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I am referring to the documentation here, but it does not give many examples on how to actually perform the test. I have a pandas dataframe with two columns:

  • Column 1 is first day of every week,
  • Column 2 is demand, and this data goes back over 150 weeks.

How would I perform a CH test to see if there is any seasonality in my data?

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In general this could be achieved with the snippet below where you have to replace x with your observations.

However I'm not sure whether the Caonva-Hansen-Test is suitable for weekly observations (m=52) since these sort of tests are usually designed with monthly or quarterly time series in mind. Therefore it might be better to aggregate your observations to a monthly level (m=12).

from pmdarima.arima import CHTest
import numpy as np
 
x=np.random.normal(size=1000)
CHTest(m=52).estimate_seasonal_differencing_term(x)
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