NUM: inequality with complex dtypes #28050
Description
TL;DR: our comparisons with complex dtypes are not internally consistent:
arr = np.arange(5).astype(np.complex128)
ser = pd.Series(arr)
df = ser.to_frame()
>>> df < df.astype(object)
[...]
TypeError: '<' not supported between instances of 'complex' and 'complex'
>>> df.lt(df.astype(object))
0
0 False
1 False
2 False
3 False
4 False
Digging into this...
numpy has some surprising behavior for comparing complex dtypes:
arr = np.arange(5)
arr = arr + arr*1j
arr2 = arr*2 - 1
>>> arr < arr2
array([False, True, True, True, True])
I would expect these inequalities to be undefined, and in fact, if we cast to object we get a TypeError:
>>> arr < arr2.astype(object)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: '<' not supported between instances of 'complex' and 'complex'
That's the behavior I expected in the first place, but then trying it on just the scalars:
>>> arr[0] < arr2[0]
False