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我在使用简单的自建函数基于熊猫滚动窗口的数据处理方面遇到了一些问题。我有三列值，并希望使用简单的列表理解来计算其中的一列以进行进一步处理。在我的示例中，我简单地总结了为每个窗口产生一个值的值。但似乎列表理解失败了...... import pandas as pd import numpy as np from collections import Counter as count

df = pd.DataFrame(np.random.randint(0,100,size=(50, 3)), columns=list('ABC'))

def my_test(data): Abs = [int(np.sqrt(x[0]**2+x[1]**2+x[2]**2)/10) for x in data] return sum(Abs)

entr = df.rolling(10).apply(my_test)

这是我在执行函数时收到的错误消息：

entr =  df.rolling(10).apply(my_test)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "C:\Users\tpotrusil\AppData\Local\Programs\Python\Python36\lib\site-packages\pandas\core\window.py", line 1207, in apply
    return super(Rolling, self).apply(func, args=args, kwargs=kwargs)
  File "C:\Users\tpotrusil\AppData\Local\Programs\Python\Python36\lib\site-packages\pandas\core\window.py", line 856, in apply
    center=False)
  File "C:\Users\tpotrusil\AppData\Local\Programs\Python\Python36\lib\site-packages\pandas\core\window.py", line 799, in _apply
    result = np.apply_along_axis(calc, self.axis, values)
  File "C:\Users\tpotrusil\AppData\Local\Programs\Python\Python36\lib\site-packages\numpy\lib\shape_base.py", line 116, in apply_along_axis
    res = asanyarray(func1d(inarr_view[ind0], *args, **kwargs))
  File "C:\Users\tpotrusil\AppData\Local\Programs\Python\Python36\lib\site-packages\pandas\core\window.py", line 795, in calc
    closed=self.closed)
  File "C:\Users\tpotrusil\AppData\Local\Programs\Python\Python36\lib\site-packages\pandas\core\window.py", line 853, in f
    offset, func, args, kwargs)
  File "pandas\_libs\window.pyx", line 1450, in pandas._libs.window.roll_generic (pandas\_libs\window.c:36061)
  File "<stdin>", line 2, in my_test
  File "<stdin>", line 2, in <listcomp>
IndexError: invalid index to scalar variable.

知道如何访问滚动数据吗？

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1 回答 1

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尝试这个。转换为一系列列表，然后应用此函数：

def my_test(r):
    return int(np.sqrt(sum(r**2)/10))

dfs = pd.Series(data=[df.loc[x].values for x in df.index], index=df.index)
dfs.apply(my_test).rolling(10).sum()
于 2018-01-31T09:33:30.493 回答