Get the summary of dataset in R using Dply

In this article, we will discuss how to get a summary of the dataset in the R programming language using Dplyr package. To get the summary of a dataset summarize() function of this module is used. This function basically gives the summary based on some required action for a group or ungrouped data, which in turn helps summarize the dataset.

Syntax: summarize(action)

The dataset in use: bestsellers3

Here, action can be any operation to be performed on grouped data, it can be frequency count, mean, average, etc.

Example: Summarize the dataset using summarize()

R

library(dplyr)

data<-read.csv("bestsellers.csv")
data %>% group_by(Genre) %>%
  summarize(n())

Output:

# A tibble: 2 x 2
 Genre       `n()`
 <fct>       <int>
1 Fiction        82
2 Non Fiction   117

Summarize ungrouped dataset

It is also possible to summarize ungrouped data. There are three possible functions that can be used for this.

• summarize_all().
• summarize_at().
• summarize_if().

summarize_all():

summarize_all() function summarizes all the columns based on the action to be performed.

Syntax: summarize_all(action)

R

library(dplyr)

data<-read.csv("bestsellers.csv")
data %>% group_by(Genre) %>%
  summarize_all(mean)

Output:

summarize_at():

summarize_at() function is used to apply a required action to some specific columns and generate a summary based on that

Syntax: summarize_at(vector_of_columns,action)

R

library(dplyr)

data<-read.csv("bestsellers.csv")
data %>% group_by(Genre) %>%
  summarize_at(c('User.Rating','Price'),mean)

Output:

summarize_if():

summarize_if() function is used to get dataset summary if a certain condition is specified.

Syntax: summarize_if(condition, action)

R

library(dplyr)

data<-read.csv("bestsellers.csv")
data %>% group_by(Genre) %>%
  summarize_if(is.numeric, mean)

Output: