Function generates a data frame of the most common statistics such as mean, standard deviation, minimum and maximum grouped by selected argument for numerical variables
table_one(numeric_vars = NULL, groupby, data)column names of numeric columns of dataframe which we want to use to have table one arguments should be typed as character vector
element which we want to group by the rest numeric variables but only one grupby element
Data frame
returns a list of the most commonly used statistical measures such as mean, standard deviation, minimum and maximum of desired numerical variables
library("toRpEDA")
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
library(stats)
table_one(numeric_vars = c("Petal.Length","Petal.Width"), groupby = "Species", data= iris)
#> setosa versicolor virginica
#> n 50 50 50
#> Petal.Length.mean (SD) 1.462 (0.174) 4.260 (0.470) 5.552 (0.552)
#> Petal.Length.min (max) 1.000 (1.900) 3.000 (5.100) 4.500 (6.900)
#> Petal.Width.mean (SD) 0.246 (0.105) 1.326 (0.198) 2.026 (0.275)
#> Petal.Width.min (max) 0.100 (0.600) 1.000 (1.800) 1.400 (2.500)
table_one(groupby = 'Species', data= iris)
#> setosa versicolor virginica
#> n 50 50 50
#> Sepal.Length.mean (SD) 5.006 (0.352) 5.936 (0.516) 6.588 (0.636)
#> Sepal.Length.min (max) 4.300 (5.800) 4.900 (7.000) 4.900 (7.900)
#> Sepal.Width.mean (SD) 3.428 (0.379) 2.770 (0.314) 2.974 (0.322)
#> Sepal.Width.min (max) 2.300 (4.400) 2.000 (3.400) 2.200 (3.800)
#> Petal.Length.mean (SD) 1.462 (0.174) 4.260 (0.470) 5.552 (0.552)
#> Petal.Length.min (max) 1.000 (1.900) 3.000 (5.100) 4.500 (6.900)
#> Petal.Width.mean (SD) 0.246 (0.105) 1.326 (0.198) 2.026 (0.275)
#> Petal.Width.min (max) 0.100 (0.600) 1.000 (1.800) 1.400 (2.500)