Reputation: 1078
I would like to do the following thing:
id calendar_week value
1 1 10
2 2 2
3 2 -2
4 2 3
5 3 10
6 3 -10
The output which I want is the list of id (or the rows) which have a positiv to negative match for a given calendar_week -> which means I want for example the id 2 and 3 because there is a match of -2 to 2 in Calendar week 2. I don't want id 4 because there is no -3 value in calendar week 2 and so on.
output:
id calendar_week value
2 2 2
3 2 -2
5 3 10
6 3 -10
Upvotes: 0
Views: 537
Reputation: 14764
Could also do:
library(dplyr)
df %>%
group_by(calendar_week, ab = abs(value)) %>%
filter(n() > 1) %>% ungroup() %>%
select(-ab)
Output:
# A tibble: 4 x 3
id calendar_week value
<int> <int> <int>
1 2 2 2
2 3 2 -2
3 5 3 10
4 6 3 -10
Given your additional clarifications, you could do:
df %>%
group_by(calendar_week, value) %>%
mutate(idx = row_number()) %>%
group_by(calendar_week, idx, ab = abs(value)) %>%
filter(n() > 1) %>% ungroup() %>%
select(-idx, -ab)
On a modified data frame:
id calendar_week value
1 1 1 10
2 2 2 2
3 3 2 -2
4 3 2 2
5 4 2 3
6 5 3 10
7 6 3 -10
8 7 4 10
9 8 4 10
This gives:
# A tibble: 4 x 3
id calendar_week value
<int> <int> <int>
1 2 2 2
2 3 2 -2
3 5 3 10
4 6 3 -10
Upvotes: 2
Reputation: 34441
If as stated in the comments only a single match is required you could try:
library(dplyr)
df %>%
group_by(calendar_week, nvalue = abs(value)) %>%
filter(!duplicated(value)) %>%
filter(sum(value) == 0) %>%
ungroup() %>%
select(-nvalue)
id calendar_week value
<int> <int> <int>
1 2 2 2
2 3 2 -2
3 5 3 -10
4 6 3 10
Upvotes: 1
Reputation: 2399
Using tidyverse
:
library(tidyverse)
df %>%
group_by(calendar_week) %>%
nest() %>%
mutate(values = map_chr(data, ~ str_c(.x$value, collapse = ', '))) %>%
unnest() %>%
filter(str_detect(values, as.character(-value))) %>%
select(-values)
Output :
calendar_week id value
<dbl> <int> <dbl>
1 2 2 2
2 2 3 -2
3 3 5 10
4 3 6 -10
Upvotes: 1