f_plot_hist: Plot Histograms

In erblast/oetteR: Collection of personal R functions

Description

Function plots smart histograms for variables in a data_ls list generated by f_clean_data(). It supports three types of histograms: Bar histograms, density histograms and violin plots. We can further specify a categorical variable to group on. The function defaults to a sensible standard output if key word arguments are not applicable for variable type. Thus we can easily pipe through long lists of variables and thus generate histograms for all variables in the input (see examples).

Usage

f_plot_hist(variable, data_ls, group = "None", graph_type = "violin",
  y_axis = "count", auto_range = T, n_breaks = 30, rug = T,
  x_min = 0, x_max = 100, y_max = 100, title = "",
  col_vector = f_plot_adjust_col_vector_length(100,
  RColorBrewer::brewer.pal(name = "Dark2", n = 8)), p_val = T,
  add = "mean", ...)

Arguments

variable	character vector naming the variable to be plotted
data_ls	data_ls object generated by f_clean_data(), or a named list list( data = <dataframe>, numericals = < vector with column names of numerical columns>)
group	character vector naming the column to be used as grouping variable, Default: NULL
graph_type	one of c("violin", "bar", "line"), Default: 'violin'
y_axis	one of c("count", "density"), Default: c("count", "density")
auto_range	boolean, Default: T
n_breaks	integer , Default: 30
rug	boolean
x_min	double, requires aut_range == F, Default: 0
x_max	double, requires aut_range == F, Default: 100
y_max	double, requires aut_range == F, Default: 100
title	character vector plot title
col_vector	vector with RGB colors, Default: f_plot_adjust_col_vector_length(100, RColorBrewer::brewer.pal(name = "Dark2", n = 8))
p_val	boolean, Default: T
add	character vector one_of( c('mean','median','none') ), This feature is currently enabled because it does not seem to be supported by ggpubr under R 3.5, Default: 'mean'
...	additional arguments passed to labs()

Value

plot object

Examples

## Not run: 
#'
#plot single variable
data_ls = f_clean_data(mtcars)
f_plot_hist('disp', data_ls)
f_plot_hist('disp', data_ls, add = 'median')
f_plot_hist('disp', data_ls, add = 'none')
f_plot_hist('disp', data_ls, y_axis = 'density')
f_plot_hist('cyl', data_ls , group = 'gear' )
f_plot_hist('cyl', data_ls , group = 'gear', y_axis = 'density' )
f_plot_hist('cyl', data_ls, y_axis = 'density' )
f_plot_hist('cyl', data_ls, y_axis = 'count' )
f_plot_hist('disp', data_ls, graph_type = 'line', group = 'cyl')
f_plot_hist('disp', data_ls, graph_type = 'bar', group = 'cyl')
f_plot_hist('disp', data_ls, graph_type = 'violin', group = 'cyl'
             , caption ='caption', title = 'title', subtitle = 'subtitle')

#plot all variables
vars = data_ls$all_variables[ data_ls$all_variables != 'cyl' ] %>%
 map( f_plot_hist, data_ls, group = 'cyl')
vars

## End(Not run)

erblast/oetteR documentation built on May 27, 2019, 12:11 p.m.