{"id":3208,"date":"2017-04-20T16:06:22","date_gmt":"2017-04-20T16:06:22","guid":{"rendered":"https:\/\/www.anychart.com\/blog\/?p=3208"},"modified":"2018-11-15T11:58:24","modified_gmt":"2018-11-15T11:58:24","slug":"data-composition-part-whole-chart-type","status":"publish","type":"post","link":"https:\/\/www.anychart.com\/blog\/2017\/04\/20\/data-composition-part-whole-chart-type\/","title":{"rendered":"Choose Right Chart Type for Data Visualization. Part 2: Data Composition, Parts to Whole"},"content":{"rendered":"<p><img decoding=\"async\" class=\"alignnone wp-image-3326 size-full\" src=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2017\/03\/chart-types-for-data-composition-part-to-whole-analysis.png\" alt=\"Chart types for data composition and part-to-whole visualization\" width=\"100%\" srcset=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2017\/03\/chart-types-for-data-composition-part-to-whole-analysis.png 1200w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2017\/03\/chart-types-for-data-composition-part-to-whole-analysis-300x170.png 300w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2017\/03\/chart-types-for-data-composition-part-to-whole-analysis-768x435.png 768w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2017\/03\/chart-types-for-data-composition-part-to-whole-analysis-1024x579.png 1024w\" sizes=\"(max-width: 1200px) 100vw, 1200px\" \/>Illustrating part-to-whole relationships for further analysis is a very popular objective\u00a0in data visualization. Basically, it is one of the most widespread ones, e.g. along with <a href=\"https:\/\/www.anychart.com\/blog\/2017\/04\/12\/data-comparison-chart-type-visualization\/\" target=\"_blank\">data comparison<\/a>. With\u00a0that in mind, the second part of the\u00a0<a href=\"https:\/\/www.anychart.com\/blog\/category\/choosing-chart-type\/\" target=\"_blank\"><em><strong>Choose Right Chart Type for Data Visualization<\/strong><\/em><\/a> series on our blog focuses on\u00a0how to display\u00a0<strong>Data Composition<\/strong>\u00a0properly.<\/p>\n<p>In particular, this article will show you the best ways to present the share percentages of\u00a0simple values, compositional patterns in large data sets and hierarchical data (also with subordination), and stages in a process.<\/p>\n<p><!--more--><\/p>\n<h2>List of Chart Types for Visualizing Composition of Data<\/h2>\n<p>First things first. Below is a basic list of chart types that explicitly serve the purpose of displaying\u00a0compositional patterns in data:<\/p>\n<ul>\n<li><span style=\"font-weight: 400;\">Pie and Donut charts;<\/span><\/li>\n<li><span style=\"font-weight: 400;\">TreeMap charts;<\/span><\/li>\n<li><span style=\"font-weight: 400;\">Funnel and Pyramid charts.<\/span><\/li>\n<\/ul>\n<p>We&#8217;ll proceed to describe and explain\u00a0these right away.<\/p>\n<h2>Choosing Charts to Display Data Composition<\/h2>\n<h3>Pie Chart, Donut Chart<\/h3>\n<p>When you are trying to <strong>figure out the percentage composition of a value<\/strong>, the first chart type that often comes to mind is the <a href=\"https:\/\/www.anychart.com\/chartopedia\/chart-types\/pie-chart\/\" target=\"_blank\">Pie chart<\/a>. These charts visualize the whole value as a circle (100%) and its parts as &#8220;slices&#8221; relative to their magnitude. The main issues you should keep in mind when using the pie chart is keep the number of parts small, 7 max, and avoid too large and too small differences between magnitudes as these can make the chart hard to read.<\/p>\n<p style=\"padding-left: 30px;\"><em><strong>AnyChart Warning: Pie Chart War!<\/strong><br \/>\nSome critics of the Pie chart such as data visualization expert Stephen Few have argued that this chart type is the worst possible way to communicate data (\u201c<a href=\"http:\/\/www.perceptualedge.com\/articles\/visual_business_intelligence\/save_the_pies_for_dessert.pdf\" target=\"_blank\" rel=\"nofollow\">Save the Pies for Dessert<\/a>\u201d). While we recognize the shortcomings of these charts, it is plain to see that the Pie chart still lives and breathes in communication of information. So if you plan to use them, do so with certain constraints in mind.<\/em><\/p>\n<p>For example: sales by channel.<\/p>\n<p><a href=\"https:\/\/playground.anychart.com\/chartopedia-gallery\/7.13.0\/samples\/Pie_Chart\" target=\"_blank\" rel=\"nofollow\"><img decoding=\"async\" class=\"alignnone wp-image-3241 size-full\" title=\"Click to see the interactive version of this Pie chart\" src=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2017\/03\/data-composition-pie-chart-type.png\" alt=\"Pie chart of sales by channel for data composition (part-to-whole) visualization and analysis\" width=\"100%\" srcset=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2017\/03\/data-composition-pie-chart-type.png 763w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2017\/03\/data-composition-pie-chart-type-300x212.png 300w\" sizes=\"(max-width: 763px) 100vw, 763px\" \/><\/a><\/p>\n<p>Additional examples include: website traffic breakdown by gender of visitors, etc.