ggplot2:在aes(..)和geom_bar(..)中使用`fill =…`.颜色重复 [英] ggplot2: Using `fill = …` in aes(..) and geom_bar(..). The colors repeat

问题描述

这是带有 ggplot 的条形图:

library(ggplot2)
ggplot(subset(dat, Gene=='3_RH2B'), aes(x=Morpho, y=Weights, fill=Model2)) + geom_bar(stat='identity') + ggtitle('RH2B')

我的问题是颜色重复出现，而不是形成一个大块.我希望每个条形图由三个颜色块组成，分别对应于变量 dat $ Model2 的三个级别.我怎样才能做到这一点?ggplot为什么创建此图而不是直接创建我想要的图?

My problem is that the colors repeat instead of forming one big block. I would like that each bar is formed by three blocks of color corresponding to the three levels of the variable dat$Model2. How can I achieve this? Why does ggplot create this graph and not directly the one I'd like?

这是data.frame dat :

Here is the data.frame dat:

      Gene    Morpho Model     Weights Model2
1   1_RH1 Morph_PC1  OUMV 0.081666667   OUMx
2   1_RH1 Morph_PC1   OUM 0.093333333   OUMx
3   1_RH1 Morph_PC1   BM1 0.286666667    BMx
4   1_RH1 Morph_PC1 OUMVA 0.191666667   OUMx
5   1_RH1 Morph_PC1   OU1 0.076666667    OU1
6   1_RH1 Morph_PC1   BMS 0.255000000    BMx
7   1_RH1 Morph_PC1  OUMA 0.013333333   OUMx
8   1_RH1 Morph_PC2   OU1 0.106666667    OU1
9   1_RH1 Morph_PC2   BM1 0.030000000    BMx
10  1_RH1 Morph_PC2   OUM 0.226666667   OUMx
11  1_RH1 Morph_PC2 OUMVA 0.346666667   OUMx
12  1_RH1 Morph_PC2  OUMA 0.238333333   OUMx
13  1_RH1 Morph_PC2  OUMV 0.045000000   OUMx
14  1_RH1 Morph_PC2   BMS 0.003333333    BMx
15  2_LWS Morph_PC1   BM1 0.545000000    BMx
16  2_LWS Morph_PC1   BMS 0.253333333    BMx
17  2_LWS Morph_PC1   OUM 0.061666667   OUMx
18  2_LWS Morph_PC1  OUMV 0.018333333   OUMx
19  2_LWS Morph_PC1  OUMA 0.015000000   OUMx
20  2_LWS Morph_PC1 OUMVA 0.110000000   OUMx
21  2_LWS Morph_PC1   OU1 0.000000000    OU1
22  2_LWS Morph_PC2   OU1 0.136666667    OU1
23  2_LWS Morph_PC2   OUM 0.078333333   OUMx
24  2_LWS Morph_PC2 OUMVA 0.373333333   OUMx
25  2_LWS Morph_PC2   BM1 0.028333333    BMx
26  2_LWS Morph_PC2  OUMV 0.018333333   OUMx
27  2_LWS Morph_PC2  OUMA 0.353333333   OUMx
28  2_LWS Morph_PC2   BMS 0.013333333    BMx
29 3_RH2B Morph_PC1   BM1 0.301666667    BMx
30 3_RH2B Morph_PC1   BMS 0.478333333    BMx
31 3_RH2B Morph_PC1   OU1 0.091666667    OU1
32 3_RH2B Morph_PC1   OUM 0.066666667   OUMx
33 3_RH2B Morph_PC1  OUMA 0.028333333   OUMx
34 3_RH2B Morph_PC1  OUMV 0.023333333   OUMx
35 3_RH2B Morph_PC1 OUMVA 0.008333333   OUMx
36 3_RH2B Morph_PC2   OUM 0.246666667   OUMx
37 3_RH2B Morph_PC2  OUMA 0.171666667   OUMx
38 3_RH2B Morph_PC2  OUMV 0.096666667   OUMx
39 3_RH2B Morph_PC2   BMS 0.106666667    BMx
40 3_RH2B Morph_PC2   OU1 0.213333333    OU1
41 3_RH2B Morph_PC2   BM1 0.140000000    BMx
42 3_RH2B Morph_PC2 OUMVA 0.025000000   OUMx

推荐答案

看来您的data.frame是一个汇总表.在这种情况下，在 geom_bar 命令中使用 stat ='identity'是合适的.除了没有您需要ggplot在摘要表上执行其他聚合.对于第一个堆叠的条形图(MORPH_PC1)，要堆叠的组件是有序的，尽管 stat ='identity'，ggplot将添加适当的权重.但是，如果您更改第一个堆叠条形图的组件顺序，那么它也将包含重复的颜色.例如，将ggplot命令与以下数据框一起使用以查看效果.这是您的数据框，只是 Model2 变量的顺序稍有变化.

It appears that your data.frame is a summary table. In which case, stat = 'identity' could be appropriate within the geom_bar command. Except not. You need ggplot to perform additional aggregations on the summary table. For the first stacked bar (MORPH_PC1), the components to be stacked are ordered, and, despite stat='identity', ggplot will add the appropriate weights. But if you change the order of the components of the first stacked bar, then it too will contain repeated colours. For instance, use your ggplot command with the following data frame to see the effect. It's your data frame except for a slight change in the order for the Model2 variable.

dat = read.table(text = "      Gene    Morpho Model     Weights Model2
29 3_RH2B Morph_PC1   BM1 0.301666667    BMx
32 3_RH2B Morph_PC1   OUM 0.066666667   OUMx
30 3_RH2B Morph_PC1   BMS 0.478333333    BMx
31 3_RH2B Morph_PC1   OU1 0.091666667    OU1
33 3_RH2B Morph_PC1  OUMA 0.028333333   OUMx
34 3_RH2B Morph_PC1  OUMV 0.023333333   OUMx
35 3_RH2B Morph_PC1 OUMVA 0.008333333   OUMx
36 3_RH2B Morph_PC2   OUM 0.246666667   OUMx
37 3_RH2B Morph_PC2  OUMA 0.171666667   OUMx
38 3_RH2B Morph_PC2  OUMV 0.096666667   OUMx
39 3_RH2B Morph_PC2   BMS 0.106666667    BMx
40 3_RH2B Morph_PC2   OU1 0.213333333    OU1
41 3_RH2B Morph_PC2   BM1 0.140000000    BMx
42 3_RH2B Morph_PC2 OUMVA 0.025000000   OUMx", header = TRUE, sep = "")

@Alpha提供的解决方案的其他解决方案:

Additional solutions to the one offered by @Alpha:

在ggplot2命令之外执行其他聚合，然后绘制:

Perform the additional aggregation outside the ggplot2 command, then plot:

datRevised = aggregate(Weights ~ Morpho + Model2, data = dat, FUN = "sum")
ggplot(datRevised, aes(x=Morpho, y=Weights, fill=Model2)) + geom_bar(stat='identity') + ggtitle('RH2B')

或者，在原始数据框上使用 weight 美观(请参见此处以获取一些详细信息-大约在页面的中间).

Or, use the weight aesthetic on the original data frame (see here for some details - about half way down the page).

ggplot(dat, aes(x=Morpho, weight=Weights, fill=Model2)) + geom_bar() + ggtitle('RH2B')

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