plot_prop: Plot the Proportion of Each Predictor Level Having a Specific...

In AndrewKostandy/MLtoolkit: Functions to Help with Machine Learning & Feature Engineering Tasks

Description

Plot the proportion of each predictor level having a specific outcome level and the 95% confidence interval of the proportion.

Usage

  plot_prop(data, predictor, outcome, ref_level, ref_value = 0.5,
            add_n = TRUE, width = 0)

Arguments

data	The dataframe containing the predictor and outcome variables.
predictor	The predictor variable name.
outcome	The outcome variable name.
ref_level	A string providing the specific outcome level to show the proportions for.
ref_value	Defaults to 0.5. A numeric providing the proportion value of interest to compare to.
add_n	Defaults to TRUE. A logical indicating whether to add the total number of observations of each level to the plot.
width	Defaults to 0. A numeric providing the width of the error bars.

Value

Returns a ggplot object with the predictor levels on the x-axis and the proportion of values in the ref_level of the outcome on the y-axis.

Figures

Author(s)

Andrew Kostandy ([e-mail])

Examples

diamonds2 <- diamonds %>%
  mutate(cut = fct_collapse(cut,
                            `>= Premium` = c("Premium", "Ideal"),
                            `<= Very Good` = c("Very Good", "Good",
                                               "Fair")))

plot_prop(diamonds2, clarity, cut, ref_level = ">= Premium",
          ref_value = 0.5, add_n = TRUE, width = 0)

AndrewKostandy/MLtoolkit documentation built on May 7, 2019, 9:51 p.m.