我有一个数据框,其中包含位置ID,商店名称和商店收入。我想确定单位面积收入最高的商店
我为此编写了代码,但不确定是否有更好的方法来处理这种情况
import pandas as pd
dframe=pd.DataFrame({"Loc_Id":[1,2,2,1,2,1,3,3],"Store":["A","B","C","B","D","B","A","C"],
"Revenue":[50,70,45,35,80,70,90,65]})
#group by location id, then save max per location in new column
dframe["max_value"]=dframe.groupby("Loc_Id")["Revenue"].transform(max)
#create new column by checking if the revenue equal to max revenue
dframe["is_loc_max"]=dframe.apply(lambda x: 1 if x["Revenue"]==x["max_value"] else 0,axis=1)
#drop the intermediate column
dframe.drop(columns=["max_value"],inplace=True)
有没有更好的方法来获取此输出
答案 0 :(得分:2)
通过比较eq
(==
)创建布尔型掩码,并将其转换为integer
s-0, 1
到False, True
:
s = dframe.groupby("Loc_Id")["Revenue"].transform('max')
dframe["max_value"]= s.eq(dframe["Revenue"]).astype(int)
print (dframe)
Loc_Id Store Revenue max_value
0 1 A 50 0
1 2 B 70 0
2 2 C 45 0
3 1 B 35 0
4 2 D 80 1
5 1 B 70 1
6 3 A 90 1
7 3 C 65 0