Although I have searched a lot on stackoverflow I could not find an answer for my problem. It is quite tricky because I want only to compare row values in one column given that 3 conditions are fulfilled. I want to compare 2 row values within the same column (Result) if and only if they they are in the same treatment, group and period. My goal is then to evaluate whether player 1 and player 2 scored the same result (1 = if yes, 0= if no). In total, I have five columns: Treatment; Player; Group; Result; Period. Below the table.
df
T Player Group Result Period Same Result
1 1 6 20 1 1
1 2 6 20 1 1
1 1 5 20 1 0
1 2 1 20 1 1
1 1 1 20 1 1
1 2 2 20 1 1
1 1 2 20 1 1
1 2 4 120 1 1
1 1 3 20 1 1
1 2 3 20 1 1
1 1 4 120 1 1
1 2 5 120 1 0
2 1 2 20 1 1
2 2 1 120 1 1
2 1 4 20 1 0
2 2 5 20 1 1
2 1 6 20 1 1
2 2 2 20 1 1
2 1 3 20 1 1
2 2 3 20 1 1
2 1 1 120 1 1
2 2 6 20 1 1
2 1 5 20 1 1
2 2 4 120 1 0
Any ideas? Help would be very much appreciated. Thanks a lot in advance!
With tidyverse you can do the following. First, group_by your 3 columns of interest: treatment, group, and period. Then, use n_distinct for each group to see if only 1 unique result for that group.
library(tidyverse)
df %>%
group_by(T, Group, Period) %>%
mutate(Same_Result_2 = +(n_distinct(Result) == 1))
Alternative with data.table package:
library(data.table)
setDT(df)
df[, Same_Result_3 := if(uniqueN(Result)==1) 1 else 0, by=.(T, Group, Period)]
Output
Same_Result_1 is value provided in example. Same_Result_2 is determined by above tidyverse code.
# A tibble: 24 x 7
# Groups: T, Group, Period [12]
T Player Group Result Period Same_Result_1 Same_Result_2
<int> <int> <int> <int> <int> <int> <int>
1 1 1 6 20 1 1 1
2 1 2 6 20 1 1 1
3 1 1 5 20 1 0 0
4 1 2 1 20 1 1 1
5 1 1 1 20 1 1 1
6 1 2 2 20 1 1 1
7 1 1 2 20 1 1 1
8 1 2 4 120 1 1 1
9 1 1 3 20 1 1 1
10 1 2 3 20 1 1 1
11 1 1 4 120 1 1 1
12 1 2 5 120 1 0 0
13 2 1 2 20 1 1 1
14 2 2 1 120 1 1 1
15 2 1 4 20 1 0 0
16 2 2 5 20 1 1 1
17 2 1 6 20 1 1 1
18 2 2 2 20 1 1 1
19 2 1 3 20 1 1 1
20 2 2 3 20 1 1 1
21 2 1 1 120 1 1 1
22 2 2 6 20 1 1 1
23 2 1 5 20 1 1 1
24 2 2 4 120 1 0 0