I have the following dataframe:
Catergory Reason Species
1 Decline Genuine 24
2 Improved Genuine 16
3 Improved Misclassified 85
4 Decline Misclassified 41
5 Decline Taxonomic 2
6 Improved Taxonomic 7
7 Decline Unclear 41
8 Improved Unclear 117
I'm trying to make a grouped bar chart, species as height and then 2 colours for catergory.
here is my code:
Reasonstats<-read.csv("bothstats.csv")
Reasonstats2<-as.matrix(Reasonstats[,3])
barplot((Reasonstats2),beside=T,col=c("darkblue","red"),ylab="number of
species",names.arg=Reasonstats$Reason, cex.names=0.8,las=2,space=c(0,100)
,ylim=c(0,120))
box(bty="l")
Now what I want, is to not have to label the two bars twice and to group them apart, I've tried changing the space value to all sorts of things and it doesn't seem to move the bars apart. Can anyone tell me what I'm doing wrong?
with ggplot2:
library(ggplot2)
Animals <- read.table(
header=TRUE, text='Category Reason Species
1 Decline Genuine 24
2 Improved Genuine 16
3 Improved Misclassified 85
4 Decline Misclassified 41
5 Decline Taxonomic 2
6 Improved Taxonomic 7
7 Decline Unclear 41
8 Improved Unclear 117')
ggplot(Animals, aes(factor(Reason), Species, fill = Category)) +
geom_bar(stat="identity", position = "dodge") +
scale_fill_brewer(palette = "Set1")
There are several ways to do plots in R; lattice
is one of them, and always a reasonable solution, +1 to @agstudy. If you want to do this in base graphics, you could try the following:
Reasonstats <- read.table(text="Category Reason Species
Decline Genuine 24
Improved Genuine 16
Improved Misclassified 85
Decline Misclassified 41
Decline Taxonomic 2
Improved Taxonomic 7
Decline Unclear 41
Improved Unclear 117", header=T)
ReasonstatsDec <- Reasonstats[which(Reasonstats$Category=="Decline"),]
ReasonstatsImp <- Reasonstats[which(Reasonstats$Category=="Improved"),]
Reasonstats3 <- cbind(ReasonstatsImp[,3], ReasonstatsDec[,3])
colnames(Reasonstats3) <- c("Improved", "Decline")
rownames(Reasonstats3) <- ReasonstatsImp$Reason
windows()
barplot(t(Reasonstats3), beside=TRUE, ylab="number of species",
cex.names=0.8, las=2, ylim=c(0,120), col=c("darkblue","red"))
box(bty="l")
Here's what I did: I created a matrix with two columns (because your data were in columns) where the columns were the species counts for Decline
and for Improved
. Then I made those categories the column names. I also made the Reason
s the row names. The barplot()
function can operate over this matrix, but wants the data in rows rather than columns, so I fed it a transposed version of the matrix. Lastly, I deleted some of your arguments to your barplot()
function call that were no longer needed. In other words, the problem was that your data weren't set up the way barplot()
wants for your intended output.
Not a barplot
solution but using lattice
and barchart
:
library(lattice)
barchart(Species~Reason,data=Reasonstats,groups=Catergory,
scales=list(x=list(rot=90,cex=0.8)))
I wrote a function wrapper called bar()
for barplot()
to do what you are trying to do here, since I need to do similar things frequently. The Github link to the function is here. After copying and pasting it into R, you do
bar(dv = Species,
factors = c(Category, Reason),
dataframe = Reasonstats,
errbar = FALSE,
ylim=c(0, 140)) #I increased the upper y-limit to accommodate the legend.
The one convenience is that it will put a legend on the plot using the names of the levels in your categorical variable (e.g., "Decline" and "Improved"). If each of your levels has multiple observations, it can also plot the error bars (which does not apply here, hence errbar=FALSE
Source: Stackoverflow.com