impute_median imputes the median for a vector. To get it to work on all variables, use impute_median_all. 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_median_all(.tbl)

impute_median_at(.tbl, .vars)

impute_median_if(.tbl, .predicate)

Arguments

.tbl

a data.frame

.vars

variables to impute

.predicate

variables to impute

Value

an dataset with values imputed

Examples

# select variables starting with a particular string. library(dplyr) impute_median_all(airquality)
#> Ozone Solar.R Wind Temp Month Day #> 1 41.0 190 7.4 67 5 1 #> 2 36.0 118 8.0 72 5 2 #> 3 12.0 149 12.6 74 5 3 #> 4 18.0 313 11.5 62 5 4 #> 5 31.5 205 14.3 56 5 5 #> 6 28.0 205 14.9 66 5 6 #> 7 23.0 299 8.6 65 5 7 #> 8 19.0 99 13.8 59 5 8 #> 9 8.0 19 20.1 61 5 9 #> 10 31.5 194 8.6 69 5 10 #> 11 7.0 205 6.9 74 5 11 #> 12 16.0 256 9.7 69 5 12 #> 13 11.0 290 9.2 66 5 13 #> 14 14.0 274 10.9 68 5 14 #> 15 18.0 65 13.2 58 5 15 #> 16 14.0 334 11.5 64 5 16 #> 17 34.0 307 12.0 66 5 17 #> 18 6.0 78 18.4 57 5 18 #> 19 30.0 322 11.5 68 5 19 #> 20 11.0 44 9.7 62 5 20 #> 21 1.0 8 9.7 59 5 21 #> 22 11.0 320 16.6 73 5 22 #> 23 4.0 25 9.7 61 5 23 #> 24 32.0 92 12.0 61 5 24 #> 25 31.5 66 16.6 57 5 25 #> 26 31.5 266 14.9 58 5 26 #> 27 31.5 205 8.0 57 5 27 #> 28 23.0 13 12.0 67 5 28 #> 29 45.0 252 14.9 81 5 29 #> 30 115.0 223 5.7 79 5 30 #> 31 37.0 279 7.4 76 5 31 #> 32 31.5 286 8.6 78 6 1 #> 33 31.5 287 9.7 74 6 2 #> 34 31.5 242 16.1 67 6 3 #> 35 31.5 186 9.2 84 6 4 #> 36 31.5 220 8.6 85 6 5 #> 37 31.5 264 14.3 79 6 6 #> 38 29.0 127 9.7 82 6 7 #> 39 31.5 273 6.9 87 6 8 #> 40 71.0 291 13.8 90 6 9 #> 41 39.0 323 11.5 87 6 10 #> 42 31.5 259 10.9 93 6 11 #> 43 31.5 250 9.2 92 6 12 #> 44 23.0 148 8.0 82 6 13 #> 45 31.5 332 13.8 80 6 14 #> 46 31.5 322 11.5 79 6 15 #> 47 21.0 191 14.9 77 6 16 #> 48 37.0 284 20.7 72 6 17 #> 49 20.0 37 9.2 65 6 18 #> 50 12.0 120 11.5 73 6 19 #> 51 13.0 137 10.3 76 6 20 #> 52 31.5 150 6.3 77 6 21 #> 53 31.5 59 1.7 76 6 22 #> 54 31.5 91 4.6 76 6 23 #> 55 31.5 250 6.3 76 6 24 #> 56 31.5 135 8.0 75 6 25 #> 57 31.5 127 8.0 78 6 26 #> 58 31.5 47 10.3 73 6 27 #> 59 31.5 98 11.5 80 6 28 #> 60 31.5 31 14.9 77 6 29 #> 61 31.5 138 8.0 83 6 30 #> 62 135.0 269 4.1 84 7 1 #> 63 49.0 248 9.2 85 7 