8000 TST/CLN: Fixturize frame/test_analytics by h-vetinari · Pull Request #22733 · pandas-dev/pandas · GitHub
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Merged
merged 15 commits into from
Oct 6, 2018
Merged

TST/CLN: Fixturize frame/test_analytics #22733

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d23ac16
Fixturize frame/test_analytics.py
h-vetinari Sep 17, 2018
485e0d8
Review (WillAyd)
h-vetinari Sep 18, 2018
f1a394a
Revert disambiguating underscores
h-vetinari Sep 25, 2018
7ac476e
Pure copy/paste of _check_stat_op and _check_bool_op
h-vetinari Sep 25, 2018
e1a8c5a
Pure unindent of _check_stat_op and _check_bool_op
h-vetinari Sep 25, 2018
6c4a702
Make _check_stat_op and _check_bool_op run
h-vetinari Sep 25, 2018
98f3243
Correctly group tests within _check_[stat/bool]_op
h-vetinari Sep 25, 2018
b043bb4
Consistent naming of parameters
h-vetinari Sep 25, 2018
4a2adeb
Break up _check_[stat/bool]_op
h-vetinari Sep 25, 2018
56020d7
Final touches
h-vetinari Sep 25, 2018
c07c5ed
Merge remote-tracking branch 'upstream/master' into fixturize_frame_a…
h-vetinari Oct 5, 2018
7a56cfb
Revert "Final touches"
h-vetinari Oct 5, 2018
e197fe7
Revert "Break up _check_[stat/bool]_op"
h-vetinari Oct 5, 2018
48272d9
Revert "Consistent naming of parameters"
h-vetinari Oct 5, 2018
c227fa2
Revert "Correctly group tests within _check_[stat/bool]_op"
h-vetinari Oct 5, 2018
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Pure unindent of _check_stat_op and _check_bool_op
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@h-vetinari
h-vetinari committed Sep 25, 2018
commit e1a8c5a47bdcdd0a414ba24ce0d8bae9ea92dc5b
268 changes: 134 additions & 134 deletions pandas/tests/frame/test_analytics.py
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Expand Up @@ -25,145 +25,145 @@
import pandas.util._test_decorators as td


def _check_stat_op(self, name, alternative, main_frame, float_frame,
float_string_frame, has_skipna=True,
has_numeric_only=False, check_dtype=True,
check_dates=False, check_less_precise=False,
skipna_alternative=None):

f = getattr(main_frame, name)

if check_dates:
df = DataFrame({'b': date_range('1/1/2001', periods=2)})
_f = getattr(df, name)
result = _f()
assert isinstance(result, Series)

df['a'] = lrange(len(df))
result = getattr(df, name)()
assert isinstance(result, Series)
assert len(result)

if has_skipna:
def wrapper(x):
return alternative(x.values)

skipna_wrapper = tm._make_skipna_wrapper(alternative,
skipna_alternative)
result0 = f(axis=0, skipna=False)
result1 = f(axis=1, skipna=False)
tm.assert_series_equal(result0, main_frame.apply(wrapper),
check_dtype=check_dtype,
check_less_precise=check_less_precise)
# HACK: win32
tm.assert_series_equal(result1, main_frame.apply(wrapper, axis=1),
10000 check_dtype=False,
check_less_precise=check_less_precise)
else:
skipna_wrapper = alternative
def _check_stat_op(self, name, alternative, main_frame, float_frame,
float_string_frame, has_skipna=True,
has_numeric_only=False, check_dtype=True,
check_dates=False, check_less_precise=False,
skipna_alternative=None):

f = getattr(main_frame, name)

if check_dates:
df = DataFrame({'b': date_range('1/1/2001', periods=2)})
_f = getattr(df, name)
result = _f()
assert isinstance(result, Series)

df['a'] = lrange(len(df))
result = getattr(df, name)()
assert isinstance(result, Series)
assert len(result)

if has_skipna:
def wrapper(x):
return alternative(x.values)

result0 = f(axis=0)
result1 = f(axis=1)
tm.assert_series_equal(result0, main_frame.apply(skipna_wrapper),
skipna_wrapper = tm._make_skipna_wrapper(alternative,
skipna_alternative)
result0 = f(axis=0, skipna=False)
result1 = f(axis=1, skipna=False)
tm.assert_series_equal(result0, main_frame.apply(wrapper),
check_dtype=check_dtype,
check_less_precise=check_less_precise)
# HACK: win32
tm.assert_series_equal(result1, main_frame.apply(wrapper, axis=1),
check_dtype=False,
check_less_precise=check_less_precise)
else:
skipna_wrapper = alternative

result0 = f(axis=0)
result1 = f(axis=1)
tm.assert_series_equal(result0, main_frame.apply(skipna_wrapper),
check_dtype=check_dtype,
check_less_precise=check_less_precise)
if name in ['sum', 'prod']:
expected = main_frame.apply(skipna_wrapper, axis=1)
tm.assert_series_equal(result1, expected, check_dtype=False,
check_less_precise=check_less_precise)

# check dtypes
if check_dtype:
lcd_dtype = main_frame.values.dtype
assert lcd_dtype == result0.dtype
assert lcd_dtype == result1.dtype

# bad axis
tm.assert_raises_regex(ValueError, 'No axis named 2', f, axis=2)
# make sure works on mixed-type frame
getattr(float_string_frame, name)(axis=0)
getattr(float_string_frame, name)(axis=1)

if has_numeric_only:
getattr(float_string_frame, name)(axis=0, numeric_only=True)
getattr(float_string_frame, name)(axis=1, numeric_only=True)
getattr(float_frame, name)(axis=0, numeric_only=False)
getattr(float_frame, name)(axis=1, numeric_only=False)

