{"id":1757622,"date":"2022-12-06T09:30:19","date_gmt":"2022-12-06T17:30:19","guid":{"rendered":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&#038;p=1757622"},"modified":"2024-06-13T16:58:31","modified_gmt":"2024-06-13T23:58:31","slug":"best-practices-for-mapping-demographics-within-arcgis-faq","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq","title":{"rendered":"Your Demographic Questions Answered"},"author":318562,"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":[112192,24571,33021,268131],"industry":[],"product":[36711,36581,36551,36561,37011],"class_list":["post-1757622","blog","type-blog","status-publish","format-standard","hentry","category-mapping","tag-business-analyst","tag-demographics","tag-infographics","tag-living-atlas","product-bus-analyst","product-arcgis-living-atlas","product-arcgis-online","product-arcgis-pro","product-esri-demographics"],"acf":{"authors":[{"ID":318562,"user_firstname":"Summers","user_lastname":"Cleary","nickname":"scleary","user_nicename":"scleary","display_name":"Summers Cleary","user_email":"scleary@esri.com","user_url":"","user_registered":"2022-09-16 14:12:25","user_description":"(she\/her\/hers) Summers is a Product Engineer on ArcGIS Living Atlas' Policy Map team. She works to create maps and stories that reveal opportunities to intervene, particularly focused on the intersection of conservation, natural resources, and Public Policy.","user_avatar":"<img data-del=\"avatar\" src='https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/12\/Headshot-213x200.jpg' class='avatar pp-user-avatar avatar-96 photo ' height='96' width='96'\/>"},{"ID":6461,"user_firstname":"Lisa","user_lastname":"Berry","nickname":"Lisa Berry","user_nicename":"lisa_berry","display_name":"Lisa Berry","user_email":"LBerry@esri.com","user_url":"","user_registered":"2018-03-02 00:18:23","user_description":"I am a Principal GIS Engineer and ArcGIS Living Atlas Evangelist at Esri. I promote all things Living Atlas, ArcGIS Online, ArcGIS Arcade, Smart Mapping, python, and cartography. I also specialize in socioeconomic and demographic datasets within Living Atlas, and how to visualize them.","user_avatar":"<img data-del=\"avatar\" src='https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/05\/UC-2024-Plenary-213x200.png' class='avatar pp-user-avatar avatar-96 photo ' height='96' width='96'\/>"},{"ID":7121,"user_firstname":"Diana","user_lastname":"Lavery","nickname":"Diana Lavery","user_nicename":"dianaclavery_global","display_name":"Diana Lavery","user_email":"DLavery@esri.com","user_url":"","user_registered":"2018-03-02 00:19:20","user_description":"(she\/her\/hers) Diana loves working with data. She has over 15 years experience as a practitioner of demography, sociology, economics, policy analysis, and GIS. Diana holds a BA in quantitative economics and an MA in applied demography. She is a senior GIS engineer on ArcGIS Living Atlas of the World's Policy Maps team. Diana enjoys strong coffee and clean datasets, usually simultaneously.","user_avatar":"<img data-del=\"avatar\" src='https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/diana-lavery-3z7a9428-213x200.jpg' class='avatar pp-user-avatar avatar-96 photo ' height='96' width='96'\/>"},{"ID":7031,"user_firstname":"Julia","user_lastname":"Holtzclaw","nickname":"Julia Holtzclaw","user_nicename":"juliah_esri","display_name":"Julia Holtzclaw","user_email":"JHoltzclaw@esri.com","user_url":"","user_registered":"2018-03-02 00:19:08","user_description":"Julia Holtzclaw is a Senior Product Engineer on Esri's Demographic Data Development team. When not exploring new ways to map data, she's out walking with her pups or enjoying a cup of espresso - or two.","user_avatar":"<img data-del=\"avatar\" src='https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/08\/Julia_Holtzclaw-465x465.jpg' class='avatar pp-user-avatar avatar-96 photo ' height='96' width='96'\/>"}],"short_description":"Learn how to find and use demographic data throughout the ArcGIS platform to better understand your community.","flexible_content":[{"acf_fc_layout":"content","content":"<p><span data-contrast=\"auto\">Demographic data helps us better understand the socioeconomic factors within our communities. We can learn more about the population, housing, jobs, poverty, and other features that can impact policy, logistics, and business decisions. Depending on your needs, there are various ways to find, access, and use demographic data using the power of mapping within ArcGIS. But sometimes knowing where to start can feel like a daunting task. With thousands of demographic attributes to choose from and hundreds of data layers to use in your maps, it can feel confusing how to properly use each nuanced attribute if you aren\u2019t a trained demographer. <\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">This blog provides a list of some of the most common questions asked when mapping demographic data within ArcGIS. Jump to a question to gain insight and resources so that you can start mapping demographic data more confidently within your GIS projects today!<\/span><\/p>\n<h2><a name=\"menu\"><\/a><strong>Jump to a question:<\/strong><\/h2>\n<h3><strong>General Questions<\/strong><\/h3>\n<ul>\n<li><a href=\"#access\">How can I find and access demographics in ArcGIS?<\/a><\/li>\n<li><a href=\"#difference\">What is the difference between Esri Demographics, Census decennial data, and American Community Survey (ACS)?<\/a><\/li>\n<li><a href=\"#attributes\">What does it cost to use demographic data?<\/a><\/li>\n<li><a href=\"#enrich\">What does it mean to enrich data?<\/a><\/li>\n<li><a href=\"#projections\">What is the difference between current year and future projections in Esri Demographics?<\/a><\/li>\n<li><a href=\"#estimates\">What is the difference between the 1-year and 5-year ACS estimates?<\/a><\/li>\n<li><a href=\"#definitions\">Definitions &#8211; What is a Numerator? What is a Denominator?<\/a><\/li>\n<li><a href=\"#percentage\">I want to calculate a percentage. How do I choose the proper denominator for the division?<\/a><\/li>\n<li><a href=\"#null\">Is there a difference between a &#8220;null&#8221; value and a &#8220;0&#8221; value?<\/a><\/li>\n<li><a href=\"#rateRatioPerc\">What is the difference between a rate, a ratio, and a percent?<\/a><\/li>\n<li><a href=\"#percentagePoint\">What is the difference between percent change and percentage-point change over time?<\/a><\/li>\n<li><a href=\"#raceEthnicity\">How can I better understand the race\/ethnicity attributes when mapping?<\/a><\/li>\n<li><a href=\"#housing\">What is the difference between a housing unit and a household?<\/a><\/li>\n<li><a href=\"#household\">What is the difference between household population and group quarters population?<\/a><\/li>\n<li><a href=\"#ethics\">What are some resources and best practices for mapping with ethics?<\/a><\/li>\n<li><a href=\"#nested\">Do different levels of Census boundaries line up nicely? (Nested vs non-nested boundaries)<\/a><\/li>\n<li><a href=\"#bias\">How do I avoid bias in my data?<\/a><\/li>\n<li><a href=\"#enterprise\">I use an Enterprise implementation of ArcGIS behind our organization&#8217;s firewall (aka ArcGIS Enterprise). Do I get the same Living Atlas data at the same release times?<\/a><\/li>\n<\/ul>\n<h3><strong>Leveraging Demographics in ArcGIS<\/strong><\/h3>\n<ul>\n<li><a href=\"#living\">How can I use Living Atlas layers in ArcGIS online and ArcGIS Pro?<\/a><\/li>\n<li><a href=\"#acsAttribute\">How can I find the ACS attribute I need in Living Atlas?<\/a><\/li>\n<li><a href=\"#useACS\">I found an ACS attribute that sounds interesting, and I may want to use it in my map. How do I learn more about that?<\/a><\/li>\n<li><a href=\"#customize\">How can I customize Living Atlas Census ACS layers for my needs?<\/a><\/li>\n<li><a href=\"#market\">How can I use Esri Demographics Market Potential data?<\/a><\/li>\n<li><a href=\"#index\">How can I better understand a collection of multiple demographic attributes, or create an indexed value using socioeconomic factors?<\/a><\/li>\n<li><a href=\"#equity\">How can I map topics related to equity?<\/a><\/li>\n<li><a href=\"#practices\">What are the best practices when mapping demographic data?<\/a><\/li>\n<li><a href=\"#margins\">I want to use American Community Survey (ACS) data, but I don&#8217;t understand the margins of error. How can I learn how to use and map this information?<\/a><\/li>\n<li><a href=\"#statistics\">How do I calculate population statistics for my unique area of interest?<\/a><\/li>\n<li><a href=\"#aggregate\">I want to aggregate smaller geographies to a larger boundary. What is the best way to do this?<\/a><\/li>\n<li><a href=\"#exact\">Instead of aggregating, I want exact data, but can&#8217;t find it in the Living Atlas. Where can I find these?<\/a><\/li>\n<\/ul>\n<p><a name=\"access\"><\/a><\/p>\n<h2><strong>How can I find and access demographics in ArcGIS?<\/strong><\/h2>\n<p><span data-contrast=\"auto\">Mapping demographic data helps us better understand our communities and the socioeconomic factors that impact our area the most. There are many ways to access and use demographics within the ArcGIS environment depending on how you need to use and share the information.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Within ArcGIS, you can access many data sources including Esri Demographics, International Data from Michael Bauer Research, country-specific National Statistical Organization data, and many others. Depending on your needs and resources, there are various options for accessing and using demographic data. <\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><strong><span style=\"text-decoration: underline\">ArcGIS Business Analyst<\/span> &#8211; <\/strong><span class=\"TextRun SCXW83644954 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW83644954 BCX0\">provides an interactive experience for finding and using demographic data.<\/span><span class=\"NormalTextRun SCXW83644954 BCX0\"> Business Analyst demographic <a href=\"https:\/\/www.esri.com\/en-us\/capabilities\/mapping\/overview\">mapping software<\/a> helps you identify under-performing markets, pinpoint the right growth sites, find where your target customers live, and share the analysis across your organization as accurate infographic reports and dynamic presentations.<\/span><span class=\"NormalTextRun SCXW83644954 BCX0\"> You can produce maps, <\/span><span class=\"NormalTextRun SCXW83644954 BCX0\">analytics, <a class=\"Hyperlink SCXW83644954 BCX0\" href=\"https:\/\/www.esri.com\/en-us\/arcgis\/products\/arcgis-business-analyst\/data-infographics\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW83644954 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\">infographics<\/span><\/a>, and more. Access this powerful tool on the <a class=\"Hyperlink SCXW83644954 BCX0\" href=\"https:\/\/www.esri.com\/en-us\/arcgis\/products\/arcgis-business-analyst\/applications\/web-mobile-apps\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW83644954 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\">web<\/span><\/a>, within a <a class=\"Hyperlink SCXW83644954 BCX0\" href=\"https:\/\/www.esri.com\/en-us\/arcgis\/products\/arcgis-business-analyst\/applications\/desktop\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW83644954 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\">desktop<\/span><\/a> product, mobile, and even an <a class=\"Hyperlink SCXW83644954 BCX0\" href=\"https:\/\/www.esri.com\/en-us\/arcgis\/products\/arcgis-business-analyst\/applications\/enterprise\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW83644954 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\">Enterprise<\/span><\/a> deployment. For more information, click <a class=\"Hyperlink SCXW83644954 BCX0\" href=\"https:\/\/www.esri.com\/en-us\/arcgis\/products\/arcgis-business-analyst\/overview\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW83644954 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\">here<\/span><\/a>.<\/span><\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1765392,"id":1765392,"title":"Business Analyst","filename":"Business-Analyst.png","filesize":862438,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Business-Analyst.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\/business-analyst","alt":"","author":"318562","description":"","caption":"","name":"business-analyst","status":"inherit","uploaded_to":1757622,"date":"2022-11-09 15:53:37","modified":"2022-11-09 15:55:32","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1175,"height":864,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Business-Analyst-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Business-Analyst.png","medium-width":355,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Business-Analyst.png","medium_large-width":768,"medium_large-height":565,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Business-Analyst.png","large-width":1175,"large-height":864,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Business-Analyst.png","1536x1536-width":1175,"1536x1536-height":864,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Business-Analyst.png","2048x2048-width":1175,"2048x2048-height":864,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Business-Analyst-632x465.png","card_image-width":632,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Business-Analyst.png","wide_image-width":1175,"wide_image-height":864}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Business-Analyst.png"},{"acf_fc_layout":"content","content":"<p><span style=\"text-decoration: underline\"><strong><span class=\"TextRun Underlined SCXW202393534 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW202393534 BCX0\">E<\/span><span class=\"NormalTextRun SCXW202393534 BCX0\">nrich <\/span><span class=\"NormalTextRun SCXW202393534 BCX0\">a<\/span><span class=\"NormalTextRun SCXW202393534 BCX0\">n<\/span><span class=\"NormalTextRun SCXW202393534 BCX0\">y<\/span> <span class=\"NormalTextRun SCXW202393534 BCX0\">bounda<\/span><span class=\"NormalTextRun SCXW202393534 BCX0\">ry<\/span><\/span><\/strong><\/span> <span class=\"TextRun SCXW202393534 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW202393534 BCX0\">\u2013 <\/span><span class=\"NormalTextRun SCXW202393534 BCX0\">U<\/span><span class=\"NormalTextRun SCXW202393534 BCX0\">sing a<\/span><span class=\"NormalTextRun SCXW202393534 BCX0\"> custom <\/span><span class=\"NormalTextRun SCXW202393534 BCX0\">boundary<\/span><span class=\"NormalTextRun SCXW202393534 BCX0\"> or a standard geography boundary layer from Living Atlas,<\/span><span class=\"NormalTextRun SCXW202393534 BCX0\"> you can<\/span><span class=\"NormalTextRun SCXW202393534 BCX0\"> apportion demographic<\/span><span class=\"NormalTextRun SCXW202393534 BCX0\"> data<\/span><span class=\"NormalTextRun SCXW202393534 BCX0\"> to your area of interest. <\/span><span class=\"NormalTextRun SCXW202393534 BCX0\">This method of apportionment uses <\/span><span class=\"NormalTextRun SCXW202393534 BCX0\">the <\/span><span class=\"NormalTextRun SCXW202393534 BCX0\">underlying <\/span><span class=\"NormalTextRun SCXW202393534 BCX0\">ArcGIS <\/span><span class=\"NormalTextRun SpellingErrorV2Themed SCXW202393534 BCX0\">G<\/span><span class=\"NormalTextRun SpellingErrorV2Themed SCXW202393534 BCX0\">eo<\/span><span class=\"NormalTextRun SpellingErrorV2Themed SCXW202393534 BCX0\">E<\/span><span class=\"NormalTextRun SpellingErrorV2Themed SCXW202393534 BCX0\">nrichment<\/span><span class=\"NormalTextRun SCXW202393534 BCX0\"> service, which can be used in <\/span><\/span><a class=\"Hyperlink SCXW202393534 BCX0\" href=\"https:\/\/doc.arcgis.com\/en\/arcgis-online\/analyze\/enrich-layer.htm\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW202393534 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW202393534 BCX0\" data-ccp-charstyle=\"Hyperlink\">ArcGIS Online<\/span><\/span><\/a><span class=\"TextRun SCXW202393534 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW202393534 BCX0\">, <\/span><\/span><a class=\"Hyperlink SCXW202393534 BCX0\" href=\"https:\/\/pro.arcgis.com\/en\/pro-app\/latest\/tool-reference\/analysis\/enrich.htm\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW202393534 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW202393534 BCX0\" data-ccp-charstyle=\"Hyperlink\">ArcGIS Pro<\/span><\/span><\/a><span class=\"TextRun SCXW202393534 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW202393534 BCX0\">, and even <\/span><\/span><a class=\"Hyperlink SCXW202393534 BCX0\" href=\"https:\/\/doc.arcgis.com\/en\/insights\/latest\/analyze\/enrich-data.htm\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW202393534 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW202393534 BCX0\" data-ccp-charstyle=\"Hyperlink\">ArcGIS Insights<\/span><\/span><\/a><span class=\"TextRun SCXW202393534 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW202393534 BCX0\">. <\/span><span class=\"NormalTextRun SCXW202393534 BCX0\">Look for the \u201cEnrich Layer\u201d tool to enrich your boundaries. <\/span><span class=\"NormalTextRun SCXW202393534 BCX0\">Within the US, y<\/span><span class=\"NormalTextRun SCXW202393534 BCX0\">ou\u2019ll have access to Esri Updated Demographics whcih include current year estimates and 5-year projections, recent American Community Survey attributes, as well as lifestyle, spending and behavioral data. <\/span><span class=\"NormalTextRun SCXW202393534 BCX0\">Globally, there are over 170 countries with data from Michael Bauer Research, local National Statistical Organizations, and other data providers. <\/span><span class=\"NormalTextRun SCXW202393534 BCX0\">Click <\/span><\/span><a class=\"Hyperlink SCXW202393534 BCX0\" href=\"https:\/\/doc.arcgis.com\/en\/esri-demographics\/latest\/regional-data\/united-states.htm#ESRI_SECTION1_D38EB1254E0E471FBCE88CA06A8DDCF9\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW202393534 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW202393534 BCX0\" data-ccp-charstyle=\"Hyperlink\">here<\/span><\/span><\/a><span class=\"TextRun SCXW202393534 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW202393534 BCX0\"> for more information about the <\/span><span class=\"NormalTextRun SCXW202393534 BCX0\">US <\/span><span class=\"NormalTextRun SCXW202393534 BCX0\">available datasets<\/span><span class=\"NormalTextRun SCXW202393534 BCX0\">, and <\/span><\/span><a class=\"Hyperlink SCXW202393534 BCX0\" href=\"https:\/\/doc.arcgis.com\/en\/esri-demographics\/latest\/regional-data\/regional-data.htm\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW202393534 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW202393534 BCX0\" data-ccp-charstyle=\"Hyperlink\">here<\/span><\/span><\/a><span class=\"TextRun SCXW202393534 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW202393534 BCX0\"> for an introduction to the international datasets<\/span><span class=\"NormalTextRun SCXW202393534 BCX0\">. <\/span><span class=\"NormalTextRun SCXW202393534 BCX0\">Visit <\/span><\/span><a class=\"Hyperlink SCXW202393534 BCX0\" href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/data-management\/make-a-demographic-map-in-5-minutes\/\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW202393534 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW202393534 BCX0\" data-ccp-charstyle=\"Hyperlink\">this blog<\/span><\/span><\/a><span class=\"TextRun SCXW202393534 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW202393534 BCX0\"> for a short tutorial within ArcGIS Online.