Read Gzipped CSV Directly from a Url in R

Read gzipped csv directly from a url in R

I am almost certain I answered this question once before. The upshot is that Connections API of R (file(), url(), pipe(), ...) can do decompression on the fly, I do not think you can do it for remote http objects.

So do the very two-step you have described: use download.file() with a tempfile() result as second argument to fetch the compressed file, and then read from it. As tempfile() object, it will get cleaned up automatically at the end of your R session so the one minor fix I can suggest is to skip the unlink() (but then I like explicit cleanups, so you may as well keep it).

Edit: Got it:

con <- gzcon(url(paste("http://dumps.wikimedia.org/other/articlefeedback/",
                       "aa_combined-20110321.csv.gz", sep="")))
txt <- readLines(con)
dat <- read.csv(textConnection(txt))

dim(dat)
# [1] 1490   19

summary(dat[,1:3])
# aa_page_id       page_namespace                 page_title  
# Min.   :     324   Min.   :0      United_States        :  79  
# 1st Qu.:   88568   1st Qu.:0      2011_NBA_Playoffs    :  52  
# Median : 2445733   Median :0      IPad_2               :  43  
# Mean   : 8279600   Mean   :0      IPod_Touch           :  38  
# 3rd Qu.:16179920   3rd Qu.:0      True_Grit_(2010_film):  38  
# Max.   :31230028   Max.   :0      IPhone_4             :  26  
# (Other)              :1214  

The key was the hint the gzcon help that it can put decompression around an existing stream. We then need the slight detour of readLines and reading via textConnection from that as read.csv wants to go back and forth in the data (to validate column width, I presume).

R: readr: How to read a file that is provided via URL and gzipped

version 0.2.2 of reader can handle both nicely. The error was with older version.

Downloading and extracting .gz data file using R

Some additional options, with base R:

url <- "http://cbio.mskcc.org/microrna_data/human_predictions_S_C_aug2010.txt.gz"
tmp <- tempfile()
##
download.file(url,tmp)
##
data <- read.csv(
  gzfile(tmp),
  sep="\t",
  header=TRUE,
  stringsAsFactors=FALSE)
names(data)[1] <- sub("X\\.","",names(data)[1])
##
R> head(data)
   mirbase_acc mirna_name gene_id gene_symbol transcript_id ext_transcript_id           mirna_alignment
1 MIMAT0000062 hsa-let-7a    5270    SERPINE2    uc002vnu.2         NM_006216   uuGAUAUGUUGGAUGAU-GGAGu
2 MIMAT0000062 hsa-let-7a  494188      FBXO47    uc002hrc.2      NM_001008777 uugaUA-UGUU--GGAUGAUGGAGu
3 MIMAT0000062 hsa-let-7a   80025       PANK2    uc002wkc.2         NM_153638   uugauaUGUUGG-AUGAUGGAgu
4 MIMAT0000062 hsa-let-7a   26036      ZNF451    uc003pdp.2          AK027074    uuGAUAUGUUGGAUGAUGGAGu
5 MIMAT0000062 hsa-let-7a     586       BCAT1    uc001rgd.3         NM_005504    uugaUAUGUUGGAUGAUGGAGu
6 MIMAT0000062 hsa-let-7a   22903       BTBD3    uc002wnz.2         NM_014962  uuGAUAUGUUGGAU-GAUGG-AGu
                  alignment            gene_alignment mirna_start mirna_end gene_start gene_end
1     | :|: ||:|| ||| ||||    aaCGGUGAAAUCU-CUAGCCUCu           2        21        495      516
2     || |||:  ::||||||||:  acaaAUCACAGUUUUUACUACCUUc           2        19        459      483
3         |::||: ||||||||     aauuucAUGACUGUACUACCUga           3        17         77       99
4      || || |   | |||||||     ccCUCUAGA---UUCUACCUCa           2        21       1282     1300
5        :|| |:   ||||||||     guagGUAAAGGAAACUACCUCa           2        19       6410     6431
6    || || ||| || ||||| ||   uaCUUUAAAACAUAUCUACCAUCu           2        21       2265     2288
              genome_coordinates conservation align_score seed_cat energy mirsvr_score
1 [hg19:2:224840068-224840089:-]       0.5684         122        0 -14.73      -0.7269
2  [hg19:17:37092945-37092969:-]       0.6464         140        0 -16.38      -0.1156
3    [hg19:20:3904018-3904040:+]       0.6522         139        0 -16.04      -0.2066
4   [hg19:6:56966300-56966318:+]       0.7627         144        7 -14.51      -0.8609
5  [hg19:12:24964511-24964532:-]       0.6775         150        7 -15.09      -0.2735
6  [hg19:20:11906579-11906602:+]       0.5740         131        0 -12.59      -0.2540

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Or if you are on a Unix-like system, you could obtain the .txt file (either outside of R or using system or system2 from within R) like this:

[nathan@nrussell tmp]$ url="http://cbio.mskcc.org/microrna_data/human_predictions_S_C_aug2010.txt.gz"
[nathan@nrussell tmp]$ wget "$url" && gunzip human_predictions_S_C_aug2010.txt.gz

and then proceed as above, where you are reading in human_predictions_S_C_aug2010.txt from wherever wget and gunzip were executed,

data <- read.csv(
  "~/tmp/human_predictions_S_C_aug2010.txt",
  stringsAsFactors=FALSE,
  header=TRUE,
  sep="\t")

in my case.

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