Prints descriptive statistics for numeric variables — print

Prints summary statistics (mean, median, quartiles, range, etc.) for numeric variables.

Usage

print_numeric(x, digits = 1, width = 15)

Arguments

x: Data frame, matrix, or vector containing numerical variables.
digits: Integer specifying the number of decimal places for the test statistic.
width: Integer specifying the maximum width for wrapping text.

Value

A tibble with one row per numeric variable and the following columns:

Variables: Character specifying the variable name.
Mean+/-SD: Character specifying the mean and standard deviation.
Median+/-IQR: Character specifying the median and interquartile range.
Q1-Q3: Character specifying the first and third quartiles.
Range: Character specifying the minimum and maximum values.
Kurtosis: Numeric specifying the kurtosis coefficient.
Skewness: Numeric specifying the skewness coefficient.
Normality: Character specifying the Shapiro-Wilk normality test significance code.
Zeros: Integer specifying the number of zero values.
NAs: Integer specifying the number of missing values.

Examples

x <- data.frame(A = rnorm(100), B = rnorm(100))
print_numeric(x)
#> # A tibble: 2 × 10
#>   Variables `Mean+/-SD` `Median+/-IQR` `Q1-Q3` Range Kurtosis Skewness Normality
#>   <chr>     <chr>       <chr>          <chr>   <chr>    <dbl>    <dbl> <chr>    
#> 1 A         0.1+/-1     0.1+/-1.2      -0.5;0… -2.4…      0.1      0.1 ns       
#> 2 B         0+/-1       0.1+/-1.2      -0.5;0… -3.1…      0.1     -0.5 ns       
#> # ℹ 2 more variables: Zeros <int>, NAs <int>
print_numeric(x, digits = 2, width = 5)
#> # A tibble: 2 × 10
#>   Variables `Mean+/-SD` `Median+/-IQR` `Q1-Q3` Range Kurtosis Skewness Normality
#>   <chr>     <chr>       <chr>          <chr>   <chr>    <dbl>    <dbl> <chr>    
#> 1 A         "0.11\n+/-… "0.12\n+/-1.2… -0.53;… -2.4…     0.07     0.1  ns       
#> 2 B         "0.03\n+/-… "0.14\n+/-1.1… -0.53;… -3.1…     0.06    -0.46 ns       
#> # ℹ 2 more variables: Zeros <int>, NAs <int>