Pie plot criticism
Before the explanations, it is worth to mention that pie charts, even very popular, have been widely criticized. As they are more difficult to read than other chart alternatives, are known to be misleading statistical graphs. The following plots represent the same variables displayed with pie charts and with bar plots.
As you can see in the previous example, bar plots are easier to read than pie charts. Nonetheless, pie charts can be useful in many situations, for instance, where the data is very unbalanced.
How to draw a pie chart in R?
A circle chart can be created with the
pie function in base R. Even though there exists more packages to create pie charts, like
ggplot2, in this tutorial we will review how to create circle chart with the
pie function and the
PieChart function of the
lessR package, to display percentages.
The pie() R function
pie function allows you to create a pie chart in R. Consider, for instance, that you want to create a piechart of the following variable, that represents the count of some event:
count <- c(7, 25, 16, 12, 10, 30)
The code for a pie chart in R is as follows. Note that you can customize the size of the pie (from -1 to 1) with the
radius argument, that by default takes the value 0.8.
You can also modify the direction of the pie with the
clockwise argument, that by default is
pie(count, clockwise = TRUE)
However, you may have noticed that the plot doesn’t display the corresponding value of each slice. To solve this issue you can pass the vector to the
labels argument as follows.
pie(count, labels = count)
If preferred, you can add a character vector with the names you desire to represent each slice:
pie(count, labels = c("0-15", "16-30", "31-45", "46-60", "61-75", "76-90"))
In addition, you can modify the color of the graph with the
col argument. In the following block of code we show you how to use different color palettes. Note that the
cex argument allows you to modify the size of the labels.
par(mfrow = c(1, 3)) pie(count, labels = count, col = 1:6, cex = 2) pie(count, labels = count, col = rainbow(6), cex = 2) pie(count, labels = count, col = topo.colors(6), cex = 2) par(mfrow = c(1, 1))
However, the best pie chart color palettes may be the ones of the
brewer.pal function of the
# install.packages("RColorBrewer") library(RColorBrewer) color <- brewer.pal(length(count), "Set2") pie(count, labels = count, col = color)
You can also specify a vector of colors for the border of each slice. If you want the color to be equal to the color of the area of the slice you can type:
pie(count, labels = count, col = color, border = color)
If you want to modify the line type of the borders of the plot you can make use of the
pie(count, labels = count, col = color, lty = 2)
Furthermore, you can add shading lines with the
density argument. The greater the value, the greater number of lines to be displayed. Note that the
angle argument can be used to modify the angle of the lines.
pie(count, labels = count, col = color, density = 50, angle = 45)
Finally, you can also customize the number of polygons used to create the chart. By default, the
edges argument is 200, but if you specify a lower value you can create something like the following:
pie(count, labels = count, edges = 10)
Pie chart in R with percentage
Circle charts are very useful to show percentages, but the
pie function doesn’t allow you to automatically display them. In order to show percentages for the sample vector (as the sum of the elements is equal to 100), you can type:
pie(count, labels = paste0(count, "%"))
Nevertheless, a more generic approach is to calculate the corresponding percentages. For that purpose. consider the following vector:
count_2 <- c(15, 27, 25, 10)
As in this case, the sum of the components of the vector is not equal to 100, the corresponding percentage is different to the corresponding number of the vector. In the next block of code we show you how to calculate the percentages. Note that the
round function allows you to modify the number of decimals.
pie_labels <- paste0(round(100 * count_2/sum(count_2), 2), "%") pie(count_2, labels = pie_labels)
However, if you also want to display the numbers or labels of the original vector you could write:
pie_labels <- paste0(count_2, " = ", round(100 * count_2/sum(count_2), 2), "%") pie(count_2, labels = pie_labels)
An alternative to display percentages on the pie chart is to use the
PieChart function of the
lessR package, that shows the percentages in the middle of the slices. However, the input of this function has to be a categorical variable (or numeric, if each different value represents a category, as in the example) of a data frame, instead of a numeric vector. Recall to type
help(PieChart) for additional information.
# install.packages("lessR) library(lessR) # Data frame with the new variable my_data <- data.frame(x = c(rep(count_2, count_2), # 15 times 15 rep(count_2, count_2), # 27 times 27 rep(count_2, count_2), # 25 times 25 rep(count_2, count_2))) # 10 times 10 PieChart(x, hole = 0, values = "%", data = my_data, fill = 1:4, main = "")
Pie chart of categorical data
Consider, for instance, that you want to create a circle chart with the corresponding percentage of males and females registrered in some event. You have the following data:
gender_var <- factor(c(rep("Male", 10), rep("Female", 20))) gender_var
Male Male Male Male Male Male Male Male Male Male Female Female Female Female Female Female Female Female Female Female Female Female Female Female Female Female Female Female Female Female Levels: Female Male
Hence, as you have a character variable, you can use the
table function to count the number of males and females of the character vector and pass the output to the
gender_table <- table(gender_var) pie(gender_table)
An alternative is to use the
PieChart function, but as we pointed out before, you need to create a data frame with a character or factor variable:
gender <- data.frame(gend = gender_var) # install.packages("lessR") library(lessR) PieChart(gend, hole = 0, values = "%", data = gender, fill = c("lightblue", "pink"), main = "")
Adding a legend
In order to create a pie chart in R with legend you need to use the
legend function. As an example, if you want to display a legend in the top left of the image you can execute the following code:
count_3 <- c(20, 50, 30) # sum(count_3) # 100 pie(count_3, labels = paste0(count_3, "%")) legend("topleft", legend = c("Theatre", "Series", "Movies"), fill = c("white", "lightblue", "mistyrose"))
3D pie chart
In this final section you will learn how to draw a 3D pie chart in R. For that purpose, you will need to install the
plotrix package, that contains the
pie3D function. The code to draw a 3D pie chart in R is the following:
# install.packages("plotrix") library(plotrix) num_data <- c(65, 35) pie3D(num_data)
Note that by default the function doesn’t display labels, so you will need to indicate them in the
pie3D(num_data, labels = num_data)
In addition, you can explode the pie with the
pie3D(num_data, labels = num_data, explode = 0.25)
Finally, as in other plots, you can customize several graphical parameters of the final plot, as the colors, colors of the labels or the border color, among others. Recall to type
?pie3D for additional details.
pie3D(num_data, labels = num_data, col = 2:3, labelcol = "red", border = "white")