Dear R user community,
I have many data.frames in a list, as follows (only one data.frame in the list of 21 shown for convenience):
> str(datal)
List of 21
$ BallitoRaw.DAT :'data.frame': 1083 obs. of 3 variables:
..$ Filename: Factor w/ 21 levels "BallitoRaw.DAT",..: 1 1 1 1 1 1 1 1 1 1 ...
..$ date :Class 'Date开发者_运维知识库' num [1:1083] 7318 7319 7320 7321 7322 ...
..$ temp : num [1:1083] NA 25.8 NA NA NA NA NA NA NA 24.4 ...
If I work on each data.frame in the list individually I can create a zoo object from temp and date, as such:
> BallitoRaw.zoo <- zoo(datal$BallitoRaw.DAT$temp, datal$BallitoRaw.DAT$date)
The zoo object looks like this:
> head(BallitoRaw.zoo)
1990-01-14 1990-01-15 1990-01-16 1990-01-17 1990-01-18 1990-01-19
NA 25.8 NA NA NA NA
How do I use llply or apply (or similar) to work on the whole list at once?
The output needs to go into a new list of data.frames, or a series of independent data.frames (each one named as in the zoo example above). Note that the date column, although a regular time series (days), contains missing dates (in addition to NAs for temps of existing dates); the missing dates will be filled by the zoo function. The output data.frame with the zoo object will thus be longer than the original one.
Help kindly appreciated.
makeNamedZoo <- function(dfrm){ dfrmname <- deparse(substitute(dfrm))
zooname <-dfrmname
assign(zooname, zoo(dfrm$temp, dfrm$date))
return(get(zooname)) }
ListOfZoos <- lapply(dflist, makeNamedZoo)
names(ListOfZoos) <- paste( sub("DAT$", "", names(dflist) ), "zoo", sep="")
Here is a simple test case:
df1 <- data.frame(a= letters[1:10], date=as.Date("2011-01-01")+0:9, temp=rnorm(10) )
df2 <- data.frame(a= letters[1:10], date=as.Date("2011-01-01")+0:9, temp=rnorm(10) )
dflist <- list(dfone.DAT=df1,dftwo.DAT=df2)
ListOfZoos <- lapply(dflist, makeNamedZoo)
names(ListOfZoos) <- paste( sub("DAT$", "", names(dflist) ), "zoo", sep="")
$dfone.zoo
2011-01-01 2011-01-02 2011-01-03 2011-01-04 2011-01-05 2011-01-06 2011-01-07
0.7869056 1.6523928 -1.1131432 1.2261783 1.1843587 0.2673762 -0.4159968
2011-01-08 2011-01-09 2011-01-10
-1.2686391 -0.4135859 -1.4916291
$dftwo.zoo
2011-01-01 2011-01-02 2011-01-03 2011-01-04 2011-01-05 2011-01-06 2011-01-07
0.7356612 -0.1263861 -1.6901240 -0.6441732 -1.4675871 2.3006544 1.0263354
2011-01-08 2011-01-09 2011-01-10
-0.8577544 0.6079986 0.6625564
This is an easier way to achieve what I needed:
tozoo <- function(x) zoo(x$temp, x$date)
data1.zoo <- do.call(merge, lapply(split(data1, data1$Filename), tozoo))
The result is a nice zoo object.
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