2 #> 64 32.0 236 9.2 81 7 3 #> 65 31.5 101 10.9 84 7 4 #> 66 64.0 175 4.6 83 7 5 #> 67 40.0 314 10.9 83 7 6 #> 68 77.0 276 5.1 88 7 7 #> 69 97.0 267 6.3 92 7 8 #> 70 97.0 272 5.7 92 7 9 #> 71 85.0 175 7.4 89 7 10 #> 72 31.5 139 8.6 82 7 11 #> 73 10.0 264 14.3 73 7 12 #> 74 27.0 175 14.9 81 7 13 #> 75 31.5 291 14.9 91 7 14 #> 76 7.0 48 14.3 80 7 15 #> 77 48.0 260 6.9 81 7 16 #> 78 35.0 274 10.3 82 7 17 #> 79 61.0 285 6.3 84 7 18 #> 80 79.0 187 5.1 87 7 19 #> 81 63.0 220 11.5 85 7 20 #> 82 16.0 7 6.9 74 7 21 #> 83 31.5 258 9.7 81 7 22 #> 84 31.5 295 11.5 82 7 23 #> 85 80.0 294 8.6 86 7 24 #> 86 108.0 223 8.0 85 7 25 #> 87 20.0 81 8.6 82 7 26 #> 88 52.0 82 12.0 86 7 27 #> 89 82.0 213 7.4 88 7 28 #> 90 50.0 275 7.4 86 7 29 #> 91 64.0 253 7.4 83 7 30 #> 92 59.0 254 9.2 81 7 31 #> 93 39.0 83 6.9 81 8 1 #> 94 9.0 24 13.8 81 8 2 #> 95 16.0 77 7.4 82 8 3 #> 96 78.0 205 6.9 86 8 4 #> 97 35.0 205 7.4 85 8 5 #> 98 66.0 205 4.6 87 8 6 #> 99 122.0 255 4.0 89 8 7 #> 100 89.0 229 10.3 90 8 8 #> 101 110.0 207 8.0 90 8 9 #> 102 31.5 222 8.6 92 8 10 #> 103 31.5 137 11.5 86 8 11 #> 104 44.0 192 11.5 86 8 12 #> 105 28.0 273 11.5 82 8 13 #> 106 65.0 157 9.7 80 8 14 #> 107 31.5 64 11.5 79 8 15 #> 108 22.0 71 10.3 77 8 16 #> 109 59.0 51 6.3 79 8 17 #> 110 23.0 115 7.4 76 8 18 #> 111 31.0 244 10.9 78 8 19 #> 112 44.0 190 10.3 78 8 20 #> 113 21.0 259 15.5 77 8 21 #> 114 9.0 36 14.3 72 8 22 #> 115 31.5 255 12.6 75 8 23 #> 116 45.0 212 9.7 79 8 24 #> 117 168.0 238 3.4 81 8 25 #> 118 73.0 215 8.0 86 8 26 #> 119 31.5 153 5.7 88 8 27 #> 120 76.0 203 9.7 97 8 28 #> 121 118.0 225 2.3 94 8 29 #> 122 84.0 237 6.3 96 8 30 #> 123 85.0 188 6.3 94 8 31 #> 124 96.0 167 6.9 91 9 1 #> 125 78.0 197 5.1 92 9 2 #> 126 73.0 183 2.8 93 9 3 #> 127 91.0 189 4.6 93 9 4 #> 128 47.0 95 7.4 87 9 5 #> 129 32.0 92 15.5 84 9 6 #> 130 20.0 252 10.9 80 9 7 #> 131 23.0 220 10.3 78 9 8 #> 132 21.0 230 10.9 75 9 9 #> 133 24.0 259 9.7 73 9 10 #> 134 44.0 236 14.9 81 9 11 #> 135 21.0 259 15.5 76 9 12 #> 136 28.0 238 6.3 77 9 13 #> 137 9.0 24 10.9 71 9 14 #> 138 13.0 112 11.5 71 9 15 #> 139 46.0 237 6.9 78 9 16 #> 140 18.0 224 13.8 67 9 17 #> 141 13.0 27 10.3 76 9 18 #> 142 24.0 238 10.3 68 9 19 #> 143 16.0 201 8.0 82 9 20 #> 144 13.0 238 12.6 64 9 21 #> 145 23.0 14 9.2 71 9 22 #> 146 36.0 139 10.3 81 9 23 #> 147 7.0 49 10.3 69 9 24 #> 148 14.0 20 16.6 63 9 25 #> 149 30.0 193 6.9 70 9 26 #> 150 31.5 145 13.2 77 9 27 #> 151 14.0 191 14.3 75 9 28 #> 152 18.0 131 8.0 76 9 29 #> 153 20.0 223 11.5 68 9 30
