• 欢迎访问搞代码网站,推荐使用最新版火狐浏览器和Chrome浏览器访问本网站!
  • 如果您觉得本站非常有看点,那么赶紧使用Ctrl+D 收藏搞代码吧

Python爬取股票信息,并可视化数据的示例

python 搞代码 4年前 (2022-01-08) 34次浏览 已收录 0个评论

这篇文章主要介绍了Python爬取股票信息,并可视化数据的示例,帮助大家更好的理解和使用python爬虫,感兴趣的朋友可以了解下

前言

截止2019年年底我国股票投资者数量为15975.24万户, 如此多的股民热衷于炒股,首先抛开炒股技术不说, 那么多股票数据是不是非常难找, 找到之后是不是看着密密麻麻的数据是不是头都大了?

今天带大家爬取雪球平台的股票数据, 并且实现数据可视化

先看下效果图

基本环境配置

  • python 3.6
  • pycharm
  • requests
  • csv
  • time

目标地址

https://xueqiu.com/hq

爬虫代码

请求网页

 import requests url = 'https://xueqiu.com/service/v5/stock/screener/quote/list' response = requests.get(url=url, params=params, headers=headers, cookies=cookies) html_data = response.json() 

解析数据

 data_list = html_data['data']['list'] for i in data_list: dit = {} dit['股票代码'] = i['symbol'] dit['股票名字'] = i['name'] dit['当前价'] = i['current'] dit['涨跌额'] = i['chg'] dit['涨跌幅/%'] = i['percent'] dit['年初至今/%'] = i['current_year_percent'] dit['成交量'] = i['volume'] dit['成交额'] = i['amount'] dit['换手率/%'] = i['turnover_rate'] dit['市盈率TTM'] = i['pe_ttm'] dit['股息率/%'] = i['dividend_yield'] dit['市值'] = i['market_capital'] print(dit)

保存数据

 import csv f = open('股票数据.csv', mode='a', encoding='utf-8-sig', newline='') csv_writer = csv.DictWriter(f, fieldnames=['股票代码', '股票名字', '当前价', '涨跌额', '涨跌幅/%', '年初至今/%', '成交量', '成交额', '换手率/%', '市盈率TTM', '股息率/%', '市值']) csv_writer.writeheader() csv_writer.writerow(dit) f.close()

完整代码

 import pprint import requests import time import csv f = open('股票数据.csv', mode='a', encoding='utf-8-sig', newline='') csv_writer = csv.DictWriter(f, fieldnames=['股票代码', '股票名称', '当前价', '涨跌额', '涨跌幅/%', '年初至今/%', '成交量', '成交额', '换手率/%', '市盈率TTM', '股息率/%', '市值']) csv_writer.writeheader() for page in range(1, 53): time.sleep(1) url = 'https://xueqiu.com/service/v5/stock/screener/quote/list' date = round(time.time()*1000) params = { 'page': '{}'.format(page), 'size': '30', 'order': 'desc', 'order_by': 'amount', 'exchange': 'CN', 'market': 'CN', 'type': 'sha', '_': '{}'.format(date), } cookies = { 'Cookie': 'acw_tc=2760824216007592794858354eb971860e97492387fac450a734dbb6e89afb; xq_a_token=636e3a77b735ce64db9da253b75cbf49b2518316; xqat=636e3a77b735ce64db9da253b75cbf49b2518316; xq_r_token=91c25a6a9038fa2532dd45b2dd9b573a35e28cfd; xq_id_token=eyJ0eXAiOiJKV1QiLCJhbGciOiJSUzI1NiJ9.eyJ1aWQiOi0xLCJpc3MiOiJ1YyIsImV4cCI6MTYwMjY0MzAyMCwiY3RtIjoxNjAwNzU5MjY3OTEwLCJjaWQiOiJkOWQwbjRBWnVwIn0.bengzIpmr0io9f44NJdHuc_6g9EIjtrSlMgnqwKSWVzI4syI_yIH1F-GJfK4bTelWzDirufjWMW9DfDMyMkI75TpJqiwIq8PRsa1bQ7IuCXLbN71ebsiTOGfA5OsWSPQOdVXQA0goqC4yvXLOk5KgC5FQIzZut0N4uaRDLsq7vhmcb8CBw504tCZnbIJTfGGIFIfw7TkwuUCXGY6Q-0mlOG8U4EUTcOCuxN87Ej_OIKnXN8cTSVh7XW6SFxOgU6p3yUXDgvS04rt-nFewpNNqfbGAKk965N-HJ9Mq8E52BRJ3rt_ndYP8yCaeQ6xSsz5P2mNlKwNFe9EQeltim_mDg; u=501600759279498; device_id=24700f9f1986800ab4fcc880530dd0ed; Hm_lvt_1db88642e346389874251b5a1eded6e3=1600759286; _ga=GA1.2.2049292015.1600759388; _gid=GA1.2.391362708.1600759388; s=du11eogy79; __utma=1.2049292015.1600759388.1600759397.1600759397.1; __utmc=1; __utmz=1.1600759397.1.1.utmcsr=(direct)|utmccn=(direct)|utmcmd=(none); __utmt=1; __utmb=1.3.10.1600759397; Hm_lpvt_1db88642e346389874251b5a1eded6e3=1600759448' } headers = { 'Host': '<em style="color:transparent">来源[email protected]搞@^&代*@码)网</em>xueqiu.com', 'Pragma': 'no-cache', 'Referer': 'https://xueqiu.com/hq', 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/81.0.4044.138 Safari/537.36' } response = requests.get(url=url, params=params, headers=headers, cookies=cookies) html_data = response.json() data_list = html_data['data']['list'] for i in data_list: dit = {} dit['股票代码'] = i['symbol'] dit['股票名称'] = i['name'] dit['当前价'] = i['current'] dit['涨跌额'] = i['chg'] dit['涨跌幅/%'] = i['percent'] dit['年初至今/%'] = i['current_year_percent'] dit['成交量'] = i['volume'] dit['成交额'] = i['amount'] dit['换手率/%'] = i['turnover_rate'] dit['市盈率TTM'] = i['pe_ttm'] dit['股息率/%'] = i['dividend_yield'] dit['市值'] = i['market_capital'] csv_writer.writerow(dit) print(dit) f.close()

数据分析代码

 c = ( Bar() .add_xaxis(list(df2['股票名称'].values)) .add_yaxis("股票成交量情况", list(df2['成交量'].values)) .set_global_opts( title_opts=opts.TitleOpts(title="成交量图表 - Volume chart"), datazoom_opts=opts.DataZoomOpts(), ) .render("data.html") )

以上就是Python爬取股票信息,并可视化数据的示例的详细内容,更多请关注gaodaima搞代码网其它相关文章!


搞代码网(gaodaima.com)提供的所有资源部分来自互联网,如果有侵犯您的版权或其他权益,请说明详细缘由并提供版权或权益证明然后发送到邮箱[email protected],我们会在看到邮件的第一时间内为您处理,或直接联系QQ:872152909。本网站采用BY-NC-SA协议进行授权
转载请注明原文链接:Python爬取股票信息,并可视化数据的示例

喜欢 (0)
[搞代码]
分享 (0)
发表我的评论
取消评论

表情 贴图 加粗 删除线 居中 斜体 签到

Hi,您需要填写昵称和邮箱!

  • 昵称 (必填)
  • 邮箱 (必填)
  • 网址