{"id":7718,"date":"2023-11-09T09:15:16","date_gmt":"2023-11-09T07:15:16","guid":{"rendered":"https:\/\/www.geopostcodes.com\/en-GB\/?p=7718"},"modified":"2026-04-01T07:01:01","modified_gmt":"2026-04-01T07:01:01","slug":"create-zip-code-map-tableau","status":"publish","type":"post","link":"https:\/\/www.geopostcodes.com\/en-GB\/blog\/create-zip-code-map-tableau\/","title":{"rendered":"Create a Postcode Map in Tableau: A Step-by-Step Guide"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\">Key takeaways<\/h2>\n\n\n\n<div style=\"height:30px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Tableau enables postcode mapping using built-in geographic data or custom imported polygons.<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Built-in Tableau geographic data covers limited countries with occasional accuracy and currency issues.<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Importing custom polygons gives complete control over map data quality and coverage.<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Step-by-step examples demonstrate both mapping approaches for business intelligence visualization needs.<\/li>\n<\/ul>\n\n\n\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Introduction<\/strong><\/h2>\n\n\n\n<div style=\"height:30px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>Tableau is a popular Business Intelligence tool trusted by organizations for dashboard creation. Its advantages include ease of use, shareable results, and compatibility with diverse data formats.<\/p>\n\n\n\n<p>Though not originally for geographic data, it now offers mapping capabilities for monitoring performance by area, identifying growth zones, or reassessing <a target=\"_blank\" rel=\"noreferrer noopener\" href=\"https:\/\/www.geopostcodes.com\/en-GB\/blog\/comparing-sales-territory-mapping-software-options\/\">territory divisions<\/a>. Postcodes provide convenient mapping, easily linking to <a target=\"_blank\" rel=\"noreferrer noopener\" href=\"https:\/\/www.geopostcodes.com\/en-GB\/blog\/international-address-data\/\">address data<\/a> while offering aggregated views for analysis.<br><br>This article shows two ways to create postcode maps in Tableau: using integrated geographic sources or importing <a target=\"_blank\" rel=\"noreferrer noopener\" href=\"https:\/\/www.geopostcodes.com\/en-GB\/blog\/postal-code-polygon-database\/\">custom polygons<\/a> for complete control. Step-by-step examples illustrate both approaches.<\/p>\n\n\n\n<p class=\"has-background\" style=\"background-color:#d7efff\">\ud83d\udca1 Use accurate data to create a postcode map. We offer the most comprehensive and up-to-date international postcode data for enterprises.&nbsp;<a href=\"https:\/\/public.geopostcodes.com\/portal-signup\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>Browse GeoPostcodes datasets for free and download a sample here.<\/strong><\/a><\/p>\n\n\n\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Using Tableau-embedded geographic data sources<\/strong><\/h2>\n\n\n\n<div style=\"height:30px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>Tableau includes, by default, geographic sources from several providers (including Mapbox, OpenStreetMap, and Geonames).<\/p>\n\n\n\n<p>Similarly to <a href=\"https:\/\/www.geopostcodes.com\/en-GB\/blog\/postcode-map-power-bi\/\">PowerBI<\/a>, Tableau matches data fields to pre-defined internal levels named Country\/Region, State\/Province, County, and City. In addition, it conveniently allows for mapping through widespread international geocode systems such as FIPS, ISO3166-1, and NUTS. For the USA, possibilities are extended to phone area codes, congressional districts, and CBSA\/MSA (Core-Based Statistical Areas). Finally, Tableau can link to airport codes (IATA and ICAO).<\/p>\n\n\n\n<p>The most important for this article is that Tableau also provides<a href=\"https:\/\/www.geopostcodes.com\/en-GB\/blog\/comparing-postcode-mapping-tools\/\" target=\"_blank\" rel=\"noreferrer noopener\"> <\/a><a href=\"https:\/\/www.geopostcodes.com\/en-GB\/blog\/comparing-postcode-mapping-tools\/\" target=\"_blank\" rel=\"noreferrer noopener\">postcode mapping<\/a> for 56 countries.<\/p>\n\n\n\n<p>The list of available Map layers for each country is available <a href=\"https:\/\/www.tableau.com\/mapdata#data\" target=\"_blank\" rel=\"noreferrer noopener\">here<\/a>.<\/p>\n\n\n\n<p>Tableau also offers functionality to manually match locations that would not be automatically linked to embedded data, for instance, in case of spelling differences or ambiguities (several entities sharing the same name or postcode may not be formatted the same way).<\/p>\n\n\n\n<p>Finally, you can create groups of objects. Postcodes are frequently following a hierarchical model. So, you can create groups by postcode prefixes if you want to aggregate your data at a higher level.<\/p>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">Step-by-step example: total income per postcode in Florida<\/h3>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>Let\u2019s see how we can create a map of the total income per postcode in Florida. You can download the data from GeoPostcodes&#8217; <a href=\"https:\/\/github.com\/GeoPostcodes\" target=\"_blank\" rel=\"noreferrer noopener\">Github directory<\/a>. It contains an extract of the 2020 tax report data published by the US <a href=\"https:\/\/www.irs.gov\/statistics\/soi-tax-stats-individual-income-tax-statistics-2020-zip-code-data-soi\" target=\"_blank\" rel=\"noreferrer noopener\">IRS<\/a>, providing the total income per postal code in 2020<\/p>\n\n\n\n<p>Follow these steps to build your map of income per postcode in Florida:<\/p>\n\n\n\n<p>1. To start, open Tableau and create a New dashboard. Then click on \u201cText File\u201d (1) -&gt; and select the file you have just downloaded (2).