def test_build_profile_nonstationary_reproduce_issue():
# This dataset is non-stationary but profiler reports
df = read_timeseries_csv("tests/data/complex_nonstationary.csv")
df.fillna(0, inplace=True)
profile = old_build_profile(df)
# This assertion should pass:
assert not profile["stationary"]
def test_build_profile_stationary():
df = read_timeseries_csv("tests/data/daily-total-female-births.csv")
profile = build_profile(df)
assert profile["stationary"]
def test_build_profile_nonstationary_goog200():
df = read_timeseries_csv("tests/data/goog200.csv")
profile = build_profile(df, freq="1d")
assert not profile["stationary"]
def test_build_profile_nonstationary():
df = read_timeseries_csv("tests/data/international-airline-passengers.csv")
profile = build_profile(df)
assert not profile["stationary"]
def test_build_profile_seasonal_loaded_dataset():
# dataset from https://www.kaggle.com/rtatman/us-candy-production-by-month?select=candy_production.csv
series = read_timeseries_csv("tests/data/candy_production.csv")
profile = build_seasonal_profile(series)
assert profile["seasonal"]
def test_build_profile_stationary_diff_goog200():
df = read_timeseries_csv("tests/data/diff_goog200.csv")
profile = old_build_profile(df)
assert profile["stationary"]