使用ggplot2在直方图上绘制正常曲线：代码在0处生成直线 [英] Plotting normal curve over histogram using ggplot2: Code produces straight line at 0

问题描述

这个论坛为我生成代码提供了很多帮助，我希望能够返回一个覆盖其经验正态曲线的特定变量的直方图。我用ggplot2和stat_function来编写代码。
不幸的是，代码生成了一个具有正确直方图的曲线图，但正常曲线是一条直线为零（由以下代码生成的红色曲线）。

<对于这个最小的例子，我使用了mtcars数据集 - 我的原始数据集观察到ggplot和stat_function的相同行为。

这是代码被写入和使用：

  library（ggplot2）
 mtcars 
 hist_staff<  -  ggplot（mtcars，aes（x = mtcars $ mpg））+ 
 geom_histogram（binwidth = 2，color =black，aes（fill = ..count ..））+ 
 scale_fill_gradient（Count，low =#DCDCDC ，高=＃7C7C7C）+ 
 stat_function（fun = dnorm，color =red）
 print（hist_staff）
  

我也试着指定dnorm：

  stat_function（fun = dnorm（mtcars $ mpg，mean = mean（mtcars $ mpg），sd = sd（mtcars $ mpg））
  

那也没有成功 - 返回的错误消息说明了这一点在参数不是数字。

我希望你们能帮助我！感谢您的提前！

Best，Jannik

解决方案

曲线和直方图在不同的比例尺上，并且您没有检查 stat_function 上的帮助页面，否则您将参数放在列表，如清单所示。您还没有在您的初始 ggplot 调用中执行 aes 。我诚恳地建议打出更多的教程和书籍（或者至少帮助页面），同时学习ggplot零碎。

修复 stat_function arg问题和 ggplot``aes 问题，您需要解决y轴比例差异问题。为此，您需要将直方图的y切换为使用基础 stat_bin 计算数据框中的密度：

  library（ggplot2）
 
 gg < -  ggplot（mtcars，aes（x = mpg））
 gg < -  gg + geom_histogram（binwidth = 2，color =black，
 aes（y = .. density ..，fill = .. count ..））
 gg < -  gg + scale_fill_gradient（Count ，low =＃DCDCDC，high =＃7C7C7C）
 gg < -  gg + stat_function（fun = dnorm，
 color =red，
 args = list mean = mean（mtcars $ mpg），
 sd = sd（mtcars $ mpg）））
 
 gg 
  

this forum already helped me a lot for producing the code, which I expected to return a histogram of a specific variable overlayed with its empirical normal curve. I used ggplot2 and stat_function to write the code. Unfortunately, the code produced a plot with the correct histogram but the normal curve is a straight line at zero (red line in plot produced by the following code).

For this minimal example I used the mtcars dataset - the same behavior of ggplot and stat_function is observed with my original data set.

This is the code is wrote and used:

library(ggplot2)
mtcars
hist_staff <- ggplot(mtcars, aes(x = mtcars$mpg)) + 
  geom_histogram(binwidth = 2, colour = "black", aes(fill = ..count..)) +
  scale_fill_gradient("Count", low = "#DCDCDC", high = "#7C7C7C") +
  stat_function(fun = dnorm, colour = "red")
print(hist_staff)

I also tried to specify dnorm:

stat_function(fun = dnorm(mtcars$mpg, mean = mean(mtcars$mpg), sd = sd(mtcars$mpg))

That did not work out either - an error message returned stating that the arguments are not numerical.

I hope you people can help me! Thanks a lot in advance!

Best, Jannik

解决方案

Your curve and histograms are on different y scales and you didn't check the help page on stat_function, otherwise you'd've put the arguments in a list as it clearly shows in the example. You also aren't doing the aes right in your initial ggplot call. I sincerely suggest hitting up more tutorials and books (or at a minimum the help pages) vs learn ggplot piecemeal on SO.

Once you fix the stat_function arg problem and the ggplot``aes issue, you need to tackle the y axis scale difference. To do that, you'll need to switch the y for the histogram to use the density from the underlying stat_bin calculated data frame:

library(ggplot2)

gg <- ggplot(mtcars, aes(x=mpg))
gg <- gg + geom_histogram(binwidth=2, colour="black", 
                          aes(y=..density.., fill=..count..))
gg <- gg + scale_fill_gradient("Count", low="#DCDCDC", high="#7C7C7C")
gg <- gg + stat_function(fun=dnorm,
                         color="red",
                         args=list(mean=mean(mtcars$mpg), 
                                  sd=sd(mtcars$mpg)))

gg

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