pandas.core.groupby.SeriesGroupBy.all#

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

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

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.groupby: Apply a function groupby to a Series.
DataFrame.groupby: Apply a function groupby 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