pandas.api.typing.SeriesGroupBy.all#

SeriesGroupBy.all(skipna=True)[source]#

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:

skipnabool, 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