{"id":2056,"date":"2026-07-27T02:28:09","date_gmt":"2026-07-27T02:28:09","guid":{"rendered":"https:\/\/www.vpascode.com\/pl\/docs\/uncategorized\/parallel-chart-multi-dimensional-data-analysis-guide\/"},"modified":"2026-07-27T02:28:09","modified_gmt":"2026-07-27T02:28:09","slug":"parallel-chart-multi-dimensional-data-analysis-guide","status":"publish","type":"ld_docs","link":"https:\/\/www.vpascode.com\/pl\/docs\/vpascode-docs\/parallel-chart-multi-dimensional-data-analysis-guide\/","title":{"rendered":"Wykres r\u00f3wnoleg\u0142y: analiza danych wielowymiarowych"},"content":{"rendered":"

Podczas por\u00f3wnywania punkt\u00f3w danych wielowymiarowych na wielu osiach liczbowych lub kategorycznych jednocze\u015bnie, Wykres wsp\u00f3\u0142rz\u0119dnych r\u00f3wnoleg\u0142ych<\/strong> jest niezb\u0119dnym narz\u0119dziem wizualnym. Zamiast mapowania wsp\u00f3\u0142rz\u0119dnych na prostopad\u0142e osie poziome i pionowe, wykresy r\u00f3wnoleg\u0142e umieszczaj\u0105 wszystkie wymiary obok siebie jako r\u00f3wnoleg\u0142e linie. Poszczeg\u00f3lne wpisy danych s\u0105 przedstawiane jako ci\u0105g\u0142e linie \u0142amane przecinaj\u0105ce ka\u017cd\u0105 o\u015b, co u\u0142atwia identyfikacj\u0119 klastery wieloatrybutowe, kompromisy, korelacje i warto\u015bci odstaj\u0105ce<\/em>\u2014na przyk\u0142ad por\u00f3wnanie modeli samochod\u00f3w pod k\u0105tem mocy silnika, wagi, zu\u017cycia paliwa, ceny i oceny bezpiecze\u0144stwa.<\/p>\n

Zasada dzia\u0142ania wykres\u00f3w r\u00f3wnoleg\u0142ych<\/h2>\n

W Apache ECharts wykresy wsp\u00f3\u0142rz\u0119dnych r\u00f3wnoleg\u0142ych opieraj\u0105 si\u0119 na dedykowanym bloku konfiguracyjnym parallelAxis<\/code> bloku konfiguracyjnym, kt\u00f3ry definiuje ka\u017cd\u0105 skal\u0119 r\u00f3wnoleg\u0142\u0105 (indeks osi, nazw\u0119 wymiaru i typ danych). Seria wykresu ustawia type: 'parallel'<\/code> i mapuje wiersze tablic warto\u015bci wieloelementowych na ka\u017cdy odpowiadaj\u0105cy indeks osi.<\/p>\n

1. Podstawowa konfiguracja<\/h3>\n

Aby stworzy\u0107 podstawowy wykres r\u00f3wnoleg\u0142y, zdefiniuj wymiary w tablicy parallelAxis<\/code> i przeka\u017c odpowiadaj\u0105ce tablice wsp\u00f3\u0142rz\u0119dnych wewn\u0105trz serii data<\/code>:<\/p>\n

