data3 <- data.frame(
  Count=c(61,80,47,54,41,92,14,37,33,17,5,53),
  category=c('M','M','M','M','M','M','M','M','F','F','F','F'), 
  Agecate =c('<=5', '6-14', '15-19','above 20', 
             '<=5', '6-14', '15-19','above 20',
             '<=5', '6-14', '15-19','above 20'))

I want to plot count vs category using a bar plot as

ggplot(data3, aes(x = reorder(category,Count), y = Count, fill = Agecate))  
  geom_bar(stat = "identity",position = "dodge")   theme_bw(base_size = 30) 
  geom_text(aes(label=Count), size=5, position=position_dodge(width=0.9), vjust=-0.25) 
  theme(axis.text.x = element_text(size = 25)) theme(axis.text = element_text(face="bold")) 
  xlab('Woredas') ylab('Number of hh members')  labs(fill='Age group')

How can I improve this figure on the age group sequence? category 6-14 is coming at the end but must come next to <5. And also some counts labeled twice in the bar plot?

CodePudding user response：

Just reorder your variable levels before launching plot, with factor function

data3$Agecate <- factor(data3$Agecate, 
                        levels=c("<=5", "6-14", "15-19", "above 20"))

Concerning double label issue, you have twice each information for 'M' category, only keep one or sum them so you only display labels once or create a third group to discriminate them.

The plot only took the first ones into account for bar height.