我有一个Dataframe df和一个列表li,我的dataframe列包含:
Student Score Date
A 10 15-03-19
C 11 16-03-19
A 12 16-03-19
B 10 16-03-19
A 9 17-03-19
我的列表包含所有学生的姓名li = [A,B,C] 如果某天某天还没有学生来,则在分数值为0的数据框中插入该学生的姓名
我的最终数据框应为:
Student Score Date
A 10 15-03-19
B 0 15-03-19
C 0 15-03-19
C 11 16-03-19
A 12 16-03-19
B 10 16-03-19
A 9 17-03-19
B 0 17-03-19
C 0 17-03-19
答案 0 :(得分:2)
将DataFrame.reindex
与MultiIndex.from_product
一起使用:
li = list('ABC')
mux = pd.MultiIndex.from_product([df['Date'].unique(), li], names=['Date', 'Student'])
df = df.set_index(['Date', 'Student']).reindex(mux, fill_value=0).reset_index()
print (df)
Date Student Score
0 15-03-19 A 10
1 15-03-19 B 0
2 15-03-19 C 0
3 16-03-19 A 12
4 16-03-19 B 10
5 16-03-19 C 11
6 17-03-19 A 9
7 17-03-19 B 0
8 17-03-19 C 0
替代方法是使用DataFrame.merge
和product
创建的帮助器DataFrame左连接,最后用fillna
替换缺少的值:
from itertools import product
df1 = pd.DataFrame(list(product(df['Date'].unique(), li)), columns=['Date', 'Student'])
df = df1.merge(df, how='left').fillna(0)
print (df)
Date Student Score
0 15-03-19 A 10.0
1 15-03-19 B 0.0
2 15-03-19 C 0.0
3 16-03-19 A 12.0
4 16-03-19 B 10.0
5 16-03-19 C 11.0
6 17-03-19 A 9.0
7 17-03-19 B 0.0
8 17-03-19 C 0.0