title: Joining Values with a common key in specific place
body: <p>i try to find a way to join values that share a common key (in the below example it would be the ID) into a specified place in a dataframe.</p>
  
  <p>Where i start:</p>
  
  <pre><code>df1 = pd.DataFrame({"ID" : ["x13", "x13", "", "x14", "" , "x13"], "Name":"Master1", "Slave1", "Master2", "Master3", "Master4" , "Slave2"],"value":["", "5", "7", "8", "", "1"]})
  </code></pre>
  
  <p>Output is as expected:</p>
  
  <pre><code>ID     Name      value
  0  x13  Master1
  1  x13   Slave1     5
  2       Master2     7
  3  x14  Master3     8
  4       Master4
  5  x13   Slave2     1
  </code></pre>
  
  <p>What i want to achieve is the following result:</p>
  
  <pre><code>ID     Name      value
  0  x13  Master1     5,1
  1  x13   Slave1     5
  2       Master2     7
  3  x14  Master3     8
  4       Master4
  5  x13   Slave2     1
  </code></pre>
  
  <p>In words: I want to loop through the datarame and find all not empty ID's. When found i want to join up all the values which have the common ID in a list, and store that back in the datframe on the Master of this specific ID. </p>
  
  <p>All my solution attemps ended up in loop in loop ...</p>
  
  <p>I am kind of sure that the solution would be related to the groupby functionality of pandas but I cannot get the desired output. </p>