python量化数据4：茅台为例计算股票日k线涨跌幅

一、环境

pip install pandas
pip install mootdx

二、代码

#行业业绩轮动公众号首发
from mootdx.quotes import Quotes
import pandas as pd
client = Quotes.factory(market='std')

# 获取实时行情
df = client.bars(symbol='600519', frequency=9, offset=15)  #获取最近15日茅台k线

df['收盘涨幅'] = 0
df['最高涨幅'] = 0
df['最低涨幅'] = 0
print(df)
# 计算简单移动平均线
# data['MA5'] = data['close'].rolling(window=5).mean()
# data['MA10'] = data['close'].rolling(window=10).mean() 
# print(data[['close', 'MA5', 'MA10']])
last_close = 0
def cal_zhangfu(close1=1, close2=1):
    
    zhangfu = float(close1)/float(close2)-1
    zhangfu = zhangfu*100
    zhangfu = round(zhangfu,2)
    zhangfu = str(zhangfu) + '%'
    #print("-cal-",close1,close2,zhangfu)
    return zhangfu

for id in range(len(df)):
    if 0 == last_close:
        last_close = df.iloc[id]['close'] #第1天获取收盘价跳过
        continue
    else:
        copy = df.iloc[id] 
        copy['收盘涨幅'] = cal_zhangfu(df.iloc[id]['close'],last_close)
        copy['最高涨幅'] = cal_zhangfu(df.iloc[id]['high'],last_close)
        copy['最低涨幅'] = cal_zhangfu(df.iloc[id]['low'],last_close)
        #print(df.iloc[id]['datetime'], df.iloc[id]['收盘涨幅'], df.iloc[id]['最高涨幅'], df.iloc[id]['最低涨幅'])
        df.iloc[id]  = copy
        last_close = df.iloc[id]['close'] 
print(df)

三、运行运行结果 9.26 茅台大涨9%+