\u00a0<\/span><\/span><\/p>\n<p><span style=\"text-decoration: underline\"><strong><span class=\"TextRun Underlined SCXW64417420 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW64417420 BCX0\">ArcGIS <\/span><span class=\"NormalTextRun SCXW64417420 BCX0\">Living Atlas of the World<\/span><\/span><\/strong><\/span><span class=\"TextRun SCXW64417420 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW64417420 BCX0\"> \u2013 <\/span><span class=\"NormalTextRun SCXW64417420 BCX0\">Find <\/span><span class=\"NormalTextRun SCXW64417420 BCX0\">ready-to-use <\/span><\/span><a class=\"Hyperlink SCXW64417420 BCX0\" href=\"https:\/\/livingatlas.arcgis.com\/en\/browse\/#d=2&amp;type=layers&amp;categories=People%3A1111111111\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW64417420 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW64417420 BCX0\" data-ccp-charstyle=\"Hyperlink\">layers<\/span><\/span><\/a><span class=\"TextRun SCXW64417420 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW64417420 BCX0\">, <\/span><\/span><a class=\"Hyperlink SCXW64417420 BCX0\" href=\"https:\/\/livingatlas.arcgis.com\/en\/browse\/#d=2&amp;type=maps&amp;srt=name&amp;categories=People%3A1111111111\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW64417420 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW64417420 BCX0\" data-ccp-charstyle=\"Hyperlink\">web maps<\/span><\/span><\/a><span class=\"TextRun SCXW64417420 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW64417420 BCX0\">, and <\/span><\/span><a class=\"Hyperlink SCXW64417420 BCX0\" href=\"https:\/\/livingatlas.arcgis.com\/en\/browse\/#d=2&amp;type=apps&amp;srt=name&amp;categories=People%3A1111111111\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW64417420 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW64417420 BCX0\" data-ccp-charstyle=\"Hyperlink\">apps<\/span><\/span><\/a><span class=\"TextRun SCXW64417420 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW64417420 BCX0\"> that can be customized and saved for your needs. Living Atlas contains demographic data from <\/span><\/span><a class=\"Hyperlink SCXW64417420 BCX0\" href=\"https:\/\/livingatlas.arcgis.com\/en\/browse\/?q=owner:%20Esri#d=2&amp;q=owner%3A%20Esri&amp;cont=true&amp;categories=People%3A1111111111\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW64417420 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW64417420 BCX0\" data-ccp-charstyle=\"Hyperlink\">Esri Demographics<\/span><\/span><\/a><span class=\"TextRun SCXW64417420 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW64417420 BCX0\">, <\/span><\/span><a class=\"Hyperlink SCXW64417420 BCX0\" href=\"https:\/\/livingatlas.arcgis.com\/en\/browse\/?q=census%20bureau#d=2&amp;q=Census%20Bureau&amp;cont=true&amp;categories=People%3A1111111111\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW64417420 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW64417420 BCX0\" data-ccp-charstyle=\"Hyperlink\">U.S. <\/span><span class=\"NormalTextRun SCXW64417420 BCX0\" data-ccp-charstyle=\"Hyperlink\">Census<\/span><span class=\"NormalTextRun SCXW64417420 BCX0\" data-ccp-charstyle=\"Hyperlink\"> Bureau<\/span><\/span><\/a><span class=\"TextRun SCXW64417420 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW64417420 BCX0\">, <\/span><\/span><a class=\"Hyperlink SCXW64417420 BCX0\" href=\"https:\/\/livingatlas.arcgis.com\/en\/browse\/?q=current%20acs#d=2&amp;q=current%20year%20acs&amp;cont=true&amp;categories=People%3A1111111111\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW64417420 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW64417420 BCX0\" data-ccp-charstyle=\"Hyperlink\">A<\/span><span class=\"NormalTextRun SCXW64417420 BCX0\" data-ccp-charstyle=\"Hyperlink\">merican Community Survey (ACS)<\/span><\/span><\/a><span class=\"TextRun SCXW64417420 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW64417420 BCX0\">, <\/span><\/span><a class=\"Hyperlink SCXW64417420 BCX0\" href=\"https:\/\/livingatlas.arcgis.com\/en\/browse\/?q=cdc#d=2&amp;q=cdc&amp;categories=People%3A1111111111\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW64417420 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW64417420 BCX0\" data-ccp-charstyle=\"Hyperlink\">C<\/span><span class=\"NormalTextRun SCXW64417420 BCX0\" data-ccp-charstyle=\"Hyperlink\">enters for Disease Control and Prevention (CSC)<\/span><\/span><\/a><span class=\"TextRun SCXW64417420 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW64417420 BCX0\">, <\/span><span class=\"NormalTextRun SCXW64417420 BCX0\">the <\/span><\/span><a class=\"Hyperlink SCXW64417420 BCX0\" href=\"https:\/\/livingatlas.arcgis.com\/en\/browse\/?q=nces#d=2&amp;q=NCES&amp;categories=People%3A1111111111\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW64417420 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW64417420 BCX0\" data-ccp-charstyle=\"Hyperlink\">N<\/span><span class=\"NormalTextRun SCXW64417420 BCX0\" data-ccp-charstyle=\"Hyperlink\">ational <\/span><span class=\"NormalTextRun SCXW64417420 BCX0\" data-ccp-charstyle=\"Hyperlink\">C<\/span><span class=\"NormalTextRun SCXW64417420 BCX0\" data-ccp-charstyle=\"Hyperlink\">enter for <\/span><span class=\"NormalTextRun SCXW64417420 BCX0\" data-ccp-charstyle=\"Hyperlink\">E<\/span><span class=\"NormalTextRun SCXW64417420 BCX0\" data-ccp-charstyle=\"Hyperlink\">ducation <\/span><span class=\"NormalTextRun SCXW64417420 BCX0\" data-ccp-charstyle=\"Hyperlink\">S<\/span><span class=\"NormalTextRun SCXW64417420 BCX0\" data-ccp-charstyle=\"Hyperlink\">tatistics (NCES)<\/span><\/span><\/a><span class=\"TextRun SCXW64417420 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW64417420 BCX0\">, <\/span><span class=\"NormalTextRun SCXW64417420 BCX0\">and many other sources. For more information, browse the <\/span><\/span><a class=\"Hyperlink SCXW64417420 BCX0\" href=\"https:\/\/livingatlas.arcgis.com\/en\/browse\/#d=2&amp;categories=People%3A1111111111\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW64417420 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW64417420 BCX0\" data-ccp-charstyle=\"Hyperlink\">People category of Living Atlas<\/span><\/span><\/a><span class=\"TextRun SCXW64417420 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW64417420 BCX0\">.\u00a0<\/span><span class=\"NormalTextRun SCXW64417420 BCX0\">\u00a0<\/span><\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1766592,"id":1766592,"title":"ArcGIS Living Atlas of the World","filename":"LAW.jpg","filesize":469997,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/LAW.jpg","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\/law-4","alt":"","author":"318562","description":"","caption":"","name":"law-4","status":"inherit","uploaded_to":1757622,"date":"2022-11-09 19:11:40","modified":"2022-11-09 19:11:59","menu_order":0,"mime_type":"image\/jpeg","type":"image","subtype":"jpeg","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1538,"height":1325,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/LAW-213x200.jpg","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/LAW.jpg","medium-width":303,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/LAW.jpg","medium_large-width":768,"medium_large-height":662,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/LAW.jpg","large-width":1254,"large-height":1080,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/LAW-1536x1323.jpg","1536x1536-width":1536,"1536x1536-height":1323,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/LAW.jpg","2048x2048-width":1538,"2048x2048-height":1325,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/LAW-540x465.jpg","card_image-width":540,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/LAW-1254x1080.jpg","wide_image-width":1254,"wide_image-height":1080}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/LAW.jpg"},{"acf_fc_layout":"content","content":"<p><b><span data-contrast=\"auto\">Reports<\/span><\/b> <span data-contrast=\"auto\">\u2013 In just a few clicks, you can get detailed demographic reports about locations in the US. For just $50, you can select attributes from the collection of 15,000+ available variables. Click <\/span><a href=\"https:\/\/www.esri.com\/en-us\/arcgis\/products\/data\/reports?rsource=https%3A%2F%2Fwww.esri.com%2Fen-us%2Farcgis%2Fproducts%2Fbuy-reports%2Foverview\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">here<\/span><\/a><span data-contrast=\"auto\"> to learn more.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><b><span data-contrast=\"auto\">And More!<\/span><\/b> <span data-contrast=\"auto\">&#8211; To learn more about the other places Esri Demographics can be accessed in ArcGIS, check out <\/span><a href=\"https:\/\/doc.arcgis.com\/en\/esri-demographics\/latest\/get-started\/visualize-demographics.htm\"><span data-contrast=\"none\">this list<\/span><\/a><span data-contrast=\"auto\">.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"difference\"><\/a><\/p>\n<h2><strong>What is the difference between Esri Demographics, Census decennial data, and American Community Survey (ACS)?<\/strong><\/h2>\n<p><b><span data-contrast=\"auto\">Esri Updated Demographics<\/span><\/b><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">This is the data that fuels the Enrich Layer tools in ArcGIS Online and Pro, as it goes down to the block group level. Most Living Atlas layers with Esri Demographics data are considered premium content meaning they require a login and consume credits.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\"> E<span class=\"TextRun SCXW91334950 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW91334950 BCX0\">sri\u202f<\/span><\/span><a class=\"Hyperlink SCXW91334950 BCX0\" href=\"https:\/\/www.esri.com\/en-us\/arcgis\/products\/data-location-services\/data\/demographics\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW91334950 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW91334950 BCX0\" data-ccp-charstyle=\"Hyperlink\">Updated Demographics<\/span><\/span><\/a><span class=\"TextRun SCXW91334950 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW91334950 BCX0\">\u202frepresent the suite of annually updated U.S. demographic data that provides current-year and five-year forecasts for more than two thousand demographic and socioeconomic characteristics. Included are a host of tables covering key characteristics of the population, households, housing, age, race, income, and much more.\u202f<\/span><span class=\"NormalTextRun ContextualSpellingAndGrammarErrorV2Themed SCXW91334950 BCX0\">Esri\u2018<\/span><span class=\"NormalTextRun SCXW91334950 BCX0\">s Updated Demographics data consists of point estimates, representing July 1 of the current and forecast years. View\u202f<\/span><\/span><a class=\"Hyperlink SCXW91334950 BCX0\" href=\"https:\/\/storymaps.arcgis.com\/stories\/461a6b86c8794dbd9b4c27e76ae2e37b\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW91334950 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW91334950 BCX0\" data-ccp-charstyle=\"Hyperlink\">Understanding Esri\u2019s Updated Demographics portfolio<\/span><\/span><\/a><span class=\"TextRun SCXW91334950 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW91334950 BCX0\">\u202fto familiarize yourself with what\u2019s included and how it\u2019s updated.<\/span><\/span><span class=\"EOP SCXW91334950 BCX0\" data-ccp-props=\"{&quot;134233117&quot;:true,&quot;134233118&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/span><\/p>\n<p><b><span data-contrast=\"auto\">Decennial Census<\/span><\/b><span data-contrast=\"auto\">\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">The Census Bureau is required to carry out a count of the entire population every 10 years in order to realign state apportionment and congressional districts. The decennial census only asks 10 questions, the basics as required by legislation related to voting. Decennial counts are open and free to use from Living Atlas, with both 2010 and 2020 data currently available.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><b><span data-contrast=\"auto\">American Community Survey (ACS)<\/span><\/b><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">In addition to the decennial census, the Census Bureau also surveys the population by taking a small sample every year. Everyone in the population has a chance to be in the sample: owners, renters, young and old, even those in group quarters. This survey has 44 questions, allowing for way more attributes than the decennial census. Due to the sampling, estimates from all surveys contain a margin of error. Census actually publishes <a href=\"#margins\">that margin<\/a> alongside their estimates<\/span><span data-contrast=\"auto\">. Data from the survey is used for $675 billion dollars&#8217; worth of government spending, as it helps local officials, community leaders, and businesses understand their local population, economic, social, and housing characteristics. Living Atlas contains some of the most popular ACS estimates in a set of layers that go down to the tract level. These layers are open and free to use from Living Atlas and are always updated with the most current 5-year estimates. 2010-2014 data is also available for some estimates as well.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"living\"><\/a><\/p>\n<h2><strong>How can I use Living Atlas layers in ArcGIS Online and ArcGIS Pro?<\/strong><\/h2>\n<p><span data-contrast=\"auto\">There are a wide range of ready-to-use demographic layers within Living Atlas. These layers can be customized for your mapping purposes within ArcGIS Online and ArcGIS Pro by changing the symbology and saving the map to your organization. You can zoom to your area of interest, filter to your specific region, and change the symbology and pop-up to show a different attribute from the layer. To learn more about how to do this, visit <\/span><a href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/make-an-acs-map-fast\/\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">this short blog<\/span><\/a><span data-contrast=\"auto\"> explaining how to customize American Community Survey layers from Living Atlas.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">If you find a layer within Living Atlas that is a \u201chosted feature layer\u201d, you can also export this data or use it within analysis tools.\u00a0<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1765452,"id":1765452,"title":"Hosted Feature Layer in ArcGIS Online","filename":"FeatureLayer.png","filesize":1433,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/FeatureLayer.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\/featurelayer-3","alt":"","author":"318562","description":"","caption":"","name":"featurelayer-3","status":"inherit","uploaded_to":1757622,"date":"2022-11-09 16:02:18","modified":"2022-11-09 16:02:40","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":120,"height":39,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/FeatureLayer.png","thumbnail-width":120,"thumbnail-height":39,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/FeatureLayer.png","medium-width":120,"medium-height":39,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/FeatureLayer.png","medium_large-width":120,"medium_large-height":39,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/FeatureLayer.png","large-width":120,"large-height":39,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/FeatureLayer.png","1536x1536-width":120,"1536x1536-height":39,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/FeatureLayer.png","2048x2048-width":120,"2048x2048-height":39,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/FeatureLayer.png","card_image-width":120,"card_image-height":39,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/FeatureLayer.png","wide_image-width":120,"wide_image-height":39}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/FeatureLayer.png"},{"acf_fc_layout":"content","content":"<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"attributes\"><\/a><\/p>\n<h2><strong>What does it cost to use demographic data?<\/strong><\/h2>\n<p>As part of your ArcGIS subscription, you have access to hundreds of maps, apps, layers in Living Atlas\u2026 many of which cover demographic data. Living Atlas items marked Subscriber require ArcGIS credentials but consume no credits. Items marked Premium require ArcGIS credentials and consume credits.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1766602,"id":1766602,"title":"Premium Content","filename":"Premium-Content.jpg","filesize":44862,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Premium-Content.jpg","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\/premium-content-2","alt":"","author":"318562","description":"","caption":"","name":"premium-content-2","status":"inherit","uploaded_to":1757622,"date":"2022-11-09 19:12:39","modified":"2022-11-09 19:12:39","menu_order":0,"mime_type":"image\/jpeg","type":"image","subtype":"jpeg","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":722,"height":199,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Premium-Content-213x199.jpg","thumbnail-width":213,"thumbnail-height":199,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Premium-Content.jpg","medium-width":464,"medium-height":128,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Premium-Content.jpg","medium_large-width":722,"medium_large-height":199,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Premium-Content.jpg","large-width":722,"large-height":199,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Premium-Content.jpg","1536x1536-width":722,"1536x1536-height":199,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Premium-Content.jpg","2048x2048-width":722,"2048x2048-height":199,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Premium-Content.jpg","card_image-width":722,"card_image-height":199,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Premium-Content.jpg","wide_image-width":722,"wide_image-height":199}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Premium-Content.jpg"},{"acf_fc_layout":"content","content":"<p><span data-contrast=\"auto\">Learn more about the credits that are required for Business Analyst, enrichment, business search, infographics, reports, and other methods <\/span><a href=\"https:\/\/doc.arcgis.com\/en\/arcgis-online\/administer\/credits.htm#ESRI_SECTION1_709121D2C7694DCAB9B8592F36F7A5BA\"><span data-contrast=\"none\">here<\/span><\/a><span data-contrast=\"auto\">. If you want to share a premium layer from Living Atlas, you\u2019ll need to use one of the various methods for sharing premium content. Visit <\/span><a href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/living-atlas-subscriber-content-public-apps\/\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">this blog<\/span><\/a><span data-contrast=\"auto\"> to learn how to do this.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">However, if you are accessing hosted feature layers within Living Atlas, most of these layers do not consume any credits and are free to use and share. Look for the item type \u201cFeature Layer\u201d (example in the question above).<\/span><\/p>\n<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"enrich\"><\/a><\/p>\n<h2><strong>What does it mean to enrich data?<\/strong><\/h2>\n<p><span class=\"TextRun SCXW7111714 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW7111714 BCX0\">You can use the<\/span> <\/span><a class=\"Hyperlink SCXW7111714 BCX0\" href=\"https:\/\/doc.arcgis.com\/en\/arcgis-online\/analyze\/enrich-layer.htm\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW7111714 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW7111714 BCX0\" data-ccp-charstyle=\"Hyperlink\">Enrich Layer<\/span><\/span><\/a><span class=\"TextRun SCXW7111714 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"> <span class=\"NormalTextRun SCXW7111714 BCX0\">tool in ArcGIS Online or ArcGIS Pro to<\/span> <\/span><a class=\"Hyperlink SCXW7111714 BCX0\" href=\"https:\/\/developers.arcgis.com\/rest\/geoenrichment\/api-reference\/data-apportionment.htm\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW7111714 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW7111714 BCX0\" data-ccp-charstyle=\"Hyperlink\">apportion demographic attributes to any set of polygon features<\/span><\/span><\/a><span class=\"TextRun SCXW7111714 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW7111714 BCX0\">. <\/span><\/span><a class=\"Hyperlink SCXW7111714 BCX0\" href=\"https:\/\/doc.arcgis.com\/en\/esri-demographics\/latest\/get-started\/data-browser.htm\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW7111714 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW7111714 BCX0\" data-ccp-charstyle=\"Hyperlink\">Search and add thousands of attributes<\/span><\/span><\/a><span class=\"TextRun SCXW7111714 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW7111714 BCX0\"> to boundaries important for your analysis.<\/span><\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1765472,"id":1765472,"title":"Apportionment","filename":"Apportionment.png","filesize":68143,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Apportionment.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\/apportionment","alt":"","author":"318562","description":"","caption":"","name":"apportionment","status":"inherit","uploaded_to":1757622,"date":"2022-11-09 16:05:20","modified":"2022-11-09 16:05:20","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":480,"height":216,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Apportionment-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Apportionment.png","medium-width":464,"medium-height":209,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Apportionment.png","medium_large-width":480,"medium_large-height":216,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Apportionment.png","large-width":480,"large-height":216,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Apportionment.png","1536x1536-width":480,"1536x1536-height":216,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Apportionment.png","2048x2048-width":480,"2048x2048-height":216,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Apportionment.png","card_image-width":480,"card_image-height":216,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Apportionment.png","wide_image-width":480,"wide_image-height":216}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Apportionment.png"},{"acf_fc_layout":"content","content":"<p><span data-contrast=\"auto\">Choose the attributes that are meaningful for your work, and the data will use a weighted block apportionment method to allocate data values to that polygon.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><a href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/data-management\/make-a-demographic-map-in-5-minutes\/\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">This blog<\/span><\/a><span data-contrast=\"auto\"> shows how to easily use enrichment in ArcGIS Online to make a demographics map.<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1765482,"id":1765482,"title":"Second Apportionment Example","filename":"Apportionment2.png","filesize":371223,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Apportionment2.