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BUG:Clip with a list-like threshold with a nan is broken (GH19992) #21921

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Merged
merged 7 commits into from
Jul 18, 2018
Merged

BUG:Clip with a list-like threshold with a nan is broken (GH19992) #21921

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287a400
BUG:(GH19992)
makbigc Jul 15, 2018
c5dfbfc
Update v0.24.0.txt
makbigc Jul 16, 2018
5c9f634
Update test_analytics.py
makbigc Jul 16, 2018
4eea624
Update v0.24.0.txt
makbigc Jul 17, 2018
2f50555
Update v0.23.4.txt
makbigc Jul 17, 2018
ff434ac
Merge branch 'master' into PR_TOOL_MERGE_PR_21921
jreback Jul 18, 2018
0ef2e4d
remove 0.24.0 ref
jreback Jul 18, 2018
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v0.24.0.txt
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Expand Up @@ -440,6 +440,7 @@ Missing

- Bug in :func:`DataFrame.fillna` where a ``ValueError`` would raise when one column contained a ``datetime64[ns, tz]`` dtype (:issue:`15522`)
- Bug in :func:`Series.hasnans` that could be incorrectly cached and return incorrect answers if null elements are introduced after an initial call (:issue:`19700`)
- Bug in :func:`Series.clip` and `DataFrame.clip` cannot accept list-like threshold containing nan (:issue:`19992`)
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can you add the ref for DataFrame, use double back-ticks on NaN (and sp)


MultiIndex
^^^^^^^^^^
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6 changes: 4 additions & 2 deletions pandas/core/generic.py
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Expand Up @@ -6520,9 +6520,11 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
# GH 17276
# numpy doesn't like NaN as a clip value
# so ignore
if np.any(pd.isnull(lower)):
# GH 19992
# numpy doesn't drop a list-like bound containing NaN
if not is_list_like(lower) and np.any(pd.isnull(lower)):
lower = None
if np.any(pd.isnull(upper)):
if not is_list_like(upper) and np.any(pd.isnull(upper)):
upper = None

# GH 2747 (arguments were reversed)
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15 changes: 11 additions & 4 deletions pandas/tests/frame/test_analytics.py
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Expand Up @@ -2237,13 +2237,20 @@ def test_clip_with_na_args(self):
"""Should process np.nan argument as None """
# GH # 17276
tm.assert_frame_equal(self.frame.clip(np.nan), self.frame)
tm.assert_frame_equal(self.frame.clip(upper=[1, 2, np.nan]),
self.frame)
tm.assert_frame_equal(self.frame.clip(lower=[1, np.nan, 3]),
self.frame)
tm.assert_frame_equal(self.frame.clip(upper=np.nan, lower=np.nan),
self.frame)

# GH #19992
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can you comment under the commit number what this is testing

use

result = 
expected = 
tm.assert_frame_equal(....)

do the tests in order for axis=0, axis=0, IOW so you don't have the df1, df2 variables

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Amended. Your format is better. Thanks.

df = DataFrame({'col_0': [1, 2, 3], 'col_1': [4, 5, 6],
'col_2': [7, 8, 9]})
df1 = DataFrame({'col_0': [4, 5, np.nan], 'col_1': [4, 5, np.nan],
'col_2': [7, 8, np.nan]})
df2 = DataFrame({'col_0': [4, 4, 4], 'col_1': [5, 5, 6],
'col_2': [np.nan, np.nan, np.nan]})

tm.assert_frame_equal(df.clip(lower=[4, 5, np.nan], axis=0), df1)
tm.assert_frame_equal(df.clip(lower=[4, 5, np.nan], axis=1), df2)

# Matrix-like
def test_dot(self):
a = DataFrame(np.random.randn(3, 4), index=['a', 'b', 'c'],
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8 changes: 6 additions & 2 deletions pandas/tests/series/test_analytics.py
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Expand Up @@ -1080,11 +1080,15 @@ def test_clip_with_na_args(self):
s = Series([1, 2, 3])

assert_series_equal(s.clip(np.nan), Series([1, 2, 3]))
assert_series_equal(s.clip(upper=[1, 1, np.nan]), Series([1, 2, 3]))
assert_series_equal(s.clip(lower=[1, np.nan, 1]), Series([1, 2, 3]))
assert_series_equal(s.clip(upper=np.nan, lower=np.nan),
Series([1, 2, 3]))

# GH #19992
assert_series_equal(s.clip(lower=[0, 4, np.nan]),
Series([1, 4, np.nan]))
assert_series_equal(s.clip(upper=[1, np.nan, 1]),
Series([1, np.nan, 1]))

def test_clip_against_series(self):
# GH #6966

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