How to usegroup_by() and summarise() method in R Language
The data transformation in R group_by() and summarise() methods are used collectively to group by variables of the data frame and reduce multiple values down to a single value. It is used to make the data more readable. The column name can be specified in R’s group_by() method. The data can be arranged in groups and then further summarised using the base aggregate methods in this package.
Syntax: group_by(col-name)
Syntax: group_by(col,..) %>% summarise(action)
The data in the data frame are grouped according to the col3 value. The count column indicates the number of records in each group; for instance, there are five rows with col3 = 0. The mean is then calculated for all the elements in a. particular group.
R
# Importing dplyrlibrary(dplyr)# Creating a data framedata_frame = data.frame( col1 = c(2,4,1,7,5,3,5,8), col2 = letters[1:8], col3 = c(0,1,1,1,0,0,0,0), col4 = c(9:16))print("Data Frame")print(data_frame)# Mutate data using group_by()# and summarise()data_frame_mutate <- data_frame %>% group_by(col3) %>% summarise( count = n(), mean_col1 = mean(col1) )print("Mutated Data Frame")print(data_frame_mutate) |
Output:
col1 col2 col3 col4
1 2 a 0 9
2 4 b 1 10
3 1 c 1 11
4 7 d 1 12
5 5 e 0 13
6 3 f 0 14
7 5 g 0 15
8 8 h 0 16
[1] "Mutated Data Frame"
# A tibble: 2 x 3
col3 count mean_col1
<dbl> <int> <dbl>
1 0 5 4.6
2 1 3 4
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