| pairs.panels {psych} | R Documentation |
Adapted from the help page for pairs, pairs.panels shows a scatter plot of matrices (SPLOM), with bivariate scatter plots below the diagonal, histograms on the diagonal, and the Pearson correlation above the diagonal. Useful for descriptive statistics of small data sets. If lm=TRUE, linear regression fits are shown for both y by x and x by y. Correlation ellipses are also shown. Points may be given different colors depending upon some grouping variable.
## S3 method for class 'panels'
pairs(x, smooth = TRUE, scale = FALSE, density=TRUE,ellipses=TRUE,
digits = 2,method="pearson", pch = 20,lm=FALSE,
cor=TRUE,jiggle=FALSE,factor=2,hist.col="cyan",show.points=TRUE,rug=TRUE, ...)
x |
a data.frame or matrix |
smooth |
TRUE draws loess smooths |
scale |
TRUE scales the correlation font by the size of the absolute correlation. |
density |
TRUE shows the density plots as well as histograms |
ellipses |
TRUE draws correlation ellipses |
lm |
Plot the linear fit rather than the LOESS smoothed fits. |
digits |
the number of digits to show |
method |
method parameter for the correlation ("pearson","spearman","kendall") |
pch |
The plot character (defaults to 20 which is a '.'). |
cor |
If plotting regressions, should correlations be reported? |
jiggle |
Should the points be jittered before plotting? |
factor |
factor for jittering (1-5) |
hist.col |
What color should the histogram on the diagonal be? |
show.points |
If FALSE, do not show the data points, just the data ellipses and smoothed functions |
rug |
if TRUE (default) draw a rug under the histogram, if FALSE, don't draw the rug |
... |
other options for pairs |
Shamelessly adapted from the pairs help page. Uses panel.cor, panel.cor.scale, and panel.hist, all taken from the help pages for pairs. Also adapts the ellipse function from John Fox's car package.
pairs.panels is most useful when the number of variables to plot is less than about 6-10. It is particularly useful for an initial overview of the data.
To show different groups with different colors, use a plot character (pch) between 21 and 25 and then set the background color to vary by group. (See the second example).
When plotting more than about 10 variables, it is useful to set the gap parameter to something less than 1 (e.g., 0). Alternatively, consider using cor.plot
In addition, when plotting more than about 100-200 cases, it is useful to set the plotting character to be a point. (pch=".")
Sometimes it useful to draw the correlation ellipses and best fitting lowess without the points. (points.false=TRUE).
A scatter plot matrix (SPLOM) is drawn in the graphic window. The lower off diagonal draws scatter plots, the diagonal histograms, the upper off diagonal reports the Pearson correlation (with pairwise deletion).
If lm=TRUE, then the scatter plots are drawn above and below the diagonal, each with a linear regression fit. Useful to show the difference between regression lines.
pairs which is the base from which pairs.panels is derived, cor.plot to do a heat map of correlations, and scatter.hist to draw a single correlation plot with histograms and best fitted lines.
pairs.panels(attitude) #see the graphics window
data(iris)
pairs.panels(iris[1:4],bg=c("red","yellow","blue")[iris$Species],
pch=21,main="Fisher Iris data by Species") #to show color grouping
pairs.panels(iris[1:4],bg=c("red","yellow","blue")[iris$Species],
pch=21,main="Fisher Iris data by Species",hist.col="red")
#to show changing the diagonal
#demonstrate not showing the data points
data(sat.act)
pairs.panels(sat.act,show.points=FALSE)
#better yet is to show the points as a period
pairs.panels(sat.act,pch=".")
#show many variables with 0 gap between scatterplots
# data(bfi)
# pairs.panels(bfi,show.points=FALSE,gap=0)