I have a data frame that includes multiple rows of data for each time and would like to group by time to create a condensed data frame. Columns a and b are cumulative sums from other columns and should maintain the values from the row with the highest x for each time group rather than be sums or averages.
x time group value cumsum_A cumsum_B
1 0 A 0 0 0
2 0 B 0 0 0
3 0 A 0 0 0
4 1 A 0 0 0
5 1 B 1 0 1
6 1 B 0 0 1
7 2 B 1 0 2
8 2 A 1 1 2
9 2 A 1 2 2
10 2 A -1 1 2
11 3 A 0 1 2
12 3 B 1 1 3
The ideal result would be the following:
x time group value cumsum_A cumsum_B
3 0 A 0 0 0
6 1 B 0 0 1
10 2 A -1 1 2
12 3 B 1 1 3
An option would be to group by 'time', 'group' and slice the rows where the value of 'x is max (which.max)
library(dplyr)
df1 %>%
group_by(time, group) %>%
slice(which.max(x))