<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img fetchpriority=\"high\" decoding=\"async\" width=\"986\" height=\"522\" src=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/1-1.webp\" alt=\"Map editor in tableau\" class=\"wp-image-7933\" srcset=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/1-1.webp 986w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/1-1-300x159.webp 300w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/1-1-768x407.webp 768w\" sizes=\"(max-width: 986px) 100vw, 986px\" \/><\/figure>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>2. <span style=\"font-size: 1rem; background-color: var(--ast-global-color-5);\">From the data sources panel, first, make sure the file has been opened with the correct encoding: click on the arrow next to the file name (3), then on \u201cText File Properties\u201d (4). In the \u201cLocale\u201d (5) property, select \u201cEnglish (United States)\u201d (6).<\/span><\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img decoding=\"async\" width=\"985\" height=\"517\" src=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/2.webp\" alt=\"Data sources panel\" class=\"wp-image-7914\" srcset=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/2.webp 985w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/2-300x157.webp 300w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/2-768x403.webp 768w\" sizes=\"(max-width: 985px) 100vw, 985px\" \/><\/figure>\n\n\n\n<figure class=\"wp-block-image size-full\"><img decoding=\"async\" width=\"980\" height=\"516\" src=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/3.webp\" alt=\"Data sources panel 2\" class=\"wp-image-7915\" srcset=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/3.webp 980w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/3-300x158.webp 300w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/3-768x404.webp 768w\" sizes=\"(max-width: 980px) 100vw, 980px\" \/><\/figure>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><span style=\"font-size: 1rem; background-color: var(--ast-global-color-5);\">3. Ensure the Postcode field has the Postcode Geographic role: Click on the icon on top of the postcode column (7) and select \u201cPOSTCODE Code\/Postcode\u201d as Geographic Role.<\/span><\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"962\" height=\"513\" src=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/4.webp\" alt=\"Zip geographic role\" class=\"wp-image-7916\" srcset=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/4.webp 962w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/4-300x160.webp 300w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/4-768x410.webp 768w\" sizes=\"(max-width: 962px) 100vw, 962px\" \/><\/figure>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>4. Go to your Worksheet (8), drag and drop the &#8220;Postcode&#8221; field (9) into the center of the worksheet (&#8220;Drop field here&#8221;).<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"958\" height=\"502\" src=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/5.webp\" alt=\"Worksheet\" class=\"wp-image-7917\" srcset=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/5.webp 958w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/5-300x157.webp 300w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/5-768x402.webp 768w\" sizes=\"(max-width: 958px) 100vw, 958px\" \/><\/figure>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>5. If the Postcodes are not automatically recognized, click on \u201c\u2026 unknown\u201d at the bottom right (10), then \u201cEdit Locations\u201d and make sure the \u201cCountry\/Region\u201d field (11) is set to the USA (12).<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1007\" height=\"501\" src=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/6.webp\" alt=\"Edit locations\" class=\"wp-image-7918\" srcset=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/6.webp 1007w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/6-300x149.webp 300w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/6-768x382.webp 768w\" sizes=\"(max-width: 1007px) 100vw, 1007px\" \/><\/figure>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"968\" height=\"516\" src=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/7.webp\" alt=\"Edit locations 2\" class=\"wp-image-7919\" srcset=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/7.webp 968w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/7-300x160.webp 300w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/7-768x409.webp 768w\" sizes=\"(max-width: 968px) 100vw, 968px\" \/><\/figure>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>6. <span style=\"font-size: 1rem; background-color: var(--ast-global-color-5);\">You should now see the US states with points inside them. To switch to a choropleth (colored polygons) view, click on \u201cShow Me\u201d (13) and select the \u201cMap\u201d type (14).