How can I filter lines on load in Pandas read_csv function?
If the filtered range is contiguous (as it usually is with time(stamp) filters), then the fastest solution is to hard-code the range of rows. Simply combine skiprows=range(1, start_row) with nrows=end_row parameters. Then the import takes seconds where the accepted solution would take minutes. A few experiments with the initial start_row are not a huge cost given the savings on import times. Notice we kept header row by using range(1,..).
How can I filter which lines of a CSV to be loaded into memory using pandas?  This seems like an option that one should find in read_csv.  Am I missing something?
Example: we've a CSV with a timestamp column and we'd like to load just the lines that with a timestamp greater than a given constant.