使用baostock获取上市公司情况

本文主要是介绍使用baostock获取上市公司情况，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！

起因是有个不知道什么专业的同学问了我一题在这里插入图片描述

cs:

import baostock as bs
import pandas as pd
import datetime'''
日线指标参数包括：'date,code,open,high,low,close,preclose,volume,amount,adjustflag,turn,tradestatus,pctChg,peTTM,pbMRQ,psTTM,pcfNcfTTM,isST'
周、月线指标参数包括：'date,code,open,high,low,close,volume,amount,adjustflag,turn,pctChg'
分钟指标参数包括：'date,time,code,open,high,low,close,volume,amount,adjustflag'adjustflag：复权类型，默认不复权：3；1：后复权；2：前复权。已支持分钟线、日线、周线、月线前后复权。
'''# 是否删除停盘数据
DROP_SUSPENSION = Truedef update_stk_list(date=None):# 获取指定日期的指数、股票数据stock_rs = bs.query_all_stock(date)stock_df = stock_rs.get_data()stock_df.to_csv('./stk_data/all_list.csv', encoding='gbk', index=False)stock_df.drop(stock_df[stock_df.code < 'sh.600519'].index, inplace=True)stock_df.drop(stock_df[stock_df.code > 'sh.600519'].index, inplace=True)stock_df = stock_df['code']stock_df.to_csv('./stk_data/stk_list.csv', encoding='gbk', index=False)return stock_df.tolist()def load_stk_list():df = pd.read_csv('./stk_data/stk_list.csv')return df['code'].tolist()def convert_time(t):H = t[8:10]M = t[10:12]S = t[12:14]return H + ':' + M + ':' + Sdef download_data(stk_list=[], fromdate='2013-1-1', todate=datetime.date.today(),datas='date,open,high,low,close,volume,amount,turn,pctChg',frequency='d', adjustflag='2'):for code in stk_list:print("Downloading :" + code)k_rs = bs.query_history_k_data_plus(code, datas, start_date=fromdate, end_date=todate.strftime('%Y-%m-%d'),frequency=frequency, adjustflag=adjustflag)datapath = './stk_data/' + frequency + '/' + code + '.csv'out_df = k_rs.get_data()if DROP_SUSPENSION and 'volume' in list(out_df):out_df.drop(out_df[out_df.volume == '0'].index, inplace=True)# 做time转换if frequency in ['5', '15', '30', '60'] and 'time' in list(out_df):out_df['time'] = out_df['time'].apply(convert_time)out_df.to_csv(datapath, encoding='gbk', index=False)if __name__ == '__main__':bs.login()# 首次运行stk_list = update_stk_list(datetime.date.today() - datetime.timedelta(days=31))# 非首次运行# stk_list = load_stk_list()# 下载日线download_data(stk_list)# 下载周线download_data(stk_list, frequency='w')# 下载月线download_data(stk_list, frequency='m')# 下载5分钟线download_data(stk_list, fromdate='2013-6-1', frequency='5',datas='date,time,open,high,low,close,volume,amount,adjustflag')# 下载15分钟线download_data(stk_list, fromdate='2013-6-1', frequency='15',datas='date,time,open,high,low,close,volume,amount,adjustflag')# 下载30分钟线download_data(stk_list, fromdate='2013-6-1', frequency='30',datas='date,time,open,high,low,close,volume,amount,adjustflag')# 下载60分钟线download_data(stk_list, fromdate='2013-6-1', frequency='60',datas='date,time,open,high,low,close,volume,amount,adjustflag')bs.logout()

cs2:

import pandas as pd
import matplotlib.pyplot as plt# 从CSV文件中读取股票信息
df = pd.read_csv('./stk_data/m/sh.600519.csv')  # 请替换为你的CSV文件路径# 将日期列转换为日期时间类型
df['date'] = pd.to_datetime(df['date'])# 设置图表字体为支持中文的字体（例如SimHei或Microsoft YaHei）
plt.rcParams['font.sans-serif'] = ['SimHei']  # 设置中文字体
plt.rcParams['axes.unicode_minus'] = False  # 解决负号显示为方块的问题# 绘制股票信息的图表
plt.figure(figsize=(12, 6))
plt.plot(df['date'], df['close'], marker='o', linestyle='-', color='b', label='收盘价')
plt.plot(df['date'], df['open'], marker='o', linestyle='-', color='g', label='开盘价')# 自定义图表标签和标题
plt.xlabel('日期')
plt.ylabel('价格')
plt.title('股票收盘价和开盘价')
plt.xticks(rotation=45)  # 旋转x轴标签，使其更易读# 添加图例
plt.legend()# 显示图表
plt.tight_layout()  # 自动调整图表布局，防止标签重叠
plt.show()