{"id":2064,"date":"2026-07-27T02:10:31","date_gmt":"2026-07-27T02:10:31","guid":{"rendered":"https:\/\/www.vpascode.com\/fr\/docs\/uncategorized\/boxplot-chart-statistical-distribution-and-outlier-spotting-guide\/"},"modified":"2026-07-27T02:10:31","modified_gmt":"2026-07-27T02:10:31","slug":"boxplot-chart-statistical-distribution-and-outlier-spotting-guide","status":"publish","type":"ld_docs","link":"https:\/\/www.vpascode.com\/fr\/docs\/vpascode-docs\/boxplot-chart-statistical-distribution-and-outlier-spotting-guide\/","title":{"rendered":"Graphique bo\u00eete \u00e0 moustaches : distribution statistique et d\u00e9tection des valeurs aberrantes"},"content":{"rendered":"

Lorsque vous devez analyser la dispersion des donn\u00e9es et identifier des points de donn\u00e9es inhabituels au sein de groupes, le Graphique bo\u00eete \u00e0 moustaches<\/strong> (ou diagramme bo\u00eete \u00e0 moustaches) est l’outil visuel statistique standard. En r\u00e9sumant les donn\u00e9es continues en cinq valeurs cl\u00e9s \u2014 minimum, premier quartile (Q1), m\u00e9diane (Q2), troisi\u00e8me quartile (Q3) et maximum \u2014 les graphiques bo\u00eete \u00e0 moustaches r\u00e9v\u00e8lent la dissym\u00e9trie, la variabilit\u00e9 et les valeurs aberrantes extr\u00eames<\/em> d’un coup d’\u0153il, sans encombrer l’\u00e9cran avec les donn\u00e9es brutes.<\/p>\n

Le fonctionnement des graphiques bo\u00eete \u00e0 moustaches<\/h2>\n

Dans Apache ECharts, les bo\u00eetes statistiques sont rendues en utilisant type : 'boxplot'<\/code>. Chaque entr\u00e9e de jeu de donn\u00e9es attend un tableau num\u00e9rique \u00e0 5 \u00e9l\u00e9ments ordonn\u00e9s comme suit : [Minimum, Q1, M\u00e9diane, Q3, Maximum]<\/code>. ECharts inclut \u00e9galement un outil int\u00e9gr\u00e9 de pr\u00e9paration des donn\u00e9es pour calculer directement ces limites statistiques \u00e0 partir des nombres bruts.<\/p>\n

1. Configuration de base<\/h3>\n

Pour construire un graphique bo\u00eete \u00e0 moustaches de base, mappez les cat\u00e9gories sur l’axe X et fournissez des tableaux de r\u00e9sum\u00e9 \u00e0 5 nombres calcul\u00e9s dans vos donn\u00e9es de s\u00e9rie :<\/p>\n