impute_median_at(airquality, .vars = c("Ozone", "Solar.R"))
#> Ozone Solar.R Wind Temp Month Day #> 1 41.0 190 7.4 67 5 1 #> 2 36.0 118 8.0 72 5 2 #> 3 12.0 149 12.6 74 5 3 #> 4 18.0 313 11.5 62 5 4 #> 5 31.5 205 14.3 56 5 5 #> 6 28.0 205 14.9 66 5 6 #> 7 23.0 299 8.6 65 5 7 #> 8 19.0 99 13.8 59 5 8 #> 9 8.0 19 20.1 61 5 9 #> 10 31.5 194 8.6 69 5 10 #> 11 7.0 205 6.9 74 5 11 #> 12 16.0 256 9.7 69 5 12 #> 13 11.0 290 9.2 66 5 13 #> 14 14.0 274 10.9 68 5 14 #> 15 18.0 65 13.2 58 5 15 #> 16 14.0 334 11.5 64 5 16 #> 17 34.0 307 12.0 66 5 17 #> 18 6.0 78 18.4 57 5 18 #> 19 30.0 322 11.5 68 5 19 #> 20 11.0 44 9.7 62 5 20 #> 21 1.0 8 9.7 59 5 21 #> 22 11.0 320 16.6 73 5 22 #> 23 4.0 25 9.7 61 5 23 #> 24 32.0 92 12.0 61 5 24 #> 25 31.5 66 16.6 57 5 25 #> 26 31.5 266 14.9 58 5 26 #> 27 31.5 205 8.0 57 5 27 #> 28 23.0 13 12.0 67 5 28 #> 29 45.0 252 14.9 81 5 29 #> 30 115.0 223 5.7 79 5 30 #> 31 37.0 279 7.4 76 5 31 #> 32 31.5 286 8.6 78 6 1 #> 33 31.5 287 9.7 74 6 2 #> 34 31.5 242 16.1 67 6 3 #> 35 31.5 186 9.2 84 6 4 #> 36 31.5 220 8.6 85 6 5 #> 37 31.5 264 14.3 79 6 6 #> 38 29.0 127 9.7 82 6 7 #> 39 31.5 273 6.9 87 6 8 #> 40 71.0 291 13.8 90 6 9 #> 41 39.0 323 11.5 87 6 10 #> 42 31.5 259 10.9 93 6 11 #> 43 31.5 250 9.2 92 6 12 #> 44 23.0 148 8.0 82 6 13 #> 45 31.5 332 13.8 80 6 14 #> 46 31.5 322 11.5 79 6 15 #> 47 21.0 191 14.9 77 6 16 #> 48 37.0 284 20.7 72 6 17 #> 49 20.0 37 9.2 65 6 18 #> 50 12.0 120 11.5 73 6 19 #> 51 13.0 137 10.3 76 6 20 #> 52 31.5 150 6.3 77 6 21 #> 53 31.5 59 1.7 76 6 22 #> 54 31.5 91 4.6 76 6 23 #> 55 31.5 250 6.3 76 6 24 #> 56 31.5 135 8.0 75 6 25 #> 57 31.5 127 8.0 78 6 26 #> 58 31.5 47 10.3 73 6 27 #> 59 31.5 98 11.5 80 6 28 #> 60 31.5 31 14.9 77 6 29 #> 61 31.5 138 8.0 83 6 30 #> 62 135.0 269 4.1 84 7 1 #> 63 49.0 248 9.2 85 7 2 #> 64 32.0 236 9.2 81 7 3 #> 65 31.5 101 10.9 84 7 4 #> 66 64.0 175 4.6 83 7 5 #> 67 40.0 314 10.9 83 7 6 #> 68 77.0 276 5.1 88 7 7 #> 69 97.0 