def test__last_within_datetime():
''' Last-observed variant of the above.
'''
df = get_datetime_index_test_data()
df = fancy_group_by(df, within=timedelta(hours=1), method='last')
assert all(df['OPEN'] == [20, 180])
assert all(df['CLOSE'] == [30, 190])
def test__last_within_datetime():
''' Last-observed variant of the above.
'''
df = get_datetime_index_test_data()
df = fancy_group_by(df, within=timedelta(hours=1), method='last')
assert all(df['OPEN'] == [20, 180])
assert all(df['CLOSE'] == [30, 190])
def test__first_within_datetime():
''' This shows the groupby function can give you a timeseries of points that were observed
within a rolling window of the sample time.
This is like saying 'give me the timeseries as it was on the day'.
It usually makes sense I think for the window to be the same as the sample period.
'''
df = get_datetime_index_test_data()
df = fancy_group_by(df, within=timedelta(hours=1), method='first')
assert all(df['OPEN'] == [0, 160])
assert all(df['CLOSE'] == [10, 170])
def test__first_within_datetime():
''' This shows the groupby function can give you a timeseries of points that were observed
within a rolling window of the sample time.
This is like saying 'give me the timeseries as it was on the day'.
It usually makes sense I think for the window to be the same as the sample period.
'''
df = get_datetime_index_test_data()
df = fancy_group_by(df, within=timedelta(hours=1), method='first')
assert all(df['OPEN'] == [0, 160])
assert all(df['CLOSE'] == [10, 170])
def test_fancy_group_by_raises():
with pytest.raises(ValueError):
assert(fancy_group_by(None, method=None))
def test__within_numeric_last():
df = get_numeric_index_test_data()
df = fancy_group_by(df, within=5, method='last')
assert all(df['OPEN'] == [60, 120])
assert all(df['CLOSE'] == [70, 130])
def test__within_numeric_first():
df = get_numeric_index_test_data()
df = fancy_group_by(df, within=5, method='first')
assert all(df['OPEN'] == [0, 80])
assert all(df['CLOSE'] == [10, 90])
def test__minmax_first():
df = get_numeric_index_test_data()
df = fancy_group_by(df, min_=3, max_=10, method='first')
assert all(df['OPEN'] == [60, 80, 160])
assert all(df['CLOSE'] == [70, 90, 170])
def test__minmax_last():
df = get_numeric_index_test_data()
df = fancy_group_by(df, min_=3, max_=10, method='last')
assert all(df['OPEN'] == [60, 140, 200])
assert all(df['CLOSE'] == [70, 150, 210])
def test__within_numeric_last():
df = get_numeric_index_test_data()
df = fancy_group_by(df, within=5, method='last')
assert all(df['OPEN'] == [60, 120])
assert all(df['CLOSE'] == [70, 130])
def test__within_numeric_first():
df = get_numeric_index_test_data()
df = fancy_group_by(df, within=5, method='first')
assert all(df['OPEN'] == [0, 80])
assert all(df['CLOSE'] == [10, 90])
def test__minmax_first():
df = get_numeric_index_test_data()
df = fancy_group_by(df, min_=3, max_=10, method='first')
assert all(df['OPEN'] == [60, 80, 160])
assert all(df['CLOSE'] == [70, 90, 170])
def test__minmax_last():
df = get_numeric_index_test_data()
df = fancy_group_by(df, min_=3, max_=10, method='last')
assert all(df['OPEN'] == [60, 140, 200])
assert all(df['CLOSE'] == [70, 150, 210])
def test_fancy_group_by_raises():
with pytest.raises(ValueError):
assert (fancy_group_by(None, method=None))
