{"id":1387892,"date":"2021-12-10T03:00:35","date_gmt":"2021-12-10T11:00:35","guid":{"rendered":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=1387892"},"modified":"2021-12-14T14:31:44","modified_gmt":"2021-12-14T22:31:44","slug":"python-api-geoenrichment-introspection","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/bus-analyst\/business\/python-api-geoenrichment-introspection","title":{"rendered":"ArcGIS Business Analyst in the ArcGIS API for Python!"},"author":14081,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"_searchwp_excluded":""},"categories":[23341,37171,738191],"tags":[31601],"industry":[],"product":[36841,36711,36561],"class_list":["post-1387892","blog","type-blog","status-publish","format-standard","hentry","category-analytics","category-business","category-developers","tag-data-science","product-api-python","product-bus-analyst","product-arcgis-pro"],"acf":{"short_description":"Discovering available Business Analyst countries and variables is now possible with Python","flexible_content":[{"acf_fc_layout":"content","content":"

This article is the second blog of a series of dedicated posts highlighting enhancements that were launched as a part of the ArcGIS Business Analyst Pro\u2019s November 2021<\/a>release.<\/em><\/p>\n

ArcGIS Business Analyst<\/a> is a product suite that provides access to industry-leading data, mapping, and analysis workflows to help organizations make data-based decisions. ArcGIS API for Python<\/a> can be used to automate or process big data with ArcGIS Pro and with Esri\u2019s cloud services such as data geoenrichment, geocoding, and other workflows. With thousands of global variables<\/a> available for users of ArcGIS Business Analyst products, discovering variables available for geoenrichment is an important capability.<\/p>\n

In this blog article, I will explain how the recent ArcGIS Business Analyst Pro\u2019s November release\u2019s enhancement allows users to easily find, sort, and use geoenrichment data<\/em><\/strong>\u2014whether the Business Analyst data is used via cloud data through ArcGIS Online or ArcGIS Business Analyst Enterprise or locally installed datasets–through ArcGIS API for Python.<\/p>\n

With ArcGIS API for Python (ver. 1.9.1) December 2021 release, it is now possible to discover demographic data available via ArcGIS Online services and a local data source. For those who are not familiar with ArcGIS Business Analyst data, depending on the product bundle purchased, it includes data accessed through cloud such as Online data and\/or downloadable, local data.<\/p>\n

Searching Local Data<\/h2>\n

When searching for downloaded, local Business Analyst data through ArcGIS API for Python, results are returned as a Pandas data frame, enabling filtering and searching to easily identify only variables needed for analysis. This capability enables and dramatically streamlines scripted demographic analysis and data science workflows.<\/p>\n

 <\/p>\n

 <\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1388582,"id":1388582,"title":"Python API Country Introspection","filename":"Picture1.png","filesize":26053,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture1.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/bus-analyst\/business\/python-api-geoenrichment-introspection\/picture1-20","alt":"Python API Country Introspection","author":"14081","description":"Python API Country Introspection","caption":"Python API Country Introspection","name":"picture1-20","status":"inherit","uploaded_to":1387892,"date":"2021-11-04 16:41:44","modified":"2021-11-04 16:42:26","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":326,"height":160,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture1-213x160.png","thumbnail-width":213,"thumbnail-height":160,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture1.png","medium-width":326,"medium-height":160,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture1.png","medium_large-width":326,"medium_large-height":160,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture1.png","large-width":326,"large-height":160,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture1.png","1536x1536-width":326,"1536x1536-height":160,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture1.png","2048x2048-width":326,"2048x2048-height":160,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture1.png","card_image-width":326,"card_image-height":160,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture1.png","wide_image-width":326,"wide_image-height":160}},"image_position":"left-center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

Searching Online Data<\/h2>\n

However, if a GIS object instance is created to connect to a remote data source such as Business Analyst data accessed through ArcGIS Online, all globally available countries are returned\u2014a total of over 150 countries(!).<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1388592,"id":1388592,"title":"ArcGIS Online Country Introspection using the Python API","filename":"Picture2.png","filesize":70044,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture2.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/bus-analyst\/business\/python-api-geoenrichment-introspection\/picture2-11","alt":"ArcGIS Online Country Introspection using the Python API","author":"14081","description":"ArcGIS Online Country Introspection using the Python API","caption":"ArcGIS Online Country Introspection using the Python API","name":"picture2-11","status":"inherit","uploaded_to":1387892,"date":"2021-11-04 16:43:34","modified":"2021-11-04 16:44:04","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":504,"height":216,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture2-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture2.png","medium-width":464,"medium-height":199,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture2.png","medium_large-width":504,"medium_large-height":216,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture2.png","large-width":504,"large-height":216,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture2.png","1536x1536-width":504,"1536x1536-height":216,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture2.png","2048x2048-width":504,"2048x2048-height":216,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture2.png","card_image-width":504,"card_image-height":216,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture2.png","wide_image-width":504,"wide_image-height":216}},"image_position":"left-center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

