REF: unstack #33474
Merged
REF: unstack #33474
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
gfyoung
added
Refactor
jreback
reviewed
Apr 12, 2020
| @@ -205,6 +205,9 @@ def get_new_values(self, values, fill_value=None): | |||
|
|
|||
| # we can simply reshape if we don't have a mask | |||
| if mask_all and len(values): | |||
| # TODO: Under what circumstances can we rely on sorted_values | |||
There was a problem hiding this comment.
I think if the we are sorted already then you can simplify, but I am not sure we can make that guarantee.
|
looks fine. you can try experimenting if you try to unstack on a non-sorted index and raising and see what breaks. |
3 tasks
| new_values = new_values.T[mask] | ||
| new_placement = new_placement[mask] | ||
|
|
||
| blocks = [make_block(new_values, placement=new_placement)] | ||
| blocks = [self.make_block_same_class(new_values, placement=new_placement)] |
There was a problem hiding this comment.
@jbrockmendel I think it's just this line that caused the regression in #37115 and that we don't need to revert the complete PR.
There was a problem hiding this comment.
what kind of block(s) do you end up with instead?
There was a problem hiding this comment.
corrupted? an IntBlock with dtype float64
>>> pd.__version__
'1.2.0.dev0+1432.g5fdf642368'
>>>
>>> df1 = pd.DataFrame(
... {
... "a": ["A", "A", "B"],
... "b": ["ca", "cb", "cb"],
... "v": [10] * 3,
... }
... )
>>> df1 = df1.set_index(["a", "b"])
>>> df1["is_"] = 1
>>> df1
v is_
a b
A ca 10 1
cb 10 1
B cb 10 1
>>>
>>> df1._data
BlockManager
Items: Index(['v', 'is_'], dtype='object')
Axis 1: MultiIndex([('A', 'ca'),
('A', 'cb'),
('B', 'cb')],
names=['a', 'b'])
IntBlock: slice(0, 1, 1), 1 x 3, dtype: int64
IntBlock: slice(1, 2, 1), 1 x 3, dtype: int64
>>>
>>> df2 = df1.unstack("b")
>>> df2
v is_
b ca cb ca cb
a
A 10.0 10.0 1.0 1.0
B NaN 10.0 NaN 1.0
>>>
>>> df2._data
BlockManager
Items: MultiIndex([( 'v', 'ca'),
( 'v', 'cb'),
('is_', 'ca'),
('is_', 'cb')],
names=[None, 'b'])
Axis 1: Index(['A', 'B'], dtype='object', name='a')
IntBlock: slice(0, 2, 1), 2 x 2, dtype: float64
IntBlock: slice(2, 4, 1), 2 x 2, dtype: float64
>>>
There was a problem hiding this comment.
run the test suite with just this change reverted and all tests pass. will put up a PR shortly.
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
cc @jreback this moves a small amount of the unstack logic up the call stack, which is worthwhile, but the big wins available are if you can help me figure out the questions in inline comments.