How to specify columns in facet_grid OR how to change labels in facet_wrap

I have a large number of data series that I want to plot using small multiples. A combination of ggplot2 and facet_wrap does what I want, typically resulting a nice little block of 6 x 6 facets. Here's a simpler version:

The problem is that I don't have adequate control over the labels in facet strips. The names of the columns in the data frame are short and I want to keep them that way, but I want the labels in the facets to be more descriptive. I can use facet_grid so that I can take advantage of the labeller function but then there seems to be no straightforward way to specify the number of columns and a long row of facets just doesn't work for this particular task. Am I missing something obvious?

Q. How can I change the facet labels when using facet_wrap without changing the column names? Alternatively, how can I specify the number of columns and rows when using facet_grid?

Code for a simplified example follows. In real life I am dealing with multiple groups each containing dozens of data series, each of which changes frequently, so any solution would have to be automated rather than relying on manually assigning values.

require(ggplot2)
require(reshape)

# Random data with short column names
set.seed(123)
myrows <- 30
mydf <- data.frame(date = seq(as.Date('2012-01-01'), by = "day", length.out = myrows),
                   aa = runif(myrows, min=1, max=2),
                   bb = runif(myrows, min=1, max=2),
                   cc = runif(myrows, min=1, max=2),
                   dd = runif(myrows, min=1, max=2),
                   ee = runif(myrows, min=1, max=2),
                   ff = runif(myrows, min=1, max=2))

# Plot using facet wrap - we want to specify the columns
# and the rows and this works just fine, we have a little block
# of 2 columns and 3 rows

mydf <- melt(mydf, id = c('date'))

p1 <- ggplot(mydf, aes(y = value, x = date, group = variable)) +
    geom_line() +
    facet_wrap( ~ variable, ncol = 2)
print (p1)

# Problem: we want more descriptive labels without changing column names.
# We can change the labels, but doing so requires us to
# switch from facet_wrap to facet_grid
# However, in facet_grid we can't specify the columns and rows...

mf_labeller <- function(var, value){ # lifted bodily from the R Cookbook
    value <- as.character(value)
    if (var=="variable") {
        value[value=="aa"]   <- "A long label"
        value[value=="bb"]   <- "B Partners"
        value[value=="cc"]   <- "CC Inc."
        value[value=="dd"]   <- "DD Company"
        value[value=="ee"]   <- "Eeeeeek!"
        value[value=="ff"]   <- "Final"
    }
    return(value)
}

p2 <- ggplot(mydf, aes(y = value, x = date, group = variable)) +
    geom_line() +
    facet_grid( ~ variable, labeller = mf_labeller)
print (p2)

Solution 1:

I don't quite understand. You've already written a function that converts your short labels to long, descriptive labels. What is wrong with simply adding a new column and using facet_wrap on that column instead?

mydf <- melt(mydf, id = c('date'))
mydf$variableLab <- mf_labeller('variable',mydf$variable)

p1 <- ggplot(mydf, aes(y = value, x = date, group = variable)) +
    geom_line() +
    facet_wrap( ~ variableLab, ncol = 2)
print (p1)

Solution 2:

To change the label names, just change the factor levels of the factor you use in facet_wrap. These will be used in facet_wrap on the strips. You can use a similar setup as you would using the labeller function in facet_grid. Just do something like:

new_labels = sapply(levels(df$factor_variable), custom_labeller_function)
df$factor_variable = factor(df$factor_variable, levels = new_labels)

Now you can use factor_variable in facet_wrap.