在dplyr窗口函数中使用多列？ [英] Using multiple columns in dplyr window functions?

问题描述

来自SQL，我希望我能够在dplyr中执行以下操作，这可能吗？

Comming from SQL i would expect i was able to do something like the following in dplyr, is this possible?

# R
tbl %>% mutate(n = dense_rank(Name, Email))

-- SQL
SELECT Name, Email, DENSE_RANK() OVER (ORDER BY Name, Email) AS n FROM tbl

还有 PARTITION BY ？

推荐答案

我确实遇到了这个问题，这是我的解决方案：

I did struggle with this problem and here is my solution:

如果找不到支持多个变量排序的函数，建议您使用 paste（）<>将它们按优先级从左到右连接。 / code>。

In case you can't find any function which supports ordering by multiple variables, I suggest that you concatenate them by their priority level from left to right using paste().

下面是代码示例：

tbl %>%
  mutate(n = dense_rank(paste(Name, Email))) %>%
  arrange(Name, Email) %>%
  view()

此外，我想group_by与SQL中的PARTITION BY等效。

Moreover, I guess group_by is the equivalent for PARTITION BY in SQL.

此解决方案的不足之处在于，您只能按2（或更多）具有相同方向的变量进行排序。如果您需要按方向不同的多个列进行排序，即1个asc和1个desc，建议您尝试以下操作：
基于多个变量的关系计算排名

The shortfall for this solution is that you can only order by 2 (or more) variables which have the same direction. In the case that you need to order by multiple columns which have different direction, saying that 1 asc and 1 desc, I suggest you to try this: Calculate rank with ties based on more than one variable

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