pyspark.pandas.DataFrame.explode#
- DataFrame.explode(column, ignore_index=False)[source]#
Transform each element of a list-like to a row, replicating index values.
- Parameters
- columnstr or tuple
Column to explode.
- ignore_indexbool, default False
If True, the resulting index will be labeled 0, 1, …, n - 1.
- Returns
- DataFrame
Exploded lists to rows of the subset columns; index will be duplicated for these rows.
See also
DataFrame.unstack
Pivot a level of the (necessarily hierarchical) index labels.
DataFrame.melt
Unpivot a DataFrame from wide format to long format.
Examples
>>> df = ps.DataFrame({'A': [[1, 2, 3], [], [3, 4]], 'B': 1}) >>> df A B 0 [1, 2, 3] 1 1 [] 1 2 [3, 4] 1
>>> df.explode('A') A B 0 1.0 1 0 2.0 1 0 3.0 1 1 NaN 1 2 3.0 1 2 4.0 1
>>> df.explode('A', ignore_index=True) A B 0 1.0 1 1 2.0 1 2 3.0 1 3 NaN 1 4 3.0 1 5 4.0 1