根据其他列的结果向数据框添加新列

Question

I'm very new to R so I hope my question will be interesting. What I want to do is quite straightforward. Here's a sample of my dataset:

> head(belongliness)
   ACTIVITY_X ACTIVITY_Y ACTIVITY_Z   Event  cluster1    cluster2     cluster3    cluster4
1:         40         47         62 Head-up 0.1900989 0.768225365 0.0160654667 0.025610279
2:         60         74         95 Head-up 0.5392218 0.038558310 0.0064671635 0.415752686
3:         62         63         88 Head-up 0.7953673 0.044981152 0.0067121719 0.152939414
4:         60         56         82 Head-up 0.9941016 0.002608879 0.0003007537 0.002988748
5:         66         61         90 Head-up 0.7027407 0.048318016 0.0079239680 0.241017291
6:         60         53         80 Head-up 0.9541378 0.023338896 0.0024442116 0.020079071

I would like to create a new column "winning cluster" to the right side of column "cluster 4" . Column "winning cluster" will take the highest value among columns "cluster 1" to "cluster 4" for each row and display the index name of that column.

For row 1 that will be cluster 2 , for row 2 cluster 1 , for row 3 cluster 1 etc.

Any help is appreciated!

Answer 1

If the dataset is a data.table class, specify the columns of interest in .SDcols , get the column index of highest value in each row with max.col , use that to select the column name and assign ( := ) as 'winning_cluster'

library(data.table)
belongliness[, winning_cluster := names(.SD)[max.col(.SD)], 
           .SDcols = cluster1:cluster4]

Answer 2

In basic R, this is easily done:

belongliness$`winning cluster` = apply(belongliness[,5:8], 1, max)

where belongliness[,5:8] corresponds to columns cluster1 through cluster4 .

Or if you wanted the index,

belongliness$`winning cluster` = apply(belongliness[,5:8], 1, which.max)
belongliness$`winning cluster` = paste0('cluster', belongliness$`winning cluster`)

Edit: the right hand side of the first line is essentially max.col :

belongliness$`winning cluster` = max.col(belongliness[,5:8])