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BUG: fix IntervalIndex for pivot table raise type error #26765

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Merged
merged 12 commits into from
Jun 13, 2019
Merged

BUG: fix IntervalIndex for pivot table raise type error #26765

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c242a8e
BUG: Cannot use categorical IntervalIndex as index when creating pivo…
peterpanmj Jun 6, 2019
28fa071
modify tests for reshape pivot for interval index
peterpanmj Jun 11, 2019
f8b39f3
add issue number in the updated test for inteval index
peterpanmj Jun 11, 2019
e6d1249
update whatsnews's reshaping section
peterpanmj Jun 11, 2019
6ddeb26
update reshape/test_pivot.py
peterpanmj Jun 12, 2019
44ab111
update whatsnew ,add backticks for TypeError
peterpanmj Jun 12, 2019
b011bbc
simplify tests cases when create Dataframe
peterpanmj Jun 12, 2019
d6b06e4
use double backticks for TypeError in whatsnew
peterpanmj Jun 12, 2019
72a316e
move whatsnew entry from v0.24.2 to v0.25.0
peterpanmj Jun 12, 2019
1e0b5e4
remove extra fixtures in test_pivot, use top level conftest instead
peterpanmj Jun 12, 2019
be7f21a
modification of whatsnew entry
peterpanmj Jun 12, 2019
64dcfee
Merge remote-tracking branch 'upstream/master' into peterpanmj-cat_index
TomAugspurger Jun 13, 2019
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2 changes: 1 addition & 1 deletion pandas/core/arrays/categorical.py
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Original file line number Diff line number Diff line change
Expand Up @@ -181,7 +181,7 @@ def contains(cat, key, container):
# can't be in container either.
try:
loc = cat.categories.get_loc(key)
except KeyError:
except (KeyError, TypeError):
return False

# loc is the location of key in categories, but also the *value*
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11 changes: 11 additions & 0 deletions pandas/tests/reshape/test_pivot.py
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Expand Up @@ -198,6 +198,17 @@ def test_pivot_with_non_observable_dropna(self, dropna):

tm.assert_frame_equal(result, expected)

def test_pivot_with_interval_index(self, dropna):
df = pd.DataFrame(
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can you add the issue number as a comment

{'A': pd.Categorical([pd.Interval(0, 1)] * 4),
'B': [1] * 4})
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does this fully replicate the OP issue?

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I just added a fixture to include more scenarios.

result = df.pivot_table(index='A', values='B', dropna=dropna)
expected = pd.DataFrame(
{'B': [1]},
index=pd.Index(pd.Categorical([pd.Interval(0, 1)]),
name='A'))
tm.assert_frame_equal(result, expected)

def test_pass_array(self):
result = self.data.pivot_table(
'D', index=self.data.A, columns=self.data.C)
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