Python爬取股票信息，并可视化数据的示例
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
爬虫代码
请求网页
import requestsurl = '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 csvf = 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 pprintimport requestsimport timeimport csvf = 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': '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'))
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