|
|
Product Description
An accessible primer on how to create effective graphics from data
This 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 “small multiple†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 ggplot2
- Shows how the “tidyverse†of data analysis tools makes working with R easier and more consistent
- Includes a library of data sets, code, and functions
Customers Who Bought This Item Also Bought
- R for Everyone: Advanced Analytics and Graphics (2nd Edition) (Addison-Wesley Data & Analytics Series)
- The Truthful Art: Data, Charts, and Maps for Communication (Voices That Matter)
- Visualize This: The FlowingData Guide to Design, Visualization, and Statistics
- Regression Modeling with Actuarial and Financial Applications (International Series on Actuarial Science)
- Advanced R, Second Edition (Chapman & Hall/CRC The R Series)
- An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
- R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
- R Graphics Cookbook: Practical Recipes for Visualizing Data
- Fundamentals of Data Visualization: A Primer on Making Informative and Compelling Figures
- ggplot2: Elegant Graphics for Data Analysis (Use R!)
*If this is not the "Data Visualization: A Practical Introduction" product you were looking for, you can check the other results by clicking this link








