Variables with Python Forecasting

samuel_robertson

Is there a way to use variables with a Python forecast model like ARIMA or Random Forest?

I have a linear regression working, and I'm able to extract the coefficients, create variables, and use a Beast Mode calculation to generate a forecast. However, I'm unsure if this can be done with models that aren’t linear.

Ideally, I'd like the user to input their exogenous/explanatory variables and see a forecast at the dashboard level. Has anyone done something similar?

ArborRose

You should be able to use the Python tile to use Domo inputs or filtering. Run something like

from statsmodels.tsa.arima.model import ARIMA



y = your_time_series

X = your_exogenous_variable



model = ARIMA(y, exog=X, order=(p, d, q))



model_fit = model.fit()



forecast = model_fit.forecast(steps=10, exog=user_input_exog)

ArborRose

Um…I did not put those numbers on that code. Hmm.

samuel_robertson

I have a dataset and the model working right now, but the problem is getting input on the dashboard side of things.

If I create a webform I can create my own forecasts, but I'd like to be able to visualize that and incorporate variables so the user can see impact in real-time