util_optimize_histogram_bins: Utility function to compute and optimize bin breaks for histograms

Description

Utility function to compute and optimize bin breaks for histograms

Usage

util_optimize_histogram_bins(
  x,
  iqr_bw,
  n_bw,
  min_within = NULL,
  max_within = NULL,
  min_plot = NULL,
  max_plot = NULL,
  nbins_max = NULL
)

Value

a list with bin breaks below, within and above limits

Arguments

x: a vector of data values (numeric or datetime)
iqr_bw: the interquartile range of values which should be included to calculate the Freedman-Diaconis bandwidth (e.g., for con_limit_deviations only values within limits)
n_bw: the number of values which should be included to calculate the Freedman-Diaconis bandwidth (e.g., for con_limit_deviations the number of values within limits)
min_within: the minimum value which is still within limits (needed for con_limit_deviations)
max_within: the maximum value which is still within limits (needed for con_limit_deviations)
min_plot: the minimum value which should be included in the plot
max_plot: the maximum value which should be included in the plot
nbins_max: the maximum number of bins for the histogram. Strong outliers can cause too many narrow bins, which might be even to narrow to be plotted. This also results in large files and rendering problems. So it is sensible to limit the number of bins. The function will produce a warning if it reduces the number of bins in such a case. Reasons could be unspecified missing value codes, or minimum or maximum values far away from most of the data values, or (for con_limit_deviations) no or few values within limits.