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Support non unique period indexes on join and merge operations #16949

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Jul 15, 2017
Merged

Support non unique period indexes on join and merge operations #16949

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e841c53
Support non unique period indexes on join and merge operations
alanbato Jul 15, 2017
40b964a
Add frame assertion on tests and release notes
alanbato Jul 15, 2017
1560d75
Explicitly use dtype int64 on arange
alanbato Jul 15, 2017
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4 changes: 2 additions & 2 deletions pandas/core/indexes/base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3119,14 +3119,14 @@ def _join_multi(self, other, how, return_indexers=True):
def _join_non_unique(self, other, how='left', return_indexers=False):
from pandas.core.reshape.merge import _get_join_indexers

left_idx, right_idx = _get_join_indexers([self.values],
left_idx, right_idx = _get_join_indexers([self._values],
[other._values], how=how,
sort=True)

left_idx = _ensure_platform_int(left_idx)
right_idx = _ensure_platform_int(right_idx)

join_index = np.asarray(self.values.take(left_idx))
join_index = np.asarray(self._values.take(left_idx))
mask = left_idx == -1
np.putmask(join_index, mask, other._values.take(right_idx))

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7 changes: 7 additions & 0 deletions pandas/tests/reshape/test_join.py
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Expand Up @@ -550,6 +550,13 @@ def test_join_mixed_non_unique_index(self):
index=[1, 2, 2, 'a'])
tm.assert_frame_equal(result, expected)

def test_join_non_unique_period_index(self):
per_index = pd.period_range('2016-01-01', periods=16, freq='M')
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add the issue number here as a comment

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call this index

per_df = DataFrame([i for i in range(len(per_index))],
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call this df

index=per_index, columns=['pnum'])
df2 = concat([per_df, per_df])
per_df.join(df2, how='outer', rsuffix='_df2')
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result =

and provide an expected result; compare using tm.assert_frame_equal


def test_mixed_type_join_with_suffix(self):
# GH #916
df = DataFrame(np.random.randn(20, 6),
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7 changes: 7 additions & 0 deletions pandas/tests/reshape/test_merge.py
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Expand Up @@ -585,6 +585,13 @@ def test_merge_on_datetime64tz(self):
assert result['value_x'].dtype == 'datetime64[ns, US/Eastern]'
assert result['value_y'].dtype == 'datetime64[ns, US/Eastern]'

def test_merge_non_unique_period_index(self):
per_index = pd.period_range('2016-01-01', periods=16, freq='M')
per_df = DataFrame([i for i in range(len(per_index))],
index=per_index, columns=['pnum'])
df2 = concat([per_df, per_df])
per_df.merge(df2, left_index=True, right_index=True, how='outer')

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same here

def test_merge_on_periods(self):
left = pd.DataFrame({'key': pd.period_range('20151010', periods=2,
freq='D'),
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