Winsorize outliers by capping extreme values
winsorize.RdReplaces extreme values in selected columns with the specified top and bottom quantile thresholds, rather than deleting them. This is useful for reducing the influence of outliers while preserving sample size.
Arguments
- data
A data frame, matrix, or numeric vector.
- cols
The column indices or names of selected variables. If NULL, all columns are used.
- top
The top quantile threshold. Values above this are capped at the threshold.
- bottom
The bottom quantile threshold. Values below this are capped at the threshold.
- group
Optional grouping column for group-wise winsorization.
- verbose
Logical; if
TRUE, prints progress message.
Examples
winsorize(data[1:100, c(1, 4, 17:19)], cols = 3:5)
#> date monthyear 3.98 4.47 5.01
#> 1 2019-12-31 16:00:00 January 2020 NA NA NA
#> 2 2019-12-31 16:10:00 January 2020 NA NA NA
#> 3 2019-12-31 16:20:00 January 2020 NA NA NA
#> 4 2019-12-31 16:30:00 January 2020 42.9722 74.778500 24.83750
#> 5 2019-12-31 16:40:00 January 2020 NA 6.865100 44.71760
#> 6 2019-12-31 16:50:00 January 2020 61.2601 NA NA
#> 7 2019-12-31 17:00:00 January 2020 115.8960 NA NA
#> 8 2019-12-31 17:10:00 January 2020 NA NA NA
#> 9 2019-12-31 17:20:00 January 2020 61.2601 NA NA
#> 10 2019-12-31 17:30:00 January 2020 60.9405 6.592109 42.93320
#> 11 2019-12-31 17:40:00 January 2020 NA NA NA
#> 12 2019-12-31 17:50:00 January 2020 NA NA NA
#> 13 2019-12-31 18:00:00 January 2020 NA 13.949800 90.86510
#> 14 2019-12-31 18:10:00 January 2020 NA NA NA
#> 15 2019-12-31 18:20:00 January 2020 61.2601 NA NA
#> 16 2019-12-31 18:30:00 January 2020 130.9630 218.996150 75.69510
#> 17 2019-12-31 18:40:00 January 2020 NA NA NA
#> 18 2019-12-31 18:50:00 January 2020 NA NA NA
#> 19 2019-12-31 19:00:00 January 2020 NA NA NA
#> 20 2019-12-31 19:10:00 January 2020 133.1902 148.200000 49.22410
#> 21 2019-12-31 19:20:00 January 2020 61.2601 NA NA
#> 22 2019-12-31 19:40:00 January 2020 NA NA NA
#> 23 2019-12-31 19:50:00 January 2020 NA NA NA
#> 24 2019-12-31 20:00:00 January 2020 NA NA NA
#> 25 2019-12-31 20:10:00 January 2020 NA NA NA
#> 26 2019-12-31 20:20:00 January 2020 42.8723 74.604700 24.77970
#> 27 2019-12-31 20:30:00 January 2020 42.9722 74.778500 24.83750
#> 28 2019-12-31 20:40:00 January 2020 NA NA NA
#> 29 2019-12-31 20:50:00 January 2020 NA 7.220000 47.02920
#> 30 2019-12-31 21:00:00 January 2020 NA NA NA
#> 31 2019-12-31 21:10:00 January 2020 96.5514 72.156500 23.97317
#> 32 2019-12-31 21:20:00 January 2020 39.7904 75.611000 64.48590
#> 33 2019-12-31 21:30:00 January 2020 96.7000 72.500300 24.08080
#> 34 2019-12-31 21:40:00 January 2020 NA NA NA
#> 35 2019-12-31 21:50:00 January 2020 NA NA NA
#> 36 2019-12-31 22:00:00 January 2020 NA NA NA
#> 37 2019-12-31 22:10:00 January 2020 NA NA NA
#> 38 2019-12-31 22:20:00 January 2020 45.0185 78.339400 26.02020
#> 39 2019-12-31 22:30:00 January 2020 61.2601 NA NA
#> 40 2019-12-31 22:40:00 January 2020 82.6597 150.506000 91.18910
#> 41 2019-12-31 22:50:00 January 2020 NA NA NA
