本文介绍了根据其他列设置列的值的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我有一个看起来像这样的数据框:
I have a data frame which looks like this:
ID Score New.ID New.Score 123 5 456 456 1 789 789 0 123我想给New.ID列提供相同的分数(只是顺序不同).
I would like to give the same scores to the New.ID column (which are just in a different order).
所需结果:
ID Score New.ID New.Score 123 5 456 1 456 1 789 0 789 0 123 5用于重构数据帧的代码:
Code to reconstruct data frame:
ID <- as.factor(c(123,456,789)) Score <- c(5,1,0) New.ID<- as.factor(c(456, 789, 123)) New.Score <- c(1,0,5) dt <- data.frame(ID, Score, New.ID, New.Score)更新
所需的输出:
Group ID Score New.ID New.Score 1 123 5 456 1 1 456 1 789 0 1 789 0 123 5 2 555 1 999 0 2 123 1 123 1 2 999 0 555 1因此,我试图尝试对每个组使用该功能. ID 123在组1中的得分为5,但在组2中其得分为1.而且我只想使用每个组中显示的分数.
So I am trying to attempt to use the function for each group. The ID 123 has score 5 in group 1, but in group 2 it has score 1. And I only want to use the scores that appear within each group.
我尝试使用ave:
mtch <- function(x) { dt[match(x,dt$ID),"Score"] } dt$New.Score <- ave(dt$New.ID, dt$Group, FUN = mtch)但是它给了我NA值.
第二个df的代码:
Group <- as.factor(c(1, 1, 1, 2, 2, 2)) ID <- as.factor(c(123,456,789, 555, 123, 999)) Score <- c(5,1,0, 1,1,0) dt <- data.frame(Group, ID, Score, New.ID)推荐答案
简单的match应该可以解决问题.使用您提供的数据:
A simple match should do the trick. Using the data you provided:
data <- data.frame(ID, Score, New.ID) data$New.Score <- data[match(data$New.ID,data$ID),"Score"]然后检查它是否是我们想要的结果:
And then checking that it's our desired result:
identical(dt,data) #[1] TRUE更多推荐
根据其他列设置列的值
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