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Fixturize tests/frame/test_asof.py #25628

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Merged
merged 2 commits into from
Mar 10, 2019
Merged

Fixturize tests/frame/test_asof.py #25628

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b84dc2f
Fixturize tests/frame/test_asof.py
h-vetinari Mar 10, 2019
072a2f6
Review (jreback)
h-vetinari Mar 10, 2019
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12 changes: 12 additions & 0 deletions pandas/tests/frame/conftest.py
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Original file line number Diff line number Diff line change
Expand Up @@ -67,6 +67,18 @@ def datetime_frame():
return DataFrame(tm.getTimeSeriesData())


@pytest.fixture
def date_range_frame():
"""
Fixture for DataFrame of ints with date_range index
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not in love with this as a generalized fixture, if you put in test_asof would be ok

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So far, the requirement was always that this should be on tests/frame/conftest to be reusable for other test modules. But I don't care either way - can put it into test_asof.py as well.


Columns are ['A', 'B'].
"""
N = 50
rng = date_range('1/1/1990', periods=N, freq='53s')
return DataFrame({'A': np.arange(N), 'B': np.arange(N)}, index=rng)


@pytest.fixture
def float_string_frame():
"""
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43 changes: 17 additions & 26 deletions pandas/tests/frame/test_asof.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,21 +6,14 @@
from pandas import DataFrame, Series, Timestamp, date_range, to_datetime
import pandas.util.testing as tm

from .common import TestData

class TestFrameAsof():

class TestFrameAsof(TestData):
def setup_method(self, method):
self.N = N = 50
self.rng = date_range('1/1/1990', periods=N, freq='53s')
self.df = DataFrame({'A': np.arange(N), 'B': np.arange(N)},
index=self.rng)

def test_basic(self):
df = self.df.copy()
def test_basic(self, date_range_frame):
df = date_range_frame
N = 50
df.loc[15:30, 'A'] = np.nan
dates = date_range('1/1/1990', periods=self.N * 3,
freq='25s')
dates = date_range('1/1/1990', periods=N * 3, freq='25s')

result = df.asof(dates)
assert result.notna().all(1).all()
Expand All @@ -35,11 +28,9 @@ def test_basic(self):
rs = result[mask]
assert (rs == 14).all(1).all()

def test_subset(self):
def test_subset(self, date_range_frame):
N = 10
rng = date_range('1/1/1990', periods=N, freq='53s')
df = DataFrame({'A': np.arange(N), 'B': np.arange(N)},
index=rng)
df = date_range_frame.iloc[:N].copy()
df.loc[4:8, 'A'] = np.nan
dates = date_range('1/1/1990', periods=N * 3,
freq='25s')
Expand All @@ -54,20 +45,18 @@ def test_subset(self):
expected = df.asof(dates)
tm.assert_frame_equal(result, expected)

# B gives self.df.asof
# B gives df.asof
result = df.asof(dates, subset='B')
expected = df.resample('25s', closed='right').ffill().reindex(dates)
expected.iloc[20:] = 9

tm.assert_frame_equal(result, expected)

def test_missing(self):
def test_missing(self, date_range_frame):
# GH 15118
# no match found - `where` value before earliest date in index
N = 10
rng = date_range('1/1/1990', periods=N, freq='53s')
df = DataFrame({'A': np.arange(N), 'B': np.arange(N)},
index=rng)
df = date_range_frame.iloc[:N].copy()
result = df.asof('1989-12-31')

expected = Series(index=['A', 'B'], name=Timestamp('1989-12-31'))
Expand All @@ -78,22 +67,24 @@ def test_missing(self):
columns=['A', 'B'], dtype='float64')
tm.assert_frame_equal(result, expected)

def test_all_nans(self):
def test_all_nans(self, date_range_frame):
# GH 15713
# DataFrame is all nans
result = DataFrame([np.nan]).asof([0])
expected = DataFrame([np.nan])
tm.assert_frame_equal(result, expected)

# testing non-default indexes, multiple inputs
dates = date_range('1/1/1990', periods=self.N * 3, freq='25s')
result = DataFrame(np.nan, index=self.rng, columns=['A']).asof(dates)
N = 150
rng = date_range_frame.index
dates = date_range('1/1/1990', periods=N, freq='25s')
result = DataFrame(np.nan, index=rng, columns=['A']).asof(dates)
expected = DataFrame(np.nan, index=dates, columns=['A'])
tm.assert_frame_equal(result, expected)

# testing multiple columns
dates = date_range('1/1/1990', periods=self.N * 3, freq='25s')
result = DataFrame(np.nan, index=self.rng,
dates = date_range('1/1/1990', periods=N, freq='25s')
result = DataFrame(np.nan, index=rng,
columns=['A', 'B', 'C']).asof(dates)
expected = DataFrame(np.nan, index=dates, columns=['A', 'B', 'C'])
tm.assert_frame_equal(result, expected)
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