I have the following dataframe called df (dput below):
value
1 -4
2 -3
3 -2
4 -1
5 0
6 1
7 2
8 3
9 -3
10 -2
11 -1
12 0
13 1
14 2
15 3
16 -3
17 -2
18 -1
19 0
20 1
21 2
22 -2
23 -1
24 0
25 1
26 2
27 3
28 4
I would like to group the sequence column 'value' based on when a positive value becomes its negative value, when that happens it was a group. So row 8 has value 3 and row 9 has value -3 which means the positive value changed in its negative value so all rows to row 8 are a group. The shift also happens by row 15 and 16 and so on. Here is the desired output:
value group
1 -4 1
2 -3 1
3 -2 1
4 -1 1
5 0 1
6 1 1
7 2 1
8 3 1
9 -3 2
10 -2 2
11 -1 2
12 0 2
13 1 2
14 2 2
15 3 2
16 -3 3
17 -2 3
18 -1 3
19 0 3
20 1 3
21 2 3
22 -2 4
23 -1 4
24 0 4
25 1 4
26 2 4
27 3 4
28 4 4
So I was wondering if anyone knows how to group this sequence based on a positive to its negative value shift?
dput of df:
df <- structure(list(value = c(-4, -3, -2, -1, 0, 1, 2, 3, -3, -2,
-1, 0, 1, 2, 3, -3, -2, -1, 0, 1, 2, -2, -1, 0, 1, 2, 3, 4)), class = "data.frame", row.names = c(NA,
-28L))
CodePudding user response：
Edit: Updated the answer to stabilise the output.
I think you could use
library(dplyr)
df %>%
group_by(grp = cumsum(coalesce(value == -lag(value, n = 1), TRUE)))
This returns
# A tibble: 28 x 2
# Groups: grp [4]
value grp
<dbl> <int>
1 -4 1
2 -3 1
3 -2 1
4 -1 1
5 0 1
6 1 1
7 2 1
8 3 1
9 -3 2
10 -2 2
11 -1 2
12 0 2
13 1 2
14 2 2
15 3 2
16 -3 3
17 -2 3
18 -1 3
19 0 3
20 1 3
21 2 3
22 -2 4
23 -1 4
24 0 4
25 1 4
26 2 4
27 3 4
28 4 4
I used group_by to do the grouping, replace it with mutate if you just need a new column.