Python爬取股票交易数据并可视化展示 Python爬取股票交易数据并可视

开发环境
第三方模块
爬虫案例的步骤
爬虫程序全部代码

分析网页
导入模块
请求数据
解析数据
翻页
保存数据

实现效果

数据可视化全部代码

导入数据
读取数据
可视化图表
效果展示

开发环境解释器版本: python 3.8
代码编辑器: pycharm 2021.2

第三方模块 requests: pip install requests
csv

爬虫案例的步骤 1.确定url地址(链接地址)
2.发送网络请求
3.数据解析(筛选数据)
4.数据的保存(数据库(mysql\mongodb\redis), 本地文件)

爬虫程序全部代码
分析网页
打开开发者工具，搜索关键字，找到正确url

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导入模块

import requests# 发送网络请求import csv

请求数据

url = f'https://xueqiu.com/service/v5/stock/screener/quote/list?page=1&size=30&order=desc&order_by=amount&exchange=CN&market=CN&type=sha&_=1637908787379'# 伪装headers = {# 浏览器伪装'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/96.0.4664.45 Safari/537.36'}response = requests.get(url, headers=headers)json_data = https://www.it610.com/article/response.json()

解析数据

data_list = json_data['data']['list']for data in data_list:data1 = data['symbol']data2 = data['name']data3 = data['current']data4 = data['chg']data5 = data['percent']data6 = data['current_year_percent']data7 = data['volume']data8 = data['amount']data9 = data['turnover_rate']data10 = data['pe_ttm']data11 = data['dividend_yield']data12 = data['market_capital']print(data1, data2, data3, data4, data5, data6, data7, data8, data9, data10, data11, data12)data_dict = {'股票代码': data1,'股票名称': data2,'当前价': data3,'涨跌额': data4,'涨跌幅': data5,'年初至今': data6,'成交量': data7,'成交额': data8,'换手率': data9,'市盈率(TTM)': data10,'股息率': data11,'市值': data12,}csv_write.writerow(data_dict)

翻页
对比1、2、3页数据url，找到规律

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for page in range(1, 56):url = f'https://xueqiu.com/service/v5/stock/screener/quote/list?page={page}&size=30&order=desc&order_by=amount&exchange=CN&market=CN&type=sha&_=1637908787379'

保存数据

file = open('data2.csv', mode='a', encoding='utf-8', newline='')csv_write = csv.DictWriter(file, 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_write.writeheader()file.close()

实现效果

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数据可视化全部代码
导入数据

import pandas as pdfrom pyecharts import options as optsfrom pyecharts.charts import Bar

读取数据

data_df = pd.read_csv('data2.csv')df = data_df.dropna()df1 = df[['股票名称', '成交量']]df2 = df1.iloc[:20]print(df2['股票名称'].values)print(df2['成交量'].values)

可视化图表

c = (Bar().add_xaxis(list(df2['股票名称'])).add_yaxis("股票成交量情况", list(df2['成交量'])).set_global_opts(title_opts=opts.TitleOpts(title="成交量图表 - Volume chart"),datazoom_opts=opts.DataZoomOpts(),).render("data.html"))print('数据可视化结果完成,请在当前目录下查找打开 data.html 文件!')

效果展示