Description Usage Arguments Details Value Note Author(s) Examples
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”.
1 2 |
x |
the name of the x variable |
y |
the name of the y variable (if missing, |
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 |
main |
the main title |
xlim |
a numeric vector of length 2 (like |
ylim |
y-axis limits; similar to |
xlab |
x-axis title |
ylab |
y-axis title |
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.
A scatter plot
Using more than one color (including border colors) can lead to serious
speed issues; this plot is fastest when we only use a single color and a
single size. As the number of unique colors increases, the plotting can be
slower based on a same dataset. Using more than one size is also slower
than using a single size for all points; the internal painting functions
are different for the two cases (qdrawCircle
for the
former, and qdrawGlyph
for the latter).
Heike Hofmann, Di Cook, Yihui Xie
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 | 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()
|
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