以上代码输出获取SPY的日内数据 (2022-05-09 到 2024-04-22)...
成功获取79015条minute数据
获取SPY的日线数据 (2022-05-09 到 2024-04-22)...
成功获取203条day数据
获取SPY的股息数据并过滤...
计算日内数据指标...
Traceback (most recent call last):
File "E:\python课\Lib\site-packages\pandas\core\indexes\datetimes.py", line 603, in get_loc
parsed, reso = self._parse_with_reso(key)
File "E:\python课\Lib\site-packages\pandas\core\indexes\datetimes.py", line 559, in _parse_with_reso
parsed, reso = super()._parse_with_reso(label)
File "E:\python课\Lib\site-packages\pandas\core\indexes\datetimelike.py", line 293, in _parse_with_reso
parsed, reso_str = parsing.parse_datetime_string_with_reso(label, freqstr)
File "pandas/_libs/tslibs/parsing.pyx", line 442, in pandas._libs.tslibs.parsing.parse_datetime_string_with_reso
File "pandas/_libs/tslibs/parsing.pyx", line 666, in pandas._libs.tslibs.parsing.dateutil_parse
pandas._libs.tslibs.parsing.DateParseError: Unknown datetime string format, unable to parse: volume
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "E:\python课\Lib\idlelib\idle.py", line 200, in <module>
intra_data = calculate_metrics(intra_data.copy())
File "E:\python课\Lib\idlelib\idle.py", line 161, in calculate_metrics
df['cum_pv'] = df.groupby('day').transform(
File "E:\python课\Lib\site-packages\pandas\core\groupby\generic.py", line 1815, in transform
return self._transform(
File "E:\python课\Lib\site-packages\pandas\core\groupby\groupby.py", line 2021, in _transform
return self._transform_general(func, engine, engine_kwargs, *args, **kwargs)
File "E:\python课\Lib\site-packages\pandas\core\groupby\generic.py", line 1732, in _transform_general
path, res = self._choose_path(fast_path, slow_path, group)
File "E:\python课\Lib\site-packages\pandas\core\groupby\generic.py", line 1834, in _choose_path
res = slow_path(group)
File "E:\python课\Lib\site-packages\pandas\core\groupby\generic.py", line 1827, in <lambda>
slow_path = lambda group: group.apply(
File "E:\python课\Lib\site-packages\pandas\core\frame.py", line 10381, in apply
return op.apply().__finalize__(self, method="apply")
File "E:\python课\Lib\site-packages\pandas\core\apply.py", line 916, in apply
return self.apply_standard()
File "E:\python课\Lib\site-packages\pandas\core\apply.py", line 1063, in apply_standard
results, res_index = self.apply_series_generator()
File "E:\python课\Lib\site-packages\pandas\core\apply.py", line 1081, in apply_series_generator
results[i] = self.func(v, *self.args, **self.kwargs)
File "E:\python课\Lib\site-packages\pandas\core\groupby\generic.py", line 1828, in <lambda>
lambda x: func(x, *args, **kwargs), axis=self.axis
File "E:\python课\Lib\idlelib\idle.py", line 162, in <lambda>
lambda x: (x['volume'] * (x['high'] + x['low'] + x['close']) / 3).cumsum()
File "E:\python课\Lib\site-packages\pandas\core\series.py", line 1130, in __getitem__
return self._get_value(key)
File "E:\python课\Lib\site-packages\pandas\core\series.py", line 1246, in _get_value
loc = self.index.get_loc(label)
File "E:\python课\Lib\site-packages\pandas\core\indexes\datetimes.py", line 605, in get_loc
raise KeyError(key) from err
KeyError: 'volume'基于以上问题重新生成代码