run_arima.py

def run_arima(chunked_data, price_col='y', n_prediction_units=1):
  # consume chunked data from https://gist.github.com/justinhchae/13d246e8e2e2d521a8d2cce20eb09a09
    # supress trivial warnings from ARIMA
    warnings.simplefilter('ignore', ConvergenceWarning)

    # initialize a list to hold results (a list of dataframes)
    results = []

    # numerate through a list of chunked tuples, each having a pair of dataframes
    for idx, (x_i, y_i) in enumerate(chunked_data):
        # create ARIMA model based on x_i values
        m = ARIMA(x_i[price_col].values, order=(0, 1, 0))
        # fit the model
        m_fit = m.fit()
        # forecast for n_prediction_units
        yhat = m_fit.forecast(steps=n_prediction_units)

        # return a dataframe of targets and predictions of len targets
        y_i['yhat'] = yhat[:len(y_i)]

        # save results to a list and then return the list
        results.append(y_i)

    return results