<\/p>\n<p>To <strong>display data composition and better use the space<\/strong> at the same time, you can consider the <a href=\"https:\/\/www.anychart.com\/chartopedia\/chart-types\/donut-chart\/\" target=\"_blank\">Donut chart<\/a>, a Pie chart with the hole in the center. This allows you room to add\u00a0a title\u00a0to\u00a0the chart or any other important information without wasting the space outside the chart. Recommendations for Donut chart applications are basically the same as for Pie charts.<\/p>\n<p><a href=\"https:\/\/www.anychart.com\/products\/anychart\/gallery\/Pie_and_Donut_Charts\/Donut_Chart_with_Custom_Categories.php\" target=\"_blank\"><img decoding=\"async\" class=\"alignnone wp-image-3617 size-full\" title=\"Click to see the interactive version of this Donut chart\" src=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2017\/04\/data-composition-donut-chart-type_.png\" alt=\"Donut chart of bonds and stocks for data composition (part-to-whole) visualization and analysis\" width=\"100%\" srcset=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2017\/04\/data-composition-donut-chart-type_.png 800w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2017\/04\/data-composition-donut-chart-type_-300x179.png 300w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2017\/04\/data-composition-donut-chart-type_-768x457.png 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/><\/a><\/p>\n<p>You can find more <a href=\"https:\/\/www.anychart.com\/products\/anychart\/gallery\/Pie_and_Donut_Charts\/\" target=\"_blank\">Pie and Donut chart samples in this gallery<\/a>.<\/p>\n<h3>TreeMap Chart<\/h3>\n<p>To <strong>observe hierarchical data<\/strong>, when the composition is rather complex and tree-structured, a <a href=\"https:\/\/www.anychart.com\/chartopedia\/chart-types\/treemap\/\" target=\"_blank\">TreeMap chart<\/a> is a great solution. With this chart type, the whole (the &#8220;tree&#8221;) is visualized\u00a0as a rectangle tiled with smaller rectangles depicting branches and sub-branches proportionally, which makes it easier to grasp the structure and compare the shares.<\/p>\n<p>In fact, while Pie and Donut charts work with a small number of points, TreeMap charts are suitable <strong>for large datasets<\/strong>.<\/p>\n<p>For example: export by country of destination.<\/p>\n<p><a href=\"https:\/\/playground.anychart.com\/gallery\/7.10.0\/Tree_Maps\/Top_10_Chinese_Exports_to_the_World\" target=\"_blank\" rel=\"nofollow\"><img decoding=\"async\" class=\"alignnone wp-image-3239 size-full\" title=\"Click to see the interactive version of this TreeMap chart\" src=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2017\/03\/data-composition-treemap-chart-type.png\" alt=\"TreeMap of export by country of destination for data composition (part-to-whole) visualization and analysis\" width=\"100%\" srcset=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2017\/03\/data-composition-treemap-chart-type.png 828w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2017\/03\/data-composition-treemap-chart-type-300x203.png 300w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2017\/03\/data-composition-treemap-chart-type-768x520.png 768w\" sizes=\"(max-width: 828px) 100vw, 828px\" \/><\/a><\/p>\n<p>Additional examples include: products by group and revenue, website traffic by category of referral sources and number of visitors, etc. Take a look at more <a href=\"https:\/\/www.anychart.com\/products\/anychart\/gallery\/Tree_Map_Charts\/\" target=\"_blank\">TreeMap chart samples in this gallery<\/a>.<\/p>\n<h3>Funnel Chart, Pyramid Chart<\/h3>\n<p>When\u00a0<strong>evaluating the stages of a process<\/strong> starting with 100% and ending with a smaller percentage, to see steps, and for revealing bottlenecks (at what stages the decrease happened and at what rate), you might like the <a href=\"https:\/\/www.anychart.com\/chartopedia\/chart-types\/funnel-chart\/\" target=\"_blank\">Funnel chart<\/a>\u00a0type.<\/p>\n<p>For example: conversion of website visitors into paying customers.<\/p>\n<p><a href=\"https:\/\/www.anychart.com\/products\/anychart\/gallery\/Funnel_-_Pyramid_Charts\/Website_Statistics.php\" target=\"_blank\"><img decoding=\"async\" class=\"alignnone wp-image-3238 size-full\" title=\"Click to see the interactive version of this Funnel chart\" src=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2017\/03\/data-composition-funnel-chart-type.png\" alt=\"Funnel chart of conversion of website visitors into paying customers for data composition (part-to-whole) visualization and analysis\" width=\"100%\" srcset=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2017\/03\/data-composition-funnel-chart-type.png 862w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2017\/03\/data-composition-funnel-chart-type-300x174.png 300w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2017\/03\/data-composition-funnel-chart-type-768x445.png 768w\" sizes=\"(max-width: 862px) 100vw, 862px\" \/><\/a><\/p>\n<p>Additional examples include: sales funnels, etc.