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How to extract the row for groupwise maximum in another column of an R data.table object?
To extract the row for groupwise maximum in another column of an R data.table object, can make use of which.max function by defining the grouping column. It means that if we have a categorical/grouping column and a numerical column then we groupwise maximum will be the maximum for each grouping level in the numerical column and we can extract the row based on these two columns. Check out the examples to understand how it works.
Example1
Loading data.table package and creating a data.table object −
> library(data.table)
> x1<-sample(c("A","B","C"),20,replace=TRUE)
> x2<-rpois(20,5)
> x3<-rpois(20,2)
> DT1<-data.table(x1,x2,x3)
> DT1Output
x1 x2 x3
1: B 3 2 2: C 6 0 3: B 4 1 4: C 8 3 5: A 3 6 6: B 5 3 7: C 4 1 8: B 4 0 9: B 5 2 10: C 6 1 11: A 4 1 12: C 5 0 13: B 2 3 14: A 5 0 15: C 8 6 16: A 5 2 17: B 4 2 18: A 3 3 19: C 10 2 20: C 3 2
Extracting groupwise maximum rows from DT1 −
> DT1[,.SD[which.max(x2)],by=x1]
Output
x1 x2 x3 1: B 5 3 2: C 10 2 3: A 5 0
Example2
> y1<-sample(c("Male","Female"),20,replace=TRUE)
> y2<-rnorm(20)
> y3<-rnorm(20)
> DT2<-data.table(y1,y2,y3)
> DT2Output
y1 y2 y3 1: Female 0.09094138 -0.4011408 2: Male -0.51845798 0.9946824 3: Male 0.73189425 0.2013690 4: Male 0.58616939 0.6290771 5: Male 2.53714401 -0.9434801 6: Female -0.98726606 -0.9564542 7: Male 1.28230337 0.2018570 8: Female -0.60125038 1.0522084 9: Female 1.06912678 -0.3825166 10: Female 0.99567103 -0.1200035 11: Male 0.66163046 -0.3596741 12: Male -0.62465260 2.2215039 13: Male 2.09315525 1.4402211 14: Male -1.18256083 0.3528192 15: Male -0.36751044 0.4837127 16: Male -0.23044236 -0.8761699 17: Male -0.84228258 -0.5922790 18: Female 0.80129337 1.5403199 19: Male 0.76037129 -0.4590728 20: Female 0.17482961 0.3189389
Extracting groupwise maximum rows from DT2 −
> DT2[,.SD[which.max(y3)],by=y1]
Output
y1 y2 y3 1: Female 0.8012934 1.540320 2: Male -0.6246526 2.221504
Updated on: 05-Mar-2021
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