to_lists

to_lists#

NestSeriesAccessor.to_lists(columns: list[str] | str | None = None, large_list: bool = False) → DataFrame[source]#

Convert nested series into dataframe of list-array columns

Parameters:

  • columns (list[str] or str or None, optional) – Names of the column(s) to include. Default is None, which means all columns.

  • large_list (bool, optional) – If False (default), use regular list_ (int32 offsets). Set to True to use large_list (int64 offsets), which is required when the total number of nested elements across all rows exceeds ~2.1 billion (int32 max).

Returns:

Dataframe of list-arrays.

Return type:

pd.DataFrame

Examples

>>> from nested_pandas.datasets.generation import generate_data
>>> nf = generate_data(5, 2, seed=1)

>>> nf["nested"].nest.to_lists()
                           t                       flux flux_error       band
0  [ 8.38389029 13.4093502 ]  [80.07445687 89.46066635]    [1. 1.]  ['r' 'g']
1  [13.70439001  8.34609605]  [96.82615757  8.50442114]    [1. 1.]  ['g' 'g']
2  [ 4.08904499 11.17379657]  [31.34241782  3.90547832]    [1. 1.]  ['g' 'g']
3  [17.56234873  2.80773877]  [69.23226157 16.98304196]    [1. 1.]  ['r' 'r']
4    [0.54775186 3.96202978]  [87.63891523 87.81425034]    [1. 1.]  ['g' 'r']