Re: [R] Apply pmax to dataframe with different args based on dataframe factor
damn, that's pretty clever. +1
thanks
On Thu, Feb 9, 2012 at 8:11 PM, ilai wrote:
> Your attempt was just overly complicated. All you needed was
>
> threshold <- c( .2 , .4 , .5 )[ df$track ]
> df$value <- pmax(threshold, df$value)
> df # desired outcome
>
> Cheers
>
> On Thu, Feb 9, 2012 at 3:56 PM, Idris Raja wrote:
> > # I have a dataframe in the following form:
> >
> > track <- c(rep('A', 3), rep('B', 4), rep('C', 4))
> > value <- c(0.15, 0.25, 0.35, 0.05, 0.99, 0.32, 0.13, 0.80, 0.75, 0.60,
> 0.44)
> > df <- data.frame(track=factor(track), value=value)
> >
> > #> print(df)
> > #track value
> > #1 A 0.15
> > #2 A 0.25
> > #3 A 0.35
> > #4 B 0.05
> > #5 B 0.99
> > #6 B 0.32
> > #7 B 0.13
> > #8 C 0.80
> > #9 C 0.75
> > #10 C 0.60
> > #11 C 0.44
> >
> >
> > # If any of the values are below a threshold value, I want to replace it
> > with the
> > # threshold value. The twist is that there is a different threshold value
> > for
> > # every track.
> >
> > # I tried something like this, but it's not working
> >
> > threshold <- list()
> > threshold['A'] <- 0.2
> > threshold['B'] <- 0.4
> > threshold['C'] <- 0.5
> >
> >
> > for (track in levels(df$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]]
> >
> > __
> > 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.
>
[[alternative HTML version deleted]]
__
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Re: [R] Apply pmax to dataframe with different args based on dataframe factor
Your attempt was just overly complicated. All you needed was
threshold <- c( .2 , .4 , .5 )[ df$track ]
df$value <- pmax(threshold, df$value)
df # desired outcome
Cheers
On Thu, Feb 9, 2012 at 3:56 PM, Idris Raja wrote:
> # I have a dataframe in the following form:
>
> track <- c(rep('A', 3), rep('B', 4), rep('C', 4))
> value <- c(0.15, 0.25, 0.35, 0.05, 0.99, 0.32, 0.13, 0.80, 0.75, 0.60, 0.44)
> df <- data.frame(track=factor(track), value=value)
>
> #> print(df)
> #track value
> #1 A 0.15
> #2 A 0.25
> #3 A 0.35
> #4 B 0.05
> #5 B 0.99
> #6 B 0.32
> #7 B 0.13
> #8 C 0.80
> #9 C 0.75
> #10 C 0.60
> #11 C 0.44
>
>
> # If any of the values are below a threshold value, I want to replace it
> with the
> # threshold value. The twist is that there is a different threshold value
> for
> # every track.
>
> # I tried something like this, but it's not working
>
> threshold <- list()
> threshold['A'] <- 0.2
> threshold['B'] <- 0.4
> threshold['C'] <- 0.5
>
>
> for (track in levels(df$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]]
>
> __
> 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.
__
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.
[R] 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]]
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
