使用python为分组数据创建新变量

您可以使用 cumcount

s=df.groupby(['Prod','name']).cumcount().add(1)
df['counter']=s.mask(s.gt(1),0)
df
Out[1417]: 
  Prod Qty  name  counter
0  101   5  john        1
1  102   4  john        1
2  101   1  john        0
3  501   3   Tim        1
4  505   5   Tim        1
5  301   4   Tim        1
6  302   1   Bob        1
7  302   3   Bob        0

更新时间:

s=df.groupby(['name']).cumcount().add(1).le(1).astype(int)
s
Out[1421]: 
0    1
1    0
2    0
3    1
4    0
5    0
6    1
7    0
dtype: int32

更快

df.loc[df.name.drop_duplicates().index,'counter']=1
df.fillna(0)
Out[1430]: 
  Prod Qty  name  counter
0  101   5  john      1.0
1  102   4  john      0.0
2  101   1  john      0.0
3  501   3   Tim      1.0
4  505   5   Tim      0.0
5  301   4   Tim      0.0
6  302   1   Bob      1.0
7  302   3   Bob      0.0

我们可以直接使用字典d并循环创建新条目。

d = {'name': ['john', 'john', 'john', 'Tim', 'Tim', 'Tim','Bob', 'Bob'], 'Prod': ['101', '102', '101', '501', '505', '301', '302', '302'],'Qty': ['5', '4', '1', '3', '5', '4', '1', '3']}
names = set() #store names that have appeared
id = []
for i in d['name']:
    if i in names: #if it appeared add 0
         id.append(0)
    else:
         id.append(1) #add 1 and note that it has appeared
         names.add(i)
d['id'] = id #add entry to your dictionary
df = pandas.DataFrame(data= d)