Introduction to Creating Faceted Histograms with R and ggplot2

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Creating faceted histograms is a common task in statistical data analysis. In this post, we will explore how to efficiently create 18 faceted histograms using the ggplot2 package in R from a wide-format dataset.

Problem Statement

The problem statement presents a scenario where we need to create a “faceted” histogram showing distributions for all of the groups in one frame from a large amount of data in a wide format. The data has 18 variables, each with its own distribution, and we want to visualize these distributions for different groups.

Solution Overview

To efficiently draw lots of graphs in R from data in a wide format, we will:

1. Reform the data into a “long” format.
2. Use one of the “apply” functions to create a list of ggplot objects.
3. Store the plots in this variable and plot them with different formats.

Step 1: Reformatting Data into Long Format

The wide-format dataset has each individual’s data represented by a row, with demographic information and 18 values for 18 variables. We will reform this data into a “long” format using the stack() function from base R.

# Identify those variables to be stacked (they all start with 'v')
sel <- grepl("^v", names(wide))
long <- data.frame(wide[!sel], stack(wide[sel]))
head(long)

Step 2: Creating a List of ggplot Objects

We will use the lapply() function to create a list of ggplot objects, each corresponding to one variable.

library(ggplot2) # to use ggplot...
plotList <- lapply(levels(long$ind), function(i)
  ggplot(data = subset(long, ind == i), aes(x = values))
    + geom_histogram(bins = 10)
    + facet_wrap(~ group, nrow = 2)
    + labs(caption = paste("Variable", i)))
names(plotList) <- levels(long$ind) # name the list elements for convenience

Step 3: Plotting the Faceted Histograms

To examine each of the 18 plots, we will turn off the ‘ask’ option using par(opar).

opar <- par(ask = TRUE)
plotList # This is the same as print(plotList)
par(opar) # turn off the 'ask' option

Step 4: Saving the Plots to File

To save the plots to file, we can use a for loop with the pdf() function.

for (v in levels(long$ind)) {
  fname <- paste(v, "pdf", sep = ".")
  fname <- file.path("~", fname) # change this to specify a directory
  pdf(fname, width = 6.5, height = 7, paper = "letter")
  print(plotList[[v]])
  dev.off()
}

Step 5: Alternative Solution using Lattice

Alternatively, we can use the lattice package to create a simpler faceted histogram.

library(lattice)
idx <- split(levels(long$ind), gl(3, 6, 18))
opar <- par(ask = TRUE)
for (i in idx) plot(histogram(~values | group + ind, data = long,
  subset = ind %in% i, as.table = TRUE))
par(opar)

Conclusion

In this post, we have explored how to efficiently create faceted histograms using the ggplot2 package in R from a wide-format dataset. We reformatted the data into a “long” format, used one of the “apply” functions to create a list of ggplot objects, stored the plots in this variable, and plotted them with different formats.

The resulting code can be used as a starting point for your own projects involving faceted histograms and wide-format datasets.

Last modified on 2024-09-29