Count from n to N
count_functions.Rd![[Stable]](figures/lifecycle-stable.svg)
Arguments
- ...
-
Columns to pick.
You can't pick grouping columns because they are already automatically handled by the verb (i.e.
summarise()ormutate()).
Details
These functions are used for indexing observations or generating sequences of numbers.
n_()generates a running counter within a group of variables and represents the number of the current observation.N_()provides the total count within each group of variables.
You can do these operations using dplyr::n() in this way.
See examples below using iris dataset.
iris |> mutate(.N_ = n()) |> head() iris |> mutate(.n_ = 1:n()) |> head() iris |> group_by(Species) |> mutate(.n_ = 1:n()) |> slice(1:5) |> ungroup()
See also
Other Data Management:
append(),
codebook(),
cut(),
tag_duplicates()
Examples
# Example with a custom dataset
df <- data.frame(
x = c(1, 1, 2, 2, 2, 3, 4, 4, 4, 4),
y = letters[1:10]
)
library(dplyr)
#>
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#>
#> filter, lag
#> The following objects are masked from ‘package:base’:
#>
#> intersect, setdiff, setequal, union
# Generate a running counter for each observation within the "x" group using mutate()
mutate(df, n = n_(x))
#> x y n
#> 1 1 a 1
#> 2 1 b 2
#> 3 2 c 1
#> 4 2 d 2
#> 5 2 e 3
#> 6 3 f 1
#> 7 4 g 1
#> 8 4 h 2
#> 9 4 i 3
#> 10 4 j 4
# Generate a running counter for each observation for all columns using mutate()
mutate(df, n = n_(everything()))
#> x y n
#> 1 1 a 1
#> 2 1 b 1
#> 3 2 c 1
#> 4 2 d 1
#> 5 2 e 1
#> 6 3 f 1
#> 7 4 g 1
#> 8 4 h 1
#> 9 4 i 1
#> 10 4 j 1
# Generate the total count of observations using summarise()
reframe(df, n = n_(x))
#> n
#> 1 1
#> 2 2
#> 3 1
#> 4 2
#> 5 3
#> 6 1
#> 7 1
#> 8 2
#> 9 3
#> 10 4
# Generate the total count of observations within the "x" group using summarise()
mutate(df, N = N_(everything()))
#> x y N
#> 1 1 a 1
#> 2 1 b 1
#> 3 2 c 1
#> 4 2 d 1
#> 5 2 e 1
#> 6 3 f 1
#> 7 4 g 1
#> 8 4 h 1
#> 9 4 i 1
#> 10 4 j 1
mutate(df, N = N_(x))
#> x y N
#> 1 1 a 2
#> 2 1 b 2
#> 3 2 c 3
#> 4 2 d 3
#> 5 2 e 3
#> 6 3 f 1
