这实质上是一个背靠背的barplot，类似于使用 ggplot2 在优秀的学习者博客中： http://learnr.wordpress.com/2009/09/24/ggplot2-back-to-back-bar-charts/

你可以在这些图中使用 coord_flip ，但我不确定你是如何得到它以共享上面两张图之间的y轴标签的。下面的代码应该让你足够接近原始数据：

首先创建一个数据样本数据框，将Age列转换为具有所需断点的因子：

  require（ggplot2）
 df 年龄=样本（18:60，1000，替换= TRUE））

 AgesFactor<  -  ordered （df $ Age，break = c（18，seq（20,60,5）），
 include.lowest = TRUE））

 df $年龄  

现在开始构建情节：使用相应的数据子集创建男性和女性情节，压制图例等

  gg  
 gg.male<  -  gg + 
 geom_bar（subset =。（Type =='Male'），
 aes（y = ..count ../ sum（.. count ..），fill =年龄））+ 
 scale_y_continuous（''，formatter ='perc '）+ 
 opts（legend.position ='none'）+ 
 opts（axis.text.y = theme_blank（），axis.title.y = theme_blank（））+ 
 opts（title ='Male'，plot.title = theme_text（size = 10））+ 
 coord_flip（）
 

对于女性情节，使用 trans =reverse ...颠倒'Percent'轴。

  gg.female<  -  gg + 
 geom_bar（subset =。（Type =='Female'），
 aes（y = .. count ../sum(..count ..），fill = Age））+ 
 scale_y_continuous（''，formatter ='percent'，trans ='reverse'）+ 
 opts（legend.position = 'none'）+ 
 opts（axis.text.y = theme_blank（），
 axis.title.y = theme_blank（），
 title ='女'）+ 
 opts（plot.title = theme_text（size = 10））+ 
 coord_flip（）
 

现在使用 geom_text 创建一个只显示年龄段的绘图，但也可以使用一个虚拟的 geom_bar 以确保此图中年龄轴的缩放比例与男性和女性情节中的缩放一致：

  gg.ages  geom_bar（subset =。（Type =='Male'），aes（y = 0，fill = alpha（'white'，0）））+ 
 geom_text（aes（y = 0，label = as.character（Age）），size = 3）+ 
 coord_flip（）+ 
 opts（title ='Ages'，
 legend。 position ='none'，
 axis.text.y = theme_blank（），
 axis.title.y = theme_blank（），
 axis.text.x = theme_blank（），
 axis.ticks = theme_blank（），
 plot.title = theme_text（size = 10））
 

最后，使用Hadley Wickham的书中的方法在网格上排列图：

  grid.newpage（） 

 pushViewport（viewport（layout = grid.layout（1,3，widths = c（.4，.2，.4））））

 vplayout<  - function（x，y）viewport（layout.pos.row = x，layout.pos.col = y）

 pri nt（gg.female，vp = vplayout（1,1））
 print（gg.ages，vp = vplayout（1,2））
 print（gg.male，vp = vplayout（1， 3））
 

I need to draw a pyramid plot, like the one attached.

I found an example using R (but not ggplot) from here, can anyone give me some hint on doing this using ggplot? Thanks!

This is essentially a back-to-back barplot, something like the ones generated using ggplot2 in the excellent learnr blog: http://learnr.wordpress.com/2009/09/24/ggplot2-back-to-back-bar-charts/

You can use coord_flip with one of those plots, but I'm not sure how you get it to share the y-axis labels between the two plots like what you have above. The code below should get you close enough to the original:

First create a sample data frame of data, convert the Age column to a factor with the required break-points:

require(ggplot2)
df <- data.frame(Type = sample(c('Male', 'Female', 'Female'), 1000, replace=TRUE),
                 Age = sample(18:60, 1000, replace=TRUE))

AgesFactor <- ordered( cut(df$Age, breaks = c(18,seq(20,60,5)), 
                           include.lowest = TRUE))

df$Age <- AgesFactor

Now start building the plot: create the male and female plots with the corresponding subset of the data, suppressing legends, etc.

gg <- ggplot(data = df, aes(x=Age))

gg.male <- gg + 
  geom_bar( subset = .(Type == 'Male'), 
            aes( y = ..count../sum(..count..), fill = Age)) +
  scale_y_continuous('', formatter = 'percent') + 
  opts(legend.position = 'none') +
  opts(axis.text.y = theme_blank(), axis.title.y = theme_blank()) + 
  opts(title = 'Male', plot.title = theme_text( size = 10) ) +  
  coord_flip()    

For the female plot, reverse the 'Percent' axis using trans = "reverse"...

gg.female <- gg + 
  geom_bar( subset = .(Type == 'Female'), 
            aes( y = ..count../sum(..count..), fill = Age)) +
  scale_y_continuous('', formatter = 'percent', trans = 'reverse') + 
  opts(legend.position = 'none') +
  opts(axis.text.y = theme_blank(), 
       axis.title.y = theme_blank(), 
       title = 'Female') +
  opts( plot.title = theme_text( size = 10) ) +
  coord_flip()

Now create a plot just to display the age-brackets using geom_text, but also use a dummy geom_bar to ensure that the scaling of the "age" axis in this plot is identical to those in the male and female plots:

gg.ages <- gg + 
  geom_bar( subset = .(Type == 'Male'), aes( y = 0, fill = alpha('white',0))) +
  geom_text( aes( y = 0,  label = as.character(Age)), size = 3) +
  coord_flip() +
  opts(title = 'Ages',
       legend.position = 'none' ,
       axis.text.y = theme_blank(),
       axis.title.y = theme_blank(),
       axis.text.x = theme_blank(),
       axis.ticks = theme_blank(),          
       plot.title = theme_text( size = 10))       

Finally, arrange the plots on a grid, using the method in Hadley Wickham's book:

grid.newpage()

pushViewport( viewport( layout = grid.layout(1,3, widths = c(.4,.2,.4))))

vplayout <- function(x, y) viewport(layout.pos.row = x, layout.pos.col = y)

print(gg.female, vp = vplayout(1,1))
print(gg.ages,   vp = vplayout(1,2))
print(gg.male,   vp = vplayout(1,3))