborn est le meilleur choix d&rsquo;outil de DataViz pour des visualisations de donn\u00e9es statistiques. En revanche, <strong>Matplotlib r\u00e9pond mieux aux besoins en customisation<\/strong>.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-13ef48f elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"13ef48f\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-8609a80\" data-id=\"8609a80\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-98f1ea4 elementor-widget elementor-widget-image\" data-id=\"98f1ea4\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"583\" height=\"1024\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/Cheat-sheet-matplotlib-583x1024.png\" class=\"attachment-large size-large wp-image-58187\" alt=\"\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/Cheat-sheet-matplotlib-583x1024.png 583w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/Cheat-sheet-matplotlib-171x300.png 171w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/Cheat-sheet-matplotlib-768x1349.png 768w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/Cheat-sheet-matplotlib-875x1536.png 875w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/Cheat-sheet-matplotlib-1166x2048.png 1166w\" sizes=\"(max-width: 583px) 100vw, 583px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5051d9d elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"5051d9d\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-grow\" href=\"\/formation-data-scientist\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Apprendre \u00e0 utiliser Seaborn<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-92fd253 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"92fd253\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-81b8727\" data-id=\"81b8727\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-4daf8d3 elementor-widget elementor-widget-heading\" data-id=\"4daf8d3\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Pourquoi et comment apprendre \u00e0 utiliser Seaborn ? Les formations DataScientest<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-5e995f6 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"5e995f6\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-12b4e17\" data-id=\"12b4e17\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-6c17a92 elementor-widget elementor-widget-video\" data-id=\"6c17a92\" data-element_type=\"widget\" data-settings=\"{&quot;youtube_url&quot;:&quot;https:\\\/\\\/www.youtube.com\\\/watch?v=SNNK6z03TaA&amp;t=57s&quot;,&quot;video_type&quot;:&quot;youtube&quot;,&quot;controls&quot;:&quot;yes&quot;}\" data-widget_type=\"video.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-video .elementor-widget-container{overflow:hidden;transform:translateZ(0)}.elementor-widget-video .elementor-wrapper{aspect-ratio:var(--video-aspect-ratio)}.elementor-widget-video .elementor-wrapper iframe,.elementor-widget-video .elementor-wrapper video{height:100%;width:100%;display:flex;border:none;background-color:#000}@supports not (aspect-ratio:1\/1){.elementor-widget-video .elementor-wrapper{position:relative;overflow:hidden;height:0;padding-bottom:calc(100% \/ var(--video-aspect-ratio))}.elementor-widget-video .elementor-wrapper iframe,.elementor-widget-video .elementor-wrapper video{position:absolute;top:0;right:0;bottom:0;left:0}}.elementor-widget-video .elementor-open-inline .elementor-custom-embed-image-overlay{position:absolute;top:0;right:0;bottom:0;left:0;background-size:cover;background-position:50%}.elementor-widget-video .elementor-custom-embed-image-overlay{cursor:pointer;text-align:center}.elementor-widget-video .elementor-custom-embed-image-overlay:hover .elementor-custom-embed-play i{opacity:1}.elementor-widget-video .elementor-custom-embed-image-overlay img{display:block;width:100%;aspect-ratio:var(--video-aspect-ratio);-o-object-fit:cover;object-fit:cover;-o-object-position:center center;object-position:center center}@supports not (aspect-ratio:1\/1){.elementor-widget-video .elementor-custom-embed-image-overlay{position:relative;overflow:hidden;height:0;padding-bottom:calc(100% \/ var(--video-aspect-ratio))}.elementor-widget-video .elementor-custom-embed-image-overlay img{position:absolute;top:0;right:0;bottom:0;left:0}}.elementor-widget-video .e-hosted-video .elementor-video{-o-object-fit:cover;object-fit:cover}.e-con-inner>.elementor-widget-video,.e-con>.elementor-widget-video{width:var(--container-widget-width);--flex-grow:var(--container-widget-flex-grow)}<\/style>\t\t<div class=\"elementor-wrapper elementor-open-inline\">\n\t\t\t<div class=\"elementor-video\"><\/div>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-5119b2a elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"5119b2a\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-9259e1d\" data-id=\"9259e1d\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-0dd8e15 elementor-widget elementor-widget-text-editor\" data-id=\"0dd8e15\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>La visualisation de donn\u00e9es est tr\u00e8s utilis\u00e9e dans tous les secteurs d&rsquo;activit\u00e9. Par cons\u00e9quent, ma\u00eetriser un outil de DataViz est <strong>une comp\u00e9tence pr\u00e9cieuse et convoit\u00e9e<\/strong>.<\/p><p>Les <strong><a href=\"https:\/\/datascientest.com\/formations-data\">formations en Data de DataScientest<\/a><\/strong> permettent d&rsquo;acqu\u00e9rir cette ma\u00eetrise. Les outils Matplotlib et Seaborn sont tous deux <strong>au programme du module Data Visualization<\/strong> de nos formations Data Analyst, Data Scientist et Data Management.<\/p><p>\u00c0 travers ces cursus, vous pouvez<strong> acqu\u00e9rir toutes les comp\u00e9tences requises<\/strong> pour exercer les m\u00e9tiers d&rsquo;analyste, de manager ou de scientifiques des donn\u00e9es. Outre la DataViz, vous apprendrez aussi la programmation, le maniement des bases de donn\u00e9es, ou encore le Machine Learning et le Deep Learning.