R help - Feb 2012 - Apply pmax to dataframe with different args based on dataframe factor

# 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]]

Your attempt was just overly complicated. All you needed was

threshold <- c( .2 , .4 , .5 )[ df$track ]
df$value <- pmax(threshold, df$value)
df # desired outcome

Cheers

On Thu, Feb 9, 2012 at 3:56 PM, Idris Raja <idris.raja at gmail.com>
wrote:
> # 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]]
>
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