<\/span><\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"986\" height=\"517\" src=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/8.1.webp\" alt=\"US states with points\" class=\"wp-image-7920\" srcset=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/8.1.webp 986w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/8.1-300x157.webp 300w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/8.1-768x403.webp 768w\" sizes=\"(max-width: 986px) 100vw, 986px\" \/><\/figure>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>7. C<span style=\"font-size: 1rem; background-color: var(--ast-global-color-5);\">onvert the \u201cAverage Income\u201d field to a measure: click on the arrow on its right (15) and select \u201cConvert to measure\u201d (16)<\/span>.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1005\" height=\"531\" src=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/9.webp\" alt=\"Convert to measure\" class=\"wp-image-7921\" srcset=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/9.webp 1005w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/9-300x159.webp 300w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/9-768x406.webp 768w\" sizes=\"(max-width: 1005px) 100vw, 1005px\" \/><\/figure>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><span style=\"font-size: 1rem; background-color: var(--ast-global-color-5);\">8. Now drag the \u201cAverage Income\u201d field to the \u201cColour\u201d icon (17)<\/span>.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"987\" height=\"518\" src=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/10.webp\" alt=\"Color field\" class=\"wp-image-7922\" srcset=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/10.webp 987w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/10-300x157.webp 300w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/10-768x403.webp 768w\" sizes=\"(max-width: 987px) 100vw, 987px\" \/><\/figure>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>9. There it is. You have built your map of total income per postcode in Florida. Note that the IRS does not report values for Postcodes with less than 100 returners, while there are a couple of empty zones on the map.<\/p>\n\n\n\n<p>10. The map&#8217;s contrast is not great so far because of the distribution of average incomes (a few outliers with high values, but the vast majority of incomes are within a lower range). To change that, we can color according to the logarithm of the average incomes. Click on the arrow next to \u201cAverage Income\u201d (18), then \u201cCreate\u201d (19) and \u201cCalculated field\u201d (20).<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"980\" height=\"513\" src=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/11.webp\" alt=\"Modify the contrast\" class=\"wp-image-7923\" srcset=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/11.webp 980w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/11-300x157.webp 300w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/11-768x402.webp 768w\" sizes=\"(max-width: 980px) 100vw, 980px\" \/><\/figure>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>11. Rename the field to \u201cLog_income\u201d (21) and enter \u201cLog([Average Income])\u201d as formula (22), then click on ok (23).<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"987\" height=\"520\" src=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/12.webp\" alt=\"Log income formula\" class=\"wp-image-7924\" srcset=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/12.webp 987w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/12-300x158.webp 300w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/12-768x405.webp 768w\" sizes=\"(max-width: 987px) 100vw, 987px\" \/><\/figure>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>12. Drag the \u201cLog_income\u201d field over the \u201cSUM[Average Income]\u201d to replace the coloring variable (24).<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"987\" height=\"518\" src=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/24.webp\" alt=\"Replace coloring variable\" class=\"wp-image-7927\" srcset=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/24.webp 987w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/24-300x157.webp 300w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/24-768x403.webp 768w\" sizes=\"(max-width: 987px) 100vw, 987px\" \/><\/figure>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>13. To improve the displayed tooltip when you hover over the postcode areas, drag the \u201cAverage Income\u201d field to the \u201cTooltip\u201d icon (25).<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"978\" height=\"503\" src=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/25.webp\" alt=\"Tooltip icon\" class=\"wp-image-7928\" srcset=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/25.webp 978w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/25-300x154.webp 300w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/25-768x395.webp 768w\" sizes=\"(max-width: 978px) 100vw, 978px\" \/><\/figure>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>14. Click on the Tooltip icon (26), remove the line for log incomes (27), and, because amounts from the IRS field are in thousands of dollars, add \u201c,000$\u201d after the Average income variable (27).