If you want to create an interactive scatterplot, you can use the
scatterplot3js
function from the threejs package.
About this task
You can use RStudio
to create this 100,000-point interactive scatter plot, or you can use the
TERR
console and display the results in a browser.
Before you begin
TERR, access to the internet, and a browser.
Procedure
-
From the TERR console or RStudio
prompt,
install the threejs package.
install.packages("threejs")
TERR checks TRAN and then CRAN for
the packages to install, and then installs them along with any packages they
require.
-
Call the
library
function to load the required packages.
-
Assign the value
10000
to
N1
, and the value
90000
to the name
N2
.
-
Assign the point distribution to the
x
axis.
Set a random normal distribution for both
N1
and
N2
, with the standard deviation for
N1
of
.05
, and the standard deviation for
N2
of
2
.
x <- c(rnorm(N1, sd=0.5), rnorm(N2, sd=2))
-
Assign the point distribution to the
y
axis.
Set a random normal distribution for both
N1
and
N2
, with the standard deviation for
N1
set to
.05
, and the standard deviation for
N2
set to
2
.
y <- c(rnorm(N1, sd=0.5), rnorm(N2, sd=2))
-
Assign the point distribution to the
z
axis.
Set a random normal distribution for
N1
, with the standard deviation of
.05
, and a random Poisson distribution for
N2
with lambda of
20
to specify the means. Subtract 20 from the
concatenation to center the points correctly on the
z
axis.
z <- c(rnorm(N1, sd=0.5), rpois(N2, lambda=20)-20)
-
Assign to
col
the color values for
N1
and
N2
.
Set
N1
points to be yellow (#ffff00
)
and set the
N2
points to be blue (#0000ff
).
col <- c(rep("#ffff00",N1),rep("#0000ff",N2))
-
Call the threejs function
scatterplot3js
to create the three-dimensional plot.
Plot the points for the coordinate values
x
,
y
, and
z
axes in the three-dimensional graph, setting the
colors to
col
, and the point size to
0.25
.
scatterplot3js(x,y,z, color=col, size=0.25)
Results
A browser opens and
shows the three-dimensional scatterplot, which you can reposition to see the
point distribution.
Tip: Dragging
the visualization vertically reveals the
N1
points centered in the cloud of
N2
points.