使用dplyr选择前n个组,然后绘制其他变量

Question

我有一个数据集,我试图通过计算一个类别来选择前n个,但随后使用数据集中的其他变量进行绘图 - 基本上是前n个的一个聚合级别,但需要返回到完整数据到情节ggplot.

所以在下面的问题中,我想要两个最常见的examNames,然后facetwrap按照计数绘制它们year.

ap <- 
      tribble(
        ~year, ~examName,
        2014, "Statistics",
        2015, "Statistics",
        2016, "Statistics",
        2016, "Statistics",
        2016, "Statistics",
        2016, "Statistics",
        2017, "Statistics",
        2017, "Statistics",
        2017, "Statistics",
        2017, "Statistics",
        2017, "Statistics",
        2013, "Macroeconomics",
        2013, "Macroeconomics",
        2014, "Macroeconomics",
        2015, "Macroeconomics",
        2016, "Macroeconomics",
        2016, "Macroeconomics",
        2016, "Macroeconomics",
        2016, "Macroeconomics",
        2016, "Macroeconomics",
        2017, "Macroeconomics",
        2017, "Macroeconomics",
        2017, "Macroeconomics",
        2017, "Macroeconomics",
        2017, "Macroeconomics",
        2017, "Macroeconomics",
        2013, "Calculus",
        2014, "Calculus",
        2015, "Calculus",
        2016, "Calculus",
        2017, "Calculus",
        2017, "Psychology",
        2017, "Psychology",
        2017, "Psychology",
        2017, "Psychology",
        2017, "Psychology",
        2018, "Psychology",
        2018, "Psychology")


ap_top <- ap %>% 
    count(examName, sort = TRUE) %>% 
    head(2) %>% 
    inner_join(ap, by = "examName") %>% 
    select(-n)

ap_top %>% 
    count(examName, year) %>% 
    ggplot(aes(x = year, y = n, group = examName)) +
    geom_line() +
    facet_wrap(~ examName)

我的想法是获得我的前n个,然后inner_join回到原始数据集.然后使用那个绘图; 基本上使用内部联接作为过滤器.

我知道有更好的方法来做到这一点,我希望有一个更优雅的解决方案!我全都耳朵!给出的示例数据集(对不起,这么久).

Answer 1

你不需要inner_join()我只是在一个单独的声明中确定前两个考试然后过滤那些.

top_exams <- count(ap, examName) %>% 
  top_n(2, n) %>% pull(examName)

ap %>% 
  filter(examName %in% top_exams) %>% 
  count(year, examName) %>% 
  ggplot(aes(x = year, y = n, group = examName)) +
  geom_line() +
  facet_wrap(~ examName)