CLN: consistent signatures for equals methods #35636
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| """ | ||
| Determines if two IntervalIndex objects contain the same elements. | ||
| """ | ||
| if self.is_(other): | ||
| return True | ||
|
|
||
| # if we can coerce to an II | ||
| # then we can compare | ||
| # if we can coerce to an IntervalIndex then we can compare |
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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
>>>
pandas/core/arrays/base.py
Outdated
| @@ -762,7 +762,8 @@ def equals(self, other: "ExtensionArray") -> bool: | |||
| """ | |||
| if not type(self) == type(other): | |||
| return False | |||
| elif not self.dtype == other.dtype: | |||
| other = cast(ExtensionArray, other) | |||
| if not self.dtype == other.dtype: | |||
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i guess this is fine, though more consisten to use is_dtype_equal no?
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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.
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. |
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