Filter rows via integer/numeric position or logical vector
filter_data(.data, ...)
| .data | Data frame or two dimensional array |
|---|---|
| ... | Each argument/expression should should evaluate and reduce down to
an integer (row number) or logical vector. The filter will keep all row
numbers that appear in all evaluated expressions (commas are the equivalent
to |
Sliced/filtered data frame
set.seed(12) d <- data.frame( mpg = rnorm(100, 25, 3), gear = sample(3:6, 100, replace = TRUE), vs = sample(0:1, 100, replace = TRUE), stringsAsFactors = FALSE ) filter_data(d, mpg > 30)#> mpg gear vs #> 1 31.02160 3 0 #> 2 31.21611 3 1 #> 3 31.06100 3 0 #> 4 30.86232 6 0filter_data(d, !mpg < 30)#> mpg gear vs #> 1 31.02160 3 0 #> 2 31.21611 3 1 #> 3 31.06100 3 0 #> 4 30.86232 6 0filter_data(d, mpg > 30, !mpg < 30)#> mpg gear vs #> 1 31.02160 3 0 #> 2 31.21611 3 1 #> 3 31.06100 3 0 #> 4 30.86232 6 0filter_data(d, mpg > 30, gear == 4)#> mpg gear vs #> 1 20.55830 6 1 #> 2 29.73151 3 1 #> 3 22.12977 5 1 #> 4 22.23998 6 1 #> 5 19.00707 6 0 #> 6 24.18311 5 1 #> 7 24.05395 4 0 #> 8 23.11523 3 1 #> 9 24.68061 5 1 #> 10 26.28404 4 1 #> 11 22.66684 6 1 #> 12 21.11835 3 1 #> 13 22.66130 4 1 #> 14 25.03586 5 0 #> 15 24.54275 5 0 #> 16 22.88961 5 0 #> 17 28.56664 3 1 #> 18 26.02154 4 1 #> 19 26.52090 6 1 #> 20 24.12008 3 1 #> 21 25.67092 5 0 #> 22 31.02160 3 0 #> 23 28.03594 4 1 #> 24 24.09262 5 0 #> 25 21.92427 4 0 #> 26 24.19785 3 0 #> 27 24.40268 6 1 #> 28 25.39337 5 1 #> 29 25.43740 3 0 #> 30 26.08619 5 0 #> 31 27.02194 3 0 #> 32 31.21611 3 1 #> 33 23.37691 4 0 #> 34 21.78852 4 1 #> 35 23.88263 4 1 #> 36 23.54458 4 0 #> 37 25.82435 5 0 #> 38 23.56146 4 1 #> 39 27.39432 6 1 #> 40 21.98665 6 1 #> 41 25.31495 4 0 #> 42 21.53202 3 0 #> 43 26.73440 6 0 #> 44 20.21312 4 0 #> 45 24.07449 5 0 #> 46 26.34840 5 0 #> 47 22.06884 3 0 #> 48 25.56999 6 1 #> 49 27.19436 3 1 #> 50 23.52220 5 1 #> 51 24.87195 6 1 #> 52 24.66199 3 0 #> 53 26.37048 4 0 #> 54 31.06100 3 0 #> 55 21.84733 6 1 #> 56 27.20396 6 0 #> 57 26.61775 3 1 #> 58 21.05718 6 0 #> 59 24.24988 4 0 #> 60 25.94261 3 0 #> 61 26.21964 6 0 #> 62 27.98326 4 0 #> 63 27.56731 5 0 #> 64 25.59139 4 0 #> 65 27.50298 3 0 #> 66 27.54037 3 1 #> 67 30.86232 6 0 #> 68 18.55222 6 0 #> 69 27.91336 4 0 #> 70 28.43518 6 1 #> 71 23.42380 6 0 #> 72 25.75096 3 0 #> 73 23.71178 5 0 #> 74 24.45244 5 1 #> 75 24.69007 6 1 #> 76 23.09849 5 0 #> 77 21.18684 3 1 #> 78 23.84815 5 1 #> 79 26.55027 5 1 #> 80 24.46609 3 1 #> 81 25.01277 6 1 #> 82 21.17782 3 0 #> 83 24.39367 3 0 #> 84 28.49340 4 0 #> 85 24.92986 6 1 #> 86 27.69147 3 1 #> 87 24.46983 6 1 #> 88 28.34113 3 0 #> 89 23.37433 3 1 #> 90 22.10981 6 1 #> 91 26.12935 3 1 #> 92 22.04598 6 0 #> 93 27.69268 3 1 #> 94 25.38779 6 0 #> 95 28.10111 5 1 #> 96 23.97313 4 0 #> 97 26.35684 3 0 #> 98 22.91579 5 0 #> 99 24.28296 3 0 #> 100 21.97810 6 1filter_data(d, mpg > 30 | gear == 4, vs == 1)#> mpg gear vs #> 1 26.28404 4 1 #> 2 22.66130 4 1 #> 3 26.02154 4 1 #> 4 28.03594 4 1 #> 5 31.21611 3 1 #> 6 21.78852 4 1 #> 7 23.88263 4 1 #> 8 23.56146 4 1