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R Data Visualization Cookbook

R Data Visualization Cookbook

By : Gohil
4.2 (6)
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R Data Visualization Cookbook

R Data Visualization Cookbook

4.2 (6)
By: Gohil

Overview of this book

If you are a data journalist, academician, student or freelance designer who wants to learn about data visualization, this book is for you. Basic knowledge of R programming is expected.
Table of Contents (12 chapters)
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11
Index

Connecting points in a scatter plot


The primary objective of this recipe is to understand how we can connect points in a scatter plot. The plot is inspired by Alberto Cairo infographic regarding the Gini coefficient, and the GDP data under various president's tenure in Brazil and connected points based on these three variables. In this recipe, we will apply the same concept to the USA economy.

Tip

For all the data visualizations and references used in recipes in this book, please refer to the See also section in each recipe

How to do it…

We will start to import the data in R. The dataset comprises of the Gini coefficient, the GDP data of the USA and USA presidents. The Gini coefficient is used as a measure of inequality in a country:

data = read.csv("ginivsgdp1.csv", header = TRUE)

The plot can be generated using the plot() function:

plot(income$gdp_ann,income$Gini,pch = 20, col = c(data$Presidents), type = "o",xlab =" GDP of USA", ylab = "Gini coefficient",main = "Inequality in USA", xaxp = c...
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R Data Visualization Cookbook
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