Distance profiles have long been used in urban demography to explore how demographic characteristics of metropolitan areas vary by distance from their urban cores. Distance profile visualizations graphically illustrate these relationships and are useful in exploratory demographic data analysis of urban areas. The purpose of this article is to demonstrate how to build distance profile visualizations reproducibly within R, a free and open-source programming language and data analysis environment. The approach to distance profile visualization in this article involves the graphical display of a smoothed relationship between the location quotient of a demographic group for a metropolitan Census tract and the distance between the tract centroid and its respective urban core. Data acquisition, analysis, and visualization are all handled in R. The tidycensus, sf, and ggplot2 R packages are featured in this framework. Distance profile visualizations for educational attainment are used as illustrative examples, and reveal how the geography of metropolitan educational attainment varies both over time and across different types of metropolitan areas.

中文翻译：

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可重现的框架，用于可视化美国大都市地区的人口距离剖面

距离剖面在城市人口统计学中一直被使用，以探索大都市区的人口统计学特征如何随距城市核心区的距离而变化。距离剖面可视化以图形方式说明了这些关系，并且在城市地区的人口统计数据探索研究中很有用。本文的目的是演示如何在R（一种免费的开源编程语言和数据分析环境）中可再现地构建距离轮廓可视化。本文中距离轮廓可视化的方法涉及图形化显示大城市人口普查区域的人口统计群体的位置商与区域质心及其各自的城市核心之间的距离之间的平滑关系。数据采集​​，分析和可视化都在R中处理。tidycensus，sf和ggplot2 R软件包在此框架中具有特色。用于教育程度的距离概图可视化被用作说明性示例，并揭示了都市教育程度的地理位置如何随时间以及跨不同类型的都市区域而变化。