doctest issues

Author: topper-123

pandas/core/generic.py

@@ -10485,7 +10485,7 @@ def _doc_parms(cls):
 True
 >>> pd.Series([True, False]).all()
 False
->>> pd.Series([]).all()
+>>> pd.Series([], dtype=object).all()
 True
 >>> pd.Series([np.nan]).all()
 True
@@ -10853,7 +10853,7 @@ def _doc_parms(cls):
 False
 >>> pd.Series([True, False]).any()
 True
->>> pd.Series([]).any()
+>>> pd.Series([], dtype=object).any()
 False
 >>> pd.Series([np.nan]).any()
 False
@@ -10955,13 +10955,13 @@ def _doc_parms(cls):
 
 By default, the sum of an empty or all-NA Series is ``0``.
 
->>> pd.Series([]).sum()  # min_count=0 is the default
+>>> pd.Series([], dtype=float).sum()  # min_count=0 is the default
 0.0
 
 This can be controlled with the ``min_count`` parameter. For example, if
 you'd like the sum of an empty series to be NaN, pass ``min_count=1``.
 
->>> pd.Series([]).sum(min_count=1)
+>>> pd.Series([], dtype=float).sum(min_count=1)
 nan
 
 Thanks to the ``skipna`` parameter, ``min_count`` handles all-NA and
@@ -11002,12 +11002,12 @@ def _doc_parms(cls):
 --------
 By default, the product of an empty or all-NA Series is ``1``
 
->>> pd.Series([]).prod()
+>>> pd.Series([], dtype=float).prod()
 1.0
 
 This can be controlled with the ``min_count`` parameter
 
->>> pd.Series([]).prod(min_count=1)
+>>> pd.Series([], dtype=float).prod(min_count=1)
 nan
 
 Thanks to the ``skipna`` parameter, ``min_count`` handles all-NA and