267 6.3 92 7 8 #> 70 97.0 272 5.7 92 7 9 #> 71 85.0 175 7.4 89 7 10 #> 72 31.5 139 8.6 82 7 11 #> 73 10.0 264 14.3 73 7 12 #> 74 27.0 175 14.9 81 7 13 #> 75 31.5 291 14.9 91 7 14 #> 76 7.0 48 14.3 80 7 15 #> 77 48.0 260 6.9 81 7 16 #> 78 35.0 274 10.3 82 7 17 #> 79 61.0 285 6.3 84 7 18 #> 80 79.0 187 5.1 87 7 19 #> 81 63.0 220 11.5 85 7 20 #> 82 16.0 7 6.9 74 7 21 #> 83 31.5 258 9.7 81 7 22 #> 84 31.5 295 11.5 82 7 23 #> 85 80.0 294 8.6 86 7 24 #> 86 108.0 223 8.0 85 7 25 #> 87 20.0 81 8.6 82 7 26 #> 88 52.0 82 12.0 86 7 27 #> 89 82.0 213 7.4 88 7 28 #> 90 50.0 275 7.4 86 7 29 #> 91 64.0 253 7.4 83 7 30 #> 92 59.0 254 9.2 81 7 31 #> 93 39.0 83 6.9 81 8 1 #> 94 9.0 24 13.8 81 8 2 #> 95 16.0 77 7.4 82 8 3 #> 96 78.0 205 6.9 86 8 4 #> 97 35.0 205 7.4 85 8 5 #> 98 66.0 205 4.6 87 8 6 #> 99 122.0 255 4.0 89 8 7 #> 100 89.0 229 10.3 90 8 8 #> 101 110.0 207 8.0 90 8 9 #> 102 31.5 222 8.6 92 8 10 #> 103 31.5 137 11.5 86 8 11 #> 104 44.0 192 11.5 86 8 12 #> 105 28.0 273 11.5 82 8 13 #> 106 65.0 157 9.7 80 8 14 #> 107 31.5 64 11.5 79 8 15 #> 108 22.0 71 10.3 77 8 16 #> 109 59.0 51 6.3 79 8 17 #> 110 23.0 115 7.4 76 8 18 #> 111 31.0 244 10.9 78 8 19 #> 112 44.0 190 10.3 78 8 20 #> 113 21.0 259 15.5 77 8 21 #> 114 9.0 36 14.3 72 8 22 #> 115 31.5 255 12.6 75 8 23 #> 116 45.0 212 9.7 79 8 24 #> 117 168.0 238 3.4 81 8 25 #> 118 73.0 215 8.0 86 8 26 #> 119 31.5 153 5.7 88 8 27 #> 120 76.0 203 9.7 97 8 28 #> 121 118.0 225 2.3 94 8 29 #> 122 84.0 237 6.3 96 8 30 #> 123 85.0 188 6.3 94 8 31 #> 124 96.0 167 6.9 91 9 1 #> 125 78.0 197 5.1 92 9 2 #> 126 73.0 183 2.8 93 9 3 #> 127 91.0 189 4.6 93 9 4 #> 128 47.0 95 7.4 87 9 5 #> 129 32.0 92 15.5 84 9 6 #> 130 20.0 252 10.9 80 9 7 #> 131 23.0 220 10.3 78 9 8 #> 132 21.0 230 10.9 75 9 9 #> 133 24.0 259 9.7 73 9 10 #> 134 44.0 236 14.9 81 9 11 #> 135 21.0 259 15.5 76 9 12 #> 136 28.0 238 6.3 77 9 13 #> 137 9.0 24 10.9 71 9 14 #> 138 13.0 112 11.5 71 9 15 #> 139 46.0 237 6.9 78 9 16 #> 140 18.0 224 13.8 67 9 17 #> 141 13.0 27 10.3 76 9 18 #> 142 24.0 238 10.3 68 9 19 #> 143 16.0 201 8.0 82 9 20 #> 144 13.0 238 12.6 64 9 21 #> 145 23.0 14 9.2 71 9 22 #> 146 36.0 139 10.3 81 9 23 #> 147 7.0 49 10.3 69 9 24 #> 148 14.0 20 16.6 63 9 25 #> 149 30.0 193 6.9 70 9 26 #> 150 31.5 145 13.2 77 9 27 #> 151 14.0 191 14.3 75 9 28 #> 152 18.0 131 8.0 76 9 29 #> 153 20.0 223 11.5 68 9 30