# all NA case
if has_skipna:
all_na = float_frame * np.NaN
r0 = getattr(all_na, name)(axis=0)
r1 = getattr(all_na, name)(axis=1)
if name in ['sum', 'prod']:
expected = main_frame.apply(skipna_wrapper, axis=1)
tm.assert_series_equal(result1, expected, check_dtype=False,
check_less_precise=check_less_precise)

# check dtypes
if check_dtype:
lcd_dtype = main_frame.values.dtype
assert lcd_dtype == result0.dtype
assert lcd_dtype == result1.dtype

# bad axis
tm.assert_raises_regex(ValueError, 'No axis named 2', f, axis=2)
# make sure works on mixed-type frame
getattr(float_string_frame, name)(axis=0)
getattr(float_string_frame, name)(axis=1)

if has_numeric_only:
getattr(float_string_frame, name)(axis=0, numeric_only=True)
getattr(float_string_frame, name)(axis=1, numeric_only=True)
getattr(float_frame, name)(axis=0, numeric_only=False)
getattr(float_frame, name)(axis=1, numeric_only=False)

# all NA case
if has_skipna:
all_na = float_frame * np.NaN
r0 = getattr(all_na, name)(axis=0)
r1 = getattr(all_na, name)(axis=1)
if name in ['sum', 'prod']:
unit = int(name == 'prod')
expected = pd.Series(unit, index=r0.index, dtype=r0.dtype)
tm.assert_series_equal(r0, expected)
expected = pd.Series(unit, index=r1.index, dtype=r1.dtype)
tm.assert_series_equal(r1, expected)


def _check_bool_op(self, name, alternative, frame, float_string_frame,
has_skipna=True, has_bool_only=False):

f = getattr(frame, name)

if has_skipna:
def skipna_wrapper(x):
nona = x.dropna().values
return alternative(nona)

def wrapper(x):
return alternative(x.values)

result0 = f(axis=0, skipna=False)
result1 = f(axis=1, skipna=False)
tm.assert_series_equal(result0, frame.apply(wrapper))
tm.assert_series_equal(result1, frame.apply(wrapper, axis=1),
check_dtype=False) # HACK: win32
unit = int(name == 'prod')
expected = pd.Series(unit, index=r0.index, dtype=r0.dtype)
tm.assert_series_equal(r0, expected)
expected = pd.Series(unit, index=r1.index, dtype=r1.dtype)
tm.assert_series_equal(r1, expected)


def _check_bool_op(self, name, alternative, frame, float_string_frame,
has_skipna=True, has_bool_only=False):

f = getattr(frame, name)

if has_skipna:
def skipna_wrapper(x):
nona = x.dropna().values
return alternative(nona)

def wrapper(x):
return alternative(x.values)

result0 = f(axis=0, skipna=False)
result1 = f(axis=1, skipna=False)
tm.assert_series_equal(result0, frame.apply(wrapper))
tm.assert_series_equal(result1, frame.apply(wrapper, axis=1),
check_dtype=False) # HACK: win32
else:
skipna_wrapper = alternative
wrapper = alternative

result0 = f(axis=0)
result1 = f(axis=1)
tm.assert_series_equal(result0, frame.apply(skipna_wrapper))
tm.assert_series_equal(result1, frame.apply(skipna_wrapper, axis=1),
check_dtype=False)

# bad axis
pytest.raises(ValueError, f, axis=2)

# make sure works on mixed-type frame
mixed = float_string_frame
mixed['_bool_'] = np.random.randn(len(mixed)) > 0
getattr(mixed, name)(axis=0)
getattr(mixed, name)(axis=1)

class NonzeroFail(object):

def __nonzero__(self):
raise ValueError

mixed['_nonzero_fail_'] = NonzeroFail()

if has_bool_only:
getattr(mixed, name)(axis=0, bool_only=True)
getattr(mixed, name)(axis=1, bool_only=True)
getattr(frame, name)(axis=0, bool_only=False)
getattr(frame, name)(axis=1, bool_only=False)

# all NA case
if has_skipna:
all_na = frame * np.NaN
r0 = getattr(all_na, name)(axis=0)
r1 = getattr(all_na, name)(axis=1)
if name == 'any':
assert not r0.any()
assert not r1.any()
else:
skipna_wrapper = alternative
wrapper = alternative

result0 = f(axis=0)
result1 = f(axis=1)
tm.assert_series_equal(result0, frame.apply(skipna_wrapper))
tm.assert_series_equal(result1, frame.apply(skipna_wrapper, axis=1),
check_dtype=False)

# bad axis
pytest.raises(ValueError, f, axis=2)

# make sure works on mixed-type frame
mixed = float_string_frame
mixed['_bool_'] = np.random.randn(len(mixed)) > 0
getattr(mixed, name)(axis=0)
getattr(mixed, name)(axis=1)

class NonzeroFail(object):

def __nonzero__(self):
raise ValueError

mixed['_nonzero_fail_'] = NonzeroFail()

if has_bool_only:
getattr(mixed, name)(axis=0, bool_only=True)
getattr(mixed, name)(axis=1, bool_only=True)
getattr(frame, name)(axis=0, bool_only=False)
getattr(frame, name)(axis=1, bool_only=False)

# all NA case
if has_skipna:
all_na = frame * np.NaN
r0 = getattr(all_na, name)(axis=0)
r1 = getattr(all_na, name)(axis=1)
if name == 'any':
assert not r0.any()
assert not r1.any()
else:
assert r0.all()
assert r1.all()
assert r0.all()
assert r1.all()


class TestDataFrameAnalytics():
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