How to use the group_map method In R Language

Method 1: Using mutate method

The group_map() method can also apply a function to each group in the tibble. The method returns the number of tibbles equivalent to the number of groups returned. It has the following syntax :

Syntax: group_map(.data, .f, …, .keep = FALSE)

Arguments :

.data – A grouped tibble

.f – The function to be applied

The following code snippet illustrates the usage of the group_map() method on a grouped tibble, wherein user-defined entries are grouped based on column x values. The sum of column y values is computed against each tibble group value. A user-defined sum_y function is declared and defined, which returns the output as the sum of the input vector values.

R

# Importing dplyr 
library(dplyr) 
  
# Creating a tibble 
data = tibble( 
  x = c(2,4,5,6,2,5,6,6,2,6),  
  y = 1:10) 
print("Data") 
print(data) 
  
sum_y = function(vector) { 
  return(tibble::tibble(sum = sum(vector))) 
} 
  
# Grouping the data by x and  
# then computing the group wise 
# sum using y column 
data %>% 
  group_by(x) %>% 
  group_map(~sum_y(.x$y))

Output:

[1] "Data"
> print(data)
# A tibble: 10 × 2
       x     y
   <dbl> <int>
 1     2     1
 2     4     2
 3     5     3
 4     6     4
 5     2     5
 6     5     6
 7     6     7
 8     6     8
 9     2     9
10     6    10

[[1]]
# A tibble: 1 x 1
    sum
  <int>
1    15

[[2]]
# A tibble: 1 x 1
    sum
  <int>
1     2

[[3]]
# A tibble: 1 x 1
    sum
  <int>
1     9

[[4]]
# A tibble: 1 x 1
    sum
  <int>
1    29

Apply a function to each group using Dplyr in R

In this article, we are going to learn how to apply a function to each group using dplyr in the R programming language.

The dplyr package in R is used for data manipulations and modifications. The package can be downloaded and installed into the working space using the following command :

install.packages("dplyr")

Tags:

#R Language

Method 1: Using mutate method

How to use the group_map method In R Language

R

Apply a function to each group using Dplyr in R

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