How to produce a heatmap with ggplot2?

Question

I am trying to produce a heat map using ggplot2. I found this example , which I am essentially trying to replicate with my data, but I am having difficulty. My data is a simple .csv file that looks like this:

people,apple,orange,peach
mike,1,0,6
sue,0,0,1
bill,3,3,1
ted,1,1,0

I would like to produce a simple heat map where the name of the fruit is on the x-axis and the person is on the y-axis. The graph should depict squares where the color of each square is a representation of the number of fruit consumed. The square corresponding to mike:peach should be the darkest.

Here is the code I am using to try to produce the heatmap:

data <- read.csv("/Users/bunsen/Desktop/fruit.txt", head=TRUE, sep=",")
fruit <- c(apple,orange,peach)
people <- data[,1]
(p <- ggplot(data, aes(fruit, people)) + geom_tile(aes(fill = rescale), colour = "white") +    scale_fill_gradient(low = "white", high = "steelblue"))

When I plot this data I get the number of fruit on the x-axis and people on the y-axis. I also do not get color gradients representing number of fruit. How can I get the names of the fruits on the x-axis with the number of fruit eaten by a person displayed as a heat map? The current output I am getting in R looks like this:

Answer 1

To be honest @dr.bunsen - your example above was poorly reproducable and you didn't read the first part of the tutorial that you linked . Here is probably what you are looking for:

 library(reshape)
 library(ggplot2)
 library(scales)

 data <- structure(list(people = structure(c(2L, 3L, 1L, 4L), 
                                           .Label = c("bill", "mike", "sue", "ted"), 
                                           class = "factor"), 
                        apple = c(1L, 0L, 3L, 1L), 
                        orange = c(0L, 0L, 3L, 1L), 
                        peach = c(6L, 1L, 1L, 0L)), 
                    .Names = c("people", "apple", "orange", "peach"),
                    class = "data.frame", 
                    row.names = c(NA, -4L))
 data.m <- melt(data)
 data.m <- ddply(data.m, .(variable), transform, rescale = rescale(value))
 p <- ggplot(data.m, aes(variable, people)) + 
         geom_tile(aes(fill = rescale), colour = "white") 
 p + scale_fill_gradient(low = "white", high = "steelblue")

Answer 2

Seven (!) years later, the best way to format your data correctly is to use tidyr rather than reshape

Using gather from tidyr , it is very easy to reformat your data to get the expected 3 columns ( person for the y-axis, fruit for the x-axis and count for the values):

library("dplyr")
library("tidyr")

hm <- readr::read_csv("people,apple,orange,peach
mike,1,0,6
sue,0,0,1
bill,3,3,1
ted,1,1,0")

hm <- hm %>%
  gather(fruit, count, apple:peach)
  #syntax: key column (to create), value column (to create), columns to gather (will become (key, value) pairs)

The data now looks like:

# A tibble: 12 x 3
   people fruit  count
   <chr>  <chr>  <dbl>
 1 mike   apple      1
 2 sue    apple      0
 3 bill   apple      3
 4 ted    apple      1
 5 mike   orange     0
 6 sue    orange     0
 7 bill   orange     3
 8 ted    orange     1
 9 mike   peach      6
10 sue    peach      1
11 bill   peach      1
12 ted    peach      0

Perfect! Let's get plotting. The basic geom to do a heatmap with ggplot2 is geom_tile to which we'll provide aesthetic x , y and fill .

library("ggplot2")
ggplot(hm, aes(x=x, y=y, fill=value)) + geom_tile() 

OK not too bad but we can do much better.

• For heatmaps, I like the black & white theme theme_bw() which gets rid of the grey background.

• I also like to use a palette from RColorBrewer (with direction = 1 to get the darker colors for higher values, or -1 otherwise). There is a lot of available palettes: Reds, Blues, Spectral, RdYlBu (red-yellow-blue), RdBu (red-blue), etc. Below I use "Greens". Run RColorBrewer::display.brewer.all() to see what the palettes look like.

• If you want the tiles to be squared, simply use coord_equal() .

• I often find the legend is not useful but it depends on your particular use case. You can hide the fill legend with guides(fill=F) .

• You can print the values on top of the tiles using geom_text (or geom_label ). It takes aesthetics x , y and label but in our case, x and y are inherited. You can also print higher values bigger by passing size=count as an aesthetic -- in that case you will also want to pass size=F to guides to hide the size legend.

• You can draw lines around the tiles by passing a color to geom_tile .

Putting it all together:

ggplot(hm, aes(x=fruit, y=people, fill=count)) +
  # tile with black contour
  geom_tile(color="black") + 
  # B&W theme, no grey background
  theme_bw() + 
  # square tiles
  coord_equal() + 
  # Green color theme for `fill`
  scale_fill_distiller(palette="Greens", direction=1) + 
  # printing values in black
  geom_text(aes(label=count), color="black") +
  # removing legend for `fill` since we're already printing values
  guides(fill=F) +
  # since there is no legend, adding a title
  labs(title = "Count of fruits per person")

To remove anything, simply remove the corresponding line.