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\/apportionment2","alt":"","author":"318562","description":"","caption":"","name":"apportionment2","status":"inherit","uploaded_to":1757622,"date":"2022-11-09 16:06:01","modified":"2022-11-09 16:06:24","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":486,"height":456,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Apportionment2-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Apportionment2.png","medium-width":278,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Apportionment2.png","medium_large-width":486,"medium_large-height":456,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Apportionment2.png","large-width":486,"large-height":456,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Apportionment2.png","1536x1536-width":486,"1536x1536-height":456,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Apportionment2.png","2048x2048-width":486,"2048x2048-height":456,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Apportionment2.png","card_image-width":486,"card_image-height":456,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Apportionment2.png","wide_image-width":486,"wide_image-height":456}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Apportionment2.png"},{"acf_fc_layout":"content","content":"<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"projections\"><\/a><\/p>\n<h2><strong>What is the difference between current year and future projections in Esri Demographics?<\/strong><\/h2>\n<p><span data-contrast=\"auto\">Esri Demographics is a global collection of demographic data, encompassing over 170 countries and regions. There are thousands of demographic and socioeconomic attributes included in the Esri Demographics data suite. Attribute availability varies by country, with the United States containing over 15 thousand attributes and some small international countries containing five.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Current year and future projection data are included in Esri U.S. Demographic data. \u201cCurrent year\u201d data are demographic data current as of July 1<\/span><span data-contrast=\"auto\">st<\/span><span data-contrast=\"auto\"> of the applicable year. So, 2022 U.S. estimates are current as of July 1, 2022.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">\u201cFuture projections\u201d are five-year projections for many variables within the Esri Demographics dataset. Projections are derived from current and past events and are updated annually alongside current year data. <\/span><a href=\"https:\/\/storymaps.arcgis.com\/stories\/dd6c5388d48c448798613778644a1eaa#ref-n-NVR5Ka\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">Visit this StoryMap<\/span><\/a><span data-contrast=\"auto\"> for a full list of variables included in the latest future year projections.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Access <\/span><a href=\"https:\/\/doc.arcgis.com\/en\/esri-demographics\/latest\/reference\/methodologies.htm\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">a comprehensive list of methodologies<\/span><\/a><span data-contrast=\"auto\"> for all countries included in Esri Demographics.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Read about <\/span><a href=\"https:\/\/storymaps.arcgis.com\/stories\/dd6c5388d48c448798613778644a1eaa\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">the latest vintage update<\/span><\/a><span data-contrast=\"auto\"> to Esri Demographics.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Read the <\/span><a href=\"https:\/\/doc.arcgis.com\/en\/esri-demographics\/latest\/reference\/faq.htm\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">frequently asked questions<\/span><\/a><span data-contrast=\"auto\"> surrounding Esri Demographics.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"estimates\"><\/a><\/p>\n<h2><strong>What is the difference between the 1-year and 5-year ACS estimates?<\/strong><\/h2>\n<p><span data-contrast=\"auto\">Census publishes both 1-year and 5-year estimates, for example, there are both 2021 1-year estimates and 2017-2021 5-year estimates. A sample from only one year can provide us with high-level information for large places and counties. All estimates from ACS are really midpoints of a range, which is provided with the margin of error.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">By pooling together 5 years of responses, Census is able to create smaller ranges (more reliable estimates) for those same estimates for large places and counties. It&#8217;s a tradeoff between recency and reliability.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Furthermore, by merging 5 years of responses, Census is able to create and publish estimates for smaller geographies such as tracts. The type of work that GIS Analysts do often necessitates smaller geographic resolution, hence the Living Atlas layers use the 5-year estimates.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">For more guidance on when to use the 1-year vs. the 5-year estimates, see <\/span><a href=\"https:\/\/www.census.gov\/programs-surveys\/acs\/guidance\/estimates.html\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">Census documentation<\/span><\/a><span data-contrast=\"auto\">.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"acsAttribute\"><\/a><\/p>\n<h2><strong>How can I find the ACS attribute I need in Living Atlas?<\/strong><\/h2>\n<p><span data-contrast=\"auto\">There are over 100 ready-to-use Census ACS layers available in Living Atlas, ready to be mapped. These layers require no credits and can immediately be used in your mapping projects with just a few clicks. These layers contain state, county, and tract values for the entire US plus Washington D.C. and Puerto Rico. These can be found from Living Atlas by adjusting the filter to find only layers, and use the search phrase \u201c<a href=\"https:\/\/livingatlas.arcgis.com\/en\/browse\/?q=current%20acs#d=2&amp;q=current%20year%20acs%20owner%3Aesri_demographics&amp;type=layers\" target=\"_blank\" rel=\"noopener\">current year acs<\/a>\u201d.<\/span><span data-contrast=\"auto\">\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">These layers follow a naming pattern: ACS + topic + &#8211; Boundaries\/Centroids. The topic can help you narrow down which layer might contain the attribute(s) you need for your mapping project. The Boundaries provide the TIGER boundaries, while the Centroids version provides the point centroid of each feature.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Once you find the layer topic you\u2019re interested in, you can explore the fields in a few different ways. For example, this <\/span><a href=\"https:\/\/www.arcgis.com\/home\/item.html?id=0e468b75bca545ee8dc4b039cbb5aff6\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">ACS Poverty Variables \u2013 Boundaries<\/span><\/a><span data-contrast=\"auto\"> layer covers poverty topics, and the item page tells us that the layer contains values from the B17020 table, and I can see metadata about the vintage and where the data was downloaded from.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">To see which attributes are included in the layer, go to the \u201cData\u201d tab from the item page link, and choose \u201cFields\u201d at the top of the page. Each field maintains its ACS table and position as the field name, but also has an alias name and long description, which brings the ACS metadata directly into the map-making experience.<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1766612,"id":1766612,"title":"Alias names in item descriptions","filename":"Alias-names.jpg","filesize":84352,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Alias-names.jpg","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\/alias-names-2","alt":"","author":"318562","description":"","caption":"","name":"alias-names-2","status":"inherit","uploaded_to":1757622,"date":"2022-11-09 19:13:20","modified":"2022-11-09 19:13:32","menu_order":0,"mime_type":"image\/jpeg","type":"image","subtype":"jpeg","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1124,"height":180,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Alias-names-213x180.jpg","thumbnail-width":213,"thumbnail-height":180,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Alias-names.jpg","medium-width":464,"medium-height":74,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Alias-names.jpg","medium_large-width":768,"medium_large-height":123,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Alias-names.jpg","large-width":1124,"large-height":180,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Alias-names.jpg","1536x1536-width":1124,"1536x1536-height":180,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Alias-names.jpg","2048x2048-width":1124,"2048x2048-height":180,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Alias-names-826x132.jpg","card_image-width":826,"card_image-height":132,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Alias-names.jpg","wide_image-width":1124,"wide_image-height":180}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Alias-names.jpg"},{"acf_fc_layout":"content","content":"<p><span class=\"NormalTextRun SCXW50589467 BCX0\">You can also see the alias name and long description when choosing a field in Map Viewer, <\/span><span class=\"NormalTextRun AdvancedProofingIssueV2Themed SCXW50589467 BCX0\">and also<\/span><span class=\"NormalTextRun SCXW50589467 BCX0\"> within the Table view in ArcGIS Online.<\/span><\/p>\n<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"useACS\"><\/a><\/p>\n<h2><strong>I found an ACS attribute that sounds interesting, and I may want to use it within my map. How do I learn more about it?<\/strong><\/h2>\n<p><span data-contrast=\"auto\">When using demographic layers from Living Atlas, particularly the Census ACS 5-year estimates, it is important to understand the metadata for each field in order to effectively map and use the attributes.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Alias names and long descriptions within ArcGIS Online allow you to learn more about the metadata from each attribute. These are included in all American Community Survey (ACS) Living Atlas layers. <a href=\"#acsAttribute\">See the question above<\/a> to learn more about how to find and access the long descriptions for each attribute.<\/span><\/p>\n<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"customize\"><\/a><\/p>\n<h2><strong>How can I customize Living Atlas Census ACS layers for my needs?<\/strong><\/h2>\n<p><span data-contrast=\"auto\">Once you find the layer and attribute you need from the Living Atlas Census ACS layers, you can easily customize the layer to your needs within ArcGIS Online or ArcGIS Pro. You can share, filter, symbolize, and use these layers within analysis.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">For more inspiration and instructions for how to use these layers, visit <\/span><a href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/make-an-acs-map-fast\/\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">this blog about making a map about your community<\/span><\/a><span data-contrast=\"auto\"> or <\/span><a href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/add-census-data-to-any-map-with-the-living-atlas\/\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">this blog about how to access the ACS layers<\/span><\/a><span data-contrast=\"auto\">.<\/span><\/p>\n<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"definitions\"><\/a><\/p>\n<h2><strong>Definitions &#8211; What is a Numerator? What is a Denominator?<\/strong><\/h2>\n<p><span data-contrast=\"auto\">When working with demographic data, we often come across numerators and denominators \u2013 but what are they? A numerator represents the number of parts out of the whole, which is the denominator. For example, we want to find the number or percentage of vacant housing units in a city. The numerator is housing units that are vacant. The denominator is <\/span><i><span data-contrast=\"auto\">all housing units<\/span><\/i><b><i><span data-contrast=\"auto\"> \u2013 <\/span><\/i><\/b><span data-contrast=\"auto\">this means it includes all housing units regardless of occupancy\/vacancy status.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">When working with numerators and denominators, pay attention to the variables you are choosing. <a href=\"#percentage\">See the next question<\/a> <\/span><span data-contrast=\"auto\">on choosing the proper denominator to help guide your calculations.<\/span><\/p>\n<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"percentage\"><\/a><\/p>\n<h2><strong>I want to calculate a percentage. How do I choose the proper denominator for the division?<\/strong><\/h2>\n<p><span data-contrast=\"auto\">The denominator in ACS data will either be individuals, households, or housing units. First ensure that both the numerator and denominator are keeping these consistent. If your numerator is a group of individuals (e.g. veterans), your denominator should be individuals as well. If your numerator is a group of housing units (e.g., vacant housing units), your denominator should be housing units as well.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">However, it&#8217;s always best to fine-tune your denominator so that only those in the denominator have a chance to be in the numerator. That&#8217;s why many ACS estimates restrict the denominators to very specific groups. Let&#8217;s look at some examples:<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Individuals age 16+ is the denominator for many of the attributes in the <\/span><a href=\"https:\/\/livingatlas.arcgis.com\/en\/browse\/?q=%22ACS%20Employment%20Status%22#d=2&amp;q=%22ACS%20Employment%20Status%22&amp;type=layers\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">ACS Employment Status layers<\/span><\/a><span data-contrast=\"auto\">, since 16 is the youngest age that a person can legally work. Individuals age 15+ is the denominator in the <\/span><a href=\"https:\/\/livingatlas.arcgis.com\/en\/browse\/?q=%22ACS%20Marital%20Status%22#d=2&amp;q=%22ACS%20Marital%20Status%22&amp;type=layers\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">ACS Marital Status layers<\/span><\/a><span data-contrast=\"auto\"> since it is possible to marry at age 15 (under exceptional circumstances). This blog <\/span><a href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/make-several-nuanced-policy-maps-from-one-arcgis-living-atlas-layer\/\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">on making several nuanced maps from one layer<\/span><\/a><span data-contrast=\"auto\"> mentions that changes to the denominator can change the question you&#8217;re answering. Fine-tuning the denominator like this helps us compare &#8220;apples to apples&#8221; when comparing state, county, or tract numbers, and be sure that the differences are not being driven by differences in age structure, sex ratio, or other population dynamics.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">While restricting the age groups is a simple way that Census has fine-tuned the denominator, there are other more complex examples. Let&#8217;s look at three of the most specific denominators out there:<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<ul>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"17\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">&#8220;For whom poverty status is determined&#8221; is often the denominator for the percent of individuals in poverty. It&#8217;s because poverty status is not calculated for most people in group quarters nor for unrelated individuals under 15 years old (generally foster children).<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"17\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span data-contrast=\"auto\">&#8220;Civilian noninstitutionalized population&#8221; is often the denominator for health insurance variables. This restricts the percentage to only considering civilians (not active duty service members), as well as those who are considered noninstitutionalized: household population as well as people in group quarters such as college dorms and shelters, where they&#8217;re able to come and go. Institutionalized group quarters have long-term care provided (by definition), so the concept of health insurance is very different. &lt;<\/span><span data-contrast=\"auto\">link to group quarters question, below&gt;<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"17\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"3\" data-aria-level=\"1\"><span data-contrast=\"auto\">&#8220;Population under 18 in households excluding householders, spouses, or unmarried partners&#8221; is the denominator for child living arrangements. If we unpack this, we see that it&#8217;s only children in households (no children living in group homes, residential schools, juvenile halls, or 17 year-olds living in college dorms). Additionally, it&#8217;s the population under 18 who are not &#8220;householders, spouses, or unmarried partners,&#8221; so it&#8217;s just population under 18 in households living <\/span><i><span data-contrast=\"auto\">as children<\/span><\/i><span data-contrast=\"auto\"> (no 16 or 17 year-olds living with roommates, with their significant other, or by themselves).<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<\/ul>\n<p><span data-contrast=\"auto\">The ACS layers in Living Atlas have lots of pre-calculated percentages baked into the layers, with the formulas exposed in the long field description. However, we recognize that we do not have every possible calculation. If you need to derive your own percentages, here are some best practices:<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<ul>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"16\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">See if you can use one of ours by subtracting from 100. For example, are you looking for the percentage of population age 5+ who speak a language other than English at home? Use one of calculated percentages available in our <\/span><a href=\"https:\/\/livingatlas.arcgis.com\/en\/browse\/?q=%22ACS%20Language%20Spoken%20at%20Home%22#d=2&amp;q=%22ACS%20Language%20Spoken%20at%20Home%22&amp;type=layers\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">ACS Language Spoken at Home layers<\/span><\/a><span data-contrast=\"auto\"> \u2013 Percent of population age 5+ who speak only English at home \u2013 and subtract it from 100. Then, as an additional check, add up the percentages for the appropriate categories and verify that it yields the same result.\u00a0\u00a0\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"16\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span data-contrast=\"auto\">If trying to calculate age-specific rates or sex-specific rates (for poverty, disability, or other variables), this will involve adding two or more estimates together to get the denominator. Many of these layers have the estimate for the age group who are in the group of interest (those who are living in poverty, have a disability, etc.) and an estimate for the age group who are not in that group. Let&#8217;s look to the formulas in the long field descriptions of the calculated fields in <\/span><a href=\"https:\/\/livingatlas.arcgis.com\/en\/browse\/?q=%22ACS%20Fertility%22#d=2&amp;q=%22ACS%20Fertility%22&amp;type=layers\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">our ACS Fertility in Past 12 Months by Age<\/span><\/a><span data-contrast=\"auto\"> layers as an example. To get the age-specific fertility rate for 45 to 50 year-olds, we add females ages 45 to 50 who have had a birth in the past 12 months (<\/span><span data-contrast=\"auto\">B13016_009E) and those in the same age group who did not have a birth in the past 12 months (B13016_017E) to get the denominator for our final calculation:\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<\/ul>\n<p style=\"text-align: center\"><b><span data-contrast=\"auto\">B13016_009E \/ (B13016_009E + B13016_017E).<\/span><\/b><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335551550&quot;:2,&quot;335551620&quot;:2,&quot;335559685&quot;:720,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><strong><i>I see nulls for some percentages, why?<\/i>\u00a0<\/strong><\/p>\n<p><span data-contrast=\"auto\">The percent is null (undefined) if the value for the denominator is zero. For example, percent of households with no internet in a tract that has no households will be null. The percentage is not applicable here. This is fundamentally different from a tract in which 0% of households have internet. This is a tract that has a number of households, and those households could benefit from investment, programs, or other policies that make it easier for households to get internet. Tracts that are major cemeteries, national parks, or other places with no households would not benefit from such investment because there are no households there in the first place.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">If you know there&#8217;s population in a given tract, but the percentages are still null, this is most likely a tract with only group quarters population and you are looking at an estimate for households.