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Jun 18th, 2019
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  1. s = data.groupby('key').agg({'low':'min','high':'max','close':'last'}).sum(axis=1) / 3
  2.  
  3. data['s'] = data['key'].map(s.shift())
  4. print(data)
  5. open high low close key s
  6. 0 110 115 105 111 1 NaN
  7. 1 11 16 6 12 1 NaN
  8. 2 12 17 7 13 1 NaN
  9. 3 12 16 6 11 2 44.666667
  10. 4 9 13 4 13 2 44.666667
  11. 5 13 18 9 12 3 11.000000
  12. 6 14 16 10 13 3 11.000000
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