#> 42 2019-12-31 23:00:00 January 2020 61.2601 NA NA
#> 43 2019-12-31 23:10:00 January 2020 NA NA NA
#> 44 2019-12-31 23:20:00 January 2020 57.7803 NA NA
#> 45 2019-12-31 23:30:00 January 2020 NA NA NA
#> 46 2019-12-31 23:40:00 January 2020 NA NA NA
#> 47 2019-12-31 23:50:00 January 2020 61.2601 NA NA
#> 48 2020-01-01 00:00:00 January 2020 NA NA NA
#> 49 2020-01-01 00:10:00 January 2020 NA NA NA
#> 50 2020-01-01 00:20:00 January 2020 NA NA NA
#> 51 2020-01-01 00:30:00 January 2020 NA NA NA
#> 52 2020-01-01 00:40:00 January 2020 36.2432 76.502400 111.10200
#> 53 2020-01-01 00:50:00 January 2020 NA NA NA
#> 54 2020-01-01 01:00:00 January 2020 NA NA NA
#> 55 2020-01-01 01:10:00 January 2020 61.2601 NA NA
#> 56 2020-01-01 01:20:00 January 2020 94.8684 76.232500 25.32040
#> 57 2020-01-01 01:30:00 January 2020 NA 6.607000 43.03640
#> 58 2020-01-01 01:40:00 January 2020 NA 6.974900 45.43250
#> 59 2020-01-01 01:50:00 January 2020 NA NA NA
#> 60 2020-01-01 02:20:00 January 2020 NA NA NA
#> 61 2020-01-01 02:30:00 January 2020 NA NA NA
#> 62 2020-01-01 02:40:00 January 2020 NA NA NA
#> 63 2020-01-01 02:50:00 January 2020 NA NA NA
#> 64 2020-01-01 03:00:00 January 2020 NA NA NA
#> 65 2020-01-01 03:10:00 January 2020 NA NA NA
#> 66 2020-01-01 03:20:00 January 2020 NA NA NA
#> 67 2020-01-01 03:30:00 January 2020 122.5200 NA NA
#> 68 2020-01-01 03:40:00 January 2020 NA NA NA
#> 69 2020-01-01 03:50:00 January 2020 NA NA NA
#> 70 2020-01-01 04:00:00 January 2020 NA NA NA
#> 71 2020-01-01 04:10:00 January 2020 NA NA NA
#> 72 2020-01-01 04:20:00 January 2020 129.7860 148.343000 49.27180
#> 73 2020-01-01 04:30:00 January 2020 NA NA NA
#> 74 2020-01-01 04:40:00 January 2020 NA NA NA
#> 75 2020-01-01 04:50:00 January 2020 NA NA NA
#> 76 2020-01-01 05:00:00 January 2020 NA NA NA
#> 77 2020-01-01 05:40:00 January 2020 NA NA NA
#> 78 2020-01-01 05:50:00 January 2020 NA NA NA
#> 79 2020-01-01 06:00:00 January 2020 NA NA NA
#> 80 2020-01-01 06:10:00 January 2020 NA NA NA
#> 81 2020-01-01 06:20:00 January 2020 NA 6.974900 45.43250
#> 82 2020-01-01 06:30:00 January 2020 NA NA NA
#> 83 2020-01-01 06:40:00 January 2020 NA 21.183000 134.88903
#> 84 2020-01-01 06:50:00 January 2020 NA 13.949800 90.86510
#> 85 2020-01-01 07:00:00 January 2020 NA NA NA
#> 86 2020-01-01 07:10:00 January 2020 NA NA NA
#> 87 2020-01-01 07:20:00 January 2020 122.5200 NA NA
#> 88 2020-01-01 07:30:00 January 2020 NA 7.233200 47.11520
#> 89 2020-01-01 07:40:00 January 2020 42.9722 74.778500 24.83750
#> 90 2020-01-01 07:50:00 January 2020 NA NA NA
#> 91 2020-01-01 08:00:00 January 2020 NA NA NA
#> 92 2020-01-01 08:10:00 January 2020 NA NA NA
#> 93 2020-01-01 08:20:00 January 2020 NA NA NA
#> 94 2020-01-01 08:30:00 January 2020 NA NA NA
#> 95 2020-01-01 08:40:00 January 2020 NA NA NA
#> 96 2020-01-01 08:50:00 January 2020 NA NA NA
#> 97 2020-01-01 09:00:00 January 2020 NA NA NA
#> 98 2020-01-01 09:10:00 January 2020 NA NA NA
#> 99 2020-01-01 09:20:00 January 2020 NA NA NA
#> 100 2020-01-01 09:30:00 January 2020 NA NA NA