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Feb 18th, 2019
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  1. df<- read.table(header=T, text='yyyymm amount
  2. 200809 261900
  3. 200810 149000
  4. 200908 120000
  5. 201104 81500
  6. 201107 30000
  7. 201112 75000
  8. 201306 56000
  9. 201310 98000
  10. 201311 40000
  11. 201402 95000
  12. 201408 28900
  13. 201505 33000
  14. 201511 65000
  15. 201601 78000
  16. 201610 50000
  17. 201701 50000
  18. 201711 81500')
  19.  
  20. yyyymm amount sum_amt
  21. 200809 261900 NA
  22. 200810 261900 261900
  23. 200908 120000 410900
  24. 201104 81500 NA
  25. 201107 30000 81500
  26. 201112 75000 111500
  27. 201306 56000 NA
  28. 201310 98000 56000
  29. 201311 40000 154000
  30. 201402 95000 194000
  31. 201408 28900 233000
  32. 201505 33000 28900
  33. 201511 65000 33000
  34. 201601 78000 98000
  35. 201610 50000 143000
  36. 201701 50000 128000
  37. 201711 81500 50000
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