Enhancement Makes Search Easier<\/h2>\n

To make it easier to view metadata and filter the available countries,\u00a0get_countries<\/em><\/a>\u00a0can now return a Pandas data frame by passing\u00a0True<\/em>\u00a0into the new\u00a0as_df<\/em>\u00a0parameter. It\u2019s also much faster!<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1388642,"id":1388642,"title":"Python API Country Introspection Returning a Data Frame","filename":"Picture3.png","filesize":90496,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture3.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/bus-analyst\/business\/python-api-geoenrichment-introspection\/picture3-11","alt":"Python API Country Introspection Returning a Data Frame","author":"14081","description":"Python API Country Introspection Returning a Data Frame","caption":"Python API Country Introspection Returning a Data Frame","name":"picture3-11","status":"inherit","uploaded_to":1387892,"date":"2021-11-04 16:46:35","modified":"2021-11-04 16:47:27","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":732,"height":428,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture3-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture3.png","medium-width":446,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture3.png","medium_large-width":732,"medium_large-height":428,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture3.png","large-width":732,"large-height":428,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture3.png","1536x1536-width":732,"1536x1536-height":428,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture3.png","2048x2048-width":732,"2048x2048-height":428,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture3.png","card_image-width":732,"card_image-height":428,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture3.png","wide_image-width":732,"wide_image-height":428}},"image_position":"left-center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

New Enhancement for Using Local Data<\/h2>\n

When working with downloaded, local data, you also now can search not only the most current year, but any previous year\u2019s data as well. This is particularly useful when you need to run a model developed against a specific year of data.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1388702,"id":1388702,"title":"Python API County Introspection for Previous Years","filename":"Picture4.png","filesize":53304,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture4.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/bus-analyst\/business\/python-api-geoenrichment-introspection\/picture4-9","alt":"Python API County Introspection for Previous Years","author":"14081","description":"Python API County Introspection for Previous Years","caption":"Python API County Introspection for Previous Years","name":"picture4-9","status":"inherit","uploaded_to":1387892,"date":"2021-11-04 16:54:27","modified":"2021-11-04 16:55:02","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":488,"height":346,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture4-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture4.png","medium-width":368,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture4.png","medium_large-width":488,"medium_large-height":346,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture4.png","large-width":488,"large-height":346,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture4.png","1536x1536-width":488,"1536x1536-height":346,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture4.png","2048x2048-width":488,"2048x2048-height":346,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture4.png","card_image-width":488,"card_image-height":346,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture4.png","wide_image-width":488,"wide_image-height":346}},"image_position":"left-center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

Enrich Variable Discovery<\/h2>\n

Thousands of variables are available for geoenrichment, so the ability to filter and search for variables is important. Fortunately, geoenrichment variables can be returned as a Pandas data frame for filtering and searching using the\u00a0enrich_variables<\/em><\/a>\u00a0property of an instantiated\u00a0Country<\/em><\/a>\u00a0object.\u00a0Country<\/em>\u00a0objects are instantiated using the three-letter ISO3 identifier. Similar to searching for countries, the variables are returned as a data frame, searching, and filtering to identify a specific set of variables for subsequent geoenrichment is possible.<\/p>\n

In the following example, I am interested in retrieving Esri-curated variables describing general socioeconomic characteristics. In general, what I am looking for are quantitative demographic variables for the current year. The first step is creating a\u00a0Country<\/em>\u00a0object referencing the United States.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1388712,"id":1388712,"title":"Country Object Instance Creation","filename":"Picture5.png","filesize":51968,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture5.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/bus-analyst\/business\/python-api-geoenrichment-introspection\/picture5-8","alt":"Country Object Instance Creation","author":"14081","description":"Country Object Instance Creation","caption":"Country Object Instance Creation","name":"picture5-8","status":"inherit","uploaded_to":1387892,"date":"2021-11-04 16:57:14","modified":"2021-11-04 16:57:34","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":488,"height":346,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture5-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture5.png","medium-width":368,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture5.png","medium_large-width":488,"medium_large-height":346,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture5.png","large-width":488,"large-height":346,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture5.png","1536x1536-width":488,"1536x1536-height":346,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture5.png","2048x2048-width":488,"2048x2048-height":346,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture5.png","card_image-width":488,"card_image-height":346,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture5.png","wide_image-width":488,"wide_image-height":346}},"image_position":"left-center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

