r - Subsetting dataframe by day according to most non zero data

Question

I have an example dataframe:

a <- c(1:6)
b <- c("05/12/2012 05:00","05/12/2012 06:00","06/12/2012 05:00",
   "06/12/2012 06:00", "07/12/2012 09:00","07/12/2012 07:00")
c <-c("0","0","0","1","1","1")
df1 <- data.frame(a,b,c,stringsAsFactors = FALSE)

Firstly, I want to make sure R recognises the date and time format, so I used:

df1$b <- strptime(df1$b, "%d/%m/%Y %H:%M")

However this can't be right as R always aborts my session as soon as I try to view the new dataframe.

Assuming that this gets resolves, I want to get a subset of the data according to whichever day in the dataframe contains the most data in 'C' that is not a zero. In the above example I should be left with the two data points on 7th Dec 2012.

I also have an additional, related question.
If I want to be left with a subset of the data with the most non zero values between a certain time period in the day (say between 07:00 and 08:00), how would I go about doing this?

Any help on the above problems would be greatly appreciated.

Answer 1

Agreeing with Jack. Sounds like a corrupted installation of R. First thing to try would be to delete the .Rdata file that holds the results of the prior session. They are hidden in both Mac and Windows so unless you "reveal" the 'dotfiles'(system files), the OS file manager (Finder.app and Windows Explorer) will not show them. How you find and delete that file is OS-specific task. It's going to be in your working directory and you will need to do the deletion outside of R since once R is started it will have locked access to it. It's also possible to get a corrupt .history file but in my experience that is not usually the source of the problem.

If that is not successful, you may need to reinstall R.