#> 7 4 g 4
#> 8 4 h 4
#> 9 4 i 4
#> 10 4 j 4
reframe(df, N = N_(x))
#> N
#> 1 2
#> 2 2
#> 3 3
#> 4 3
#> 5 3
#> 6 1
#> 7 4
#> 8 4
#> 9 4
#> 10 4
# iris dataset
mutate(iris, n = n_(everything()))
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species n
#> 1 5.1 3.5 1.4 0.2 setosa 1
#> 2 4.9 3.0 1.4 0.2 setosa 1
#> 3 4.7 3.2 1.3 0.2 setosa 1
#> 4 4.6 3.1 1.5 0.2 setosa 1
#> 5 5.0 3.6 1.4 0.2 setosa 1
#> 6 5.4 3.9 1.7 0.4 setosa 1
#> 7 4.6 3.4 1.4 0.3 setosa 1
#> 8 5.0 3.4 1.5 0.2 setosa 1
#> 9 4.4 2.9 1.4 0.2 setosa 1
#> 10 4.9 3.1 1.5 0.1 setosa 1
#> 11 5.4 3.7 1.5 0.2 setosa 1
#> 12 4.8 3.4 1.6 0.2 setosa 1
#> 13 4.8 3.0 1.4 0.1 setosa 1
#> 14 4.3 3.0 1.1 0.1 setosa 1
#> 15 5.8 4.0 1.2 0.2 setosa 1
#> 16 5.7 4.4 1.5 0.4 setosa 1
#> 17 5.4 3.9 1.3 0.4 setosa 1
#> 18 5.1 3.5 1.4 0.3 setosa 1
#> 19 5.7 3.8 1.7 0.3 setosa 1
#> 20 5.1 3.8 1.5 0.3 setosa 1
#> 21 5.4 3.4 1.7 0.2 setosa 1
#> 22 5.1 3.7 1.5 0.4 setosa 1
#> 23 4.6 3.6 1.0 0.2 setosa 1
#> 24 5.1 3.3 1.7 0.5 setosa 1
#> 25 4.8 3.4 1.9 0.2 setosa 1
#> 26 5.0 3.0 1.6 0.2 setosa 1
#> 27 5.0 3.4 1.6 0.4 setosa 1
#> 28 5.2 3.5 1.5 0.2 setosa 1
#> 29 5.2 3.4 1.4 0.2 setosa 1
#> 30 4.7 3.2 1.6 0.2 setosa 1
#> 31 4.8 3.1 1.6 0.2 setosa 1
#> 32 5.4 3.4 1.5 0.4 setosa 1
#> 33 5.2 4.1 1.5 0.1 setosa 1
#> 34 5.5 4.2 1.4 0.2 setosa 1
#> 35 4.9 3.1 1.5 0.2 setosa 1
#> 36 5.0 3.2 1.2 0.2 setosa 1
#> 37 5.5 3.5 1.3 0.2 setosa 1
#> 38 4.9 3.6 1.4 0.1 setosa 1
#> 39 4.4 3.0 1.3 0.2 setosa 1
#> 40 5.1 3.4 1.5 0.2 setosa 1
#> 41 5.0 3.5 1.3 0.3 setosa 1
#> 42 4.5 2.3 1.3 0.3 setosa 1
#> 43 4.4 3.2 1.3 0.2 setosa 1
#> 44 5.0 3.5 1.6 0.6 setosa 1
#> 45 5.1 3.8 1.9 0.4 setosa 1
#> 46 4.8 3.0 1.4 0.3 setosa 1
#> 47 5.1 3.8 1.6 0.2 setosa 1
#> 48 4.6 3.2 1.4 0.2 setosa 1
#> 49 5.3 3.7 1.5 0.2 setosa 1
#> 50 5.0 3.3 1.4 0.2 setosa 1
#> 51 7.0 3.2 4.7 1.4 versicolor 1
#> 52 6.4 3.2 4.5 1.5 versicolor 1
#> 53 6.9 3.1 4.9 1.5 versicolor 1
#> 54 5.5 2.3 4.0 1.3 versicolor 1
#> 55 6.5 2.8 4.6 1.5 versicolor 1
#> 56 5.7 2.8 4.5 1.3 versicolor 1
#> 57 6.3 3.3 4.7 1.6 versicolor 1
#> 58 4.9 2.4 3.3 1.0 versicolor 1
