R / ggplot2 - 如何使用Facet_grid和geom直方图/误差条处理不均匀的分组大小

Question

我希望在代码的最后一行使用+facet_grid(.~sample,scales = "free_x")强制分面，但结果看起来相当不美观（见图2）（依我之见）。我想知道是否有一种方法可以强制geom_histogram的每个条形图具有特定大小，以便无论组是否平衡，条形图都看起来相似。

谢谢， Vivian

示例数据：

samplenote  prod    N   mean    sd  se  sampleprod  sample
Sample A    PRODUCT A   3   0.562103162 0.120039901 0.069305069 Sample A PRODUCT A  Sample A
Sample A    PRODUCT B   3   0.516322045 0.039250354 0.022661203 Sample A PRODUCT B  Sample A
Sample B    PRODUCT A   3   0.504789098 0.055005623 0.031757511 Sample B PRODUCT A  Sample B
Sample B    PRODUCT B   3   0.564334594 0.035685751 0.020603178 Sample B PRODUCT B  Sample B
Sample C    PRODUCT A   3   0.337747481 0.042670562 0.024635861 Sample C PRODUCT A  Sample C
Sample C    PRODUCT B   3   0.470207809 0.012102641 0.006987463 Sample C PRODUCT B  Sample C
Sample C group1 PRODUCT A   3   0.666033925 0   0   Sample C group1 PRODUCT A   Sample C
Sample C group1 PRODUCT B   3   0.775242276 0.017019353 0.009826128 Sample C group1 PRODUCT B   Sample C
Sample C group2 PRODUCT A   3   0.53594287  0.062336653 0.035990084 Sample C group2 PRODUCT A   Sample C
Sample C group2 PRODUCT B   3   0.4705616   0.009122911 0.005267115 Sample C group2 PRODUCT B   Sample C

示例图1：

ggplot(data=test.df,aes(x=samplenote,y=mean,fill=prod))+
geom_bar(stat="identity",col="black",size = 0.4,position='dodge')+
scale_fill_manual(values=c("#B50000","#0039e6"))+
geom_errorbar(data=test.df,aes(x=samplenote,ymax=mean+sd,ymin=mean,width=.2),position=position_dodge(.9),colour="black",size = 0.4)+
theme_classic()+
theme(axis.text=element_text(colour="black"))+
theme(axis.ticks=element_line(colour="black"))+
    coord_cartesian(ylim=c(0,1.13),expand = TRUE)+
scale_y_continuous(expand=c(0,0),breaks=c(0,0.25,0.5,0.75,1))+
ylab("g/g prod")+
xlab("")+
theme(legend.title=element_blank())+
theme(axis.line=element_line(size=0.4))

图1 图2

编辑

Brian 给出的解决方案：

ggplot(data=test.df,aes(x=samplenote,y=mean,fill=prod))+
geom_bar(stat="identity",col="black",size = 0.4,position='dodge')+
scale_fill_manual(values=c("#B50000","#0039e6"))+
geom_errorbar(data=test.df,aes(x=samplenote,ymax=mean+sd,ymin=mean,width=.2),position=position_dodge(.9),colour="black",size = 0.4)+
theme_classic()+
theme(axis.text=element_text(colour="black"))+
theme(axis.ticks=element_line(colour="black"))+
    coord_cartesian(ylim=c(0,1.13),expand = TRUE)+
scale_y_continuous(expand=c(0,0),breaks=c(0,0.25,0.5,0.75,1))+
ylab("g/g prod")+
xlab("")+
theme(legend.title=element_blank())+
theme(axis.line=element_line(size=0.4))+facet_grid(.~sample,scales = "free_x",space="free_x")

展示图3

- Vivi

Answer 1

您需要使用+ facet_grid（〜样本，scales =“free_x”，space =“free_x”）。 space参数调整分面大小，以使条形图宽度保持一致（或更精确地说，使X轴上刻度之间的间距相同）。

require(dplyr)
data_frame(x = c("a", "a", "b", "b", "c", "c"),
           y = runif(length(x)),
           sample = rep(c("A", "B"), 3),
           grouping = c(1, 1, 1, 1, 2, 2)) %>% 
  ggplot(aes(x, y, fill = sample)) + geom_bar(stat = "identity", position = "dodge") + 
  facet_grid(~grouping, space = "free_x", scales = "free_x")

编辑：

有时候你可能会发现缺少数据，导致柱状图不平衡：

data_frame(x = c("a", "a", "b", "b", "c", "c"),
           y = runif(length(x)),
           sample = rep(c("A", "B"), 3),
           grouping = c(1, 1, 1, 2, 2, 2)) %>% 
  ggplot(aes(x, y, fill = sample)) + geom_bar(stat = "identity", position = "dodge") + 
  facet_grid(~grouping, space = "free_x", scales = "free_x")

解决这个问题的方法是使用tidyr包，它可以让你包含显式的NA值，这样就可以为缺失的柱形图留出空间。

data_frame(x = c("a", "a", "b", "b", "c", "c"),
           y = runif(length(x)),
           sample = rep(c("A", "B"), 3),
           grouping = c(1, 1, 1, 2, 2, 2)) %>% 
  group_by(grouping) %>% 
  tidyr::complete(crossing(sample, x)) %>% 
  ggplot(aes(x, y, fill = sample)) + geom_bar(stat = "identity", position = "dodge") + 
  facet_grid(~grouping, space = "free_x", scales = "free_x")

- Brian

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谢谢Brian。确实，space = "free_x" 函数! - Vivi

tidyr::complete()中的crossing是不必要的。 - Jake Kaupp