Data Visualization (eBook)

A Practical Introduction

Kieran Healy (Autor)

eBook Download: EPUB

2024
296 Seiten
Princeton University Press (Verlag)
978-0-691-27084-5 (ISBN)

Infos

An accessible primer on how to create effective graphics from dataThis book provides students and researchers a hands-on introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible methods, and how to think about data visualization in an honest and effective way.Data Visualization builds the reader's expertise in ggplot2, a versatile visualization library for the R programming language. Through a series of worked examples, this accessible primer then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics. Topics include plotting continuous and categorical variables; layering information on graphics; producing effective "e;small multiple"e; plots; grouping, summarizing, and transforming data for plotting; creating maps; working with the output of statistical models; and refining plots to make them more comprehensible.Effective graphics are essential to communicating ideas and a great way to better understand data. This book provides the practical skills students and practitioners need to visualize quantitative data and get the most out of their research findings.Provides hands-on instruction using R and ggplot2Shows how the "e;tidyverse"e; of data analysis tools makes working with R easier and more consistentIncludes a library of data sets, code, and functions

Produkt-Details

• Erscheint lt. Verlag: 10.9.2024
• Zusatzinfo: 185 color illus.
• Sprache: englisch
• Themenwelt: Sozialwissenschaften ► Pädagogik
• Themenwelt: Sozialwissenschaften ► Soziologie
• Schlagworte: Accuracy and precision • Addition • Backslash • Bar chart • Calculation • Cartesian coordinate system • Case sensitivity • Categorical variable • cheat sheet • Cherry Picking • cluster analysis • coefficient • Convenience function • Cook's Distance • Correlation does not imply causation • data set • Data Visualization • Debugging • Dummy variable (statistics) • Error bar • estimation • Exploratory data analysis • generalized additive model • GEOM • ggplot2 • grammar • Hadley Wickham • histogram • inference • Instance (computer science) • Instruction set • knitr • Level of detail • Life Expectancy • Likert Scale • linear regression • Lossless Compression • markdown • Model Checking • Newline • Path (computing) • percentage • pie chart • plain text • Poisson Point Process • Polynomial Regression • Portable Network Graphics • Purple America • Quantity • Ranking (information retrieval) • result • robust regression • RStudio • Rule Of Thumb • Sanity check • Scatter plot • Schematic • scientific notation • Sensitivity Analysis • Shapefile • Spline (mathematics) • Statistic • Subset • Subtitle (captioning) • summary statistics • Syntax error • Temporary variable • Typeface • Variable (computer science) • year
• ISBN-10: 0-691-27084-8 / 0691270848
• ISBN-13: 978-0-691-27084-5 / 9780691270845