BUG: Retain name in PeriodIndex resample

closes #12769 Author: Maximilian Roos <maximilian@sixtycapital.com> Closes #12771 from MaximilianR/retain-period-index-name-on-resample and squashes the following commits: 7b17a7e [Maximilian Roos] name retained in PeriodIndex resample

Author: max-sixty

doc/source/whatsnew/v0.18.1.txt

@@ -220,7 +220,7 @@ Bug Fixes
 
 
 - Bug in ``CategoricalIndex.get_loc`` returns different result from regular ``Index`` (:issue:`12531`)
-
+- Bug in ``PeriodIndex.resample`` where name not propagated (:issue:`12769`)
 
 
 

pandas/tseries/resample.py

@@ -672,16 +672,18 @@ def aggregate(self, arg, *args, **kwargs):
  def _get_new_index(self):
  """ return our new index """
  ax = self.ax
+ ax_attrs = ax._get_attributes_dict()
+ ax_attrs['freq'] = self.freq
  obj = self._selected_obj
 
  if len(ax) == 0:
- new_index = PeriodIndex(data=[], freq=self.freq)
+ new_index = PeriodIndex(data=[], **ax_attrs)
  return obj.reindex(new_index)
 
  start = ax[0].asfreq(self.freq, how=self.convention)
  end = ax[-1].asfreq(self.freq, how='end')
 
- return period_range(start, end, freq=self.freq)
+ return period_range(start, end, **ax_attrs)
 
  def _downsample(self, how, **kwargs):
  """

pandas/tseries/tests/test_resample.py

@@ -1891,6 +1891,85 @@ def test_monthly_upsample(self):
  expected = expected.asfreq(targ, 'ffill').to_period()
  assert_series_equal(result, expected)
 
+ def test_resample_basic(self):
+ # GH3609
+ s = Series(range(100), index=date_range(
+ '20130101', freq='s', periods=100, name='idx'), dtype='float')
+ s[10:30] = np.nan
+ index = PeriodIndex([
+ Period('2013-01-01 00:00', 'T'),
+ Period('2013-01-01 00:01', 'T')], name='idx')
+ expected = Series([34.5, 79.5], index=index)
+ result = s.to_period().resample('T', kind='period').mean()
+ assert_series_equal(result, expected)
+ result2 = s.resample('T', kind='period').mean()
+ assert_series_equal(result2, expected)
+
+ def test_resample_empty(self):
+
+ # GH12771
+ index = PeriodIndex(start='2000', periods=0, freq='D', name='idx')
+ s = Series(index=index)
+ result = s.resample('M').sum()
+
+ # after GH12774 is resolved, this should be a PeriodIndex
+ expected_index = DatetimeIndex([], name='idx')
+ expected = Series(index=expected_index)
+ assert_series_equal(result, expected)
+
+ def test_with_local_timezone_pytz(self):
+ # GH5430
+ tm._skip_if_no_pytz()
+ import pytz
+
+ local_timezone = pytz.timezone('America/Los_Angeles')
+
+ start = datetime(year=2013, month=11, day=1, hour=0, minute=0,
+ tzinfo=pytz.utc)
+ # 1 day later
+ end = datetime(year=2013, month=11, day=2, hour=0, minute=0,
+ tzinfo=pytz.utc)
+
+ index = pd.date_range(start, end, freq='H')
+
+ series = pd.Series(1, index=index)
+ series = series.tz_convert(local_timezone)
+ result = series.resample('D', kind='period').mean()
+
+ # Create the expected series
+ # Index is moved back a day with the timezone conversion from UTC to
+ # Pacific
+ expected_index = (pd.period_range(start=start, end=end, freq='D') - 1)
+ expected = pd.Series(1, index=expected_index)
+ assert_series_equal(result, expected)
+
+ def test_with_local_timezone_dateutil(self):
+ # GH5430
+ tm._skip_if_no_dateutil()
+ import dateutil
+
+ local_timezone = 'dateutil/America/Los_Angeles'
+
+ start = datetime(year=2013, month=11, day=1, hour=0, minute=0,
+ tzinfo=dateutil.tz.tzutc())
+ # 1 day later
+ end = datetime(year=2013, month=11, day=2, hour=0, minute=0,
+ tzinfo=dateutil.tz.tzutc())
+
+ index = pd.date_range(start, end, freq='H', name='idx')
+
+ series = pd.Series(1, index=index)
+ series = series.tz_convert(local_timezone)
+ result = series.resample('D', kind='period').mean()
+
+ # Create the expected series
+ # Index is moved back a day with the timezone conversion from UTC to
+ # Pacific
+ expected_index = (pd.period_range(start=start, end=end, freq='D',
+ name='idx') - 1)
+ expected = pd.Series(1, index=expected_index)
+ assert_series_equal(result, expected)
+
  def test_fill_method_and_how_upsample(self):
  # GH2073
  s = Series(np.arange(9, dtype='int64'),
@@ -1983,12 +2062,6 @@ def test_upsample_daily_business_daily(self):
  expected = ts.asfreq('H', how='s').reindex(exp_rng)
  assert_series_equal(result, expected)
 
