ezplot: How to Easily Make ggplot2 Graphics for Data Analysis
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ezplot: How to Easily Make ggplot2 Graphics for Data Analysis

About the Book

Six years ago, I started a data science consulting company. Almost all my projects require some kind of data visualization. Because I'm a R programmer, ggplot2 became my primary charting tool. The thing about ggplot2 is that making a generic plot is easy, but customizing is hard. There're just too much details to remember. At first, I did a lot of code recycling, but that was still very inefficient as I had to manually change things to make old code work with new data. As the repertoire of reusable codebase grew, it became painful to find the right piece of code for the things I wanted to do. Moreover, code recycling lead to code repetition, which made my R script lengthy and difficult to read. One day, the frustration became unbearable, and I decided to change it all. The result is ezplot, a R package based off ggplot2. It's available on github. Ezplot has saved me tons of hours. A plot that used to takes me 30+ minutes now takes me less than 1 minute. I now use ezplot for all my projects. I truly love it, and I think you’ll love it too.

This book teaches you how to use ezplot step by step with many examples. Start reading FREE sample chapters now.

About the Author

Guangming Lang
Guangming Lang

Guangming Lang is the founder and Chief Data Scientist at Cabaceo LLC. He also teaches people how to do data analysis using the R programming language at MasterR.org, where you can receive high quality training materials for free. He used to work for FICO. He has a masters degree in biostatistics from the University of Michigan and a bachelor's degree in mathematics from the New College of Florida. 


Table of Contents

  • Preface
  • Set up
  • Plot the Distribution of a Continuous Variable
    • Histogram
    • Density Plot
    • Boxplot
    • CDF Plot
    • Q-Q Plot
    • Check if observed data follow the exponential distribution.
    • Check if observed data follow the normal distribution.
    • Check if observed data follow the lognormal distribution.
    • Check if observed data follow the pareto distribution.
  • Plot the Distribution of a Categorical Variable
    • Regular Bar Chart
    • Dodged or Stacked Bar Chart
    • Horizontal Bar Chart & Lollipop Plot
    • Likert Chart
  • Plot the Relationship of Two or More Variables
    • Scatter Plot
    • Line Plots
    • Rank-Order Plots and Lift Charts
    • Dumbbell Plot
    • Heatmap
    • Forest Plot
  • Other Topics
    • Web Display
  • Combine Plots
  • Conclusion

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