The verdict, per the ADF test, is that we should not difference. Pmdarima also provides a more handy interface for estimating your d parameter more directly: from pmdarima.arima.utils import ndiffs # Estimate the number of differences using an ADF test: n_adf = ndiffs (y, test = 'adf') # -> 0 # Or a KPSS test (auto_arima default): n_kpss Interpreting results of KPSS test in R. I've been trying to create an ARIMA model however, I'm not sure how to determine if the data is stationary or not. I preformed a KPSS test in R using kpss.test from package tseries and these are the results: KPSS Level = 1.966, Truncation lag parameter = 5, p-value = 0.01 Warning message: In kpss.test It is highly recommended that KPSS and ADF Test are used for testing stationarity in the data. Hence, the following aspects might arise if using both the tests :-1. ADF and KPSS Test conclude that CL604Eg.

kpss test vs adf test