I got a data.frame ABC_Score
.
ABC_Score <- data.frame(Level = c("A", "A", "A", "B", "B", "C", "C",
"C", "C"), result = c(2, 3, 3, 7, 9, 18, 20, 17, 20))
What I need is the moving average of the result
per Level
.
Currently I have the moving average with the following script.
install.packages("TTR")
library(TTR)
`ABC_Score$MA` <- runMean(ABC_Score$result, 2)
Level result MA
1 A 2 NA
2 A 3 2.5
3 A 3 3.0
4 B 7 5.0
5 B 9 8.0
6 C 18 13.5
7 C 20 19.0
8 C 17 18.5
9 C 20 18.5
but here I need to specify the number of rows (result
) where the moving average will be calculated over. In this example 2
which is incorrect since results
from different Levels
are now mixed in the moving average.
How can the moving average automatically be calculated over the result
per Level
?
You could use group_by
and mutate
from dplyr
.
library(TTR)
library(dplyr)
ABC_Score <- data.frame(
Level = c("A", "A", "A", "B", "B", "C", "C", "C", "C"),
result = c(2, 3, 3, 7, 9, 18, 20, 17, 20))
ABC_Score %>% group_by(Level) %>% mutate(ra = runMean(result, 2))
# A tibble: 9 x 3
# Groups: Level [3]
Level result ra
<fctr> <dbl> <dbl>
1 A 2 NA
2 A 3 2.5
3 A 3 3.0
4 B 7 NA
5 B 9 8.0
6 C 18 NA
7 C 20 19.0
8 C 17 18.5
9 C 20 18.5
Using function on sinbgle vectors with levels of a factor is what the ave function does:
ABC_Score$MA <- with(ABC_Score, ave(result, Level, FUN=function(x)
TTR::runMean(x, n=2)) )
> ABC_Score
Level result MA
1 A 2 NA
2 A 3 2.5
3 A 3 3.0
4 B 7 NA
5 B 9 8.0
6 C 18 NA
7 C 20 19.0
8 C 17 18.5
9 C 20 18.5
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