title: Pandas group by : Include all rows even the ones with empty column values
body: <p>I am using Pandas and trying to test something to fully understand some functionalities. </p>
  
  <p>I am grouping and aggregating my data after I load everything from a csv using the following code:</p>
  
  <pre><code>s = df.groupby(['ID','Site']).agg({'Start Date': 'min', 'End Date': 'max', 'Value': 'sum'})
  print(s)
  </code></pre>
  
  <p>and it works with the following file:</p>
  
  <p><a href="https://i.stack.imgur.com/wsK6r.png" rel="noreferrer"><img src="https://i.stack.imgur.com/wsK6r.png" alt="enter image description here"></a></p>
  
  <p>but it does not work with this file:</p>
  
  <p><a href="https://i.stack.imgur.com/MkLAt.png" rel="noreferrer"><img src="https://i.stack.imgur.com/MkLAt.png" alt="enter image description here"></a></p>
  
  <p>For the second file, I am getting the data only for the 56311 ID. The reason is that some columns have empty values. But that should not matter. I have not found anything relevant about that. I have only found how to exclude the null columns. </p>
  
  <p>Except for this issue, what are the main things that I should take into account before grouping? Is there any chance that rows will be excluded because for example of a format (date or number)?</p>