<\/span><\/p>\n<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"null\"><\/a><\/p>\n<h2><strong>Is there a difference between a &#8220;null&#8221; value and a &#8220;0&#8221; value?<\/strong><\/h2>\n<p><span data-contrast=\"auto\">When looking at attributes you may see null and 0 values. These are not the same thing. A value of 0 reflects the possibility of that attribute to be present and have value in the given geographic area of interest, but currently that value is <\/span><b><span data-contrast=\"auto\">0<\/span><\/b><span data-contrast=\"auto\"> or \u201cnot present\u201d. We can think of a <\/span><b><span data-contrast=\"auto\">null<\/span><\/b><span data-contrast=\"auto\"> value as \u201cno data\u201d or \u201cnot applicable.\u201d This means that the attribute you are mapping is not applicable or does not exist in a particular geographic space. However, no data is still incredibly valuable data and can provide a lot of information.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Let\u2019s take a concept as an example: <\/span><b><i><span data-contrast=\"auto\">number of households without access to a car in fire prone areas. <\/span><\/i><\/b><span data-contrast=\"auto\">In one fire prone area, we see a value of \u201c0.\u201d This means that all households have access to a vehicle (or 0 households do not have access to a vehicle). In another fire prone area, we see a value of \u201cnull.\u201d This means that the question we are asking is <\/span><i><span data-contrast=\"auto\">not applicable<\/span><\/i><span data-contrast=\"auto\">. There are no households present, therefore no one without access to a vehicle and our question cannot be solved (this could be because the area is an agricultural field, or national forest land).\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Why is this important? The difference is in the response or application of our question. The \u201cnull\u201d areas may become lower priority for evacuation assistance since there isn\u2019t the risk of people without access to cars trying to evacuate. The areas of \u201c0\u201d value may rank higher than this &#8211; while all households have access to a vehicle, there may be issues or intricacies with evacuations that might require resources from response units.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">In short, don\u2019t ignore your nulls! They represent entirely different information than a value of 0 and can help illuminate why certain patterns do or do not exist across geographic space.<\/span><\/p>\n<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"rateRatioPerc\"><\/a><\/p>\n<h2><strong>What is the difference between a rate, ratio, and percent?<\/strong><\/h2>\n<p><b><span data-contrast=\"auto\">Rate:<\/span><\/b><span data-contrast=\"auto\"> &#8220;X per 1,000&#8221; or &#8220;X per 100,000&#8221;<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Rates are often used to measure prevalence, especially for indicators where a percentage would be too small. For example, infant mortality rates, HIV rates, number of doctors in a community, or other phenomena for which there&#8217;s fewer than 1 case per 100. Let&#8217;s consider infant mortality rates, which are expressed as X per 1,000. Many large hospitals see more than 1,000 births per year, think about how many more there are at the county or state level. In 2020, Colorado had an infant mortality rate of 4.8 per 1,000 live births. New Mexico had an infant mortality rate of 5.3 that same year (<\/span><a href=\"https:\/\/www.cdc.gov\/nchs\/pressroom\/sosmap\/infant_mortality_rates\/infant_mortality.htm\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">CDC<\/span><\/a><span data-contrast=\"auto\">). The decimal places might not seem like a big difference, but they allow us to express the detail in the magnitude of rare events when scaled up to population-level numbers. If Colorado had New Mexico&#8217;s infant mortality rate, the state would have seen 31 more infant deaths that year. However, both rates look like only half a percent when written as a percentage: 0.48% and 0.53%, both of which round to 0.5%. It&#8217;s better to communicate this as 4.8 per 1,000 and 5.3 per 1,000.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<p><b><span data-contrast=\"auto\">Ratio: &#8220;<\/span><\/b><span data-contrast=\"auto\">X:1&#8243; or &#8220;X:100&#8221;<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Ratios are often used to compare the relative size of two groups. The one ratio we include in the ACS layers in Living Atlas is the ratio of males to females in the <\/span><a href=\"https:\/\/livingatlas.arcgis.com\/en\/browse\/?q=%22ACS%20Population%20Variables%22#d=2&amp;q=%22ACS%20Population%20Variables%22&amp;type=layers\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">Total Population layers.<\/span><\/a><span data-contrast=\"auto\"> Because it&#8217;s defined as males:females, ratios above 100 indicate a larger male population, whereas ratios below 100 indicate a larger female population. For example, the sex-ratio in Alaska \u2013 a state with a sizeable military presence &#8211; was 109.2 males to 100 females in the 2016-2020 estimates, whereas the sex-ratio in Florida \u2013 a state with a sizeable elderly population &#8211; was 95.7 males to 100 females. Again, the decimal places make a difference when scaling up to state-level numbers, and when comparing with other states. For example, we can quickly see that Florida has a slightly more even sex-ratio than New Jersey does when comparing 95.7 to 95.5. While both round to 96 males, rounding can result in large differences when scaling up to a population. The larger that population is, the more risk of misinforming resource allocation.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<p><b><span data-contrast=\"auto\">Percent:<\/span><\/b><span data-contrast=\"auto\"> Percentages are often used to express &#8220;part per hundred&#8221; where the hundred represents the denominator or total. Percentages over 100 do not make sense.<\/span><\/p>\n<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"percentagePoint\"><\/a><\/p>\n<h2><strong>What is the difference between percent change and percentage-point change over time?<\/strong><\/h2>\n<p><span data-contrast=\"auto\">Let&#8217;s take a look at a headline from a <\/span><a href=\"https:\/\/www.census.gov\/library\/stories\/2022\/09\/record-drop-in-child-poverty.html#:~:text=Child%20poverty%2C%20calculated%20by%20the,Census%20Bureau%20data%20released%20today.\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">real-life news story<\/span><\/a><span data-contrast=\"auto\">: &#8220;<\/span><span data-contrast=\"none\">Child poverty, calculated by the Supplemental Poverty Measure (SPM), fell to its lowest recorded level in 2021, declining 46% from 9.7% in 2020 to 5.2% in 2021, according to U.S. Census Bureau data released today.&#8221;<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">This is a 46 <\/span><i><span data-contrast=\"auto\">percent<\/span><\/i><span data-contrast=\"auto\"> decrease, since it was almost cut in half (which would be a 50% decrease). It is also a 4.5 <\/span><i><span data-contrast=\"auto\">percentage-point<\/span><\/i><span data-contrast=\"auto\"> decrease, since it went from 9.7% to 5.2%, a difference of 4.5. Saying that this is a 4.5 <\/span><i><span data-contrast=\"auto\">percent<\/span><\/i><span data-contrast=\"auto\"> change would be wrong.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">A percent change can be over 100% if something increased more than double. But a percentage-point change can only be from 0 to 100.<\/span><\/p>\n<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"market\"><\/a><\/p>\n<h2><strong>How can I use Esri Demographics Market Potential data?<\/strong><\/h2>\n<p><span data-contrast=\"auto\">Esri Market Potential data provides insight into how people spend their time and money, what they value, and how these behaviors vary geographically. It is a US dataset that is updated every year to capture the latest changes in the marketplace and ever-evolving consumer patterns.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Market Potential variables are available throughout ArcGIS products \u2013 in ArcGIS Business Analyst, through ArcGIS GeoEnrichment Service, and in ArcGIS Online as premium content.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Additionally, here are more ways to access the data:<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<ul>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"6\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span data-contrast=\"auto\">Access ready-to-use maps through <\/span><a href=\"https:\/\/livingatlas.arcgis.com\/en\/browse\/?q=market%20potential%22%20\\l%20%22d=2&amp;q=Market%20Potential\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">ArcGIS Living Atlas of the World<\/span><\/a><span data-contrast=\"none\">.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"6\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><a href=\"https:\/\/www.esri.com\/en-us\/arcgis\/products\/data\/reports\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"auto\">Buy Esri Reports<\/span><\/a><span data-contrast=\"auto\"> online.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"6\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span data-contrast=\"auto\">For information about purchasing Esri Market Potential data as a stand-alone dataset, contact <\/span><a href=\"mailto:datasales@esri.com\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"auto\">datasales@esri.com<\/span><\/a><span data-contrast=\"auto\">.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<\/ul>\n<p><span data-contrast=\"auto\">In the Business Analyst data browser, you can view Market Potential variables by clicking the Behaviors category (for behaviors) or the Psychographics category (for opinions and attitudes).<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Visit <\/span><a href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/esri-demographics\/business\/five-minutes-market-potential\/\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">this blog<\/span><\/a><span data-contrast=\"auto\"> for more information.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><i><span data-contrast=\"auto\">Thanks to Gemma Goodale-Sussen for this valuable information!<\/span><\/i><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"index\"><\/a><\/p>\n<h2><strong>How can I better understand a collection of multiple demographic attributes, or create an indexed value using socioeconomic factors?<\/strong><\/h2>\n<p><span class=\"TextRun SCXW91203992 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW91203992 BCX0\">Creating an index helps us visualize one or more attributes in relation to a guideline, threshold, or meaningful value. For example, many indices like the <\/span><\/span><a class=\"Hyperlink SCXW91203992 BCX0\" href=\"https:\/\/livingatlas.arcgis.com\/en\/browse\/?q=cdc%20svi#d=2&amp;q=cdc%20svi\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW91203992 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW91203992 BCX0\" data-ccp-charstyle=\"Hyperlink\">CDC&#8217;s Social Vulnerability Index<\/span><\/span><\/a><span class=\"TextRun SCXW91203992 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"> <span class=\"NormalTextRun SCXW91203992 BCX0\">normalize multiple factors into a single value in order to immediately assess the most at-risk communities across the US.<\/span><\/span><span class=\"EOP SCXW91203992 BCX0\" data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1766622,"id":1766622,"title":"Social Vulnerability Index","filename":"SVI.jpg","filesize":314474,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/SVI.jpg","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\/svi-3","alt":"","author":"318562","description":"","caption":"","name":"svi-3","status":"inherit","uploaded_to":1757622,"date":"2022-11-09 19:13:53","modified":"2022-11-09 19:14:12","menu_order":0,"mime_type":"image\/jpeg","type":"image","subtype":"jpeg","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1639,"height":905,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/SVI-213x200.jpg","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/SVI.jpg","medium-width":464,"medium-height":256,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/SVI.jpg","medium_large-width":768,"medium_large-height":424,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/SVI.jpg","large-width":1639,"large-height":905,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/SVI-1536x848.jpg","1536x1536-width":1536,"1536x1536-height":848,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/SVI.jpg","2048x2048-width":1639,"2048x2048-height":905,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/SVI-826x456.jpg","card_image-width":826,"card_image-height":456,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/SVI.jpg","wide_image-width":1639,"wide_image-height":905}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/SVI.jpg"},{"acf_fc_layout":"content","content":"<p><a class=\"Hyperlink SCXW132791269 BCX0\" href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/local-government\/index-maps-inform-help-inform-strategies\/\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW132791269 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW132791269 BCX0\" data-ccp-charstyle=\"Hyperlink\">Index mapping can help us inform strategies<\/span><\/span><\/a><span class=\"TextRun SCXW132791269 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW132791269 BCX0\"> with this use of multi-factor mapping. <\/span><span class=\"NormalTextRun SCXW132791269 BCX0\">By visualizing and comparing demographic attributes against each other or a meaningful value like a national average, we can evaluate areas of need in a standardized method.<\/span><\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1765522,"id":1765522,"title":"Example of Index Mapping","filename":"Index-Map.png","filesize":1960793,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Index-Map.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\/index-map","alt":"","author":"318562","description":"","caption":"","name":"index-map","status":"inherit","uploaded_to":1757622,"date":"2022-11-09 16:19:46","modified":"2022-11-09 16:20:05","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1766,"height":888,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Index-Map-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Index-Map.png","medium-width":464,"medium-height":233,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Index-Map.png","medium_large-width":768,"medium_large-height":386,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Index-Map.png","large-width":1766,"large-height":888,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Index-Map-1536x772.png","1536x1536-width":1536,"1536x1536-height":772,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Index-Map.png","2048x2048-width":1766,"2048x2048-height":888,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Index-Map-826x415.png","card_image-width":826,"card_image-height":415,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Index-Map.png","wide_image-width":1766,"wide_image-height":888}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Index-Map.png"},{"acf_fc_layout":"content","content":"<p><span class=\"TextRun SCXW162167083 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW162167083 BCX0\">To learn how to create your own index, <\/span><\/span><a class=\"Hyperlink SCXW162167083 BCX0\" href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/map-the-factors-stressing-your-community-with-an-index-map\/\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW162167083 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW162167083 BCX0\" data-ccp-charstyle=\"Hyperlink\">visit this blog<\/span><\/span><\/a><span class=\"TextRun SCXW162167083 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW162167083 BCX0\"> that provides a ready-to-use template and workflow.<\/span><\/span><\/p>\n<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"equity\"><\/a><\/p>\n<h2><strong>How can I map topics related to equity?<\/strong><\/h2>\n<p><span data-contrast=\"auto\">GIS is a powerful tool that can be leveraged to affect positive change and address inequities across communities. Esri has a host of resources that can help guide you through mapping topics related to equity and approach your mapping with ethical methodologies and understanding.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Esri\u2019s <\/span><a href=\"https:\/\/gis-for-racialequity.hub.arcgis.com\/#data-racialequity\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">Racial Equity GIS Hub<\/span><\/a><span data-contrast=\"auto\"> is a resource created to help organizations and individuals address racial inequities. Resources included in the Racial Equity Hub include the <\/span><a href=\"https:\/\/www.arcgis.com\/apps\/instant\/portfolio\/index.html?appid=057760ab8d014c678ae5c43f0c650af7\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">Justice40 Atlas<\/span><\/a><span data-contrast=\"auto\">, an atlas of ready-to-use web maps focusing disadvantaged communities under the <\/span><a href=\"https:\/\/screeningtool.geoplatform.gov\/en\/methodology\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">Justice40 Initiative Criteria,<\/span><\/a><span data-contrast=\"auto\"> and ready-to-use data <\/span><a href=\"https:\/\/gis-for-racialequity.hub.arcgis.com\/apps\/disasterresponse::health-racial-economic-equity-data-group\/about\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">surrounding health, racial and economic equity data.<\/span><\/a><span data-contrast=\"auto\">\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">The Living Atlas of the World now contains gender identity and sexual orientation data for the nation, states, and the 15 largest metro areas. <\/span><a href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/announcements\/gender-identity-sexual-orientation\/\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">Read about the dataset here<\/span><\/a><span data-contrast=\"auto\"> and <\/span><a href=\"https:\/\/www.arcgis.com\/home\/item.html?id=802c2ff7625b4d5ca5273aa406f11824\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">access the feature layer<\/span><\/a><span data-contrast=\"auto\"> on the Living Atlas.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">The <\/span><a href=\"https:\/\/livingatlas.arcgis.com\/policy\/overview\/\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">Esri Maps for Public Policy<\/span><\/a><span data-contrast=\"auto\"> site hosts numerous layers, maps and applications that can help you map topics related to equity. Use resources on the Policy site to explore topics like <\/span><a href=\"https:\/\/www.arcgis.com\/apps\/mapviewer\/index.html?webmap=4160631703d54462b7559412fa04279e\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">broadband access<\/span><\/a><span data-contrast=\"auto\">, historic racial inequities using <\/span><a href=\"https:\/\/www.arcgis.com\/home\/item.html?id=ef0f926eb1b146d082c38cc35b53c947\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">redlined neighborhood data<\/span><\/a><span data-contrast=\"auto\">, or map community health using <\/span><a href=\"https:\/\/livingatlas.arcgis.com\/policy\/issues\/#q=County%20Health%20Rankings&amp;category=Social%20Equity%20and%20Health&amp;start=1\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">current and historic County Health Rankings data<\/span><\/a><span data-contrast=\"auto\">.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Explore and utilize these resources to help you map equity in your area of interest.<\/span><\/p>\n<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"raceEthnicity\"><\/a><\/p>\n<h2><strong>How can I better understand the race\/ethnicity attributes when mapping?<\/strong><\/h2>\n<p><span data-contrast=\"auto\">The data on race were derived from answers to the question on race that was asked of individuals in the United States. The Census Bureau collects racial data in accordance with guidelines provided by the U.S. Office of Management and Budget (OMB), and these data are based on self-identification. The racial categories included in census questionnaires generally reflect a social definition of race recognized in this country and not an attempt to define race biologically, anthropologically, or genetically.\u202fThe categories represent a social-political construct designed for collecting data on the race and ethnicity of broad population groups in this country, and are not anthropologically or scientifically based.\u202f<\/span><a href=\"https:\/\/www.census.gov\/topics\/population\/race\/about.html\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"auto\">Learn more here.<\/span><\/a><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><i><span data-contrast=\"auto\">Hispanic vs. Not Hispanic:<\/span><\/i><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Hispanic origin is the heritage, nationality, lineage, or country of birth of a person, or a person\u2019s parents or ancestors. People who identify as Hispanic, Latino, or Spanish may be any race. Some people who identify as Hispanic or Latino also identify with another racial identity.