Hi I am new here and a beginner in R,
My problem:
in the case i have more than one file (test1.dat, test2.dat,...) to work with in R i use this code to read them in
filelist <- list.files(pattern = "*.dat")
df_list <- lapply(filelist, function(x) read.table(x, header = FALSE, sep = ","
,colClasses = "factor", comment.char = "",
col.names = "raw"))
Now i have the problem that my data is big, i found a solution to speed things up using the sqldf-package :
sql <- file("test2.dat")
df <- sqldf("select * from sql", dbname = tempfile(),
file.format = list(header = FALSE, row.names = FALSE, colClasses = "factor",
comment.char = "", col.names ="raw"))
it is working well for one file but i am not able to change the code to read-in multiple files like in the first code snippet. can someone help me? Thank you! Momo
This seems to work (but i assume there is a quicker sql
way to this)
sql.l <- lapply(filelist , file)
df_list2 <- lapply(sql.l, function(i) sqldf("select * from i" ,
dbname = tempfile(), file.format = list(header = TRUE, row.names = FALSE)))
Look at speeds - partially taken from mnel's post Quickly reading very large tables as dataframes in R
library(data.table)
library(sqldf)
# test data
n=1e6
DT = data.table( a=sample(1:1000,n,replace=TRUE),
b=sample(1:1000,n,replace=TRUE),
c=rnorm(n),
d=sample(c("foo","bar","baz","qux","quux"),n,replace=TRUE),
e=rnorm(n),
f=sample(1:1000,n,replace=TRUE) )
# write 5 files out
lapply(1:5, function(i) write.table(DT,paste0("test", i, ".dat"),
sep=",",row.names=FALSE,quote=FALSE))
read: data.table
filelist <- list.files(pattern = "*.dat")
system.time(df_list <- lapply(filelist, fread))
# user system elapsed
# 5.244 0.200 5.457
read: sqldf
sql.l <- lapply(filelist , file)
system.time(df_list2 <- lapply(sql.l, function(i) sqldf("select * from i" ,
dbname = tempfile(), file.format = list(header = TRUE, row.names = FALSE))))
# user system elapsed
# 35.594 1.432 37.357
Check - seems ok except for attributes
all.equal(df_list , df_list2)