使用ggplot2在R中具有正态分布的直方图

Question

I'm trying to plot a histogram with ggplot2.

I wrote a simple code for this in R

dnorm.count <- function(x, mean = 0, sd = 1, log = FALSE, n = 1, binwidth = 1){
  n * binwidth * dnorm(x = x, mean = mean, sd = sd, log = log) 
}
mtcars %>% 
  ggplot(aes(x =  mpg)) +
  geom_histogram(bins =60,color = "white", fill = "#9FE367",boundary = 0.5) +
  geom_vline(aes(xintercept = mean(mpg)), 
             linetype="dashed",
             size = 1.6, 
             color = "#FF0000")+
  geom_text(aes(label = ..count..), stat= "count",vjust = -0.6)+
  stat_function(fun = dnorm.count, color = "#6D67E3", 
                args = list(mean= mean(mtcars$mpg), 
                            sd = sd(mtcars$mpg),
                            n = nrow(mtcars)), 
                lwd = 1.2) +
  scale_y_continuous(labels = comma, name = "Frequency") +
  scale_x_continuous(breaks=seq(0,max(mtcars$mpg)))+
  geom_text(aes(label = paste0("mean = ", round(mean(mtcars$mpg), 2)), 
                x = mean(mtcars$mpg)*1.2, 
                y  = mean(mtcars$mpg)/5))+
  geom_vline(aes(xintercept = sd(mpg)), linetype="dashed",size = 1.6, color = "#FF0000") 

What I got is this!

The question is how do I Plot the histogram similar to this

using ggplot2 and is it possible to convert the code to R function?

Edit: For the better explanation of what I'm trying to do:

---

I wanna create a Histogram exactly the same as the one attached for reference using ggplot2 and then I wanna create a function for the same to reduce the coding. Use any package+ggplot2 you like. The histograms should have lines depicting the standard deviation & mean like the one in reference. If possible depict the standard deviation in the plot as the reference image, that's what I'm trying to achieve.

Answer 1

If your question how to plot histograms like the one you attached in your last figure, this 9 lines of code produce a very similar result.

library(magrittr) ; library(ggplot2)
set.seed(42)
data <- rnorm(1e5)
p <- data %>%
  as.data.frame() %>%
  ggplot(., aes(x = data)) +
  geom_histogram(fill = "white", col = "black", bins = 30 ) +
  geom_density(aes( y = 0.3 *..count..)) +
  labs(x = "Statistics", y = "Probability/Density") +
  theme_bw() + theme(axis.text = element_blank())

You could use annotate() to add symbols or text and geom_segment to show the intervals on the plot like this:

p + annotate(x = sd(data)/2 , y = 8000, geom = "text", label = "σ", size = 10) +
    annotate(x = sd(data) , y = 6000, geom = "text", label = "2σ", size = 10) +
    annotate(x = sd(data)*1.5 , y = 4000, geom = "text", label = "3σ", size = 10) +     
    geom_segment(x = 0, xend = sd(data), y = 7500, yend = 7500) +
    geom_segment(x = 0, xend = sd(data)*2, y = 5500, yend = 5500) +
    geom_segment(x = 0, xend = sd(data)*3, y = 3500, yend = 3500) 

This chunk of code would give you something like this: