pandas で NaN に対する論理和(or)と論理積(and)

import pandas as pd
import numpy as np

s1 = pd.Series([np.nan, 2, 3])
s2 = pd.Series([4, np.nan, 6])

# s1 の値:
# 0    NaN
# 1    2.0
# 2    3.0
# dtype: float64

# s2 の値:
# 0    4.0
# 1    NaN
# 2    6.0
# dtype: float64

s1 | s2
# 結果:
# ---------------------------------------------------------------------------
# TypeError                                 Traceback (most recent call last)
# File /opt/conda/lib/python3.10/site-packages/pandas/core/ops/array_ops.py:301, in na_logical_op(x, y, op)
#     292 try:
#     293     # For exposition, write:
#     294     #  yarr = isinstance(y, np.ndarray)
#    (...)
#     299     # Then Cases where this goes through without raising include:
#     300     #  (xint or xbool) and (yint or bool)
# --> 301     result = op(x, y)
#     302 except TypeError:
#
# TypeError: unsupported operand type(s) for |: 'float' and 'float'
#
# During handling of the above exception, another exception occurred:
#
# TypeError                                 Traceback (most recent call last)
# Input In [25], in <cell line: 1>()
# ----> 1 s1 | s2
#
# File /opt/conda/lib/python3.10/site-packages/pandas/core/ops/common.py:70, in _unpack_zerodim_and_defer.<locals>.new_method(self, other)
#      66             return NotImplemented
#      68 other = item_from_zerodim(other)
# ---> 70 return method(self, other)
#
# File /opt/conda/lib/python3.10/site-packages/pandas/core/arraylike.py:78, in OpsMixin.__or__(self, other)
#      76 @unpack_zerodim_and_defer("__or__")
#      77 def __or__(self, other):
# ---> 78     return self._logical_method(other, operator.or_)
#
# File /opt/conda/lib/python3.10/site-packages/pandas/core/series.py:5634, in Series._logical_method(self, other, op)
#    5631 lvalues = self._values
#    5632 rvalues = extract_array(other, extract_numpy=True, extract_range=True)
# -> 5634 res_values = ops.logical_op(lvalues, rvalues, op)
#    5635 return self._construct_result(res_values, name=res_name)
#
# File /opt/conda/lib/python3.10/site-packages/pandas/core/ops/array_ops.py:391, in logical_op(left, right, op)
#     387 # For int vs int `^`, `|`, `&` are bitwise operators and return
#     388 #   integer dtypes.  Otherwise these are boolean ops
#     389 filler = fill_int if is_self_int_dtype and is_other_int_dtype else fill_bool
# --> 391 res_values = na_logical_op(lvalues, rvalues, op)
#     392 # error: Cannot call function of unknown type
#     393 res_values = filler(res_values)  # type: ignore[operator]
#
# File /opt/conda/lib/python3.10/site-packages/pandas/core/ops/array_ops.py:308, in na_logical_op(x, y, op)
#     306     x = ensure_object(x)
#     307     y = ensure_object(y)
# --> 308     result = libops.vec_binop(x.ravel(), y.ravel(), op)
#     309 else:
#     310     # let null fall thru
#     311     assert lib.is_scalar(y)
#
# File /opt/conda/lib/python3.10/site-packages/pandas/_libs/ops.pyx:252, in pandas._libs.ops.vec_binop()
#
# File /opt/conda/lib/python3.10/site-packages/pandas/_libs/ops.pyx:245, in pandas._libs.ops.vec_binop()
#
# TypeError: unsupported operand type(s) for |: 'float' and 'bool'

s1 or s2
# ---------------------------------------------------------------------------
# ValueError                                Traceback (most recent call last)
# Input In [26], in <cell line: 1>()
# ----> 1 s1 or s2
#
# File /opt/conda/lib/python3.10/site-packages/pandas/core/generic.py:1527, in NDFrame.__nonzero__(self)
#    1525 @final
#    1526 def __nonzero__(self):
# -> 1527     raise ValueError(
#    1528         f"The truth value of a {type(self).__name__} is ambiguous. "
#    1529         "Use a.empty, a.bool(), a.item(), a.any() or a.all()."
#    1530     )
#
# ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

s1 * 0 + s2

# 0    NaN
# 1    NaN
# 2    6.0
# dtype: float64

s1.combine_first(s2)

# 0    4.0
# 1    2.0
# 2    3.0
# dtype: float64