impute_below operates on all variables. To only impute variables that satisfy a specific condition, use the scoped variants, impute_below_at, and impute_below_if. To use _at effectively, you must know that _at`` affects variables selected with a character vector, or withvars()`.

impute_below_at(.tbl, .vars, prop_below = 0.1, jitter = 0.05, ...)

Arguments

.tbl

a data.frame

.vars

variables to impute

prop_below

the degree to shift the values. default is

jitter

the amount of jitter to add. default is 0.05

...

extra arguments

Value

an dataset with values imputed

Examples

# select variables starting with a particular string. library(dplyr)
#> #> Attaching package: ‘dplyr’
#> The following object is masked from ‘package:testthat’: #> #> matches
#> The following objects are masked from ‘package:stats’: #> #> filter, lag
#> The following objects are masked from ‘package:base’: #> #> intersect, setdiff, setequal, union
impute_below_at(airquality, .vars = c("Ozone", "Solar.R"))
#> Ozone Solar.R Wind Temp Month Day #> 1 41.00000 190.00000 7.4 67 5 1 #> 2 36.00000 118.00000 8.0 72 5 2 #> 3 12.00000 149.00000 12.6 74 5 3 #> 4 18.00000 313.00000 11.5 62 5 4 #> 5 -19.72321 -33.57778 14.3 56 5 5 #> 6 28.00000 -33.07810 14.9 66 5 6 #> 7 23.00000 299.00000 8.6 65 5 7 #> 8 19.00000 99.00000 13.8 59 5 8 #> 9 8.00000 19.00000 20.1 61 5 9 #> 10 -18.51277 194.00000 8.6 69 5 10 #> 11 7.00000 -21.37719 6.9 74 5 11 #> 12 16.00000 256.00000 9.7 69 5 12 #> 13 11.00000 290.00000 9.2 66 5 13 #> 14 14.00000 274.00000 10.9 68 5 14 #> 15 18.00000 65.00000 13.2 58 5 15 #> 16 14.00000 334.00000 11.5 64 5 16 #> 17 34.00000 307.00000 12.0 66 5 17 #> 18 6.00000 78.00000 18.4 57 5 18 #> 19 30.00000 322.00000 11.5 68 5 19 #> 20 11.00000 44.00000 9.7 62 5 20 #> 21 1.00000 8.00000 9.7 59 5 21 #> 22 11.00000 320.00000 16.6 73 5 22 #> 23 4.00000 25.00000 9.7 61 5 23 #> 24 32.00000 92.00000 12.0 61 5 24 #> 25 -17.81863 66.00000 16.6 57 5 25 #> 26 -19.43853 266.00000 14.9 58 5 26 #> 27 -15.14310 -24.60954 8.0 57 5 27 #> 28 23.00000 13.00000 12.0 67 5 28 #> 29 45.00000 252.00000 14.9 81 5 29 #> 30 115.00000 223.00000 5.7 79 5 30 #> 31 37.00000 279.00000 7.4 76 5 31 #> 32 -16.17315 286.00000 8.6 78 6 1 #> 33 -14.65883 287.00000 9.7 74 6 2 #> 34 -17.85609 242.00000 16.1 67 6 3 #> 35 -13.29299 186.00000 9.2 84 6 4 #> 36 -16.16323 220.00000 8.6 85 6 5 #> 37 -19.60935 264.00000 14.3 79 6 6 #> 38 29.00000 127.00000 9.7 82 6 7 #> 39 -19.65780 273.00000 6.9 87 6 8 #> 40 71.00000 291.00000 13.8 90 6 9 #> 41 39.00000 