【发布时间】：2021-12-24 09:44:18
【问题描述】：
当有要应用r.apply({"price" : vwap, "qty": sum_qty, "quoteQty": sum_quoteQty}) 的函数列表时，我对pandas.Resampler.agg 有疑问。它总是返回类似AttributeError: 'Series' object has no attribute 'price' 的错误。但它只适用于一个函数r.apply(vwap)。
我的数据框具有price、qty 等属性：
我定义了要在 Resampler 上应用的函数列表。我添加了一些打印来调试：
如果我使用函数列表，则重采样器无法找到我的数据帧的属性price：
AttributeError Traceback (most recent call last)
/tmp/ipykernel_939/4117684543.py in <module>
----> 1 r.apply({"price" : vwap, "qty": sum_qty, "quoteQty": sum_quoteQty})
/SSD/lime/conda/lib/python3.9/site-packages/pandas/core/resample.py in aggregate(self, func, *args, **kwargs)
332 def aggregate(self, func, *args, **kwargs):
333
--> 334 result = ResamplerWindowApply(self, func, args=args, kwargs=kwargs).agg()
335 if result is None:
336 how = func
/SSD/lime/conda/lib/python3.9/site-packages/pandas/core/apply.py in agg(self)
159
160 if is_dict_like(arg):
--> 161 return self.agg_dict_like()
162 elif is_list_like(arg):
163 # we require a list, but not a 'str'
/SSD/lime/conda/lib/python3.9/site-packages/pandas/core/apply.py in agg_dict_like(self)
433 else:
434 # key used for column selection and output
--> 435 results = {
436 key: obj._gotitem(key, ndim=1).agg(how) for key, how in arg.items()
437 }
/SSD/lime/conda/lib/python3.9/site-packages/pandas/core/apply.py in <dictcomp>(.0)
434 # key used for column selection and output
435 results = {
--> 436 key: obj._gotitem(key, ndim=1).agg(how) for key, how in arg.items()
437 }
438
/SSD/lime/conda/lib/python3.9/site-packages/pandas/core/groupby/generic.py in aggregate(self, func, engine, engine_kwargs, *args, **kwargs)
263
264 try:
--> 265 return self._python_agg_general(func, *args, **kwargs)
266 except KeyError:
267 # TODO: KeyError is raised in _python_agg_general,
/SSD/lime/conda/lib/python3.9/site-packages/pandas/core/groupby/groupby.py in _python_agg_general(self, func, *args, **kwargs)
1308 try:
1309 # if this function is invalid for this dtype, we will ignore it.
-> 1310 result = self.grouper.agg_series(obj, f)
1311 except TypeError:
1312 warnings.warn(
/SSD/lime/conda/lib/python3.9/site-packages/pandas/core/groupby/ops.py in agg_series(self, obj, func, preserve_dtype)
1026
1027 else:
-> 1028 result = self._aggregate_series_fast(obj, func)
1029
1030 npvalues = lib.maybe_convert_objects(result, try_float=False)
/SSD/lime/conda/lib/python3.9/site-packages/pandas/core/groupby/ops.py in _aggregate_series_fast(self, obj, func)
1249 # - len(self.bins) > 0
1250 sbg = libreduction.SeriesBinGrouper(obj, func, self.bins)
-> 1251 result, _ = sbg.get_result()
1252 return result
1253
/SSD/lime/conda/lib/python3.9/site-packages/pandas/_libs/reduction.pyx in pandas._libs.reduction.SeriesBinGrouper.get_result()
/SSD/lime/conda/lib/python3.9/site-packages/pandas/_libs/reduction.pyx in pandas._libs.reduction._BaseGrouper._apply_to_group()
/SSD/lime/conda/lib/python3.9/site-packages/pandas/core/groupby/groupby.py in <lambda>(x)
1294 def _python_agg_general(self, func, *args, **kwargs):
