Sweeping through data in R

How do you apply one particular row of your data to all other rows?

Today I came across a data set which showed the revenue split by product and location. The data was formated to show only the split by product for each location and the overall split by location, similar to the example in the table below.

Revenue by product and continent

I wanted to understand the revenue split by product and location. Hence, I have to multiply the total split by continent for each product in each column. Or in other words I would like to use the total line and sweep it through my data. Of course there is a function in base R for that. It is called sweep. To my surprise I can’t remember that I ever used sweep before. The help page for sweep states that it used to be based on apply, so maybe that’s how I would have approached those tasks in the past.

Anyhow, the sweep function requires an array or matrix as an input and not a data frame. Thus let’s store the above table in a matrix.

Product <- c("A", "B", "C", "Total")
Continent <- c("Africa", "America", "Asia", "Australia", "Europe")
values <- c(0.4, 0.2, 0.4, 0.1, 0.3, 0.4, 0.3, 0.4, 0.5, 0.2, 
            0.3, 0.2, 0.4, 0.3, 0.3, 0.1, 0.4, 0.4, 0.2, 0.2)

M <- matrix(values, ncol=5, dimnames=list(Product, Continent))

Now I can sweep through my data. The arguments for sweep are the data set itself (in my case the first three rows of my matrix), the margin dimension (here 2, as I want to apply the calculations to the second dimension / columns), the summary statistics to be applied (in my case the totals in row 4) and the function to be applied (in my scenario a simple multiplication "*"):

swept.M <- sweep(M[1:3,], 2, M[4,], "*")

The output is what I desired and can be plotted nicely as a bar plot.

> swept.M
Product Africa America Asia Australia Europe
      A   0.04    0.12 0.10      0.04   0.08
      B   0.02    0.16 0.04      0.03   0.08
      C   0.04    0.12 0.06      0.03   0.04

barplot(swept.M*100, legend=dimnames(swept.M)[["Product"]],
       main="Revenue by product and continent",
       ylab="Revenue split %") 
</pre><div class="separator" style="clear: both; text-align: center;"><a href="/img/magesblog/SweepingThroughData.png" imageanchor="1" style="margin-left:1em; margin-right:1em"><img border="0" height="315" width="400" src="/img/magesblog/SweepingThroughData.png" /></a></div><p><h2>One more example</h2>Another classical example for using the <code>sweep</code> function is of course the case when you have revenue information and would like to calculate the income split by product for each location:
Revenue <- matrix(1:15, ncol=5)
sweep(Revenue, 2, colSums(Revenue), "/")

This is actually the same as prop.table(Revenue, 2), which is short for:

sweep(x, margin, margin.table(x, margin), "/") 

Reading the help file for margin.table shows that this function is the same as apply(x, margin, sum) and colSum is just a faster version of the same statement.


For attribution, please cite this work as:

Markus Gesmann (Apr 14, 2012) Sweeping through data in R. Retrieved from https://magesblog.com/post/2012-04-14-sweeping-through-data-in-r/

BibTeX citation:

@misc{ 2012-sweeping-through-data-in-r,
 author = { Markus Gesmann },
 title = { Sweeping through data in R },
 url = { https://magesblog.com/post/2012-04-14-sweeping-through-data-in-r/ },
 year = { 2012 }
 updated = { Apr 14, 2012 }