python - Pandas - 使用前一列的聚合创建一个新列
问题描述
我有一个包含 2 列的数据框:
CLASS STUDENT
'Sci' 'Francy'
'math' 'Alex'
'math' 'Arthur'
'math' 'Katy'
'eng' 'Jack'
'eng' 'Paul'
'eng' 'Francy'
我想为“数学”班的所有学生添加一个新列
CLASS STUDENT NEW_COL
'Sci' 'Francy' NaN
'math' 'Alex' 'Alex', 'Arthur, Katy'
'math' 'Arthur' 'Alex', 'Arthur, Katy'
'math' 'Katy' 'Alex', 'Arthur, Katy'
'eng' 'Jack' NaN
'eng' 'Paul' NaN
'eng' 'Francy' NaN
我一直在尝试这样的事情,但我并没有走得太远:
def get_all_students(class_series, df):
return df.groupby(['CLASS','STUDENT']).size().rest_index()['CLASS'== measurement].tolist()
...
df['NEW_COL'] = np.where(df['CLASS']=='math', get_all_students(df['CLASS'],df),np.NaN)
解决方案
IIUC 使用groupby
+条件赋值transform
df.loc[df.CLASS=='math','New']=df.groupby('CLASS').STUDENT.transform(','.join)
df
Out[290]:
CLASS STUDENT New
0 Sci Francy NaN
1 math Alex Alex,Arthur,Katy
2 math Arthur Alex,Arthur,Katy
3 math Katy Alex,Arthur,Katy
4 eng Jack NaN
5 eng Paul NaN
6 eng Francy NaN
更多信息,因为我计算了所有分组groupby
,所以您可以全部分配它们,或者只选择您需要的条件分配
df.groupby('CLASS').STUDENT.transform(','.join)
Out[291]:
0 Francy
1 Alex,Arthur,Katy
2 Alex,Arthur,Katy
3 Alex,Arthur,Katy
4 Jack,Paul,Francy
5 Jack,Paul,Francy
6 Jack,Paul,Francy
Name: STUDENT, dtype: object