根据数据框中日期时间的时间做出决定

Making decisions based on the times of datetime in a dataframe

我是编程新手 python。经过数小时的研究,我想向社区寻求帮助。我想使用数据回测基于伦敦时段开始的交易策略。

我有一个数据框:

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 28766 entries, 0 to 28765
Data columns (total 6 columns):
| #  | Column | Non-Null Count  |Dtype   |      
|--- |------ |--------------  |----- |        
| 0  |Time   |28766 non-null  |datetime64[ns]|
| 1  |Open   |28766 non-null  |float64 |
| 2 |...|

|    |Time                  |Open    | High   | Low    |Close   |Volume  |
|--- |--------------------- |------- |------- |------- |------- | ------|
|8   |2017-05-23 08:00:00   |2180.7  |2187.2  |2139.2  | 2170.2 | 97.0  |

现在我想定义一个函数来识别其中包含 08:00 GMT 的每一行:

def LondonSession(df):
df = df.copy()
for t in df['Time']:
    if df[df['Time'].dt.hour == (8)]:
        df['StopLoss'] = technicals(df)['atr'] * (-1)
        df['TakeProfit'] = technicals(df)['atr'] * (2)
    else: 
        df['StopLoss'] = technicals(df)['atr'] * (0)
        df['TakeProfit'] = technicals(df)['atr'] * (0)
return df

print(LondonSession(df)[0:10])

不幸的是,我不知道如何解决错误消息:

ValueError                                Traceback (most recent call last) Input In [204], in <module>
      9             df['TakeProfit'] = technicals(df)['atr'] * (0)
     10     return df
---> 11 print(LondonSession(df)[0:10])

Input In [204], in LondonSession(df)
      2 df = df.copy()
      3 for t in df['Time']:
----> 4     if df[df['Time'].dt.hour == (8)]:
      5         df['StopLoss'] = technicals(df)['atr'] * (-1)
      6         df['TakeProfit'] = technicals(df)['atr'] * (2)

File ~\AppData\Local\Programs\Python\Python310\lib\site-packages\pandas\core\generic.py:1537, in NDFrame.__nonzero__(self)    1535 @final    1536 def
__nonzero__(self):
-> 1537     raise ValueError(    1538         f"The truth value of a {type(self).__name__} is ambiguous. "    1539         "Use a.empty, a.bool(), a.item(), a.any() or a.all()."    1540     )

ValueError: The truth value of a DataFrame is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

推荐任何输入。 提前致谢!

这里的问题是您在第一个 if 条件中写的内容:df[df['Time'].dt.hour == (8)]。此代码不是 return 布尔值,而是一个数据框,其中所选行是属性时间等于 8 的行。

如果您想保留 for 循环结构,则应使用 if t.hour == 8 更改条件。但请记住,对于 pandas,您应该避免使用 for 循环并使用行过滤(您可以在 pandas official tutorial 上阅读更多相关内容)。

我的解决方案是:

test2.loc[test2['Time'].dt.hour == (8), 'TakeProfit'] = (test2['atr'] * (1.5)) test2.loc[test2['Time'].dt.hour == (8), 'StopLoss'] = (test2['atr'] * (-1)) test2.loc[test2['Time'].dt.hour != (8), 'TakeProfit'] = (0) test2.loc[test2['Time'].dt.hour != (8), 'StopLoss'] = (0)

我在这篇文章中读到:enter link description here

这篇文章描述了我的问题的更多选项。但是我第一次成功了。