熊猫数据框通过时间戳聚合到x分钟箱

我有一些像这样的财务数据时间戳OHCL。现在我想将我的熊猫数据框聚合到1分钟的条中。熊猫有这样的优雅方式吗？熊猫数据框通过时间戳聚合到x分钟箱

2015-08-30 ThatQuantDude

请问您可以添加目前为止的代码和一些示例数据给您吗？ – albert

您可以将它舍入到最近的（x？）分钟，然后执行聚合。也许你可以找到一些灵感[这里]（http://stackoverflow.com/questions/24479577/pandas-timestamp-index-rounding-to-the-nearest-5th-minute） – chappers

'resample'是一种标准的方式 – JohnE

您可能需要做一些处理，但pd.cut（）可以做到这一点。

>>> seconds = [10.5,12.5,22.5,33.5,15.02, 19.26, 35.26] 
>>> bins = [10,11,12,13,14,15,20,25,30,40] 
>>> cats = pd.cut(seconds, bins) 
>>> cats 
[(10, 11], (12, 13], (20, 25], (30, 40], (15, 20], (15, 20], (30, 40]]

一旦你有了这个，你可以通过这个列聚合，但适合你的分析。

来源

2015-08-30 13:53:58 Chris

正如@JohnE提到的，resample是您需要的工具。您可以通过how='ohlc'到resample以获得所需的输出。

import pandas as pd 
import numpy as np 

# generate some artificial data 
# =========================================== 
np.random.seed(0) 
dt_rng = pd.date_range(start='2015-09-02 09:30:00', end='2015-09-02 15:59:59', freq='s') 
df = pd.DataFrame(100+np.random.randn(len(dt_rng)).cumsum(), columns=['px'], index=dt_rng) 
print(df) 

          px 
2015-09-02 09:30:00 101.7641 
2015-09-02 09:30:01 102.1642 
2015-09-02 09:30:02 103.1429 
2015-09-02 09:30:03 105.3838 
2015-09-02 09:30:04 107.2514 
2015-09-02 09:30:05 106.2741 
2015-09-02 09:30:06 107.2242 
2015-09-02 09:30:07 107.0729 
...      ... 
2015-09-02 15:59:52 79.0222 
2015-09-02 15:59:53 81.2040 
2015-09-02 15:59:54 81.6277 
2015-09-02 15:59:55 82.3117 
2015-09-02 15:59:56 83.0102 
2015-09-02 15:59:57 82.7588 
2015-09-02 15:59:58 81.0294 
2015-09-02 15:59:59 81.3962 

[23400 rows x 1 columns] 

# processing 
# ======================= 
df.resample('1min', how='ohlc') 

          px        
         open  high  low  close 
2015-09-02 09:30:00 101.7641 113.8188 101.7641 104.6000 
2015-09-02 09:31:00 103.9276 115.9134 96.2217 115.9134 
2015-09-02 09:32:00 116.2898 120.5850 115.1904 116.7901 
2015-09-02 09:33:00 116.4361 116.5853 108.7353 111.4434 
2015-09-02 09:34:00 110.8060 110.8060 99.6007 108.2589 
2015-09-02 09:35:00 106.9523 108.6105 92.8644 93.4848 
2015-09-02 09:36:00 94.1833 95.6041 84.2610 91.4362 
2015-09-02 09:37:00 92.3657 92.9479 80.2402 85.0347 
...      ...  ...  ...  ... 
2015-09-02 15:52:00 64.6560 69.4697 56.4659 69.1167 
2015-09-02 15:53:00 69.3775 73.6731 64.6894 73.6731 
2015-09-02 15:54:00 74.6119 81.2891 67.9659 78.4973 
2015-09-02 15:55:00 78.9224 81.8589 72.9847 77.1010 
2015-09-02 15:56:00 77.7440 91.1469 77.7440 88.8073 
2015-09-02 15:57:00 88.9114 90.8509 83.8462 87.7416 
2015-09-02 15:58:00 88.2430 89.0107 80.5122 87.0581 
2015-09-02 15:59:00 87.1443 87.1443 77.6822 81.3962 

[390 rows x 4 columns]

来源

2015-08-30 16:32:53

熊猫数据框通过时间戳聚合到x分钟箱

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