impute_median_at(airquality, .vars = vars(Ozone))
#> Ozone Solar.R Wind Temp Month Day #> 1 41.0 190 7.4 67 5 1 #> 2 36.0 118 8.0 72 5 2 #> 3 12.0 149 12.6 74 5 3 #> 4 18.0 313 11.5 62 5 4 #> 5 31.5 NA 14.3 56 5 5 #> 6 28.0 NA 14.9 66 5 6 #> 7 23.0 299 8.6 65 5 7 #> 8 19.0 99 13.8 59 5 8 #> 9 8.0 19 20.1 61 5 9 #> 10 31.5 194 8.6 69 5 10 #> 11 7.0 NA 6.9 74 5 11 #> 12 16.0 256 9.7 69 5 12 #> 13 11.0 290 9.2 66 5 13 #> 14 14.0 274 10.9 68 5 14 #> 15 18.0 65 13.2 58 5 15 #> 16 14.0 334 11.5 64 5 16 #> 17 34.0 307 12.0 66 5 17 #> 18 6.0 78 18.4 57 5 18 #> 19 30.0 322 11.5 68 5 19 #> 20 11.0 44 9.7 62 5 20 #> 21 1.0 8 9.7 59 5 21 #> 22 11.0 320 16.6 73 5 22 #> 23 4.0 25 9.7 61 5 23 #> 24 32.0 92 12.0 61 5 24 #> 25 31.5 66 16.6 57 5 25 #> 26 31.5 266 14.9 58 5 26 #> 27 31.5 NA 8.0 57 5 27 #> 28 23.0 13 12.0 67 5 28 #> 29 45.0 252 14.9 81 5 29 #> 30 115.0 223 5.7 79 5 30 #> 31 37.0 279 7.4 76 5 31 #> 32 31.5 286 8.6 78 6 1 #> 33 31.5 287 9.7 74 6 2 #> 34 31.5 242 16.1 67 6 3 #> 35 31.5 186 9.2 84 6 4 #> 36 31.5 220 8.6 85 6 5 #> 37 31.5 264 14.3 79 6 6 #> 38 29.0 127 9.7 82 6 7 #> 39 31.5 273 6.9 87 6 8 #> 40 71.0 291 13.8 90 6 9 #> 41 39.0 323 11.5 87 6 10 #> 42 31.5 259 10.9 93 6 11 #> 43 31.5 250 9.2 92 6 12 #> 44 23.0 148 8.0 82 6 13 #> 45 31.5 332 13.8 80 6 14 #> 46 31.5 322 11.5 79 6 15 #> 47 21.0 191 14.9 77 6 16 #> 48 37.0 284 20.7 72 6 17 #> 49 20.0 37 9.2 65 6 18 #> 50 12.0 120 11.5 73 6 19 #> 51 13.0 137 10.3 76 6 20 #> 52 31.5 150 6.3 77 6 21 #> 53 31.5 59 1.7 76 6 22 #> 54 31.5 91 4.6 76 6 23 #> 55 31.5 250 6.3 76 6 24 #> 56 31.5 135 8.0 75 6 25 #> 57 31.5 127 8.0 78 6 26 #> 58 31.5 47 10.3 73 6 27 #> 59 31.5 98 11.5 80 6 28 #> 60 31.5 31 14.9 77 6 29 #> 61 31.5 138 8.0 83 6 30 #> 62 135.0 269 4.1 84 7 1 #> 63 49.0 248 9.2 85 7 2 #> 64 32.0 236 9.2 81 7 3 #> 65 31.5 101 10.9 84 7 4 #> 66 64.0 175 4.6 83 7 5 #> 67 40.0 314 10.9 83 7 6 #> 68 77.0 276 5.1 88 7 7 #> 69 97.0 267 6.3 92 7 8 #> 70 97.0 272 5.7 92 7 9 #> 71 85.0 175 7.4 89 7 10 #> 72 31.5 139 8.6 82 7 11 #> 73 10.0 264 14.3 73 7 12 #> 74 27.0 175 14.9 81 7 13 #> 75 31.5 