python爬虫股票数据分析判断股票好坏_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 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()

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，更多关于Python爬取股票信息的资料请关注脚本之家其它相关文章！