1295 func = com.is_builtin_func(func)
-> 1296 f = lambda x: func(x, *args, **kwargs)
1297
1298 # iterate through "columns" ex exclusions to populate output dict
/tmp/ipykernel_939/2003501728.py in vwap(x)
2 print("it's vwap")
3 print(x)
----> 4 p = x.price
5 print("it's p")
6 print(p)
/SSD/lime/conda/lib/python3.9/site-packages/pandas/core/generic.py in __getattr__(self, name)
5485 ):
5486 return self[name]
-> 5487 return object.__getattribute__(self, name)
5488
5489 def __setattr__(self, name: str, value) -> None:
AttributeError: 'Series' object has no attribute 'price'
但是，它可以与单个函数 r.apply(vwap) 一起正常工作，并且可以检索属性 price 和 qty：
调试打印验证了我的假设：
2021-09-01 00:00:00.023 1391646824
2021-09-01 00:00:00.093 1391646825
2021-09-01 00:00:00.994 1391646826
2021-09-01 00:00:00.994 1391646827
2021-09-01 00:00:00.994 1391646828
2021-09-01 00:00:00.994 1391646829
Name: trade Id, dtype: int64
it's vwap
trade Id price qty quoteQty isBuyerMaker
time
2021-09-01 00:00:00.023 1391646824 47150.32 0.002 94.30 True
2021-09-01 00:00:00.093 1391646825 47150.33 0.002 94.30 False
2021-09-01 00:00:00.994 1391646826 47150.33 0.021 990.15 False
2021-09-01 00:00:00.994 1391646827 47150.33 0.021 990.15 False
2021-09-01 00:00:00.994 1391646828 47152.97 0.002 94.30 False
2021-09-01 00:00:00.994 1391646829 47153.48 0.006 282.92 False
it's p
time
2021-09-01 00:00:00.023 47150.32
2021-09-01 00:00:00.093 47150.33
2021-09-01 00:00:00.994 47150.33
2021-09-01 00:00:00.994 47150.33
2021-09-01 00:00:00.994 47152.97
2021-09-01 00:00:00.994 47153.48
Name: price, dtype: float64
it's q
time
2021-09-01 00:00:00.023 0.002
2021-09-01 00:00:00.093 0.002
2021-09-01 00:00:00.994 0.021
2021-09-01 00:00:00.994 0.021
2021-09-01 00:00:00.994 0.002
2021-09-01 00:00:00.994 0.006
Name: qty, dtype: float64
it's vwap
Empty DataFrame
Columns: [trade Id, price, qty, quoteQty, isBuyerMaker]
Index: []
it's p
Series([], Name: price, dtype: float64)
it's q
Series([], Name: qty, dtype: float64)
it's vwap
trade Id price qty quoteQty isBuyerMaker
time
2021-09-01 00:00:02.050 1391646830 47153.47 0.006 282.92 True
2021-09-01 00:00:02.889 1391646831 47153.47 0.054 2546.28 True
2021-09-01 00:00:02.889 1391646832 47153.47 0.050 2357.67 True
2021-09-01 00:00:02.889 1391646833 47153.47 0.050 2357.67 True
it's p
time
2021-09-01 00:00:02.050 47153.47
2021-09-01 00:00:02.889 47153.47
2021-09-01 00:00:02.889 47153.47
2021-09-01 00:00:02.889 47153.47
Name: price, dtype: float64
it's q
time
2021-09-01 00:00:02.050 0.006
2021-09-01 00:00:02.889 0.054
2021-09-01 00:00:02.889 0.050
2021-09-01 00:00:02.889 0.050
Name: qty, dtype: float64
但是当我尝试官方文档的示例时，即使使用函数列表也一切正常：
所以我真的不知道问题出在哪里......
【问题讨论】：
-
只是在这里拍摄：在访问 cols 时尝试使用括号索引表示法，而不是点表示法，例如
x['price']而不是x.price等。我曾经遇到过点符号的问题... -
@user17242583 现在它得到一个
KeyError: 'price'而不是 AttributeError... -
能否将创建
r的代码添加到问题中？ -
@user17242583 非常标准：
r = csv.head(10).resample('1s', label='right')，如果我删除label='right'，结果是一样的。
标签： python pandas dataframe pandas-groupby