CLN: consistent signatures for equals methods

[simonjayhawkins]

No description provided.

[simonjayhawkins]

from #33940

Index and Series are consistent when it comes to not being equal with other array-likes:

not necessarily in this PR, but is this behaviour consistent with other Index types

>>> x = np.linspace(0, 100, num=3)
>>> x
array([  0.,  50., 100.])
>>>
>>> idx = pd.IntervalIndex.from_breaks(x)
>>> idx
IntervalIndex([(0.0, 50.0], (50.0, 100.0]],
              closed='right',
              dtype='interval[float64]')
>>>
>>> arr = idx.values
>>> arr
<IntervalArray>
[(0.0, 50.0], (50.0, 100.0]]
Length: 2, closed: right, dtype: interval[float64]
>>>
>>> idx.equals(arr)
True
>>>
>>> arr.equals(idx)
False
>>>

[jreback]

i guess this is fine, though more consisten to use is_dtype_equal no?

[simonjayhawkins]

I had to break the if elif to get the cast in. so this is unchanged. but agreed is_dtype_equal would be more consistent so will update.

[jreback]

couple of places where codecov thinks we don't have tests, in a followup can remove / test if possible..

[simonjayhawkins]

couple of places where codecov thinks we don't have tests, in a followup can remove / test if possible..

the code added was from static analysis. (mypy is still testing but codecov thinks we don't have tests)

so in this case we don't want to remove.

dynamic type testing has become less necessary now we are using mypy.