qscatter: Draw a scatter plot

Description

This function creates a scatter plot with two numeric variables. It supports colors and sizes generated by qdata. When the sizes are not the same, a scatter plot becomes what is called the ``bubble chart''.

Usage

qscatter(x, y, data, edges = NULL, main = "", xlim = NULL, ylim = NULL, xlab = NULL,  ylab = NULL, asp = 1, alpha = 1, unibrushcolor = TRUE)

Arguments

the name of the x variable

the name of the y variable (if missing, x will be plotted against its indices, i.e., y will become x and x will be indices)

edges

matrix of two columns to indicate which lines to connect

asp

aspect ratio (ratio of the physical height of a plot to its width; unlike other R graphics systems, this will not affect the ranges of axes)

data

a mutaframe created by qdata

main

the main title

xlim

a numeric vector of length 2 (like c(x0, x1)) for x-axis limits; it will be calculated from the data limits if not specified (NULL). Note when x0 > x1, the axis direction will be reversed (i.e. from larger values to small values)

ylim

y-axis limits; similar to xlim

xlab

x-axis title

ylab

y-axis title

Value

A scatter plot

Details

All the common interactions like brushing and deleting are documented in common_key_press.

In the identify mode, the plot will show the row id(s) of the identified point(s) as well as x and y values.

Arrow keys are used in scatter plots for interactions: without the Shift key, Up and Down will increase/decrease the sizes of points; with the Shift key being pressed, Up, Down, Left and Right will move the (background of) plot to the corresponding direction.

Mouse wheel is used to zoom in and zoom out the plot. Together with keyboard interactions, this will enable us to see details in data.

Examples

Run this code

library(cranvas)

### (1) tennis data
qtennis <- qdata(tennis)

qscatter(first.serve.pct, second.serve.pts, data = qtennis, xlab = "First Serve %", 
    ylab = "Second Serve Points")
qscatter(return.games, first.serves, data = qtennis)

### (2) flea: color by categorical variable, and linking
data(flea, package = "tourr")
qflea <- qdata(flea, color = species)  # use species to create colors

qscatter(tars1, aede1, data = qflea)
qscatter(tars2, head, data = qflea)

qscatter(tars1, tars2, data = qflea, asp = 0.7)  # aspect ratio

qscatter(tars1, tars2, data = qflea, unibrushcolor = FALSE)  # brush color

## link qflea to itself using species
id <- link_cat(qflea, "species")

## remove linking
remove_link(qflea, id)

## a bubble chart
qflea2 <- qdata(flea, color = NA, border = species, size = tars1)
qscatter(tars1, tars2, data = qflea2)

### (3) NRC rankings

qnrc <- qdata(nrcstat, color = RegCode)

qscatter(RRankings5th, RRankings95th, data = qnrc)

qscatter(SRankings5th, SRankings95th, data = qnrc)

qscatter(SRankings5th, SRankings95th, data = qnrc, unibrushcolor = FALSE)

### (4) secrets in the pollen data
library(animation)
data(pollen, package = "animation")
head(pollen)
qpollen <- qdata(pollen, size = 2)
qscatter(RIDGE, CRACK, data = qpollen)
## try zooming into the center or press +/-

### (5) pressure test; run with care!
n <- 1e+06  # a million still works (at least for me)
df <- qdata(data.frame(x = rnorm(n), y = rnorm(n), z = gl(4, n/4)), color = z)
qscatter(x, y, data = df)

cranvas_off()

Run the code above in your browser using DataCamp Workspace