[英]Plotting by quantile in R
I want to plot foo ~ bar
. 我想绘制foo ~ bar
。 However, I don't want to look at the exact data, I'd rather break bar
into say quantiles, and plot mean(foo)
for every quantile (so my final plot will have 5 data points). 但是,我不想查看确切的数据,我宁愿将分bar
分成多个分位数,并为每个分位数绘制mean(foo)
(这样我的最终图将有5个数据点)。 Is this possible? 这可能吗?
foo <- rnorm(100)
bar <- rnorm(100)
mn.foo.byQ10bar <- tapply(foo, cut(bar, quantile(bar, (0:5)/5, na.rm=TRUE)), mean)
> mn.foo.byQ5bar
(-3.31,-0.972] (-0.972,-0.343] (-0.343,0.317] (0.317,0.792] (0.792,2.71]
0.13977839 0.03281258 -0.18243804 -0.14242885 -0.01696712
plot(mn.foo.byQ5bar)
This is a fairly standard task and Harrell's Hmisc package's cut2
function has a nice gr= argument that lets you do this by just specifying an integer for the number of groups. 这是一个相当标准的任务,Harrell的Hmisc程序包的cut2
函数具有一个不错的gr =参数,您可以通过仅为组数指定一个整数来执行此操作。 I also like it because the intervals from the cut operation are left-closed instead of R default for right-closed. 我也喜欢它,因为剪切操作的间隔是左关闭的,而不是右关闭的R default。
You can combine a lot of these lines into more concise code, but here it is broken down 您可以将许多这些行组合成更简洁的代码,但此处已将其细分
# Sample Data:
x <- 1:100; y <- rnorm(x)
# Number Of Groups
N <- 5
# quantiles
Q.y <- quantile(y, probs=seq(0, 1, length=(N+1)))
Q.x <- quantile(x, probs=seq(0, 1, length=N))
# means of y by quantile
means.y <- c(by(y, cut(y, Q.y), mean))
# plot them
qplot(Q.x, means.y)
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