combine two data frames in one graph

Question

I have two data frames first 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

and 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

I draw bar plot using ggplot for both using this command

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")

I have those graphs

I would like to combine them in one graph with the same axes where column of efficiency beside each other to show the difference between the factory ans worker efficiency: for example in case of factory_D it will be factory efficiency for France "with red" is 93% followed by the worker efficiency 36% and Germany 91% for factory followed by 50% for worker etc.. for all factories

what I tried is:

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")

but it gave this graph and it is not what I need

Help would be appreciated

Answer 1

To do that you need to combine your 2 dataframes:

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)

Because we want to keep track of which one is for worker/factory I add an extra column type to both df:

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

We then merge them and to make it easy the third column is renamed to a similar name : efficiency

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

We bind them with rbind()(or bind_rows if you're used to dplyr)

dftot=rbind(df1,df2)

Using ggplot2 and interaction() in the grouping we plot the histogram

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))

Following Axeman's suggestion, I added alpha to differentiate worker from factory and scale_alpha_discrete(range= c(0.5, 1)) which allows to set the alphas manually.
coulour="grey" is optional, it adds a contour.

Note: the order of the factor in interaction() matters, if you do interaction(Country,type) you will have 3 bars for the factory followed by 3 bars for the workers.

Answer 2

Using @Haboryme's data prep (thanks!):

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())

Or:

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

Or:

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