cudf.Series.to_pandas#

Series.to_pandas(*, index: bool = True, nullable: bool = False, arrow_type: bool = False) → Series[source]#

Convert to a pandas Series.

Parameters:

indexBoolean, Default True: If index is True, converts the index of cudf.Series and sets it to the pandas.Series. If index is False, no index conversion is performed and pandas.Series will assign a default index.
nullableBoolean, Default False: If nullable is True, the resulting series will be having a corresponding nullable Pandas dtype. If there is no corresponding nullable Pandas dtype present, the resulting dtype will be a regular pandas dtype. If nullable is False, the resulting series will either convert null values to np.nan or None depending on the dtype.
arrow_typebool, Default False: Return the Series with a pandas.ArrowDtype

Returns:

outpandas Series

Notes

nullable and arrow_type cannot both be set to True

Examples

>>> import cudf
>>> ser = cudf.Series([-3, 2, 0])
>>> pds = ser.to_pandas()
>>> pds
0   -3
1    2
2    0
dtype: int64
>>> type(pds)
<class 'pandas.core.series.Series'>

nullable=True converts the result to pandas nullable types:

>>> ser = cudf.Series([10, 20, None, 30])
>>> ser
0      10
1      20
2    <NA>
3      30
dtype: int64
>>> ser.to_pandas(nullable=True)
0      10
1      20
2    <NA>
3      30
dtype: Int64
>>> ser.to_pandas(nullable=False)
0    10.0
1    20.0
2     NaN
3    30.0
dtype: float64

arrow_type=True converts the result to pandas.ArrowDtype:

>>> ser.to_pandas(arrow_type=True)
0      10
1      20
2    <NA>
3      30
dtype: int64[pyarrow]