pandas.DataFrame.to_orc#

DataFrame.to_orc(path=None,*,engine='pyarrow',index=None,engine_kwargs=None)[source]#

Write a DataFrame to the ORC format.

Added in version 1.5.0.

Parameters:

pathstr, file-like object or None, default None

If a string, it will be used as Root Directory pathwhen writing a partitioned dataset. By file-like object,we refer to objects with a write() method, such as a file handle(e.g. via builtin open function). If path is None,a bytes object is returned.

engine{‘pyarrow’}, default ‘pyarrow’

ORC library to use.

indexbool, optional

IfTrue, include the dataframe’s index(es) in the file output.IfFalse, they will not be written to the file.IfNone, similar toinfer the dataframe’s index(es)will be saved. However, instead of being saved as values,the RangeIndex will be stored as a range in the metadata so itdoesn’t require much space and is faster. Other indexes willbe included as columns in the file output.

engine_kwargsdict[str, Any] or None, default None

Additional keyword arguments passed topyarrow.orc.write_table().

Returns:

bytes if no path argument is provided else None

Raises:

NotImplementedError

Dtype of one or more columns is category, unsigned integers, interval,period or sparse.

ValueError

engine is not pyarrow.

See also

read_orc

Read a ORC file.

DataFrame.to_parquet

Write a parquet file.

DataFrame.to_csv

Write a csv file.

DataFrame.to_sql

Write to a sql table.

DataFrame.to_hdf

Write to hdf.

Notes

• Before using this function you should read theuser guide aboutORC andinstall optional dependencies.

• This function requirespyarrowlibrary.

• For supported dtypes please refer tosupported ORC features in Arrow.

• Currently timezones in datetime columns are not preserved when adataframe is converted into ORC files.

Examples

>>>df=pd.DataFrame(data={'col1':[1,2],'col2':[4,3]})>>>df.to_orc('df.orc')>>>pd.read_orc('df.orc')   col1  col20     1     41     2     3

If you want to get a buffer to the orc content you can write it to io.BytesIO

>>>importio>>>b=io.BytesIO(df.to_orc())>>>b.seek(0)0>>>content=b.read()