**R Video tutorial for Spatial Statistics**, and kindly contributed to R-bloggers)

Sometimes I have the need to reduce the number of images for a presentation or an article. A good way of doing it is putting multiple plot on the same tif or jpg file.

R has multiple functions to achieve this objective and a nice tutorial for this topic can be reached at this link: http://www.statmethods.net/advgraphs/layout.html

The most common function is par. This function let the user create a table of plots by defining the number of rows and columns.

An example found in website above, is:

`attach(mtcars)`

par(mfrow=c(3,1))

hist(wt)

hist(mpg)

hist(disp)

In this case I create a table with 3 rows and 1 column and therefore each of the 3 plot will occupy a single line in the table.

The limitation of this method is that I can only create ordered tables of plots. So for example, if I need to create an image with 3 plots, my options are limited:

A plot per line, created with the code above, or a table of 2 columns and 2 rows:

attach(mtcars)

par(mfrow=c(2,2))

hist(wt)

hist(mpg)

hist(disp)

However, for my taste this is not appealing. I would rather have an image with 2 plots on top and 1 in the line below but centered.

To do this we can use the function layout. Let us see how it can be used:

First of all I created a fake dataset:

`data<-data.frame(D1=rnorm(500,mean=2,sd=0.5),`

D2=rnorm(500,mean=2.5,sd=1),

D3=rnorm(500,mean=5,sd=1.3),

D4=rnorm(500,mean=3.5,sd=1),

D5=rnorm(500,mean=4.3,sd=0.8),

D6=rnorm(500,mean=5,sd=0.4),

D7=rnorm(500,mean=3.3,sd=1.3))

I will use this data frame to create 3 identical boxplots.

The lines of code to create a single boxplot are the following:

`boxplot(data,par(mar = c(10, 5, 1, 2) + 0.1),`

ylab="Rate of Change (%)",

cex.lab=1.5, names=c("24/01/2011","26/02/2011",

"20/03/2011","25/04/2011","23/05/2011",

"23/06/2011","24/07/2011"),

col=c("white","grey","red","blue"),

at=c(1,3,5,7,9,11,13),

yaxt="n",

las=2)

axis(side=2,at=seq(0,8,1),las=2)

abline(0,0)

mtext("Time (days)",1,line=8,at=7)

mtext("a)",2,line=2,at=-4,las=2,cex=2)

This creates the following image:

I used the same options I explored in one of my previous post about box plots: BoxPlots

Notice however how the label of the y axes is bigger than the label on the x axes. This was done by using the option **cex.lab = 1.5** in the boxplot function.

Also notice that the label on the x axes (“Time (days)”) is two lines below the names. This was done by increasing the line parameter in the **mtext **call.

These two elements are crucial for producing the final image, because when we will plot the three boxplots together in a jpg file, all these elements will appear natural. Try different option to see the differences.

Now we can put the 3 plots together with the function **layout**.

This function uses a matrix to identify the position of each plots, in may case I use the function with the following options:

layout(matrix(c(1,1,1,1,1,0,2,2,2,2,2,0,0,0,3,3,3,3,3,0,0,0), 2, 11, byrow = TRUE))

This creates a 2×11 matrix that looks like this:

1 1 1 1 1 0 2 2 2 2 2

0 0 0 3 3 3 3 3 0 0 0

what this tells the function is:

- create a plotting window with 2 rows and 11 columns
- populate the first 5 cells of the first row with plot number 1
- create a space (that’s what the 0 means)
- populate the remaining 5 spaces of the first row with plot number 2
- in the second row create 3 spaces
- add plot number 3 and use 5 spaces to do so
- finish with 3 spaces

The results is the image below:

The script is available here: Multiple_Plots_Script.r

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**R Video tutorial for Spatial Statistics**.

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