I'm trying to read a text file with different row lengths:
1
1 2
1 2 3
1 2 3 4
1 2 3 4 5
1 2 3 4 5 6
1 2 3 4 5 6 7
1 2 3 4 5 6 7 8
To overcome this problem, I'm using the argument fill=TRUE in read.table, so:
data<-read.table("test",sep="\t",fill=TRUE)
Unfortunately, to assess the maximum row length, read.table reads only the first 5 lines of the file, and generates an object looking like this:
data
V1 V2 V3 V4 V5
1 1 NA NA NA NA
2 1 2 NA NA NA
3 1 2 3 NA NA
4 1 2 3 4 NA
5 1 2 3 4 5
6 1 2 3 4 5
7 6 NA NA NA NA
8 1 2 3 4 5
9 6 7 NA NA NA
10 1 2 3 4 5
11 6 7 8 NA NA
Is there a way to force re开发者_如何学Cad.table to scroll over the whole file to assess the maximum row length? I know a possible solution would be to provide the column number, like:
data<-read.table("test",sep="\t",fill=TRUE,col.names=c(1:8))
But since I have a lot of files, I wanted to assess this automatically within R. Any suggestion? :-)
EDIT: the original file doesn't contain progressive numbers, so this is not a solution:
data1<-read.table("test",sep="\t",fill=TRUE)
data2<-read.table("test",sep="\t",fill=TRUE,col.names=c(1:max(data1))
There is nice function count.fields
(see help) which counts number of column per row:
count.fields("test", sep = "\t")
#[1] 1 2 3 4 5 6 7 8
So, using your second solution:
no_col <- max(count.fields("test", sep = "\t"))
data <- read.table("test",sep="\t",fill=TRUE,col.names=1:no_col)
data
# X1 X2 X3 X4 X5 X6 X7 X8
# 1 1 NA NA NA NA NA NA NA
# 2 1 2 NA NA NA NA NA NA
# 3 1 2 3 NA NA NA NA NA
# 4 1 2 3 4 NA NA NA NA
# 5 1 2 3 4 5 NA NA NA
# 6 1 2 3 4 5 6 NA NA
# 7 1 2 3 4 5 6 7 NA
# 8 1 2 3 4 5 6 7 8
Using count.fields
is definitely the right approach for this, but just for completeness:
Another option is to bring in all the raw text and parse it within R:
x <- readLines(textConnection(
"1\t
1\t2
1\t2\t3
1\t2\t3\t4
1\t2\t3\t4\t5
1\t2\t3\t4\t5\t6"))
x <- strsplit(x,"\t")
To combine a list of unequal length vectors, the easiest approach is to use the rbind.fill
function from plyr
:
library(plyr)
# requires data.frames with column names
x <- lapply(x,function(x) {x <- as.data.frame(t(x)); colnames(x)=1:length(x); return(x)})
do.call(rbind.fill,x)
1 2 3 4 5 6
1 1 <NA> <NA> <NA> <NA> <NA>
2 1 2 <NA> <NA> <NA> <NA>
3 1 2 3 <NA> <NA> <NA>
4 1 2 3 4 <NA> <NA>
5 1 2 3 4 5 <NA>
6 1 2 3 4 5 6
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