Hello,
I believe you should follow Jeremiah's sugestion to first read all csv
files into a list and then rbind them.
Something like the following.
file_list <- list.files(pattern = "*.csv")
df_list <- lapply(file_list, read.csv)
result <- do.call(rbind, df_list)
Hope this helps,
Rui Barradas
Thanks, Richard. But if the data cannot fill the constructed data frame,
will there be NA values?
On Fri, Jan 6, 2017 at 10:07 PM, Richard M. Heiberger
wrote:
> Incrementally increasing the size of an array is not efficient in R.
> The recommended technique is to allocate as much space as you w
As a rule never rbind in a loop. It has O(n^2) run time because the rbind
itself can be O(n) (where n is the number of data.frames). Instead either
put them all into a list with lapply or vector("list", length=) and then
datatable::rbindlist, do.call(rbind, thelist) or use the equivalent from
dply
Incrementally increasing the size of an array is not efficient in R.
The recommended technique is to allocate as much space as you will
need, and then fill it.
> system.time({tmp <- 1:5 ; for (i in 1:1000) tmp <- rbind(tmp, 1:5)})
user system elapsed
0.011 0.000 0.011
> dim(tmp)
[1] 1001
Hi Rui,
Thanks for your reply. Yes, when I tried to rbind two dataframes, it works.
However, if there are more than 50, it got stuck for hours. When I tried to
terminate the process and open the csv file separately, it has only one
data frame. What is the problem? Thanks.
On Fri, Jan 6, 2017 at
Hello,
Works with me:
set.seed(6574)
pre.mat = data.frame()
for(i in 1:10){
mat.temp = data.frame(x = rnorm(5), A = sample(LETTERS, 5, TRUE))
pre.mat = rbind(pre.mat, mat.temp)
}
nrow(pre.mat) # should be 50
Can you give us an example that doesn't work?
Rui Barradas
Em 06-01-2017
Hi R users,
I have a question about filling a dataframe in R using a for loop.
I created an empty dataframe first and then filled it, using the code:
pre.mat = data.frame()
for(i in 1:10){
mat.temp = data.frame(some values filled in)
pre.mat = rbind(pre.mat, mat.temp)
}
However, the resul
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