**stattler.com - R**, and kindly contributed to R-bloggers)

In this article I am trying to show how to produce bar plots using R. Many of my friends think SPSS is the most useful software for producing plots and they keep using it (some of them even use Excel!).

My goal is to show that R can do every type of graphs that other commercial softwares can do. In fact it does much better than the simple point and click packages, as R gives us much better control over our analysis.

The data of my concern is –

sex income district female 21 dhaka male 11 dhaka male 43 chittagong female 22 dhaka male 56 barisal female 23 barisal female 66 dhaka male 76 dhaka female 11 chittagong female 89 dhaka

This data is not a real data, completely created by me just to do experiments using R codes.

Now, I want to produce a bar plot where ‘sex’ would be the category axis and the clusters will represent mean and median ‘income’, i.e. I want to produce a plot that we produce in SPSS by the command-

graph /bar=mean(income) median(income) by sex.

So, at first I calculate mean and median ‘income’ for both male and female.

m1<-tapply(data\$income,data\$sex,mean) m2<-tapply(data\$income,data\$sex,median) r<-rbind(m1,m2) b<-barplot(r,col=c("green","blue"),ylim=c(0,65),beside=T) legend("topleft",c("mean","median"),col=c("green","blue"),pch=15)

Then if I want to put the numbers represented by the bars above them,

the code will be-

text(x=b,y=c(r[1],r[2],r[3],r[4]),labels=c(round(r[1],2), round(r[2],2),r[3],r[4]),pos=3,col="black",cex=1.25)

And the plot is-

Now, if I want to produce a more complex plot that is a bar plot that will show mean income for all the three districts separately for male and female, i.e. the plot we produce in SPSS by the command-

graph /bar=mean(income) by sex by district.

For the required summary statistics I used a package ‘Epi’ and with the following command produced a very useful summary table-

`s=stat.table(list(district,sex),contents=list(mean(income)))`

And the produced table is-

----------------------------- -------sex------- district female male ----------------------------- barisal 23.00 56.00 chittagong 11.00 43.00 dhaka 49.50 43.50 -----------------------------

As we all know this statistics can also be found by a few lines of codes instead of ‘stat.table’, but I used it just to cut down some codes.

Then, I did the following commands-

female<-c(s[1],s[2],s[3]) male<-c(s[4],s[5],s[6]) r<-cbind(female,male) row.names(r)<-c('barisal','chittagong','dhaka') b<-barplot(r,col=c("red","green","yellow"),beside=T,ylim=c(0,60)) legend("topleft",c("barisal","chittagong","dhaka"),col= c("red","green","yellow"),pch=15,bty="n") text(x=b,y=c(r[1:6]),labels=c(r[1:6]),cex=1.25,pos=3)

And the plot is-

Hope this codes will be useful to those who really want to do every type of statistical work(including producing graphs) in R.

**leave a comment**for the author, please follow the link and comment on his blog:

**stattler.com - R**.

R-bloggers.com offers

**daily e-mail updates**about R news and tutorials on topics such as: visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...