title: Plot the result of a groupby operation in pandas
body: <p>I have this sample table:</p>
  
  <pre><code>    ID   Date      Days Volume/Day
  0   111 2016-01-01  20  50
  1   111 2016-02-01  25  40
  2   111 2016-03-01  31  35
  3   111 2016-04-01  30  30
  4   111 2016-05-01  31  25
  5   111 2016-06-01  30  20
  6   111 2016-07-01  31  20
  7   111 2016-08-01  31  15
  8   111 2016-09-01  29  15
  9   111 2016-10-01  31  10
  10  111 2016-11-01  29  5
  11  111 2016-12-01  27  0
  0   112 2016-01-01  31  55
  1   112 2016-02-01  26  45
  2   112 2016-03-01  31  40
  3   112 2016-04-01  30  35
  4   112 2016-04-01  31  30
  5   112 2016-05-01  30  25
  6   112 2016-06-01  31  25
  7   112 2016-07-01  31  20
  8   112 2016-08-01  30  20
  9   112 2016-09-01  31  15
  10  112 2016-11-01  29  10
  11  112 2016-12-01  31  0
  </code></pre>
  
  <p>I'm trying to make my table final table look like this below after grouping by ID and Date.</p>
  
  <pre><code>    ID   Date      CumDays  Volume/Day
  0   111 2016-01-01  20       50
  1   111 2016-02-01  45       40
  2   111 2016-03-01  76       35
  3   111 2016-04-01  106      30
  4   111 2016-05-01  137      25
  5   111 2016-06-01  167      20
  6   111 2016-07-01  198      20
  7   111 2016-08-01  229      15
  8   111 2016-09-01  258      15
  9   111 2016-10-01  289      10
  10  111 2016-11-01  318      5
  11  111 2016-12-01  345      0
  0   112 2016-01-01  31       55
  1   112 2016-02-01  57       45
  2   112 2016-03-01  88       40
  3   112 2016-04-01  118      35
  4   112 2016-05-01  149      30
  5   112 2016-06-01  179      25
  6   112 2016-07-01  210      25
  7   112 2016-08-01  241      20
  8   112 2016-09-01  271      20
  9   112 2016-10-01  302      15
  10  112 2016-11-01  331      10
  11  112 2016-12-01  362       0
  </code></pre>
  
  <p>Next, I want to be able to extract the first value of Volume/Day per ID, all the CumDays values and all the Volume/Day values per ID and Date. So I can use them for further computation and plotting Volume/Day vs CumDays. Example for ID:111, the first value of Volume/Day will be only 50 and ID:112, it will be only 55. All CumDays values for ID:111 will be 20,45... and ID:112, it will be 31,57...For all Volume/Day --- ID:111, will be 50, 40... and ID:112 will be 55,45... </p>
  
  <p>My solution:</p>
  
  <pre><code>def get_time_rate(grp_df):
      t = grp_df['Days'].cumsum()
      r = grp_df['Volume/Day']
      return t,r
  
  vals = df.groupby(['ID','Date']).apply(get_time_rate)
  vals
  </code></pre>
  
  <p>Doing this, the cumulative calculation doesn't take effect at all. It returns the original Days value. This didn't allow me move further in  extracting the first value of Volume/Day, all the CumDays values and all the Volume/Day values I need. Any advice or help on how to go about it will be appreciated. Thanks</p>