Adding missing data.frame values for geom_area (ggplot2)

r, reshape, reshape2

Solution

# Expand the data.frame
p.data <- merge(d,
                expand.grid(x=unique(d$x),
                            cat=unique(d$cat),
                            stringsAsFactors=F),
                all.y=T)

# Fill NA values with zeros
p.data$y[is.na(p.data$y)] <- 0

# Plot the graph
ggplot(p.data, aes(x, y, fill=cat)) +
    geom_area()

Problem

I want to create ggplot2::geom_area plots from summary datasets that have some data categories missing for some of the data periods (month), for instance: ``` require(ggplot2) set.seed(1) d = data.frame(x = rep(1:10,each=4), y = rnorm(40,10), cat=rep(c('A','B','C','D'), 10)) (d = d[-sample(1:40,10),]) # remove some rows ggplot(d, aes(x, y, fill=cat)) + geom_area() ``` Ggplot's stacked area plot doesn't respond well to missing values, so it seems we need to add zero entries to the data.frame. The best way I can think (unless any better suggestions?) of is to `reshape2::dcast` it, convert NA's to zeros and reshape back. But I can't figure out the right formula. Grateful for assistance from someone who understands reshape(2). ``` require(reshape2) dcast(d, x ~ cat) # right direction but missing the data x A B C D 1 1 A B C D 2 2 <NA> B C <NA> 3 3 A B C D 4 4 <NA> B C <NA> 5 5 A <NA> C D 6 6 A B C D 7 7 <NA> B C <NA> 8 8 A B C D 9 9 <NA> B <NA> D 10 10 A B <NA> D ```

Original source