{"product_id":"analyzing-us-census-data-methods-maps-and-models-in-r-9781032366449","title":"Analyzing US Census Data: Methods, Maps, and Models in R","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003e\n\u003cbr\u003eR provides easy access to US Census Bureau geographic and demographic data for analysis and visualization.  The tidyverse and sf packages make it easy to work with Census data, including margins of error in the American Community Survey. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Paperback \/ softback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 352 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 16 February 2023\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Taylor \u0026amp; Francis Ltd\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eThe R programming language provides a seamless interface to access the vast geographic and demographic data resources of the US Census Bureau. With the help of the tidyverse tools, users can effortlessly wrangle Census data, analyze margins of error in the American Community Survey, create visually appealing maps and interactive web visualizations using US Census data, and employ spatial analysis techniques with the sf package to explore Census data in a spatial context. Furthermore, users can integrate Census data into spatial and machine learning models to gain deeper insights and make informed decisions.\u003cbr\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003eAccess US Census Bureau geographic and demographic data directly within R.\u003c\/p\u003e\u003cp\u003eThe R programming language offers a seamless interface to tap into the vast geographic and demographic data resources of the US Census Bureau. By leveraging the powerful tidyverse tools, users can effortlessly wrangle Census data, conduct comprehensive analysis of margins of error in the American Community Survey, create visually appealing maps and interactive web visualizations utilizing US Census data, and employ spatial analysis techniques with the sf package to explore Census data in a spatial context.\u003c\/p\u003e\u003cp\u003eFurthermore, users can integrate Census data into spatial and machine learning models to gain deeper insights and make informed decisions.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 680g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 254 x 178 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9781032366449\u003c\/p\u003e","brand":"Kyle Walker","offers":[{"title":"Paperback \/ softback","offer_id":44103845183738,"sku":"9781032366449","price":58.55,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/1676641019284_book.jpg?v=1676912332","url":"https:\/\/shulphink.com\/products\/analyzing-us-census-data-methods-maps-and-models-in-r-9781032366449","provider":"Shulph Ink","version":"1.0","type":"link"}