title: Creating bar chart with CSV data python
body: <p>I have a CSV with data like</p>
  
  <pre><code>4be390eefaf9a64e7cb52937c4a5c77a,"e1.ru",2014-09-30 18:14:58,57,4
  4be390eefaf9a64e7cb52937c4a5c77a,"e1.ru",2014-09-30 20:11:15,1884,90
  4be390eefaf9a64e7cb52937c4a5c77a,"e1.ru",2014-10-04 09:44:21,1146,6
  4be390eefaf9a64e7cb52937c4a5c77a,"avito.ru",2014-09-29 21:01:29,48,3
  </code></pre>
  
  <p>I sort this like </p>
  
  <pre><code>print(infile.groupby(['address', infile['used_at'].dt.year]).active_seconds.sum())
  </code></pre>
  
  <p>And I got data:</p>
  
  <pre><code>address            used_at
  am.ru              2014         413071
                     2015         183402
  auto.ru            2014        9122342
                     2015        6923367
  avito.ru           2014       84503151
                     2015       87688571
  avtomarket.ru      2014         106849
                     2015          95927
  cars.mail.ru/sale  2014         211456
                     2015         167278
  drom.ru            2014       11014955
                     2015        9704124
  e1.ru              2014       28678357
                     2015       27961857
  irr.ru/cars        2014         222193
                     2015         133678
  </code></pre>
  
  <p>I need to create bar chart like this <a href="http://matplotlib.org/examples/api/barchart_demo.html" rel="nofollow">example</a></p>
  
  <p>But insted men and women I need to 2014 and 2015 year to every web-site(at axis x) and sum of <code>active_seconds</code>(at axis y). 
  In example they use np.array, but I have object type series.</p>
  
  <p>I try do this with:</p>
  
  <pre><code>width = 0.35
  plt.figure()
  ax = graph_by_duration['address'].plot(kind='bar', secondary_y=['active_seconds'])
  ax.set_ylabel('Time online')
  ax.set_title('Time spent online per web site, per year')
  plt.show()
  </code></pre>
  
  <p>Should I convert it to np.array or process to do this?</p>