291 14.9 91 7 14 #> 76 7.0 48 14.3 80 7 15 #> 77 48.0 260 6.9 81 7 16 #> 78 35.0 274 10.3 82 7 17 #> 79 61.0 285 6.3 84 7 18 #> 80 79.0 187 5.1 87 7 19 #> 81 63.0 220 11.5 85 7 20 #> 82 16.0 7 6.9 74 7 21 #> 83 31.5 258 9.7 81 7 22 #> 84 31.5 295 11.5 82 7 23 #> 85 80.0 294 8.6 86 7 24 #> 86 108.0 223 8.0 85 7 25 #> 87 20.0 81 8.6 82 7 26 #> 88 52.0 82 12.0 86 7 27 #> 89 82.0 213 7.4 88 7 28 #> 90 50.0 275 7.4 86 7 29 #> 91 64.0 253 7.4 83 7 30 #> 92 59.0 254 9.2 81 7 31 #> 93 39.0 83 6.9 81 8 1 #> 94 9.0 24 13.8 81 8 2 #> 95 16.0 77 7.4 82 8 3 #> 96 78.0 NA 6.9 86 8 4 #> 97 35.0 NA 7.4 85 8 5 #> 98 66.0 NA 4.6 87 8 6 #> 99 122.0 255 4.0 89 8 7 #> 100 89.0 229 10.3 90 8 8 #> 101 110.0 207 8.0 90 8 9 #> 102 31.5 222 8.6 92 8 10 #> 103 31.5 137 11.5 86 8 11 #> 104 44.0 192 11.5 86 8 12 #> 105 28.0 273 11.5 82 8 13 #> 106 65.0 157 9.7 80 8 14 #> 107 31.5 64 11.5 79 8 15 #> 108 22.0 71 10.3 77 8 16 #> 109 59.0 51 6.3 79 8 17 #> 110 23.0 115 7.4 76 8 18 #> 111 31.0 244 10.9 78 8 19 #> 112 44.0 190 10.3 78 8 20 #> 113 21.0 259 15.5 77 8 21 #> 114 9.0 36 14.3 72 8 22 #> 115 31.5 255 12.6 75 8 23 #> 116 45.0 212 9.7 79 8 24 #> 117 168.0 238 3.4 81 8 25 #> 118 73.0 215 8.0 86 8 26 #> 119 31.5 153 5.7 88 8 27 #> 120 76.0 203 9.7 97 8 28 #> 121 118.0 225 2.3 94 8 29 #> 122 84.0 237 6.3 96 8 30 #> 123 85.0 188 6.3 94 8 31 #> 124 96.0 167 6.9 91 9 1 #> 125 78.0 197 5.1 92 9 2 #> 126 73.0 183 2.8 93 9 3 #> 127 91.0 189 4.6 93 9 4 #> 128 47.0 95 7.4 87 9 5 #> 129 32.0 92 15.5 84 9 6 #> 130 20.0 252 10.9 80 9 7 #> 131 23.0 220 10.3 78 9 8 #> 132 21.0 230 10.9 75 9 9 #> 133 24.0 259 9.7 73 9 10 #> 134 44.0 236 14.9 81 9 11 #> 135 21.0 259 15.5 76 9 12 #> 136 28.0 238 6.3 77 9 13 #> 137 9.0 24 10.9 71 9 14 #> 138 13.0 112 11.5 71 9 15 #> 139 46.0 237 6.9 78 9 16 #> 140 18.0 224 13.8 67 9 17 #> 141 13.0 27 10.3 76 9 18 #> 142 24.0 238 10.3 68 9 19 #> 143 16.0 201 8.0 82 9 20 #> 144 13.0 238 12.6 64 9 21 #> 145 23.0 14 9.2 71 9 22 #> 146 36.0 139 10.3 81 9 23 #> 147 7.0 49 10.3 69 9 24 #> 148 14.0 20 16.6 63 9 25 #> 149 30.0 193 6.9 70 9 26 #> 150 31.5 145 13.2 77 9 27 #> 151 14.0 191 14.3 75 9 28 #> 152 18.0 131 8.0 76 9 29 #> 153 20.0 223 11.5 68 9 30
impute_median_if(airquality, .predicate = is.numeric)
