From 2f01243c9a42071cc53bbeaf8d9fea8bd3bda9e3 Mon Sep 17 00:00:00 2001
From: hnu202109070102 <hnu202109070102@qq.com>
Date: Tue, 31 May 2022 21:12:09 +0800
Subject: [PATCH] ADD file via upload

---
 中国五百强公司信息爬取 | 100 ++++++++++++++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 中国五百强公司信息爬取

diff --git a/中国五百强公司信息爬取 b/中国五百强公司信息爬取
new file mode 100644
index 0000000..9ab162e
--- /dev/null
+++ b/中国五百强公司信息爬取
@@ -0,0 +1,100 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Sat May 21 21:38:27 2022
+
+@author: dell
+"""
+
+# 首先我们需要导入 requests 库
+import requests
+# 请求的url
+url = "https://top.chinaz.com/gongsi/index_zhuce.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
+print(html)
+# 导入 re 模快
+import re
+# 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('<em>(.+?)</em>注册资本</div>', html)
+
+pageOne = list(zip(company,money))
+
+
+# 存储内容
+message = []
+# 总共16个页面的数据
+for page in range(17):
+    # 组装url
+    if page == 0:
+        url = "https://top.chinaz.com/gongsi/index_zhuce.html"
+    else:
+        url = "https://top.chinaz.com/gongsi/index_zhuce_{}.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)
+    money=re.findall('<em>(.+?)</em>注册资本</div>', html)
+   
+    pageOne = list(zip(company,money))
+    # 合并列表
+    message.extend(pageOne)
+
+
+
+# 导入python中的内置模块csv
+import csv
+with open("content.csv", "w") as f:
+    w = csv.writer(f)
+    w.writerows(message)
+    
+    
+import pandas as pd
+
+# 读取数据
+df = pd.read_csv("content.csv", names=["company",'money'],encoding='gbk')
+df.head()
+df.info()
+
+#数据预处理
+df['money']=df['money'].apply(lambda x:x.replace('亿','') )
+df['money']=df['money'].apply(lambda x: float(x) )
+#获取top20
+df1=df.sort_values(by='money',ascending=False)
+df2=df1.iloc[0:20]
+#数据可视化 绘制水平条形图
+import matplotlib.pyplot as plt
+x=df2['company']
+y=df2['money']
+plt.barh(x,y,height=0.8)
+for i,j in zip(x,y):
+      plt.text(j,i,j)
+plt.title('中国500强注册资金top20企业')
+plt.show()
+
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