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  • Analyzing US Census Data (Chapman & Hall/CRC The R Series)

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Analyzing US Census Data (Chapman & Hall/CRC The R Series) 1st Edition

by Kyle Walker (Author)
4.4 out of 5 stars (12)
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Census data is widely used by practitioners to understand demographic change, allocate resources, address inequalities, and make sound business decisions. Until recently, projects using US Census data have required proficiency with multiple web interfaces and software platforms to prepare, map, and present data products. This book introduces readers to tools in the R programming language for accessing and analyzing Census data and shows how to carry out demographic analyses in a single computing environment.

Chapters in this book cover the following key topics:

• Rapidly acquiring data from the decennial US Census and American Community Survey using R, then analyzing these datasets using tidyverse tools;

• Visualizing US Census data with a wide range of methods including charts in ggplot2 as well as both static and interactive maps;

• Using R as a geographic information system (GIS) to manage, analyze, and model spatial demographic data from the US Census;

• Working with and modeling individual-level microdata from the American Community Survey’s PUMS datasets;

• Applying these tools and workflows to the analysis of historical Census data, other US government datasets, and international Census data from countries like Canada, Brazil, Kenya, and Mexico.

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  1. ISBN-10
    1032366443
  2. ISBN-13
    978-1032366449
  3. Edition
    1st
  4. Publication date
    February 16, 2023
  5. Part of series
    Chapman & Hall/CRC The R
  6. Language
    English
  7. Dimensions
    7.01 x 0.86 x 10 inches
  8. Print length
    352 pages
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Editorial Reviews

Review

"This book is destined to become the go-to text for people wanting to use R for the analysis of US Census data. I think this is a strong, clear, and comprehensive introduction to the tidycensus package and the tidyverse. I have been using tidycensus and Walker’s tigris package probably since he initially contributed them to the community of R users years ago. Although I use the packages regularly for teaching and research, I still learned quite a bit about their functionality in the chapters I reviewed. Thus, I think it will be a useful text for both novices and experienced R users. I could see this book being used in a variety of social science courses relating to research methodology, data visualization, and cartography."
-Hugh Bartling, Associate Professor, DePaul University

"Walker [...] is clearly familiar with the material and how to use R to the best advantage for mapping and modeling. Indeed, he has written the code for some of the many R packages covered in this title. In this book, he recommends which R package is most suitable for each application and then provides code examples to highlight how to carry out a simple version of each task with the package. Some of the specific scenarios include the creation of data visualizations using ggplot2 or tmap, a discussion of handling margins of error with the American Community Survey data using tidycensus, and historical census data analysis and mapping using ipumsr. The code samples are suitable for users who are quite familiar with R or similar GIS software. This title would function well as a reference or a textbook for graduate-level students or faculty.
-J. Parker, SUNY Cortland in CHOICE, April 2024

About the Author

Kyle Walker is an associate professor of geography at Texas Christian University, director of TCU’s Center for Urban Studies, and a spatial data science consultant. His research focuses on demographic trends in the United States, demographic data visualization, and software tools for open spatial data science. He is the lead author of a number of R packages including tigris, tidycensus, and mapboxapi.

Product details

  • Publisher ‏ : ‎ Chapman and Hall/CRC
  • Publication date ‏ : ‎ February 16, 2023
  • Edition ‏ : ‎ 1st
  • Language ‏ : ‎ English
  • Print length ‏ : ‎ 352 pages
  • ISBN-10 ‏ : ‎ 1032366443
  • ISBN-13 ‏ : ‎ 978-1032366449
  • Item Weight ‏ : ‎ 1.5 pounds
  • Dimensions ‏ : ‎ 7.01 x 0.86 x 10 inches
  • Part of series ‏ : ‎ Chapman & Hall/CRC The R
  • Best Sellers Rank: #1,277,656 in Books (See Top 100 in Books)
  • Customer Reviews:
    4.4 out of 5 stars (12)

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Customer reviews

4.4 out of 5 stars
12 global ratings

Top reviews from the United States

  • CalifPhoto
    5.0 out of 5 stars One of the best books ever for learning R and Big Govt Data
    Reviewed in the United States on December 10, 2024
    Format: PaperbackVerified Purchase
    This book is my bedrock, my main source for the code needed for working on any database.
    Helpful
     Report
  • Justan
    5.0 out of 5 stars Great resource for public health professionals
    Reviewed in the United States on March 19, 2024
    Format: PaperbackVerified Purchase
    This book provides an excellent overview of the tidycensus and tigris R packages, as well as the most popular mapping packages in R, such as ggplot, leaflet, tmap, and mapview. The instructions on how to use these packages is thorough, and the examples throughout the text are excellent. Beyond just showing how to retrieve and map census data, this book also provides examples of some statistical models using geographic data. Census data is important for assessing certain social determinants of health among populations, and this book has helped me more easily access this data. No more cumbersome manual processes for saving large census data tables and associated shape files; it all can be done easily within R with just a few lines of code!
    Helpful
     Report
  • Travis Miller
    5.0 out of 5 stars Great companion text for compiling and analyzing Census data
    Reviewed in the United States on January 20, 2025
    Format: Paperback
    I've been using this for research in a graduate setting and found it to be very useful. As is often the case with these sorts of texts, some links referenced in the text examples are already becoming outdated; it's unfortunate because it can render sections difficult to navigate, but I've only come across a couple like that. The lesson is still navigable when it comes up, though replicating the data might be challenging in said examples. Overall, this has gotten me in a great position to compile, analyze and visualize this type of data. The author hosts a website that's an excellent supplement as well.
    Helpful
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