R ggplot2阴影和一个绘图中的多个数据点

我测量了两种

化合物
丙酮
和
乙醛
的
排放量
，共测量了116天
九次。我画了一张这样的图：

df%>%
  ggplot(aes(x=days, y=emission))+
  geom_point(color="darkblue", size=3.5) +
  geom_errorbar(aes(ymin=emission, ymax=emission+se), width=.2,
                position=position_dodge(0.05)) +
  labs(color = "", size= "") +
  labs(x = "Incubation time (days)", y = "Production (umol g-1 dw soil h-1)") +
  theme_bw() +
  facet_wrap(vars(compound), scales = "free_y")


测量分为三组：
a
、
b
和
c

我试图在图表中绘制
b组和
c组的平均值（和标准误差）。这个符号必须是不同的

有什么想法吗

数据如下所示

df <- structure(list(compound = c("Acetaldehyde", "Acetaldehyde", "Acetaldehyde", 
"Acetaldehyde", "Acetaldehyde", "Acetaldehyde", "Acetaldehyde", 
"Acetaldehyde", "Acetaldehyde", "Acetone", "Acetone", "Acetone", 
"Acetone", "Acetone", "Acetone", "Acetone", "Acetone", "Acetone"
), days = c(0, 4, 10, 17, 24, 66, 81, 94, 116, 0, 4, 10, 17, 
24, 66, 81, 94, 116), emission = c(26.13, 59.09, 45, 11.41, 6.71, 
0.07, 0, 0.53, 0.56, 28.47, 46.65, 44.03, 56.68, 29.08, 2.73, 
7.72, 0.38, 0.21), se = c(5.88, 11.04, 11.4, 4.31, 3.54, 0.03, 
0, 0.25, 0.31, 7.44, 8.98, 9.92, 22.79, 13.83, 1.2, 6.38, 0.09, 
0.07), group = c("a", "b", "b", "b", "b", "b", "c", "c", "c", 
"a", "b", "b", "b", "b", "b", "c", "c", "c")), row.names = c(NA, 
-18L), class = "data.frame")

---------------------------------更新---------------------------------

我可以看出我在解释我要做的事情时做得很糟糕

数据中有一列名为
组
。在此列中，测量值分为
a
、
b
和
c
。我想在我显示的图的顶部绘制这些组的平均值（其中所有测量值都是。在
a
中只有一个测量值，因此这对这个组没有意义。但是对于
b
组和
c
组，我希望绘制平均值（和标准误差）当然，这些符号需要与我已经绘制的不同

此外，我正在尝试更改每个
组后面的背景颜色，使其具有不同的颜色，类似于我在谷歌上找到的这个图：

.
我编辑了我的答案：

library(ggplot2)
library(magrittr)
library(plotrix)
library(knitr)
library(dplyr)

#creating group b acetaldehyde mean and standart error
b_mean_ald <- mean(df$emission[df$group == "b" & df$compound == "Acetaldehyde"])
b_se_ald <- std.error(df$emission[df$group == "b" & df$compound == "Acetaldehyde"])

#creating group b acetone mean and standart error
b_mean_acet <- mean(df$emission[df$group == "b" & df$compound == "Acetone"])
b_se_acet <- std.error(df$emission[df$group == "b" & df$compound == "Acetone"])

#creating group c acetaldehyde mean and standart error
c_mean_ald <- mean(df$emission[df$group == "c" & df$compound == "Acetaldehyde"])
c_se_ald <- std.error(df$emission[df$group == "c" & df$compound == "Acetaldehyde"])

#creating group c acetone mean and standart error
c_mean_acet <- mean(df$emission[df$group == "c" & df$compound == "Acetone"])
c_se_acet <- std.error(df$emission[df$group == "c" & df$compound == "Acetone"])


# making a dataframe which contains mean and se of each compounds per groups
mean_df <- data.frame(
  compound = c("Acetaldehyde", "Acetaldehyde", "Acetone", "Acetone"),
  days = c(33, 95, 33, 95),
  emission = c(b_mean_ald, c_mean_ald, b_mean_acet, c_mean_acet),
  se = c(b_se_ald, c_se_ald, b_se_acet, c_se_acet), 
  group = c("b", "c", "b", "c")
) 



最终绘图：






如果您想在legend中包含组，您应该做一些技巧：

#final plot with groups and measurments legend
df_fin%>%
  ggplot(aes(x=days, y=emission))+
  labs(color = "", size= "") +
  labs(x = "Incubation time (days)", y = "Production (umol g-1 dw soil h-1)") +
  facet_wrap(vars(compound), scales = "free_y") +
  geom_rect(xmin = -2, xmax = 2.2, ymin = 85, ymax = 100,
            fill="green",alpha = 0.05)+
  geom_rect(xmin = 2.2, xmax = 69, ymin = 85, ymax = 100,
            fill = "yellow", alpha = 0.05) +
  geom_rect(xmin = 69, xmax = 120, ymin = 85, ymax = 100,
            fill="purple",alpha = 0.05) +
  geom_rect(xmin = -2, xmax = 2.2, ymin = -20, ymax = 0,
            fill="green",alpha = 0.05)+
  geom_rect(xmin = 2.2, xmax = 69, ymin = -20, ymax = 0,
            fill = "yellow", alpha = 0.05) +
  geom_rect(xmin = 69, xmax = 120, ymin = -20, ymax = 0,
            fill="purple",alpha = 0.05) +
  geom_rect(aes(xmin = -2, xmax = 2.2, ymin = 0, ymax = 85,
              fill="A", alpha = "D"))+
  geom_rect(aes(xmin = 2.2, xmax = 69, ymin = 0, ymax = 85,
             fill = "B", alpha = "E")) +
  geom_rect(aes(xmin = 69, xmax = 120, ymin = 0, ymax = 85,
              fill="C",alpha = "F"))+
  
