Question: How to import huge .csv files in R studio?
0
gravatar for krushnach80
15 months ago by
krushnach80270
krushnach80270 wrote:

I want to import an expression .csv file in R studio ,but the size limit is 5 mb max my file is 30 mb how do I do that?

The file is mrna seq data from TCGA which I want to extract.How can I do that is there any way to import the huge file and see ?

rna-seq R • 2.5k views
ADD COMMENTlink modified 15 months ago by Ron690 • written 15 months ago by krushnach80270

I think you may use ff lib

library(ff)

your_data <- read.csv.ffdf(file = 'your_file.csv', header = T)

other solution use bigmemory

the authors successfully load a CSV with size as large as 11GB

more details and other solution could be found here

ADD REPLYlink modified 15 months ago • written 15 months ago by Medhat7.4k
6
gravatar for Devon Ryan
15 months ago by
Devon Ryan76k
Freiburg, Germany
Devon Ryan76k wrote:

Try using read.csv() rather than clicking on files. The limitation is there to prevent you from trying to edit large files, which will degrade performance significantly.

ADD COMMENTlink written 15 months ago by Devon Ryan76k
4
gravatar for sm30
15 months ago by
sm3040
sm3040 wrote:

CRAN pakage TCGA2STAT can be used to directly import TCGA data into R.

ADD COMMENTlink written 15 months ago by sm3040

yes finally I used that library

ADD REPLYlink written 15 months ago by krushnach80270
4
gravatar for Ron
15 months ago by
Ron690
United States
Ron690 wrote:

http://stackoverflow.com/questions/1727772/quickly-reading-very-large-tables-as-dataframes-in-r

read.csv.sql() from https://cran.r-project.org/web/packages/sqldf/sqldf.pdf

ADD COMMENTlink written 15 months ago by Ron690
3
gravatar for Santosh Anand
15 months ago by
Santosh Anand3.4k
Santosh Anand3.4k wrote:

fread() from data.table package is blazing fast for reading large files. It tries to guess the delimiter and header automatically. It will give you an object of class "data.table", which is very similar to data.frame though quirky sometimes. You can easily convert it to your familiar data.frame by using as.data.frame(x) or by using data.table=FALSE in the argument of fread().

ADD COMMENTlink modified 10 hours ago • written 15 months ago by Santosh Anand3.4k
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