python-3.x - Python 中的重采样

Question

我最近参加了一项测试，其中要求我为 Data Sheet 构建一个筛选器。 。 问题如下:

Build a Screener on the data sheet attached. 
The strategy workflow is as follows:-
•   Convert 1 minute time frame data into 15 minutes
•   If low of candle is less than previous low we enter short position, with 2 exit criteria’s
    o   Exit at end of day
    o   Exit if the high of previous candle is broken

我在重新采样数据时遇到问题。
我是初学者，请帮助我!

Link to Github Repository

Answer 1

要重新采样，您需要首先确保数据帧具有 DateTimeIndex 类型的索引。在您自己的情况下，您需要下采样(即较低的频率)，之后您需要在新的采样频率(在您的情况下为15分钟)内聚合值。这是一个工作代码。

#read data as csv
df = pd.read_csv('data.csv',index_col = 'Time')

#convert df index to DataTimeIndex
df.index = pd.to_datetime(df.index)

#downsample and aggregate
df.resample('15T').sum()

结果:

    Open    High    Low Close   Volume
Time                    
2020-08-22 09:15:00 67651.75    68489.75    66555.80    67449.95    20526750
2020-08-22 09:30:00 66925.60    67568.40    66227.60    66917.05    13935600
2020-08-22 09:45:00 66661.35    67223.20    66065.30    66685.30    11484225
2020-08-22 10:00:00 65943.20    66399.60    65396.70    65902.50    8253600
2020-08-22 10:15:00 66893.50    67397.70    66409.60    66904.75    8384775
2020-08-22 10:30:00 66306.30    66784.25    65789.65    66274.60    7927350
2020-08-22 10:45:00 66410.70    66873.80    65964.20    66424.20    7811550
2020-08-22 11:00:00 65391.45    65818.80    64933.00    65408.95    7302525
2020-08-22 11:15:00 62587.45    63031.15    62059.35    62522.10    6503775
2020-08-22 11:30:00 62369.40    62891.20    61854.70    62387.40    7074825
2020-08-22 11:45:00 63602.35    64068.20    63132.15    63613.05    7082175
2020-08-22 12:00:00 63347.25    63814.55    62903.80    63342.15    6986250
2020-08-22 12:15:00 62588.20    63128.45    62165.75    62655.05    7644375
2020-08-22 12:30:00 64288.35    64769.35    63759.40    64241.20    7598400
2020-08-22 12:45:00 61430.25    61916.45    60898.85    61379.00    8495775
2020-08-22 13:00:00 61137.65    61740.60    60630.45    61213.70    10142250
2020-08-22 13:15:00 61139.60    61723.20    60493.55    61092.30    9513900
2020-08-22 13:30:00 62049.05    62659.50    61437.50    62044.85    10065750
2020-08-22 13:45:00 64004.35    64515.00    63334.60    63936.95    7864125
2020-08-22 14:00:00 63347.80    63923.20    62694.10    63284.55    9224025
2020-08-22 14:15:00 61649.90    62177.70    60951.70    61551.35    8542350
2020-08-22 14:30:00 61993.75    62647.80    61423.70    62058.45    9870600
2020-08-22 14:45:00 62134.75    62697.90    61474.25    62062.55    10302600
2020-08-22 15:00:00 62679.55    63249.90    62063.75    62676.35    12184050
2020-08-22 15:15:00 62727.55    63091.80    62329.15    62717.75    11147250