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><i><span data-contrast=\"auto\">Alone vs. Alone or in Combination:<\/span><\/i><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">People may choose to report more than one race group. For example, In our &#8220;<\/span><a href=\"https:\/\/livingatlas.arcgis.com\/en\/browse\/?q=%22ACS%20Specific%20Asian%20Groups%22#d=2&amp;q=%22ACS%20Specific%20Asian%20Groups%22&amp;type=layers\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"auto\">ACS Specific Asian Groups<\/span><\/a><span data-contrast=\"auto\">&#8221; layers, you&#8217;ll notice a field called &#8220;Asian alone,&#8221; and another field called &#8220;Asian alone or in combination with one or more races&#8221; which includes individuals who identify as Asian as well as another group <\/span><span data-contrast=\"auto\">(American Indian and Alaska Native, Black or African American, Native Hawaiian or Other Pacific Islander, White, Other Race). Let&#8217;s explore some differences using the 2021 ACS 1-year estimates, going from the broadest group to the smallest group:<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:true,&quot;201341983&quot;:0,&quot;335559738&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<table style=\"font-weight: 400\" data-tablestyle=\"MsoTableGrid\" data-tablelook=\"1184\">\n<tbody>\n<tr>\n<td data-celllook=\"0\">\n<p style=\"text-align: center\"><b><span data-contrast=\"auto\">Group<\/span><\/b><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:true,&quot;201341983&quot;:0,&quot;335559738&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<\/td>\n<td style=\"text-align: center\" data-celllook=\"0\"><b><span data-contrast=\"auto\">Count<\/span><\/b><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:true,&quot;201341983&quot;:0,&quot;335559738&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/td>\n<td style=\"text-align: center\" data-celllook=\"0\"><b><span data-contrast=\"auto\">Percent of U.S population<\/span><\/b><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:true,&quot;201341983&quot;:0,&quot;335559738&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/td>\n<td data-celllook=\"0\">\n<p style=\"text-align: center\"><b><span data-contrast=\"auto\">Source Table<\/span><\/b><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:true,&quot;201341983&quot;:0,&quot;335559738&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td data-celllook=\"0\"><span data-contrast=\"auto\">Asian alone or in combination with other races<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:true,&quot;201341983&quot;:0,&quot;335559738&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/td>\n<td data-celllook=\"0\"><span data-contrast=\"auto\">23,545,238<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:true,&quot;201341983&quot;:0,&quot;335551550&quot;:2,&quot;335551620&quot;:2,&quot;335559738&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/td>\n<td data-celllook=\"0\"><span data-contrast=\"auto\">7.1%<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:true,&quot;201341983&quot;:0,&quot;335551550&quot;:2,&quot;335551620&quot;:2,&quot;335559738&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/td>\n<td data-celllook=\"0\"><span data-contrast=\"auto\">B02011<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:true,&quot;201341983&quot;:0,&quot;335551550&quot;:2,&quot;335551620&quot;:2,&quot;335559738&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/td>\n<\/tr>\n<tr>\n<td data-celllook=\"0\"><span data-contrast=\"auto\">Asian alone<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:true,&quot;201341983&quot;:0,&quot;335559738&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/td>\n<td data-celllook=\"0\"><span data-contrast=\"auto\">19,157,288<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:true,&quot;201341983&quot;:0,&quot;335551550&quot;:2,&quot;335551620&quot;:2,&quot;335559738&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/td>\n<td data-celllook=\"0\"><span data-contrast=\"auto\">5.8%<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:true,&quot;201341983&quot;:0,&quot;335551550&quot;:2,&quot;335551620&quot;:2,&quot;335559738&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/td>\n<td data-celllook=\"0\"><span data-contrast=\"auto\">B02001<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:true,&quot;201341983&quot;:0,&quot;335551550&quot;:2,&quot;335551620&quot;:2,&quot;335559738&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/td>\n<\/tr>\n<tr>\n<td data-celllook=\"0\"><span data-contrast=\"auto\">Asian alone, not Hispanic or Latino<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:true,&quot;201341983&quot;:0,&quot;335559738&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/td>\n<td data-celllook=\"0\"><span data-contrast=\"auto\">18,889,050<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:true,&quot;201341983&quot;:0,&quot;335551550&quot;:2,&quot;335551620&quot;:2,&quot;335559738&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/td>\n<td data-celllook=\"0\"><span data-contrast=\"auto\">5.7%<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:true,&quot;201341983&quot;:0,&quot;335551550&quot;:2,&quot;335551620&quot;:2,&quot;335559738&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/td>\n<td data-celllook=\"0\"><span data-contrast=\"auto\">B03002<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:true,&quot;201341983&quot;:0,&quot;335551550&quot;:2,&quot;335551620&quot;:2,&quot;335559738&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><em><span class=\"TextRun SCXW208100015 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW208100015 BCX0\">W<\/span><span class=\"NormalTextRun SCXW208100015 BCX0\">hich fields add up to <\/span><span class=\"NormalTextRun ContextualSpellingAndGrammarErrorV2Themed SCXW208100015 BCX0\">total<\/span><span class=\"NormalTextRun SCXW208100015 BCX0\"> pop<\/span><span class=\"NormalTextRun SCXW208100015 BCX0\">ulation<\/span><span class=\"NormalTextRun SCXW208100015 BCX0\">?<\/span><\/span><\/em><span class=\"EOP SCXW208100015 BCX0\" data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1765532,"id":1765532,"title":"Race\/Ethnicity in Los Angeles, CA","filename":"RaceEthnicity_in_LosAngeles.png","filesize":194183,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/RaceEthnicity_in_LosAngeles.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\/raceethnicity_in_losangeles","alt":"","author":"318562","description":"","caption":"","name":"raceethnicity_in_losangeles","status":"inherit","uploaded_to":1757622,"date":"2022-11-09 16:22:29","modified":"2022-11-09 16:22:45","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":624,"height":218,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/RaceEthnicity_in_LosAngeles-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/RaceEthnicity_in_LosAngeles.png","medium-width":464,"medium-height":162,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/RaceEthnicity_in_LosAngeles.png","medium_large-width":624,"medium_large-height":218,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/RaceEthnicity_in_LosAngeles.png","large-width":624,"large-height":218,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/RaceEthnicity_in_LosAngeles.png","1536x1536-width":624,"1536x1536-height":218,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/RaceEthnicity_in_LosAngeles.png","2048x2048-width":624,"2048x2048-height":218,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/RaceEthnicity_in_LosAngeles.png","card_image-width":624,"card_image-height":218,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/RaceEthnicity_in_LosAngeles.png","wide_image-width":624,"wide_image-height":218}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/RaceEthnicity_in_LosAngeles.png"},{"acf_fc_layout":"content","content":"<p><span data-contrast=\"auto\">In order to add up to 100% and not more than 100%, the groups need to be mutually exclusive. That&#8217;s why you&#8217;ll notice groups with the words &#8220;Alone, Not Hispanic Latino&#8221; at the end of 7 of the 8 standard race\/ethnic groups used in our <\/span><a href=\"https:\/\/livingatlas.arcgis.com\/en\/browse\/?q=%22ACS%20Race%20and%20Hispanic%20Origin%22#d=2&amp;q=%22ACS%20Race%20and%20Hispanic%20Origin%22&amp;type=layers\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">ACS Race and Hispanic Origin layers<\/span><\/a><span data-contrast=\"auto\"> and in our <\/span><a href=\"https:\/\/www.arcgis.com\/home\/item.html?id=2603a03fc55244c19f7f73d04cd53cea\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">most common race\/ethnicity web map<\/span><\/a><span data-contrast=\"auto\">.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<ul>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"15\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">White Alone, not Hispanic or Latino<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"15\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">Black or African American Alone, not Hispanic or Latino<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"15\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">American Indian and Alaska Native Alone, not Hispanic or Latino<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"15\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"3\" data-aria-level=\"1\"><span data-contrast=\"auto\">Asian Alone, not Hispanic or Latino<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"15\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"4\" data-aria-level=\"1\"><span data-contrast=\"auto\">Native Hawaiian and Other Pacific Islander, not Hispanic or Latino<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"15\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"5\" data-aria-level=\"1\"><span data-contrast=\"auto\">Some other race, not Hispanic or Latino<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"15\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">Two or more races, not Hispanic or Latino<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"15\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span data-contrast=\"auto\">Hispanic or Latino<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<\/ul>\n<p><span data-contrast=\"auto\">The published &#8220;Two or more races&#8221; group is tabulated by Census from those who check more than one box when responding to the survey (for example, white and American Indian, or Asian and Black). There is not an explicit option on the questionnaire called &#8220;Two or more races.&#8221;<\/span><\/p>\n<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"housing\"><\/a><\/p>\n<h2><strong>What is the difference between a housing unit and a household?<\/strong><\/h2>\n<p><span data-contrast=\"auto\">The ACS only creates estimates for three entities: individuals, households, and housing units.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Housing units are the actual housing structures with walls and roofs that can be either occupied or vacant. This may be a house, an apartment, a mobile home, or rooms which have direct access from outside the building or through a common hall. Boats, recreational vehicles (RVs), vans, tents, railroad cars, and the like are included in the count of housing units only if they are occupied as someone&#8217;s current place of residence. Housing units have attributes such as vacancy status, structure type, year built, and heating fuel used.<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1765692,"id":1765692,"title":"ACS Housing Units Layers in ArcGIS Living Atlas of the World","filename":"HousingUnitsLayers.png","filesize":164101,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/HousingUnitsLayers.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\/housingunitslayers","alt":"","author":"318562","description":"","caption":"","name":"housingunitslayers","status":"inherit","uploaded_to":1757622,"date":"2022-11-09 16:43:59","modified":"2022-11-09 16:44:23","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":624,"height":211,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/HousingUnitsLayers-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/HousingUnitsLayers.png","medium-width":464,"medium-height":157,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/HousingUnitsLayers.png","medium_large-width":624,"medium_large-height":211,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/HousingUnitsLayers.png","large-width":624,"large-height":211,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/HousingUnitsLayers.png","1536x1536-width":624,"1536x1536-height":211,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/HousingUnitsLayers.png","2048x2048-width":624,"2048x2048-height":211,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/HousingUnitsLayers.png","card_image-width":624,"card_image-height":211,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/HousingUnitsLayers.png","wide_image-width":624,"wide_image-height":211}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/HousingUnitsLayers.png"},{"acf_fc_layout":"content","content":"<p><span class=\"TextRun Highlight SCXW195444739 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW195444739 BCX0\">A household <\/span><span class=\"NormalTextRun SCXW195444739 BCX0\">is the group of people in <\/span><span class=\"NormalTextRun SCXW195444739 BCX0\">an <\/span><\/span><span class=\"TextRun Highlight SCXW195444739 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW195444739 BCX0\">occupied<\/span><\/span><span class=\"TextRun Highlight SCXW195444739 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW195444739 BCX0\"> housing unit<\/span><span class=\"NormalTextRun SCXW195444739 BCX0\">. This means <\/span><span class=\"NormalTextRun SCXW195444739 BCX0\">the number of households and the number of occupied housing units are the same <\/span><span class=\"NormalTextRun SCXW195444739 BCX0\">(by definition) <\/span><span class=\"NormalTextRun SCXW195444739 BCX0\">for any given geography<\/span><span class=\"NormalTextRun SCXW195444739 BCX0\">. <\/span><span class=\"NormalTextRun SCXW195444739 BCX0\">A household <\/span><span class=\"NormalTextRun SCXW195444739 BCX0\">must have at least one person<\/span><span class=\"NormalTextRun SCXW195444739 BCX0\">, but often has more<\/span><span class=\"NormalTextRun SCXW195444739 BCX0\">.<\/span> <span class=\"NormalTextRun SCXW195444739 BCX0\">Groups of people living in the same housing unit take many forms: <\/span><span class=\"NormalTextRun SCXW195444739 BCX0\">nuclear families with two married adults and children<\/span><span class=\"NormalTextRun SCXW195444739 BCX0\"> only make up a fraction of all households. Households also include groups of roommates, <\/span><span class=\"NormalTextRun SCXW195444739 BCX0\">cohabiting partners, <\/span><span class=\"NormalTextRun SCXW195444739 BCX0\">retired empty nesters, multigenerational households, <\/span><span class=\"NormalTextRun SCXW195444739 BCX0\">widows<\/span><span class=\"NormalTextRun SCXW195444739 BCX0\">\/<\/span><span class=\"NormalTextRun SCXW195444739 BCX0\">widowers<\/span><span class=\"NormalTextRun SCXW195444739 BCX0\">, <\/span><span class=\"NormalTextRun SCXW195444739 BCX0\">other<\/span><span class=\"NormalTextRun SCXW195444739 BCX0\"> i<\/span><span class=\"NormalTextRun SCXW195444739 BCX0\">ndividuals living alone<\/span><span class=\"NormalTextRun SCXW195444739 BCX0\">, and more<\/span><span class=\"NormalTextRun SCXW195444739 BCX0\">.<\/span> <span class=\"NormalTextRun SCXW195444739 BCX0\">Households have attributes such as vehicle availability<\/span><span class=\"NormalTextRun SCXW195444739 BCX0\">, household income<\/span><span class=\"NormalTextRun SCXW195444739 BCX0\">, and household size<\/span><span class=\"NormalTextRun SCXW195444739 BCX0\">.<\/span><\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1765712,"id":1765712,"title":"ACS Household Layers in ArcGIS Living Atlas of the World","filename":"HouseholdLayers.png","filesize":154803,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/HouseholdLayers.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\/householdlayers","alt":"","author":"318562","description":"","caption":"","name":"householdlayers","status":"inherit","uploaded_to":1757622,"date":"2022-11-09 16:44:59","modified":"2022-11-09 16:45:20","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":624,"height":210,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/HouseholdLayers-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/HouseholdLayers.png","medium-width":464,"medium-height":156,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/HouseholdLayers.png","medium_large-width":624,"medium_large-height":210,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/HouseholdLayers.png","large-width":624,"large-height":210,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/HouseholdLayers.png","1536x1536-width":624,"1536x1536-height":210,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/HouseholdLayers.png","2048x2048-width":624,"2048x2048-height":210,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/HouseholdLayers.png","card_image-width":624,"card_image-height":210,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/HouseholdLayers.png","wide_image-width":624,"wide_image-height":210}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/HouseholdLayers.png"},{"acf_fc_layout":"content","content":"<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"household\"><\/a><\/p>\n<h2><strong>What is the difference between household population and group quarters population?<\/strong><\/h2>\n<p><span data-contrast=\"auto\">Even though &#8220;households&#8221; encompass a vast array of people, about 2.5% of the population do not live in households at all. They live in group quarters. Group quarters are places where people live or stay in a group-based living arrangement rather than a household. People in correctional facilities, nursing\/assisted living facilities, military barracks, college dorms, juvenile group homes, juvenile residential schools, emergency or transitional shelters, farm workers&#8217; camps, and many more all make up the group quarters population. For a detailed list of various types of group quarters populations, see <\/span><a href=\"https:\/\/www2.census.gov\/programs-surveys\/acs\/tech_docs\/group_definitions\/2021GQ_Definitions.pdf?\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">Census doc on group quarters definitions<\/span><\/a><span data-contrast=\"auto\">. In some census tracts, the group quarters population can be a large portion of the overall population, such as those that contain a university campus, a military base, or a prison.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">There are two general guidelines used when classifying a dwelling place as group quarters:<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<ul>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"13\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">People living here are often not related to each other<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"13\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span data-contrast=\"auto\">The place is often managed by the organization providing the housing<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<\/ul>\n<p><span data-contrast=\"auto\">For most attributes, the group quarters population is included in estimates <\/span><i><span data-contrast=\"auto\">of individuals<\/span><\/i><span data-contrast=\"auto\"> (median age, educational attainment, marital status, race\/ethnicity). The group quarters population is not included in estimates of <\/span><i><span data-contrast=\"auto\">households <\/span><\/i><span data-contrast=\"auto\">(internet, vehicle availability, housing cost burden).<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Census also makes a distinction between &#8220;institutionalized&#8221; group quarters such as nursing\/assisted living facilities and correctional facilities, vs. &#8220;noninstitutionalized&#8221; group quarters such as college dorms and shelters. In institutionalized group quarters, there is long-term care provided. In noninstitutionalized group quarters, no long-term care is provided, and residents can generally leave the building during the day.<\/span><\/p>\n<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"ethics\"><\/a><\/p>\n<h2><strong>What are some resources and best practices for mapping with ethics?<\/strong><\/h2>\n<p><span data-contrast=\"auto\">As mapmakers, our work is often viewed as a reliable, authoritative source of information. We therefore have a responsibility to approach our analyses and our presentation of spatial, and especially demographic, information with ethical considerations. Using honest, open, and sound methodologies can guide us through ethical approaches to mapping.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Here are some resources to help guide through the process of mapping, ensuring you are making the right decisions to provide valuable information and minimize harm.