#> 59 6.6 2.9 4.6 1.3 versicolor 1
#> 60 5.2 2.7 3.9 1.4 versicolor 1
#> 61 5.0 2.0 3.5 1.0 versicolor 1
#> 62 5.9 3.0 4.2 1.5 versicolor 1
#> 63 6.0 2.2 4.0 1.0 versicolor 1
#> 64 6.1 2.9 4.7 1.4 versicolor 1
#> 65 5.6 2.9 3.6 1.3 versicolor 1
#> 66 6.7 3.1 4.4 1.4 versicolor 1
#> 67 5.6 3.0 4.5 1.5 versicolor 1
#> 68 5.8 2.7 4.1 1.0 versicolor 1
#> 69 6.2 2.2 4.5 1.5 versicolor 1
#> 70 5.6 2.5 3.9 1.1 versicolor 1
#> 71 5.9 3.2 4.8 1.8 versicolor 1
#> 72 6.1 2.8 4.0 1.3 versicolor 1
#> 73 6.3 2.5 4.9 1.5 versicolor 1
#> 74 6.1 2.8 4.7 1.2 versicolor 1
#> 75 6.4 2.9 4.3 1.3 versicolor 1
#> 76 6.6 3.0 4.4 1.4 versicolor 1
#> 77 6.8 2.8 4.8 1.4 versicolor 1
#> 78 6.7 3.0 5.0 1.7 versicolor 1
#> 79 6.0 2.9 4.5 1.5 versicolor 1
#> 80 5.7 2.6 3.5 1.0 versicolor 1
#> 81 5.5 2.4 3.8 1.1 versicolor 1
#> 82 5.5 2.4 3.7 1.0 versicolor 1
#> 83 5.8 2.7 3.9 1.2 versicolor 1
#> 84 6.0 2.7 5.1 1.6 versicolor 1
#> 85 5.4 3.0 4.5 1.5 versicolor 1
#> 86 6.0 3.4 4.5 1.6 versicolor 1
#> 87 6.7 3.1 4.7 1.5 versicolor 1
#> 88 6.3 2.3 4.4 1.3 versicolor 1
#> 89 5.6 3.0 4.1 1.3 versicolor 1
#> 90 5.5 2.5 4.0 1.3 versicolor 1
#> 91 5.5 2.6 4.4 1.2 versicolor 1
#> 92 6.1 3.0 4.6 1.4 versicolor 1
#> 93 5.8 2.6 4.0 1.2 versicolor 1
#> 94 5.0 2.3 3.3 1.0 versicolor 1
#> 95 5.6 2.7 4.2 1.3 versicolor 1
#> 96 5.7 3.0 4.2 1.2 versicolor 1
#> 97 5.7 2.9 4.2 1.3 versicolor 1
#> 98 6.2 2.9 4.3 1.3 versicolor 1
#> 99 5.1 2.5 3.0 1.1 versicolor 1
#> 100 5.7 2.8 4.1 1.3 versicolor 1
#> 101 6.3 3.3 6.0 2.5 virginica 1
#> 102 5.8 2.7 5.1 1.9 virginica 1
#> 103 7.1 3.0 5.9 2.1 virginica 1
#> 104 6.3 2.9 5.6 1.8 virginica 1
#> 105 6.5 3.0 5.8 2.2 virginica 1
#> 106 7.6 3.0 6.6 2.1 virginica 1
#> 107 4.9 2.5 4.5 1.7 virginica 1
#> 108 7.3 2.9 6.3 1.8 virginica 1
#> 109 6.7 2.5 5.8 1.8 virginica 1
#> 110 7.2 3.6 6.1 2.5 virginica 1
#> 111 6.5 3.2 5.1 2.0 virginica 1
#> 112 6.4 2.7 5.3 1.9 virginica 1
#> 113 6.8 3.0 5.5 2.1 virginica 1
#> 114 5.7 2.5 5.0 2.0 virginica 1
#> 115 5.8 2.8 5.1 2.4 virginica 1
#> 116 6.4 3.2 5.3 2.3 virginica 1
#> 117 6.5 3.0 5.5 1.8 virginica 1
#> 118 7.7 3.8 6.7 2.2 virginica 1
