On Oct 29, 2009, at 3:26 PM, Jason Rupert wrote:
Currently I have a CSV with mixed input types that I am trying to
read in and reformat without having to list off all the column
names. Below is an example of the data:
HouseColor, HouseSize, HouseCost
Blue, 1600, 160e3
Blue, 1600, 160e3
Actually I have about 60 columns like this, so imagine the above
repeated about 30 times column-wise.
Luckily the ones in scientific notation are grouped together, i.e.
columns 11-56.
Using read.csv or as.numeric, is there a way to convert all those in
scientific format over to general numeric syntax?
Option 1: do it in the read step. (in my experience the more dificult
and error-prone method when you are starting out.)
?read.table
see section on colClasses, and define your columns as "character" or
"numeric" appropriately.
Option 2:
Read them in with as.is=TRUE, and stringsAsFactors=FALSE
convert them in a loop
for (i in 11:56) DFhouses[, i] <- as.numeric( DFhouses[, i] )
Right now I have something like the following
input_df<-read.csv(InputFile, skip=0, header=TRUE, strip.white = TRUE)
I tried:
as.numeric(input_df[, 11:56])
but this returns an error
Error: (list) object cannot be coerced to type 'double'
Oddly it does appear to work successfully row-
wiseas.numeric(input_df[1, 11:56])
as.numeric(input_df[2, 11:56])
etc.
However, trying it on multiple rows produces the same error as above:
as.numeric(input_df[1:2, 11:56])
After a bit, I became a bit frustrated that this was not working so
I tried just deleting the columns:
input_df[1, 11:56]<-NULL
This also failed, so are there any suggestions about how to convert
the values in scientific notation over to standard numeric syntaix?
Thank you again again for all your insights and feedback.
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David Winsemius, MD
Heritage Laboratories
West Hartford, CT
______________________________________________
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
