The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
library(presenter)
library(dplyr)
Transpose a tibble of summary statistics in tidy format. Convenient
function for transposing the output of dplyr”s group_by
and
summarize
operation.
Transpose a 1 row numerical summary:
wide format
%>%
iris summarize(across(where(is.numeric), mean), .groups = "drop") -> sumr0
sumr0#> Sepal.Length Sepal.Width Petal.Length Petal.Width
#> 1 5.843333 3.057333 3.758 1.199333
long format
%>%
sumr0 pivot_summary()
#> # A tibble: 4 × 2
#> column V1
#> <chr> <dbl>
#> 1 Sepal.Length 5.84
#> 2 Sepal.Width 3.06
#> 3 Petal.Length 3.76
#> 4 Petal.Width 1.20
A grouped summary can be transposed by providing the name of the group column.
wide format
%>%
iris group_by(Species) %>%
summarize(across(where(is.numeric), mean), .groups = "drop") -> sumr1
sumr1#> # A tibble: 3 × 5
#> Species Sepal.Length Sepal.Width Petal.Length Petal.Width
#> <fct> <dbl> <dbl> <dbl> <dbl>
#> 1 setosa 5.01 3.43 1.46 0.246
#> 2 versicolor 5.94 2.77 4.26 1.33
#> 3 virginica 6.59 2.97 5.55 2.03
long format
%>%
sumr1 pivot_summary(Species)
#> # A tibble: 4 × 4
#> column setosa versicolor virginica
#> <chr> <dbl> <dbl> <dbl>
#> 1 Sepal.Length 5.01 5.94 6.59
#> 2 Sepal.Width 3.43 2.77 2.97
#> 3 Petal.Length 1.46 4.26 5.55
#> 4 Petal.Width 0.246 1.33 2.03
Supports transposing numerical summaries with multiple groups using tidyselect.
long format
%>%
iris mutate(Species1 = sample(Species)) %>%
group_by(Species, Species1) %>%
summarize(across(where(is.numeric), mean), .groups = "drop") -> sumr2
sumr2#> # A tibble: 9 × 6
#> Species Species1 Sepal.Length Sepal.Width Petal.Length Petal.Width
#> <fct> <fct> <dbl> <dbl> <dbl> <dbl>
#> 1 setosa setosa 5.13 3.61 1.46 0.269
#> 2 setosa versicolor 4.99 3.34 1.46 0.217
#> 3 setosa virginica 4.93 3.38 1.47 0.258
#> 4 versicolor setosa 5.92 2.78 4.34 1.32
#> 5 versicolor versicolor 5.94 2.78 4.23 1.35
#> 6 versicolor virginica 5.95 2.75 4.2 1.3
#> 7 virginica setosa 6.73 3.11 5.73 2.08
#> 8 virginica versicolor 6.62 2.92 5.44 1.95
#> 9 virginica virginica 6.42 2.87 5.44 2.02
Group names are concatenated and pivoted.
wide format
%>%
sumr2 pivot_summary(matches("Spec"))
#> # A tibble: 4 × 10
#> column setos…¹ setos…² setos…³ versi…⁴ versi…⁵ versi…⁶ virgi…⁷ virgi…⁸ virgi…⁹
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 Sepal… 5.13 4.99 4.93 5.92 5.94 5.95 6.73 6.62 6.42
#> 2 Sepal… 3.61 3.34 3.38 2.78 2.78 2.75 3.11 2.92 2.87
#> 3 Petal… 1.46 1.46 1.47 4.34 4.23 4.2 5.73 5.44 5.44
#> 4 Petal… 0.269 0.217 0.258 1.32 1.35 1.3 2.08 1.95 2.02
#> # … with abbreviated variable names ¹setosa_setosa, ²setosa_versicolor,
#> # ³setosa_virginica, ⁴versicolor_setosa, ⁵versicolor_versicolor,
#> # ⁶versicolor_virginica, ⁷virginica_setosa, ⁸virginica_versicolor,
#> # ⁹virginica_virginica
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.