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# pandas.Series.explode

Series.explode(ignore_index=False)

  Transform each element of a list-like to a row.

  This method expands list-like elements so that each item in the list gets its own row, while non-list-like elements remain unchanged. The index is duplicated for the expanded rows.

  Parameters:
    ignore_index bool, default False

      If True, the resulting index will be labeled 0, 1, …, n - 1.

  Returns:
    Series

      Exploded lists to rows; index will be duplicated for these rows.

  See also

  `Series.str.split`

    Split string values on specified separator.

  `Series.unstack`

    Unstack, a.k.a. pivot, Series with MultiIndex to produce DataFrame.

  `DataFrame.melt`

    Unpivot a DataFrame from wide format to long format.

  `DataFrame.explode`

    Explode a DataFrame from list-like columns to long format.

  Notes

  This routine will explode list-likes including lists, tuples, sets, Series, and np.ndarray. The result dtype of the subset rows will be object. Scalars will be returned unchanged, and empty list-likes will result in an np.nan for that row. In addition, the ordering of elements in the output will be non-deterministic when exploding sets.

  Reference the user guide for more examples.

  Examples

      >>> s = pd.Series([[1, 2, 3], "foo", [], [3, 4]])
      >>> s
      0    [1, 2, 3]
      1          foo
      2           []
      3       [3, 4]
      dtype: object

      >>> s.explode()
      0      1
      0      2
      0      3
      1    foo
      2    NaN
      3      3
      3      4
      dtype: object