# Counting filtered rows inline

#1

Hi - does anyone know if there's a way to apply a count function to a filter function on the fly?

For example - instead of this:

``````mtcars %>%
filter(cyl==6) %>%
nrow()
``````

is something like this possible:

``````mtcars %>%
nrow(filter(cyl==6))
``````

The reason I'm asking is because I want to use this in mutate to add a column that returns a count of the number of filtered rows i.e. let's say add a column called "num_six_cyl" where the count of six cylinder cars repeats for each row.

If anyone knows DAX, this would be the equivalent of a CALCULATE function where you could put 'cyl = 6' in the filters section of the formula.

#2

Hey there -- I'm not totally sure what your expected output is, but will this achieve what you want?

``````library(dplyr)
mtcars %>%
mutate(num_six_cyl = length(cyl[cyl == 6]))
#>     mpg cyl  disp  hp drat    wt  qsec vs am gear carb num_six_cyl
#> 1  21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4           7
#> 2  21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4           7
#> 3  22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1           7
#> 4  21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1           7
#> 5  18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2           7
#> 6  18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1           7
#> 7  14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4           7
#> 8  24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2           7
#> 9  22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2           7
#> 10 19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4           7
#> 11 17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4           7
#> 12 16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3           7
#> 13 17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3           7
#> 14 15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3           7
#> 15 10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4           7
#> 16 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4           7
#> 17 14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4           7
#> 18 32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1           7
#> 19 30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2           7
#> 20 33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1           7
#> 21 21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1           7
#> 22 15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2           7
#> 23 15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2           7
#> 24 13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4           7
#> 25 19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2           7
#> 26 27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1           7
#> 27 26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2           7
#> 28 30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2           7
#> 29 15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4           7
#> 30 19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6           7
#> 31 15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8           7
#> 32 21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2           7
``````

Instead of `filter()`, which expects a data frame as input, you can use the base subset operator, `[]`, on the `cyl` column for the conditions you want within the `mutate()` call, and then the length of that vector will be the number of rows that meet the given condition (`cyl == 6`).

#3

It is a variant of @mfherman answer. in R, logical values are converted to 0 and 1 if needed. You can then sum a logical vector to count the number of `TRUE` values.

``````library(dplyr, warn.conflicts = F)

mtcars %>%
mutate(num_six_cyl = sum(cyl == 6))
#>     mpg cyl  disp  hp drat    wt  qsec vs am gear carb num_six_cyl
#> 1  21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4           7
#> 2  21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4           7
#> 3  22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1           7
#> 4  21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1           7
#> 5  18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2           7
#> 6  18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1           7
#> 7  14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4           7
#> 8  24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2           7
#> 9  22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2           7
#> 10 19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4           7
#> 11 17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4           7
#> 12 16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3           7
#> 13 17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3           7
#> 14 15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3           7
#> 15 10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4           7
#> 16 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4           7
#> 17 14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4           7
#> 18 32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1           7
#> 19 30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2           7
#> 20 33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1           7
#> 21 21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1           7
#> 22 15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2           7
#> 23 15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2           7
#> 24 13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4           7
#> 25 19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2           7
#> 26 27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1           7
#> 27 26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2           7
#> 28 30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2           7
#> 29 15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4           7
#> 30 19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6           7
#> 31 15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8           7
#> 32 21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2           7
``````

Created on 2018-01-01 by the reprex package (v0.1.1.9000).

#4

Thank you both so much for your prompt replies, this is exactly what I was looking to do.