<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"991\" height=\"520\" src=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/26.webp\" alt=\"Average income variable\" class=\"wp-image-7929\" srcset=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/26.webp 991w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/26-300x157.webp 300w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/26-768x403.webp 768w\" sizes=\"(max-width: 991px) 100vw, 991px\" \/><\/figure>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>15. Your map is ready now, with a bit more contrast thanks to the logarithmic coloring and a nice tooltip to show you the average incomes per postcode when you hover each polygon.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"982\" height=\"703\" src=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/27.webp\" alt=\"Final map\" class=\"wp-image-7930\" srcset=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/27.webp 982w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/27-300x215.webp 300w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/27-768x550.webp 768w\" sizes=\"(max-width: 982px) 100vw, 982px\" \/><\/figure>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>As you can see, it was extremely easy to create that map, just using the tabular data (2 fields: POSTCODE and average income) we had downloaded and leveraging Tableau\u2019s embedded geographical data. Unfortunately, setting up your dashboards is not always easy when you want to map data from different countries or at other aggregation levels. Let\u2019s now talk a bit about the <a href=\"https:\/\/www.geopostcodes.com\/en-GB\/blog\/the-7-challenges-of-building-a-standardized-zip-code-database\/\" target=\"_blank\" rel=\"noreferrer noopener\">challenges<\/a> you will face.<\/p>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">The challenges with Tableau\u2019s embedded polygons<\/h3>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>The main difficulties in using the embedded geographic data in Tableau relate to coverage,&nbsp; quality, and lack of control. Here are a few more details, both on the general cases of leveraging geographic mapping directly from Tableau (for administrative divisions or Postcodes) and the specific cases of Postcode mapping:<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>Quality<\/strong>: in several countries, the <a href=\"https:\/\/www.geopostcodes.com\/en-GB\/boundaries-database\/\" target=\"_blank\" rel=\"noreferrer noopener\">administrative boundaries<\/a> are not up-to-date. For example, in Belgium, there is level 3 encoding through the NUTS codes, but these don\u2019t include the changes from 2019. This is shown in Figure Y, where the level 3 subdivisions appear in dark blue, and the missing areas in light blue (Belgium is covered entirely by level 3 subdivisions, but Tableau misses some, as indicated by the 8 \u201cunknown\u201d regions).<\/li>\n<\/ol>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"551\" src=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/pasted-image-0-1024x551.webp\" alt=\"Administrative boundaries map in Tableau\" class=\"wp-image-7931\" srcset=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/pasted-image-0-1024x551.webp 1024w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/pasted-image-0-300x161.webp 300w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/pasted-image-0-768x413.webp 768w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/pasted-image-0-1536x827.webp 1536w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/pasted-image-0.webp 1600w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>For Algeria, Provinces still refer to the 48 Provinces existing before 2019. Since then, there have been 58 Provinces in Algeria, but they are not all available through Tableau. Similarly, in Latvia, Tableau is still referring to the divisions before the administrative reorganization which entered into force in July 2021 (moving from 110 to 43 cities).<\/p>\n\n\n\n<p>For Sweden, Tableau reports 10.006 postal codes available. This is over 500 postal codes short of the country&#8217;s total number of active postal codes. That means 5% of the postal codes you will not be able to display through Tableau, and there are some wrong shapes for the existing ones.<\/p>\n\n\n\n<p>Furthermore, the (simplified) polygons are not perfectly aligned, as shown in the following figure, where 2 US postcodes overlap in one area.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"594\" src=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/2-1024x594-1.webp\" alt=\"Simplified polygons in a map\" class=\"wp-image-7932\" srcset=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/2-1024x594-1.webp 1024w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/2-1024x594-1-300x174.webp 300w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/2-1024x594-1-768x446.webp 768w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>Simplifying shapes makes sense for Tableau&#8217;s typical use cases: high-level maps showing many polygons across large areas. Detailed polygon features would be unnecessary and often invisible at these scales. However, gaps and overlaps between simplified polygons not only reduce map aesthetics but can cause analysis confusion and errors. You can learn how to build an accurate postal code polygon database <a href=\"https:\/\/www.geopostcodes.com\/en-GB\/blog\/postal-code-polygon-database\/\" target=\"_blank\" rel=\"noreferrer noopener\">here<\/a>.