import csv
import requests
import re
import pandas as pd
from matplotlib import pyplot as plt
# 用黑体显示中文
plt.rcParams['font.sans-serif'] = ['SimHei']
# 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"
}
# 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">(.+?)</a></h3>', html)
    # 法定代表人
    person = re.findall('法定代表人：</span>(.*?)</p>', html)
    # 注册时间
    signDate = re.findall('注册时间：</span>(.*?)</p>', html)
    # 证券类别
    category = re.findall('证券类别：</span>(.*?)</p>', html)
    pageOne = list(zip(company, person, signDate, category))
    # 合并列表
    message.extend(pageOne)
with open("content.csv", "w") as f:
    w = csv.writer(f)
    w.writerows(message)
# 读取数据
df = pd.read_csv("content.csv", names=["company", "person", "signDate", "category"],encoding='gbk')
# 根据证券类型进行分组
df1 = df.groupby("category").count()["company"]
print(df1)
# 每个扇形的标签
labels = df1.index
# 每个扇形的占比
sizes = df1.values
plt.figure(figsize=(80,40),dpi=80)
fig1, ax1 = plt.subplots()
# 绘制饼图
ax1.pie(sizes, labels=labels, autopct='%d%%',radius=1.3,textprops={'fontsize': 20},
        shadow=False, startangle=90)
ax1.axis()

plt.show()