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First, the reason you've gotten some down votes is most likely because you haven't given much in your question to go on. For one thing, you haven't shown us what
(dataframe[z, ])$variable
is, which makes it hard for us to formulate a complete answer. You seem to be trying to extract a single value from a dataframe, is that right? If so, I've never seen it done that way, try replacing the above with:
dataframe$variable[z]
My guess is what you're trying to achieve is a comparison of an entire column of the dataframe called "variable", since that's generally more useful...
Having said that, I often come up against issues with time data, and from what I've heard, my experiences are not uncommon. When I'm dealing with just times, as it appears you are here, I prefer the chron::times format over POSIXct (POSIX is a date-time format, so a date is always included, it also tries to correct for timezone changes, as well as daylight savings changes, which tends to get in my way more than help). If you've got your data in the format you've specified in your first as.POSIXct call, you won't even need to specify that in calling the times function instead.
x <- chron::times( dataframe$variable )
print(x)
position <- ifelse ( x >= chron::times( "06:00:00" ) &
x < chron::times( "12:00:00" ),
"first", "not first"
)
This will output a vector "position", with a result for all values taken from dataframe$variable. Does that achieve what you're hoping for?
From here, if you did want to extract the comparison result for the particular row "z" in dataframe, you can still do that with
position[z]
EDIT to add:
It might be worth checking for missing values in "variable". This should return TRUE:
sum( is.na( dataframe$variable ) ) == 0
Also check for any that aren't correctly formatted. Again, this should return TRUE:
sum( is.na( chron::times( dataframe$variable ) ) ) == 0
EDIT to add:
As per the comments, it looks like some values in your "variables" column aren't converting properly. You should be able to find them with
subset( dataframe, is.na( chron::times( variable ) ) )
That should let you see what's wrong. It may be a single cell, or it may be a number of them. You'll need to tidy up that data, which you can do in a few ways. You could go through and fix them manually, you could add a function in your script to repair them before the conversion (this might be a good idea if there is a common issue between all of those values, or if you expect the same issue to happen again as new data comes in, if indeed you need to allow for that).
The other option is simply to exclude those rows from your analysis. If you go this route, make sure it's appropriate to the analysis you're running. If it is appropriate in your case, you can add a step to clean up the dataframe before running the steps in your question:
dataframe <- subset( dataframe, !is.na( chron::times( variable ) ) )
NOTE: there's a good chance this will come up with a warning. If you run the same line twice, and the warning goes away the second time (after the offending rows have been removed), you may need to look further into it.
That should drop the offending values, leaving only values that are properly converting to the times format, which should help with the steps you're trying to run. Check how your dataframe dimensions change before and after that step; that'll tell you how many rows you're dropping.
You could do the same thing with POSIXct if that's what you're comfortable with, I'm just personally more comfortable with times for what you're doing.
