title: How can I add missing rows to a pandas DataFrame depending on a date and a combination of two columns?
body: <p>I have a scenario in which I have a dataframe which contains 4 columns:</p>
  
  <pre class="lang-none prettyprint-override"><code>date, product, store, sales_amt
  
  1/1/2019, A,A,200
  
  1/1/2019,A,B,120
  
  1/2/2019, A,A,75
  
  1/3/2019,A,A,69
  
  1/3/2019,A,B,23
  
  --
  --
  --
  
  1/31/2019,A,B,49
  </code></pre>
  
  <p>The dates are supposed to span a whole month (e.g. in this case, January 2019) but there are some missing days in the dataframe.</p>
  
  <p>Does anyone have any tips on Python code that can loop through the dates for a particular month and add a new row to the dataframe with the missing <code>date</code>, <code>product</code>/<code>store</code> combination and a <code>sales_amt</code> of zero?</p>
  
  <p>For example, there is no entry for the <code>product</code>/<code>store</code> combination of A/B on 1/2/2019.</p>
  
  <p>The goal at the end is to have an entry for every day of that month for every <code>product</code>/<code>store</code> combination.</p>
  
  <p>How can I do this?</p>