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# pandas.api.typing.DataFrameGroupBy.all

DataFrameGroupBy.all(skipna=True)

  Return True if all values in the group are truthful, else False.

  This is equivalent to calling `bool` on each value in the group and returning `True` only if all are truthful.

  Parameters:
    skipna bool, default True

      Flag to ignore nan values during truth testing.

  Returns:
    Series or DataFrame

      DataFrame or Series of boolean values, where a value is True if all elements are True within its respective group, False otherwise.

  See also

  `Series.all`

    Apply function all to a Series.

  `DataFrame.all`

    Apply function all to each row or column of a DataFrame.

  Examples

  For SeriesGroupBy:

      >>> lst = ["a", "a", "b"]
      >>> ser = pd.Series([1, 2, 0], index=lst)
      >>> ser
      a    1
      a    2
      b    0
      dtype: int64
      >>> ser.groupby(level=0).all()
      a     True
      b    False
      dtype: bool

  For DataFrameGroupBy:

      >>> data = [[1, 0, 3], [1, 5, 6], [7, 8, 9]]
      >>> df = pd.DataFrame(
      ...     data, columns=["a", "b", "c"], index=["ostrich", "penguin", "parrot"]
      ... )
      >>> df
               a  b  c
      ostrich  1  0  3
      penguin  1  5  6
      parrot   7  8  9
      >>> df.groupby(by=["a"]).all()
             b      c
      a
      1  False   True
      7   True   True