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Racial Equity Hub: <\/span><a href=\"https:\/\/www.esri.com\/en-us\/racial-equity\/overview\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">https:\/\/www.esri.com\/en-us\/racial-equity\/overview<\/span><\/a><span data-contrast=\"auto\">\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Advancing Ethics in Mapmaking: <\/span><a href=\"https:\/\/www.esri.com\/about\/newsroom\/arcnews\/advancing-ethics-in-mapmaking\/\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">https:\/\/www.esri.com\/about\/newsroom\/arcnews\/advancing-ethics-in-mapmaking\/<\/span><\/a><span data-contrast=\"auto\">\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Ethics in mapping: <\/span><a href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/mapping\/ethics-in-mapping\/\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/mapping\/ethics-in-mapping\/<\/span><\/a><span data-contrast=\"auto\">\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">The Mapmaker&#8217;s Mantra: <\/span><a href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-online\/mapping\/mapmakers-mantra\/\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-online\/mapping\/mapmakers-mantra\/<\/span><\/a><span data-contrast=\"auto\">\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Ethical considerations for surveys: <\/span><a href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/survey123\/constituent-engagement\/ethics\/\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">https:\/\/www.esri.com\/arcgis-blog\/products\/survey123\/constituent-engagement\/ethics\/<\/span><\/a><span data-contrast=\"auto\">\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"practices\"><\/a><\/p>\n<h2><strong>What are the best practices when mapping demographic data?<\/strong><\/h2>\n<p><span data-contrast=\"auto\">There are many ways to map socioeconomic factors to help communicate key narratives from the data. A few tips\/suggestions when mapping demographics:<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><b><span data-contrast=\"auto\">Counts = Size<\/span><\/b><span data-contrast=\"auto\">: Mapping a count? For example, if I want to know where there are high counts of Hispanic or Latino populations by county in the US, I would use a proportional size symbol to show this:<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1766632,"id":1766632,"title":"Mapping with Size","filename":"Size.jpg","filesize":403756,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Size.jpg","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\/size-4","alt":"","author":"318562","description":"","caption":"","name":"size-4","status":"inherit","uploaded_to":1757622,"date":"2022-11-09 19:14:51","modified":"2022-11-09 19:15:04","menu_order":0,"mime_type":"image\/jpeg","type":"image","subtype":"jpeg","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1867,"height":1001,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Size-213x200.jpg","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Size.jpg","medium-width":464,"medium-height":249,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Size.jpg","medium_large-width":768,"medium_large-height":412,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Size.jpg","large-width":1867,"large-height":1001,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Size-1536x824.jpg","1536x1536-width":1536,"1536x1536-height":824,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Size.jpg","2048x2048-width":1867,"2048x2048-height":1001,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Size-826x443.jpg","card_image-width":826,"card_image-height":443,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Size.jpg","wide_image-width":1867,"wide_image-height":1001}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Size.jpg"},{"acf_fc_layout":"content","content":"<p><span data-contrast=\"auto\">When mapping the count of a population, it is best practice to use a size symbol to represent this quantity. This allows you to see where the largest groupings of that population type are.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Click <\/span><a href=\"https:\/\/storymaps.arcgis.com\/collections\/9dd9f03ac2554da4af78b42020fb40c1?item=5\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">here<\/span><\/a><span data-contrast=\"auto\"> for more information about how to map a count attribute with size.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><b><span data-contrast=\"auto\">Normalized attribute = Color<\/span><\/b><span data-contrast=\"auto\">: Are you mapping a percent, index or ratio? Thematic coloring is the way to go. For example, if you want to visualize the percent of total population who are Hispanic or Latino, color is a more appropriate method than size:<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1766642,"id":1766642,"title":"Mapping with Color","filename":"Color.jpg","filesize":234488,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Color.jpg","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\/color-24","alt":"","author":"318562","description":"","caption":"","name":"color-24","status":"inherit","uploaded_to":1757622,"date":"2022-11-09 19:15:29","modified":"2022-11-09 19:15:41","menu_order":0,"mime_type":"image\/jpeg","type":"image","subtype":"jpeg","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1861,"height":1000,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Color-213x200.jpg","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Color.jpg","medium-width":464,"medium-height":249,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Color.jpg","medium_large-width":768,"medium_large-height":413,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Color.jpg","large-width":1861,"large-height":1000,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Color-1536x825.jpg","1536x1536-width":1536,"1536x1536-height":825,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Color.jpg","2048x2048-width":1861,"2048x2048-height":1000,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Color-826x444.jpg","card_image-width":826,"card_image-height":444,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Color.jpg","wide_image-width":1861,"wide_image-height":1000}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Color.jpg"},{"acf_fc_layout":"content","content":"<p><span data-contrast=\"auto\">When mapping a normalized attribute, it is best practice to use a choropleth polygon fill for your thematic map. This allows you to visualize the density more clearly.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Click <\/span><a href=\"https:\/\/storymaps.arcgis.com\/collections\/9dd9f03ac2554da4af78b42020fb40c1?item=6\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">here<\/span><\/a><span data-contrast=\"auto\"> for more information about how to map a count attribute with color.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><b><span data-contrast=\"auto\">Percent + count = Color &amp; Size:<\/span><\/b><span data-contrast=\"auto\"> If you want to reinforce a topic, use the percentage for the color and then use the denominator as the size attribute. For example, you can show both the count of Hispanic or Latino population alongside the percentage of total population who are Hispanic or Latino to combine the two maps above into a single map:<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1766652,"id":1766652,"title":"Mapping with Color and Size","filename":"Color-and-Size.jpg","filesize":290004,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Color-and-Size.jpg","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\/color-and-size-2","alt":"","author":"318562","description":"","caption":"","name":"color-and-size-2","status":"inherit","uploaded_to":1757622,"date":"2022-11-09 19:16:08","modified":"2022-11-09 19:16:21","menu_order":0,"mime_type":"image\/jpeg","type":"image","subtype":"jpeg","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1866,"height":1005,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Color-and-Size-213x200.jpg","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Color-and-Size.jpg","medium-width":464,"medium-height":250,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Color-and-Size.jpg","medium_large-width":768,"medium_large-height":414,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Color-and-Size.jpg","large-width":1866,"large-height":1005,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Color-and-Size-1536x827.jpg","1536x1536-width":1536,"1536x1536-height":827,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Color-and-Size.jpg","2048x2048-width":1866,"2048x2048-height":1005,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Color-and-Size-826x445.jpg","card_image-width":826,"card_image-height":445,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Color-and-Size.jpg","wide_image-width":1866,"wide_image-height":1005}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Color-and-Size.jpg"},{"acf_fc_layout":"content","content":"<p><span data-contrast=\"auto\">By combining both a percentage and count of a related topic, we can visualize not only the overall quantity, but also the overall density. This technique allows us to combine two maps into a single map.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Click <\/span><a href=\"https:\/\/storymaps.arcgis.com\/collections\/9dd9f03ac2554da4af78b42020fb40c1?item=7\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">here<\/span><\/a><span data-contrast=\"auto\"> for more information about how to map a count attribute with color and size.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><b><span data-contrast=\"auto\">Compare multiple counts = Dot Density\/Predominance\/Charts<\/span><\/b><span data-contrast=\"auto\">: When you are mapping attributes that fall under the same universe, you can use these techniques as different comparison methods.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><strong>Predominance<\/strong><span data-contrast=\"auto\"> (which value is the largest?) For example, if you want to see which race or ethnicity is most common within an area, you can use a predominance mapping style to see which one is most prevalent:<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1766662,"id":1766662,"title":"Mapping with Predominance","filename":"Predominance.jpg","filesize":243505,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Predominance.jpg","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\/predominance-5","alt":"","author":"318562","description":"","caption":"","name":"predominance-5","status":"inherit","uploaded_to":1757622,"date":"2022-11-09 19:16:43","modified":"2022-11-09 19:16:57","menu_order":0,"mime_type":"image\/jpeg","type":"image","subtype":"jpeg","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1862,"height":1004,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Predominance-213x200.jpg","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Predominance.jpg","medium-width":464,"medium-height":250,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Predominance.jpg","medium_large-width":768,"medium_large-height":414,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Predominance.jpg","large-width":1862,"large-height":1004,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Predominance-1536x828.jpg","1536x1536-width":1536,"1536x1536-height":828,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Predominance.jpg","2048x2048-width":1862,"2048x2048-height":1004,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Predominance-826x445.jpg","card_image-width":826,"card_image-height":445,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Predominance.jpg","wide_image-width":1862,"wide_image-height":1004}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Predominance.jpg"},{"acf_fc_layout":"content","content":"<p><strong><span class=\"TextRun Underlined SCXW86645960 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW86645960 BCX0\">Dot Density:<\/span><\/span><\/strong><span class=\"TextRun SCXW86645960 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW86645960 BCX0\"> (where are the values the <\/span><span class=\"NormalTextRun ContextualSpellingAndGrammarErrorV2Themed SCXW86645960 BCX0\">most dense<\/span><span class=\"NormalTextRun SCXW86645960 BCX0\">\/least dense?)<\/span><span class=\"NormalTextRun SCXW86645960 BCX0\"> For example, if you want to see the overall density of population by the different race\/ethnicity groups, dot density visualizes the data as points within each feature:<\/span><\/span><span class=\"EOP SCXW86645960 BCX0\" data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1766692,"id":1766692,"title":"Mapping with Dot Density","filename":"Dot-Density.jpg","filesize":503668,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Dot-Density.jpg","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\/dot-density-2","alt":"","author":"318562","description":"","caption":"","name":"dot-density-2","status":"inherit","uploaded_to":1757622,"date":"2022-11-09 19:20:36","modified":"2022-11-09 19:20:51","menu_order":0,"mime_type":"image\/jpeg","type":"image","subtype":"jpeg","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1763,"height":859,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Dot-Density-213x200.jpg","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Dot-Density.jpg","medium-width":464,"medium-height":226,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Dot-Density.jpg","medium_large-width":768,"medium_large-height":374,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Dot-Density.jpg","large-width":1763,"large-height":859,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Dot-Density-1536x748.jpg","1536x1536-width":1536,"1536x1536-height":748,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Dot-Density.jpg","2048x2048-width":1763,"2048x2048-height":859,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Dot-Density-826x402.jpg","card_image-width":826,"card_image-height":402,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Dot-Density.jpg","wide_image-width":1763,"wide_image-height":859}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Dot-Density.jpg"},{"acf_fc_layout":"content","content":"<p><span class=\"TextRun SCXW32960375 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><strong><span class=\"NormalTextRun SCXW32960375 BCX0\">Charts <\/span><span class=\"NormalTextRun SCXW32960375 BCX0\">or Charts and Size: <\/span><\/strong><span class=\"NormalTextRun SCXW32960375 BCX0\">(what is the distribution of the different data values?)<\/span> <span class=\"NormalTextRun SCXW32960375 BCX0\">If you wanted to instead see the overall breakdown of each race\/ethnicity group, the Charts and Size method lets you visualize the breakdown within a pie chart symbol, and you can use the size to show overall count:<\/span><\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1766672,"id":1766672,"title":"Mapping with Charts or Charts and Size","filename":"Charts.jpg","filesize":349792,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Charts.jpg","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\/charts-11","alt":"","author":"318562","description":"","caption":"","name":"charts-11","status":"inherit","uploaded_to":1757622,"date":"2022-11-09 19:17:23","modified":"2022-11-09 19:17:39","menu_order":0,"mime_type":"image\/jpeg","type":"image","subtype":"jpeg","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1863,"height":1004,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Charts-213x200.jpg","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Charts.jpg","medium-width":464,"medium-height":250,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Charts.jpg","medium_large-width":768,"medium_large-height":414,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Charts.jpg","large-width":1863,"large-height":1004,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Charts-1536x828.jpg","1536x1536-width":1536,"1536x1536-height":828,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Charts.jpg","2048x2048-width":1863,"2048x2048-height":1004,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Charts-826x445.jpg","card_image-width":826,"card_image-height":445,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Charts.jpg","wide_image-width":1863,"wide_image-height":1004}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Charts.jpg"},{"acf_fc_layout":"content","content":"<p><span data-contrast=\"auto\">You can also use the charts method without the size component if you have trouble getting the symbols to tell a clear story.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">All three of these maps are valid, and they all communicate a different story about the data. Easily swap between the different styles to see which one works best for your needs.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">To learn more about these mapping styles and how to apply them:<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<ul>\n<li data-leveltext=\"-\" data-font=\"Calibri\" data-listid=\"1\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Calibri&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;-&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><a href=\"https:\/\/storymaps.arcgis.com\/collections\/9dd9f03ac2554da4af78b42020fb40c1?item=9\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">Predominance<\/span><\/a><span data-contrast=\"auto\">\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"-\" data-font=\"Calibri\" data-listid=\"1\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Calibri&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;-&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"2\" data-aria-level=\"1\"><a href=\"https:\/\/storymaps.arcgis.com\/collections\/9dd9f03ac2554da4af78b42020fb40c1?item=14\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">Dot Density<\/span><\/a><span data-contrast=\"auto\">\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"-\" data-font=\"Calibri\" data-listid=\"1\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Calibri&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;-&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"3\" data-aria-level=\"1\"><a href=\"https:\/\/storymaps.arcgis.com\/collections\/9dd9f03ac2554da4af78b42020fb40c1?item=15\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">Charts<\/span><\/a><span data-contrast=\"auto\">\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<\/ul>\n<p><b><span data-contrast=\"auto\">Compare multiple normalized attributes = Relationship:<\/span><\/b><span data-contrast=\"auto\"> If you want to compare two normalized attributes to see where their patterns converge or diverge, you can explore these visual patterns using a bivariate method called a relationship map. For example, if you want to see where the patterns exist for both the Black or African American Populations and the Hispanic or Latino populations, you could use a relationship map to visualize both patterns at once:<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1766682,"id":1766682,"title":"Mapping with Relationships","filename":"Relationship.jpg","filesize":320537,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Relationship.jpg","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\/relationship-4","alt":"","author":"318562","description":"","caption":"","name":"relationship-4","status":"inherit","uploaded_to":1757622,"date":"2022-11-09 19:18:01","modified":"2022-11-09 19:18:18","menu_order":0,"mime_type":"image\/jpeg","type":"image","subtype":"jpeg","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1862,"height":1004,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Relationship-213x200.jpg","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Relationship.jpg","medium-width":464,"medium-height":250,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Relationship.jpg","medium_large-width":768,"medium_large-height":414,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Relationship.jpg","large-width":1862,"large-height":1004,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Relationship-1536x828.jpg","1536x1536-width":1536,"1536x1536-height":828,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Relationship.jpg","2048x2048-width":1862,"2048x2048-height":1004,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Relationship-826x445.jpg","card_image-width":826,"card_image-height":445,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Relationship.jpg","wide_image-width":1862,"wide_image-height":1004}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Relationship.jpg"},{"acf_fc_layout":"content","content":"<p><span class=\"TextRun SCXW31793911 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW31793911 BCX0\">Click <\/span><\/span><a class=\"Hyperlink SCXW31793911 BCX0\" href=\"https:\/\/storymaps.arcgis.com\/collections\/9dd9f03ac2554da4af78b42020fb40c1?item=10\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW31793911 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW31793911 BCX0\" data-ccp-charstyle=\"Hyperlink\">here<\/span><\/span><\/a><span class=\"TextRun SCXW31793911 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW31793911 BCX0\"> to learn more about how to apply the relationship mapping style to your maps.\u00a0<\/span><\/span><\/p>\n<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"margins\"><\/a><\/p>\n<h2><strong>I want to use American Community Survey (ACS) data, but I don&#8217;t understand the margins of error. How can I learn how to use and map this information?