I have a bunch of .csv files which I have to read and look for data. The .csv file is of the format:

A row of data I will ignore

In every csv file, the order of columns is not consistent. For example in csv1 the order can be State,County,City, in csv2 it can be City,County,State. What I am interested is the State and County. Given a county I want to find out what State it is in. I am ignoring the fact that same counties can exist in multiple States. The way I am approaching this:

with open(‘file.csv’) as f:
    data = f.read()

# convert the data to iterable, skip the first line
reader = csv.DictReader(data.splitlines(1)[1:])
lines = list(reader)
counties = {k: v for (k,v in ((line[‘county’], line[‘State’]) for line in lines)}

Is there a better approach to this?


1 Answer 1


You're on the right track, using a with block to open the file and csv.DictReader() to parse it.

Your list handling is a bit clumsy, though. To skip a line, use next(f). Avoid making a list of the entire file's data, if you can process the file line by line. The dict comprehension has an unnecessary complication as well.

with open('file.csv') as f:
    _ = next(f)
    reader = csv.DictReader(f)
    counties = { line['County']: line['State'] for line in reader }

Your sample file had County as the header, whereas your code looked for line[‘county’]. I assume that the curly quotes are an artifact of copy-pasting, but you should pay attention to the capitalization.

  • \$\begingroup\$ I am really getting the data from an S3 bucket, but I didn't want to make the code more complicated in my example. So, I get the key from the bucket and then I say data = key.get_contents_as_string() So I am not really reading from a file. Instead, the contents of the key are the string representation of the csv file. I like the way you eliminated the list and cleaned up the dict comprehension, is there a way that I can avoid doing the data.splitlines(1)[1:]) when I create the reader since I already have the data in a string? (and i need to ignore the first row) \$\endgroup\$
    – Mark
    Commented Nov 26, 2014 at 3:39

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