CODEWITHSUNDEEP
rdplyr
prog
prog

Reputation: 1073

get previous value to the current value

How can i get the previous value of each group in a new column C and the starting value for each group will be empty as it does not have previous value of respective group!

Can dplyr can perform this?

Code:

df <- data.frame(A = c('a1','a1','b1','b1','b1','c2','d2','d2'),
                B = c("2017-02-20","2018-02-14","2017-02-06","2017-02-27","2017-02-29","2017-02-28","2017-02-09","2017-02-10"))

Dataframe:

A       B         
a1   2017-02-20
a1   2018-02-14 
b1   2017-02-06
b1   2017-02-27 
b1   2017-02-29 
c2   2017-02-28
d2   2017-02-09
d2   2017-02-10

Expected Output

A       B         C
a1   2017-02-20
a1   2018-02-14 2017-02-20
b1   2017-02-06
b1   2017-02-27 2017-02-06
b1   2017-02-29 2017-02-27
c2   2017-02-28
d2   2017-02-09
d2   2017-02-10 2017-02-09

Upvotes: 0

Views: 390

Answers (1)

MDEWITT
MDEWITT

Reputation: 2368

You could use the lag function from dplyr:

df <- data.frame(A = c('a1','a1','b1','b1','b1','c2','d2','d2'),
                 B = c("2017-02-20","2018-02-14","2017-02-06",
                       "2017-02-27","2017-02-29","2017-02-28",
                                    "2017-02-09","2017-02-10"))


library(dplyr)
df %>% 
  group_by(A) %>% 
  mutate(C = lag(B, 1, default = NA))

This will apply the lag function for each group of "A"

Output:

# A tibble: 8 x 3
# Groups:   A [4]
  A     B          C         
  <fct> <fct>      <fct>     
1 a1    2017-02-20 NA        
2 a1    2018-02-14 2017-02-20
3 b1    2017-02-06 NA        
4 b1    2017-02-27 2017-02-06
5 b1    2017-02-29 2017-02-27
6 c2    2017-02-28 NA        
7 d2    2017-02-09 NA        
8 d2    2017-02-10 2017-02-09

Upvotes: 1

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