我尝试将以下数据框转换为每月数据？
date v1 v2
0 1996-12 1,789.20 1,001.19
1 1997-12 2,077.09 1,218.06
2 1998-12 2,377.18 1,458.75
3 1999-03 406.50 237.90
4 1999-06 954.70 541.20
5 1999-09 1,531.00 NaN
6 1999-12 2,678.82 1,693.13
7 2000-03 449.10 263.40
8 2000-06 1,044.10 599.90
9 2000-09 1,693.40 970.00
10 2000-12 3,161.66 2,049.12
如何使用熊猫来做到这一点？我正在考虑bfill或用0来填写NaN的月份值，如果您有更好的解决方案，感谢您的分享。
答案 0 :(得分：2)
您可以执行以下操作。您也可以将fillna(0)更改为fillna(method='ffill')
df['date']=pd.to_datetime(df['date'])
df.set_index('date').resample('M').last().fillna(0).reset_index()
输出
date v1 v2
0 1996-12-31 1,789.20 1,001.19
1 1997-01-31 0 0
2 1997-02-28 0 0
3 1997-03-31 0 0
4 1997-04-30 0 0
5 1997-05-31 0 0
6 1997-06-30 0 0
7 1997-07-31 0 0
8 1997-08-31 0 0
9 1997-09-30 0 0
10 1997-10-31 0 0
11 1997-11-30 0 0
12 1997-12-31 2,077.09 1,218.06
13 1998-01-31 0 0
14 1998-02-28 0 0
15 1998-03-31 0 0
16 1998-04-30 0 0
17 1998-05-31 0 0
18 1998-06-30 0 0
19 1998-07-31 0 0
20 1998-08-31 0 0
21 1998-09-30 0 0
22 1998-10-31 0 0
23 1998-11-30 0 0
24 1998-12-31 2,377.18 1,458.75
25 1999-01-31 0 0
26 1999-02-28 0 0
27 1999-03-31 406.50 237.90
28 1999-04-30 0 0
29 1999-05-31 0 0
30 1999-06-30 954.70 541.20
31 1999-07-31 0 0
32 1999-08-31 0 0
33 1999-09-30 1,531.00 0
34 1999-10-31 0 0
35 1999-11-30 0 0
36 1999-12-31 2,678.82 1,693.13
37 2000-01-31 0 0
38 2000-02-29 0 0
39 2000-03-31 449.10 263.40
40 2000-04-30 0 0
41 2000-05-31 0 0
42 2000-06-30 1,044.10 599.90
43 2000-07-31 0 0
44 2000-08-31 0 0
45 2000-09-30 1,693.40 970.00
46 2000-10-31 0 0
47 2000-11-30 0 0
48 2000-12-31 3,161.66 2,049.12
答案 1 :(得分：2)
IIUC，试试这个
s = pd.to_datetime(df.date).dt.to_period('M')
df.drop('date',1).set_index(s).resample('M').bfill().reset_index()
Out[266]:
date v1 v2
0 1996-12 1,789.20 1,001.19
1 1997-01 2,077.09 1,218.06
2 1997-02 2,077.09 1,218.06
3 1997-03 2,077.09 1,218.06
4 1997-04 2,077.09 1,218.06
5 1997-05 2,077.09 1,218.06
6 1997-06 2,077.09 1,218.06
7 1997-07 2,077.09 1,218.06
8 1997-08 2,077.09 1,218.06
9 1997-09 2,077.09 1,218.06
10 1997-10 2,077.09 1,218.06
11 1997-11 2,077.09 1,218.06
12 1997-12 2,077.09 1,218.06
13 1998-01 2,377.18 1,458.75
14 1998-02 2,377.18 1,458.75
15 1998-03 2,377.18 1,458.75
16 1998-04 2,377.18 1,458.75
17 1998-05 2,377.18 1,458.75
18 1998-06 2,377.18 1,458.75
19 1998-07 2,377.18 1,458.75
20 1998-08 2,377.18 1,458.75
21 1998-09 2,377.18 1,458.75
22 1998-10 2,377.18 1,458.75
23 1998-11 2,377.18 1,458.75
24 1998-12 2,377.18 1,458.75
25 1999-01 406.50 237.90
26 1999-02 406.50 237.90
27 1999-03 406.50 237.90
28 1999-04 954.70 541.20
29 1999-05 954.70 541.20
30 1999-06 954.70 541.20
31 1999-07 1,531.00 NaN
32 1999-08 1,531.00 NaN
33 1999-09 1,531.00 NaN
34 1999-10 2,678.82 1,693.13
35 1999-11 2,678.82 1,693.13
36 1999-12 2,678.82 1,693.13
37 2000-01 449.10 263.40
38 2000-02 449.10 263.40
39 2000-03 449.10 263.40
40 2000-04 1,044.10 599.90
41 2000-05 1,044.10 599.90
42 2000-06 1,044.10 599.90
43 2000-07 1,693.40 970.00
44 2000-08 1,693.40 970.00
45 2000-09 1,693.40 970.00
46 2000-10 3,161.66 2,049.12
47 2000-11 3,161.66 2,049.12
48 2000-12 3,161.66 2,049.12