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h-vetinarih-vetinari
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Make _check_stat_op and _check_bool_op run
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‎pandas/tests/frame/test_analytics.py

+53-53
Original file line numberDiff line numberDiff line change
@@ -25,7 +25,7 @@
2525
import pandas.util._test_decorators as td
2626

2727

28-
def _check_stat_op(self, name, alternative, main_frame, float_frame,
28+
def _check_stat_op(name, alternative, main_frame, float_frame,
2929
float_string_frame, has_skipna=True,
3030
has_numeric_only=False, check_dtype=True,
3131
check_dates=False, check_less_precise=False,
@@ -103,7 +103,7 @@ def wrapper(x):
103103
tm.assert_series_equal(r1, expected)
104104

105105

106-
def _check_bool_op(self, name, alternative, frame, float_string_frame,
106+
def _check_bool_op(name, alternative, frame, float_string_frame,
107107
has_skipna=True, has_bool_only=False):
108108

109109
f = getattr(frame, name)
@@ -596,10 +596,10 @@ def test_reduce_mixed_frame(self):
596596

597597
def test_count(self, float_frame_with_na, float_frame, float_string_frame):
598598
f = lambda s: notna(s).sum()
599-
self._check_stat_op('count', f, float_frame_with_na, float_frame,
600-
float_string_frame, has_skipna=False,
601-
has_numeric_only=True, check_dtype=False,
602-
check_dates=True)
599+
_check_stat_op('count', f, float_frame_with_na, float_frame,
600+
float_string_frame, has_skipna=False,
601+
has_numeric_only=True, check_dtype=False,
602+
check_dates=True)
603603

604604
# corner case
605605
frame = DataFrame()
@@ -628,9 +628,9 @@ def test_count(self, float_frame_with_na, float_frame, float_string_frame):
628628
def test_nunique(self, float_frame_with_na, float_frame,
629629
float_string_frame):
630630
f = lambda s: len(algorithms.unique1d(s.dropna()))
631-
self._check_stat_op('nunique', f, float_frame_with_na,
632-
float_frame, float_string_frame, has_skipna=False,
633-
check_dtype=False, check_dates=True)
631+
_check_stat_op('nunique', f, float_frame_with_na,
632+
float_frame, float_string_frame, has_skipna=False,
633+
check_dtype=False, check_dates=True)
634634

635635
df = DataFrame({'A': [1, 1, 1],
636636
'B': [1, 2, 3],
@@ -644,15 +644,15 @@ def test_nunique(self, float_frame_with_na, float_frame,
644644

645645
def test_sum(self, float_frame_with_na, mixed_float_frame,
646646
float_frame, float_string_frame):
647-
self._check_stat_op('sum', np.sum, float_frame_with_na, float_frame,
648-
float_string_frame, has_numeric_only=True,
649-
skipna_alternative=np.nansum)
647+
_check_stat_op('sum', np.sum, float_frame_with_na, float_frame,
648+
float_string_frame, has_numeric_only=True,
649+
skipna_alternative=np.nansum)
650650

651651
# mixed types (with upcasting happening)
652-
self._check_stat_op('sum', np.sum,
653-
mixed_float_frame.astype('float32'), float_frame,
654-
float_string_frame, has_numeric_only=True,
655-
check_dtype=False, check_less_precise=True)
652+
_check_stat_op('sum', np.sum,
653+
mixed_float_frame.astype('float32'), float_frame,
654+
float_string_frame, has_numeric_only=True,
655+
check_dtype=False, check_less_precise=True)
656656

657657
@pytest.mark.parametrize('method', ['sum', 'mean', 'prod', 'var',
658658
'std', 'skew', 'min', 'max'])
@@ -679,13 +679,13 @@ def test_stat_operators_attempt_obj_array(self, method):
679679
tm.assert_series_equal(result, expected)
680680

681681
def test_mean(self, float_frame_with_na, float_frame, float_string_frame):
682-
self._check_stat_op('mean', np.mean, float_frame_with_na,
683-
float_frame, float_string_frame, check_dates=True)
682+
_check_stat_op('mean', np.mean, float_frame_with_na,
683+
float_frame, float_string_frame, check_dates=True)
684684

685685
def test_product(self, float_frame_with_na, float_frame,
686686
float_string_frame):
687-
self._check_stat_op('product', np.prod, float_frame_with_na,
688-
float_frame, float_string_frame)
687+
_check_stat_op('product', np.prod, float_frame_with_na,
688+
float_frame, float_string_frame)
689689

690690
# TODO: Ensure warning isn't emitted in the first place
691691
@pytest.mark.filterwarnings("ignore:All-NaN:RuntimeWarning")
@@ -696,18 +696,18 @@ def wrapper(x):
696696
return np.nan
697697
return np.median(x)
698698

699-
self._check_stat_op('median', wrapper, float_frame_with_na,
700-
float_frame, float_string_frame, check_dates=True)
699+
_check_stat_op('median', wrapper, float_frame_with_na,
700+
float_frame, float_string_frame, check_dates=True)
701701

702702
def test_min(self, float_frame_with_na, int_frame,
703703
float_frame, float_string_frame):
704704
with warnings.catch_warnings(record=True):
705705
warnings.simplefilter("ignore", RuntimeWarning)
706-
self._check_stat_op('min', np.min, float_frame_with_na,
707-
float_frame, float_string_frame,
708-
check_dates=True)
709-
self._check_stat_op('min', np.min, int_frame, float_frame,
710-
float_string_frame)
706+
_check_stat_op('min', np.min, float_frame_with_na,
707+
float_frame, float_string_frame,
708+
check_dates=True)
709+
_check_stat_op('min', np.min, int_frame, float_frame,
710+
float_string_frame)
711711

