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dc.creatorWalker, Kyle E.
dc.date.accessioned2019-07-12T16:01:46Z
dc.date.available2019-07-12T16:01:46Z
dc.date.issued2018-03-07
dc.identifier.urihttps://doi.org/10.1007/s40980-018-0042-7
dc.identifier.urihttps://repository.tcu.edu/handle/116099117/26404
dc.identifier.urihttps://link.springer.com/article/10.1007/s40980-018-0042-7
dc.description.abstractDistance 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.en_US
dc.language.isoenen_US
dc.publisherSpringerNature
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceSpatial Demography
dc.subjectDistance profilesen_US
dc.subjectData visualizationen_US
dc.subjectRen_US
dc.subjectCensusen_US
dc.subjectAmerican Community Surveyen_US
dc.titleA Reproducible Framework for Visualizing Demographic Distance Profiles in US Metropolitan Areasen_US
dc.typeArticleen_US
dc.rights.holderKyle E. Walker et al.
dc.rights.licenseCC BY 4.0
local.collegeAddRan College of Liberal Arts
local.departmentGeography
local.personsWalker (GEOG)


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