{"id":2062,"date":"2026-07-27T02:10:31","date_gmt":"2026-07-27T02:10:31","guid":{"rendered":"https:\/\/www.vpascode.com\/de\/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\/de\/docs\/vpascode-docs\/boxplot-chart-statistical-distribution-and-outlier-spotting-guide\/","title":{"rendered":"Boxplot-Diagramm: Statistische Verteilung und Ausrei\u00dfererkennung"},"content":{"rendered":"

Wenn Sie die Datenstreuung analysieren und ungew\u00f6hnliche Datenpunkte \u00fcber Gruppen hinweg identifizieren m\u00fcssen, ist das Boxplot-Diagramm<\/strong> (oder Box-and-Whisker-Diagramm) das Standardwerkzeug der statistischen Visualisierung. Durch die Zusammenfassung kontinuierlicher Daten in f\u00fcnf Schl\u00fcsselzahlen \u2013 Minimum, Erstes Quartil (Q1), Median (Q2), Drittes Quartil (Q3) und Maximum \u2013 zeigen Boxplot-Diagramme Schiefheit, Variabilit\u00e4t und extreme Ausrei\u00dfer<\/em> auf einen Blick, ohne den Bildschirm mit Rohdaten zu \u00fcberladen.<\/p>\n

Die Funktionsweise von Boxplot-Diagrammen<\/h2>\n

In Apache ECharts werden statistische Boxen mit type: 'boxplot'<\/code>. Jeder Datensatz-Eintrag erwartet ein 5-elementiges numerisches Array in der Reihenfolge [Minimum, Q1, Median, Q3, Maximum]<\/code>. ECharts verf\u00fcgt au\u00dferdem \u00fcber ein integriertes Werkzeug zur Datenbereinigung, das diese statistischen Grenzen direkt aus Rohzahlen berechnet.<\/p>\n

1. Grundlegende Einrichtung<\/h3>\n

Um ein grundlegendes Boxplot zu erstellen, ordnen Sie Kategorien entlang der X-Achse zu und geben Sie berechnete 5-Zahlen-Zusammenfassungs-Arrays innerhalb Ihrer Seriendaten an:<\/p>\n

\n
\nECharts<\/span>
\n
\n<\/path><\/path><\/svg>
\nECharts in VPasCode bearbeiten<\/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: ['Kategorie 1', 'Kategorie 2', 'Kategorie 3', 'Kategorie 4', 'Kategorie 5']\r\n    },\r\n    yAxis: {\r\n        type: 'value',\r\n        name: 'Verteilungswert'\r\n    },\r\n    series: [\r\n        {\r\n            name: 'Boxplot',\r\n            type: 'boxplot',\r\n            data: [\r\n                [655, 850, 940, 980, 1070], \/\/ [Min, Q1, Median, 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>
\nECharts in VPasCode bearbeiten<\/span>
\n<\/a>\n<\/div>\n<\/div>\n
\"\"<\/p>\n
\u00a0<\/p>\n
Erweiterte strukturelle Techniken<\/h2>\n
Sie k\u00f6nnen Ausrei\u00dfer-Streudiagramme \u00fcberlagern oder horizontale Boxplots f\u00fcr Kategorien mit langen Namen erstellen.<\/p>\n
1. Horizontales Boxplot-Layout<\/h3>\n
Legen Sie yAxis<\/code> als Kategorien-Skala und xAxis<\/code> als numerische Wert-Skala fest, um Boxplots horizontal zu drehen, um die Beschriftungslesbarkeit zu verbessern:<\/p>\n
\n
\nECharts<\/span>
\n
\n<\/path><\/path><\/svg>
\nECharts in VPasCode bearbeiten<\/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: ['Server Alpha', 'Server Beta', 'Server Gamma']\r\n    },\r\n    series: [\r\n        {\r\n            name: 'Latenz (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>
\nECharts in VPasCode bearbeiten<\/span>
\n<\/a>\n<\/div>\n<\/div>\n
\"\"<\/p>\n
\u00a0<\/p>\n
Feinabstimmung von Layout und Stil<\/h2>\n
Benutzerdefinierte Boxfarben, Whisker-Breiten und Formatierung der Medianlinie verbessern die visuelle Unterscheidbarkeit in komplexen Dashboard-Layouts.<\/p>\n
1. Benutzerdefinierte F\u00fcllung der Box und Darstellung von Ausrei\u00dfern<\/h3>\n
Stile Box-R\u00e4nder, F\u00fcllfarben und Whisker-Linie-Eigenschaften, um sie an Ihr Schnittstellen-Design anzupassen:<\/p>\n
\n
\nECharts<\/span>
\n
\n<\/path><\/path><\/svg>
\nECharts in VPasCode bearbeiten<\/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: ['Gruppe A', 'Gruppe B', 'Gruppe C']\r\n    },\r\n    yAxis: {\r\n        type: 'value'\r\n    },\r\n    series: [\r\n        {\r\n            name: 'Score-Verteilung',\r\n            type: 'boxplot',\r\n            boxWidth: ['20%', '50%'], \/\/ Responsive box width boundaries\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>
\nECharts in VPasCode bearbeiten<\/span>
\n<\/a>\n<\/div>\n<\/div>\n
\"\"<\/p>\n
\u00a0<\/p>\n
Strategische Best Practices<\/h2>\n
    \n
  • \u00dcberpr\u00fcfen Sie die Reihenfolge der Zusammenfassung:<\/strong>Stellen Sie sicher, dass die Array-Werte der strengen Reihenfolge folgen:[Minimum, Q1, Median, Q3, Maximum]<\/code>. Falsche Reihenfolge f\u00fchrt zu Darstellungsfehlern.<\/li>\n
  • \u00dcberlagern Sie Ausrei\u00dfer mit einer Streuungsreihe:<\/strong>Verwenden Sie eine sekund\u00e4reStreuung<\/code>Reihe \u00fcber der Boxplot-Darstellung, um extreme statistische Ausrei\u00dfer als einzelne Datenpunkte darzustellen.<\/li>\n
  • Rastereinr\u00fcckung anpassen:<\/strong>Stellen Sie sicher, dass ausreichendgrid.bottom<\/code>odergrid.left<\/code>Einr\u00fcckung vorhanden ist, damit lange Kategorienamen nicht mit Whisker-Linien kollidieren.<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"
    Wenn Sie die Datenstreuung analysieren und ungew\u00f6hnliche Datenpunkte \u00fcber Gruppen hinweg identifizieren m\u00fcssen, ist das Boxplot-Diagramm (oder Box-and-Whisker-Diagramm) das Standardwerkzeug der statistischen Visualisierung. Durch die Zusammenfassung kontinuierlicher Daten in f\u00fcnf Schl\u00fcsselzahlen \u2013 Minimum, Erstes Quartil (Q1), Median (Q2), Drittes Quartil…<\/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\/de\/docs\/vpascode-docs\/boxplot-chart-statistical-distribution-and-outlier-spotting-guide\/\" \/>\n<meta property=\"og:locale\" content=\"de_DE\" \/>\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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