"%ni%" is a convenience shortcut for the negation of the match function (i.e. the %in%" operator).
x %ni% ythe values to be negatively matched.
the values to be negatively matched against.
A logical vector of the same length as x which is FALSE for matching values of y and TRUE for non-matching values of y.
c(1:100) %ni% c(2, 3, 5, 10, 78:91)
#> [1] TRUE FALSE FALSE TRUE FALSE TRUE TRUE TRUE TRUE FALSE TRUE TRUE
#> [13] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
#> [25] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
#> [37] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
#> [49] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
#> [61] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
#> [73] TRUE TRUE TRUE TRUE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
#> [85] FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE TRUE
#> [97] TRUE TRUE TRUE TRUE
#subset data to extract rows with matching values using "%in%"
subset(pdata, g %in% c("a", "e"))
#> # A tibble: 4,944 × 10
#> id d g high_low even y1 y2 x1 x2 x3
#> <int> <date> <fct> <chr> <lgl> <dbl> <dbl> <int> <int> <int>
#> 1 1 2008-01-01 e high FALSE 106. 118. 59 116 248
#> 2 5 2008-01-01 a high FALSE 99.7 113. 96 196 284
#> 3 6 2008-01-01 a high TRUE 102. 114. 19 163 206
#> 4 9 2008-01-01 e low FALSE 99.8 89.8 92 106 277
#> 5 11 2008-01-01 a high FALSE 93.8 102. 56 142 285
#> 6 12 2008-01-01 a low TRUE 96.5 92.4 100 111 277
#> 7 13 2008-01-01 a low FALSE 86.6 86.0 69 119 228
#> 8 14 2008-01-01 a high TRUE 86.5 105. 44 182 290
#> 9 15 2008-01-01 a high FALSE 99.6 101. 91 124 294
#> 10 19 2008-01-01 a high FALSE 99.6 108. 3 139 275
#> # … with 4,934 more rows
#subset data to extract rows with non-matching values using "%ni%"
subset(pdata, g %ni% c("a", "e"))
#> # A tibble: 7,056 × 10
#> id d g high_low even y1 y2 x1 x2 x3
#> <int> <date> <fct> <chr> <lgl> <dbl> <dbl> <int> <int> <int>
#> 1 2 2008-01-01 c high TRUE 96.5 107. 5 101 238
#> 2 3 2008-01-01 d low FALSE 99.3 96.2 71 111 250
#> 3 4 2008-01-01 c high TRUE 109. 102. 60 130 287
#> 4 7 2008-01-01 d low FALSE 91.0 87.9 77 133 201
#> 5 8 2008-01-01 b low TRUE 109. 98.7 74 191 249
#> 6 10 2008-01-01 c low TRUE 122. 83.6 4 134 209
#> 7 16 2008-01-01 b low TRUE 112. 99.8 35 179 295
#> 8 17 2008-01-01 c low FALSE 91.1 88.1 27 111 218
#> 9 18 2008-01-01 b low TRUE 103. 86.2 27 187 210
#> 10 20 2008-01-01 c low TRUE 109. 82.7 71 146 267
#> # … with 7,046 more rows
#equivalent to subset function for tidyverse users
dplyr::filter(pdata, g %ni% c("a", "e"))
#> # A tibble: 7,056 × 10
#> id d g high_low even y1 y2 x1 x2 x3
#> <int> <date> <fct> <chr> <lgl> <dbl> <dbl> <int> <int> <int>
#> 1 2 2008-01-01 c high TRUE 96.5 107. 5 101 238
#> 2 3 2008-01-01 d low FALSE 99.3 96.2 71 111 250
#> 3 4 2008-01-01 c high TRUE 109. 102. 60 130 287
#> 4 7 2008-01-01 d low FALSE 91.0 87.9 77 133 201
#> 5 8 2008-01-01 b low TRUE 109. 98.7 74 191 249
#> 6 10 2008-01-01 c low TRUE 122. 83.6 4 134 209
#> 7 16 2008-01-01 b low TRUE 112. 99.8 35 179 295
#> 8 17 2008-01-01 c low FALSE 91.1 88.1 27 111 218
#> 9 18 2008-01-01 b low TRUE 103. 86.2 27 187 210
#> 10 20 2008-01-01 c low TRUE 109. 82.7 71 146 267
#> # … with 7,046 more rows