python - 如何应用以调用者作为参数的函数

Question

我试图在数据帧上逐列运行 np 的相关函数，但我想要运行的相关性是系列本身。例如，假设 df 是我们的数据帧，ts 是 df 的第一列。我想调用 np.correlate(ts, ts, method="full")。

df = pd.DataFrame([[1,1],[2,2],[3,3],[4,4],[5,5]], index=range(5), columns=list("ab"))

def acf(R):
    """
    Calcualte the auto correlation function of a series with lag 0 up to the length
    of the series. 
    """
    y = R - R.mean()
    result = y.apply(np.correlate, (y, "full"))
    result = result[len(result)//2:]
    result /= result[0]
    return result

acf(df)

NameError: name 'y' is not defined

我应该怎么做才能实现这个目标？

Answer 1

pandas.Series 对象往往与 numpy 函数配合良好，因此将函数定义为

def acf(R):
    """
    Calcualte the auto correlation function of a series with lag 0 up to the length
    of the series. 
    """
    y = R - R.mean()
    result = np.correlate(y, y, 'full')
    result = result[len(result)//2:]
    result /= result[0]
    return result

然后使用 df.apply(acf) 将其应用到 DataFrame 应该可以工作。

In [4]: import numpy as np

In [5]: import pandas as pd
   ...: def acf(R):
   ...:     """
   ...:     Calcualte the auto correlation function of a series with lag 0    up to the length
   ...:     of the series. 
   ...:     """
   ...:     y = R - R.mean()
   ...:     result = np.correlate(y, y, 'full')
   ...:     result = result[len(result)//2:]
   ...:     result /= result[0]
   ...:     return result
   ...: df = pd.DataFrame([[1,1],[2,2],[3,3],[4,4],[5,5]], index=range(5), columns=list("ab"))
   ...: 

In [6]: df.apply(acf)
Out[6]: 
     a    b
0  1.0  1.0
1  0.4  0.4
2 -0.1 -0.1
3 -0.4 -0.4
4 -0.4 -0.4