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Jun 19th, 2019
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  1. # --------------------------------------
  2. # Construct xts data.
  3. # --------------------------------------
  4.  
  5. rows_to_build <- 6
  6.  
  7. dates <- seq(
  8. as.POSIXct("2019-01-01 09:01:00"),
  9. length.out = rows_to_build,
  10. by = "1 min",
  11. tz = "CEST"
  12. )
  13.  
  14. master_decision = c(
  15. 3, # Keep (there no [3] above)
  16. 2, # Keep (there no [2] above)
  17. 2, # Deleted due to no [2] on line above.
  18. 3, # Keep (there no [2] above)
  19. 3, # Deleted due to no [3] on line above.
  20. 2 # Keep (no [2] above)
  21. )
  22.  
  23. data <- data.frame(master_decision)
  24. xts1 <- xts(x = data, order.by = dates)
  25.  
  26.  
  27. rm(list = ls()[! ls() %in% c("xts1")]) # Only keep [xts1].
  28.  
  29.  
  30. # ------------------------------------------------------------
  31. # For loop with purpose to remove duplicates that are grouped.
  32. # ------------------------------------------------------------
  33.  
  34. for (i in 2:nrow(xts1)) {
  35. if(xts1[[i]] == xts1[[i-1]]) {
  36. xts1[-c(i)]
  37. }
  38. }
  39.  
  40. master_decision
  41. 2019-01-01 09:01:00 3
  42. 2019-01-01 09:02:00 2
  43. 2019-01-01 09:03:00 2
  44. 2019-01-01 09:04:00 3
  45. 2019-01-01 09:05:00 3
  46. 2019-01-01 09:06:00 2
  47.  
  48. master_decision
  49. 2019-01-01 09:01:00 3
  50. 2019-01-01 09:02:00 2
  51. 2019-01-01 09:03:00 2
  52. 2019-01-01 09:04:00 3
  53. 2019-01-01 09:06:00 2
  54.  
  55. 2019-01-01 09:01:00 3
  56. 2019-01-01 09:02:00 2
  57. 2019-01-01 09:04:00 3
  58. 2019-01-01 09:06:00 2
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