\n
\nECharts<\/span>
\n
\n<\/path><\/path><\/svg>
\nModifier ECharts dans VPasCode<\/span>
\n<\/a>\n<\/div>\n
\n
\r\n
\r\n ECharts<\/span>\r\n \r\n <\/path><\/path><\/svg>\r\n Edit ECharts in VPasCode<\/span>\r\n <\/a>\r\n <\/div>\r\n
\r\n 
option = {\r\n    tooltip: {\r\n        trigger: 'item',\r\n        axisPointer: { type: 'shadow' }\r\n    },\r\n    xAxis: {\r\n        type: 'category',\r\n        data: ['Cat\u00e9gorie 1', 'Cat\u00e9gorie 2', 'Cat\u00e9gorie 3', 'Cat\u00e9gorie 4', 'Cat\u00e9gorie 5']\r\n    },\r\n    yAxis: {\r\n        type: 'value',\r\n        name: 'Valeur de distribution'\r\n    },\r\n    series: [\r\n        {\r\n            name: 'Bo\u00eete \u00e0 moustaches',\r\n            type: 'boxplot',\r\n            data: [\r\n                [655, 850, 940, 980, 1070], \/\/ [Min, Q1, M\u00e9diane, Q3, Max]\r\n                [760, 800, 845, 885, 960],\r\n                [780, 840, 855, 880, 940],\r\n                [720, 767, 815, 865, 920],\r\n                [890, 920, 950, 970, 990]\r\n            ]\r\n        }\r\n    ]\r\n};<\/code><\/pre>                <\/div>\r\n                
\r\n                    \r\n                        <\/path><\/path><\/svg>\r\n                        Edit ECharts in VPasCode<\/span>\r\n                    <\/a>\r\n                <\/div>\r\n            <\/div>\r\n            \n<\/p><\/div>\n
\n
\n<\/path><\/path><\/svg>
\nModifier ECharts dans VPasCode<\/span>
\n<\/a>\n<\/div>\n<\/div>\n
\"\"<\/p>\n
\u00a0<\/p>\n
Techniques structurelles avanc\u00e9es<\/h2>\n
Vous pouvez superposer des points de dispersion des valeurs aberrantes ou cr\u00e9er des graphiques bo\u00eete \u00e0 moustaches horizontaux pour des cat\u00e9gories dont les noms sont longs.<\/p>\n
1. Disposition horizontale du graphique bo\u00eete \u00e0 moustaches<\/h3>\n
D\u00e9finissez yAxis<\/code> comme \u00e9chelle des cat\u00e9gories et xAxis<\/code> comme \u00e9chelle des valeurs num\u00e9riques pour retourner les graphiques bo\u00eete \u00e0 moustaches horizontalement afin d’am\u00e9liorer la lisibilit\u00e9 des \u00e9tiquettes :<\/p>\n
\n
\nECharts<\/span>
\n
\n<\/path><\/path><\/svg>
\nModifier ECharts dans VPasCode<\/span>
\n<\/a>\n<\/div>\n
\n            
\r\n                                
\r\n                    ECharts<\/span>\r\n                    \r\n                        <\/path><\/path><\/svg>\r\n                        Edit ECharts in VPasCode<\/span>\r\n                    <\/a>\r\n                <\/div>\r\n                                
\r\n                    
option = {\r\n    tooltip: {\r\n        trigger: 'item',\r\n        axisPointer: { type: 'shadow' }\r\n    },\r\n    xAxis: {\r\n        type: 'value'\r\n    },\r\n    yAxis: {\r\n        type: 'category',\r\n        data: ['Serveur Alpha', 'Serveur Beta', 'Serveur Gamma']\r\n    },\r\n    series: [\r\n        {\r\n            name: 'Latence (ms)',\r\n            type: 'boxplot',\r\n            data: [\r\n                [12, 18, 22, 28, 35],\r\n                [15, 24, 30, 38, 48],\r\n                [8, 12, 15, 20, 27]\r\n            ],\r\n            itemStyle: {\r\n                color: '#e0f2fe',\r\n                borderColor: '#0284c7',\r\n                borderWidth: 2\r\n            }\r\n        }\r\n    ]\r\n};<\/code><\/pre>                <\/div>\r\n                
\r\n                    \r\n                        <\/path><\/path><\/svg>\r\n                        Edit ECharts in VPasCode<\/span>\r\n                    <\/a>\r\n                <\/div>\r\n            <\/div>\r\n            \n<\/p><\/div>\n
\n
\n<\/path><\/path><\/svg>
\nModifier ECharts dans VPasCode<\/span>
\n<\/a>\n<\/div>\n<\/div>\n
\"\"<\/p>\n
\u00a0<\/p>\n
Affinage du layout et du style<\/h2>\n
Les couleurs personnalis\u00e9es des bo\u00eetes, les largeurs des moustaches et le formatage de la ligne m\u00e9diane am\u00e9liorent la distinction visuelle dans les tableaux de bord complexes.<\/p>\n
1. Remplissage personnalis\u00e9 des bo\u00eetes et style des valeurs aberrantes<\/h3>\n