  geom_pointrange(aes(x = days, y = emission, ymin = emission, ymax = emission + se, color = category, shape = category, group = category),
                  size = 0.5) +
  scale_color_manual(name = "Measurments", labels = c("Period Mean", "Emission"), 
                     values = c("red", "darkblue")) +
  scale_fill_manual(name = "Groups", labels = c("A", "B","C"), values = c("green", "yellow","purple"))+
  scale_shape_manual(name = "Measurments", labels = c("Period Mean", "Emission"), values = c(17, 19))+
  scale_alpha_manual(name = "Groups", labels = c("A", "B", "C"), values = c(0.05,0.05,0.05)) +
  guides(fill = guide_legend(override.aes = list(alpha = 1)))


使用组和测量图例进行绘图：


在最后一个绘图中，由于带有alpha值的图例的小矩形显示不好，我们在绘图代码末尾使用guides（）函数覆盖图例alpha而不影响主绘图alpha，因此组的图例的alpha值比主绘图的alpha值多。


在此绘图中，我特意将图例组的alpha设置为1，将绘图的alpha设置为0.05，以显示它们之间的差异。您可以为每个图例组设置任何alpha，以使它们更相似

下图显示了图例和绘图的类似alpha：
（通过将绘图alpha设置为0.05，将图例alpha设置为0.2）



---------

您还可以在最后一个绘图的末尾添加
theme_bw（）
以创建边框（我没有在最后一个绘图中包含它）
您可以定义如何将测量分为三组吗？另外变量
daysincubated4
似乎缺失。如果您可以使问题重现，那就太好了。您想将所有三个测量都绘制成图形吗（a、b、c）在一个地块（叠加）或者不同的绘图？你说的背景色是什么意思？谢谢你的更正@Peter。我不确定你说的可复制是什么意思？谢谢你的评论@Killbill！是的，所有内容都应该在一个绘图中。可复制：当其他人将问题中的数据和代码复制到他们的控制台时，代码会产生所述的问题在问题中。请阅读以获得真正有用的指南。@Tiptop，我编辑了我的答案，它有一个包含组和测量符号的图例。geom_rect（x=…）如果不使用aes，则在绘图上绘制一个不会影响轴比例的矩形，因此我们可以将矩形延伸到绘图的最顶部或最底部区域。我使用它们在绘图的上部和下部绘制矩形。但是如果您希望在绘图面板中具有图例的矩形，则应在几何矩形（aes）的辅助部分中添加颜色（x=…）.Geom_-rect（aes（））和Geom_-rect（）在我的绘图中在面板区域有轻微重叠。那么“有点不对劲”是什么意思呢.如果你能发布你的情节，那就容易了fixed@Tiptop，现在您可以在我编辑的答案中看到最终绘图，图例alpha与绘图alpha不同。请完全复制新的最终绘图代码。您可以根据首选的alpha更改它。您可以在指南（）中更改图例的alpha函数位于代码末尾，以及scale_alpha_manual（）中绘图的alpha，代码最后一行前一行。
#final plot with groups and measurments legend
df_fin%>%
  ggplot(aes(x=days, y=emission))+
  labs(color = "", size= "") +
  labs(x = "Incubation time (days)", y = "Production (umol g-1 dw soil h-1)") +
  facet_wrap(vars(compound), scales = "free_y") +
  geom_rect(xmin = -2, xmax = 2.2, ymin = 85, ymax = 100,
            fill="green",alpha = 0.05)+
  geom_rect(xmin = 2.2, xmax = 69, ymin = 85, ymax = 100,
            fill = "yellow", alpha = 0.05) +
  geom_rect(xmin = 69, xmax = 120, ymin = 85, ymax = 100,
            fill="purple",alpha = 0.05) +
  geom_rect(xmin = -2, xmax = 2.2, ymin = -20, ymax = 0,
            fill="green",alpha = 0.05)+
  geom_rect(xmin = 2.2, xmax = 69, ymin = -20, ymax = 0,
            fill = "yellow", alpha = 0.05) +
  geom_rect(xmin = 69, xmax = 120, ymin = -20, ymax = 0,
            fill="purple",alpha = 0.05) +
  geom_rect(aes(xmin = -2, xmax = 2.2, ymin = 0, ymax = 85,
              fill="A", alpha = "D"))+
  geom_rect(aes(xmin = 2.2, xmax = 69, ymin = 0, ymax = 85,
             fill = "B", alpha = "E")) +
  geom_rect(aes(xmin = 69, xmax = 120, ymin = 0, ymax = 85,
              fill="C",alpha = "F"))+
  
  geom_pointrange(aes(x = days, y = emission, ymin = emission, ymax = emission + se, color = category, shape = category, group = category),
                  size = 0.5) +
  scale_color_manual(name = "Measurments", labels = c("Period Mean", "Emission"), 
                     values = c("red", "darkblue")) +
  scale_fill_manual(name = "Groups", labels = c("A", "B","C"), values = c("green", "yellow","purple"))+
  scale_shape_manual(name = "Measurments", labels = c("Period Mean", "Emission"), values = c(17, 19))+
  scale_alpha_manual(name = "Groups", labels = c("A", "B", "C"), values = c(0.05,0.05,0.05)) +
  guides(fill = guide_legend(override.aes = list(alpha = 1)))