Once this step has been completed, I can retrieve a subset of variables for follow on analysis fitting my criteria using filtering by naming conventions. As shown, it is useful to take advantage of the regular expressions for filtering.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1388722,"id":1388722,"title":"Filtering Enrichment Variables Using Regular Expressions","filename":"Picture6.png","filesize":279023,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture6.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/bus-analyst\/business\/python-api-geoenrichment-introspection\/picture6-5","alt":"Filtering Enrichment Variables Using Regular Expressions","author":"14081","description":"Filtering Enrichment Variables Using Regular Expressions","caption":"Filtering Enrichment Variables Using Regular Expressions","name":"picture6-5","status":"inherit","uploaded_to":1387892,"date":"2021-11-04 17:02:41","modified":"2021-11-04 17:03:11","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":792,"height":814,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture6-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture6.png","medium-width":254,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture6.png","medium_large-width":768,"medium_large-height":789,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture6.png","large-width":792,"large-height":814,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture6.png","1536x1536-width":792,"1536x1536-height":814,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture6.png","2048x2048-width":792,"2048x2048-height":814,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture6-452x465.png","card_image-width":452,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture6.png","wide_image-width":792,"wide_image-height":814}},"image_position":"left-center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

You may have also noticed I saved the output to a temporary feature class in memory. This is because I frequently immediately convert it to a Pandas data frame for subsequent analysis\u2014taking advantage of the function chaining abilities of Pandas data frames to quickly clean up the data for follow on analysis.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1388752,"id":1388752,"title":"Setting Country Source and Using Enrich Layer","filename":"Picture7.png","filesize":134622,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture7.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/bus-analyst\/business\/python-api-geoenrichment-introspection\/picture7-7","alt":"Setting Country Source and Using Enrich Layer","author":"14081","description":"Setting Country Source and Using Enrich Layer","caption":"Setting Country Source and Using Enrich Layer","name":"picture7-7","status":"inherit","uploaded_to":1387892,"date":"2021-11-04 17:14:32","modified":"2021-11-04 17:15:03","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":732,"height":482,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture7-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture7.png","medium-width":396,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture7.png","medium_large-width":732,"medium_large-height":482,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture7.png","large-width":732,"large-height":482,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture7.png","1536x1536-width":732,"1536x1536-height":482,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture7.png","2048x2048-width":732,"2048x2048-height":482,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture7-706x465.png","card_image-width":706,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture7.png","wide_image-width":732,"wide_image-height":482}},"image_position":"left-center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

You may have also noticed I saved the output to a temporary feature class in memory. This is because I frequently immediately convert it to a Pandas data frame for subsequent analysis\u2014taking advantage of the function chaining abilities of Pandas data frames to quickly clean up the data for follow on analysis.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1388762,"id":1388762,"title":"Converting Memory Feature Class to a Pandas Data Frame","filename":"Picture8.png","filesize":104492,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture8.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/bus-analyst\/business\/python-api-geoenrichment-introspection\/picture8-6","alt":"Converting Memory Feature Class to a Pandas Data Frame","author":"14081","description":"Converting Memory Feature Class to a Pandas Data Frame","caption":"Converting Memory Feature Class to a Pandas Data Frame","name":"picture8-6","status":"inherit","uploaded_to":1387892,"date":"2021-11-04 17:16:10","modified":"2021-11-04 17:16:51","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":936,"height":498,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture8-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture8.png","medium-width":464,"medium-height":247,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture8.png","medium_large-width":768,"medium_large-height":409,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture8.png","large-width":936,"large-height":498,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture8.png","1536x1536-width":936,"1536x1536-height":498,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture8.png","2048x2048-width":936,"2048x2048-height":498,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture8-826x439.png","card_image-width":826,"card_image-height":439,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/11\/Picture8.png","wide_image-width":936,"wide_image-height":498}},"image_position":"left-center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

While only one example, it illustrates the ability to discover and filter through the staggering number of geoenrichment variables available. This example, along with others, is available in a\u00a0public repository of examples<\/a>\u00a0you can view and use\u00a0in your own work.<\/p>\n"},{"acf_fc_layout":"content","content":"

Additional Resources<\/h2>\n

Please visit the following links for more information regarding ArcGIS Busines Analyst:<\/p>\n