Personnalisez les bordures des bo\u00eetes, les couleurs de remplissage et les propri\u00e9t\u00e9s des lignes des moustaches pour correspondre \u00e0 votre design d’interface :<\/p>\n
\n
\nECharts<\/span>
\n
\n<\/path><\/path><\/svg>
\nModifier ECharts dans VPasCode<\/span>
\n<\/a>\n<\/div>\n
\n            
\r\n                                
\r\n                    ECharts<\/span>\r\n                    \r\n                        <\/path><\/path><\/svg>\r\n                        Edit ECharts in VPasCode<\/span>\r\n                    <\/a>\r\n                <\/div>\r\n                                
\r\n                    
option = {\r\n    grid: {\r\n        left: '10%',\r\n        right: '10%',\r\n        containLabel: true\r\n    },\r\n    xAxis: {\r\n        type: 'category',\r\n        data: ['Groupe A', 'Groupe B', 'Groupe C']\r\n    },\r\n    yAxis: {\r\n        type: 'value'\r\n    },\r\n    series: [\r\n        {\r\n            name: 'R\u00e9partition des scores',\r\n            type: 'boxplot',\r\n            boxWidth: ['20%', '50%'], \/\/ Limites de largeur de bo\u00eete r\u00e9active\r\n            itemStyle: {\r\n                color: '#f0fdf4',\r\n                borderColor: '#16a34a',\r\n                borderWidth: 2\r\n            },\r\n            data: [\r\n                [40, 55, 68, 82, 95],\r\n                [50, 62, 75, 88, 98],\r\n                [30, 45, 58, 70, 85]\r\n            ]\r\n        }\r\n    ]\r\n};<\/code><\/pre>                <\/div>\r\n                
\r\n                    \r\n                        <\/path><\/path><\/svg>\r\n                        Edit ECharts in VPasCode<\/span>\r\n                    <\/a>\r\n                <\/div>\r\n            <\/div>\r\n            \n<\/p><\/div>\n
\n
\n<\/path><\/path><\/svg>
\nModifier ECharts dans VPasCode<\/span>
\n<\/a>\n<\/div>\n<\/div>\n
\"\"<\/p>\n
\u00a0<\/p>\n
Meilleures pratiques strat\u00e9giques<\/h2>\n
    \n
  • V\u00e9rifiez l’ordre des r\u00e9sum\u00e9s :<\/strong>V\u00e9rifiez que les valeurs du tableau suivent l’ordre strict :[Minimum, Q1, M\u00e9diane, Q3, Maximum]<\/code>. Un ordre incorrect provoquera des artefacts d’affichage.<\/li>\n
  • Superposez les valeurs aberrantes avec une s\u00e9rie en nuage de points :<\/strong>Utilisez une s\u00e9rie secondairenuage de points<\/code> sur le dessus du diagramme en bo\u00eete pour afficher les valeurs aberrantes statistiques extr\u00eames comme des points de donn\u00e9es individuels.<\/li>\n
  • Ajustez les marges de la grille :<\/strong>Assurez-vous d’avoir une marge suffisantegrid.bottom<\/code> ou grid.left<\/code> pour que les noms de cat\u00e9gorie longs ne heurtent pas les lignes des moustaches.<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"
    Lorsque vous devez analyser la dispersion des donn\u00e9es et identifier des points de donn\u00e9es inhabituels au sein de groupes, le Graphique bo\u00eete \u00e0 moustaches (ou diagramme bo\u00eete \u00e0 moustaches) est l’outil visuel statistique standard. En r\u00e9sumant les donn\u00e9es continues en…<\/p>\n","protected":false},"author":3,"featured_media":0,"parent":0,"menu_order":14,"template":"","meta":{"inline_featured_image":false,"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"default","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center 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Boxplot Chart Guide | VPasCode Text to Diagram Tool<\/title>\n<meta name=\"description\" content=\"Plot statistical quartile distributions and outliers with ECharts boxplot scripts in VPasCode, a diagram-as-code tool.\" \/>\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.vpascode.com\/fr\/docs\/vpascode-docs\/boxplot-chart-statistical-distribution-and-outlier-spotting-guide\/\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"ECharts Boxplot Chart Guide | VPasCode Text to Diagram Tool\" \/>\n<meta property=\"og:description\" content=\"Plot statistical quartile distributions and outliers with ECharts boxplot scripts in VPasCode, a diagram-as-code tool.\" \/>\n<meta property=\"og:url\" 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