R - 使用 ggplot2 一次绘制 4 个变量

Question

我想使用 ggplot 生成具有 4 个不同值的图。在下面的示例数据框中，我有 4 个颜色，我想将它们全部绘制在一个图中。我想让“Code”为x轴，“Cor”为y轴，“Vari”用不同的颜色显示，“Con”用不同的符号显示。

我知道如何用 4 列中的 3 列绘制它，到目前为止我只绘制了 2 个不同的图，一个只有“Vari”，一个只有“Con”。但我想把它们结合起来。我试过了：

library(ggplot2)
library(scales)
library(dplyr)

data %>% 
  mutate(bin = Cor < 0) %>%
  
  # plot the data using a facet_grid with free y scales
  ggplot(aes(x = Code, y = Cor, fill = Con, shape = Vari) +
  facet_grid(bin ~ ., scale='free_y') +
  theme(legend.position="bottom") +
  theme(axis.text.x = element_text(angle=90, vjust=0.6)) + 
  theme(strip.text.y = element_blank())

但我想我必须以不同的方式使用这些形状。我也想手动选择颜色和形状，我知道我必须添加

scale_fill_manual(values=c())

对于颜色，但我在形状上苦苦挣扎。

structure(list(Vari = c("PM", "TMK", "VPM", 
                             "TMK", "TXK", "TNK", "TGK", "VPM", "TMK", 
                             "TXK", "TNK", "TGK", "VPM", "TMK", "VPM", 
                             "TMK", "TNK", "TGK", "VPM", "TMK", "TXK", 
                             "TNK", "TGK", "VPM", "TNK", "TGK", "VPM", 
                             "TMK", "TXK", "TNK", "TGK", "TNK", "TGK", 
                             "TMK", "TXK", "TNK", "TGK"), Code = c("R10", 
                                                                                         "J06", "J20-J22", "J20-J22", "J20-J22", "J20-J22", "J20-J22", 
                                                                                         "J20-J22", "J20-J22", "J20-J22", "J20-J22", "J20-J22", "J06", 
                                                                                         "J06", "J20", "J20", "J20", "J20", "J20-J22", "J20-J22", "J20-J22", 
                                                                                         "J20-J22", "J20-J22", "J20", "J20", "J20", "J20-J22", "J20-J22", 
                                                                                         "J20-J22", "J20-J22", "J20-J22", "H00-H06", "H00-H06", "B85-B89", 
                                                                                         "B85-B89", "I20-I25", "I20-I25"), Corr = c(-0.569, -0.5125, 
                                                                                                                                             -0.5739, -0.5843, -0.5603, -0.5744, -0.5547, -0.6168, -0.5897, 
                                                                                                                                             -0.5458, -0.5867, -0.5628, -0.5047, -0.5086, -0.5172, -0.512, 
                                                                                                                                             -0.5229, -0.5257, -0.6172, -0.6003, -0.5599, -0.602, -0.5912, 
                                                                                                                                             -0.5032, -0.5121, -0.5187, -0.5966, -0.59, -0.5661, -0.5879, 
                                                                                                                                             -0.5589, 0.5104, 0.5758, 0.5491, 0.528, -0.5153, -0.5516), Con = c("Hi", 
                                                                                                                                                                                                                      "Eg", "Eg", "Eg", "Eg", "Eg", "Eg", "WFX", 
                                                                                                                                                                                                                      "WFX", "WFX", "WFX", "WFX", "WFM", 
                                                                                                                                                                                                                      "WFM", "WFM", "WFM", "WFM", "WFM", 
                                                                                                                                                                                                                      "WFM", "WFM", "WFM", "WFM", "WFM", 
                                                                                                                                                                                                                      "No2", "No2", "No2", "No2", "No2", "No2", 
                                                                                                                                                                                                                      "No2", "No2", "PM25", "PM25", "MAM", "MAM", 
                                                                                                                                                                                                                      "Hi", "Hi")), row.names = c(23L, 35L, 36L, 37L, 38L, 
                                                                                                                                                                                                                                                              39L, 40L, 43L, 44L, 45L, 46L, 47L, 50L, 51L, 52L, 53L, 54L, 55L, 
                                                                                                                                                                                                                                                              58L, 59L, 60L, 61L, 62L, 64L, 65L, 66L, 67L, 68L, 69L, 70L, 71L, 
                                                                                                                                                                                                                                                              74L, 75L, 86L, 87L, 100L, 101L), class = "data.frame")

Answer 1

不太确定问题是什么 - 我觉得从你的问题中你应该知道答案......

