Reading large text files with Pandas

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A solution for a similar question was given here some time after the posting of this question. Basically, it suggests to read the file in chunks by doing the following:

chunksize = 10 ** 6  # number of rows per chunk
for chunk in pd.read_csv(filename, chunksize=chunksize):
    process(chunk)

You should specify the chunksize parameter accordingly to your machine's capabilities (that is, make sure it can process the chunk).

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marillion
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marillion

Updated on June 12, 2022

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  • marillion
    marillion almost 2 years

    I have been trying to read a few large text files (sizes around 1.4GB - 2GB) with Pandas, using the read_csv function, with no avail. Below are the versions I am using:

    • Python 2.7.6
    • Anaconda 1.9.2 (64-bit) (default, Nov 11 2013, 10:49:15) [MSC v.1500 64 bit (AMD64)]
    • IPython 1.1.0
    • Pandas 0.13.1

    I tried the following:

    df = pd.read_csv(data.txt')
    

    and it crashed Ipython with a message: Kernel died, restarting.

    Then I tried using an iterator:

    tp = pd.read_csv('data.txt', iterator = True, chunksize=1000)
    

    again, I got the Kernel died, restarting error.

    Any ideas? Or any other way to read big text files?

    Thank you!