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

Python爬取股票信息，并可视化数据的示例

基本环境配置

python 3.6
pycharm
requests
csv
time

目标地址

https://xueqiu.com/hq

Python爬取股票信息，并可视化数据的示例

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\': \'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()

Python爬取股票信息，并可视化数据的示例

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\")
)

Python爬取股票信息，并可视化数据的示例