pandas.read_parquet

pandas.read_parquet(path, engine='auto', columns=None, storage_options=None, use_nullable_dtypes=_NoDefault.no_default, dtype_backend=_NoDefault.no_default, **kwargs)

Load a parquet object from the file path, returning a DataFrame.

Parameters

pathstr, path object or file-like object

String, path object (implementing os.PathLike[str]), or file-like object implementing a binary read() function. The string could be a URL. Valid URL schemes include http, ftp, s3, gs, and file. For file URLs, a host is expected. A local file could be: file://localhost/path/to/table.parquet. A file URL can also be a path to a directory that contains multiple partitioned parquet files. Both pyarrow and fastparquet support paths to directories as well as file URLs. A directory path could be: file://localhost/path/to/tables or s3://bucket/partition_dir.

engine{‘auto’, ‘pyarrow’, ‘fastparquet’}, default ‘auto’

Parquet library to use. If ‘auto’, then the option io.parquet.engine is used. The default io.parquet.engine behavior is to try ‘pyarrow’, falling back to ‘fastparquet’ if ‘pyarrow’ is unavailable.

columnslist, default=None

If not None, only these columns will be read from the file.

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 to fsspec.open. Please see fsspec and urllib for more details, and for more examples on storage options refer here.

New in version 1.3.0.

use_nullable_dtypesbool, default False

If True, use dtypes that use pd.NA as missing value indicator for the resulting DataFrame. (only applicable for the pyarrow engine) As new dtypes are added that support pd.NA in the future, the output with this option will change to use those dtypes. Note: this is an experimental option, and behaviour (e.g. additional support dtypes) may change without notice.

Deprecated since version 2.0.

dtype_backend{“numpy_nullable”, “pyarrow”}, defaults to NumPy backed DataFrames

Which dtype_backend to use, e.g. whether a DataFrame should have NumPy arrays, nullable dtypes are used for all dtypes that have a nullable implementation when “numpy_nullable” is set, pyarrow is used for all dtypes if “pyarrow” is set.

The dtype_backends are still experimential.

New in version 2.0.

**kwargs

Any additional kwargs are passed to the engine.

Returns

DataFrame