- def test_resample_empty(self):
- ts = _simple_pts('1/1/2000', '2/1/2000')[:0]
-
- result = ts.resample('A').asfreq()
- self.assertEqual(len(result), 0)
-
  def test_resample_irregular_sparse(self):
  dr = date_range(start='1/1/2012', freq='5min', periods=1000)
  s = Series(np.array(100), index=dr)

pandas/tseries/tests/test_timeseries.py

@@ -1,42 +1,38 @@
 # pylint: disable-msg=E1101,W0612
 import calendar
-from datetime import datetime, time, timedelta
-import sys
 import operator
+import sys
 import warnings
+from datetime import datetime, time, timedelta
+from numpy.random import rand
+from numpy.testing.decorators import slow
+
 import nose
 import numpy as np
-import pandas.tseries.frequencies as frequencies
+import pandas.index as _index
 import pandas.lib as lib
 import pandas.tslib as tslib
-import pandas.index as _index
-import pandas as pd
-from pandas import (Index, Series, DataFrame, isnull, date_range, Timestamp,
- Period, DatetimeIndex, Int64Index, to_datetime,
- bdate_range, Float64Index, NaT, timedelta_range, Timedelta)
 
-from pandas.compat.numpy_compat import np_datetime64_compat
+import pandas as pd
+import pandas.compat as compat
+import pandas.core.common as com
 import pandas.core.datetools as datetools
+import pandas.tseries.frequencies as frequencies
 import pandas.tseries.offsets as offsets
 import pandas.tseries.tools as tools
-
-
-from pandas.util.testing import assert_series_equal, assert_almost_equal,\
- _skip_if_has_locale
 import pandas.util.testing as tm
-
-from pandas.tslib import iNaT
-
+from pandas import (
+ Index, Series, DataFrame, isnull, date_range, Timestamp, Period,
+ DatetimeIndex, Int64Index, to_datetime, bdate_range, Float64Index,
+ NaT, timedelta_range, Timedelta, _np_version_under1p8, concat,
+ PeriodIndex)
 from pandas.compat import range, long, StringIO, lrange, lmap, zip, product
-from numpy.random import rand
-from pandas.util.testing import assert_frame_equal
+from pandas.compat.numpy_compat import np_datetime64_compat
 from pandas.core.common import PerformanceWarning
-import pandas.compat as compat
-import pandas.core.common as com
-from pandas import concat
-from pandas import _np_version_under1p8
-
-from numpy.testing.decorators import slow
+from pandas.tslib import iNaT
+from pandas.util.testing import (
+ assert_frame_equal, assert_series_equal, assert_almost_equal,
+ _skip_if_has_locale)
 
 randn = np.random.randn
 
@@ -1247,23 +1243,6 @@ def test_asfreq_keep_index_name(self):
  tm.assert_equal(index_name, df.index.name)
  tm.assert_equal(index_name, df.asfreq('10D').index.name)
 
