I have a large series of Visual FoxPro (.dbf) files that I want to convert to a plain text (.csv) file. I wrote a quick script to do all of this for me. With a little tweaking it seemed to work like a charm. But, when I looked at my newly created text files carefully, I discovered a problem. Every single file produced by my script had a few extra columns in it.
To better understand this, I imported a single file. Here are my results: ---------------------------------------------------- > library(foreign) > temp.df <- read.dbf("Activity.dbf") ilp.dbc changed to: X.ilp.dbc Field name: changed to: X Field name: changed to: X.1 Field name: changed to: X.2 Field name: changed to: X.3 Field name: changed to: X.4 Field name: changed to: X.5 Field name: changed to: X.6 ---------------------------------------------------- Based on the table definitions I received from the state, none of these tables have a column called ilp.dbc. When I open these same .dbf files in OpenOffice.org, individually, I do not see these columns. When I look at the temp.df in R, these mystery columns are all empty. Otherwise, the data appears to be fine. I looked at ?read.dbf and I did not see any options to play with that would seem to help. At the moment, I have a work-around in my script that prevents these extra columns from being written to the csv files, but I am curious to learn what I am doing wrong. The problem may be entirely of my own creation. Most of the info in these files is protected by HIPAA, which limits my ability to provide example files. If anyone really wants one, I can look to see if there are any files that I can release. Or I can try deleting all of the info and see if the problem persists. Version Information: r-project: 2.8.1 foreign: 0.8.30-1 Ubuntu: 9.04 (32-bit) Thanks for any thoughts. --andy -- This is the price and the promise of citizenship. - Barack Obama ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.