python - 填充具有重复值的索引中的缺失值

Question

所以基本上我想重新索引一个数据帧，保留重复的索引

考虑以下数据框

Index Block Size Check

6       25        Yes
6       32        No
9       18        Yes
12      17        No
15      23        Yes
15      11        Yes
15      15        Yes

我想得到以下输出

Index Block Size Check

1        0         0
2        0         0
3        0         0
4        0         0
5        0         0
6       25        Yes
6       32        No
7        0         0
8        0         0
9       18        Yes
10       0         0
11       0         0
12      17        No
13       0         0
14       0         0
15      23        Yes
15      11        Yes
15      15        Yes

尝试过这个 data_out = data_in.reindex(pd.RangeIndex(data_in.index.max()+1)).fillna(0) 给出错误

Answer 1

试试这个

import pandas as pd

df = pd.DataFrame({"id":[6,6,9,12,15,15,15],"block":[25,32,18,17,23,11,15],"check":["yes","no","yes","no","yes","yes","yes"]})
df = df.set_index("id")

inds = df.index.unique().values
al=[i for i in range(1,max(inds))]
newdf = pd.DataFrame({"id":list(set(al) - set(inds)),"block":0,"check":0})
newdf=newdf.set_index("id")

alldf = pd.concat([df,newdf]).sort_index()

输出

    block check
id             
1       0     0
2       0     0
3       0     0
4       0     0
5       0     0
6      25   yes
6      32    no
7       0     0
8       0     0
9      18   yes
10      0     0
11      0     0
12     17    no
13      0     0
14      0     0
15     15   yes
15     23   yes
15     11   yes