Visualizing usability data with a heat map in R

_uxr-heatmap.md

This example shows how to create a heat map in R to visualize task success data.

data.csv

heatmap.R

library(ggplot2)
library(reshape)

# Change this to point to your directory
setwd('~/Desktop/uxr-heatmap')

# Read in data
data.df <- read.csv('data.csv')
num.users <- dim(data.df)[1]
num.tasks <- dim(data.df)[2]

# When R imports the data, spaces in the header row are replaced with "."... let's revert that
task.names <- gsub(".", " ", names(data.df), fixed=TRUE)

# Create a data frame with the total number of successes for each task
total <- data.frame(
  task=task.names,
  value=colSums(data.df)
)

# Reshape the data... ggplot2 uses long format, which has a column for variable types and a column for those variables' values
total.m <- melt(total)

#### Steps to create heat map ####

# 1. Create heat map
dark.orange <- '#d66a00'
light.gray <- '#f8f8f8'
p <- ggplot(total.m, aes(x=task, y=variable, label=value)) +
  geom_tile(aes(fill=value), colour='white') +
  scale_fill_gradient(low=dark.orange, high=light.gray, limits=c(0, num.users))

# 2. Add text
p <- p + geom_text()

# 3. Re-size the plot
p <- p + coord_fixed(ratio=2/num.tasks)

# 4. Give finishing touches
p <- p + labs(title='Number of users that successfully completed each task') +
  theme(
    panel.background=element_blank(),
    axis.title.x=element_blank(),
    axis.title.y=element_blank(),
    axis.ticks.x=element_blank(),
    axis.ticks.y=element_blank(),
    axis.text.y=element_blank()
  )
  
# 5. Save the plot
ggsave(filename='heatmap.png', width=6, height=3)

total.csv