\n
\nECharts<\/span>
\n
\n<\/path><\/path><\/svg>
\nEdytuj ECharts w 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    parallelAxis: [\r\n        { dim: 0, name: 'Cena ($)' },\r\n        { dim: 1, name: 'Ocena' },\r\n        { dim: 2, name: 'Waga (kg)' },\r\n        { dim: 3, name: 'Moc (KM)' }\r\n    ],\r\n    series: [\r\n        {\r\n            type: 'parallel',\r\n            lineStyle: {\r\n                width: 2\r\n            },\r\n            data: [\r\n                [1299, 4.5, 1.2, 120],\r\n                [899, 4.0, 1.5, 95],\r\n                [1599, 4.8, 1.1, 150],\r\n                [499, 3.5, 2.0, 80],\r\n                [2100, 4.9, 0.9, 180]\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>
\nEdytuj ECharts w VPasCode<\/span>
\n<\/a>\n<\/div>\n<\/div>\n
\"\"<\/p>\n
\u00a0<\/p>\n
Zaawansowane techniki strukturalne<\/h2>\n
Wykresy r\u00f3wnoleg\u0142e mog\u0105 by\u0107 \u0142\u0105czone z gradientami kolor\u00f3w wizualnymi lub mieszanymi skalami kategorycznymi w celu oceny skomplikowanych kompromis\u00f3w mi\u0119dzy r\u00f3\u017cnymi kategoriami produkt\u00f3w.<\/p>\n
1. Gradienty kolor\u00f3w mapy wizualnej na przestrzeni wymiar\u00f3w<\/h3>\n
Po\u0142\u0105cz komponent visualMap<\/code> z kluczowym wymiarem osi (na przyk\u0142ad mapowanie koloru linii na oceny wydajno\u015bci), aby natychmiast wyr\u00f3\u017cni\u0107 najlepszych wykonawc\u00f3w na wszystkich osiach r\u00f3wnoleg\u0142ych:<\/p>\n
\n
\nECharts<\/span>
\n
\n<\/path><\/path><\/svg>
\nEdytuj ECharts w 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    osiecioweOsi: [\r\n        { dim: 0, name: 'Liczba rdzeni CPU' },\r\n        { dim: 1, name: 'RAM (GB)' },\r\n        { dim: 2, name: 'Pami\u0119\u0107 (TB)' },\r\n        { dim: 3, name: 'Miesi\u0119czne koszty ($)', min: 0, max: 200 }\r\n    ],\r\n    mapaWizualna: {\r\n        pokazuj: true,\r\n        typ: 'ci\u0105g\u0142y',\r\n        min: 0,\r\n        max: 200,\r\n        wymiar: 3, \/\/ Kolorowanie \u015bcie\u017cek linii na podstawie indeksu wymiaru 3 (Miesi\u0119czne koszty)\r\n        wZakresie: {\r\n            kolor: ['#91cc75', '#fac858', '#ee6666'] \/\/ Zielony (niskie koszty) do czerwonego (wysokie koszty)\r\n        },\r\n        orientacja: 'pozioma',\r\n        g\u00f3rna: '2%',\r\n        lewa: '\u015brodek'\r\n    },\r\n    osieR\u00f3wnoleg\u0142e: {\r\n        g\u00f3rna: '18%',\r\n        dolna: '10%'\r\n    },\r\n    serie: [\r\n        {\r\n            typ: 'osieR\u00f3wnoleg\u0142e',\r\n            stylLinii: {\r\n                szeroko\u015b\u0107: 3,\r\n                przezroczysto\u015b\u0107: 0.8\r\n            },\r\n            dane: [\r\n                [4, 8, 0.5, 25],\r\n                [8, 16, 1.0, 50],\r\n                [16, 32, 2.0, 110],\r\n                [32, 64, 4.0, 185],\r\n                [12, 24, 1.5, 80]\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>
\nEdytuj ECharts w VPasCode<\/span>
\n<\/a>\n<\/div>\n<\/div>\n
\"\"<\/p>\n
\u00a0<\/p>\n
Dostosowanie uk\u0142adu i filtrowanie interaktywne<\/h2>\n
Dodanie wyg\u0142adzonych krzywych i przezroczysto\u015bci linii zapobiega przesyceniu interfejsu u\u017cytkownika przez g\u0119ste, krzy\u017cuj\u0105ce si\u0119 w\u0105tki danych.<\/p>\n
1. Wyg\u0142adzone \u015bcie\u017cki krzywych i niewyra\u017ane w\u0105tki<\/h3>\n
Ustaw smooth: true<\/code>i zmniejsz przezroczysto\u015b\u0107 linii, aby nadpisywanie danych o wysokiej g\u0119sto\u015bci i skupiska by\u0142y naturalnie widoczne:<\/p>\n
\n
\nECharts<\/span>
\n
\n<\/path><\/path><\/svg>
