熊猫：从CSV

Question

生成日常数据每小时的数据我有每天都有数据如下CSV文件：

DateTime  Price 
10/3/2016 0:00 2.84 
9/30/2016 0:00 2.84 
9/29/2016 0:00 2.98 
9/28/2016 0:00 3.07 

我想每一天创造24小时价格序列上方，每小时的价格将是与从csv文件读取的每日价格相同。

我做了以下内容：

import pandas as pd 
price4mCSV = pd.read_csv(r'C:\Price.csv', index_col='DateTime', parse_dates=['DateTime']).asfreq('1H', method='ffill') 

然而，price4mCSV是空白。

Answer 1

试试这个：

In [125]: df.set_index('DateTime').resample('H').pad() 
Out[125]: 
        Price 
DateTime 
2016-09-28 00:00:00 3.07 
2016-09-28 01:00:00 3.07 
2016-09-28 02:00:00 3.07 
2016-09-28 03:00:00 3.07 
2016-09-28 04:00:00 3.07 
2016-09-28 05:00:00 3.07 
2016-09-28 06:00:00 3.07 
2016-09-28 07:00:00 3.07 
2016-09-28 08:00:00 3.07 
2016-09-28 09:00:00 3.07 
2016-09-28 10:00:00 3.07 
2016-09-28 11:00:00 3.07 
2016-09-28 12:00:00 3.07 
2016-09-28 13:00:00 3.07 
2016-09-28 14:00:00 3.07 
2016-09-28 15:00:00 3.07 
2016-09-28 16:00:00 3.07 
2016-09-28 17:00:00 3.07 
2016-09-28 18:00:00 3.07 
2016-09-28 19:00:00 3.07 
2016-09-28 20:00:00 3.07 
2016-09-28 21:00:00 3.07 
2016-09-28 22:00:00 3.07 
2016-09-28 23:00:00 3.07 
2016-09-29 00:00:00 2.98 
...     ... 
2016-10-02 00:00:00 2.84 
2016-10-02 01:00:00 2.84 
2016-10-02 02:00:00 2.84 
2016-10-02 03:00:00 2.84 
2016-10-02 04:00:00 2.84 
2016-10-02 05:00:00 2.84 
2016-10-02 06:00:00 2.84 
2016-10-02 07:00:00 2.84 
2016-10-02 08:00:00 2.84 
2016-10-02 09:00:00 2.84 
2016-10-02 10:00:00 2.84 
2016-10-02 11:00:00 2.84 
2016-10-02 12:00:00 2.84 
2016-10-02 13:00:00 2.84 
2016-10-02 14:00:00 2.84 
2016-10-02 15:00:00 2.84 
2016-10-02 16:00:00 2.84 
2016-10-02 17:00:00 2.84 
2016-10-02 18:00:00 2.84 
2016-10-02 19:00:00 2.84 
2016-10-02 20:00:00 2.84 
2016-10-02 21:00:00 2.84 
2016-10-02 22:00:00 2.84 
2016-10-02 23:00:00 2.84 
2016-10-03 00:00:00 2.84 

[121 rows x 1 columns] 

或者这个，如果你不希望有DateTime作为索引：

df.set_index('DateTime').resample('H').pad()