中国股市历史数据获取工具
baoshare的Python项目详细描述
- 它很容易使用,因为返回的大多数数据都是pandas dataframe对象
- 我们有自己的数据服务器,运行高效稳定
- 自由中国股市数据
- 易于机器学习和数据挖掘
目标用户
- 中国金融市场分析师
- 金融数据分析爱好者
- 对中国股市感兴趣的投资者
安装
pip install baoshare
升级
pip install baoshare –upgrade
快速启动
import baostock as bs import pandas as pd # 登陆系统 lg = bs.login(user_id="anonymous", password="123456") # 显示登陆返回信息 print(lg.error_code) print(lg.error_msg) # 详细指标参数,参见“历史行情指标参数”章节 rs = bs.query_history_k_data("sh.601398", "date,code,open,high,low,close,volume,amount,adjustflag", start_date='2017-01-01', end_date='2017-01-31', frequency="d", adjustflag="3") print(rs.error_code) print(rs.error_msg) # 获取具体的信息 result = pd.DataFrame(columns=["date","code","open","high","low","close","volume","amount","adjustflag"]) while (rs.error_code == '0') & rs.next(): # 分页查询,将每页信息合并在一起 result = result.append(rs.get_row_data(), ignore_index=True) result.to_csv("D:\history_k_data.csv", index=False) print(result) # 登出系统 bs.logout()
返回:
date code open high low close preclose volume 0 2017-01-03 sh.601398 4.4000 4.4300 4.3900 4.4300 4.4100 104161632 1 2017-01-04 sh.601398 4.4200 4.4400 4.4100 4.4300 4.4300 118923425 2 2017-01-05 sh.601398 4.4300 4.4500 4.4200 4.4400 4.4300 87356137 3 2017-01-06 sh.601398 4.4400 4.4500 4.4300 4.4400 4.4400 87008191 4 2017-01-09 sh.601398 4.4500 4.4800 4.4300 4.4600 4.4400 117454094 5 2017-01-10 sh.601398 4.4500 4.4700 4.4400 4.4600 4.4600 63663257 6 2017-01-11 sh.601398 4.4600 4.4800 4.4500 4.4700 4.4600 52395427 7 2017-01-12 sh.601398 4.4600 4.4700 4.4400 4.4700 4.4700 62166279 amount adjustflag turn tradestatus 0 460087744.0000 3 0.038634 1 1 526408816.0000 3 0.044109 1 2 387580736.0000 3 0.032401 1 3 386138112.0000 3 0.032272 1 4 523539392.0000 3 0.043564 1 5 283646224.0000 3 0.023613 1 6 233898107.0000 3 0.019434 1 7 277258304.0000 3 0.023058 1