獲取statsmodels ACF功能的輸出與熊貓滾動窗口

Question

我可以提取特定的滯後時間與此自相關值：

df.rolling(window = 10).apply(lambda x: acf(x, nlags = 5)[5]).plot() 

但是由於acf實際上是在做所有的計算，無論如何，我想計算所有結果，而不僅僅是一個。這個想法是，我可以解開這個單一的返回數組/列表成一堆列並分別繪製每一個，但不會通過acf這麼多不必要的時間。所以，我想：

df.rolling(window = 10).apply(lambda x: list(acf(x, nlags = 5))) 

這引發以下錯誤：

--------------------------------------------------------------------------- 
TypeError         Traceback (most recent call last) 
<ipython-input-63-e5f337100eb5> in <module>() 
----> 1 df.rolling(window = 10).apply(lambda x: list(acf(x, nlags = 5))) 

/Users/a/anaconda3/lib/python3.5/site-packages/pandas/core/window.py in apply(self, func, args, kwargs) 
    861  @Appender(_shared_docs['apply']) 
    862  def apply(self, func, args=(), kwargs={}): 
--> 863   return super(Rolling, self).apply(func, args=args, kwargs=kwargs) 
    864 
    865  @Substitution(name='rolling') 

/Users/a/anaconda3/lib/python3.5/site-packages/pandas/core/window.py in apply(self, func, args, kwargs) 
    619 
    620   return self._apply(f, func, args=args, kwargs=kwargs, 
--> 621       center=False) 
    622 
    623  def sum(self, **kwargs): 

/Users/a/anaconda3/lib/python3.5/site-packages/pandas/core/window.py in _apply(self, func, name, window, center, check_minp, how, **kwargs) 
    556 
    557    if values.ndim > 1: 
--> 558     result = np.apply_along_axis(calc, self.axis, values) 
    559    else: 
    560     result = calc(values) 

/Users/a/anaconda3/lib/python3.5/site-packages/numpy/lib/shape_base.py in apply_along_axis(func1d, axis, arr, *args, **kwargs) 
    89  outshape = asarray(arr.shape).take(indlist) 
    90  i.put(indlist, ind) 
---> 91  res = func1d(arr[tuple(i.tolist())], *args, **kwargs) 
    92  # if res is a number, then we have a smaller output array 
    93  if isscalar(res): 

/Users/a/anaconda3/lib/python3.5/site-packages/pandas/core/window.py in calc(x) 
    553 
    554     def calc(x): 
--> 555      return func(x, window, min_periods=self.min_periods) 
    556 
    557    if values.ndim > 1: 

/Users/a/anaconda3/lib/python3.5/site-packages/pandas/core/window.py in f(arg, window, min_periods) 
    616    minp = _use_window(min_periods, window) 
    617    return algos.roll_generic(arg, window, minp, offset, func, args, 
--> 618          kwargs) 
    619 
    620   return self._apply(f, func, args=args, kwargs=kwargs, 

pandas/algos.pyx in pandas.algos.roll_generic (pandas/algos.c:51581)() 

TypeError: a float is required 

這是否意味着apply風格與操作rolling只能處理花車？至少對於groupby我經常有機會返回列表或集合，但也許rolling不那麼靈活？

Answer 1

要繪製的ACF的結果，你可能會想嘗試tsaplots.plot_acf()：

from statsmodels.graphics import tsaplots 

tsaplots.plot_acf(x, lags = 5, alpha = 0.05)