323.00000 11.5 87 6 10 #> 42 -13.40961 259.00000 10.9 93 6 11 #> 43 -13.53728 250.00000 9.2 92 6 12 #> 44 23.00000 148.00000 8.0 82 6 13 #> 45 -19.65993 332.00000 13.8 80 6 14 #> 46 -16.48342 322.00000 11.5 79 6 15 #> 47 21.00000 191.00000 14.9 77 6 16 #> 48 37.00000 284.00000 20.7 72 6 17 #> 49 20.00000 37.00000 9.2 65 6 18 #> 50 12.00000 120.00000 11.5 73 6 19 #> 51 13.00000 137.00000 10.3 76 6 20 #> 52 -17.17718 150.00000 6.3 77 6 21 #> 53 -16.74073 59.00000 1.7 76 6 22 #> 54 -13.65786 91.00000 4.6 76 6 23 #> 55 -16.78786 250.00000 6.3 76 6 24 #> 56 -12.30098 135.00000 8.0 75 6 25 #> 57 -13.33171 127.00000 8.0 78 6 26 #> 58 -16.77414 47.00000 10.3 73 6 27 #> 59 -17.08225 98.00000 11.5 80 6 28 #> 60 -15.98818 31.00000 14.9 77 6 29 #> 61 -19.17558 138.00000 8.0 83 6 30 #> 62 135.00000 269.00000 4.1 84 7 1 #> 63 49.00000 248.00000 9.2 85 7 2 #> 64 32.00000 236.00000 9.2 81 7 3 #> 65 -14.27138 101.00000 10.9 84 7 4 #> 66 64.00000 175.00000 4.6 83 7 5 #> 67 40.00000 314.00000 10.9 83 7 6 #> 68 77.00000 276.00000 5.1 88 7 7 #> 69 97.00000 267.00000 6.3 92 7 8 #> 70 97.00000 272.00000 5.7 92 7 9 #> 71 85.00000 175.00000 7.4 89 7 10 #> 72 -13.51764 139.00000 8.6 82 7 11 #> 73 10.00000 264.00000 14.3 73 7 12 #> 74 27.00000 175.00000 14.9 81 7 13 #> 75 -13.48998 291.00000 14.9 91 7 14 #> 76 7.00000 48.00000 14.3 80 7 15 #> 77 48.00000 260.00000 6.9 81 7 16 #> 78 35.00000 274.00000 10.3 82 7 17 #> 79 61.00000 285.00000 6.3 84 7 18 #> 80 79.00000 187.00000 5.1 87 7 19 #> 81 63.00000 220.00000 11.5 85 7 20 #> 82 16.00000 7.00000 6.9 74 7 21 #> 83 -16.92150 258.00000 9.7 81 7 22 #> 84 -16.60335 295.00000 11.5 82 7 23 #> 85 80.00000 294.00000 8.6 86 7 24 #> 86 108.00000 223.00000 8.0 85 7 25 #> 87 20.00000 81.00000 8.6 82 7 26 #> 88 52.00000 82.00000 12.0 86 7 27 #> 89 82.00000 213.00000 7.4 88 7 28 #> 90 50.00000 275.00000 7.4 86 7 29 #> 91 64.00000 253.00000 7.4 83 7 30 #> 92 59.00000 254.00000 9.2 81 7 31 #> 93 39.00000 83.00000 6.9 81 8 1 #> 94 9.00000 24.00000 13.8 81 8 2 #> 95 16.00000 77.00000 7.4 82 8 3 #> 96 78.00000 -30.94374 6.9 86 8 4 #> 97 35.00000 -33.38707 7.4 85 8 5 #> 98 66.00000 -21.48980 4.6 87 8 6 #> 99 122.00000 255.00000 4.0 89 8 7 #> 100 89.00000 229.00000 10.3 90 8 8 #> 101 110.00000 207.00000 8.0 90 8 9 #> 102 -14.78907 222.00000 8.6 92 8 10 #> 103 -16.19151 137.00000 11.5 86 8 11 #> 104 44.00000 192.00000 11.5 86 8 12 #> 105 28.00000 273.00000 11.5 82 8 13 #> 106 65.00000 157.00000 9.7 80 8 14 #> 107 -19.73591 64.00000 11.5 79 8 15 #> 108 22.00000 71.00000 10.3 77 8 16 #> 109 59.00000 51.00000 6.3 79 8 17 #> 110 23.00000 115.00000 7.4 76 8 18 #> 111 31.00000 244.00000 10.9 78 8 19 #> 112 44.00000 190.00000 10.3 78 8 20 #> 113 21.00000 259.00000 15.5 77 8 21 #> 114 9.00000 36.00000 14.3 72 8 22 #> 115 -18.92235 255.00000 12.6 75 8 23 #> 116 45.00000 212.00000 9.7 79 8 24 #> 117 168.00000 238.00000 3.4 81 8 25 #> 118 73.00000 215.00000 8.0 86 8 26 #> 119 -14.86296 153.00000 5.7 88 8 27 #> 120 76.00000 203.00000 9.7 97 8 28 #> 121 118.00000 225.00000 2.3 94 8 29 #> 122 84.00000 237.00000 6.3 96 8 30 #> 123 85.00000 188.00000 6.3 94 8 31 #> 124 96.00000 167.00000 6.9 91 9 1 #> 125 78.00000 197.00000 5.1 92 9 2 #> 126 73.00000 183.00000 2.8 93 9 3 #> 127 91.00000 189.00000 4.6 93 9 4 #> 128 47.00000 95.00000 7.4 87 9 5 #> 129 32.00000 92.00000 15.5 84 9 6 #> 130 20.00000 252.00000 10.9 80 9 7 #> 131 23.00000 220.00000 10.3 78 9 8 #> 132 21.00000 230.00000 10.9 75 9 9 #> 133 24.00000 259.00000 9.7 73 9 10 #> 134 44.00000 236.00000 14.9 81 9 11 #> 135 21.00000 259.00000 15.5 76 9 12 #> 136 28.00000 238.00000 6.3 77 9 13 #> 137 9.00000 24.00000 10.9 71 9 14 #> 138 13.00000 112.00000 11.5 71 9 15 #> 139 46.00000 237.00000 6.9 78 9 16 #> 140 18.00000 224.00000 13.8 67 9 17 #> 141 13.00000 27.00000 10.3 76 9 18 #> 142 24.00000 238.00000 10.3 68 9 19 #> 143 16.00000 201.00000 8.0 82 9 20 #> 144 13.00000 238.00000 12.6 64 9 21 #> 145 23.00000 14.00000 9.2 71 9 22 #> 146 36.00000 139.00000 10.3 81 9 23 #> 147 7.00000 49.00000 10.3 69 9 24 #> 148 14.00000 20.00000 16.6 63 9 25 #> 149 30.00000 193.00000 6.9 70 9 26 #> 150 -14.83089 145.00000 13.2 77 9 27 #> 151 14.00000 191.00000 14.3 75 9 28 #> 152 18.00000 131.00000 8.0 76 9 29 #> 153 20.00000 223.00000 11.5 68 9 30
impute_below_at(airquality, .vars = 1:2)
#> Ozone Solar.R Wind Temp Month Day #> 1 41.00000 190.00000 7.4 67 5 1 #> 2 36.00000 118.00000 8.0 72 5 2 #> 3 12.00000 149.00000 12.6 74 5 3 #> 4 18.00000 313.00000 11.5 62 5 4 #> 5 -19.72321 -33.57778 14.3 56 5 5 #> 6 28.00000 -33.07810 14.9 66 5 6 #> 7 23.00000 299.00000 8.6 65 5 7 #> 8 19.00000 99.00000 13.8 59 5 8 #> 9 8.00000 19.00000 20.1 61 5 9 #> 10 -18.51277 194.00000 8.6 69 5 10 #> 11 7.00000 -21.37719 6.9 74 5 11 #> 12 16.00000 256.00000 9.7 69 5 12 #> 13 11.00000 290.00000 9.2 66 5 13 #> 14 14.00000 274.00000 10.9 68 5 14 #> 15 18.00000 65.00000 13.2 58 5 15 #> 16 14.00000 334.00000 11.5 64 5 16 #> 17 34.00000 307.00000 12.0 66 5 17 #> 18 6.00000 78.00000 18.4 57 5 18 #> 19 30.00000 322.00000 11.5 68 5 19 #> 20 11.00000 44.00000 9.7 62 5 20 #> 