bigframes.pandas.DataFrame.explode#

DataFrame.explode(column: Hashable | Sequence[Hashable], *, ignore_index: bool | None = False) → DataFrame[source]#

Transform each element of an array to a row, replicating index values.

Examples:

>>> df = bpd.DataFrame({'A': [[0, 1, 2], [], [], [3, 4]],
...                     'B': 1,
...                     'C': [['a', 'b', 'c'], np.nan, [], ['d', 'e']]})
>>> df.explode('A')
    A  B              C
0     0  1  ['a' 'b' 'c']
0     1  1  ['a' 'b' 'c']
0     2  1  ['a' 'b' 'c']
1  <NA>  1             []
2  <NA>  1             []
3     3  1      ['d' 'e']
3     4  1      ['d' 'e']

[7 rows x 3 columns]
>>> df.explode(list('AC'))
    A  B     C
0     0  1     a
0     1  1     b
0     2  1     c
1  <NA>  1  <NA>
2  <NA>  1  <NA>
3     3  1     d
3     4  1     e

[7 rows x 3 columns]

Parameters:

• column (str, Sequence[str]) Column(s) to explode. For multiple columns, specify a non-empty list with each element be str or tuple, and all specified columns their list-like data on same row of the frame must have matching length.

• ignore_index (bool, default False) If True, the resulting index will be labeled 0, 1, , n - 1.

Returns:

Exploded lists to rows of the subset columns; index will be duplicated for these rows.

Return type:

bigframes.pandas.DataFrame

Raises:

• ValueError

  • If columns of the frame are not unique. * If specified columns to explode is empty list. * If specified columns to explode have not matching count of elements rowwise in the frame.

• KeyError If incorrect column names are provided