Code for my Medium article demonstrating how to use NeuralProphet

plot_forecast.py

def plot_forecast(model, data, periods, historic_pred=True, highlight_steps_ahead=None):
  
    """ plot_forecast function - generates and plots the forecasts for a NeuralProphet model
    - model -> a trained NeuralProphet model
    - data -> the dataframe used for training
    - periods -> the number of periods to forecast
    - historic_pred -> a flag indicating whether or not to plot the model's predictions on historic data
    - highlight_steps_ahead -> the number of steps ahead of the forecast line to highlight, used for autoregressive models only"""
    
    future = model.make_future_dataframe(data, 
                                         periods=periods, 
                                         n_historic_predictions=historic_pred)
    forecast = model.predict(future)
    
    if highlight_steps_ahead is not None:
        model = model.highlight_nth_step_ahead_of_each_forecast(highlight_steps_ahead)
        model.plot_last_forecast(forecast)
    else:    
        model.plot(forecast)