I have a list in R that contains several data frames. I want to iterate over the data frames and calculate the min/max of a value from the data frame. Here's the code that I have right now:
firstname = names(dats)[1]
xlim = c( min( dats[[firstname]][,xlab] ), max( dats[[firstname]][,xlab] ) )
for ( name in names(dats) ) {
xlim = c( min(xlim[1],dats[[name]][,xlab]), max(xlim[2],dats[[name]][,xlab]) )
}
This seems ugly to me, as it requires a lot of code to do something very simple. Is there a more canonical way to do this in R?
You can use lapply
to extract the xlab
column out of all the data-frames, and unlist
to combine into one vector, then take the min
or max
:
xlab <- 'a'
dats <- list( df1 = data.frame(a=sample(1:3), b = sample(11:13)),
df2 = data.frame(a=sample(1:3), b = sample(11:13)))
> min( unlist( lapply( dats, '[', xlab ) ) )
[1] 1
> max( unlist( lapply( dats, '[', xlab ) ) )
[1] 3
Can you combine the data frames from the list of data frames into one data frame? I would use the plyr
package and rbind.fill
, which would allow the data frames to have mismatched columns as long as the column of interest is named the same in all data frames.
library(plyr)
df.orig <- data.frame(one = rep(1:4, each = 4), two = 1:16)
df.list <- dlply(df.orig, "one")
df.new <- rbind.fill(df.list)
xlim <- with(df.new, c(min(two), max(two)))
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