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其中一个时间序列:
宁沪高速
2015-06-01 0.889979
2015-06-02 0.905299
2015-06-03 0.948019
2015-06-04 0.936253
2015-06-05 0.959451
2015-06-08 1.001514
2015-06-09 1.003785
2015-06-10 0.996485
2015-06-11 0.981700
2015-06-12 1.042110
2015-06-15 1.152470
2015-06-16 1.142535
2015-06-17 1.121491
2015-06-18 1.113738
2015-06-19 1.053950
2015-06-23 1.045791
2015-06-24 1.070320
2015-06-25 1.007301
2015-06-26 0.935514
2015-06-29 0.954426
2015-06-30 0.962283
2015-07-02 0.863278
2015-07-03 0.804982
2015-07-06 0.843035
2015-07-07 0.819140
2015-07-08 0.787451
2015-07-09 0.823873
2015-07-10 0.871263
2015-07-13 0.908293
2015-07-14 0.865360
代码:
for i in stationary_pair.columns :
x=1
#定义移动天数
j=10
temp=np.log(stationary_pair.loc[:,i]/stationary_pair.loc[:,i].shift(1))
temp1=temp.rolling(j)
plt.figure(num=x,figsize=(25,10))
plt.plot(temp)
plt.axhline(temp.mean(), color='black')
plt.axhline(temp1.mean(), color='black')
plt.axhline(temp1.mean()+temp1.std(), color='red')
plt.axhline(temp1.mean()-temp1.std(), color='green')
plt.title(i,fontproperties='SimHei',fontsize=15)
plt.show()
x+=1
报错:
ValueError Traceback (most recent call last)
<ipython-input-79-1670db8e6fba> in <module>()
26 plt.plot(temp)
27 plt.axhline(temp.mean(), color='black')
---> 28 plt.axhline(temp1, color='black')
29 plt.axhline(temp1.mean()+temp1.std(), color='red')
30 plt.axhline(temp1.mean()-temp1.std(), color='green')
~\Anaconda3\lib\site-packages\matplotlib\pyplot.py in axhline(y, xmin, xmax, hold, **kwargs)
2693 mplDeprecation)
2694 try:
-> 2695 ret = ax.axhline(y=y, xmin=xmin, xmax=xmax, **kwargs)
2696 finally:
2697 ax._hold = washold
~\Anaconda3\lib\site-packages\matplotlib\axes\_axes.py in axhline(self, y, xmin, xmax, **kwargs)
716 self._process_unit_info(ydata=y, kwargs=kwargs)
717 yy = self.convert_yunits(y)
--> 718 scaley = (yy < ymin) or (yy > ymax)
719
720 trans = self.get_yaxis_transform(which='grid')
~\Anaconda3\lib\site-packages\pandas\core\generic.py in __nonzero__(self)
1574 raise ValueError("The truth value of a {0} is ambiguous. "
1575 "Use a.empty, a.bool(), a.item(), a.any() or a.all()."
-> 1576 .format(self.__class__.__name__))
1577
1578 __bool__ = __nonzero__
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
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