pandas.read_orc#

pandas.read_orc(path, columns=None, dtype_backend=<no_default>, filesystem=None, **kwargs)[source]#

Load an ORC 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, and file. For file URLs, a host is expected. A local file could be: file://localhost/path/to/table.orc.

columnslist, default None

If not None, only these columns will be read from the file. Output always follows the ordering of the file and not the columns list. This mirrors the original behaviour of pyarrow.orc.ORCFile.read().

dtype_backend{‘numpy_nullable’, ‘pyarrow’}

Back-end data type applied to the resultant DataFrame (still experimental). If not specified, the default behavior is to not use nullable data types. If specified, the behavior is as follows:

Added in version 2.0.

filesystemfsspec or pyarrow filesystem, default None

Filesystem object to use when reading the orc file.

Added in version 2.1.0.

**kwargs

Any additional kwargs are passed to pyarrow.

Returns:
DataFrame

DataFrame based on the ORC file.

See also

read_csv

Read a comma-separated values (csv) file into a pandas DataFrame.

read_excel

Read an Excel file into a pandas DataFrame.

read_spss

Read an SPSS file into a pandas DataFrame.

read_sas

Load a SAS file into a pandas DataFrame.

read_feather

Load a feather-format object into a pandas DataFrame.

Notes

Before using this function you should read the user guide about ORC and install optional dependencies.

If path is a URI scheme pointing to a local or remote file (e.g. “s3://”), a pyarrow.fs filesystem will be attempted to read the file. You can also pass a pyarrow or fsspec filesystem object into the filesystem keyword to override this behavior.

Examples

>>> result = pd.read_orc("example_pa.orc")
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