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YunHao-Von/Electrician_Cup
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指数移动平均线
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【量化投资-python & pandas技巧系列】使用python计算移动平均线
【量化小讲堂 – python & pandas技巧系列】使用python计算各类移动平均线
计算移动平均线是最常见的需求，下面这段代码将完成以下三件事情：
1. 从csv格式的文件中导入股票数据，数据例图如下：
—————- —————- —————- —————- —————- —————- —————- —————- —————- —————- —————- —————- —————-
# -*- coding: utf-8 -*-
“””
@author: yucezhe
@contact: QQ:2089973054 email:[email protected]
“””
import pandas as pd
# ========== 从原始csv文件中导入股票数据，以浦发银行sh600000为例
# 导入数据 – 注意：这里请填写数据文件在您电脑中的路径
stock_data = pd.read_csv( ‘stock data/sh600000.csv’ , parse_dates =[ 1 ])
# 将数据按照交易日期从远到近排序
stock_data.sort( ‘date’ , inplace = True )
# ========== 计算移动平均线
# 分别计算5日、20日、60日的移动平均线
ma_list 指数移动平均线 = [ 5 , 20 , 60 ]
# 计算简单算术移动平均线MA – 注意：stock_data[‘close’]为股票每天的收盘价
for ma in ma_list:
stock_data[ ‘MA_’ + str (ma)] = pd.rolling_mean(stock_data[ ‘close’ ] , ma)
# 计算指数平滑移动平均线EMA
for ma in ma_list:
stock_data[ ‘EMA_’ + str (ma)] = pd.ewma(stock_data[ ‘close’ ] , span =ma)
# 将数据按照交易日期从近到远排序
stock_data.sort( ‘date’ , ascending = False , inplace = 指数移动平均线 True )
代码输出的数据截图如下：
现在想到的之后几期会讲的内容：
【量化小讲堂 – python & pandas技巧系列】如何在windows环境安装python和pandas
【量化小讲堂 – python & pandas技巧系列】如何在mac OSX环境安装python和pandas
【量化小讲堂 – python & pandas技巧系列】使用python计算KDJ指标
【量化小讲堂 – python & pandas技巧系列】使用python计算MACD指标
【量化小讲堂 – 投资策略系列】KDJ、MACD指标双金叉选股效果
【量化小讲堂 – python & pandas技巧系列】使用pytho将日线数据转换成周线、月线数据