title: How to reverse a seasonal log difference of timeseries in python
body: <p>Could you please help me with this issue as I made many searches but cannot solve it. I have a multivariate dataframe for electricity consumption and I am doing a forecasting using VAR (Vector Auto-regression) model for time series.
  I made the predictions but I need to reverse the time series (energy_log_diff) as I applied a seasonal log difference to make the serie stationary, in order to get the real energy value:</p>
  
  <pre><code>df['energy_log'] = np.log(df['energy'])
  df['energy_log_diff'] = df['energy_log'] - df['energy_log'].shift(1)
  </code></pre>
  
  <p>For that, I did first: </p>
  
  <pre><code>df['energy'] = np.exp(df['energy_log_diff']) 
  </code></pre>
  
  <p>This is supposed to give the energy difference between 2 values lagged by 365 days but I am not sure for this neither.</p>
  
  <p>How can I do this?</p>