I have data.frame objects with normalized names into my global env and I want to save them into .Rda files.
My first question is, should I save them into one big .Rda file or should I create one file for each data frame ? (df have 14 col and ~260 000 row).
Assuming that I'll save them into differents files, I was thinking about a function like this : (All my data.frame names begin by "errDatas")
sapply(ls(pattern = "errDatas"), function(x) save(as.name(x), file = paste0(x, ".Rda")))
But I have this error :
Error in save(as.name(x), file = paste0(x, ".Rda")) :
objet ‘as.name(x)’ introuvable
Seems like save
can't parse as.name(x)
and evaluate it as is. I tried also with eval(parse(text = x))
but it's the same thing.
Do you have an idea about how I can manage to save my data frames within a loop ? Thanks.
And I have a bonus question to know if what I'm trying to do is useful and legit :
These data frames come from csv files (one data frame by csv file which I import with read.csv
). Each day I have one new csv file and I want to do some analysis on all the csv files. I realized that reading from csv is much slower than saving and loading a Rda file. So instead of reading all the csv each time I run my program, I actualy want to read each csv file only once, saving it into a Rda file and then loading it. Is this a good idea ? Is there best-practices for that with R ?