Thank you Gabor for your prompt reply. I had tried checking for class, but it returns three types of my dataset, which are numeric, integer and character. The problem with that is, I need to classify some columns as categorical and in doing so I have a cut off of 100 or less unique values in the column/variable.
In case of dates, I cannot consider it to be categorical, since in a 100,000 row dataset, dates will take more than 100 unique values, and checking for its class will return character. If i could somehow know it was a date, then I could provide a Time Series analysis for it. The same may hold true for, example serial number. I tried using regexpr to check for the presence of "/" OR "-" to check for it being a date column, but it returns the presence of the first "/" which if is at the position 3, could mean a date format of dd/mm/yyyy or mm/dd/yyyy. This would be a long winded approach, and I am looking for something more efficient. Thank you for your time. Harsh Singhal On Mon, Nov 24, 2008 at 7:06 PM, Gabor Grothendieck <[EMAIL PROTECTED]> wrote: > The classes of the columns are: > > sapply(DF, class) > > > On Mon, Nov 24, 2008 at 3:39 AM, Harsh <[EMAIL PROTECTED]> wrote: >> Hello, >> This is my first time posting to the R-help list and I apologize for >> the apparent triviality of my query. >> I am creating an R script to create Univariate Exploratory Analysis of >> a input dataset (No meta-data to provide extra information about each >> column) >> . >> Providing summary statistics is possible in case of numeric data and >> using all.is.numeric() from the Hmisc package allows me to filter out >> those columns with alpha-numeric content. >> >> I have tried to check if a column is a date field or not, but have not >> been able to do so. Are Regular Expressions the only answer? I've also >> looked for CRAN packages but haven't found any. >> Bering a newbie user of R, I do not possess the requisite knowledge to >> write my own function for the above objective. >> >> Thank you for your time >> Harsh >> Decisions Systems Group >> Mu Sigma Inc. >> Chicago, IL >> >> ______________________________________________ >> 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. >> > ______________________________________________ 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.