我会改用颜色美学，因为有填充的形状不多。

每种美学都有一个 scale_(*aes*)_manual。我已经添加了这个，虽然值 1:6 是相当随机的。

df <- structure(list(Vari = c(
  "PM", "TMK", "VPM",
  "TMK", "TXK", "TNK", "TGK", "VPM", "TMK",
  "TXK", "TNK", "TGK", "VPM", "TMK", "VPM",
  "TMK", "TNK", "TGK", "VPM", "TMK", "TXK",
  "TNK", "TGK", "VPM", "TNK", "TGK", "VPM",
  "TMK", "TXK", "TNK", "TGK", "TNK", "TGK",
  "TMK", "TXK", "TNK", "TGK"
), Code = c(
  "R10",
  "J06", "J20-J22", "J20-J22", "J20-J22", "J20-J22", "J20-J22",
  "J20-J22", "J20-J22", "J20-J22", "J20-J22", "J20-J22", "J06",
  "J06", "J20", "J20", "J20", "J20", "J20-J22", "J20-J22", "J20-J22",
  "J20-J22", "J20-J22", "J20", "J20", "J20", "J20-J22", "J20-J22",
  "J20-J22", "J20-J22", "J20-J22", "H00-H06", "H00-H06", "B85-B89",
  "B85-B89", "I20-I25", "I20-I25"
), Corr = c(
  -0.569, -0.5125,
  -0.5739, -0.5843, -0.5603, -0.5744, -0.5547, -0.6168, -0.5897,
  -0.5458, -0.5867, -0.5628, -0.5047, -0.5086, -0.5172, -0.512,
  -0.5229, -0.5257, -0.6172, -0.6003, -0.5599, -0.602, -0.5912,
  -0.5032, -0.5121, -0.5187, -0.5966, -0.59, -0.5661, -0.5879,
  -0.5589, 0.5104, 0.5758, 0.5491, 0.528, -0.5153, -0.5516
), Con = c(
  "Hi",
  "Eg", "Eg", "Eg", "Eg", "Eg", "Eg", "WFX",
  "WFX", "WFX", "WFX", "WFX", "WFM",
  "WFM", "WFM", "WFM", "WFM", "WFM",
  "WFM", "WFM", "WFM", "WFM", "WFM",
  "No2", "No2", "No2", "No2", "No2", "No2",
  "No2", "No2", "PM25", "PM25", "MAM", "MAM",
  "Hi", "Hi"
)), row.names = c(
  23L, 35L, 36L, 37L, 38L,
  39L, 40L, 43L, 44L, 45L, 46L, 47L, 50L, 51L, 52L, 53L, 54L, 55L,
  58L, 59L, 60L, 61L, 62L, 64L, 65L, 66L, 67L, 68L, 69L, 70L, 71L,
  74L, 75L, 86L, 87L, 100L, 101L
), class = "data.frame")

library(tidyverse)

df %>%
  mutate(bin = Corr < 0) %>%
  ggplot(aes(x = Code, y = Corr, color = Con, shape = Vari)) +
  geom_point() +
  colorblindr::scale_color_OkabeIto() +
  scale_shape_manual(values = 1:6) +
  facet_grid(bin ~ ., scale = "free_y") +
  theme(
    legend.position = "bottom",
    axis.text.x = element_text(angle = 90, vjust = 0.6),
    strip.text.y = element_blank()
  )

^{由 reprex package (v2.0.0)}

于 2021-04-19 创建

R - 使用 ggplot2 一次绘制 4 个变量

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