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84 lines
3.8 KiB
Markdown
84 lines
3.8 KiB
Markdown
# Drop unused levels preserving label data
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This extends \[forcats::fct_drop()\] to natively work across a
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data.frame and replaces \[base::droplevels()\].
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## Usage
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``` r
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fct_drop(x, ...)
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# S3 method for class 'data.frame'
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fct_drop(x, ...)
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# S3 method for class 'factor'
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fct_drop(x, ...)
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```
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## Arguments
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- x:
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Factor to drop unused levels
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- ...:
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Other arguments passed down to method.
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## Examples
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``` r
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mtcars |>
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numchar2fct() |>
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fct_drop()
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#> # A tibble: 32 × 11
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#> mpg cyl disp hp drat wt qsec vs am gear carb
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#> <dbl> <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <fct> <fct> <fct> <fct>
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#> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4
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#> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4
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#> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
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#> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1
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#> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2
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#> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1
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#> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4
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#> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2
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#> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2
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#> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4
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#> # ℹ 22 more rows
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mtcars |>
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numchar2fct() |>
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dplyr::mutate(vs = fct_drop(vs))
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#> mpg cyl disp hp drat wt qsec vs am gear carb
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#> Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
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#> Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
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#> Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
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#> Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
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#> Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2
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#> Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
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#> Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4
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#> Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
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#> Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
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#> Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
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#> Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
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#> Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3
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#> Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3
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#> Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3
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#> Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4
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#> Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4
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#> Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4
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#> Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
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#> Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
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#> Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
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#> Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1
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#> Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2
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#> AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2
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#> Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4
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#> Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2
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#> Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
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#> Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
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#> Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
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#> Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4
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#> Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
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#> Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8
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#> Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2
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```
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