将两个数据框组合在一个图中

Question

我先有两个数据框 percentage_of_worker

Country,Factory,worker_efficiency
USA,factory_A,90
Germany,factory_A,93
France,factory_A,90
USA,factory_B,80
Germany,factory_B,94
France,factory_B,91
USA,factory_C,78
Germany,factory_C,95
France,factory_C,92
USA,factory_D,90
Germany,factory_D,50
France,factory_D,36

和percentage_of_factory

Country,Factory,factory_efficiency
USA,factory_A,95
Germany,factory_A,93
France,factory_A,90
USA,factory_B,96
Germany,factory_B,94
France,factory_B,91
USA,factory_C,97
Germany,factory_C,95
France,factory_C,92
USA,factory_D,90
Germany,factory_D,91
France,factory_D,93

我使用 ggplot 为这两个命令绘制条形图

factory_plot <- ggplot(percentage_of_factory,aes(Factory,factory_efficiency, fill=Country)) + 
  geom_bar(stat="identity", position=position_dodge()) +   geom_text(aes(label = round(factory_efficiency,1)) , position=position_dodge(width=0.9), vjust=-0.25, size = 3) + 
  labs(title = "Factory performance percentage", x = "Factory") 

worker_plot <- ggplot(percentage_of_worker,aes(Factory,worker_efficiency, fill=Country)) + 
  geom_bar(stat="identity", position=position_dodge()) +   geom_text(aes(label = round(worker_efficiency,1)) , position=position_dodge(width=0.9), vjust=-0.25, size = 3) + 
  labs(title = "worker performance percentage", x = "Factory")

我有那些图表

我想将它们组合在一张图表中，坐标轴相同，其中效率列彼此相邻，以显示工厂效率与工人效率之间的差异：例如，在 factory_D 的情况下，法国 "with red" 的工厂效率为 93%，其次是工人效率 36%，德国工厂效率为 91%，其次是工人效率为 50% 等等。对于所有工厂

我试过的是：

c <- percentage_of_factory
c$name <- "factory"
colnames(c)[3] <- "Efficiency"
p <- percentage_of_worker
p$name <- "worker"
colnames(p)[3] <- "Efficiency"
l <- rbind(c, p)
ggplot(l, aes(x=Factory, y=Efficiency , group=Country, fill=Country,  colour=name)) +
  geom_bar(stat="identity", position="dodge") + scale_colour_brewer(palette = "Set1")

但它给出了这张图，但它不是我需要的

帮助将不胜感激

Answer 1

为此，您需要合并 2 个数据帧：

df1=read.table(text="Country,Factory,worker_efficiency
USA,factory_A,90
Germany,factory_A,93
France,factory_A,90
USA,factory_B,80
Germany,factory_B,94
France,factory_B,91
USA,factory_C,78
Germany,factory_C,95
France,factory_C,92
USA,factory_D,90
Germany,factory_D,50
France,factory_D,36",sep=",",header=T)
df2=read.table(text="Country,Factory,factory_efficiency
USA,factory_A,95
Germany,factory_A,93
France,factory_A,90
USA,factory_B,96
Germany,factory_B,94
France,factory_B,91
USA,factory_C,97
Germany,factory_C,95
France,factory_C,92
USA,factory_D,90
Germany,factory_D,91
France,factory_D,93",sep=",",header=T)

因为我们想跟踪哪一个是给 worker/factory 我添加一个额外的列 type 到两个 df:

df1$type<-"worker"
df2$type<-"factory"

然后我们合并它们，为方便起见，将第三列重命名为类似的名称：efficiency

colnames(df1)[3]<-"efficiency"
colnames(df2)[3]<-"efficiency"

我们将它们与 rbind() 绑定（或 bind_rows，如果您习惯 dplyr）

dftot=rbind(df1,df2)

在分组中使用 ggplot2 和 interaction() 我们绘制直方图

ggplot(dftot)+geom_bar(aes(x=Factory,y=efficiency,group=interaction(type,Country),fill=Country,alpha=type),position="dodge",colour="grey",stat="identity")+ scale_alpha_discrete(range= c(0.5, 1))

根据 Axeman 的建议，我添加了 alpha 以区分工人和工厂，以及 scale_alpha_discrete(range= c(0.5, 1)) 允许手动设置 alpha。
coulour="grey" 是可选的，它添加了一个轮廓。

注意： interaction() 中因素的顺序很重要，如果你进行交互（国家/地区，类型），你将有 3 个用于工厂的条，然后是 3 个酒吧的工人。

Answer 2

使用@Haboryme 的数据准备（感谢！）：

ggplot(dftot, aes(x = type, y = efficiency, group = Country, fill = Country))+
  geom_bar(position = "dodge", stat = "identity") + 
  facet_grid(~Factory) +
  theme(axis.title.x = element_blank())

或者：

ggplot(dftot, aes(x = Factory, y = efficiency, fill = type))+
    geom_bar(position = "dodge", stat = "identity") + 
    facet_grid(~Country) +
    theme(axis.title.x = element_blank())

或者：

ggplot(dftot, aes(x = Country, y = efficiency, fill = type))+
    geom_bar(position = "dodge", stat = "identity") + 
    facet_grid(~Factory) +
    theme(axis.title.x = element_blank())

将两个数据框组合在一个图中

combine two data frames in one graph

r

ggplot2

dataframe

geom-bar