<\/p>\n\n\n\n<ol start=\"2\" class=\"wp-block-list\">\n<li><strong>Coverage<\/strong>: <a href=\"https:\/\/www.geopostcodes.com\/en-GB\/boundaries-database\/\" target=\"_blank\" rel=\"noreferrer noopener\">Postal code boundaries<\/a> exist for only 56 countries. Administrative boundaries often lack lower hierarchy levels. France stops at level 2 (departments), missing arrondissements and municipalities. Belgium includes arrondissements but not municipalities. Italy offers just 107 Provinces, lacking more detailed administrative data. For Belgium, Tableau&#8217;s PLACES feature only contains larger towns, omitting smaller localities and villages.<\/li>\n\n\n\n<li><strong>Disambiguation work<\/strong>: Places and administrative divisions often share names with other entities. The USA has 30 counties and 1 Parish named &#8220;Washington.&#8221; Over half of US states have subdivisions named after George Washington. When importing county data, Tableau can&#8217;t determine which specific County you mean. It marks locations as &#8220;unknown&#8221; until you specify the administrative hierarchy. This requires having hierarchy data linked to your original dataset. Similar issues occur with postal codes. Though unique per country (except one case in Cambodia, which Tableau doesn&#8217;t cover), postal codes from different countries may share values. Always include a country field in your data.<\/li>\n\n\n\n<li><strong>Lack of control<\/strong>: You can&#8217;t see what happens behind the scenes. What&#8217;s available? Where&#8217;s it from? Is it accurate and current? What if you need custom groupings? When will underlying data update next? Data updates may break dashboards until you include new keys (like new Provinces).<\/li>\n\n\n\n<li><strong>Expertise needed<\/strong>: as you don\u2019t control what\u2019s available in Tableau, and as it may not be accurate or up-to-date, you can&#8217;t know if what you see are reliable polygons unless you have expertise in the domain. Getting help and even more fixes if you\u2019re questioning the served data is not straightforward.<\/li>\n<\/ol>\n\n\n\n<p>For all those reasons, taking control of the used data is desirable. So you know exactly what is in it (and what\u2019s not) and update it when you can, want, or have to. Luckily, Tableau offers possibilities to use other geographical data sources. Let\u2019s now explore how custom geographical files can be imported into Tableau.<\/p>\n\n\n\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>How to import custom postcode polygons into Tableau<\/strong><\/h2>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">Available file formats<\/h3>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>Tableau can ingest several geographical data formats: Shapefile, geoJSON, KML, MapInfo, topojson. Note, however, that it can\u2019t read the \u201cExtendedData\u201d out of KML files at the time of writing, which hinders linking KML files to other data in the application: you can only leverage the ID field as a key.<\/p>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">Linking to other data<\/h3>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>Linking geographical data to other sources is extremely easy as Tableau offers a relationship\/join interface allowing users to choose which keys should be related to the joined files. Tableau can even perform joins through geographical data (linking datasets based on the relationship between their geometries).<\/p>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Step-by-step example: showing the Population per postal code in South Korea<\/strong><\/h3>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>In this second example, we will join two files: a geographic file that includes the polygons of the postal codes in Sejong City and a CSV file that gives the population per postal code.<\/p>\n\n\n\n<p>1. Download all the data from our <a href=\"https:\/\/github.com\/GeoPostcodes\/blogs\/tree\/main\/creating-zip-maps-in-Tableau\/KR_pop_example\" target=\"_blank\" rel=\"noreferrer noopener\">Github repository<\/a>. It contains the simplified postal boundaries for Busanjin County (GPC-BNDR-PST-VIZ-Busanjin.*) and the population per postcode (KR_Busanjin_pop_per_zip.csv).<\/p>\n\n\n\n<p>2. Upload the 2 files to Tableau. Start a new project and connect to a new data source. Select \u201cspatial file\u201d and then browse your hard drive to select the .shp file you downloaded. Next, click \u201cAdd,\u201d select \u201cText file\u201d and point to the population CSV. Then, drag the \u201cKR_Busanjin_pop_per_zip.csv\u201d file from the left menu towards the right pane (1).<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"977\" height=\"502\" src=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/1.webp\" alt=\"Upload files to tableau\" class=\"wp-image-7934\" srcset=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/1.webp 977w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/1-300x154.webp 300w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/1-768x395.webp 768w\" sizes=\"(max-width: 977px) 100vw, 977px\" \/><\/figure>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>3. Ensure the postcode columns in both files are string data types (2 and 3 for the CSV file). Additionally, check the geographical roles for the Postcodes (and all fields except the geometry) are set to \u201cNone\u201d (4).