I'm trying to take the moving average of a players fantasy points, based on their past performance against the same hand pitcher, over the past 3 games.
FP <- data.frame(player = c(rep("A",10), rep("B",10), rep("C",10)),
pitcher_hand = rep(c("R","L"),15),
fantasy_points = runif(30, min = 0, max = 25))
I know i can use rollapplyr from (zoo) to take moving averages, but here I need the conditional moving average, based on another column. For instance, the new column moving average for row 7 would be the average fantasy points for row 5, 3, and 1, since it was against the same handed pitcher. I've tried:
FP <- FP %>%
group_by(player) %>%
mutate(FP_L3 = rollapplyr(.,list(-(3:1)),function(x) mean(x[x[['pitcher_hand']]==pitcher_hand]),fill=NA))
How can this be done? I can do this in a big loop, iterating through every row in my dataframe and searching for correct matches, however I want to avoid this since my dataframe is quite large.
Include pitcher_hand in group_by -
library(dplyr)
FP %>%
group_by(player, pitcher_hand) %>%
mutate(FP_L3 = lag(rollmeanr(fantasy_points, 3, fill = NA))) %>%
ungroup
# player pitcher_hand fantasy_points FP_L3
# <chr> <chr> <dbl> <dbl>
# 1 A R 12.7 NA
# 2 A L 6.48 NA
# 3 A R 10.7 NA
# 4 A L 18.1 NA
# 5 A R 16.3 NA
# 6 A L 7.92 NA
# 7 A R 5.62 13.2
# 8 A L 22.5 10.8
# 9 A R 14.8 10.9
#10 A L 5.32 16.2
# … with 20 more rows