Raise ValueError when using levels with non-unique values in MultiIndex constructor #17557
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jschendel
reviewed
Sep 17, 2017
pandas/core/indexes/multi.py
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| for i, level in enumerate(levels): | ||
| if len(level) != len(set(level)): | ||
| raise ValueError("Level values must be unique: %s " | ||
| "on level %d" % ([value for value |
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Can you use .format syntax instead of %? I realize that other places within this file use % formatting, but there's an ongoing effort to transition all % formatting in the pandas codebase to .format, so might as well minimize the number of changes that will need to be made.
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Of course! I do prefer .format but decided to stick with % because of the other tests. Thank you for telling me, I'll keep it in mind in future contributions :)
jreback
requested changes
Sep 17, 2017
pandas/core/indexes/multi.py
Outdated
| for i, level in enumerate(levels): | ||
| if len(level) != len(set(level)): | ||
| raise ValueError("Level values must be unique: {0}" | ||
| " on level {1}".format([value for value |
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your check is not checking the values
i would be surprised that you have any failures though it is possible
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I'm checking if all the values inside a level are unique by comparing its length with the length of the set containing all the unique values. Should I be doing it in some other way? Maybe I misunderstood what needs to be checked.
Here are the tests that failed with the new check
========================================================================================== FAILURES ==========================================================================================
__________________________________________________________________________________ TestMultiIndex.test_is_ ___________________________________________________________________________________
self = <pandas.tests.indexes.test_multi.TestMultiIndex object at 0x7fb0e671a780>
def test_is_(self):
mi = MultiIndex.from_tuples(lzip(range(10), range(10)))
assert mi.is_(mi)
assert mi.is_(mi.view())
assert mi.is_(mi.view().view().view().view())
mi2 = mi.view()
# names are metadata, they don't change id
mi2.names = ["A", "B"]
assert mi2.is_(mi)
assert mi.is_(mi2)
assert mi.is_(mi.set_names(["C", "D"]))
mi2 = mi.view()
mi2.set_names(["E", "F"], inplace=True)
assert mi.is_(mi2)
# levels are inherent properties, they change identity
mi3 = mi2.set_levels([lrange(10), lrange(10)])
assert not mi3.is_(mi2)
# shouldn't change
assert mi2.is_(mi)
mi4 = mi3.view()
> mi4.set_levels([[1 for _ in range(10)], lrange(10)], inplace=True)
pandas/tests/indexes/test_multi.py:1584:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
pandas/core/indexes/multi.py:254: in set_levels
verify_integrity=verify_integrity)
pandas/core/indexes/multi.py:183: in _set_levels
self._verify_integrity(levels=new_levels)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = MultiIndex(levels=[[0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]],
labels=[[0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]],
names=['E', 'F'])
labels = FrozenList([[0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]]), levels = FrozenList([[1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]])
def _verify_integrity(self, labels=None, levels=None):
"""
Parameters
----------
labels : optional list
Labels to check for validity. Defaults to current labels.
levels : optional list
Levels to check for validity. Defaults to current levels.
Raises
------
ValueError
* if length of levels and labels don't match or any label would
exceed level bounds
"""
# NOTE: Currently does not check, among other things, that cached
# nlevels matches nor that sortorder matches actually sortorder.
labels = labels or self.labels
levels = levels or self.levels
if len(levels) != len(labels):
raise ValueError("Length of levels and labels must match. NOTE:"
" this index is in an inconsistent state.")
label_length = len(self.labels[0])
for i, (level, label) in enumerate(zip(levels, labels)):
if len(label) != label_length:
raise ValueError("Unequal label lengths: %s" %
([len(lab) for lab in labels]))
if len(label) and label.max() >= len(level):
raise ValueError("On level %d, label max (%d) >= length of"
" level (%d). NOTE: this index is in an"
" inconsistent state" % (i, label.max(),
len(level)))
for i, level in enumerate(levels):
if len(level) != len(set(level)):
raise ValueError("Level values must be unique: {0}"
" on level {1}".format([value for value
> in level], i))
E ValueError: Level values must be unique: [1, 1, 1, 1, 1, 1, 1, 1, 1, 1] on level 0
pandas/core/indexes/multi.py:154: ValueError
____________________________________________________________________ TestMultiIndex.test_level_setting_resets_attributes _____________________________________________________________________
self = <pandas.tests.indexes.test_multi.TestMultiIndex object at 0x7fb0e69834e0>
def test_level_setting_resets_attributes(self):
ind = MultiIndex.from_arrays([
['A', 'A', 'B', 'B', 'B'], [1, 2, 1, 2, 3]
])
assert ind.is_monotonic
ind.set_levels([['A', 'B', 'A', 'A', 'B'], [2, 1, 3, -2, 5]],
> inplace=True)
pandas/tests/indexes/test_multi.py:2387:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
pandas/core/indexes/multi.py:254: in set_levels
verify_integrity=verify_integrity)
pandas/core/indexes/multi.py:183: in _set_levels
self._verify_integrity(levels=new_levels)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = MultiIndex(levels=[['A', 'B'], [1, 2, 3]],
labels=[[0, 0, 1, 1, 1], [0, 1, 0, 1, 2]]), labels = FrozenList([[0, 0, 1, 1, 1], [0, 1, 0, 1, 2]])
levels = FrozenList([['A', 'B', 'A', 'A', 'B'], [2, 1, 3, -2, 5]])
def _verify_integrity(self, labels=None, levels=None):
"""
Parameters
----------
labels : optional list
Labels to check for validity. Defaults to current labels.
levels : optional list
Levels to check for validity. Defaults to current levels.
