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R Data Visualization Cookbook

You're reading from   R Data Visualization Cookbook Over 80 recipes to analyze data and create stunning visualizations with R

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Product type Paperback
Published in Jan 2015
Publisher
ISBN-13 9781783989508
Length 236 pages
Edition 1st Edition
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Toc

Table of Contents (12) Chapters Close

Preface 1. A Simple Guide to R FREE CHAPTER 2. Basic and Interactive Plots 3. Heat Maps and Dendrograms 4. Maps 5. The Pie Chart and Its Alternatives 6. Adding the Third Dimension 7. Data in Higher Dimensions 8. Visualizing Continuous Data 9. Visualizing Text and XKCD-style Plots 10. Creating Applications in R Index

Data frames in R

One of the useful and widely used functions in R is the data.frame() function. Data frame, according to the R manual, is a matrix structure whose columns can be of differing types, such as numeric, logical, factor, or character.

How to do it…

A data frame in R is a collection of variables. A simple way to construct a data frame is using the data.frame() function in R:

data = data.frame(x = c(1:4), y = c("tom","jerry","luke","brian"))
data

Many times, we will encounter plotting functions that require data to be in a data frame. In order to coerce our data into a data frame, we can use the data.frame() function. In the following example, we create a matrix and convert it into a data frame:

mat = matrix(c(1:10), nrow = 2, ncol = 5)
data.frame(mat)

The data.frame() function comes with various arguments and can be explored by typing ?data.frame in the R console window. The code file under the title Data Frames – 2 provides additional functions that can help in understanding the underlying structure of our data. We can always get additional help by using the R documentation.

You have been reading a chapter from
R Data Visualization Cookbook
Published in: Jan 2015
Publisher:
ISBN-13: 9781783989508
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