使用plyr-R进行分块后，从一列中获取具有最高值的行 [英] Get row with highest value from one column after chunking with plyr - R

问题描述

假设我有一个看起来像这样的数据框:

Suppose I have a dataframe that looks like this:

   v1 v2 v3 v4 v5 v6
r1 1  2  2  4  5  9
r2 1  2  2  4  5  10
r3 1  2  2  4  5  7
r4 1  2  2  4  5  12
r5 2  2  2  4  5  9
r6 2  2  2  4  5  10

我想获取v6中具有最高值的行，而该行在v1中具有值1. 由于上一个答案，我知道如何获取v1 = 1的所有行并选择其中的第一行问题:

I would like to get the row with the highest value in v6 that has the value 1 in v1. I know how to get all rows where v1 = 1 and select the first row of that, thanks to this answer to a previous question:

ddply( df , .variables = "v1" , .fun = function(x) x[1,] )

如何更改功能，以便在v6中获得具有最高值的行?

How can I change the function so that I get the row with the highest value in v6?

推荐答案

从先前的结果中，我将使用[使用logical比较器在第一个条件下进行子集化，然后在第二个条件下进行第二个子集化因为正如@sgibb在注释中指出的那样，v6的max值可能不在v1 == 1所在的行中.

From the previous results, I'd use [ to subset on your first condition using logical comparators and then do a second subset on your second condition because as @sgibb points out in the comments, the max value of v6 might not be in a row where v1 == 1.

#  Subset to those rows where v1 == 1
tmp <- df[ df$v1 == 1 , ]

#  Then select those rows where the max value of v6 appears
tmp[ tmp$v6 == max( tmp$v6 ) , ]

如果您想第一次出现，请使用which.max()

If you want the first occurence, use which.max()

这篇关于使用plyr-R进行分块后，从一列中获取具有最高值的行的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！