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BUG: first/last lose timezone in groupby with as_index=False #21573

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Merged
merged 4 commits into from
Jun 22, 2018
Merged

BUG: first/last lose timezone in groupby with as_index=False #21573

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4d7e1cf
BUG: first/last lose timezone in groupby
reidy-p Jun 19, 2018
f46ce84
simplify
jreback Jun 22, 2018
7408aab
Fix whatsnew and add tests
reidy-p Jun 22, 2018
ef5d5b1
lint
reidy-p Jun 22, 2018
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2 changes: 1 addition & 1 deletion doc/source/whatsnew/v0.24.0.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -225,7 +225,7 @@ Plotting
Groupby/Resample/Rolling
^^^^^^^^^^^^^^^^^^^^^^^^

-
- Bug in :func:`pandas.core.groupby.GroupBy.first` and :func:`pandas.core.groupby.GroupBy.last` with ``as_index=False`` leading to the loss of timezone information (:issue:`15884`)
-
-

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2 changes: 1 addition & 1 deletion pandas/core/groupby/groupby.py
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Expand Up @@ -4740,7 +4740,7 @@ def _wrap_transformed_output(self, output, names=None):

def _wrap_agged_blocks(self, items, blocks):
if not self.as_index:
index = np.arange(blocks[0].values.shape[1])
index = np.arange(blocks[0].values.shape[-1])
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@reidy-p pushed a simplification. but maybe need some additional tests that do this when a column is selected

e.g. df.groupby('id', as_index=False)['foo'].first()

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Nice simplification. I added some new tests.

mgr = BlockManager(blocks, [items, index])
result = DataFrame(mgr)

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61 changes: 60 additions & 1 deletion pandas/tests/groupby/test_nth.py
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@@ -1,11 +1,12 @@
import numpy as np
import pandas as pd
from pandas import DataFrame, MultiIndex, Index, Series, isna
from pandas import DataFrame, MultiIndex, Index, Series, isna, Timestamp
from pandas.compat import lrange
from pandas.util.testing import (
assert_frame_equal,
assert_produces_warning,
assert_series_equal)
import pytest


def test_first_last_nth(df):
Expand Down Expand Up @@ -219,6 +220,64 @@ def test_nth_multi_index(three_group):
assert_frame_equal(result, expected)


@pytest.mark.parametrize('data, expected_first, expected_last', [
({'id': ['A'],
'time': Timestamp('2012-02-01 14:00:00',
tz='US/Central'),
'foo': [1]},
{'id': ['A'],
'time': Timestamp('2012-02-01 14:00:00',
tz='US/Central'),
'foo': [1]},
{'id': ['A'],
'time': Timestamp('2012-02-01 14:00:00',
tz='US/Central'),
'foo': [1]}),
({'id': ['A', 'B', 'A'],
'time': [Timestamp('2012-01-01 13:00:00',
tz='America/New_York'),
Timestamp('2012-02-01 14:00:00',
tz='US/Central'),
Timestamp('2012-03-01 12:00:00',
tz='Europe/London')],
'foo': [1, 2, 3]},
{'id': ['A', 'B'],
'time': [Timestamp('2012-01-01 13:00:00',
tz='America/New_York'),
Timestamp('2012-02-01 14:00:00',
tz='US/Central')],
'foo': [1, 2]},
{'id': ['A', 'B'],
'time': [Timestamp('2012-03-01 12:00:00',
tz='Europe/London'),
Timestamp('2012-02-01 14:00:00',
tz='US/Central')],
'foo': [3, 2]})
])
def test_first_last_tz(data, expected_first, expected_last):
# GH15884
# Test that the timezone is retained when calling first
# or last on groupby with as_index=False

df = DataFrame(data)

result = df.groupby('id', as_index=False).first()
expected = DataFrame(expected_first)
cols = ['id', 'time', 'foo']
assert_frame_equal(result[cols], expected[cols])

result = df.groupby('id', as_index=False)['time'].first()
assert_frame_equal(result, expected[['id', 'time']])

result = df.groupby('id', as_index=False).last()
expected = DataFrame(expected_last)
cols = ['id', 'time', 'foo']
assert_frame_equal(result[cols], expected[cols])

result = df.groupby('id', as_index=False)['time'].last()
assert_frame_equal(result, expected[['id', 'time']])


def test_nth_multi_index_as_expected():
# PR 9090, related to issue 8979
# test nth on MultiIndex
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