python-大智慧-VMACD-量指数平滑移动平均线

# -*- 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_EMA(df,N):  
    for i in range(len(df)):  
        if i==0:  
            df.ix[i,'ema']=df.ix[i,'volume']  
        if i>0:  
            df.ix[i,'ema']=(2*df.ix[i-1,'volume']+(N-1)*df.ix[i,'volume'])/(N+1)  
    ema=list(df['ema'])  
    return ema  
def get_VMACD(df,short=12,long=26,M=9):  
    a=get_EMA(df,short)  
    b=get_EMA(df,long)  
    df['diff']=pd.Series(a)-pd.Series(b)  
    #print(df['diff'])  
    for i in range(len(df)):  
        if i==0:  
            df.ix[i,'dea']=df.ix[i,'diff']  
        if i>0:  
            df.ix[i,'dea']=(2*df.ix[i-1,'diff']+(M-1)*df.ix[i,'diff'])/(M+1)  
    df['macd']=2*(df['diff']-df['dea'])  
    return df  
get_VMACD(df,12,26,9)  
df.tail()