title: Forecasting each time series from a group of time series
body: <p>I have a dataset that has multiple time series and I want my predictions on each of the time series in that group. Let me explain with an example</p>
  <pre><code>    Month StoreName Product Sales
      01/21     A      Pasta   100
      02/21     A      Pasta   70
      03/21     A      Pasta   140
      02/21     A      Rice    30
      03/21     A      Rice    10
      04/21     A      Rice    30
      03/21     B      pasta   200
      04/21     B      pasta   30
      01/21     B      Rice    120
      03/21     B      Rice    180
      04/21     B      Rice    100
  </code></pre>
  <p>Now, For a given StoreName and Product what will be the sales in the upcoming months. There are few things to be noted here.</p>
  <ol>
  <li>Intermittent demand (example: missing sales in February for store B)</li>
  <li>Encoding the categorical variables which have 200+ products, 200+ stores.</li>
  <li>Time series model for each set. ([A, Pasta], [A, Rice], [B, Pasta], [B, Rice])</li>
  </ol>
  <p>Is it possible to model multiple time series without looping because of high cardinality? Any sort of solution in python is much appreciated.</p>
  <p>Thanks in advance.</p>