712712
def test_cummin(self, datetime_frame):
713713
datetime_frame.loc[5:10, 0] = nan
@@ -759,26 +759,26 @@ def test_max(self, float_frame_with_na, int_frame,
759759
float_frame, float_string_frame):
760760
with warnings.catch_warnings(record=True):
761761
warnings.simplefilter("ignore", RuntimeWarning)
762-
self._check_stat_op('max', np.max, float_frame_with_na,
763-
float_frame, float_string_frame,
764-
check_dates=True)
765-
self._check_stat_op('max', np.max, int_frame, float_frame,
766-
float_string_frame)
762+
_check_stat_op('max', np.max, float_frame_with_na,
763+
float_frame, float_string_frame,
764+
check_dates=True)
765+
_check_stat_op('max', np.max, int_frame, float_frame,
766+
float_string_frame)
767767

768768
def test_mad(self, float_frame_with_na, float_frame, float_string_frame):
769769
f = lambda x: np.abs(x - x.mean()).mean()
770-
self._check_stat_op('mad', f, float_frame_with_na, float_frame,
771-
float_string_frame)
770+
_check_stat_op('mad', f, float_frame_with_na, float_frame,
771+
float_string_frame)
772772

773773
def test_var_std(self, float_frame_with_na, datetime_frame, float_frame,
774774
float_string_frame):
775775
alt = lambda x: np.var(x, ddof=1)
776-
self._check_stat_op('var', alt, float_frame_with_na, float_frame,
777-
float_string_frame)
776+
_check_stat_op('var', alt, float_frame_with_na, float_frame,
777+
float_string_frame)
778778

779779
alt = lambda x: np.std(x, ddof=1)
780-
self._check_stat_op('std', alt, float_frame_with_na, float_frame,
781-
float_string_frame)
780+
_check_stat_op('std', alt, float_frame_with_na, float_frame,
781+
float_string_frame)
782782

783783
result = datetime_frame.std(ddof=4)
784784
expected = datetime_frame.apply(lambda x: x.std(ddof=4))
@@ -892,8 +892,8 @@ def test_cumprod(self, datetime_frame):
892892
def test_sem(self, float_frame_with_na, datetime_frame,
893893
float_frame, float_string_frame):
894894
alt = lambda x: np.std(x, ddof=1) / np.sqrt(len(x))
895-
self._check_stat_op('sem', alt, float_frame_with_na,
896-
float_frame, float_string_frame)
895+
_check_stat_op('sem', alt, float_frame_with_na,
896+
float_frame, float_string_frame)
897897

898898
result = datetime_frame.sem(ddof=4)
899899
expected = datetime_frame.apply(
@@ -917,8 +917,8 @@ def alt(x):
917917
return np.nan
918918
return skew(x, bias=False)
919919

920-
self._check_stat_op('skew', alt, float_frame_with_na,
921-
float_frame, float_string_frame)
920+
_check_stat_op('skew', alt, float_frame_with_na,
921+
float_frame, float_string_frame)
922922

923923
@td.skip_if_no_scipy
924924
def test_kurt(self, float_frame_with_na, float_frame, float_string_frame):
@@ -929,8 +929,8 @@ def alt(x):
929929
return np.nan
930930
return kurtosis(x, bias=False)
931931

932-
self._check_stat_op('kurt', alt, float_frame_with_na,
933-
float_frame, float_string_frame)
932+
_check_stat_op('kurt', alt, float_frame_with_na,
933+
float_frame, float_string_frame)
934934

935935
index = MultiIndex(levels=[['bar'], ['one', 'two', 'three'], [0, 1]],
936936
labels=[[0, 0, 0, 0, 0, 0],
@@ -1205,9 +1205,9 @@ def wrapper(x):
12051205
return np.nan
12061206
return np.median(x)
12071207

1208-
self._check_stat_op('median', wrapper, int_frame, float_frame,
1209-
float_string_frame, check_dtype=False,
1210-
check_dates=True)
1208+
_check_stat_op('median', wrapper, int_frame, float_frame,
1209+
float_string_frame, check_dtype=False,
1210+
check_dates=True)
12111211

12121212
# Miscellanea
12131213

@@ -1263,12 +1263,12 @@ def test_idxmax(self, float_frame, int_frame):
12631263
# Logical reductions
12641264

12651265
def test_any_all(self, bool_frame_with_na, float_string_frame):
1266-
self._check_bool_op('any', np.any, bool_frame_with_na,
1267-
float_string_frame, has_skipna=True,
1268-
has_bool_only=True)
1269-
self._check_bool_op('all', np.all, bool_frame_with_na,
1270-
float_string_frame, has_skipna=True,
1271-
has_bool_only=True)
1266+
_check_bool_op('any', np.any, bool_frame_with_na,
1267+
float_string_frame, has_skipna=True,
1268+
has_bool_only=True)
1269+
_check_bool_op('all', np.all, bool_frame_with_na,
1270+
float_string_frame, has_skipna=True,
1271+
has_bool_only=True)
12721272

12731273
def test_any_all_extra(self):
12741274
df = DataFrame({

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