{"id":2067,"date":"2026-07-27T02:00:51","date_gmt":"2026-07-27T02:00:51","guid":{"rendered":"https:\/\/www.vpascode.com\/fr\/docs\/uncategorized\/scatter-chart-bivariate-distribution-and-point-clustering-guide\/"},"modified":"2026-07-27T02:00:51","modified_gmt":"2026-07-27T02:00:51","slug":"scatter-chart-bivariate-distribution-and-point-clustering-guide","status":"publish","type":"ld_docs","link":"https:\/\/www.vpascode.com\/fr\/docs\/vpascode-docs\/scatter-chart-bivariate-distribution-and-point-clustering-guide\/","title":{"rendered":"Graphique en nuage de points : distribution bivari\u00e9e et regroupement de points"},"content":{"rendered":"

Lorsqu’on explore les relations ou les corr\u00e9lations entre deux variables continues, le Graphique en nuage de points<\/strong> (ou graphique de dispersion) est l’outil analytique principal. En tra\u00e7ant des points de donn\u00e9es sur une grille bidimensionnelle bas\u00e9e sur des coordonn\u00e9es num\u00e9riques X et Y, les graphiques en nuage de points permettent de r\u00e9v\u00e9ler des regroupements, des valeurs aberrantes, des tendances et des corr\u00e9lations<\/em> sur des jeux de donn\u00e9es complexes, tels que les d\u00e9penses marketing par rapport \u00e0 la g\u00e9n\u00e9ration de leads ou l’exp\u00e9rience des employ\u00e9s par rapport au salaire.<\/p>\n

Le fonctionnement des graphiques en nuage de points<\/h2>\n

Contrairement aux graphiques \u00e0 colonnes ou \u00e0 lignes pilot\u00e9s par des cat\u00e9gories, les graphiques en nuage de points utilisent des axes de valeurs num\u00e9riques pour les deux dimensions. Dans Apache ECharts, d\u00e9finir type: 'scatter'<\/code> attend des donn\u00e9es format\u00e9es sous forme de tableaux de coordonn\u00e9es num\u00e9riques \u00e0 deux \u00e9l\u00e9ments [x, y]<\/code> ou des objets de donn\u00e9es mapp\u00e9s sur des axes num\u00e9riques xAxis<\/code> et yAxis<\/code> configurations.<\/p>\n

