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Fixturize tests/frame/test_arithmetic #22736

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merged 8 commits into from
Sep 26, 2018
Merged

Fixturize tests/frame/test_arithmetic #22736

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9ce1860
Fixturize tests/frame/test_arithmetic
h-vetinari Sep 17, 2018
0d8aa09
PEP8 fix
h-vetinari Sep 18, 2018
1f8a5d6
Review (jreback)
h-vetinari Sep 18, 2018
1acc6b1
PEP8
h-vetinari Sep 18, 2018
054f4e9
Merge remote-tracking branch 'upstream/master' into fixturize_frame_a…
h-vetinari Sep 19, 2018
3ee3b70
Split up test_arith_flex_frame (review jreback)
h-vetinari Sep 20, 2018
b6e14b0
Review (jreback)
h-vetinari Sep 23, 2018
b0b82a7
Review (jbrockmendel)
h-vetinari Sep 26, 2018
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18 changes: 10 additions & 8 deletions pandas/tests/frame/conftest.py
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Original file line number Diff line number Diff line change
Expand Up @@ -70,9 +70,10 @@ def mixed_float_frame():
Columns are ['A', 'B', 'C', 'D'].
"""
df = DataFrame(tm.getSeriesData())
df.A = df.A.astype('float16')
df.A = df.A.astype('float32')
df.B = df.B.astype('float32')
df.C = df.C.astype('float64')
df.C = df.C.astype('float16')
df.D = df.D.astype('float64')
return df


Expand All @@ -84,9 +85,10 @@ def mixed_float_frame2():
Columns are ['A', 'B', 'C', 'D'].
"""
df = DataFrame(tm.getSeriesData())
df.D = df.D.astype('float16')
df.D = df.D.astype('float32')
df.C = df.C.astype('float32')
df.B = df.B.astype('float64')
df.B = df.B.astype('float16')
df.D = df.D.astype('float64')
return df


Expand All @@ -99,10 +101,10 @@ def mixed_int_frame():
"""
df = DataFrame({k: v.astype(int)
for k, v in compat.iteritems(tm.getSeriesData())})
df.A = df.A.astype('uint8')
df.B = df.B.astype('int32')
df.C = df.C.astype('int64')
df.D = np.ones(len(df.D), dtype='uint64')
df.A = df.A.astype('int32')
df.B = np.ones(len(df.B), dtype='uint64')
df.C = df.C.astype('uint8')
df.D = df.C.astype('int64')
return df


Expand Down
193 changes: 74 additions & 119 deletions pandas/tests/frame/test_arithmetic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,8 +4,7 @@
import pytest
import numpy as np

from pandas.compat import range, PY3
import pandas.io.formats.printing as printing
from pandas.compat import range

import pandas as pd
import pandas.util.testing as tm
Expand Down Expand Up @@ -127,132 +126,88 @@ def test_df_add_flex_filled_mixed_dtypes(self):
'B': ser * 2})
tm.assert_frame_equal(result, expected)

def test_arith_flex_frame(self):
seriesd = tm.getSeriesData()
frame = pd.DataFrame(seriesd).copy()

mixed_float = pd.DataFrame({'A': frame['A'].copy().astype('float32'),
'B': frame['B'].copy().astype('float32'),
'C': frame['C'].copy().astype('float16'),
'D': frame['D'].copy().astype('float64')})

intframe = pd.DataFrame({k: v.astype(int)
for k, v in seriesd.items()})
mixed_int = pd.DataFrame({'A': intframe['A'].copy().astype('int32'),
'B': np.ones(len(intframe), dtype='uint64'),
'C': intframe['C'].copy().astype('uint8'),
'D': intframe['D'].copy().astype('int64')})

# force these all to int64 to avoid platform testing issues
intframe = pd.DataFrame({c: s for c, s in intframe.items()},
dtype=np.int64)

ops = ['add', 'sub', 'mul', 'div', 'truediv', 'pow', 'floordiv', 'mod']
if not PY3:
aliases = {}
else:
aliases = {'div': 'truediv'}

for op in ops:
try:
alias = aliases.get(op, op)
f = getattr(operator, alias)
result = getattr(frame, op)(2 * frame)
exp = f(frame, 2 * frame)
tm.assert_frame_equal(result, exp)

# vs mix float
result = getattr(mixed_float, op)(2 * mixed_float)
exp = f(mixed_float, 2 * mixed_float)
tm.assert_frame_equal(result, exp)
_check_mixed_float(result, dtype=dict(C=None))

# vs mix int
if op in ['add', 'sub', 'mul']:
result = getattr(mixed_int, op)(2 + mixed_int)
exp = f(mixed_int, 2 + mixed_int)

# no overflow in the uint
dtype = None
if op in ['sub']:
dtype = dict(B='uint64', C=None)
elif op in ['add', 'mul']:
dtype = dict(C=None)
tm.assert_frame_equal(result, exp)
_check_mixed_int(result, dtype=dtype)

# rops
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rops were only tested within that if-block. Now they're all tested

r_f = lambda x, y: f(y, x)
result = getattr(frame, 'r' + op)(2 * frame)
exp = r_f(frame, 2 * frame)
tm.assert_frame_equal(result, exp)

# vs mix float
result = getattr(mixed_float, op)(2 * mixed_float)
exp = f(mixed_float, 2 * mixed_float)
tm.assert_frame_equal(result, exp)
_check_mixed_float(result, dtype=dict(C=None))

result = getattr(intframe, op)(2 * intframe)
exp = f(intframe, 2 * intframe)
tm.assert_frame_equal(result, exp)

# vs mix int
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For some reason, this part was tested twice. only once in cleaned-up version

if op in ['add', 'sub', 'mul']:
result = getattr(mixed_int, op)(2 + mixed_int)
exp = f(mixed_int, 2 + mixed_int)