<\/p>\n<p>To <strong>understand the structure of hierarchical data (and its size) or simple subordination<\/strong>, use the <a href=\"https:\/\/www.anychart.com\/chartopedia\/chart-types\/pyramid-chart\/\" target=\"_blank\">Pyramid chart<\/a>\u00a0for your data visualization.<\/p>\n<p>For example: Open Systems Interconnection (OSI) model.<\/p>\n<p><a href=\"https:\/\/www.anychart.com\/products\/anychart\/gallery\/Funnel_-_Pyramid_Charts\/Sales_Retail_Channels.php\" target=\"_blank\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-3237 size-full\" title=\"Click to see the interactive version of such a Pyramid chart\" src=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2017\/03\/data-composition-pyramid-chart-type.png\" alt=\"Pyramid chart of OSI model for data composition (part-to-whole) visualization and analysis\" width=\"776\" height=\"509\" srcset=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2017\/03\/data-composition-pyramid-chart-type.png 776w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2017\/03\/data-composition-pyramid-chart-type-300x197.png 300w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2017\/03\/data-composition-pyramid-chart-type-768x504.png 768w\" sizes=\"auto, (max-width: 776px) 100vw, 776px\" \/><\/a><\/p>\n<p>Additional examples include: salary of employees at different managerial levels, categories of top referral sources by their weight in website traffic, risks in advertising, etc.<\/p>\n<p>You can find more <a href=\"https:\/\/www.anychart.com\/products\/anychart\/gallery\/Funnel_-_Pyramid_Charts\/\" target=\"_blank\">Funnel chart and Pyramid chart samples in this gallery<\/a>.<\/p>\n<h2>Conclusion<\/h2>\n<p>Whenever your purpose is to visualize\u00a0data composition, in most cases you can move along with\u00a0a Pie (Donut) chart, a TreeMap chart, or a Funnel (Pyramid) chart. Keep in mind that every situation is special. So, you should never forget that blindly following these or absolutely any other instructions might be too risky. Before making a final decision on which chart type to choose, think of exactly what kind of data (and questions to it) you have. Then double-check if your first idea has been right or if you should pick\u00a0some other form of visualization.<\/p>\n<p>For complex solutions or\u00a0when you are simply unsure, refer to <a href=\"https:\/\/www.anychart.com\/chartopedia\/\" target=\"_blank\">Chartopedia<\/a>. It describes and provides illustrations for many dozens of chart types grouped by purpose of use. Here, you&#8217;ll find even more <a href=\"https:\/\/www.anychart.com\/chartopedia\/usage-type\/chart-to-show-part-of-the-whole\/\" target=\"_blank\">options for displaying part-to-whole data composition<\/a>\u00a0(or <a href=\"https:\/\/www.anychart.com\/chartopedia\/usage-type\/chart-to-show-proportion\/\" target=\"_blank\">proportion<\/a>, etc.). In addition, AnyChart&#8217;s <a href=\"https:\/\/api.anychart.com\" target=\"_blank\" rel=\"nofollow\">API Reference<\/a> and <a href=\"https:\/\/docs.anychart.com\" target=\"_blank\" rel=\"nofollow\">Chart Documentation<\/a> will\u00a0help you create charts of any type you want with easy JavaScript\/HTML5.<\/p>\n<!-- AddThis Advanced Settings generic via filter on the_content --><!-- AddThis Share Buttons generic via filter on the_content -->","protected":false},"excerpt":{"rendered":"<p>Illustrating part-to-whole relationships for further analysis is a very popular objective\u00a0in data visualization. Basically, it is one of the most widespread ones, e.g. along with data comparison. With\u00a0that in mind, the second part of the\u00a0Choose Right Chart Type for Data Visualization series on our blog focuses on\u00a0how to display\u00a0Data Composition\u00a0properly. In particular, this article will [&hellip;]<!-- AddThis Advanced Settings generic via filter on get_the_excerpt --><!-- AddThis Share Buttons generic via filter on get_the_excerpt --><\/p>\n","protected":false},"author":9,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[178,4],"tags":[53,35,127,128,44,129,49,193,54,191,32,55,77,144,36,141,81,57,58,65,56,64,84,192,30,190],"class_list":["post-3208","post","type-post","status-publish","format-standard","hentry","category-choosing-chart-type","category-tips-and-tricks","tag-anychart","tag-business-intelligence","tag-chart-types","tag-chartopedia","tag-charts-and-art","tag-choosing-the-right-chart-type","tag-dashboards","tag-data-composition","tag-data-visualization","tag-funnel-chart","tag-html5","tag-html5-charts","tag-html5-dashboards","tag-infographics","tag-javascript","tag-javascript-charting","tag-javascript-charting-library","tag-javascript-charts","tag-js-chart","tag-js-charting","tag-js-charts","tag-pie-chart","tag-pie-charts","tag-pyramid-chart","tag-tips-and-tricks","tag-treemap-chart","wpautop"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.1.1 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Data Composition, Parts to Whole: Choose Right Chart Type for Data Visualization (Part 2)<\/title>\n<meta name=\"description\" content=\"Illustrating part-to-whole relationships is a popular goal of data visualization. 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