From 15adb2ced362424e0f5fa981c73ab9d9fea0952e Mon Sep 17 00:00:00 2001
From: hnu202110040110 <hnu202110040110@qq.com>
Date: Sun, 29 May 2022 21:22:14 +0800
Subject: [PATCH] ADD file via upload

---
 ChinaTop500Company.py | 76 +++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 76 insertions(+)
 create mode 100644 ChinaTop500Company.py

diff --git a/ChinaTop500Company.py b/ChinaTop500Company.py
new file mode 100644
index 0000000..6403b6b
--- /dev/null
+++ b/ChinaTop500Company.py
@@ -0,0 +1,76 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Thu May 12 14:45:14 2022
+
+@author: pzh
+"""
+
+# %% ChinaTop500Company.py
+import requests
+import re
+import csv
+import pandas as pd
+# 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)
+    # 注册资本
+    money = re.findall('注册资本：</span>(.*?)</p>', html)
+    pageOne = list(zip(company, money))
+    # 合并列表
+    message.extend(pageOne)
+
+with open('content2.csv', 'w') as f:
+    w = csv.writer(f)
+    w.writerows(message)
+    
+# %% 读取数据
+import matplotlib.pyplot as plt
+plt.rcParams['font.sans-serif'] = ['SimHei']
+plt.rcParams['axes.unicode_minus'] = False
+df = pd.read_csv("content2.csv", names=["company", "money"], encoding = 'gbk')
+money = df['money'].values
+output = []
+i = 0
+for elem in money:
+    st = str(elem)
+    if '万美元' in st:
+        num = eval(re.sub(u'([^\u0030-\u0039\u002e\uffe5])', '', st)) / 10000 * 6.79
+    elif '万' in st:
+        num = eval(re.sub(u'([^\u0030-\u0039\u002e\uffe5])', '', st)) / 10000
+
+    elif st == 'nan':
+        num = 0
+    else:
+        num = eval(re.sub(u'([^\u0030-\u0039\u002e\uffe5])', '', st))
+    df['money'].values[i] = round(num, 2)
+    i = i + 1
+df2 = df.sort_values(by = ['money'], ascending = False)
+df3 = df2.head(20)
+
+#绘图
+x = list(range(20))
+x = x[::-1]
+y = df3['money'].values
+plt.barh(x, y)
+k = 0
+plt.yticks(x, df3['company'].values)
+for i, j in zip(x, y):
+    plt.text(j, i, j, ha = 'right', va = 'center', fontsize = 8)
+    k = k + 1
+plt.savefig('ChinaTop500Company.png')
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