histogram_w_outlier_bins function

Histogram with outlier bins

Create a histogram with outlier bins

histogram_w_outlier_bins(
  vector = NULL,
  bin_cutoffs = NULL,
  outlier_bin_left = TRUE,
  outlier_bin_right = TRUE,
  x_tick_marks = NULL,
  x_tick_mark_labels = NULL,
  y_tick_marks = NULL,
  outlier_bin_fill_color = "coral",
  non_outlier_bin_fill_color = "cyan4",
  border_color = "black",
  y_axis_title_vjust = 0.85,
  x_axis_title = NULL,
  y_axis_title = NULL,
  notify_na_count = NULL,
  plot_proportion = TRUE,
  plot_frequency = FALSE,
  mean = TRUE,
  ci = TRUE,
  median = TRUE,
  median_position = 15,
  error_bar_size = 3
)

Arguments

• vector: a numeric vector
• bin_cutoffs: cutoff points for bins
• outlier_bin_left: logical. Should the leftmost bin treated as an outlier bin? (default = TRUE)
• outlier_bin_right: logical. Should the rightmost bin treated as an outlier bin? (default = TRUE)
• x_tick_marks: a vector of values at which to place tick marks on the x axis. Note that the first bar spans from 0.5 to 1.5, second bar from 1.5 to 2.5, ... nth bar from n - 0.5 to n + 0.5. See the example. By default, tick marks will be placed at every cutoff point for bins
• x_tick_mark_labels: a character vector to label tick marks. By default, the vector of cutoff points for bins will also be used as labels.
• y_tick_marks: a vector of values at which to place tick marks on the y axis (e.g., setting y_tick_marks = seq(0, 10, 5) will put tick marks at 0, 5, and 10.)
• outlier_bin_fill_color: color to fill inside of the outlier bins (default = "coral")
• non_outlier_bin_fill_color: color to fill inside of the non-outlier bins (default = "cyan4")
• border_color: color for borders of the bins (default = "black")
• y_axis_title_vjust: position of the y axis title (default = 0.85).
• x_axis_title: title for x axis (default = "Value"). If x_axis_title = FALSE, x axis title will be removed from the plot.
• y_axis_title: title for y axis. By default, it will be either "Proportion" or "Count".
• notify_na_count: if TRUE, notify how many observations were removed due to missing values. By default, NA count will be printed only if there are any NA values.
• plot_proportion: logical. Should proportions be plotted, as opposed to frequencies? (default = TRUE)
• plot_frequency: logical. Should frequencies be plotted, as opposed to proportions? (default = FALSE). If plot_frequency = TRUE, plot_proportion will switch to be FALSE.
• mean: logical. Should mean marked on the histogram? (default = TRUE)
• ci: logical. Should 95% confidence interval marked on the histogram? (default = TRUE)
• median: logical. Should median marked on the histogram? (default = TRUE)
• median_position: position of the median label as a percentage of height of the tallest bin (default = 15)
• error_bar_size: size of the error bars (default = 3)

Returns

a ggplot object

Examples

histogram_w_outlier_bins(vector = 1:100, bin_cutoffs = seq(0, 100, 10))
histogram_w_outlier_bins(vector = 0:89, bin_cutoffs = seq(0, 90, 10),
x_tick_marks = seq(0.5, 9.5, 3), x_tick_mark_labels = seq(0, 90, 30))
histogram_w_outlier_bins(vector = 1:10, bin_cutoffs = seq(0, 10, 2.5))
histogram_w_outlier_bins(vector = 1:5, bin_cutoffs = seq(0, 10, 2.5))
histogram_w_outlier_bins(vector = 1:15, bin_cutoffs = c(5.52, 10.5))