geom_bar: Bars, rectangles with bases on x-axisi

In SKKU-SKT/ggplot2.SparkR: Big Data Visualization for R and Spark

Description

There are two types of bar charts, determined by what is mapped to bar height. By default, geom_bar uses stat_count which makes the height of the bar proportion to the number of cases.

Usage

geom_bar(mapping = NULL, data = NULL, stat = "count",
  position = "stack", width = NULL, binwidth = NULL, ..., na.rm = FALSE,
  show.legend = NA, inherit.aes = TRUE)

Arguments

mapping	Set of aesthetic mapping created by aes or aes_.
data	The data to be displayed in this layer.
stat	Override the default connection between geom_bar and stat_count
position	Position adjustment, either as a string, or the result of a call to a position adjustment function.
width	Bar width.
binwidth	geom_bar no longer has a binwidth argument
...	other arguments passed on to layer.
na.rm	If FALSE, removes missing values with a warning (not used in ggplot2.SparkR).
show.legend	logical. Should this layer be included in the legends?
inherit.aes	If FALSE, overrides the default aesthetics, rather ehan combining with them.

Details

A bar chart maps the height of the bar to a variable, and so the base of the bar must always be shown to produce a valid visual comparison. Naomi Robbins has a nice article on this topic. This is why it doesn't make sense to use a log-scaled y axis with a bar chart.

Examples

## Not run: 
ggplot(faithful, aes(x = eruptions)) + geom_bar()

df <- createDataFrame(sqlContext, faithful)
ggplot(df, aes(x = eruptions)) + geom_bar()

df2 <- createDataFrame(sqlContext, diamonds)
ggplot(df2, aes(x = cut, fill = color)) + geom_bar(position = "dodge")
ggplot(df2, aes(cut)) + geom_bar() + facet_grid(. ~ clarity)

## End(Not run)

SKKU-SKT/ggplot2.SparkR documentation built on May 9, 2019, 11:13 a.m.