python - 你如何清理和转发用 Pandas 填充多天的 1 分钟时间序列？

Question

我有一个 csv 文件，其中包含跨越多天的 1 分钟股票数据。每天从 9:30 到 16:00。

时间序列中的某些分钟缺失:(此处缺少 2013-09-16 09:32:00 和 2013-09-17 09:31:00)

2013-09-16 09:30:00,461.01,461.49,461,461,183507
2013-09-16 09:31:00,460.82,461.6099,460.39,461.07,212774
2013-09-16 09:33:00,460.0799,460.88,458.97,459.2401,207880
2013-09-16 09:34:00,458.97,460.08,458.8,460.04,148121
...
2013-09-16 15:59:00,449.72,450.0774,449.59,449.95,146399
2013-09-16 16:00:00,450.12,450.12,449.65,449.65,444594
2013-09-17 09:30:00,448,448,447.5,447.96,173624
2013-09-17 09:32:00,450.6177,450.9,449.05,449.2701,268715
2013-09-17 09:33:00,451.39,451.96,450.58,450.7061,197019
...
...

对于 pandas，我如何前向填充系列以便每一分钟都在场？我应该看起来像这样:

2013-09-16 09:30:00,461.01,461.49,461,461,183507
2013-09-16 09:31:00,460.82,461.6099,460.39,461.07,212774
2013-09-16 09:32:00,460.82,461.6099,460.39,461.07,212774 <-- forward filled
2013-09-16 09:33:00,460.0799,460.88,458.97,459.2401,207880
2013-09-16 09:34:00,458.97,460.08,458.8,460.04,148121
...
2013-09-16 15:59:00,449.72,450.0774,449.59,449.95,146399
2013-09-16 16:00:00,450.12,450.12,449.65,449.65,444594
2013-09-17 09:30:00,448,448,447.5,447.96,173624
2013-09-17 09:31:00,448,448,447.5,447.96,173624 <-- forward filled
2013-09-17 09:32:00,450.6177,450.9,449.05,449.2701,268715
2013-09-17 09:33:00,451.39,451.96,450.58,450.7061,197019
...

它还需要考虑是否连续丢失了多分钟...

Answer 1

所以我将你的前 4 行复制到一个数据框中:

Out[49]:
                    0         1         2       3         4       5
0 2013-09-16 09:30:00  461.0100  461.4900  461.00  461.0000  183507
1 2013-09-16 09:31:00  460.8200  461.6099  460.39  461.0700  212774
2 2013-09-16 09:33:00  460.0799  460.8800  458.97  459.2401  207880
3 2013-09-16 09:34:00  458.9700  460.0800  458.80  460.0400  148121

然后

df1 = df.set_index(keys=[0]).resample('1min', fill_method='ffill')
df1

Out[52]:
                            1         2       3         4       5
0                                                                
2013-09-16 09:30:00  461.0100  461.4900  461.00  461.0000  183507
2013-09-16 09:31:00  460.8200  461.6099  460.39  461.0700  212774
2013-09-16 09:32:00  460.8200  461.6099  460.39  461.0700  212774
2013-09-16 09:33:00  460.0799  460.8800  458.97  459.2401  207880
2013-09-16 09:34:00  458.9700  460.0800  458.80  460.0400  148121

这还将处理多个缺失值并向前填充它们。

所以如果我有这样的数据

2013-09-17 09:30:00,448,448,447.5,447.96,173624
2013-09-17 09:33:00,451.39,451.96,450.58,450.7061,197019

然后做和之前一样的事情:

Out[55]:
                          1       2       3         4       5
0                                                            
2013-09-17 09:30:00  448.00  448.00  447.50  447.9600  173624
2013-09-17 09:31:00  448.00  448.00  447.50  447.9600  173624
2013-09-17 09:32:00  448.00  448.00  447.50  447.9600  173624
2013-09-17 09:33:00  451.39  451.96  450.58  450.7061  197019

这里的关键是你必须有一个日期时间索引，如果你想把它作为一个列，那么你可以设置 drop=False在 set_index .