{"id":2677312,"date":"2025-02-11T10:31:17","date_gmt":"2025-02-11T18:31:17","guid":{"rendered":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=2677312"},"modified":"2025-02-11T11:30:06","modified_gmt":"2025-02-11T19:30:06","slug":"normalization-for-choropleth-maps","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-online\/mapping\/normalization-for-choropleth-maps","title":{"rendered":"Normalization for choropleth maps"},"author":7411,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"_searchwp_excluded":""},"categories":[22941],"tags":[23201,26451,778192,31301,27911],"industry":[],"product":[36551,36561],"class_list":["post-2677312","blog","type-blog","status-publish","format-standard","hentry","category-mapping","tag-cartographic-design","tag-cartography","tag-normalization","tag-symbology","tag-tutorial","product-arcgis-online","product-arcgis-pro"],"acf":{"short_description":"Three short videos that share advice, examples, and analogies to help explain normalization for choropleth maps.","flexible_content":[{"acf_fc_layout":"content","content":"

Choropleth maps are filled areas of color representing quantitative data. Normalization is an important step in making choropleth maps. The goal of normalization is to allow for meaningful comparisons across features.<\/p>\n

How do you know if you need to normalize your data? How should you normalize it? How can you tell if normalization is working? What is the point? These short videos share advice, examples, and analogies to help answer these questions and explain normalization for choropleth maps.<\/p>\n

Video #1. Choropleth maps versus graduated symbols<\/h2>\n

First, you need to decide if a choropleth is really the best way to map your data. The general rule to follow is that raw values should be mapped with graduated or proportional symbols, and derived values should be mapped with color.<\/p>\n"},{"acf_fc_layout":"kaltura","video_id":"1_zh5j94m9","time":false,"start":0,"stop":""},{"acf_fc_layout":"content","content":"

The data shown in this video is derived from\u00a0Street Lights<\/a>\u00a0and\u00a0Census 2021 Dissemination Areas<\/a>\u00a0from\u00a0Halifax Open Data<\/a>.<\/span><\/em><\/p>\n

Video #2. Why do you need to normalize choropleth maps?<\/h2>\n

You can turn raw values into derived values by normalizing them. Probably the most common way to normalize data for choropleth maps is to divide by area.<\/p>\n"},{"acf_fc_layout":"kaltura","video_id":"1_9s0r966y","time":false,"start":0,"stop":""},{"acf_fc_layout":"content","content":"

The data used in this video is\u00a0Census 2021 Dissemination Areas<\/a>\u00a0and\u00a0Buildings\u00a0<\/a>from\u00a0Halifax Open Data<\/a>, and\u00a0North America Hexbins 10km<\/a>: Sahr K, White D, Kimerling AJ. 2003. Geodesic discrete global grid systems. Cartography and Geographic Information Science 30(2):121-134.<\/span><\/em><\/p>\n

Video #3. Does your map allow for meaningful comparisons?<\/h2>\n

This is the heart of the matter\u2014the purpose of normalization. Take some time to assess your map and ensure it’s achieving this goal.<\/p>\n"},{"acf_fc_layout":"kaltura","video_id":"1_dosbonyu","time":false,"start":0,"stop":""},{"acf_fc_layout":"content","content":"

The following data is featured in this video:<\/span><\/em><\/p>\n