title: using several independent variables in fbprophet model
body: <p>I tend to use fbprophet like so to predict time series uni variate-ly:</p>
  
  <pre><code>import pandas as pd
  from fbprophet import Prophet
  import matplotlib.pyplot as plt
  
  plt.style.use('fivethirtyeight')
  
  stock = 'FB'
  
  df = pd.read_csv('C:/Bla/' + stock + '.csv')
  df['Date'] = pd.DatetimeIndex(df['Date'])
  
  df = df.rename(columns={'Date': 'ds',
                          'Close': 'y'})
  
  my_model = Prophet(
      weekly_seasonality=True
      , interval_width=0.95
  )
  my_model.fit(df)
  
  future_dates = my_model.make_future_dataframe(periods=5, freq='B')
  future_dates.tail()
  
  forecast = my_model.predict(future_dates)
  forecast[['ds', 'yhat', 'yhat_lower', 'yhat_upper']].tail()
  
  my_model.plot(forecast, uncertainty=True)
  plt.show()
  </code></pre>
  
  <p>I think one can now also predict using multiple independent variables (using add_regressor?). Did someone do this? If so, could you please provide some code example? Let us assume the independent variable is called X1 in the above df. Thanks! </p>