pandas.Series.struct.field#
- Series.struct.field(name_or_index)[source]#
Extract a child field of a struct as a Series.
- Parameters:
- name_or_indexstr | bytes | int | expression | list
Name or index of the child field to extract.
For list-like inputs, this will index into a nested struct.
- Returns:
- pandas.Series
The data corresponding to the selected child field.
See also
Series.struct.explode
Return all child fields as a DataFrame.
Notes
The name of the resulting Series will be set using the following rules:
For string, bytes, or integer name_or_index (or a list of these, for a nested selection), the Series name is set to the selected field’s name.
For a
pyarrow.compute.Expression
, this is set to the string form of the expression.For list-like name_or_index, the name will be set to the name of the final field selected.
Examples
>>> import pyarrow as pa >>> s = pd.Series( ... [ ... {"version": 1, "project": "pandas"}, ... {"version": 2, "project": "pandas"}, ... {"version": 1, "project": "numpy"}, ... ], ... dtype=pd.ArrowDtype(pa.struct( ... [("version", pa.int64()), ("project", pa.string())] ... )) ... )
Extract by field name.
>>> s.struct.field("project") 0 pandas 1 pandas 2 numpy Name: project, dtype: string[pyarrow]
Extract by field index.
>>> s.struct.field(0) 0 1 1 2 2 1 Name: version, dtype: int64[pyarrow]
Or an expression
>>> import pyarrow.compute as pc >>> s.struct.field(pc.field("project")) 0 pandas 1 pandas 2 numpy Name: project, dtype: string[pyarrow]
For nested struct types, you can pass a list of values to index multiple levels:
>>> version_type = pa.struct([ ... ("major", pa.int64()), ... ("minor", pa.int64()), ... ]) >>> s = pd.Series( ... [ ... {"version": {"major": 1, "minor": 5}, "project": "pandas"}, ... {"version": {"major": 2, "minor": 1}, "project": "pandas"}, ... {"version": {"major": 1, "minor": 26}, "project": "numpy"}, ... ], ... dtype=pd.ArrowDtype(pa.struct( ... [("version", version_type), ("project", pa.string())] ... )) ... ) >>> s.struct.field(["version", "minor"]) 0 5 1 1 2 26 Name: minor, dtype: int64[pyarrow] >>> s.struct.field([0, 0]) 0 1 1 2 2 1 Name: major, dtype: int64[pyarrow]