Question: How to import huge .csv files in R studio?
0
gravatar for krushnach80
19 months ago by
krushnach80300
krushnach80300 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 • 4.2k views
ADD COMMENTlink modified 19 months ago by Ron750 • written 19 months ago by krushnach80300

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 19 months ago • written 19 months ago by Medhat7.6k
6
gravatar for Devon Ryan
19 months ago by
Devon Ryan80k
Freiburg, Germany
Devon Ryan80k 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 19 months ago by Devon Ryan80k
4
gravatar for sm30
19 months ago by
sm3040
sm3040 wrote:

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

ADD COMMENTlink written 19 months ago by sm3040

yes finally I used that library

ADD REPLYlink written 19 months ago by krushnach80300
4
gravatar for Ron
19 months ago by
Ron750
United States
Ron750 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 19 months ago by Ron750
3
gravatar for Santosh Anand
19 months ago by
Santosh Anand3.5k
Santosh Anand3.5k 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 3 months ago • written 19 months ago by Santosh Anand3.5k
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