R dplyr group_by & summarize Functions don’t Work Properly (Example)

In this R tutorial you’ll learn how to make the group_by and summarize functions of the dplyr package work properly.

Table of contents:

Let’s start right away!

Creation of Example Data

Consider the example data below:

data <- data.frame(value = 1:12,    # Create example data
                   group = factor(rep(letters[1:3], each = 4)))
data                                # Print example data

Table 1 shows the structure of our example data: It consists of twelve rows and two variables. The column value contains different numeric values and the column group contains a group indicator.

Example 1: Apply group_by & summarize Functions After Loading plyr Package

This example illustrates why the group_by and summarize functions might not work as expected.

We first need to install and load the dplyr package, in order to use the corresponding functions:

install.packages("dplyr")           # Install dplyr package
library("dplyr")                    # Load dplyr package

Next, we also have to install and load the plyr package:

install.packages("plyr")            # Install & load plyr package
library("plyr")

Now, we might try to apply the group_by and summarize functions of the dplyr package as shown below:

data %>%                            # plyr version
  group_by(group) %>% 
  summarize(mean = mean(value))
#   mean
# 1  6.5

As you can see based on the output of the RStudio console, the previous R code returned only the mean of the entire variable. However, we expected a group version…

The reason for this is that the plyr package also contains a function that is called summarize. Since we have loaded the plyr package after the dplyr package, the R programming language automatically used the plyr version of the function.

So how can we solve this problem? That’s what I’ll explain next!

Example 2: Apply group_by & summarize Functions with Explicit dplyr Specification

In Example 2, I’ll illustrate how to handle the issue of unexpected outputs when using the group_by and summarize functions of the dplyr package.

As explained in the previous example, the problem is that R automatically uses the plyr version of the summarize function.

We can tell R to use the dplyr version by specifying the name of the package (i.e. dplyr::) in front of the summarize function.

Have a look at the R code below:

data %>%                            # dplyr version
  group_by(group) %>% 
  dplyr::summarize(mean = mean(value))
# # A tibble: 3 x 2
#   group  mean
#   <fct> <dbl>
# 1 a       2.5
# 2 b       6.5
# 3 c      10.5

As you can see, now the group_by and summarize functions work fine.

Video & Further Resources

Have a look at the following video of my YouTube channel. In the video, I’m explaining the R programming codes of the present tutorial in the R programming language.

The YouTube video will be added soon.

In addition, you may read the related articles on this website. Please find a selection of articles about dplyr below.

• Rank Functions of dplyr Package
• mutate & transmute R Functions of dplyr Package (2 Example Codes)
• select & rename R Functions of dplyr Package
• bind_rows & bind_cols R Functions of dplyr Package
• R Commands List (Examples)
• All R Programming Tutorials

Summary: In this tutorial you have learned how to make the dplyr group_by and summarize functions work in the R programming language. Note that similar errors may occur when using other packages where functions have the same name such as ggplot2.

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