CODEWITHSUNDEEP
rdplyr
Wafa
Wafa

Reputation: 89

Create a conditional timeline based on events in R

I have data where the 'Law' variable indicates changes in legislation, in different places ('Place'):

Person  Place  Year  Law
1         A    1990   0
2         A    1991   1
3         A    1992   1
4         B    1990   0
5         B    1991   0
6         B    1992   1
7         B    1993   1
8         B    1993   1
9         B    1993   1
10        B    1992   1

Basically the law was implemented in place A in 1991 and remained in force for all subsequent time periods. It was implemented in place B in 1992 and remained in force, & so on.

I would like to create a new variable that takes on a value of 0 for the year the law was implemented, 1 for 1 year after, 2 for 2 years after, -1 for the year before, -2 for 2 years before, and so on.

I need the final dataframe to look like:

Person  Place  Year  Law  timeline 
1         A    1990   0     -1
2         A    1991   1      0
3         A    1992   1      1
4         B    1990   0     -2
5         B    1991   0     -1
6         B    1992   1      0
7         B    1993   1      1
8         B    1993   1      2
9         B    1993   1      2
10        B    1992   1      1

I have tried:

library(dplyr)
df %>% 
 group_by(Place) %>%
 arrange(Year) %>%
 mutate(timeline = rank(Law))

but it's not working like I need. What am I doing wrong? Can I do this in dplyr or do I need to create a complex for loop?

Upvotes: 3

Views: 171

Answers (2)

Onyambu
Onyambu

Reputation: 79288

using data.table

library(data.table)
setDT(dat)[,timeline:=sequence(.N)-which.min(!Law),by=Place]
dat
   Person Place Year Law timeline
1:      1     A 1990   0       -1
2:      2     A 1991   1        0
3:      3     A 1992   1        1
4:      4     B 1990   0       -2
5:      5     B 1991   0       -1
6:      6     B 1992   1        0
7:      7     B 1993   1        1

Using base r:

transform(dat,timeline=ave(Law,Place,FUN=function(x)1:length(x)-which.min(!x)))
  Person Place Year Law timeline
1      1     A 1990   0       -1
2      2     A 1991   1        0
3      3     A 1992   1        1
4      4     B 1990   0       -2
5      5     B 1991   0       -1
6      6     B 1992   1        0
7      7     B 1993   1        1

Upvotes: 0

akuiper
akuiper

Reputation: 215047

You can subtract the row_numer by the index where the Law is implemented:

df %>% 
    arrange(Year) %>% 
    group_by(Place) %>% 
    mutate(timeline = row_number() - which(diff(Law) == 1) - 1) %>% 
    arrange(Place)

# A tibble: 7 x 5
# Groups:   Place [2]
#  Person Place  Year   Law timeline
#   <int> <fct> <int> <int>    <dbl>
#1      1 A      1990     0      -1.
#2      2 A      1991     1       0.
#3      3 A      1992     1       1.
#4      4 B      1990     0      -2.
#5      5 B      1991     0      -1.
#6      6 B      1992     1       0.
#7      7 B      1993     1       1.

Upvotes: 1

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