pandas.read_pickle¶
-
pandas.
read_pickle
(filepath_or_buffer, compression='infer', storage_options=None)[source]¶ Load pickled pandas object (or any object) from file.
Warning
Loading pickled data received from untrusted sources can be unsafe. See here.
- Parameters
- filepath_or_bufferstr, path object or file-like object
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.
- compression{‘infer’, ‘gzip’, ‘bz2’, ‘zip’, ‘xz’, None}, default ‘infer’
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).
- storage_optionsdict, optional
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 tofsspec
. Please seefsspec
andurllib
for more details.New in version 1.2.0.
- Returns
- unpickledsame type as object stored in file
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")