I am trying to merge
several data.frames
into one data.frame
. Since I have a whole list of files I am trying to do it with a loop structure.
So far the loop approach works fine. However, it looks pretty inefficient and I am wondering if there is a faster and easier approach.
Here is the scenario:
I have a directory with several .csv
files. Each file contains the same identifier which can be used as the merger variable. Since the files are rather 开发者_运维知识库large in size I thought to read each file one at a time into R instead of reading all files at once.
So I get all the files of the directory with list.files
and read in the first two files. Afterwards I use merge
to get one data.frame
.
FileNames <- list.files(path=".../tempDataFolder/")
FirstFile <- read.csv(file=paste(".../tempDataFolder/", FileNames[1], sep=""),
header=T, na.strings="NULL")
SecondFile <- read.csv(file=paste(".../tempDataFolder/", FileNames[2], sep=""),
header=T, na.strings="NULL")
dataMerge <- merge(FirstFile, SecondFile, by=c("COUNTRYNAME", "COUNTRYCODE", "Year"),
all=T)
Now I use a for
loop to get all the remaining .csv
files and merge
them into the already existing data.frame
:
for(i in 3:length(FileNames)){
ReadInMerge <- read.csv(file=paste(".../tempDataFolder/", FileNames[i], sep=""),
header=T, na.strings="NULL")
dataMerge <- merge(dataMerge, ReadInMerge, by=c("COUNTRYNAME", "COUNTRYCODE", "Year"),
all=T)
}
Even though it works just fine I was wondering if there is a more elegant way to get the job done?
You may want to look at the closely related question on stackoverflow.
I would approach this in two steps: import all the data (with plyr
), then merge it together:
filenames <- list.files(path=".../tempDataFolder/", full.names=TRUE)
library(plyr)
import.list <- llply(filenames, read.csv)
That will give you a list of all the files that you now need to merge together. There are many ways to do this, but here's one approach (with Reduce
):
data <- Reduce(function(x, y) merge(x, y, all=T,
by=c("COUNTRYNAME", "COUNTRYCODE", "Year")), import.list, accumulate=F)
Alternatively, you can do this with the reshape
package if you aren't comfortable with Reduce
:
library(reshape)
data <- merge_recurse(import.list)
If I'm not mistaken, a pretty simple change could eliminate the 3:length(FileNames)
kludge:
FileNames <- list.files(path=".../tempDataFolder/", full.names=TRUE)
dataMerge <- data.frame()
for(f in FileNames){
ReadInMerge <- read.csv(file=f, header=T, na.strings="NULL")
dataMerge <- merge(dataMerge, ReadInMerge,
by=c("COUNTRYNAME", "COUNTRYCODE", "Year"), all=T)
}
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