1. Configuration essentielle<\/h3>\n

Pour cr\u00e9er un graphique en nuage de points basique, d\u00e9finissez type: 'value'<\/code> sur les deux axes et fournissez des paires de coordonn\u00e9es num\u00e9riques dans votre tableau de 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        formatter: 'X\u00a0: {c0}\r\nY\u00a0: {c1}'\r\n    },\r\n    xAxis: {\r\n        type: 'value',\r\n        name: 'D\u00e9penses publicitaires (en milliers $)'\r\n    },\r\n    yAxis: {\r\n        type: 'value',\r\n        name: 'Conversions'\r\n    },\r\n    series: [\r\n        {\r\n            type: 'scatter',\r\n            symbolSize: 12,\r\n            data: [\r\n                [10.0, 8.04],\r\n                [8.07, 6.95],\r\n                [13.0, 7.58],\r\n                [9.05, 8.81],\r\n                [11.0, 8.33],\r\n                [14.0, 9.96],\r\n                [6.03, 7.24],\r\n                [12.0, 4.26],\r\n                [7.08, 4.82],\r\n                [5.02, 5.68]\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
Les graphiques en nuage de points peuvent int\u00e9grer un redimensionnement dynamique pour repr\u00e9senter une troisi\u00e8me variable (graphique \u00e0 bulles) ou afficher des superpositions de regroupements multiculturels.<\/p>\n
1. Taille variable des points (effet bulle)<\/h3>\n
Passez une fonction personnalis\u00e9e ou un mappage de valeurs de donn\u00e9es \u00e0 symbolSize<\/code> pour encoder une troisi\u00e8me m\u00e9trique quantitative dans la taille des points :<\/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        formatter: function (param) {\r\n            return 'D\u00e9penses : $' + param.data[0] + 'krn' +\r\n                   'Revenus : $' + param.data[1] + 'krn' +\r\n                   'ROAS : ' + param.data[2] + 'x';\r\n        }\r\n    },\r\n    xAxis: {\r\n        type: 'value',\r\n        name: 'D\u00e9penses'\r\n    },\r\n    yAxis: {\r\n        type: 'value',\r\n        name: 'Revenus'\r\n    },\r\n    series: [\r\n        {\r\n            name: 'Campagnes',\r\n            type: 'scatter',\r\n            symbolSize: function (data) {\r\n                return data[2] * 5; \/\/ Ajuster la taille des bulles selon la troisi\u00e8me variable\r\n            },\r\n            data: [\r\n                [15, 120, 8.0],\r\n                [25, 180, 7.2],\r\n                [10, 50, 5.0],\r\n                [40, 380, 9.5],\r\n                [30, 210, 7.0]\r\n            ],\r\n            itemStyle: {\r\n                color: '#5470c6',\r\n                opacity: 0.7\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
Contr\u00f4ler l’opacit\u00e9 des marqueurs et ajouter des lignes de tendance cibles emp\u00eache les groupes denses de se transformer en masses visuelles solides.<\/p>\n
1. Marqueurs translucides et style des groupes<\/h3>\n
Appliquer des contours et des remplissages semi-transparents permet de maintenir les points de donn\u00e9es superpos\u00e9s visibles au sein des groupes \u00e0 forte densit\u00e9 :<\/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: 'value',\r\n        scale: true \/\/ Ajuster automatiquement les min\/max de l'axe pour ajuster \u00e9troitement aux donn\u00e9es\r\n    },\r\n    yAxis: {\r\n        type: 'value',\r\n        scale: true\r\n    },\r\n    series: [\r\n        {\r\n            type: 'scatter',\r\n            symbolSize: 16,\r\n            itemStyle: {\r\n                color: 'rgba(84, 112, 198, 0.6)',\r\n                borderColor: '#5470c6',\r\n                borderWidth: 2\r\n            },\r\n            data: [\r\n                [161.2, 51.6], [167.5, 59.0], [159.5, 49.2], [157.0, 63.0],\r\n                [155.8, 53.6], [170.0, 59.0], [159.1, 47.6], [166.0, 69.8],\r\n                [176.2, 66.8], [160.2, 75.2], [172.5, 55.2], [170.9, 54.2]\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
Meilleures pratiques strat\u00e9giques<\/h2>\n
    \n
  • Activer scale : true<\/code> sur les axes num\u00e9riques :<\/strong> D\u00e9finir scale : true<\/code> sur les deux axes num\u00e9riques afin que le graphique s’ajuste automatiquement \u00e0 la plage de donn\u00e9es pertinente au lieu de forcer l’origine \u00e0 (0,0)<\/code>.<\/li>\n
  • Utiliser la transparence du remplissage pour les superpositions :<\/strong> Lors du trac\u00e9 de centaines de points, r\u00e9duisez l’opacit\u00e9 du remplissage \u00e0 environ 0,4\u20130,6 afin que les zones de superposition denses apparaissent naturellement plus fonc\u00e9es.<\/li>\n
  • Fournir des \u00e9tiquettes d’axes contextuelles :<\/strong> Marquez toujours les axes X et Y explicitement avec les unit\u00e9s de mesure (par exemple, \u00ab $ en milliers \u00bb ou \u00ab Latence en ms \u00bb) afin que les valeurs soient imm\u00e9diatement claires sans avoir \u00e0 consulter les infobulles.<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"
    Lorsqu’on explore les relations ou les corr\u00e9lations entre deux variables continues, le Graphique en nuage de points (ou graphique de dispersion) est l’outil analytique principal. En tra\u00e7ant des points de donn\u00e9es sur une grille bidimensionnelle bas\u00e9e sur des coordonn\u00e9es num\u00e9riques…<\/p>\n","protected":false},"author":3,"featured_media":0,"parent":0,"menu_order":11,"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 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Scatter Chart Guide | VPasCode Text to Diagram Tool<\/title>\n<meta name=\"description\" content=\"Analyze correlation trends between data variables using ECharts scatter plots 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\/scatter-chart-bivariate-distribution-and-point-clustering-guide\/\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"ECharts Scatter Chart Guide | VPasCode Text to Diagram Tool\" \/>\n<meta property=\"og:description\" content=\"Analyze correlation trends between data variables using ECharts scatter plots in VPasCode, a diagram-as-code tool.\" \/>\n<meta property=\"og:url\" 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