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Module use

Requests > pip install requests (data request third party module)

Re # regular expression to match the extracted data

Json

Pandas

Pyecharts

Development environment

Python 3.8interpreter

Pycharm version 2021.2

Code implementation steps

Send a request to visit the website

Get data

Parsing data (extracting data)

Save data

Make a simple visualization of the bar chart

Code # 1. Send a request to visit the website headers= {'User-Agent':' Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/97.0.4692.71 Safari/537.36'} url= 'https://xueqiu.com/service/v5/stock/screener/quote/list?page=1&size=30&order=desc&order_by=amount&exchange=CN&market=CN&type=sha&_=1641730868838'response = requests.get (url=url, headers=headers) # 2. Get data json_data = response.json () # 3. Data parsing (filtering data) 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 = {'stock symbol': data1, 'stock name': data2, 'current price': data3,'up and down': data4,'up and down': data5, 'year to date': data6, 'volume': data7, 'turnover': data8 'turnover': data9, 'TTM': data10, 'dividend yield': data11, 'market capitalization': data12,} csv_write.writerow (data_dict) 4. Save address file = open ('data2.csv', mode='a', encoding='utf-8', newline='') csv_write = csv.DictWriter (file, fieldnames= [' stock symbol', 'stock name', 'current price','up and down','up and down', 'year to date', 'volume', 'turnover', 'turnover', 'price-to-earnings ratio (TTM)', 'dividend yield', 'market capitalization']) csv_write.writeheader ()

Running effect

Data visualization data_df = pd.read_csv ('data2.csv') df = data_df.dropna () df1 = df [[' stock name'' Df2 = df1.iloc [: 20] print (df2 ['stock name'] .values) print (df2 ['stock name'] .values) c = (Bar () .add _ xaxis (df2 ['stock name'] .values.tolist ()) .add _ yaxis ("stock trading volume") Df2 ['Trading Volume'] .values.tolist () .set _ global_opts (title_opts=opts.TitleOpts (title= "Trading Volume Chart-Volume chart"), datazoom_opts=opts.DataZoomOpts (),) .render ("data.html") print ('data visualization result is complete, please find the open data.html file in the current directory!')

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