read_parquet(path, engine: 'str' = 'auto', columns=None, storage_options: 'StorageOptions' = None, use_nullable_dtypes: 'bool' = False, **kwargs) -> 'DataFrame'
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
.
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.
If not None, only these columns will be read from the file.
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.
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.
Any additional kwargs are passed to the engine.
Load a parquet object from the file path, returning a DataFrame.
The following pages refer to to this document either explicitly or contain code examples using this.
pandas.io.pickle.read_pickle
pandas.core.frame.DataFrame.to_parquet
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