pandas.
read_pickle
Load pickled pandas object (or any object) from file.
Warning
Loading pickled data received from untrusted sources can be unsafe. See here.
File path, URL, or buffer where the pickled object will be loaded from.
Changed in version 1.0.0: Accept URL. URL is not limited to S3 and GCS.
If ‘infer’ and ‘path_or_url’ is path-like, then detect compression from the following extensions: ‘.gz’, ‘.bz2’, ‘.zip’, or ‘.xz’ (otherwise no compression) If ‘infer’ and ‘path_or_url’ is not path-like, then use None (= no decompression).
Extra options that make sense for a particular storage connection, e.g. host, port, username, password, etc. For HTTP(S) URLs the key-value pairs are forwarded to urllib as header options. For other URLs (e.g. starting with “s3://”, and “gcs://”) the key-value pairs are forwarded to fsspec. Please see fsspec and urllib for more details.
urllib
fsspec
New in version 1.2.0.
See also
DataFrame.to_pickle
Pickle (serialize) DataFrame object to file.
Series.to_pickle
Pickle (serialize) Series object to file.
read_hdf
Read HDF5 file into a DataFrame.
read_sql
Read SQL query or database table into a DataFrame.
read_parquet
Load a parquet object, returning a DataFrame.
Notes
read_pickle is only guaranteed to be backwards compatible to pandas 0.20.3.
Examples
>>> original_df = pd.DataFrame({"foo": range(5), "bar": range(5, 10)}) >>> original_df foo bar 0 0 5 1 1 6 2 2 7 3 3 8 4 4 9 >>> pd.to_pickle(original_df, "./dummy.pkl")
>>> unpickled_df = pd.read_pickle("./dummy.pkl") >>> unpickled_df foo bar 0 0 5 1 1 6 2 2 7 3 3 8 4 4 9
>>> import os >>> os.remove("./dummy.pkl")