<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"998\" height=\"523\" src=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/2-1.webp\" alt=\"Check geographical roles for the zips\" class=\"wp-image-7935\" srcset=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/2-1.webp 998w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/2-1-300x157.webp 300w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/2-1-768x402.webp 768w\" sizes=\"(max-width: 998px) 100vw, 998px\" \/><\/figure>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>4. Establish the relationship between the 2 data sources. Click on the link between them (5), then select the key for the first file (6) and choose \u201cPOSTCODE\u201d (7). Repeat the operation for the second file (8), choosing postcode, so your relationship reads \u201cPOSTCODE = POSTCODE.\u201d<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"975\" height=\"507\" src=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/3-1.webp\" alt=\"Establish relationships between sources\" class=\"wp-image-7936\" srcset=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/3-1.webp 975w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/3-1-300x156.webp 300w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/3-1-768x399.webp 768w\" sizes=\"(max-width: 975px) 100vw, 975px\" \/><\/figure>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>5. Access your worksheet (Click \u201cSheet 1\u201d, 9). Drag the Geometry field to the center of the worksheet (10).<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"971\" height=\"500\" src=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/4-1.webp\" alt=\"Access the worksheet\" class=\"wp-image-7937\" srcset=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/4-1.webp 971w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/4-1-300x154.webp 300w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/4-1-768x395.webp 768w\" sizes=\"(max-width: 971px) 100vw, 971px\" \/><\/figure>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>6. Drag the \u201cPOSTCODE\u201d field to the \u201cDetails\u201d icon (11).<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"968\" height=\"501\" src=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/5-1.webp\" alt=\"Drag the zip to details\" class=\"wp-image-7938\" srcset=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/5-1.webp 968w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/5-1-300x155.webp 300w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/5-1-768x397.webp 768w\" sizes=\"(max-width: 968px) 100vw, 968px\" \/><\/figure>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>7. Convert the Pop sum to a decimal number (12-13) and a measure (14), then drag it on the color icon (15).<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"982\" height=\"507\" src=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/6-1.webp\" alt=\"Convert pop up sum to decimal\" class=\"wp-image-7939\" srcset=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/6-1.webp 982w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/6-1-300x155.webp 300w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/6-1-768x397.webp 768w\" sizes=\"(max-width: 982px) 100vw, 982px\" \/><\/figure>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"972\" height=\"507\" src=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/7-1.webp\" alt=\"Convert pop up sum to decimal 2\" class=\"wp-image-7940\" srcset=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/7-1.webp 972w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/7-1-300x156.webp 300w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/7-1-768x401.webp 768w\" sizes=\"(max-width: 972px) 100vw, 972px\" \/><\/figure>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>8. You now have your choropleth map of population per postal code, combining the CSV data with the polygons you have imported through the shape file.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"533\" src=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/8.webp\" alt=\"Final choropleth map\" class=\"wp-image-7941\" srcset=\"https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/8.webp 1024w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/8-300x156.webp 300w, https:\/\/www.geopostcodes.com\/en-GB\/wp-content\/uploads\/2023\/10\/8-768x400.webp 768w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Conclusion<\/strong><\/h2>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>This article showed how easily you can create postcode-based choropleth maps in Tableau.<\/p>\n\n\n\n<p>First, we used embedded Tableau polygons and noted their limitations. Available data has imperfections affecting projects unless you accept limited country coverage and possibly outdated information. Lack of control remains the biggest issue.<\/p>\n\n\n\n<p>Next, we explored importing geographic files into Tableau. Tableau accepts popular file formats and gives full control over joins. This works internationally, despite our simplified examples. You just need consistent input data.<\/p>\n\n\n\n<p>All you need is consistent input data. However, remember Tableau remains a BI tool with display limits. Use aggregations or filters when dashboards slow down. While Tableau excels in many areas, other tools better suit territory mapping.<\/p>\n\n\n\n<p>If importing geographic data appeals to you, you may seek trustworthy geographical data sources.