- def test_asfreq_resample_set_correct_freq(self):
- # GH5613
- # we test if .asfreq() and .resample() set the correct value for .freq
- df = pd.DataFrame({'date': ["2012-01-01", "2012-01-02", "2012-01-03"],
- 'col': [1, 2, 3]})
- df = df.set_index(pd.to_datetime(df.date))
-
- # testing the settings before calling .asfreq() and .resample()
- self.assertEqual(df.index.freq, None)
- self.assertEqual(df.index.inferred_freq, 'D')
-
- # does .asfreq() set .freq correctly?
- self.assertEqual(df.asfreq('D').index.freq, 'D')
-
- # does .resample() set .freq correctly?
- self.assertEqual(df.resample('D').asfreq().index.freq, 'D')
-
  def test_promote_datetime_date(self):
  rng = date_range('1/1/2000', periods=20)
  ts = Series(np.random.randn(20), index=rng)
@@ -2246,69 +2225,22 @@ def test_concat_datetime_datetime64_frame(self):
  # it works!
  pd.concat([df1, df2_obj])
 
- def test_period_resample(self):
- # GH3609
- s = Series(range(100), index=date_range(
- '20130101', freq='s', periods=100), dtype='float')
- s[10:30] = np.nan
- expected = Series([34.5, 79.5], index=[Period(
- '2013-01-01 00:00', 'T'), Period('2013-01-01 00:01', 'T')])
- result = s.to_period().resample('T', kind='period').mean()
- assert_series_equal(result, expected)
- result2 = s.resample('T', kind='period').mean()
- assert_series_equal(result2, expected)
-
- def test_period_resample_with_local_timezone_pytz(self):
- # GH5430
- tm._skip_if_no_pytz()
- import pytz
-
- local_timezone = pytz.timezone('America/Los_Angeles')
-
- start = datetime(year=2013, month=11, day=1, hour=0, minute=0,
- tzinfo=pytz.utc)
- # 1 day later
- end = datetime(year=2013, month=11, day=2, hour=0, minute=0,
- tzinfo=pytz.utc)
-
- index = pd.date_range(start, end, freq='H')
-
- series = pd.Series(1, index=index)
- series = series.tz_convert(local_timezone)
- result = series.resample('D', kind='period').mean()
-
- # Create the expected series
- # Index is moved back a day with the timezone conversion from UTC to
- # Pacific
- expected_index = (pd.period_range(start=start, end=end, freq='D') - 1)
- expected = pd.Series(1, index=expected_index)
- assert_series_equal(result, expected)
-
- def test_period_resample_with_local_timezone_dateutil(self):
- # GH5430
- tm._skip_if_no_dateutil()
- import dateutil
-
- local_timezone = 'dateutil/America/Los_Angeles'
-
- start = datetime(year=2013, month=11, day=1, hour=0, minute=0,
- tzinfo=dateutil.tz.tzutc())
- # 1 day later
- end = datetime(year=2013, month=11, day=2, hour=0, minute=0,
- tzinfo=dateutil.tz.tzutc())
+ def test_asfreq_resample_set_correct_freq(self):
+ # GH5613
+ # we test if .asfreq() and .resample() set the correct value for .freq
+ df = pd.DataFrame({'date': ["2012-01-01", "2012-01-02", "2012-01-03"],
+ 'col': [1, 2, 3]})
+ df = df.set_index(pd.to_datetime(df.date))
 
- index = pd.date_range(start, end, freq='H')
+ # testing the settings before calling .asfreq() and .resample()
+ self.assertEqual(df.index.freq, None)
+ self.assertEqual(df.index.inferred_freq, 'D')
 
- series = pd.Series(1, index=index)
- series = series.tz_convert(local_timezone)
- result = series.resample('D', kind='period').mean()
+ # does .asfreq() set .freq correctly?
+ self.assertEqual(df.asfreq('D').index.freq, 'D')
 
- # Create the expected series
- # Index is moved back a day with the timezone conversion from UTC to
- # Pacific
- expected_index = (pd.period_range(start=start, end=end, freq='D') - 1)
- expected = pd.Series(1, index=expected_index)
- assert_series_equal(result, expected)
+ # does .resample() set .freq correctly?
+ self.assertEqual(df.resample('D').asfreq().index.freq, 'D')
 
  def test_pickle(self):