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Editorial Team
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Editorial Team
Asked: June 15, 20262026-06-15T04:24:41+00:00 2026-06-15T04:24:41+00:00

How can I filter which lines of a CSV to be loaded into memory

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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.

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  1. Editorial Team
    Editorial Team
    2026-06-15T04:24:43+00:00Added an answer on June 15, 2026 at 4:24 am

    There isn’t an option to filter the rows before the CSV file is loaded into a pandas object.

    You can either load the file and then filter using df[df['field'] > constant], or if you have a very large file and you are worried about memory running out, then use an iterator and apply the filter as you concatenate chunks of your file e.g.:

    import pandas as pd
    iter_csv = pd.read_csv('file.csv', iterator=True, chunksize=1000)
    df = pd.concat([chunk[chunk['field'] > constant] for chunk in iter_csv])
    

    You can vary the chunksize to suit your available memory. See here for more details.

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