使用ggplot2重新创建高级基础R图

sta*_*tor 4 r ggplot2

下面的代码使用R中的基本绘图函数创建一个帕累托图.如何使用ggplot创建相同的图表?

*我知道有些人会讨厌两个y轴的情节.请不要在这篇文章中包含这个辩论.谢谢

## Creating the d tribble
library(tidyverse)
d <- tribble(
  ~ category, ~defect,
  "price", 80,
  "schedule", 27,
  "supplier", 66,
  "contact", 94,
  "item", 33
)

## Creating new columns
d <- arrange(d, desc(defect)) %>%
  mutate(
    cumsum = cumsum(defect),
    freq = round(defect / sum(defect), 3),
    cum_freq = cumsum(freq)
  )

## Saving Parameters 
def_par <- par() 

## New margins
par(mar=c(5,5,4,5)) 

## bar plot, pc will hold x values for bars
pc = barplot(d$defect,  
             width = 1, space = 0.2, border = NA, axes = F,
             ylim = c(0, 1.05 * max(d$cumsum, na.rm = T)), 
             ylab = "Cummulative Counts" , cex.names = 0.7, 
             names.arg = d$category,
             main = "Pareto Chart (version 1)")

## Cumulative counts line 
lines(pc, d$cumsum, type = "b", cex = 0.7, pch = 19, col="cyan4")

## Framing plot
box(col = "grey62")

## adding axes
axis(side = 2, at = c(0, d$cumsum), las = 1, col.axis = "grey62", col = "grey62", cex.axis = 0.8)
axis(side = 4, at = c(0, d$cumsum), labels = paste(c(0, round(d$cum_freq * 100)) ,"%",sep=""), 
     las = 1, col.axis = "cyan4", col = "cyan4", cex.axis = 0.8)

## restoring default paramenter
par(def_par) 
Run Code Online (Sandbox Code Playgroud)

download.png

cam*_*lle 10

这是一个开始.我将您的dplyr函数组合成一个流,只是为了避免分配和重新分配变量d.我添加了一个mutate调用,它使用from (随附)生成category一个因子,根据相应的值排序.defectfct_reorderforcatstidyverse

我不确定的是如何让左y轴断裂.我通过获取唯一值来手动设置它们d$cumsum,但是可能有一种方法可以在breaks参数中为它编写函数scale_y_continuous.

ggplot2允许辅助轴的更新版本,但它需要基于主轴的转换.在这种情况下,这意味着它应该采用主轴的值并除以最大值以获得百分比.

正如@ClausWilke在评论中指出的那样,为了确保辅助轴与数据正确对齐,使得顶点为100%,用于~. / max(d$cumsum)设置辅助轴.

library(tidyverse)

d <- tribble(
    ~ category, ~defect,
    "price", 80,
    "schedule", 27,
    "supplier", 66,
    "contact", 94,
    "item", 33
) %>% arrange(desc(defect)) %>%
    mutate(
        cumsum = cumsum(defect),
        freq = round(defect / sum(defect), 3),
        cum_freq = cumsum(freq)
    ) %>%
    mutate(category = as.factor(category) %>% fct_reorder(defect))

brks <- unique(d$cumsum)

ggplot(d, aes(x = fct_rev(category))) +
    geom_col(aes(y = defect)) +
    geom_point(aes(y = cumsum)) +
    geom_line(aes(y = cumsum, group = 1)) +
    scale_y_continuous(sec.axis = sec_axis(~. / max(d$cumsum), labels = scales::percent), breaks = brks)
Run Code Online (Sandbox Code Playgroud)

reprex包(v0.2.0)于2018-05-12创建.