Python 如何让特征值滞后一行

# 加载库
import pandas as pd
​
# 데이터프레임을 만듭니다.
dataframe = pd.DataFrame()
​
# 模拟数据
dataframe["dates"] = pd.date_range("1/1/2001", periods=5, freq="D")
dataframe["stock_price"] = [1.1,2.2,3.3,4.4,5.5]
dataframe.head()
​
# 让值滞后一行
dataframe["previous_days_stock_price"] = dataframe["stock_price"].shift(1)
​
dataframe.head()​
dates	stock_price	previous_days_stock_price
0	2001-01-01	1.1	NaN
1	2001-01-02	2.2	1.1
2	2001-01-03	3.3	2.2
3	2001-01-04	4.4	3.3
4	2001-01-05	5.5	4.4

from scipy.stats import pearsonr
import numpy as np
 
#超前滞后相关
def leadlagcor(data1,data2,n):
	#data1和data2为两个时间序列，n设置做多少个时间步长的超前滞后
    a=-n
    b=-a
    c=b*2+1
    x=np.arange(-n,n+1,1)
    r=np.zeros((c,1))
    p=np.zeros((c,1))
 
    for i in range(c):
        if i(b):
            r[n-i],p[n-i]=pearsonr(data1[:(len(data1)-i)], data2[i:])
        else:
            r[i],p[i]=pearsonr(data1[x[i]:], data2[:len(data1)-x[i]])
    return r

def leadlagcor_plot(data1,data2,n):
	#data1和data2为两个时间序列，n设置做多少个时间步长的超前滞后
    r=leadlagcor(data1,data2,n)#调用上面写的函数做超前滞后相关
    x=range(-n,n+1,1)
    
    fig = plt.figure()
    ax = fig.add_subplot(111)
    ax.plot(x,r,'k--',linewidth=0.8)
    ax.axhline(0, color='k')
    
    b=ax.bar(x,np.squeeze(r),color='red')
    for bar,height in zip(b,r):
        if height0:
            bar.set(color='blue')
     
    print('cor_max:',np.max(r),'\n','cor_min:',np.min(r)) 
    plt.savefig('%s.jpg')
    plt.show()