df = pd.DataFrame({"name": list("ABABCD"), "value": np.arange(6)})
maxes = df.groupby(["name"]).agg("max")
df["maxvalue"]=df["name"].apply(lambda x: maxes.loc[x])
name value maxvalue
0 A 0 2
1 B 1 3
2 A 2 2
3 B 3 3
4 C 4 4
5 D 5 5
For 2 columns, I've tried this but it doesn't work:
import numpy as np
import pandas as pd
df = pd.DataFrame({"name": list("ABABCD"),"name2": list("MNOMNO"), "value": np.arange(6)})
maxes = df.groupby(["name","name2"]).agg("max")
df["maxvalue"]=df[["name","name2"]].apply(lambda x: maxes.loc[x])
