# R Graph Commands for Data Analysis

This post is notes from the Coursera Data Analysis Course.

Here are some basic R commands for creating some graphs.

#### Exploratory Graphs

``` boxplot barchart hist plot density ```

#### Final Graphs for a report

Final graphs need to look a little nicer. They must also have informative labels and a title and possibly a legend.
``` plot(data\$column1, data\$column2, pch=19, col='blue', cex=0.5, xlab='X axis label', ylab='Y axis label', main='Title of Graph', cex.lab=2, cex.axis=1.5)```

``` ``````legend(100,200, legend='Legend Info', col='blue', pch=19, cex=0.5) ```

#### Multipanels

It is often useful to display more than one graph at a time. Here is some code to display 2 graphs horizontally on the same panel.
``` par(mfrow=c(1,2)) plot(data\$column1, data\$column2) plot(data\$column3, data\$column4) ```

#### Figure Captions

``` mtext(text='some caption') ```

#### Create a PDF

``` pdf(file='myfile.pdf',height=4,width=8) par(mfrow=c(1,3)) hist(...) mtext(text='caption',side=3,line=1) plot(...) mtext(...) boxplot(...) mtext(...) dev.off() ```
A very similar thing can be done for PNG image files. Just use png() at the beginning instead.
Use dev.copy2pdf(file=’myfile.pdf’) to save an existing graph to a file. Creator of Data Science 101

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### 2 Comments on “R Graph Commands for Data Analysis”

1. Fernando Amaral says:

Dotchart is also a very usefull Graph

1. Ryan Swanstrom says:

Thanks for sharing. I am not familiar with that one. It is never too late to learn a new R graphing function. Thanks again.

Ryan