#111 import requests

请求的url

url = "https://top.chinaz.com/gongsitop/index_500top.html"

设置请求头信息

headers = { "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/95.0.4638.69 Safari/537.36" }

使用reqeusts模快发起 GET 请求

response = requests.get(url, headers=headers)

获取请求的返回结果

html = response.text import re

公司名

company = re.findall('<a.*?target="_blank">(.+?)', html)

法定代表人

person = re.findall('法定代表人：(.+?)

', html)

注册时间

signDate = re.findall('注册时间：(.+?)

', html)

证券类别

category = re.findall('证券类别：(.+?)

', html) pageOne = list(zip(company, person, signDate, category))

存储内容

message = []

总共16个页面的数据

for page in range(16): # 组装url if page == 0: url = "https://top.chinaz.com/gongsitop/index_500top.html" else: url = "https://top.chinaz.com/gongsitop/index_500top_{}.html".format(page + 1) # 使用reqeusts模快发起 GET 请求 response = requests.get(url, headers=headers) html = response.text # 使用 findall 函数来获取数据 # 公司名 company = re.findall('<a.?target="_blank">(.+?)', html) # 法定代表人 person = re.findall('法定代表人：(.?)

', html) # 注册时间 signDate = re.findall('注册时间：(.?)

', html) # 证券类别 category = re.findall('证券类别：(.?)

', html) pageOne = list(zip(company, person, signDate, category)) # 合并列表 message.extend(pageOne) import csv with open("content.csv", "w") as f: w = csv.writer(f) w.writerows(message) !cat content.csv import pandas as pd

读取数据

df = pd.read_csv("content.csv", names=["company", "person", "signDate", "category"]) df.head() df.info() df1 = df.groupby("category").count()["company"]

在jupyter中直接展示图像

%matplotlib inline import matplotlib.pyplot as plt

用黑体显示中文

plt.rcParams['font.sans-serif'] = ['SimHei']

每个扇形的标签

labels = df1.index

每个扇形的占比

sizes = df1.values

fig1, ax1 = plt.subplots()

绘制饼图

ax1.pie(sizes, labels=labels, autopct='%d%%',radius=2,textprops={'fontsize': 20}, shadow=False, startangle=90) ax1.axis()

plt.show()