diff --git a/爬虫.py b/爬虫.py
new file mode 100644
index 0000000..29936f1
--- /dev/null
+++ b/爬虫.py
@@ -0,0 +1,75 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Thu May 23 22:35:58 2024
+
+@author: Lenovo
+"""
+
+import requests
+url = "https://www.bitpush.news/covid19/"
+headers = {"User-Agent":"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36 Edg/116.0.1938.54"}
+response = requests.get(url,headers=headers)
+html = response.text
+
+from lxml import etree
+parse = etree.HTMLParser(encoding='gbk')
+doc = etree.HTML(html)
+
+area = doc.xpath('//*[@id="main"]/div[2]/div/div/div/div/div[1]/table/tbody/tr/td[1]/span/text()')
+person = doc.xpath('//*[@id="main"]/div[2]/div/div/div/div/div[1]/table/tbody/tr/td[2]/text()')
+person = [x.replace(",", "") for x in person]
+death = doc.xpath('//*[@id="main"]/div[2]/div/div/div/div/div[1]/table/tbody/tr/td[3]/text()')
+death = [x.replace(",", "") for x in death]
+message = list(zip(area, person, death))
+
+import csv
+with open("content.csv", "w") as f:
+    w = csv.writer(f)
+    w.writerows(message)
+
+import pandas as pd
+df = pd.read_csv("content.csv", names=["area", "person", "death"],encoding='gbk')
+df.head()
+df.info()
+df1 = df.drop(0).head(15)
+
+import matplotlib.pyplot as plt
+#确诊人数垂直图
+plt.rcParams['font.sans-serif'] = ['SimHei']
+plt.rcParams['figure.figsize'] = (10, 5)  
+x = df1["area"].values
+y = df1["person"].values
+plt.bar(x, y)
+plt.xlabel("地区",fontsize=14)
+plt.ylabel("确诊人数",fontsize=14)
+plt.show()
+#确诊人数水平图
+x = df1["area"].values 
+y = df1["person"].values 
+colors=['red','green','cyan','blue']
+plt.barh(x, y,height=0.8,color=colors)
+plt.yticks(x)
+plt.xlabel("确诊人数",fontsize=14)
+plt.ylabel("地区",fontsize=14)
+for i,j in zip(x,y): 
+    plt.text(j,i,j)
+plt.legend()
+plt.show()
+#死亡人数垂直图
+plt.rcParams['font.sans-serif'] = ['SimHei']
+plt.rcParams['figure.figsize'] = (10, 5)  
+x = df1["area"].values
+y = df1["death"].values
+plt.bar(x, y)
+plt.xlabel("地区",fontsize=14)
+plt.ylabel("死亡人数",fontsize=14)
+plt.show()
+#确诊人数饼图
+import numpy as np
+import matplotlib.pyplot as plt
+labels = df1["area"].values
+sizes = df1["person"].values
+explode = (0.1,0,0,0,0,0,0,0,0,0,0,0,0,0,0)
+plt.pie(sizes,explode,labels=labels,autopct='%.1f%%')
+plt.title("美国疫情确诊人数排名 top15 地区情况")
+