#> Ozone Solar.R Wind Temp Month Day #> 1 41.0 190 7.4 67 5 1 #> 2 36.0 118 8.0 72 5 2 #> 3 12.0 149 12.6 74 5 3 #> 4 18.0 313 11.5 62 5 4 #> 5 31.5 205 14.3 56 5 5 #> 6 28.0 205 14.9 66 5 6 #> 7 23.0 299 8.6 65 5 7 #> 8 19.0 99 13.8 59 5 8 #> 9 8.0 19 20.1 61 5 9 #> 10 31.5 194 8.6 69 5 10 #> 11 7.0 205 6.9 74 5 11 #> 12 16.0 256 9.7 69 5 12 #> 13 11.0 290 9.2 66 5 13 #> 14 14.0 274 10.9 68 5 14 #> 15 18.0 65 13.2 58 5 15 #> 16 14.0 334 11.5 64 5 16 #> 17 34.0 307 12.0 66 5 17 #> 18 6.0 78 18.4 57 5 18 #> 19 30.0 322 11.5 68 5 19 #> 20 11.0 44 9.7 62 5 20 #> 21 1.0 8 9.7 59 5 21 #> 22 11.0 320 16.6 73 5 22 #> 23 4.0 25 9.7 61 5 23 #> 24 32.0 92 12.0 61 5 24 #> 25 31.5 66 16.6 57 5 25 #> 26 31.5 266 14.9 58 5 26 #> 27 31.5 205 8.0 57 5 27 #> 28 23.0 13 12.0 67 5 28 #> 29 45.0 252 14.9 81 5 29 #> 30 115.0 223 5.7 79 5 30 #> 31 37.0 279 7.4 76 5 31 #> 32 31.5 286 8.6 78 6 1 #> 33 31.5 287 9.7 74 6 2 #> 34 31.5 242 16.1 67 6 3 #> 35 31.5 186 9.2 84 6 4 #> 36 31.5 220 8.6 85 6 5 #> 37 31.5 264 14.3 79 6 6 #> 38 29.0 127 9.7 82 6 7 #> 39 31.5 273 6.9 87 6 8 #> 40 71.0 291 13.8 90 6 9 #> 41 39.0 323 11.5 87 6 10 #> 42 31.5 259 10.9 93 6 11 #> 43 31.5 250 9.2 92 6 12 #> 44 23.0 148 8.0 82 6 13 #> 45 31.5 332 13.8 80 6 14 #> 46 31.5 322 11.5 79 6 15 #> 47 21.0 191 14.9 77 6 16 #> 48 37.0 284 20.7 72 6 17 #> 49 20.0 37 9.2 65 6 18 #> 50 12.0 120 11.5 73 6 19 #> 51 13.0 137 10.3 76 6 20 #> 52 31.5 150 6.3 77 6 21 #> 53 31.5 59 1.7 76 6 22 #> 54 31.5 91 4.6 76 6 23 #> 55 31.5 250 6.3 76 6 24 #> 56 31.5 135 8.0 75 6 25 #> 57 31.5 127 8.0 78 6 26 #> 58 31.5 47 10.3 73 6 27 #> 59 31.5 98 11.5 80 6 28 #> 60 31.5 31 14.9 77 6 29 #> 61 31.5 138 8.0 83 6 30 #> 62 135.0 269 4.1 84 7 1 #> 63 49.0 248 9.2 85 7 2 #> 64 32.0 236 9.2 81 7 3 #> 65 31.5 101 10.9 84 7 4 #> 66 64.0 175 4.6 83 7 5 #> 67 40.0 314 10.9 83 7 6 #> 68 77.0 276 5.1 88 7 7 #> 69 97.0 267 6.3 92 7 8 #> 70 97.0 272 5.7 92 7 9 #> 71 85.0 175 7.4 89 7 10 #> 72 31.5 139 8.6 82 7 11 #> 73 10.0 264 14.3 73 7 12 #> 74 27.0 175 14.9 81 7 13 #> 75 31.5 291 14.9 91 7 14 #> 76 7.0 48 14.3 80 7 15 #> 77 48.0 260 6.9 81 7 16 #> 78 35.0 274 10.3 82 7 17 #> 79 61.0 285 6.3 84 7 18 #> 80 79.0 187 5.1 87 7 19 #> 