<\/strong><\/h2>\n<p><span data-contrast=\"auto\">Since the American Community Survey (ACS) surveys the population by taking a sample, the estimates from the U.S. Census Bureau contain some level of error, known as the margin of error (MOE). For each estimate, there is an associated MOE, which helps us understand if the estimate is reliable. These can be useful to include when mapping surveyed data such as ACS.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">The <\/span><a href=\"https:\/\/www.census.gov\/programs-surveys\/acs\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"auto\">American Community Survey<\/span><\/a><span data-contrast=\"auto\"> (ACS) from the U.S. Census Bureau offers a margin of error for the data estimates they provide. This tells those who are using the data that the estimate is not an exact figure, but rather a range of possible values. The MOE helps us figure out that range. For example, if the estimate for a certain group of people for an area is 361 people, there will be an associated margin of error for that estimate. If the MOE is 158, the true number of people in that group there falls somewhere between 203 and 519.<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1765882,"id":1765882,"title":"Margins of Error","filename":"MOE.png","filesize":10874,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/MOE.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\/moe","alt":"","author":"318562","description":"","caption":"","name":"moe","status":"inherit","uploaded_to":1757622,"date":"2022-11-09 16:55:55","modified":"2022-11-09 16:56:05","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":565,"height":435,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/MOE-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/MOE.png","medium-width":339,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/MOE.png","medium_large-width":565,"medium_large-height":435,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/MOE.png","large-width":565,"large-height":435,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/MOE.png","1536x1536-width":565,"1536x1536-height":435,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/MOE.png","2048x2048-width":565,"2048x2048-height":435,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/MOE.png","card_image-width":565,"card_image-height":435,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/MOE.png","wide_image-width":565,"wide_image-height":435}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/MOE.png"},{"acf_fc_layout":"content","content":"<p><span data-contrast=\"auto\">This range of values is known as the \u201cconfidence interval\u201d and tells us that the Census Bureau is 90% confident that the count of population is between the upper and lower values.\u00a0\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">These are just a few examples of the many factors that can impact the reliability of our data. The fact that these errors exist and can come from so many places are why it is important to effectively communicate margins of error to our map audience. Your map reader could see a map and assume that the numbers are exact, when in fact they have sampling error. Being transparent about margins of error creates accountability for both the map\u2019s creator and those making decisions from the data.\u00a0\u00a0\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Margins of error can be communicated through your <\/span><a href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/a-straightforward-approach-to-mapping-margins-of-error\/\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">symbology<\/span><\/a><span data-contrast=\"auto\">, <\/span><a href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/effective-ways-to-communicate-margins-of-error-through-pop-ups\/\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">pop-ups<\/span><\/a><span data-contrast=\"auto\">, and <\/span><a href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/explore-labeling-in-map-viewer-to-convey-margins-of-error\/\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">labels<\/span><\/a><span data-contrast=\"auto\"> with various methods to communicate the reliability of the data.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">For more information about mapping, using, and understanding Margins of Error, <\/span><a href=\"https:\/\/learn.arcgis.com\/en\/paths\/mapping-with-margins-of-error\/\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">visit this Learn path<\/span><\/a><span data-contrast=\"auto\">.<\/span><\/p>\n<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"statistics\"><\/a><\/p>\n<h2><strong>How do I calculate population statistics for my unique area of interest?<\/strong><\/h2>\n<p><span data-contrast=\"auto\">You can quickly aggregate population data to unique boundaries, such as school districts or wildfire hazard areas, using Arcade and American Community Survey data in Living Atlas. Aggregating demographic information to your area of interest can imbue demographic details that answer questions like, \u201cWho is disproportionately at risk?\u201d \u201cHow many children do not have internet at home in this school district?\u201d or \u201cHow many people have been impacted by a flood event?\u201d<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Aggregating socioeconomic or other information using arcade is valuable as it happens on-the-fly. If your boundary or your underlying data changes, your aggregation stays up to date.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Keep in mind that when aggregating, you are presenting approximations, not exact numbers. This method is therefore great for quick estimates and summarizations \u2013 or a snapshot of what conditions may look like in each area. Be sure to express this distinction in your map and pop-ups with appropriate language.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1765902,"id":1765902,"title":"Language Example with use of Approximations or Aggregations","filename":"ApproximatelyLanguage.png","filesize":1341260,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/ApproximatelyLanguage.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\/approximatelylanguage","alt":"","author":"318562","description":"","caption":"","name":"approximatelylanguage","status":"inherit","uploaded_to":1757622,"date":"2022-11-09 16:58:25","modified":"2022-11-09 16:58:53","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1449,"height":1014,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/ApproximatelyLanguage-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/ApproximatelyLanguage.png","medium-width":373,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/ApproximatelyLanguage.png","medium_large-width":768,"medium_large-height":537,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/ApproximatelyLanguage.png","large-width":1449,"large-height":1014,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/ApproximatelyLanguage.png","1536x1536-width":1449,"1536x1536-height":1014,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/ApproximatelyLanguage.png","2048x2048-width":1449,"2048x2048-height":1014,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/ApproximatelyLanguage-664x465.png","card_image-width":664,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/ApproximatelyLanguage.png","wide_image-width":1449,"wide_image-height":1014}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/ApproximatelyLanguage.png"},{"acf_fc_layout":"content","content":"<p><a href=\"https:\/\/www.arcgis.com\/apps\/instant\/sidebar\/index.html?appid=70215ec8d3574fc5813e54ef5869c0f4\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">This application<\/span><\/a><span data-contrast=\"auto\"> aggregates socioeconomic information to school district boundaries across the United States. See the <\/span><a href=\"https:\/\/www.arcgis.com\/apps\/mapviewer\/index.html?webmap=ba1dd52b501c4c82a24e02b5f95916df\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">underlying web map<\/span><\/a><span data-contrast=\"auto\"> and open the pop-up expressions to view how the information was aggregated through Arcade.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><em>P.S. This map pulls in socioeconomic information from layers that are not present in the web map. Check out <a href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/data-management\/pump-up-your-pop-ups-with-arcade-featuresets-and-living-atlas-part-2\/\" target=\"_blank\" rel=\"noopener\">this blog<\/a> to see how this is done.<\/em><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><b><span data-contrast=\"auto\">Things of note:<\/span><\/b><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<ul>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"18\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">When aggregating, use functions like Sum() to quickly aggregate values<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"18\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span data-contrast=\"auto\">When calculating a percent, use Sum() and then calculate the percent at the end. If you use percentage fields, you will get an incorrect number.<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"18\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">Report values as \u201cestimates\u201d and \u201capproximations\u201d<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"18\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span data-contrast=\"auto\">Include a population-weighted example<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"18\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"3\" data-aria-level=\"1\"><span data-contrast=\"auto\">Geometry functions are scale based, meaning you are yielding results only as precise as the view scale. Your results may differ at each view scale. Read more about scale dependency with geometry functions <\/span><a href=\"https:\/\/developers.arcgis.com\/arcade\/function-reference\/geometry_functions\/\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">here<\/span><\/a><span data-contrast=\"auto\">.<\/span><\/li>\n<\/ul>\n<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"nested\"><\/a><\/p>\n<h2><strong>Do different levels of Census boundaries line up nicely? (Nested vs Non-Nested boundaries)<\/strong><\/h2>\n<p><span data-contrast=\"auto\">When working with demographic information, pay attention to whether your boundaries line up nicely in space. Nested boundaries, or those that line up nicely, are those that fall precisely within a larger, parent boundary. Non-nested boundaries do not fall precisely within a larger, parent boundary. Understanding the geographic relationship between your boundaries is key to your understanding and analysis. Let\u2019s look at Census data for an example.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Nested boundaries: Block groups must fall within their corresponding census tract. Census tracts must fall within their corresponding county, and counties must fall within their state. Therefore, all block groups must fall within their corresponding county and state.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><a href=\"https:\/\/www.census.gov\/newsroom\/blogs\/random-samplings\/2014\/07\/understanding-geographic-relationships-counties-places-tracts-and-more.html\"><span data-contrast=\"none\">Reference this article<\/span><\/a><span data-contrast=\"auto\"> to read more about nested boundaries and geographic relationships when using census data.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1765922,"id":1765922,"title":"U.S. Census Chart of Nested Boundaries","filename":"U.S.-Census-Chart-of-Nested-Boundaries.png","filesize":302076,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/U.S.-Census-Chart-of-Nested-Boundaries.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\/u-s-census-chart-of-nested-boundaries","alt":"","author":"318562","description":"","caption":"","name":"u-s-census-chart-of-nested-boundaries","status":"inherit","uploaded_to":1757622,"date":"2022-11-09 17:02:07","modified":"2022-11-09 17:02:07","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":733,"height":730,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/U.S.-Census-Chart-of-Nested-Boundaries-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/U.S.-Census-Chart-of-Nested-Boundaries.png","medium-width":262,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/U.S.-Census-Chart-of-Nested-Boundaries.png","medium_large-width":733,"medium_large-height":730,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/U.S.-Census-Chart-of-Nested-Boundaries.png","large-width":733,"large-height":730,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/U.S.-Census-Chart-of-Nested-Boundaries.png","1536x1536-width":733,"1536x1536-height":730,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/U.S.-Census-Chart-of-Nested-Boundaries.png","2048x2048-width":733,"2048x2048-height":730,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/U.S.-Census-Chart-of-Nested-Boundaries-467x465.png","card_image-width":467,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/U.S.-Census-Chart-of-Nested-Boundaries.png","wide_image-width":733,"wide_image-height":730}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.census.gov\/newsroom\/blogs\/random-samplings\/2014\/07\/understanding-geographic-relationships-counties-places-tracts-and-more.html"},{"acf_fc_layout":"content","content":"<p><span class=\"TextRun SCXW79149123 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW79149123 BCX0\">Non-nested boundaries: <\/span><span class=\"NormalTextRun SCXW79149123 BCX0\">non-nested<\/span><span class=\"NormalTextRun SCXW79149123 BCX0\"> boundaries<\/span><span class=\"NormalTextRun SCXW79149123 BCX0\"> are those that<\/span><span class=\"NormalTextRun SCXW79149123 BCX0\"> do not line up nicely and can change your analysis.<\/span><span class=\"NormalTextRun SCXW79149123 BCX0\"> For example, say you want to get a count of population within a <\/span><span class=\"NormalTextRun SCXW79149123 BCX0\">school district<\/span><span class=\"NormalTextRun SCXW79149123 BCX0\">. <\/span><span class=\"NormalTextRun SCXW79149123 BCX0\">School district<\/span><span class=\"NormalTextRun SCXW79149123 BCX0\"> boundaries <\/span><span class=\"NormalTextRun SCXW79149123 BCX0\">must fall within a state, and districts may cross county and census tract boundaries. <\/span><span class=\"NormalTextRun SCXW79149123 BCX0\">If you select all census tracts that cross or are within a <\/span><span class=\"NormalTextRun SCXW79149123 BCX0\">school district<\/span><span class=\"NormalTextRun SCXW79149123 BCX0\"> boundary and sum<\/span><span class=\"NormalTextRun SCXW79149123 BCX0\">marize the population, you could get an <\/span><span class=\"NormalTextRun SCXW79149123 BCX0\">inaccurate<\/span><span class=\"NormalTextRun SCXW79149123 BCX0\"> number if one of your census tracts just barely touches the <\/span><span class=\"NormalTextRun SCXW79149123 BCX0\">district<\/span><span class=\"NormalTextRun SCXW79149123 BCX0\"> boundary but <\/span><span class=\"NormalTextRun SCXW79149123 BCX0\">isn\u2019t<\/span> <span class=\"NormalTextRun SCXW79149123 BCX0\">included <\/span><span class=\"NormalTextRun SCXW79149123 BCX0\">within.<\/span><span class=\"NormalTextRun SCXW79149123 BCX0\">\u00a0<\/span><\/span><span class=\"EOP SCXW79149123 BCX0\" data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1765942,"id":1765942,"title":"Non-Nested Boundaries Example","filename":"Non-Nested-Boundaries-Example.png","filesize":317914,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Non-Nested-Boundaries-Example.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\/non-nested-boundaries-example","alt":"","author":"318562","description":"","caption":"","name":"non-nested-boundaries-example","status":"inherit","uploaded_to":1757622,"date":"2022-11-09 17:03:07","modified":"2022-11-09 17:03:07","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1683,"height":783,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Non-Nested-Boundaries-Example-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Non-Nested-Boundaries-Example.png","medium-width":464,"medium-height":216,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Non-Nested-Boundaries-Example.png","medium_large-width":768,"medium_large-height":357,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Non-Nested-Boundaries-Example.png","large-width":1683,"large-height":783,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Non-Nested-Boundaries-Example-1536x715.png","1536x1536-width":1536,"1536x1536-height":715,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Non-Nested-Boundaries-Example.png","2048x2048-width":1683,"2048x2048-height":783,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Non-Nested-Boundaries-Example-826x384.png","card_image-width":826,"card_image-height":384,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Non-Nested-Boundaries-Example.png","wide_image-width":1683,"wide_image-height":783}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Non-Nested-Boundaries-Example.png"},{"acf_fc_layout":"content","content":"<p><span class=\"NormalTextRun SCXW221084355 BCX0\">The school district boundary in red has many different census tracts that fall within and outside of <\/span><span class=\"NormalTextRun SCXW221084355 BCX0\">its<\/span><span class=\"NormalTextRun SCXW221084355 BCX0\"> boundary. If we were to pull the population from <\/span><span class=\"NormalTextRun SCXW221084355 BCX0\">all<\/span><span class=\"NormalTextRun SCXW221084355 BCX0\"> these census tracts, we would h<\/span><span class=\"NormalTextRun SCXW221084355 BCX0\">ave an over-inflated number. This census tract here barely crosses the boundary of the school district, so it wouldn\u2019t make sense to say that tract\u2019s entire population is represented inside the school district.<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1765982,"id":1765982,"title":"Census Tract non-nested boundary example","filename":"Census-Tract-non-nested.png","filesize":205748,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Census-Tract-non-nested.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\/census-tract-non-nested","alt":"","author":"318562","description":"","caption":"","name":"census-tract-non-nested","status":"inherit","uploaded_to":1757622,"date":"2022-11-09 17:04:00","modified":"2022-11-09 17:04:11","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":784,"height":738,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Census-Tract-non-nested-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Census-Tract-non-nested.png","medium-width":277,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Census-Tract-non-nested.png","medium_large-width":768,"medium_large-height":723,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Census-Tract-non-nested.png","large-width":784,"large-height":738,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Census-Tract-non-nested.png","1536x1536-width":784,"1536x1536-height":738,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Census-Tract-non-nested.png","2048x2048-width":784,"2048x2048-height":738,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Census-Tract-non-nested-494x465.png","card_image-width":494,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Census-Tract-non-nested.png","wide_image-width":784,"wide_image-height":738}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Census-Tract-non-nested.png"},{"acf_fc_layout":"content","content":"<p><span class=\"TextRun SCXW53106300 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW53106300 BCX0\">Check your boundaries for nesting or non-nesting <\/span><span class=\"NormalTextRun SCXW53106300 BCX0\">fit and<\/span><span class=\"NormalTextRun SCXW53106300 BCX0\"> adjust your approach accordingly. <\/span><span class=\"NormalTextRun CommentStart CommentHighlightPipeRest CommentHighlightRest SCXW53106300 BCX0\"><a href=\"#aggregate\">See this question<\/a> to aggregate with non-nested boundaries<\/span><span class=\"NormalTextRun CommentHighlightPipeRest SCXW53106300 BCX0\">.<\/span><\/span><span class=\"EOP SCXW53106300 BCX0\" data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"aggregate\"><\/a><\/p>\n<h2><strong>I want to aggregate smaller geographies to a larger boundary. What is the best way to do this?<\/strong><\/h2>\n<p><span data-contrast=\"auto\">When aggregating, make sure you are using centroids of your aggregated layers to ensure you capture all census tracts or blocks centroids that fall <\/span><i><span data-contrast=\"auto\">within <\/span><\/i><span data-contrast=\"auto\">your given area of interest. Using boundary layers puts you at risk for double counts, or incorrect estimates if your boundaries barely touch an area of interest.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Use Within() or Contains() in your arcade statements to capture centroids within your area of interest. If you only have boundaries, convert them to centroids in your arcade statement before summarizing.<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1841192,"id":1841192,"title":"Summarize_NoWorkingParent","filename":"Summarize_NoWorkingParent-1.png","filesize":63834,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/12\/Summarize_NoWorkingParent-1.