#> 119 7.7 2.6 6.9 2.3 virginica 1
#> 120 6.0 2.2 5.0 1.5 virginica 1
#> 121 6.9 3.2 5.7 2.3 virginica 1
#> 122 5.6 2.8 4.9 2.0 virginica 1
#> 123 7.7 2.8 6.7 2.0 virginica 1
#> 124 6.3 2.7 4.9 1.8 virginica 1
#> 125 6.7 3.3 5.7 2.1 virginica 1
#> 126 7.2 3.2 6.0 1.8 virginica 1
#> 127 6.2 2.8 4.8 1.8 virginica 1
#> 128 6.1 3.0 4.9 1.8 virginica 1
#> 129 6.4 2.8 5.6 2.1 virginica 1
#> 130 7.2 3.0 5.8 1.6 virginica 1
#> 131 7.4 2.8 6.1 1.9 virginica 1
#> 132 7.9 3.8 6.4 2.0 virginica 1
#> 133 6.4 2.8 5.6 2.2 virginica 1
#> 134 6.3 2.8 5.1 1.5 virginica 1
#> 135 6.1 2.6 5.6 1.4 virginica 1
#> 136 7.7 3.0 6.1 2.3 virginica 1
#> 137 6.3 3.4 5.6 2.4 virginica 1
#> 138 6.4 3.1 5.5 1.8 virginica 1
#> 139 6.0 3.0 4.8 1.8 virginica 1
#> 140 6.9 3.1 5.4 2.1 virginica 1
#> 141 6.7 3.1 5.6 2.4 virginica 1
#> 142 6.9 3.1 5.1 2.3 virginica 1
#> 143 5.8 2.7 5.1 1.9 virginica 2
#> 144 6.8 3.2 5.9 2.3 virginica 1
#> 145 6.7 3.3 5.7 2.5 virginica 1
#> 146 6.7 3.0 5.2 2.3 virginica 1
#> 147 6.3 2.5 5.0 1.9 virginica 1
#> 148 6.5 3.0 5.2 2.0 virginica 1
#> 149 6.2 3.4 5.4 2.3 virginica 1
#> 150 5.9 3.0 5.1 1.8 virginica 1
mutate(iris, N = N_(everything()))
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species N
#> 1 5.1 3.5 1.4 0.2 setosa 1
#> 2 4.9 3.0 1.4 0.2 setosa 1
#> 3 4.7 3.2 1.3 0.2 setosa 1
#> 4 4.6 3.1 1.5 0.2 setosa 1
#> 5 5.0 3.6 1.4 0.2 setosa 1
#> 6 5.4 3.9 1.7 0.4 setosa 1
#> 7 4.6 3.4 1.4 0.3 setosa 1
#> 8 5.0 3.4 1.5 0.2 setosa 1
#> 9 4.4 2.9 1.4 0.2 setosa 1
#> 10 4.9 3.1 1.5 0.1 setosa 1
#> 11 5.4 3.7 1.5 0.2 setosa 1
#> 12 4.8 3.4 1.6 0.2 setosa 1
#> 13 4.8 3.0 1.4 0.1 setosa 1
#> 14 4.3 3.0 1.1 0.1 setosa 1
#> 15 5.8 4.0 1.2 0.2 setosa 1
#> 16 5.7 4.4 1.5 0.4 setosa 1
#> 17 5.4 3.9 1.3 0.4 setosa 1
#> 18 5.1 3.5 1.4 0.3 setosa 1
#> 19 5.7 3.8 1.7 0.3 setosa 1
#> 20 5.1 3.8 1.5 0.3 setosa 1
#> 21 5.4 3.4 1.7 0.2 setosa 1
#> 22 5.1 3.7 1.5 0.4 setosa 1
#> 23 4.6 3.6 1.0 0.2 setosa 1
#> 24 5.1 3.3 1.7 0.5 setosa 1
#> 25 4.8 3.4 1.9 0.2 setosa 1
#> 26 5.0 3.0 1.6 0.2 setosa 1
#> 27 5.0 3.4 1.6 0.4 setosa 1
#> 28 5.2 3.5 1.5 0.2 setosa 1
