geom_bar 和 geom_point 条件颜色

Question

我有一个简单的 geom_bar 和 geom_point，想根据数据中的值对条和点进行着色。我的代码目前如下：

```df <- (Test3)

ggplot(Test3,aes(ques,diff1,subj))+
  geom_bar(stat = "identity")+
  geom_point(aes(x=ques, y= diff2))+
  facet_grid(~subj)

我的图表目前如下所示：

我的数据如下所示：

```# A tibble: 8 x 9
  subj   ques    `%` `sect%`  diff1    ci last_y  diff2    tt
  <chr>  <chr> <dbl>   <dbl>  <dbl> <dbl>  <dbl>  <dbl> <dbl>
1 geog   q1     82.1    83.6  -1.49  10.1     78   4.14  2.1 
2 geog   q2     80      50    30     10.1     54  26    -1.28
3 hist   q1     92.9    83.6   9.21  10.1     NA  NA    NA   
4 hist   q2     85.7    82.8   2.94  10.1     NA  NA    NA   
5 Sports q1     73.8    82.4  -8.61  10.1     95 -21.2   2.97
6 Sports q2     69.2    81.8 -12.6   10.1     12  57.2  -2.59
7 sci    q1     78.6    85.2  -6.66  10.1     87  -8.43 -3   
8 sci    q2     78      50    28     10.1     55  23     2 

我想要的是如果 diff1 >= ci 则条形为绿色，如果 diff1 <= ci, and grey if neither. And for the points to be green if tt >= 1.96 则条形为红色，如果 tt <= 1.96, and grey if neither. Would be grateful for assistance.

条形为红色

Answer 1

这可以像这样实现：

1. 根据您的条件，使用例如，将带有颜色的新变量添加到您的数据集中

   dplyr::mutate

   和

   dplyr::case_when

2. 将这些新变量映射到

   color

   或

   fill

   。
3. 利用

   scale_color/fill_identity

library(ggplot2)
library(dplyr)

Test3 <- Test3 %>%
  mutate(
    fill = case_when(
      diff1 >= ci ~ "green",
      diff1 < ci ~ "red",
      TRUE ~ "grey"
    ),
    color = case_when(
      tt >= 1.96 ~ "green",
      tt < 1.96 ~ "red",
      TRUE ~ "grey"
    )
  )

ggplot(Test3, aes(ques, diff1, subj)) +
  geom_col(aes(fill = fill)) +
  geom_point(aes(x = ques, y = diff2, color = color)) +
  scale_color_identity() +
  scale_fill_identity() +
  facet_grid(~subj)
#> Warning: Removed 2 rows containing missing values (geom_point).

数据

Test3 <- structure(list(subj = c(
  "geog", "geog", "hist", "hist", "Sports",
  "Sports", "sci", "sci"
), ques = c(
  "q1", "q2", "q1", "q2", "q1",
  "q2", "q1", "q2"
), `%` = c(
  82.1, 80, 92.9, 85.7, 73.8, 69.2,
  78.6, 78
), `sect%` = c(
  83.6, 50, 83.6, 82.8, 82.4, 81.8, 85.2,
  50
), diff1 = c(-1.49, 30, 9.21, 2.94, -8.61, -12.6, -6.66, 28), ci = c(10.1, 10.1, 10.1, 10.1, 10.1, 10.1, 10.1, 10.1), last_y = c(
  78L,
  54L, NA, NA, 95L, 12L, 87L, 55L
), diff2 = c(
  4.14, 26, NA, NA,
  -21.2, 57.2, -8.43, 23
), tt = c(
  2.1, -1.28, NA, NA, 2.97, -2.59,
  -3, 2
)), class = "data.frame", row.names = c(
  "1", "2", "3", "4",
  "5", "6", "7", "8"
))