Create Jittered Points Scatter Chart
v_jitter.Rd
Create Jittered Points Scatter Chart
Usage
v_jitter(
vc,
mapping = NULL,
data = NULL,
name = NULL,
width = NULL,
height = NULL,
...,
serie_id = NULL,
data_id = NULL
)
Arguments
- vc
A chart initialized with
vchart()
.- mapping
Default list of aesthetic mappings to use for chart.
- data
Default dataset to use for chart. If not already a
data.frame
, it will be coerced to withas.data.frame
.- name
Name for the serie, only used for single serie (no
color
/fill
aesthetic supplied).- width, height
Amount of vertical and horizontal jitter. The jitter is added in both positive and negative directions, so the total spread is twice the value specified here.
If omitted, defaults to 40% of the resolution of the data: this means the jitter values will occupy 80% of the implied bins. Categorical data is aligned on the integers, so a width or height of 0.5 will spread the data so it's not possible to see the distinction between the categories.
- ...
Additional parameters for the serie.
- data_id, serie_id
ID for the data/serie, can be used to further customize the chart with
v_specs()
.
Value
A vchart()
htmlwidget
object.
Examples
library(vchartr)
data("mpg", package = "ggplot2")
data("penguins", package = "palmerpenguins")
# With continuous x
vchart(mpg) %>%
v_jitter(aes(cyl, hwy))
# with discrete x
vchart(penguins) %>%
v_jitter(aes(species, bill_length_mm))
# Colour points
vchart(mpg) %>%
v_jitter(aes(cyl, hwy, colour = class))
# Use smaller width/height to emphasise categories
vchart(mpg) %>%
v_jitter(aes(cyl, hwy), width = 0.25)
# Use larger width/height to completely smooth away discreteness
vchart(mpg) %>%
v_jitter(aes(cty, hwy), width = 0.5, height = 0.5)