21 1.00000 8.00000 9.7 59 5 21 #> 22 11.00000 320.00000 16.6 73 5 22 #> 23 4.00000 25.00000 9.7 61 5 23 #> 24 32.00000 92.00000 12.0 61 5 24 #> 25 -17.81863 66.00000 16.6 57 5 25 #> 26 -19.43853 266.00000 14.9 58 5 26 #> 27 -15.14310 -24.60954 8.0 57 5 27 #> 28 23.00000 13.00000 12.0 67 5 28 #> 29 45.00000 252.00000 14.9 81 5 29 #> 30 115.00000 223.00000 5.7 79 5 30 #> 31 37.00000 279.00000 7.4 76 5 31 #> 32 -16.17315 286.00000 8.6 78 6 1 #> 33 -14.65883 287.00000 9.7 74 6 2 #> 34 -17.85609 242.00000 16.1 67 6 3 #> 35 -13.29299 186.00000 9.2 84 6 4 #> 36 -16.16323 220.00000 8.6 85 6 5 #> 37 -19.60935 264.00000 14.3 79 6 6 #> 38 29.00000 127.00000 9.7 82 6 7 #> 39 -19.65780 273.00000 6.9 87 6 8 #> 40 71.00000 291.00000 13.8 90 6 9 #> 41 39.00000 323.00000 11.5 87 6 10 #> 42 -13.40961 259.00000 10.9 93 6 11 #> 43 -13.53728 250.00000 9.2 92 6 12 #> 44 23.00000 148.00000 8.0 82 6 13 #> 45 -19.65993 332.00000 13.8 80 6 14 #> 46 -16.48342 322.00000 11.5 79 6 15 #> 47 21.00000 191.00000 14.9 77 6 16 #> 48 37.00000 284.00000 20.7 72 6 17 #> 49 20.00000 37.00000 9.2 65 6 18 #> 50 12.00000 120.00000 11.5 73 6 19 #> 51 13.00000 137.00000 10.3 76 6 20 #> 52 -17.17718 150.00000 6.3 77 6 21 #> 53 -16.74073 59.00000 1.7 76 6 22 #> 54 -13.65786 91.00000 4.6 76 6 23 #> 55 -16.78786 250.00000 6.3 76 6 24 #> 56 -12.30098 135.00000 8.0 75 6 25 #> 57 -13.33171 127.00000 8.0 78 6 26 #> 58 -16.77414 47.00000 10.3 73 6 27 #> 59 -17.08225 98.00000 11.5 80 6 28 #> 60 -15.98818 31.00000 14.9 77 6 29 #> 61 -19.17558 138.00000 8.0 83 6 30 #> 62 135.00000 269.00000 4.1 84 7 1 #> 63 49.00000 248.00000 9.2 85 7 2 #> 64 32.00000 236.00000 9.2 81 7 3 #> 65 -14.27138 101.00000 10.9 84 7 4 #> 66 64.00000 175.00000 4.6 83 7 5 #> 67 40.00000 314.00000 10.9 83 7 6 #> 68 77.00000 276.00000 5.1 88 7 7 #> 69 97.00000 267.00000 6.3 92 7 8 #> 70 97.00000 272.00000 5.7 92 7 9 #> 71 85.00000 175.00000 7.4 89 7 10 #> 72 -13.51764 139.00000 8.6 82 7 11 #> 73 10.00000 264.00000 14.3 73 7 12 #> 74 27.00000 175.00000 14.9 81 7 13 #> 75 -13.48998 291.00000 14.9 91 7 14 #> 76 7.00000 48.00000 14.3 80 7 15 #> 77 48.00000 260.00000 6.9 81 7 16 #> 78 35.00000 274.00000 10.3 82 7 17 #> 79 61.00000 285.00000 6.3 84 7 18 #> 80 79.00000 187.00000 5.1 87 7 19 #> 81 63.00000 220.00000 11.5 85 7 20 #> 82 16.00000 7.00000 6.9 74 7 21 #> 83 -16.92150 258.00000 9.7 81 7 22 #> 84 -16.60335 295.00000 11.5 82 7 23 #> 85 80.00000 294.00000 8.6 86 7 24 #> 86 108.00000 223.00000 8.0 85 7 25 #> 87 20.00000 81.00000 8.6 82 7 26 #> 88 52.00000 82.00000 