<\/p><p>Nos diff\u00e9rentes formations adoptent une approche et innovante et b\u00e9n\u00e9fique<strong> de Blended Learning<\/strong>, alliant pr\u00e9sentiel et distanciel. Elles peuvent \u00eatre r\u00e9alis\u00e9es en Formation Continue, ou en BootCamp en quelques semaines seulement.<\/p><p>\u00c0 l&rsquo;issue du parcours, les apprenants re\u00e7oivent <strong>un dipl\u00f4me certifi\u00e9 par l&rsquo;Universit\u00e9 de la Sorbonne<\/strong>. Parmi les alumnis, 93% ont trouv\u00e9 un emploi imm\u00e9diatement apr\u00e8s avoir termin\u00e9 la formation. N&rsquo;attendez plus et d\u00e9couvrez nos diff\u00e9rentes formations pour apprendre \u00e0 manier Seaborn et tous les outils de Data Science !<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-3310fb9 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"3310fb9\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-b70b328\" data-id=\"b70b328\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-c936836 elementor-widget elementor-widget-image\" data-id=\"c936836\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"632\" height=\"1024\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/Cheat-sheet-Seaborn-632x1024.jpg\" class=\"attachment-large size-large wp-image-58185\" alt=\"\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/Cheat-sheet-Seaborn-632x1024.jpg 632w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/Cheat-sheet-Seaborn-185x300.jpg 185w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/Cheat-sheet-Seaborn-768x1245.jpg 768w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/Cheat-sheet-Seaborn-948x1536.jpg 948w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/Cheat-sheet-Seaborn.jpg 1251w\" sizes=\"(max-width: 632px) 100vw, 632px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-50337d1 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"50337d1\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-fee86a4\" data-id=\"fee86a4\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-27754f3 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"27754f3\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-grow\" href=\"\/formation-data-scientist\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Se former \u00e0 Seaborn<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-1ca58ca elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"1ca58ca\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-ee46dcf\" data-id=\"ee46dcf\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-a4ae3f2 elementor-widget elementor-widget-text-editor\" data-id=\"a4ae3f2\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Vous savez tout sur Seaborn. D\u00e9couvrez <strong><a href=\"https:\/\/datascientest.com\/data-science-definition\">notre introduction \u00e0 la Data Science<\/a><\/strong>, et notre guide pour commencer \u00e0 <strong><a href=\"https:\/\/datascientest.com\/machine-learning-python-par-ou-commencer\">utiliser Python pour le Machine Learning<\/a><\/strong>.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-03f5586 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"03f5586\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-1b1cc59\" data-id=\"1b1cc59\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-1be2aff elementor-widget elementor-widget-html\" data-id=\"1be2aff\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<script type=\"application\/ld+json\">\r\n{\r\n  \"@context\": \"https:\/\/schema.org\",\r\n  \"@type\": \"FAQPage\",\r\n  \"mainEntity\": [{\r\n    \"@type\": \"Question\",\r\n    \"name\": \"Qu'est-ce que Seaborn ?\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"Seaborn est une biblioth\u00e8que permettant de cr\u00e9er des graphiques statistiques en Python. Elle est bas\u00e9e sur Matplotlib, et s'int\u00e8gre avec les structures Pandas.\"\r\n    }\r\n  },{\r\n    \"@type\": \"Question\",\r\n    \"name\": \"Seaborn et les diff\u00e9rents types de Dataviz\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"Seaborn fournit diff\u00e9rents styles et palettes de couleur par d\u00e9faut permettant de cr\u00e9er des graphismes plus attrayants. Les diff\u00e9rents types de visualisations permettent de mettre en lumi\u00e8re les relations entre les donn\u00e9es. Il peut s'agir de variables num\u00e9riques ou de groupes, de classes, de divisions.\"\r\n    }\r\n  },{\r\n    \"@type\": \"Question\",\r\n    \"name\": \"Quels sont les avantages de Seaborn ?\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"La biblioth\u00e8que Seaborn offre plusieurs avantages majeurs. Elle fournit diff\u00e9rents types de visualisations. Sa syntaxe est r\u00e9duite, et elle propose des th\u00e8mes par d\u00e9faut tr\u00e8s attrayants.\"\r\n    }\r\n  },{\r\n    \"@type\": \"Question\",\r\n    \"name\": \"Seaborn vs Matplotlib : lequel utiliser ?\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"Matplotlib et Seaborn sont les deux outils Python les plus populaires pour la Data Visualization. Chacun pr\u00e9sente des avantages et des inconv\u00e9nients.\"\r\n    }\r\n  }]\r\n}\r\n<\/script>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Seaborn est un outil de Data Visualization en langage Python. D\u00e9couvrez tout ce que vous devez savoir : pr\u00e9sentation, cas d&rsquo;usage, avantages, formations&#8230; La Data Visualization est une technique permettant aux Data Scientists de transformer des donn\u00e9es brutes en graphiques et en diagrammes. De telles illustrations facilitent la lecture et la compr\u00e9hension des donn\u00e9es, c&rsquo;est [&hellip;]<\/p>\n","protected":false},"author":77,"featured_media":57997,"comment_status":"open","ping_status":"open","sticky":false,"template":"elementor_theme","format":"standard","meta":{"content-type":"","inline_featured_image":false},"categories":[2497],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v21.7 (Yoast SEO v21.7) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Seaborn : tout savoir sur l&#039;outil de Data Visualization en Python<\/title>\n<meta name=\"description\" content=\"Seaborn est un outil de Data Visualization en langage Python. 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