autoarima.py

import pmdarima as pm

# Create auto_arima model
model1 = pm.auto_arima(df_store_2_item_28_time, #time series
                      seasonal=True, # is the time series seasonal
                      m=7, # the seasonal period - one week?
                      d=1, # non-seasonal difference order
                      D=1, # seasonal difference order
                 	  max_p=6, # max value of p to test 
                      max_q=6, # max value of p to test
                      max_P=6, # max value of P to test 
                      max_Q=6, # max value of Q to test 
                      information_criterion='aic', # used to select best mode
                      trace=True, # prints the information_criterion for each model it fits
                      error_action='ignore', # ignore orders that don't work
                      stepwise=True, # apply an intelligent order search
                      suppress_warnings=True) 

# Print model summary
print(model1.summary())