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 nestedstruct.

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 followingrules:

• For string, bytes, or integername_or_index (or a list of these, fora nested selection), the Series name is set to the selectedfield’s name.

• For apyarrow.compute.Expression, this is set tothe string form of the expression.

• For list-likename_or_index, the name will be set to thename of the final field selected.

Examples

>>>importpyarrowaspa>>>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    pandas1    pandas2     numpyName: project, dtype: string[pyarrow]

Extract by field index.

>>>s.struct.field(0)0    11    22    1Name: version, dtype: int64[pyarrow]

Or an expression

>>>importpyarrow.computeaspc>>>s.struct.field(pc.field("project"))0    pandas1    pandas2     numpyName: project, dtype: string[pyarrow]

For nested struct types, you can pass a list of values to indexmultiple 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     51     12    26Name: minor, dtype: int64[pyarrow]>>>s.struct.field([0,0])0    11    22    1Name: major, dtype: int64[pyarrow]