Dplyr - 按组变量排列一个grouping_df [英] Dplyr - Arrange a grouped_df by group variable not working

问题描述

我有一个data.frame，其中包含客户名称，年份和每年的几个收入。

I have a data.frame that contains client names, years, and several revenue numbers from each year.

df <- data.frame(client = rep(c("Client A","Client B", "Client C"),3), 
                 year = rep(c(2014,2013,2012), each=3), 
                 rev = rep(c(10,20,30),3)
                )

我想要结束一个数据框架，用于统计客户和年度的收入。然后我想按年份排序data.frame，然后按收入下降。

I want to end up with a data.frame that aggregates the revenue by client and year. I then want to sort the data.frame by year then by descending revenue.

library(dplyr)
df1 <- df %>% 
        group_by(client, year) %>%
        summarise(tot = sum(rev)) %>%
        arrange(year, desc(tot))

然而，当使用上面的代码 arrange（）函数根本不改变分组的数据框架的顺序。当我运行下面的代码并强制到一个正常的数据框架它的工作。

However, when using the code above the arrange() function doesn't change the order of the grouped data.frame at all. When I run the below code and coerce to a normal data.frame it works.

   library(dplyr)
    df1 <- df %>% 
            group_by(client, year) %>%
            summarise(tot = sum(rev)) %>%
            data.frame() %>%
            arrange(year, desc(tot))

每次尝试通过分组变量分组_df时，我需要这样做？

Am I missing something or will I need to do this every time when trying to arrange a grouped_df by a grouped variable?

R版本：3.1 .1
dplyr包版本：0.3.0.2

R Version: 3.1.1 dplyr package version: 0.3.0.2

推荐答案

尝试切换您的 group_by 语句：

df %>% 
  group_by(year, client) %>%
  summarise(tot = sum(rev)) %>%
  arrange(year, desc(tot))

我认为安排是在组内订购;在总结之后，最后一个组被删除，所以这意味着在您的第一个例子中，它正在客户端组中排列。将订单切换到 group_by（年，客户端）似乎解决了它，因为客户端组在总结。

I think arrange is ordering within groups; after summarize, the last group is dropped, so this means in your first example it's arranging rows within the client group. Switching the order to group_by(year, client) seems to fix it because the client group gets dropped after summarize.

或者，还有 ungroup（） function

Alternatively, there is the ungroup() function

df %>% 
  group_by(client, year) %>%
  summarise(tot = sum(rev)) %>%
  ungroup() %>%
  arrange(year, desc(tot))

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