# no overflow in the uint
dtype = None
if op in ['sub']:
dtype = dict(B='uint64', C=None)
elif op in ['add', 'mul']:
dtype = dict(C=None)
tm.assert_frame_equal(result, exp)
_check_mixed_int(result, dtype=dtype)
except:
printing.pprint_thing("Failing operation %r" % op)
raise

# ndim >= 3
ndim_5 = np.ones(frame.shape + (3, 4, 5))
def test_arith_flex_frame(self, all_arithmetic_operators, float_frame,
mixed_float_frame):
# one instance of parametrized fixture
op = all_arithmetic_operators

def f(x, y):
# r-versions not in operator-stdlib; get op without "r" and invert
if op.startswith('__r'):
return getattr(operator, op.replace('__r', '__'))(y, x)
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@jbrockmendel pls have a look here

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This is fine. The alternative would be to do a lookup in core.ops, but I think for a reader who is unfamiliar with core.ops this is clearer.

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Modified comment slightly

return getattr(operator, op)(x, y)

result = getattr(float_frame, op)(2 * float_frame)
exp = f(float_frame, 2 * float_frame)
tm.assert_frame_equal(result, exp)

# vs mix float
result = getattr(mixed_float_frame, op)(2 * mixed_float_frame)
exp = f(mixed_float_frame, 2 * mixed_float_frame)
tm.assert_frame_equal(result, exp)
_check_mixed_float(result, dtype=dict(C=None))

@pytest.mark.parametrize('op', ['__add__', '__sub__', '__mul__'])
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Broke up the test like you wanted

def test_arith_flex_frame_mixed(self, op, int_frame, mixed_int_frame,
mixed_float_frame):
f = getattr(operator, op)

# vs mix int
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might be more clear to move these to a separate test (from here down)

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I don't want to get into orthogonal changes here. I haven't changed anything about this except removing the indentation. This goes for the test split requested below as well.

result = getattr(mixed_int_frame, op)(2 + mixed_int_frame)
exp = f(mixed_int_frame, 2 + mixed_int_frame)

# no overflow in the uint
dtype = None
if op in ['__sub__']:
dtype = dict(B='uint64', C=None)
elif op in ['__add__', '__mul__']:
dtype = dict(C=None)
tm.assert_frame_equal(result, exp)
_check_mixed_int(result, dtype=dtype)

# vs mix float
result = getattr(mixed_float_frame, op)(2 * mixed_float_frame)
exp = f(mixed_float_frame, 2 * mixed_float_frame)
tm.assert_frame_equal(result, exp)
_check_mixed_float(result, dtype=dict(C=None))

# vs plain int
result = getattr(int_frame, op)(2 * int_frame)
exp = f(int_frame, 2 * int_frame)
tm.assert_frame_equal(result, exp)

def test_arith_flex_frame_raise(self, all_arithmetic_operators,
float_frame):
# one instance of parametrized fixture
op = all_arithmetic_operators

# Check that arrays with dim >= 3 raise
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can you add a comment here on what this is testing

Added (and expanded)

for dim in range(3, 6):
arr = np.ones((1,) * dim)
msg = "Unable to coerce to Series/DataFrame"
with tm.assert_raises_regex(ValueError, msg):
f(frame, ndim_5)
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@h-vetinari h-vetinari Sep 20, 2018 •
edited
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This part (testing via the f of the op) is removed because it's testing the same thing as testing the op from the frame directly below

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Can you separate out these dimension-specific tests?

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Split them out in a separate test

getattr(float_frame, op)(arr)

with tm.assert_raises_regex(ValueError, msg):
getattr(frame, op)(ndim_5)

# res_add = frame.add(frame)
# res_sub = frame.sub(frame)
# res_mul = frame.mul(frame)
# res_div = frame.div(2 * frame)

# tm.assert_frame_equal(res_add, frame + frame)
# tm.assert_frame_equal(res_sub, frame - frame)
# tm.assert_frame_equal(res_mul, frame * frame)
# tm.assert_frame_equal(res_div, frame / (2 * frame))
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Did this commented-out stuff go somewhere else? Or just determined to be redundant?

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Determined to be redundant with test_arith_flex_frame, which checks all arith_ops, and much more thoroughly.

def test_arith_flex_frame_corner(self, float_frame):

const_add = frame.add(1)
tm.assert_frame_equal(const_add, frame + 1)
const_add = float_frame.add(1)
tm.assert_frame_equal(const_add, float_frame + 1)

# corner cases
result = frame.add(frame[:0])
tm.assert_frame_equal(result, frame * np.nan)
result = float_frame.add(float_frame[:0])
tm.assert_frame_equal(result, float_frame * np.nan)

result = float_frame[:0].add(float_frame)
tm.assert_frame_equal(result, float_frame * np.nan)

result = frame[:0].add(frame)
tm.assert_frame_equal(result, frame * np.nan)
with tm.assert_raises_regex(NotImplementedError, 'fill_value'):
frame.add(frame.iloc[0], fill_value=3)
float_frame.add(float_frame.iloc[0], fill_value=3)

with tm.assert_raises_regex(NotImplementedError, 'fill_value'):
frame.add(frame.iloc[0], axis='index', fill_value=3)

def test_arith_flex_series(self):
arr = np.array([[1., 2., 3.],
[4., 5., 6.],
[7., 8., 9.]])
df = pd.DataFrame(arr, columns=['one', 'two', 'three'],
index=['a', 'b', 'c'])
float_frame.add(float_frame.iloc[0], axis='index', fill_value=3)

def test_arith_flex_series(self, simple_frame):
df = simple_frame

row = df.xs('a')
col = df['two']
Expand Down