Amazon cover image
Image from Amazon.com
Image from Google Jackets
Image from OpenLibrary

Data Visualization for Social and Policy Research: A Step-by-Step Approach Using R and Python / by Jose Manuel Magallanes Reyes

By: Material type: TextTextPublication details: Cambridge: University Press. 2022.Description: VI, 285 PISBN:
  • 9781108714389
  • 9781108494335
DDC classification:
  • 001.422 REY
Other classification:
Summary: All social and policy researchers need to synthesize data into a visual representation. Producing good visualizations combines creativity and technique. This book teaches the techniques and basics to produce a variety of visualizations, allowing readers to communicate data and analyses in a creative and effective way. Visuals for tables, time series, maps, text, and networks are carefully explained and organized, showing how to choose the right plot for the type of data being analysed and displayed. Examples are drawn from public policy, public safety, education, political tweets, and public health. The presentation proceeds step by step, starting from the basics, in the programming languages R and Python so that readers learn the coding skills while simultaneously becoming familiar with the advantages and disadvantages of each visualization. No prior knowledge of either Python or R is required. Code for all the visualizations are available from the book's website.
Tags from this library: No tags from this library for this title. Log in to add tags.
Holdings
Item type Current library Home library Call number Status Date due Barcode
Book Book Dept. of Futures Studies General Stacks Dept. of Futures Studies 001.422 REY (Browse shelf(Opens below)) Available DFS4577

All social and policy researchers need to synthesize data into a visual representation. Producing good visualizations combines creativity and technique. This book teaches the techniques and basics to produce a variety of visualizations, allowing readers to communicate data and analyses in a creative and effective way. Visuals for tables, time series, maps, text, and networks are carefully explained and organized, showing how to choose the right plot for the type of data being analysed and displayed. Examples are drawn from public policy, public safety, education, political tweets, and public health. The presentation proceeds step by step, starting from the basics, in the programming languages R and Python so that readers learn the coding skills while simultaneously becoming familiar with the advantages and disadvantages of each visualization. No prior knowledge of either Python or R is required. Code for all the visualizations are available from the book's website.

There are no comments on this title.

to post a comment.