COINr (version 1.1.14)

plot_bar: Bar chart

Description

Plot bar charts of single indicators. Bar charts can be coloured by an optional grouping variable by_group, or if iCode points to an aggregate, setting stack_children = TRUE will plot iCode coloured by its underlying scores.

Usage

plot_bar(
  coin,
  dset,
  iCode,
  ...,
  uLabel = "uCode",
  axes_label = "iCode",
  by_group = NULL,
  filter_to_ends = NULL,
  dset_label = FALSE,
  log_scale = FALSE,
  stack_children = FALSE,
  bar_colours = NULL,
  flip_coords = FALSE
)

Value

A ggplot2 plot object.

Arguments

coin

A coin object.

dset

Data set from which to extract the variable to plot. Passed to get_data().

iCode

Code of variable or indicator to plot. Passed to get_data().

...

Further arguments to pass to get_data(), e.g. for filtering units.

uLabel

How to label units: either "uCode", or "uName".

axes_label

How to label the y axis and group legend: either "iCode" or "iName".

by_group

Optional group variable to use to colour bars. Cannot be used if stack_children = TRUE.

filter_to_ends

Optional way to filter the bar chart to only display the top/bottom N units. This is useful in cases where the number of units is large. Specify as e.g. list(top = 10) or list(bottom = 10) to return only the top or bottom ten units respectively (the value 10 can be changed of course).

dset_label

Logical: whether to include the data set in the y axis label.

log_scale

Logical: if TRUE uses a log scale for the y axis.

stack_children

Logical: if TRUE and iCode refers to an aggregate, will plot iCode with each bar split into its underlying component values (the underlying indicators/aggregates used to create iCode). To use this, you must have aggregated your data and dset must point to a data set where the underlying (child) scores of iCode are available.

bar_colours

Optional vector of colour codes for colouring bars.

flip_coords

Logical; if TRUE flips to horizontal bars.

Details

This function uses ggplot2 to generate plots, so the plot can be further manipulated using ggplot2 commands. See vignette("visualisation) for more details on plotting.

Examples

# build example coin
coin <- build_example_coin(up_to = "new_coin", quietly = TRUE)

# bar plot of CO2 by GDP per capita group
plot_bar(coin, dset = "Raw", iCode = "CO2",
         by_group = "GDPpc_group", axes_label = "iName")