Raises
------
ValueError
* if length of levels and labels don't match or any label would
exceed level bounds
"""
# NOTE: Currently does not check, among other things, that cached
# nlevels matches nor that sortorder matches actually sortorder.
labels = labels or self.labels
levels = levels or self.levels
if len(levels) != len(labels):
raise ValueError("Length of levels and labels must match. NOTE:"
" this index is in an inconsistent state.")
label_length = len(self.labels[0])
for i, (level, label) in enumerate(zip(levels, labels)):
if len(label) != label_length:
raise ValueError("Unequal label lengths: %s" %
([len(lab) for lab in labels]))
if len(label) and label.max() >= len(level):
raise ValueError("On level %d, label max (%d) >= length of"
" level (%d). NOTE: this index is in an"
" inconsistent state" % (i, label.max(),
len(level)))
for i, level in enumerate(levels):
if len(level) != len(set(level)):
raise ValueError("Level values must be unique: {0}"
" on level {1}".format([value for value
> in level], i))
E ValueError: Level values must be unique: ['A', 'B', 'A', 'A', 'B'] on level 0
pandas/core/indexes/multi.py:154: ValueError
================================================================ 2 failed, 189 passed, 2 skipped, 1 xfailed in 18.21 seconds =================================================================
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The very first example is wrong
In [17]: mi
Out[17]:
MultiIndex(levels=[[0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]],
labels=[[0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]],
names=['E', 'F'])
In [18]: mi.levels[0]
Out[18]: Int64Index([0, 1, 2, 3, 4, 5, 6, 7, 8, 9], dtype='int64', name='E')
In [19]: mi.levels[1]
Out[19]: Int64Index([0, 1, 2, 3, 4, 5, 6, 7, 8, 9], dtype='int64', name='F')
In [20]: [set(level) for i, level in enumerate(mi.levels)]
Out[20]: [{0, 1, 2, 3, 4, 5, 6, 7, 8, 9}, {0, 1, 2, 3, 4, 5, 6, 7, 8, 9}]
In [22]: list(map(lambda x: x.is_unique, mi.levels))
Out[22]: [True, True]
you can prob do something like this (or rather iterate to show exactly where the error is)
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the example from the issue
In [31]: idx0 = range(2)
...: idx1 = np.repeat(range(2), 2)
...:
...: midx = pd.MultiIndex(
...: levels=[idx0, idx1],
...: labels=[
...: np.repeat(range(len(idx0)), len(idx1)),
...: np.tile(range(len(idx1)), len(idx0))
...: ],
...: names=['idx0', 'idx1']
...: )
...:
In [32]: list(map(lambda x: x.is_unique, midx.levels))
Out[32]: [True, False]
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Isn't the first example throwing out an error because it's replacing those levels with these?
levels = FrozenList([[1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]])
And the is_unique method is indeed a more clear way to do it, thanks!
Also, I'm having troubles running the performance checks with asv 😞 Some weird I/O shutil error while trying to do pip wheel
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@jreback I don't know if the conversation got lost due to the changes on that piece of code, so I'm pinging in case you thought I didn't reply. If you're just busy, sorry to bother you!
@TomAugspurger if you have time could you look at it? :)
Thanks, both of you!
|
needs performance checking whatsnew is in the other api changes section |
|
from #17557 (comment)
For the asv, are you using conda? That's typically easiest. |
|
@TomAugspurger I ran the command again and I got it to work, but I'm seeing really weird results in the performance test, everything is either above or below 10% . Are these normal? |
|
The I'll take a look later. |
|
Alright, ping me when you've gone through it. Thanks @TomAugspurger :) |
|
Perf looked fine, though the CI failures look relevant. |
|
Yes, I think I'll need to change those tests because they they have this faulty behavior. Any advice on that? |
|
this is being closed by #17971. thanks for the effort here. many other issues if you'd like to take a look! |
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git diff upstream/master -u -- "*.py" | flake8 --diffverify_integritynow also checks if any level has non-unique values and raisesValueErrorif one does.However, some tests were broken due to this new behaviour.
I'd like to know what should I do in this case, should I add
verify_integrity=Falseto those tests, change them, or do something else?Also, how should I state this in the whatsnew file and where?
Thank you for your time! 🐼 🐍