title: Summarize grouped data in Pandas while filtering after the group part
body: <p>I am stumbling over the exact (or at least most elegant) steps to group and aggregate some data in Pandas.  Let's say I have a DataFrame that looks something like this -</p>
  
  <pre><code>system    sub_system     datatype     datacount
  a         1              foo          111
  a         1              bar          222
  a         1              baz          333
  a         2              foo          444
  a         2              baz          555
  b         1              foo          667
  b         3              baz          777
  </code></pre>
  
  <p>I'd like to get the sum of datacount while grouping by system and sub_system, as long as the datatype does not equal bar, and then put those totals back into the original dataframe.</p>
  
  <p>If I try non_bar_totals = df[df.datatype != 'bar'].groupby(['system', 'sub_sytem']).agg(np.sum), it'll get me something like -</p>
  
  <pre><code>                        count
  system    sub_system
  a         1             444
  a         2             999
  b         1             667
  b         3             777
  </code></pre>
  
  <p>But now I'm not sure how to push that count value back into the original DataFrame.  What is the right syntax to get those counts to be pushed back into the original Dataframe?    The end product should look like - </p>
  
  <pre><code>system    sub_system     datatype     datacount    non_bar_total
  a         1              foo          111          444
  a         1              bar          222          444
  a         1              baz          333          444
  a         2              foo          444          999
  a         2              baz          555          999
  b         1              foo          667          667
  b         3              baz          777          777
  </code></pre>
  
  <p>Thanks, I know this is something simple, I'm just missing the right keyword to find an example of someone doing it. </p>