python-大智慧-BIAS乖离率编写

# -*- coding: utf-8 -*-
"""
Created on Wed May 24 15:47:51 2017
@author: yunjinqi 
E-mail:yunjinqi@qq.com 
Differentiate yourself in the world from anyone else.
"""
import pandas as pd  
import numpy as np  
import datetime  
import time  
#获取数据  
df=pd.read_csv('C:/Users/HXWD/Desktop/000001.csv',encoding='gbk')  
df.columns=['date','code','name','close','high','low','open','preclose',  
'change','change_per','volume','amt']  
df=df[['date','open','high','low','close','volume','amt']]  
df.head()  
def get_BIAS(df,L1=6,L2=12,L3=24):
    '''
    乖离率
算法：
    当日收盘价与移动平均线之间的差距；
用法：
    正的乖离率愈大，表示短期获利愈大，则获利回吐的可能性愈高；负的乖离率愈大，则空头回补的可能性愈高。
    按个股收盘价与不同天数的平均价之间的差距，可绘制不同的BIAS线。
参数：
    系统绘制三条BIAS线，分别为收盘价与L1日、L2日、L3日移动平均价的差。'''
    df['bias1']=100*(df['close']-df['close'].rolling(L1).mean())/df['close'].rolling(L1).mean()
    df['bias2']=100*(df['close']-df['close'].rolling(L2).mean())/df['close'].rolling(L1).mean()
    df['bias3']=100*(df['close']-df['close'].rolling(L3).mean())/df['close'].rolling(L1).mean()
    return df
get_BIAS(df)
df.tail()