title: Using pandas' groupby and agg to merge column containing dicts
body: <p>python 3.6.5</p>
  <p>seasoned python veteran
  new to pandas and dataframes</p>
  <p>given</p>
  <pre><code>d = {'time':['2021-08-12 14:59:15.230','2021-08-12 14:59:15.230','2021-08-12 14:59:15.230']
     , 'dayy':['14:59:15.231818','14:59:15.231330','14:59:15.232206']
     , 'catg':['40B0','4035','40E8']
     , 'data':[{'OQWOWF': '0', 'OQD8S1F': '10010100'},{'OQTADT': 30.0, 'OQTAVL': '0', 'OQAOAD': 2},{'OQGS01': '0', 'OQGS02': '0', 'OQGS03': '0'}]
     }
  df = pd.DataFrame( data=d)
  print(df)
  </code></pre>
  <p>yields</p>
  <pre><code>                      time             dayy  catg                                           data
  0  2021-08-12 14:59:15.230  14:59:15.231818  40B0         {'OQWOWF': '0', 'OQD8S1F': '10010100'}
  1  2021-08-12 14:59:15.230  14:59:15.231330  4035   {'OQTADT': 30.0, 'OQTAVL': '0', 'OQAOAD': 2}
  2  2021-08-12 14:59:15.230  14:59:15.232206  40E8  {'OQGS01': '0', 'OQGS02': '0', 'OQGS03': '0'
  </code></pre>
  <p>how can I merge the dicts into one dict grouped by time?  ie</p>
  <pre><code>2021-08-12 14:59:15.230  {'OQWOWF': '0', 'OQD8S1F': '10010100', 'OQTADT': 30.0, 'OQTAVL': '0', 'OQAOAD': 2, 'OQGS01': '0', 'OQGS02': '0', 'OQGS03': '0'}
  </code></pre>
  <p>I've gotten the groupby and columns-listed parts down but sense I need either an .apply() or an .agg() function</p>
  <pre><code>df.groupby('time')['data'].???
  </code></pre>
  <p>Any ideas?</p>
  <p>TIA</p>
  <p>Still-learning Steve</p>