# I have a dataframe in the following form:
track <- c(rep('A', 3), rep('B', 4), rep('C', 4))
value <- c(0.15, 0.25, 0.35, 0.05, 0.99, 0.32, 0.13, 0.80, 0.75, 0.60, 0.44)
df <- data.frame(track=factor(track), value=value)
#> print(df)
#track value
#1 A 0.15
#2 A 0.25
#3 A 0.35
#4 B 0.05
#5 B 0.99
#6 B 0.32
#7 B 0.13
#8 C 0.80
#9 C 0.75
#10 C 0.60
#11 C 0.44
# If any of the values are below a threshold value, I want to replace it
with the
# threshold value. The twist is that there is a different threshold value
for
# every track.
# I tried something like this, but it's not working
threshold <- list()
threshold['A'] <- 0.2
threshold['B'] <- 0.4
threshold['C'] <- 0.5
for (track in levels(df$track)){
df[df$track==track,]$outcome <- pmax(df[df$track==track,]$outcome,
threshold[track])
}
# Warning messages:
# 1: In is.na(mmm) : is.na() applied to non-(list or vector) of type 'NULL'
# 2: In is.na(mmm) : is.na() applied to non-(list or vector) of type 'NULL'
# 3: In is.na(mmm) : is.na() applied to non-(list or vector) of type 'NULL'
#******************
# Desired Results:
#> print(df)
#track value
#1 A 0.20 # value changed
#2 A 0.25
#3 A 0.35
#4 B 0.40 # value changed
#5 B 0.99
#6 B 0.40 # value changed
#7 B 0.40 # value changed
#8 C 0.80
#9 C 0.75
#10 C 0.60
#11 C 0.50 # value changed
# Any ideas? Thanks for reading.
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