12.0 86 7 27 #> 89 82.00000 213.00000 7.4 88 7 28 #> 90 50.00000 275.00000 7.4 86 7 29 #> 91 64.00000 253.00000 7.4 83 7 30 #> 92 59.00000 254.00000 9.2 81 7 31 #> 93 39.00000 83.00000 6.9 81 8 1 #> 94 9.00000 24.00000 13.8 81 8 2 #> 95 16.00000 77.00000 7.4 82 8 3 #> 96 78.00000 -30.94374 6.9 86 8 4 #> 97 35.00000 -33.38707 7.4 85 8 5 #> 98 66.00000 -21.48980 4.6 87 8 6 #> 99 122.00000 255.00000 4.0 89 8 7 #> 100 89.00000 229.00000 10.3 90 8 8 #> 101 110.00000 207.00000 8.0 90 8 9 #> 102 -14.78907 222.00000 8.6 92 8 10 #> 103 -16.19151 137.00000 11.5 86 8 11 #> 104 44.00000 192.00000 11.5 86 8 12 #> 105 28.00000 273.00000 11.5 82 8 13 #> 106 65.00000 157.00000 9.7 80 8 14 #> 107 -19.73591 64.00000 11.5 79 8 15 #> 108 22.00000 71.00000 10.3 77 8 16 #> 109 59.00000 51.00000 6.3 79 8 17 #> 110 23.00000 115.00000 7.4 76 8 18 #> 111 31.00000 244.00000 10.9 78 8 19 #> 112 44.00000 190.00000 10.3 78 8 20 #> 113 21.00000 259.00000 15.5 77 8 21 #> 114 9.00000 36.00000 14.3 72 8 22 #> 115 -18.92235 255.00000 12.6 75 8 23 #> 116 45.00000 212.00000 9.7 79 8 24 #> 117 168.00000 238.00000 3.4 81 8 25 #> 118 73.00000 215.00000 8.0 86 8 26 #> 119 -14.86296 153.00000 5.7 88 8 27 #> 120 76.00000 203.00000 9.7 97 8 28 #> 121 118.00000 225.00000 2.3 94 8 29 #> 122 84.00000 237.00000 6.3 96 8 30 #> 123 85.00000 188.00000 6.3 94 8 31 #> 124 96.00000 167.00000 6.9 91 9 1 #> 125 78.00000 197.00000 5.1 92 9 2 #> 126 73.00000 183.00000 2.8 93 9 3 #> 127 91.00000 189.00000 4.6 93 9 4 #> 128 47.00000 95.00000 7.4 87 9 5 #> 129 32.00000 92.00000 15.5 84 9 6 #> 130 20.00000 252.00000 10.9 80 9 7 #> 131 23.00000 220.00000 10.3 78 9 8 #> 132 21.00000 230.00000 10.9 75 9 9 #> 133 24.00000 259.00000 9.7 73 9 10 #> 134 44.00000 236.00000 14.9 81 9 11 #> 135 21.00000 259.00000 15.5 76 9 12 #> 136 28.00000 238.00000 6.3 77 9 13 #> 137 9.00000 24.00000 10.9 71 9 14 #> 138 13.00000 112.00000 11.5 71 9 15 #> 139 46.00000 237.00000 6.9 78 9 16 #> 140 18.00000 224.00000 13.8 67 9 17 #> 141 13.00000 27.00000 10.3 76 9 18 #> 142 24.00000 238.00000 10.3 68 9 19 #> 143 16.00000 201.00000 8.0 82 9 20 #> 144 13.00000 238.00000 12.6 64 9 21 #> 145 23.00000 14.00000 9.2 71 9 22 #> 146 36.00000 139.00000 10.3 81 9 23 #> 147 7.00000 49.00000 10.3 69 9 24 #> 148 14.00000 20.00000 16.6 63 9 25 #> 149 30.00000 193.00000 6.9 70 9 26 #> 150 -14.83089 145.00000 13.2 77 9 27 #> 151 14.00000 191.00000 14.3 75 9 28 #> 152 18.00000 131.00000 8.0 76 9 29 #> 153 20.00000 223.00000 11.5 68 9 30
#' impute_below_at(airquality, .vars = vars(Ozone))