<\/p>\n\n\n\n<p><a href=\"https:\/\/www.geopostcodes.com\/en-GB\/\" target=\"_blank\" rel=\"noreferrer noopener\">GeoPostcodes <\/a>maintains the most accurate<a href=\"https:\/\/www.geopostcodes.com\/en-GB\/postal-zip-code-database\/\" target=\"_blank\" rel=\"noreferrer noopener\"> postal database<\/a> in the world. Our products include <a href=\"https:\/\/www.geopostcodes.com\/en-GB\/boundaries-database\/\" target=\"_blank\" rel=\"noreferrer noopener\">postal and administrative boundaries<\/a> for all countries. Thanks to the internal use of a topological model, we also deliver simplified versions of the polygons, still perfectly matching, like the sample you downloaded for the second exercise.<\/p>\n\n\n\n<p>These are ideal for Tableau choropleth maps. Download our files, explore them, edit if needed, upload to Tableau, and create insightful maps. You control when to update geometries. We will be happy to assist you in finding the best option for your business, so don\u2019t hesitate to <a target=\"_blank\" rel=\"noreferrer noopener\" href=\"https:\/\/public.geopostcodes.com\/request-a-quote\">reach out<\/a>.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">FAQ<\/h2>\n\n\n\n<div id=\"wp-block-themeisle-blocks-accordion-aa5641a4\" class=\"wp-block-themeisle-blocks-accordion exclusive has-light-content-bg is-style-default\">\n<details class=\"wp-block-themeisle-blocks-accordion-item\"><summary class=\"wp-block-themeisle-blocks-accordion-item__title\"><div><strong><strong>Can Tableau map postcodes?<\/strong><\/strong><\/div><\/summary><div class=\"wp-block-themeisle-blocks-accordion-item__content\">\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>Yes, Tableau map postcode functionality lets users visualize regions using built-in geographic roles, making it easy to create, customize, and export maps for insightful spatial analysis.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n<\/div><\/details>\n\n\n\n<details class=\"wp-block-themeisle-blocks-accordion-item\"><summary class=\"wp-block-themeisle-blocks-accordion-item__title\"><div><strong><strong>How to plot Postcode on a map?<\/strong><\/strong><\/div><\/summary><div class=\"wp-block-themeisle-blocks-accordion-item__content\">\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>To create a map visualization in Tableau, drag a geographic dimension (e.g., Country, State, City) to the Rows or Columns shelf and a measure (e.g., Sales, Population) to the Marks card. Tableau will automatically recognize the data as geographic and display a map.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n<\/div><\/details>\n\n\n\n<details class=\"wp-block-themeisle-blocks-accordion-item\"><summary class=\"wp-block-themeisle-blocks-accordion-item__title\"><div><strong><strong><strong>Can I make a map in Tableau with addresses?<\/strong><\/strong><\/strong><\/div><\/summary><div class=\"wp-block-themeisle-blocks-accordion-item__content\">\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>Yes, you can create a Tableau map with addresses using postcode data to build regions and export the map as a solution for location-based analysis.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n<\/div><\/details>\n\n\n\n<details class=\"wp-block-themeisle-blocks-accordion-item\"><summary class=\"wp-block-themeisle-blocks-accordion-item__title\"><div><strong><strong>How to use postcodes in Tableau?<\/strong><\/strong><\/div><\/summary><div class=\"wp-block-themeisle-blocks-accordion-item__content\">\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>Use the postcode geographic role in Tableau to map regions accurately, create a visual solution, and export the results for reporting or sharing.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n<\/div><\/details>\n\n\n\n<details class=\"wp-block-themeisle-blocks-accordion-item\"><summary class=\"wp-block-themeisle-blocks-accordion-item__title\"><div><strong><strong><strong>Does Tableau map postcodes?<\/strong><\/strong><\/strong><\/div><\/summary><div class=\"wp-block-themeisle-blocks-accordion-item__content\">\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>Tableau map postcode functionality lets users create regions, making it a powerful solution for spatial analysis that can be exported for further use.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n<\/div><\/details>\n<\/div>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Step-by-step tutorial to create postcode maps in Tableau by leveraging integrated geographic sources or importing custom 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This site is optimized with the Yoast SEO plugin v26.7 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Create a Postcode Map in Tableau: A Step-by-Step Guide<\/title>\n<meta name=\"description\" content=\"Step-by-step tutorial to create postcode maps in Tableau by leveraging integrated geographic sources or importing custom polygons.\" \/>\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.geopostcodes.com\/en-GB\/blog\/create-zip-code-map-tableau\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Create a Postcode Map in Tableau: A Step-by-Step Guide\" \/>\n<meta property=\"og:description\" content=\"Learn how to build your postal cStep-by-step tutorial to create postcode maps in Tableau by leveraging integrated geographic sources or importing custom polygons.\" 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