#> 29 5.2 3.4 1.4 0.2 setosa 1
#> 30 4.7 3.2 1.6 0.2 setosa 1
#> 31 4.8 3.1 1.6 0.2 setosa 1
#> 32 5.4 3.4 1.5 0.4 setosa 1
#> 33 5.2 4.1 1.5 0.1 setosa 1
#> 34 5.5 4.2 1.4 0.2 setosa 1
#> 35 4.9 3.1 1.5 0.2 setosa 1
#> 36 5.0 3.2 1.2 0.2 setosa 1
#> 37 5.5 3.5 1.3 0.2 setosa 1
#> 38 4.9 3.6 1.4 0.1 setosa 1
#> 39 4.4 3.0 1.3 0.2 setosa 1
#> 40 5.1 3.4 1.5 0.2 setosa 1
#> 41 5.0 3.5 1.3 0.3 setosa 1
#> 42 4.5 2.3 1.3 0.3 setosa 1
#> 43 4.4 3.2 1.3 0.2 setosa 1
#> 44 5.0 3.5 1.6 0.6 setosa 1
#> 45 5.1 3.8 1.9 0.4 setosa 1
#> 46 4.8 3.0 1.4 0.3 setosa 1
#> 47 5.1 3.8 1.6 0.2 setosa 1
#> 48 4.6 3.2 1.4 0.2 setosa 1
#> 49 5.3 3.7 1.5 0.2 setosa 1
#> 50 5.0 3.3 1.4 0.2 setosa 1
#> 51 7.0 3.2 4.7 1.4 versicolor 1
#> 52 6.4 3.2 4.5 1.5 versicolor 1
#> 53 6.9 3.1 4.9 1.5 versicolor 1
#> 54 5.5 2.3 4.0 1.3 versicolor 1
#> 55 6.5 2.8 4.6 1.5 versicolor 1
#> 56 5.7 2.8 4.5 1.3 versicolor 1
#> 57 6.3 3.3 4.7 1.6 versicolor 1
#> 58 4.9 2.4 3.3 1.0 versicolor 1
#> 59 6.6 2.9 4.6 1.3 versicolor 1
#> 60 5.2 2.7 3.9 1.4 versicolor 1
#> 61 5.0 2.0 3.5 1.0 versicolor 1
#> 62 5.9 3.0 4.2 1.5 versicolor 1
#> 63 6.0 2.2 4.0 1.0 versicolor 1
#> 64 6.1 2.9 4.7 1.4 versicolor 1
#> 65 5.6 2.9 3.6 1.3 versicolor 1
#> 66 6.7 3.1 4.4 1.4 versicolor 1
#> 67 5.6 3.0 4.5 1.5 versicolor 1
#> 68 5.8 2.7 4.1 1.0 versicolor 1
#> 69 6.2 2.2 4.5 1.5 versicolor 1
#> 70 5.6 2.5 3.9 1.1 versicolor 1
#> 71 5.9 3.2 4.8 1.8 versicolor 1
#> 72 6.1 2.8 4.0 1.3 versicolor 1
#> 73 6.3 2.5 4.9 1.5 versicolor 1
#> 74 6.1 2.8 4.7 1.2 versicolor 1
#> 75 6.4 2.9 4.3 1.3 versicolor 1
#> 76 6.6 3.0 4.4 1.4 versicolor 1
#> 77 6.8 2.8 4.8 1.4 versicolor 1
#> 78 6.7 3.0 5.0 1.7 versicolor 1
#> 79 6.0 2.9 4.5 1.5 versicolor 1
#> 80 5.7 2.6 3.5 1.0 versicolor 1
#> 81 5.5 2.4 3.8 1.1 versicolor 1
#> 82 5.5 2.4 3.7 1.0 versicolor 1
#> 83 5.8 2.7 3.9 1.2 versicolor 1
#> 84 6.0 2.7 5.1 1.6 versicolor 1
#> 85 5.4 3.0 4.5 1.5 versicolor 1
#> 86 6.0 3.4 4.5 1.6 versicolor 1
#> 87 6.7 3.1 4.7 1.5 versicolor 1
#> 88 6.3 2.3 4.4 1.3 versicolor 1
#> 89 5.6 3.0 4.1 1.3 versicolor 1
#> 90 5.5 2.5 4.0 1.3 versicolor 1
