[R] using sqldf's read.csv.sql to read a file with "NA" for missing

[David Reiner]

I'm trying to use sqdf's function read.csv.sql to read CSV files in which the missing values are represented by NA's.
Plain old read.csv works fine on these files, but they are rather large and I'd like to filter using sql-like statements.
However, even if I specify field.types correctly and nrows=-1, it still turns the columns with NA's into chars or 0.
I'm trying to make this OS independent, so I don't think I can use a filter to convert the NA's to NULL's or whatever SQLite would understand.
I can accept it everything has to be read in as char and then convert to doubles with as.numeric, but I'm looking for speed.

Here is code I thought would read the file (I've attached a small sample.)
It almost works if there are no NA's in the initial rows, but it still turns NA's into 0's instead of NA or something I can change into NA;
and it returns characters if there are NA's in the initial rows.
(0 is a possible value so I can't filter out the 0's.)

field.types <- list(V1='char', V2='char', V3='real', V4='int', V5='real', V6='int', V7='real')
dtst <- read.csv.sql("./tmp.csv", header=FALSE, field.types=field.types, nrows=-1)
str(dtst)

'data.frame':   32 obs. of  7 variables:
 $ V1: chr  "2012-07-01" "2012-07-01" "2012-07-01" "2012-07-01" ...
 $ V2: chr  "15:50:00" "15:51:00" "15:52:00" "15:53:00" ...
 $ V3: chr  "NA" "NA" "NA" "NA" ...
 $ V4: int  0 0 0 0 0 0 0 0 0 0 ...
 $ V5: chr  "NA" "NA" "NA" "NA" ...
 $ V6: int  0 0 0 0 0 0 0 0 0 0 ...
 $ V7: chr  "NA" "NA" "NA" "NA" ...

Any suggestions?
Thanks,
-- David L. Reiner




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