81 63.0 220 11.5 85 7 20 #> 82 16.0 7 6.9 74 7 21 #> 83 31.5 258 9.7 81 7 22 #> 84 31.5 295 11.5 82 7 23 #> 85 80.0 294 8.6 86 7 24 #> 86 108.0 223 8.0 85 7 25 #> 87 20.0 81 8.6 82 7 26 #> 88 52.0 82 12.0 86 7 27 #> 89 82.0 213 7.4 88 7 28 #> 90 50.0 275 7.4 86 7 29 #> 91 64.0 253 7.4 83 7 30 #> 92 59.0 254 9.2 81 7 31 #> 93 39.0 83 6.9 81 8 1 #> 94 9.0 24 13.8 81 8 2 #> 95 16.0 77 7.4 82 8 3 #> 96 78.0 205 6.9 86 8 4 #> 97 35.0 205 7.4 85 8 5 #> 98 66.0 205 4.6 87 8 6 #> 99 122.0 255 4.0 89 8 7 #> 100 89.0 229 10.3 90 8 8 #> 101 110.0 207 8.0 90 8 9 #> 102 31.5 222 8.6 92 8 10 #> 103 31.5 137 11.5 86 8 11 #> 104 44.0 192 11.5 86 8 12 #> 105 28.0 273 11.5 82 8 13 #> 106 65.0 157 9.7 80 8 14 #> 107 31.5 64 11.5 79 8 15 #> 108 22.0 71 10.3 77 8 16 #> 109 59.0 51 6.3 79 8 17 #> 110 23.0 115 7.4 76 8 18 #> 111 31.0 244 10.9 78 8 19 #> 112 44.0 190 10.3 78 8 20 #> 113 21.0 259 15.5 77 8 21 #> 114 9.0 36 14.3 72 8 22 #> 115 31.5 255 12.6 75 8 23 #> 116 45.0 212 9.7 79 8 24 #> 117 168.0 238 3.4 81 8 25 #> 118 73.0 215 8.0 86 8 26 #> 119 31.5 153 5.7 88 8 27 #> 120 76.0 203 9.7 97 8 28 #> 121 118.0 225 2.3 94 8 29 #> 122 84.0 237 6.3 96 8 30 #> 123 85.0 188 6.3 94 8 31 #> 124 96.0 167 6.9 91 9 1 #> 125 78.0 197 5.1 92 9 2 #> 126 73.0 183 2.8 93 9 3 #> 127 91.0 189 4.6 93 9 4 #> 128 47.0 95 7.4 87 9 5 #> 129 32.0 92 15.5 84 9 6 #> 130 20.0 252 10.9 80 9 7 #> 131 23.0 220 10.3 78 9 8 #> 132 21.0 230 10.9 75 9 9 #> 133 24.0 259 9.7 73 9 10 #> 134 44.0 236 14.9 81 9 11 #> 135 21.0 259 15.5 76 9 12 #> 136 28.0 238 6.3 77 9 13 #> 137 9.0 24 10.9 71 9 14 #> 138 13.0 112 11.5 71 9 15 #> 139 46.0 237 6.9 78 9 16 #> 140 18.0 224 13.8 67 9 17 #> 141 13.0 27 10.3 76 9 18 #> 142 24.0 238 10.3 68 9 19 #> 143 16.0 201 8.0 82 9 20 #> 144 13.0 238 12.6 64 9 21 #> 145 23.0 14 9.2 71 9 22 #> 146 36.0 139 10.3 81 9 23 #> 147 7.0 49 10.3 69 9 24 #> 148 14.0 20 16.6 63 9 25 #> 149 30.0 193 6.9 70 9 26 #> 150 31.5 145 13.2 77 9 27 #> 151 14.0 191 14.3 75 9 28 #> 152 18.0 131 8.0 76 9 29 #> 153 20.0 223 11.5 68 9 30
# NOT RUN { library(ggplot2) airquality %>% bind_shadow() %>% impute_median_all() %>% add_label_shadow() %>% ggplot(aes(x = Ozone, y = Solar.R, colour = any_missing)) + geom_point() # }