#> 91 5.5 2.6 4.4 1.2 versicolor 1
#> 92 6.1 3.0 4.6 1.4 versicolor 1
#> 93 5.8 2.6 4.0 1.2 versicolor 1
#> 94 5.0 2.3 3.3 1.0 versicolor 1
#> 95 5.6 2.7 4.2 1.3 versicolor 1
#> 96 5.7 3.0 4.2 1.2 versicolor 1
#> 97 5.7 2.9 4.2 1.3 versicolor 1
#> 98 6.2 2.9 4.3 1.3 versicolor 1
#> 99 5.1 2.5 3.0 1.1 versicolor 1
#> 100 5.7 2.8 4.1 1.3 versicolor 1
#> 101 6.3 3.3 6.0 2.5 virginica 1
#> 102 5.8 2.7 5.1 1.9 virginica 2
#> 103 7.1 3.0 5.9 2.1 virginica 1
#> 104 6.3 2.9 5.6 1.8 virginica 1
#> 105 6.5 3.0 5.8 2.2 virginica 1
#> 106 7.6 3.0 6.6 2.1 virginica 1
#> 107 4.9 2.5 4.5 1.7 virginica 1
#> 108 7.3 2.9 6.3 1.8 virginica 1
#> 109 6.7 2.5 5.8 1.8 virginica 1
#> 110 7.2 3.6 6.1 2.5 virginica 1
#> 111 6.5 3.2 5.1 2.0 virginica 1
#> 112 6.4 2.7 5.3 1.9 virginica 1
#> 113 6.8 3.0 5.5 2.1 virginica 1
#> 114 5.7 2.5 5.0 2.0 virginica 1
#> 115 5.8 2.8 5.1 2.4 virginica 1
#> 116 6.4 3.2 5.3 2.3 virginica 1
#> 117 6.5 3.0 5.5 1.8 virginica 1
#> 118 7.7 3.8 6.7 2.2 virginica 1
#> 119 7.7 2.6 6.9 2.3 virginica 1
#> 120 6.0 2.2 5.0 1.5 virginica 1
#> 121 6.9 3.2 5.7 2.3 virginica 1
#> 122 5.6 2.8 4.9 2.0 virginica 1
#> 123 7.7 2.8 6.7 2.0 virginica 1
#> 124 6.3 2.7 4.9 1.8 virginica 1
#> 125 6.7 3.3 5.7 2.1 virginica 1
#> 126 7.2 3.2 6.0 1.8 virginica 1
#> 127 6.2 2.8 4.8 1.8 virginica 1
#> 128 6.1 3.0 4.9 1.8 virginica 1
#> 129 6.4 2.8 5.6 2.1 virginica 1
#> 130 7.2 3.0 5.8 1.6 virginica 1
#> 131 7.4 2.8 6.1 1.9 virginica 1
#> 132 7.9 3.8 6.4 2.0 virginica 1
#> 133 6.4 2.8 5.6 2.2 virginica 1
#> 134 6.3 2.8 5.1 1.5 virginica 1
#> 135 6.1 2.6 5.6 1.4 virginica 1
#> 136 7.7 3.0 6.1 2.3 virginica 1
#> 137 6.3 3.4 5.6 2.4 virginica 1
#> 138 6.4 3.1 5.5 1.8 virginica 1
#> 139 6.0 3.0 4.8 1.8 virginica 1
#> 140 6.9 3.1 5.4 2.1 virginica 1
#> 141 6.7 3.1 5.6 2.4 virginica 1
#> 142 6.9 3.1 5.1 2.3 virginica 1
#> 143 5.8 2.7 5.1 1.9 virginica 2
#> 144 6.8 3.2 5.9 2.3 virginica 1
#> 145 6.7 3.3 5.7 2.5 virginica 1
#> 146 6.7 3.0 5.2 2.3 virginica 1
#> 147 6.3 2.5 5.0 1.9 virginica 1
#> 148 6.5 3.0 5.2 2.0 virginica 1
#> 149 6.2 3.4 5.4 2.3 virginica 1
#> 150 5.9 3.0 5.1 1.8 virginica 1