To read a pickle file and create a DataFrame in Python, the simplest way is to use the pandas read_pickle() function.


When working with data as a data science or data analyst, many times we want to read data and write data to different file types.

One common file type which analysts use is a pickle file. Pickle (.pkl) files are byte streams, and the pandas module is easily able to read and write pickle files.

In pandas, we can read pickle files with the pandas read_pickle() method.


If you need to decompress a pickle file in any way, you can pass the compression parameter with the appropriate string. The options for the compression parameter are “infer”, “gzip”, “bz2”, “zip”, “xz”, and None.

So if the file you want to read into pandas was compressed with “gzip”, then we can decompress it by passing “gzip” to the compression parameter.

df.read_pickle("./filename.pkl", compression="gzip")

If you need to write a pickle file using pandas, you can use the pandas to_pickle() method.

Hopefully this article has been useful for you to understand how to use pandas to read a pickle file with the pandas read_pickle function.

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Last Update: March 20, 2024