[英]Correlation matrix plot with ggplot2
I want to create a correlation matrix plot, ie a plot where each variable is plotted in a scatterplot against each other variable like with pairs()
or splom()
. 我想创建一个相关矩阵图,即一个图,其中每个变量在散点图中绘制,而不是像pairs()
或splom()
那样相互splom()
。 I want to do this with ggplot2. 我想用ggplot2做这个。 See here for examples . 请看这里的例子 。 The link mentions some code someone wrote for doing this in ggplot2, however, it is outdated and no longer works (even after you swap out the deprecated parts). 该链接提到了某人在ggplot2中编写的代码,但是,它已经过时且不再有效(即使在您更换了已弃用的部分之后)。
One could do this with a loop in a loop and then multiplot()
, but there must be a better way. 可以通过循环中的循环然后使用multiplot()
来做到这一点,但必须有更好的方法。 I tried melting the dataset to long, and copying the value and variable variables and then using facets. 我尝试将数据集熔化为long,然后复制值和变量,然后使用facet。 This almost gives you something correct. 这几乎给你一些正确的东西。
d = data.frame(x1=rnorm(100),
x2=rnorm(100),
x3=rnorm(100),
x4=rnorm(100),
x5=rnorm(100))
library(reshape2)
d = melt(d)
d$value2 = d$value
d$variable2 = d$variable
library(ggplot2)
ggplot(data=d, aes(x=value, y=value2)) +
geom_point() +
facet_grid(variable ~ variable2)
This gets the general structure right, but only works for the plotting each variable against itself. 这使得一般结构正确,但仅适用于绘制每个变量对自己。 Is there some more clever way of doing this without resorting to 2 loops? 是否有一些更聪明的方法来做到这一点,而不诉诸2循环?
library(GGally)
set.seed(42)
d = data.frame(x1=rnorm(100),
x2=rnorm(100),
x3=rnorm(100),
x4=rnorm(100),
x5=rnorm(100))
# estimated density in diagonal
ggpairs(d)
# blank
ggpairs(d, diag = list("continuous"="blank")
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