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
String, path object (implementing
os.PathLike[str]
), or file-like object implementing a binaryreadlines()
function.Changed in version 1.0.0: Accept URL. URL is not limited to S3 and GCS.
- compressionstr or dict, default ‘infer’
For on-the-fly decompression of on-disk data. If ‘infer’ and ‘filepath_or_buffer’ is path-like, then detect compression from the following extensions: ‘.gz’, ‘.bz2’, ‘.zip’, ‘.xz’, ‘.zst’, ‘.tar’, ‘.tar.gz’, ‘.tar.xz’ or ‘.tar.bz2’ (otherwise no compression). If using ‘zip’ or ‘tar’, the ZIP file must contain only one data file to be read in. Set to
None
for no decompression. Can also be a dict with key'method'
set to one of {'zip'
,'gzip'
,'bz2'
,'zstd'
,'tar'
} and other key-value pairs are forwarded tozipfile.ZipFile
,gzip.GzipFile
,bz2.BZ2File
,zstandard.ZstdDecompressor
ortarfile.TarFile
, respectively. As an example, the following could be passed for Zstandard decompression using a custom compression dictionary:compression={'method': 'zstd', 'dict_data': my_compression_dict}
.New in version 1.5.0: Added support for .tar files.
Changed in version 1.4.0: Zstandard support.
- 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.request.Request
as header options. For other URLs (e.g. starting with “s3://”, and “gcs://”) the key-value pairs are forwarded tofsspec.open
. Please seefsspec
andurllib
for more details, and for more examples on storage options refer here.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 provided the object was serialized with to_pickle.
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