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PEP8 fixes
1 parent abd0dc9 commit 9525131

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3 files changed

+6
-5
lines changed

3 files changed

+6
-5
lines changed

pandas/core/series.py

Lines changed: 2 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -2306,7 +2306,8 @@ def combine_first(self, other):
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name = ops.get_op_result_name(self, other) # noqa
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rs_vals = com._where_compat(isna(this), other._values, this._values)
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result = self._constructor(rs_vals, index=new_index).__finalize__(self)
2309-
# TODO DK can we simplify this using internals rather than public astype
2309+
# TODO DK can we simplify this using internals rather than public
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# astype
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if is_datetime64tz_dtype(self.dtype):
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result = result.astype(self.dtype)
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return result

pandas/tests/series/indexing/test_boolean.py

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -553,9 +553,9 @@ def test_where_datetime_conversion():
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554554
def test_where_dt_tz_values(self):
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dts1 = pd.date_range('20150101', '20150105', tz='America/New_York')
556-
df1 = pd.DataFrame({'date':dts1})
556+
df1 = pd.DataFrame({'date': dts1})
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dts2 = pd.date_range('20150103', '20150107', tz='America/New_York')
558-
df2 = pd.DataFrame({'date':dts2})
558+
df2 = pd.DataFrame({'date': dts2})
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result = df1.date.where(df1.date < df1.date[3], df2.date)
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exp_vals = pd.DatetimeIndex(['20150101', '20150102', '20150103',
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'20150106', '20150107'],

pandas/tests/series/test_combine_concat.py

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -172,9 +172,9 @@ def get_result_type(dtype, dtype2):
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def test_combine_first_dt_tz_values(self):
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dts1 = pd.date_range('20150101', '20150105', tz='America/New_York')
175-
df1 = pd.DataFrame({'date':dts1})
175+
df1 = pd.DataFrame({'date': dts1})
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dts2 = pd.date_range('20160514', '20160518', tz='America/New_York')
177-
df2 = pd.DataFrame({'date':dts2}, index=range(3, 8))
177+
df2 = pd.DataFrame({'date': dts2}, index=range(3, 8))
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result = df1.date.combine_first(df2.date)
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exp_vals = pd.DatetimeIndex(['20150101', '20150102', '20150103',
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'20150104', '20150105', '20160516',

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