#> Ozone Solar.R Wind Temp Month Day #> 1 41.00000 190 7.4 67 5 1 #> 2 36.00000 118 8.0 72 5 2 #> 3 12.00000 149 12.6 74 5 3 #> 4 18.00000 313 11.5 62 5 4 #> 5 -19.72321 NA 14.3 56 5 5 #> 6 28.00000 NA 14.9 66 5 6 #> 7 23.00000 299 8.6 65 5 7 #> 8 19.00000 99 13.8 59 5 8 #> 9 8.00000 19 20.1 61 5 9 #> 10 -18.51277 194 8.6 69 5 10 #> 11 7.00000 NA 6.9 74 5 11 #> 12 16.00000 256 9.7 69 5 12 #> 13 11.00000 290 9.2 66 5 13 #> 14 14.00000 274 10.9 68 5 14 #> 15 18.00000 65 13.2 58 5 15 #> 16 14.00000 334 11.5 64 5 16 #> 17 34.00000 307 12.0 66 5 17 #> 18 6.00000 78 18.4 57 5 18 #> 19 30.00000 322 11.5 68 5 19 #> 20 11.00000 44 9.7 62 5 20 #> 21 1.00000 8 9.7 59 5 21 #> 22 11.00000 320 16.6 73 5 22 #> 23 4.00000 25 9.7 61 5 23 #> 24 32.00000 92 12.0 61 5 24 #> 25 -17.81863 66 16.6 57 5 25 #> 26 -19.43853 266 14.9 58 5 26 #> 27 -15.14310 NA 8.0 57 5 27 #> 28 23.00000 13 12.0 67 5 28 #> 29 45.00000 252 14.9 81 5 29 #> 30 115.00000 223 5.7 79 5 30 #> 31 37.00000 279 7.4 76 5 31 #> 32 -16.17315 286 8.6 78 6 1 #> 33 -14.65883 287 9.7 74 6 2 #> 34 -17.85609 242 16.1 67 6 3 #> 35 -13.29299 186 9.2 84 6 4 #> 36 -16.16323 220 8.6 85 6 5 #> 37 -19.60935 264 14.3 79 6 6 #> 38 29.00000 127 9.7 82 6 7 #> 39 -19.65780 273 6.9 87 6 8 #> 40 71.00000 291 13.8 90 6 9 #> 41 39.00000 323 11.5 87 6 10 #> 42 -13.40961 259 10.9 93 6 11 #> 43 -13.53728 250 9.2 92 6 12 #> 44 23.00000 148 8.0 82 6 13 #> 45 -19.65993 332 13.8 80 6 14 #> 46 -16.48342 322 11.5 79 6 15 #> 47 21.00000 191 14.9 77 6 16 #> 48 37.00000 284 20.7 72 6 17 #> 49 20.00000 37 9.2 65 6 18 #> 50 12.00000 120 11.5 73 6 19 #> 51 13.00000 137 10.3 76 6 20 #> 52 -17.17718 150 6.3 77 6 21 #> 53 -16.74073 59 1.7 76 6 22 #> 54 -13.65786 91 4.6 76 6 23 #> 55 -16.78786 250 6.3 76 6 24 #> 56 -12.30098 135 8.0 75 6 25 #> 57 -13.33171 127 8.0 78 6 26 #> 58 -16.77414 47 10.3 73 6 27 #> 59 -17.08225 98 11.5 80 6 28 #> 60 -15.98818 31 14.9 77 6 29 #> 61 -19.17558 138 8.0 83 6 30 #> 62 135.00000 269 4.1 84 7 1 #> 63 49.00000 248 9.2 85 7 2 #> 64 32.00000 236 9.2 81 7 3 #> 65 -14.27138 101 10.9 84 7 4 #> 66 64.00000 175 4.6 83 7 5 #> 67 40.00000 314 10.9 83 7 6 #> 68 77.00000 276 5.1 88 7 7 #> 69 97.00000 267 6.3 92 7 8 #> 70 97.00000 272 5.7 92 7 9 #> 71 85.00000 175 7.4 89 7 10 #> 72 -13.51764 139 8.6 82 7 11 #> 73 10.00000 264 14.3 73 7 12 #> 74 27.00000 175 14.9 81 7 13 #> 75 -13.48998 291 14.9 91 7 14 #> 76 7.00000 48 14.3 80 7 15 #> 77 48.00000 260 6.9 81 7 16 #> 78 35.00000 274 10.3 82 7 17 #> 79 61.00000 285 6.3 84 7 18 #> 80 79.00000 187 5.1 87 7 