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Groupwise descriptive statistics

Source: R/ds-group-summary.R
ds_group_summary.Rd

Descriptive statistics of a continuous variable for the different levels of a categorical variable. boxplot.group_summary() creates boxplots of the continuous variable for the different levels of the categorical variable.

Usage

ds_group_summary(data, group_by, cols)

# S3 method for class 'ds_group_summary'
plot(x, print_plot = TRUE, ...)

Arguments

data

A data.frame or a tibble.

group_by

Column in data.

cols

Column in data.

x

An object of the class ds_group_summary.

print_plot

logical; if TRUE, prints the plot else returns a plot object.

...

Further arguments to be passed to or from methods.

Value

ds_group_summary() returns an object of class "ds_group_summary". An object of class "ds_group_summary" is a list containing the following components:

stats

A data frame containing descriptive statistics for the different levels of the factor variable.

tidy_stats

A tibble containing descriptive statistics for the different levels of the factor variable.

plotdata

Data for boxplot method.

See also

ds_summary_stats

Examples

# ds_group summary
ds_group_summary(mtcarz, cyl, mpg)
#>                                            by                                             
#> -----------------------------------------------------------------------------------------
#> |     Statistic/Levels|                    4|                    6|                    8|
#> -----------------------------------------------------------------------------------------
#> |                  Obs|                   11|                    7|                   14|
#> |              Minimum|                 21.4|                 17.8|                 10.4|
#> |              Maximum|                 33.9|                 21.4|                 19.2|
#> |                 Mean|                26.66|                19.74|                 15.1|
#> |               Median|                   26|                 19.7|                 15.2|
#> |                 Mode|                 22.8|                   21|                 10.4|
#> |       Std. Deviation|                 4.51|                 1.45|                 2.56|
#> |             Variance|                20.34|                 2.11|                 6.55|
#> |             Skewness|                 0.35|                -0.26|                -0.46|
#> |             Kurtosis|                -1.43|                -1.83|                 0.33|
#> |       Uncorrected SS|              8023.83|              2741.14|              3277.34|
#> |         Corrected SS|               203.39|                12.68|                 85.2|
#> |      Coeff Variation|                16.91|                 7.36|                16.95|
#> |      Std. Error Mean|                 1.36|                 0.55|                 0.68|
#> |                Range|                 12.5|                  3.6|                  8.8|
#> |  Interquartile Range|                  7.6|                 2.35|                 1.85|
#> -----------------------------------------------------------------------------------------

# boxplot
k <- ds_group_summary(mtcarz, cyl, mpg)
plot(k)


# tibble
k$tidy_stats
#> # A tibble: 3 × 15
#>   cyl   length   min   max  mean median  mode    sd variance skewness kurtosis
#>   <fct>  <int> <dbl> <dbl> <dbl>  <dbl> <dbl> <dbl>    <dbl>    <dbl>    <dbl>
#> 1 4         11  21.4  33.9  26.7   26    22.8  4.51    20.3     0.348   -1.43 
#> 2 6          7  17.8  21.4  19.7   19.7  21    1.45     2.11   -0.259   -1.83 
#> 3 8         14  10.4  19.2  15.1   15.2  10.4  2.56     6.55   -0.456    0.330
#> # ℹ 4 more variables: coeff_var <dbl>, std_error <dbl>, range <dbl>, iqr <dbl>