Note: This is similar to pandas df.groupby(["column"])["colNames"]
Examples
Obtain the column to perform group aggregate operation on
constdfd=require("danfojs-node")letdata={A: ['foo','bar','foo','bar','foo','bar','foo','foo'],B: ['one','one','two','three','two','two','one','three'],C: [1,3,2,4,5,2,6,7],D: [3,2,4,1,5,6,7,8]}letdf=newdfd.DataFrame(data)letgrp=df.groupby(["A"])//select single columnletgrpColumnC=grp.col(["C"])// convert grouop internal data to dataFramegrpColumnC.apply(x=>x).print()//select multiple columnletgrpColumnBD=grp.col(["B","D"])grpColumnBD.apply(x=>x).print()
Apparently the output are not that useful unless you perform some operations like max(), count() and the likes.