how to split fields after reading the file in R - r

Question

I have a file with this format in each line:
f1,f2,f3,a1,a2,a3,...,an
Here, f1, f2, and f3 are the fixed fields separated by ,, but f4 is the whole a1,a2,...,an where n can vary.
How can I read this into R and conveniently store those variable-length a1 to an?
Thank you.
My file looks like the following
3,a,-4,news,finance
2,b,1,politics
1,a,0
2,c,2,book,movie
...

Answer 1

It is not clear what you mean by "conveniently store". If you think a data frame will suit you, try this:
df <- read.table(text = "3,a,-4,news,finance
2,b,1,politics
1,a,0
2,c,2,book,movie",
sep = ",", na.strings = "", header = FALSE, fill = TRUE)
names(df) <- c(paste0("f", 1:3), paste0("a", 1:(ncol(df) - 3)))
Edit following #Ananda Mahto's comment.
From ?read.table:
"The number of data columns is determined by looking at the first five lines of input".
Thus, if the maximum number of columns with data occurs somewhere after the first five lines, the solution above will fail.
Example of failure
# create a file with max five columns in the first five lines,
# and six columns in the sixth row
cat("3, a, -4, news, finance",
"2, b, 1, politics",
"1, a, 0",
"2, c, 2, book,movie",
"1, a, 0",
"2, c, 2, book, movie, news",
file = "df",
sep = "\n")
# based on the first five rows, read.table determines that number of columns is five,
# and creates an incorrect data frame
df <- read.table(file = "df",
sep = ",", na.strings = "", header = FALSE, fill = TRUE)
df
Solution
# This can be solved by first counting the maximum number of columns in the text file
ncol <- max(count.fields("df", sep = ","))
# then this count is used in the col.names argument
# to handle the unknown maximum number of columns after row 5.
df <- read.table(file = "df",
sep = ",", na.strings = "", header = FALSE, fill = TRUE,
col.names = paste0("f", seq_len(ncol)))
df
# change column names as above
names(df) <- c(paste0("f", 1:3), paste0("a", 1:(ncol(df) - 3)))
df

Answer 2

#
# Read example data
#
txt <- "3,a,-4,news,finance\n2,b,1,politics\n1,a,0\n2,c,2,book,movie"
tc = textConnection(txt)
lines <- readLines(tc)
close(tc)
#
# Solution
#
lines_split <- strsplit(lines, split=",", fixed=TRUE)
ind <- 1:3
df <- as.data.frame(do.call("rbind", lapply(lines_split, "[", ind)))
df$V4 <- lapply(lines_split, "[", -ind)
#
# Output
#
V1 V2 V3 V4
1 3 a -4 news, finance
2 2 b 1 politics
3 1 a 0
4 2 c 2 book, movie

Answer 3

A place to start:
dat <- readLines(file) ## file being your file
df <- data.frame(
f1=sapply(dat_split, "[[", 1),
f2=sapply(dat_split, "[[", 2),
f3=sapply(dat_split, "[[", 3),
a=unlist( sapply(dat_split, function(x) {
if (length(x) <= 3) {
return(NA)
} else {
return(paste(x[4:length(x)], collapse=","))
}
}) )
)
and when you need to pull things out of a, you can do splitting as necessary.