在 R 中使用 Dplyr 按一个或多个变量分组

group_by()方法用于根据特定列中包含的组划分和隔离日期。所需的分组依据列被指定为该函数的参数。它可能包含多个列名。

句法：

group_by(col1, col2, …)

示例 1：按一个变量分组

R

# installing required libraries
library("dplyr")
  
# creating a data frame
data_frame <- data.frame(col1 = sample(6:7, 9 , replace = TRUE),
                         col2 = letters[1:3],
                         col3 = c(1,4,5,1,NA,NA,2,NA,2))
  
print ("Original DataFrame")
print (data_frame)
  
print ("Modified DataFrame")
  
# comouting difference of each group
data_frame%>%group_by(col1)

输出

[1] "Original DataFrame" 
col1 col2 col3 
1    6    a    1 
2    7    b    4 
3    7    c    5 
4    6    a    1 
5    7    b   NA 
6    6    c   NA 
7    6    a    2 
8    6    b   NA 
9    7    c    2 
[1] "Modified DataFrame" 
# A tibble: 9 x 3 
# Groups:   col1 [2]    
col1 col2   col3   
   
1     6 a         1 
2     7 b         4 
3     7 c         5 
4     6 a         1 
5     7 b        NA 
6     6 c        NA 
7     6 a         2 
8     6 b        NA 
9     7 c         2

分组也可以使用属于数据框的多个列来完成，只需将列的名称传递给函数。

示例 2：按多列分组

电阻

# installing required libraries
library("dplyr")
  
# creating a data frame
data_frame <- data.frame(col1 = sample(6:7, 9 , replace = TRUE),
                         col2 = letters[1:3],
                         col3 = c(1,4,5,1,NA,NA,2,NA,2))
  
print ("Original DataFrame")
print (data_frame)
  
print ("Modified DataFrame")
  
# comouting difference of each group
data_frame%>%group_by(col1,col2)

输出

[1] "Original DataFrame" 
col1 col2 col3
 1    7    a    1 
2    7    b    4 
3    7    c    5 
4    6    a    1 
5    6    b   NA 
6    6    c   NA 
7    7    a    2 
8    6    b   NA 
9    6    c    2 
[1] "Modified DataFrame" 
# A tibble: 9 x 3 
# Groups:   col1, col2 [6]    
col1 col2   col3   
   
1     7 a         1 
2     7 b         4 
3     7 c         5 
4     6 a         1 
5     6 b        NA 
6     6 c        NA 
7     7 a         2 
8     6 b        NA 
9     6 c         2