How to use the finta.utils.to_dataframe function in finta
To help you get started, we’ve selected a few finta examples, based on popular ways it is used in public projects.
Secure your code as it's written. Use Snyk Code to scan source code in minutes - no build needed - and fix issues immediately.
peerchemist / finta / tests / test_utils_unit.py View on Github 
def test_resample_calendar():
df = to_dataframe(data)
assert isinstance(resample(df, "W-Mon"), DataFrame)
assert list(resample(df, "W-Mon").index.values[-2:]) == [
numpy.datetime64("2019-05-06T00:00:00.000000000"),
numpy.datetime64("2019-05-13T00:00:00.000000000"),
]def test_trending_up():
df = to_dataframe(data)
ma = TA.HMA(df)
assert isinstance(trending_up(ma, 10), Series)
assert not trending_up(ma, 10).values[-1]def test_to_dataframe():
assert isinstance(to_dataframe(data), DataFrame)def test_trending_down():
df = to_dataframe(data)
ma = TA.HMA(df)
assert isinstance(trending_down(ma, 10), Series)
assert trending_down(ma, 10).values[-1]def test_resample():
df = to_dataframe(data)
assert isinstance(resample(df, "2d"), DataFrame)
assert list(resample(df, "2d").index.values[-2:]) == [
numpy.datetime64("2019-05-05T00:00:00.000000000"),
numpy.datetime64("2019-05-07T00:00:00.000000000"),
]finta
Common financial technical indicators implemented in Pandas.