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\/summarize_noworkingparent-2","alt":"Arcade Example: Aggregating smaller geographies to a larger boundary","author":"7121","description":"","caption":"","name":"summarize_noworkingparent-2","status":"inherit","uploaded_to":1757622,"date":"2023-02-16 01:23:46","modified":"2023-02-16 01:23:59","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":954,"height":513,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/12\/Summarize_NoWorkingParent-1-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/12\/Summarize_NoWorkingParent-1.png","medium-width":464,"medium-height":250,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/12\/Summarize_NoWorkingParent-1.png","medium_large-width":768,"medium_large-height":413,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/12\/Summarize_NoWorkingParent-1.png","large-width":954,"large-height":513,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/12\/Summarize_NoWorkingParent-1.png","1536x1536-width":954,"1536x1536-height":513,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/12\/Summarize_NoWorkingParent-1.png","2048x2048-width":954,"2048x2048-height":513,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/12\/Summarize_NoWorkingParent-1-826x444.png","card_image-width":826,"card_image-height":444,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/12\/Summarize_NoWorkingParent-1.png","wide_image-width":954,"wide_image-height":513}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.arcgis.com\/apps\/mapviewer\/index.html?webmap=ba1dd52b501c4c82a24e02b5f95916df"},{"acf_fc_layout":"content","content":"<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"exact\"><\/a><\/p>\n<h2><strong>Instead of aggregating, I want exact data, but I can&#8217;t find it in Living Atlas. Where can I find these?<\/strong><\/h2>\n<p><span class=\"TextRun SCXW226187083 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW226187083 BCX0\">If you find yourself aggregating up to approximate <\/span><span class=\"NormalTextRun SCXW226187083 BCX0\">school districts, places, metro areas, or other geography levels that Census publishes estimates for, it&#8217;s best practice to use the official estimates<\/span><span class=\"NormalTextRun SCXW226187083 BCX0\"> available on data.census.gov<\/span><span class=\"NormalTextRun SCXW226187083 BCX0\"> rather than to aggregate up and approximate them.<\/span><span class=\"NormalTextRun SCXW226187083 BCX0\"> These official estimates will <\/span><span class=\"NormalTextRun SCXW226187083 BCX0\">not only be <\/span><span class=\"NormalTextRun SCXW226187083 BCX0\">true to the boundaries, <\/span><span class=\"NormalTextRun ContextualSpellingAndGrammarErrorV2Themed SCXW226187083 BCX0\">they<\/span><span class=\"NormalTextRun SCXW226187083 BCX0\"> will also <\/span><span class=\"NormalTextRun SCXW226187083 BCX0\">have smaller margins of error <\/span><span class=\"NormalTextRun SCXW226187083 BCX0\">since <\/span><span class=\"NormalTextRun SCXW226187083 BCX0\">Census <\/span><span class=\"NormalTextRun AdvancedProofingIssueV2Themed SCXW226187083 BCX0\">actually calculate<\/span><span class=\"NormalTextRun AdvancedProofingIssueV2Themed SCXW226187083 BCX0\">s<\/span><span class=\"NormalTextRun SCXW226187083 BCX0\"> these<\/span><span class=\"NormalTextRun SCXW226187083 BCX0\"> using each response<\/span><span class=\"NormalTextRun SCXW226187083 BCX0\">, rather than aggregating up from estimates for tracts or block groups.<\/span><\/span><\/p>\n<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"bias\"><\/a><\/p>\n<h2><strong>How do I avoid bias in my data?<\/strong><\/h2>\n<p><span data-contrast=\"auto\">You can only limit bias, you can never eliminate it completely. Pay attention to the variables you are choosing to drive your analysis. Are you selecting only those variables that will falsely inflate numbers or those that will support your hypothesis? Are you looking for answers you expect or hope to find when interpreting your analysis? If so, you could be adding bias (whether intentionally or unintentionally) to your work.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">If you expect to discover certain results when analyzing your data, then you will find specific examples to prove those expected results. You may end up emphasizing certain data that supports your perceived results, or mask data that negates your perceived results. Choosing certain variables that you know will support your hypothesis skews your outcome to work positively in your favor. All of this can happen without you realizing you\u2019re doing it, making it crucial to pay attention to your decision making.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Keep an open, exploration-based mindset when interpreting your data and try to discover patterns rather than confirm what you already have guessed. Be aware that bias is present and seek to limit its presence.\u00a0<\/span><\/p>\n<p><a href=\"#menu\">Back to top of blog<\/a><br \/>\n<a name=\"enterprise\"><\/a><\/p>\n<h2><strong>I use an Enterprise implementation of ArcGIS behind our organization&#8217;s firewall (aka ArcGIS Enterprise). Do I get the same Living Atlas data at the same release times?<\/strong><\/h2>\n<p><span class=\"NormalTextRun SCXW262622888 BCX0\">ArcGIS Living Atlas content is hosted on ArcGIS Online, but your portal administrator can configure the portal to access a subset of these ArcGIS Living Atlas items. Because you are accessing content outside the portal, the life cycle of that content and the details associated with it are not completely tied to the ArcGIS Enterprise release cycle<\/span><span class=\"NormalTextRun SCXW262622888 BCX0\"> or Living Atlas release cycles<\/span><span class=\"NormalTextRun SCXW262622888 BCX0\">. Each version of ArcGIS Enterprise contains a fixed subset of ArcGIS Living Atlas items that reference content in ArcGIS Online. If the data in a <\/span><span class=\"NormalTextRun ContextualSpellingAndGrammarErrorV2Themed SCXW262622888 BCX0\">specific item changes<\/span><span class=\"NormalTextRun SCXW262622888 BCX0\">, you see those data changes when you access the portal item. However, you will not see changes to the item details, and that includes information about the item&#8217;s life cycle.<\/span><span class=\"NormalTextRun SCXW262622888 BCX0\"> To see the latest changes, including new and updated ArcGIS Living Atlas content when you upgrade the portal.<\/span><\/p>\n<p><a href=\"#menu\">Back to top of blog<\/a><\/p>\n<p>&nbsp;<\/p>\n<h2><strong>Resources<\/strong><\/h2>\n<p><a href=\"https:\/\/acs-hosted-feature-layers-faq-esri.hub.arcgis.com\/\" target=\"_blank\" rel=\"noopener\"><strong>American Community Survey Hosted Feature Layers FAQ<\/strong><\/a><\/p>\n<p><a href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-online\/data-management\/your-arcade-questions-answered\/\" target=\"_blank\" rel=\"noopener\"><strong>Your Arcade Questions Answered &#8211; FAQ Blog<\/strong><\/a><\/p>\n<p><a href=\"https:\/\/doc.arcgis.com\/en\/esri-demographics\/latest\/reference\/essential-vocabulary.htm\" target=\"_blank\" rel=\"noopener\"><strong>Esri Demographics Glossary of Essential Vocabulary<\/strong><\/a><\/p>\n<p><strong><a href=\"https:\/\/doc.arcgis.com\/en\/esri-demographics\/latest\/reference\/faq.htm\" target=\"_blank\" rel=\"noopener\">Esri Demographics FAQ<\/a><\/strong><\/p>\n<p>&nbsp;<\/p>\n<p><em>This blog post was updated on 2\/15\/23 in order to show a screenshot of the new Arcade Editor in the question: I want to aggregated smaller geographies to a larger boundary. What is the best way to do this?<\/em><\/p>\n"}],"related_articles":[{"ID":72941,"post_author":"6461","post_date":"2016-07-19 11:13:07","post_date_gmt":"2016-07-19 11:13:07","post_content":"","post_title":"Add Demographics to Your Datasets (Fast!)","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"add-demographics-to-your-datasets-fast","to_ping":"","pinged":"","post_modified":"2020-05-20 14:29:22","post_modified_gmt":"2020-05-20 21:29:22","post_content_filtered":"","post_parent":0,"guid":"http:\/\/www.esri.com\/arcgis-blog\/products\/product\/uncategorized\/add-demographics-to-your-datasets-fast\/","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":82731,"post_author":"7391","post_date":"2018-02-14 09:12:07","post_date_gmt":"2018-02-14 09:12:07","post_content":"","post_title":"Demographics: Understanding Populations","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"demographics-understanding-populations","to_ping":"","pinged":"","post_modified":"2018-05-09 17:41:50","post_modified_gmt":"2018-05-09 17:41:50","post_content_filtered":"","post_parent":0,"guid":"http:\/\/www.esri.com\/arcgis-blog\/products\/product\/uncategorized\/demographics-understanding-populations\/","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":1732812,"post_author":"78361","post_date":"2026-01-05 16:00:17","post_date_gmt":"2026-01-06 00:00:17","post_content":"","post_title":"Got five minutes? Get to know Esri Updated Demographics","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"five-minutes-esri-updated-demographics","to_ping":"","pinged":"","post_modified":"2026-01-26 19:11:51","post_modified_gmt":"2026-01-27 03:11:51","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&#038;p=1732812","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":686682,"post_author":"6461","post_date":"2019-12-20 12:15:29","post_date_gmt":"2019-12-20 20:15:29","post_content":"","post_title":"Access the Newest American Community Survey (ACS) Data in Minutes","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"access-the-newest-american-community-survey-acs-data-in-minutes","to_ping":"","pinged":"","post_modified":"2021-10-27 09:46:35","post_modified_gmt":"2021-10-27 16:46:35","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&#038;p=686682","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":361371,"post_author":"7121","post_date":"2018-12-11 05:00:22","post_date_gmt":"2018-12-11 13:00:22","post_content":"","post_title":"Mapping American Community Survey (ACS) Data Just Got Easier","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"mapping-american-community-survey-acs-data-just-got-easier","to_ping":"","pinged":"","post_modified":"2021-11-19 11:31:08","post_modified_gmt":"2021-11-19 19:31:08","post_content_filtered":"","post_parent":0,"guid":"http:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&#038;p=361371","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"0","filter":"raw"}],"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/Card.jpg","wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/PercentHispanic.png"},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v25.9 (Yoast SEO v25.9) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Your Demographic Questions Answered<\/title>\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.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Your Demographic Questions Answered\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\" \/>\n<meta property=\"og:site_name\" content=\"ArcGIS Blog\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/esrigis\/\" \/>\n<meta property=\"article:modified_time\" content=\"2024-06-13T23:58:31+00:00\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:site\" content=\"@ESRI\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"43 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":[\"Article\",\"BlogPosting\"],\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\"},\"author\":{\"name\":\"Summers Cleary\",\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/#\/schema\/person\/85ec876f0bed3c3b9142a8d71578af68\"},\"headline\":\"Your Demographic Questions Answered\",\"datePublished\":\"2022-12-06T17:30:19+00:00\",\"dateModified\":\"2024-06-13T23:58:31+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\"},\"wordCount\":4,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/#organization\"},\"keywords\":[\"Business Analyst\",\"demographics\",\"infographics\",\"Living Atlas\"],\"articleSection\":[\"Mapping\"],\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\",\"url\":\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\",\"name\":\"Your Demographic Questions Answered\",\"isPartOf\":{\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/#website\"},\"datePublished\":\"2022-12-06T17:30:19+00:00\",\"dateModified\":\"2024-06-13T23:58:31+00:00\",\"breadcrumb\":{\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/www.esri.com\/arcgis-blog\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Your Demographic Questions Answered\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/#website\",\"url\":\"https:\/\/www.esri.com\/arcgis-blog\/\",\"name\":\"ArcGIS Blog\",\"description\":\"Get insider info from Esri product teams\",\"publisher\":{\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/www.esri.com\/arcgis-blog\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"},{\"@type\":\"Organization\",\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/#organization\",\"name\":\"Esri\",\"url\":\"https:\/\/www.esri.com\/arcgis-blog\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/#\/schema\/logo\/image\/\",\"url\":\"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/04\/Esri.png\",\"contentUrl\":\"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/04\/Esri.png\",\"width\":400,\"height\":400,\"caption\":\"Esri\"},\"image\":{\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/#\/schema\/logo\/image\/\"},\"sameAs\":[\"https:\/\/www.facebook.com\/esrigis\/\",\"https:\/\/x.com\/ESRI\",\"https:\/\/www.linkedin.com\/company\/5311\/\"]},{\"@type\":\"Person\",\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/#\/schema\/person\/85ec876f0bed3c3b9142a8d71578af68\",\"name\":\"Summers Cleary\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/12\/Headshot-213x200.jpg\",\"contentUrl\":\"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/12\/Headshot-213x200.jpg\",\"caption\":\"Summers Cleary\"},\"description\":\"(she\/her\/hers) Summers is a Product Engineer on ArcGIS Living Atlas' Policy Map team. She works to create maps and stories that reveal opportunities to intervene, particularly focused on the intersection of conservation, natural resources, and Public Policy.\",\"url\":\"https:\/\/www.esri.com\/arcgis-blog\/author\/scleary\"}]}<\/script>\n<!-- \/ Yoast SEO Premium plugin. -->","yoast_head_json":{"title":"Your Demographic Questions Answered","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq","og_locale":"en_US","og_type":"article","og_title":"Your Demographic Questions Answered","og_url":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq","og_site_name":"ArcGIS Blog","article_publisher":"https:\/\/www.facebook.com\/esrigis\/","article_modified_time":"2024-06-13T23:58:31+00:00","twitter_card":"summary_large_image","twitter_site":"@ESRI","twitter_misc":{"Est. reading time":"43 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":["Article","BlogPosting"],"@id":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq#article","isPartOf":{"@id":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq"},"author":{"name":"Summers Cleary","@id":"https:\/\/www.esri.com\/arcgis-blog\/#\/schema\/person\/85ec876f0bed3c3b9142a8d71578af68"},"headline":"Your Demographic Questions Answered","datePublished":"2022-12-06T17:30:19+00:00","dateModified":"2024-06-13T23:58:31+00:00","mainEntityOfPage":{"@id":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq"},"wordCount":4,"commentCount":0,"publisher":{"@id":"https:\/\/www.esri.com\/arcgis-blog\/#organization"},"keywords":["Business Analyst","demographics","infographics","Living Atlas"],"articleSection":["Mapping"],"inLanguage":"en-US","potentialAction":[{"@type":"CommentAction","name":"Comment","target":["https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq#respond"]}]},{"@type":"WebPage","@id":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq","url":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq","name":"Your Demographic Questions Answered","isPartOf":{"@id":"https:\/\/www.esri.com\/arcgis-blog\/#website"},"datePublished":"2022-12-06T17:30:19+00:00","dateModified":"2024-06-13T23:58:31+00:00","breadcrumb":{"@id":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/www.esri.com\/arcgis-blog\/"},{"@type":"ListItem","position":2,"name":"Your Demographic Questions Answered"}]},{"@type":"WebSite","@id":"https:\/\/www.esri.com\/arcgis-blog\/#website","url":"https:\/\/www.esri.com\/arcgis-blog\/","name":"ArcGIS Blog","description":"Get insider info from Esri product teams","publisher":{"@id":"https:\/\/www.esri.com\/arcgis-blog\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.esri.com\/arcgis-blog\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/www.esri.com\/arcgis-blog\/#organization","name":"Esri","url":"https:\/\/www.esri.com\/arcgis-blog\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.esri.com\/arcgis-blog\/#\/schema\/logo\/image\/","url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/04\/Esri.png","contentUrl":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/04\/Esri.png","width":400,"height":400,"caption":"Esri"},"image":{"@id":"https:\/\/www.esri.com\/arcgis-blog\/#\/schema\/logo\/image\/"},"sameAs":["https:\/\/www.facebook.com\/esrigis\/","https:\/\/x.com\/ESRI","https:\/\/www.linkedin.com\/company\/5311\/"]},{"@type":"Person","@id":"https:\/\/www.esri.com\/arcgis-blog\/#\/schema\/person\/85ec876f0bed3c3b9142a8d71578af68","name":"Summers Cleary","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.esri.com\/arcgis-blog\/#\/schema\/person\/image\/","url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/12\/Headshot-213x200.jpg","contentUrl":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/12\/Headshot-213x200.jpg","caption":"Summers Cleary"},"description":"(she\/her\/hers) Summers is a Product Engineer on ArcGIS Living Atlas' Policy Map team. She works to create maps and stories that reveal opportunities to intervene, particularly focused on the intersection of conservation, natural resources, and Public Policy.","url":"https:\/\/www.esri.com\/arcgis-blog\/author\/scleary"}]}},"text_date":"December 6, 2022","author_name":"Multiple Authors","author_page":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/best-practices-for-mapping-demographics-within-arcgis-faq","custom_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/11\/PercentHispanic.png","primary_product":"ArcGIS Living Atlas","tag_data":[{"term_id":112192,"name":"Business Analyst","slug":"business-analyst","term_group":0,"term_taxonomy_id":112192,"taxonomy":"post_tag","description":"","parent":0,"count":59,"filter":"raw"},{"term_id":24571,"name":"demographics","slug":"demographics","term_group":0,"term_taxonomy_id":24571,"taxonomy":"post_tag","description":"","parent":0,"count":142,"filter":"raw"},{"term_id":33021,"name":"infographics","slug":"infographics","term_group":0,"term_taxonomy_id":33021,"taxonomy":"post_tag","description":"","parent":0,"count":56,"filter":"raw"},{"term_id":268131,"name":"Living Atlas","slug":"living-atlas","term_group":0,"term_taxonomy_id":268131,"taxonomy":"post_tag","description":"","parent":0,"count":89,"filter":"raw"}],"category_data":[{"term_id":22941,"name":"Mapping","slug":"mapping","term_group":0,"term_taxonomy_id":22941,"taxonomy":"category","description":"","parent":0,"count":2690,"filter":"raw"}],"product_data":[{"term_id":36711,"name":"ArcGIS Business Analyst","slug":"bus-analyst","term_group":0,"term_taxonomy_id":36711,"taxonomy":"product","description":"","parent":36591,"count":426,"filter":"raw"},{"term_id":36581,"name":"ArcGIS Living Atlas","slug":"arcgis-living-atlas","term_group":0,"term_taxonomy_id":36581,"taxonomy":"product","description":"","parent":0,"count":1171,"filter":"raw"},{"term_id":36551,"name":"ArcGIS Online","slug":"arcgis-online","term_group":0,"term_taxonomy_id":36551,"taxonomy":"product","description":"","parent":0,"count":2427,"filter":"raw"},{"term_id":36561,"name":"ArcGIS Pro","slug":"arcgis-pro","term_group":0,"term_taxonomy_id":36561,"taxonomy":"product","description":"","parent":0,"count":2037,"filter":"raw"},{"term_id":37011,"name":"Esri Demographics","slug":"esri-demographics","term_group":0,"term_taxonomy_id":37011,"taxonomy":"product","description":"","parent":36981,"count":257,"filter":"raw"}],"primary_product_link":"https:\/\/www.esri.com\/arcgis-blog\/?s=#&products=arcgis-living-atlas","_links":{"self":[{"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/blog\/1757622","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/blog"}],"about":[{"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/types\/blog"}],"author":[{"embeddable":true,"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/users\/318562"}],"replies":[{"embeddable":true,"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/comments?post=1757622"}],"version-history":[{"count":0,"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/blog\/1757622\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/media?parent=1757622"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/categories?post=1757622"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/tags?post=1757622"},{"taxonomy":"industry","embeddable":true,"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/industry?post=1757622"},{"taxonomy":"product","embeddable":true,"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/product?post=1757622"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}