freadss: The freadss() function reads in a csv and perhaps subsets the...

In mikejacktzen/datzen:

Description

The input file is read in-memory via fread. If rows are subset, there is a slow down. Hence, subsetting rows costs a one-time slow down but affords ability to bean count the read-in memory footprint

Usage

freadss(input, ss = NULL, ind_choose = NULL)

Arguments

input	character for file path of csv passed to fread
ss	integer for desired row sample size. Default of ss is NULL, meaning no subsampling.
ind_choose	optional integer vector of specific rows to read in (instead of sampling)

Details

NOTE: if both ss and ind_choose are NULL, no subsetting is done. Entire csv is read in.

Value

a 'data.frame' with optionally subsetted rows (perhaps from sampling)

See Also

fread

Examples

set.seed(1); m = matrix(rnorm(10*100),ncol=100,nrow=100)

csv = data.frame(m)
names(csv) = paste0('x',seq_along(csv))
names(csv)

tf = tempfile()
write.csv(csv,tf,row.names=FALSE)
dir_test=tf

# if ss=NULL and ind_choose=NULL
# no sub sampling, basically fread() but no flexible optional args.
# just demo, might as well use fread() directly

identical(freadss(input=dir_test),fread(dir_test))

# user wants to sample 5 random rows
freadss(input=dir_test,ss=5)

# user picks 5 specific rows
ind_pick = c(1,7,23,69,100)

df_subset_before = freadss(input=dir_test,ind_choose = ind_pick)
df_subset_after = freadss(input=dir_test)[ind_pick,]
identical(df_subset_before,df_subset_after)

mikejacktzen/datzen documentation built on June 14, 2019, 5:23 p.m.