按偏斜对 facet_wrap 内的直方图进行排序

Question

我对每个国家大约有 1000 个观测值，我使用 facet_wrap 来显示每个国家的 geom_bar，但输出是按字母顺序排列的。我想按偏斜对它们进行聚类或排序（因此最正偏斜的国家在一起并向正态分布国家移动，然后负偏斜国家以最负偏斜结束）而不关注哪些国家更相似彼此。我在想也许 psych::describe() 可能有用，因为它计算偏斜，但我很难弄清楚如何将这些信息添加到 .

任何建议都会有所帮助

Answer 1

如果没有可重现的示例，我无法详细介绍，但这将是我的一般方法。使用 psych::describe() 创建一个国家向量，这些国家/地区从最大正偏度到最小正偏度排序：country_order 。接下来，将数据集中的国家/地区列分解为 country = factor(country, levels = country_order)。当您使用 facet_wrap 时，绘图将按照与 country_order.

相同的顺序显示

Answer 2

经过一些故障排除后，我发现（我认为是）一种有效的方法：

skews <- psych::describe.By(df$DV, df$Country, mat = TRUE) #.BY and mat will produce a matrix that you can use to merge into your df easily
skews %<>%select(group1, mean, skew) %>% sjlabelled::as_factor(., group1) #Turn it into a factor, I also kept country means 
combined <- sort(union(levels(df$Country), levels(skews$group1))) #I was getting an error that my levels were inconsistent even though they were the same (since group1 came from df$Country) which I think was due to having Country reference category Germany which through off the alphabetical sort of group1 so I used [dfrankow's answer][1]
df <- left_join(mutate(df, Country=factor(Country, levels=combined)),
                mutate(skews, Country=factor(group1, levels=combined))) %>% rename(`Country skew` = "skew", `Country mean` = "mean") %>% select(-group1) 

df$`Country skew` <- round(df$`Country skew`, 2)
ggplot(df) +
  geom_bar(aes(x = DV, y=(..prop..)))+ 
  xlab("Scale axis text") + ylab("Proportion") +
  scale_x_continuous()+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1))+

  ggtitle("DV distribution by country mean")+ 
  facet_wrap(~ Country %>% fct_reorder(.,mean), nrow = 2) #this way the reorder that was important for my lm can remain intact

按偏斜对 facet_wrap 内的直方图进行排序

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