在多个不同的切片上应用聚合函数 [英] Applying an aggregate function over multiple different slices

问题描述

我有一个数据数组，包含一些关于人和项目的信息：

I have a data array that contains some information about people and projects as such:

person_id | project_id | action | time
--------------------------------------
        1 |          1 |      w |    1
        1 |          2 |      w |    2
        1 |          3 |      w |    2
        1 |          3 |      r |    3
        1 |          3 |      w |    4
        1 |          4 |      w |    4
        2 |          2 |      r |    2
        2 |          2 |      w |    3

我想要增加一些名为first_time first_time_project，它们共同标识该人第一次看到任何操作，以及开发人员第一次看到项目上的任何操作。最后，数据应如下所示：

I'd like to augment this data with a couple of more fields called "first_time" and "first_time_project" that collectively identify first time any action by that person was seen and the first time that developer saw any action on the project. In the end, the data should look like this:

person_id | project_id | action | time | first_time | first_time_project
------------------------------------------------------------------------
        1 |          1 |      w |    1 |          1 |                  1
        1 |          2 |      w |    2 |          1 |                  2
        1 |          3 |      w |    2 |          1 |                  2
        1 |          3 |      r |    3 |          1 |                  2
        1 |          3 |      w |    4 |          1 |                  2
        1 |          4 |      w |    4 |          1 |                  4
        2 |          2 |      r |    2 |          2 |                  2
        2 |          2 |      w |    3 |          2 |                  2

我这么做的天真的方式写了几个循环：

My naive way of doing this to write a couple of loops:

for (pid in unique(data$person_id)) {
    data[data$pid==pid, "first_time"] = min(data[data$pid==pid, "time"])
    for (projid in unique(data[data$pid==pid, "project_id"])) {
        data[data$pid==pid & data$project_id==projid, "first_time_project"] = min(data[data$pid==pid & data$project_id==projid, "time"]
    }
}

现在，它没有天才，看到这将是glacially慢双子嵌套循环。 ，我不能找出一种方法来处理这里在R.我可以模仿的组选项SQL。我知道，可能可以帮助，但我不知道如何做多个切片。

Now, it doesn't take a genius to see that this is going to be glacially slow with the doubly nested loops. However, I can't figure out a way to handle this in R. I'm kinda emulating the group by option for SQL. I know that by might be able to help, but I can't figure out how to do multiple slices.

关于如何将我的代码从glacially慢到更快一点的任何提示？我现在对蜗牛很满意。

Any hints on how to take my code from glacially slow to something a bit faster? I'd be happy with a snail right now.

推荐答案

尝试 ave ：

transform(data, 
   first_time = ave(time, person_id, FUN = min),
   first_time_project = ave(time, person_id, project_id, drop = TRUE, FUN = min)
)

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