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[#7292] BUG: asfreq / pct_change strange behavior #19410

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merged 13 commits into from
Jan 31, 2018
Merged

[#7292] BUG: asfreq / pct_change strange behavior #19410

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e7f4f4e
reindex resulting NDFrame after percentage calculation
minggli Jan 26, 2018
d0baf8f
update pct_change test case with freq shift
minggli Jan 26, 2018
63701a3
update pct_change test case with freq shift
minggli Jan 26, 2018
8cfb77a
whatsnew entry for issue:7292
minggli Jan 26, 2018
e594e04
add new test case for consistent pct_change output
minggli Jan 26, 2018
dc9d64e
add new test case for consistent pct_change output
minggli Jan 26, 2018
22e0c34
rephase bugfix documentation
minggli Jan 26, 2018
a1d804f
additional test cases test_pct_change_periods_freq
minggli Jan 27, 2018
106bdf4
additional test cases test_pct_change_periods_freq
minggli Jan 27, 2018
b6377df
empty containre without numpy
minggli Jan 28, 2018
b08d4c8
rephase documentation whatsnew
minggli Jan 30, 2018
27aee76
remove slash for line continuation
minggli Jan 30, 2018
75b8942
change comment to GH 7292
minggli Jan 30, 2018
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v0.23.0.txt
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Expand Up @@ -419,6 +419,7 @@ Datetimelike
- Bug in ``.astype()`` to non-ns timedelta units would hold the incorrect dtype (:issue:`19176`, :issue:`19223`, :issue:`12425`)
- Bug in subtracting :class:`Series` from ``NaT`` incorrectly returning ``NaT`` (:issue:`19158`)
- Bug in :func:`Series.truncate` which raises ``TypeError`` with a monotonic ``PeriodIndex`` (:issue:`17717`)
- Bug in :func:`~DataFrame.pct_change` using ``periods`` and ``freq`` produces different sizes frames/series (:issue:`7292`)
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Change "produces different sizes frames/series" to "returned different length outputs"

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corrected.


Timezones
^^^^^^^^^
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1 change: 1 addition & 0 deletions pandas/core/generic.py
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Expand Up @@ -7315,6 +7315,7 @@ def pct_change(self, periods=1, fill_method='pad', limit=None, freq=None,

rs = (data.div(data.shift(periods=periods, freq=freq, axis=axis,
**kwargs)) - 1)
rs = rs.reindex_like(data)
if freq is None:
mask = isna(com._values_from_object(self))
np.putmask(rs.values, mask, np.nan)
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9 changes: 8 additions & 1 deletion pandas/tests/frame/test_timeseries.py
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Expand Up @@ -108,7 +108,9 @@ def test_pct_change(self):

rs = self.tsframe.pct_change(freq='5D')
filled = self.tsframe.fillna(method='pad')
assert_frame_equal(rs, filled / filled.shift(freq='5D') - 1)
assert_frame_equal(rs,
(filled / filled.shift(freq='5D') - 1)
.reindex_like(filled))

def test_pct_change_shift_over_nas(self):
s = Series([1., 1.5, np.nan, 2.5, 3.])
Expand All @@ -120,6 +122,11 @@ def test_pct_change_shift_over_nas(self):
edf = DataFrame({'a': expected, 'b': expected})
assert_frame_equal(chg, edf)

def test_pct_change_periods_freq(self):
rs_periods = self.tsframe.pct_change(5)
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add the issue number as a comment. Can you add a few more test cases here (via parametrization if possible). include an empty frame

rs_freq = self.tsframe.pct_change(periods=1, freq='5B')
assert_frame_equal(rs_freq, rs_periods)

def test_frame_ctor_datetime64_column(self):
rng = date_range('1/1/2000 00:00:00', '1/1/2000 1:59:50', freq='10s')
dates = np.asarray(rng)
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9 changes: 8 additions & 1 deletion pandas/tests/series/test_timeseries.py
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Expand Up @@ -344,7 +344,9 @@ def test_pct_change(self):

rs = self.ts.pct_change(freq='5D')
filled = self.ts.fillna(method='pad')
assert_series_equal(rs, filled / filled.shift(freq='5D') - 1)
assert_series_equal(rs,
(filled / filled.shift(freq='5D') - 1)
.reindex_like(filled))

def test_pct_change_shift_over_nas(self):
s = Series([1., 1.5, np.nan, 2.5, 3.])
Expand All @@ -353,6 +355,11 @@ def test_pct_change_shift_over_nas(self):
expected = Series([np.nan, 0.5, np.nan, 2.5 / 1.5 - 1, .2])
assert_series_equal(chg, expected)

def test_pct_change_periods_freq(self):
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same comments as above

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added additional test cases and test when frame is empty.

rs_periods = self.ts.pct_change(5)
rs_freq = self.ts.pct_change(periods=1, freq='5B')
assert_series_equal(rs_freq, rs_periods)

def test_autocorr(self):
# Just run the function
corr1 = self.ts.autocorr()
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