\nEdytuj ECharts w 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    osieR\u00f3wnoleg\u0142e: [\r\n        { dim: 0, name: 'Wynik A' },\r\n        { dim: 1, name: 'Wynik B' },\r\n        { dim: 2, name: 'Wynik C' },\r\n        { dim: 3, name: 'Wynik D' },\r\n        { dim: 4, name: 'Wynik E' }\r\n    ],\r\n    osieR\u00f3wnoleg\u0142e: {\r\n        lewa: '10%',\r\n        prawa: '10%',\r\n        dolna: '12%',\r\n        g\u00f3rna: '12%'\r\n    },\r\n    serie: [\r\n        {\r\n            typ: 'osieR\u00f3wnoleg\u0142e',\r\n            smooth: true, \/\/ Wyg\u0142adzone \u015bcie\u017cki linii dla lepszej wizualizacji\r\n            stylLinii: {\r\n                kolor: '#5470c6',\r\n                szeroko\u015b\u0107: 2,\r\n                przezroczysto\u015b\u0107: 0.45\r\n            },\r\n            dane: [\r\n                [85, 92, 78, 90, 88],\r\n                [70, 65, 80, 72, 75],\r\n                [95, 88, 92, 96, 94],\r\n                [60, 75, 68, 62, 70],\r\n                [88, 90, 85, 89, 91],\r\n                [78, 82, 74, 80, 83]\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>
\nEdytuj ECharts w VPasCode<\/span>
\n<\/a>\n<\/div>\n<\/div>\n
\"\"<\/p>\n
\u00a0<\/p>\n
Strategiczne najlepsze praktyki<\/h2>\n
    \n
  • Rozmie\u015b\u0107 osie rozwa\u017cnie:<\/strong> Umie\u015b\u0107 silnie skorelowane lub bezpo\u015brednio por\u00f3wnywalne metryki na s\u0105siednich osiach, aby \u0142atwiej by\u0142o zauwa\u017cy\u0107 zale\u017cno\u015bci i trendy przekrywaj\u0105ce si\u0119.<\/li>\n
  • U\u017cyj ni\u017cszej przezroczysto\u015bci przy du\u017cych obj\u0119to\u015bciach danych:<\/strong> Gdy rysujesz dziesi\u0105tki lub setki linii, zmniejsz przezroczysto\u015bciLinii<\/code> do 0.2<\/code>\u20130.5<\/code> aby nak\u0142adaj\u0105ce si\u0119 trendy tworzy\u0142y naturalnie ciemniejsze, g\u0119ste pasma.<\/li>\n
  • W\u0142\u0105cz smooth: true<\/code> dla z\u0142o\u017conych zestaw\u00f3w danych:<\/strong> Zastosowanie delikatnego wygi\u0119cia \u015bcie\u017cek linii zmniejsza ostre k\u0105ty wizualne, gdy w\u0105tki przecinaj\u0105 wiele osi r\u00f3wnoleg\u0142ych w szybkim szyku.<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"
    Podczas por\u00f3wnywania punkt\u00f3w danych wielowymiarowych na wielu osiach liczbowych lub kategorycznych jednocze\u015bnie, Wykres wsp\u00f3\u0142rz\u0119dnych r\u00f3wnoleg\u0142ych jest niezb\u0119dnym narz\u0119dziem wizualnym. Zamiast mapowania wsp\u00f3\u0142rz\u0119dnych na prostopad\u0142e osie poziome i pionowe, wykresy r\u00f3wnoleg\u0142e umieszczaj\u0105 wszystkie wymiary obok siebie jako r\u00f3wnoleg\u0142e linie. Poszczeg\u00f3lne wpisy…<\/p>\n","protected":false},"author":3,"featured_media":0,"parent":0,"menu_order":19,"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 center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-4)","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":"var(--ast-global-color-4)","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":""}}},"ld_collection":[14],"class_list":["post-2056","ld_docs","type-ld_docs","status-publish","hentry","ld_collection-vpascode-docs"],"yoast_head":"\nECharts Parallel Chart Guide | VPasCode Text to Diagram Guide<\/title>\n<meta name=\"description\" content=\"Plot multi-dimensional feature comparison charts with ECharts parallel coordinates in VPasCode, a text to diagram 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\/pl\/docs\/vpascode-docs\/parallel-chart-multi-dimensional-data-analysis-guide\/\" \/>\n<meta property=\"og:locale\" content=\"pl_PL\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"ECharts Parallel Chart Guide | VPasCode Text to Diagram Guide\" \/>\n<meta property=\"og:description\" content=\"Plot multi-dimensional feature comparison charts with ECharts parallel coordinates in VPasCode, a text to diagram tool.\" \/>\n<meta property=\"og:url\" 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