Return the middle x percent of values
near_middle(x, middle, within)
x | numeric vector |
---|---|
middle | percentage you want to center around |
within | percentage around center |
logical vector
#> [1] FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE TRUE #> [13] TRUE FALSE FALSE FALSE FALSE TRUE FALSE FALSElibrary(dplyr) heights %>% features(height_cm, list(min = min)) %>% filter(near_middle(min, 0.5, 0.1))#> # A tibble: 14 x 2 #> country min #> <chr> <dbl> #> 1 Brazil 164. #> 2 Cameroon 164. #> 3 Estonia 165. #> 4 Gabon 164. #> 5 Ghana 164. #> 6 Guinea 164. #> 7 Kenya 165. #> 8 Kyrgyzstan 164. #> 9 Latvia 165. #> 10 Lithuania 165. #> 11 Netherlands 164. #> 12 Switzerland 165. #> 13 Tajikistan 165. #> 14 Uganda 165.