Sorting a dotchart with matrix input in R - r

Question

How do you generate a grouped Cleveland dot plot (dot chart), where the data is sorted from highest to loweset in each subroup, when your input is a matrix?
For example, R has a nice built-in example of a dotchart using groups with a matrix as input:
dotchart(VADeaths, main = "Death Rates in Virginia - 1940")
In this particular example, the data is already sorted in each category for each of the groups (Rural Male, Rural Female, etc.). However, if it wasn't, what are the R commands to generate a plot such that the data points in each subgroup are sorted from highest to lowest?

Answer 1

If you do not want to order your data by the column names, as #DWin suggested, but solely on numeric data, you might try:
# get data
data <- VADeaths[sample(1:5), ]
# order data by first row's numeric values
data <- data[order(data[,1]),]
dotchart(data)
Note: this will sort the dataframe by the first column only! It is not possible to sort every column in a table without specifying different rownames for each column, which is definitely not possible with table class.
If you stick to your original question: I would suggest splitting up the data by the columns, plot the dotchart for each sorted column and pile up those in a layout.

Answer 2

This shows the creation of a matrix with arbitrary row order and how one can restore it to proper order.
> set.seed(123)
> VA2 <- VADeaths[sample(1:5), ]
> VA2
Rural Male Rural Female Urban Male Urban Female
55-59 18.1 11.7 24.3 13.6
65-69 41.0 30.9 54.6 35.1
70-74 66.0 54.3 71.1 50.0
60-64 26.9 20.3 37.0 19.3
50-54 11.7 8.7 15.4 8.4
> VA2[order(rownames(VA2)), ]
Rural Male Rural Female Urban Male Urban Female
50-54 11.7 8.7 15.4 8.4
55-59 18.1 11.7 24.3 13.6
60-64 26.9 20.3 37.0 19.3
65-69 41.0 30.9 54.6 35.1
70-74 66.0 54.3 71.1 50.0
If you were faced with disordered colnames but not something with a the desired lexical order you could just use a character vector in the proper order with "["
> c2 <- c("Rural Male", "Rural Female", "Urban Male" , "Urban Female")
> VA3 <- VA2[ , sample(1:4)]
> VA3
Rural Male Rural Female Urban Male Urban Female
55-59 18.1 11.7 24.3 13.6
65-69 41.0 30.9 54.6 35.1
70-74 66.0 54.3 71.1 50.0
60-64 26.9 20.3 37.0 19.3
50-54 11.7 8.7 15.4 8.4
> VA3[ , c2]
Rural Male Rural Female Urban Male Urban Female
55-59 18.1 11.7 24.3 13.6
65-69 41.0 30.9 54.6 35.1
70-74 66.0 54.3 71.1 50.0
60-64 26.9 20.3 37.0 19.3
50-54 11.7 8.7 15.4 8.4