使用baostock获取上市公司情况

起因是有个不知道什么专业的同学问了我一题

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 = True


def 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 + ':' + S


def 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()
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84

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()
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30