title: Exponential smoothing function in python for different groups of time series data
body: <p>How to create exponential smoothening function(SES having different trends, fluctuations for each sector)  when no of sectors are more than 50 in python?</p>
  <div class="s-table-container">
  <table class="s-table">
  <thead>
  <tr>
  <th>Sector</th>
  <th>Time</th>
  <th>Demand</th>
  </tr>
  </thead>
  <tbody>
  <tr>
  <td>Sector 1</td>
  <td>23-07-2021</td>
  <td>100</td>
  </tr>
  <tr>
  <td>Sector 1</td>
  <td>24-07-2021</td>
  <td>105</td>
  </tr>
  <tr>
  <td>Sector 1</td>
  <td>25-07-2021</td>
  <td>200</td>
  </tr>
  <tr>
  <td>Sector 1</td>
  <td>26-07-2021</td>
  <td>206</td>
  </tr>
  <tr>
  <td>Sector 1</td>
  <td>23-07-2021</td>
  <td>310</td>
  </tr>
  <tr>
  <td>Sector 1</td>
  <td>25-07-2021</td>
  <td>360</td>
  </tr>
  <tr>
  <td>Sector 1</td>
  <td>26-07-2021</td>
  <td>390</td>
  </tr>
  <tr>
  <td>Sector 1</td>
  <td>27-07-2021</td>
  <td>460</td>
  </tr>
  <tr>
  <td>Sector 2</td>
  <td>19-07-2021</td>
  <td>1000</td>
  </tr>
  <tr>
  <td>Sector 2</td>
  <td>20-07-2021</td>
  <td>1050</td>
  </tr>
  <tr>
  <td>Sector 2</td>
  <td>26-07-2021</td>
  <td>2000</td>
  </tr>
  <tr>
  <td>Sector 2</td>
  <td>28-07-2021</td>
  <td>2060</td>
  </tr>
  <tr>
  <td>Sector 2</td>
  <td>29-07-2021</td>
  <td>3100</td>
  </tr>
  <tr>
  <td>Sector 2</td>
  <td>30-07-2021</td>
  <td>3605</td>
  </tr>
  <tr>
  <td>Sector 2</td>
  <td>31-07-2021</td>
  <td>3910</td>
  </tr>
  <tr>
  <td>Sector 2</td>
  <td>1-08-2021</td>
  <td>4600</td>
  </tr>
  </tbody>
  </table>
  </div>
  <p>The function should contain checking of trends and seasonality, estimate the trend and seasonality and then converting to stationary  series only for non stationary data.</p>