19 #> 81 63.00000 220 11.5 85 7 20 #> 82 16.00000 7 6.9 74 7 21 #> 83 -16.92150 258 9.7 81 7 22 #> 84 -16.60335 295 11.5 82 7 23 #> 85 80.00000 294 8.6 86 7 24 #> 86 108.00000 223 8.0 85 7 25 #> 87 20.00000 81 8.6 82 7 26 #> 88 52.00000 82 12.0 86 7 27 #> 89 82.00000 213 7.4 88 7 28 #> 90 50.00000 275 7.4 86 7 29 #> 91 64.00000 253 7.4 83 7 30 #> 92 59.00000 254 9.2 81 7 31 #> 93 39.00000 83 6.9 81 8 1 #> 94 9.00000 24 13.8 81 8 2 #> 95 16.00000 77 7.4 82 8 3 #> 96 78.00000 NA 6.9 86 8 4 #> 97 35.00000 NA 7.4 85 8 5 #> 98 66.00000 NA 4.6 87 8 6 #> 99 122.00000 255 4.0 89 8 7 #> 100 89.00000 229 10.3 90 8 8 #> 101 110.00000 207 8.0 90 8 9 #> 102 -14.78907 222 8.6 92 8 10 #> 103 -16.19151 137 11.5 86 8 11 #> 104 44.00000 192 11.5 86 8 12 #> 105 28.00000 273 11.5 82 8 13 #> 106 65.00000 157 9.7 80 8 14 #> 107 -19.73591 64 11.5 79 8 15 #> 108 22.00000 71 10.3 77 8 16 #> 109 59.00000 51 6.3 79 8 17 #> 110 23.00000 115 7.4 76 8 18 #> 111 31.00000 244 10.9 78 8 19 #> 112 44.00000 190 10.3 78 8 20 #> 113 21.00000 259 15.5 77 8 21 #> 114 9.00000 36 14.3 72 8 22 #> 115 -18.92235 255 12.6 75 8 23 #> 116 45.00000 212 9.7 79 8 24 #> 117 168.00000 238 3.4 81 8 25 #> 118 73.00000 215 8.0 86 8 26 #> 119 -14.86296 153 5.7 88 8 27 #> 120 76.00000 203 9.7 97 8 28 #> 121 118.00000 225 2.3 94 8 29 #> 122 84.00000 237 6.3 96 8 30 #> 123 85.00000 188 6.3 94 8 31 #> 124 96.00000 167 6.9 91 9 1 #> 125 78.00000 197 5.1 92 9 2 #> 126 73.00000 183 2.8 93 9 3 #> 127 91.00000 189 4.6 93 9 4 #> 128 47.00000 95 7.4 87 9 5 #> 129 32.00000 92 15.5 84 9 6 #> 130 20.00000 252 10.9 80 9 7 #> 131 23.00000 220 10.3 78 9 8 #> 132 21.00000 230 10.9 75 9 9 #> 133 24.00000 259 9.7 73 9 10 #> 134 44.00000 236 14.9 81 9 11 #> 135 21.00000 259 15.5 76 9 12 #> 136 28.00000 238 6.3 77 9 13 #> 137 9.00000 24 10.9 71 9 14 #> 138 13.00000 112 11.5 71 9 15 #> 139 46.00000 237 6.9 78 9 16 #> 140 18.00000 224 13.8 67 9 17 #> 141 13.00000 27 10.3 76 9 18 #> 142 24.00000 238 10.3 68 9 19 #> 143 16.00000 201 8.0 82 9 20 #> 144 13.00000 238 12.6 64 9 21 #> 145 23.00000 14 9.2 71 9 22 #> 146 36.00000 139 10.3 81 9 23 #> 147 7.00000 49 10.3 69 9 24 #> 148 14.00000 20 16.6 63 9 25 #> 149 30.00000 193 6.9 70 9 26 #> 150 -14.83089 145 13.2 77 9 27 #> 151 14.00000 191 14.3 75 9 28 #> 152 18.00000 131 8.0 76 9 29 #> 153 20.00000 223 11.5 68 9 30
# NOT RUN { library(ggplot2) airquality %>% bind_shadow() %>% impute_below_at(vars(Ozone, Solar.R)) %>% add_label_shadow() %>% ggplot(aes(x = Ozone, y = Solar.R, colour = any_missing)) + geom_point() # }