Slice does not work with relational databases because they have no
intrinsic notion of row order. If you want to perform the equivalent
operation, use filter()
and row_number()
.
slice(.data, ...)
.data | A tbl. |
---|---|
... | Integer row values. These arguments are automatically quoted and
evaluated in the context of the data
frame. They support unquoting and
splicing. See |
Positive values select rows to keep; negative values drop rows. The values provided must be either all positive or all negative.
When applied to a data frame, row names are silently dropped. To preserve,
convert to an explicit variable with tibble::rownames_to_column()
.
slice(mtcars, 1L)#> mpg cyl disp hp drat wt qsec vs am gear carb #> 1 21 6 160 110 3.9 2.62 16.46 0 1 4 4#> mpg cyl disp hp drat wt qsec vs am gear carb #> 1 21.4 4 121 109 4.11 2.78 18.6 1 1 4 2#> mpg cyl disp hp drat wt qsec vs am gear carb #> 1 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 #> 2 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 #> 3 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 #> 4 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 #> 5 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 #> 6 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 #> 7 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 #> 8 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3 #> 9 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3 #> 10 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3 #> 11 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4 #> 12 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4 #> 13 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4 #> 14 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1 #> 15 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2 #> 16 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1 #> 17 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1 #> 18 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 #> 19 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 #> 20 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4 #> 21 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 #> 22 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1 #> 23 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2 #> 24 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2 #> 25 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4 #> 26 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6 #> 27 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8 #> 28 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2#> mpg cyl disp hp drat wt qsec vs am gear carb #> 1 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4 #> 2 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4 #> 3 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1 #> 4 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1# In this case, the result will be equivalent to: slice(mtcars, 1:4)#> mpg cyl disp hp drat wt qsec vs am gear carb #> 1 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4 #> 2 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4 #> 3 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1 #> 4 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1#> # A tibble: 6 x 11 #> # Groups: cyl [3] #> mpg cyl disp hp drat wt qsec vs am gear carb #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 #> 2 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 #> 3 21 6 160 110 3.9 2.62 16.5 0 1 4 4 #> 4 21 6 160 110 3.9 2.88 17.0 0 1 4 4 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 6 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4# Equivalent code using filter that will also work with databases, # but won't be as fast for in-memory data. For many databases, you'll # need to supply an explicit variable to use to compute the row number. filter(mtcars, row_number() == 1L)#> mpg cyl disp hp drat wt qsec vs am gear carb #> 1 21 6 160 110 3.9 2.62 16.46 0 1 4 4#> mpg cyl disp hp drat wt qsec vs am gear carb #> 1 21.4 4 121 109 4.11 2.78 18.6 1 1 4 2#> mpg cyl disp hp drat wt qsec vs am gear carb #> 1 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 #> 2 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 #> 3 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 #> 4 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 #> 5 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 #> 6 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 #> 7 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 #> 8 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3 #> 9 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3 #> 10 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3 #> 11 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4 #> 12 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4 #> 13 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4 #> 14 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1 #> 15 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2 #> 16 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1 #> 17 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1 #> 18 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 #> 19 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 #> 20 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4 #> 21 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 #> 22 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1 #> 23 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2 #> 24 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2 #> 25 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4 #> 26 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6 #> 27 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8 #> 28 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2