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aaapachong.py(1).py

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+# -*- coding: utf-8 -*-
+"""
+Created on Fri Dec  2 21:14:38 2022
+@name:全球疫情数据爬取
+@author: 86156
+"""
+#爬取网页内容
+import requests
+from lxml import etree
+import pandas as pd
+import csv
+import matplotlib.pyplot as plt
+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/95.0.4638.69 Safari/537.36"
+}
+response = requests.get(url, headers=headers)
+html = response.text
+html
+#使用lxml解析数据信息
+parse = etree.HTMLParser(encoding='utf-8')
+doc = etree.HTML(html)
+#使用xpath语句筛选美国疫情数据
+country = doc.xpath('//div[@class="table_container"]//tbody/tr/td/span/text()')
+person = doc.xpath('//div[@class="table_container"]//tbody/tr/td[2]/text()')
+death = doc.xpath('//div[@class="table_container"]//tbody/tr/td[3]/text()')
+st=country.index('加州')#st=101
+en=country.index('美属萨摩亚')#en=158
+person = [x.replace(",", "") for x in person[st:en+1]]
+death = [x.replace(",", "") for x in death[st:en+1]]
+state=country[st:en+1]
+#将数据打包并转换成列表
+message = list(zip(state, person, death))
+message
+
+#将message中的文件保存至csv文件中
+df = pd.DataFrame(message)
+df.to_csv('content.csv')#保存在csv文件
+
+
+# 读取数据
+df = pd.read_csv("content.csv", names=["State", "person", "death"])
+df=df.sort_values(by=['person'],ascending=False)
+df1 = df.head(15)
+
+import matplotlib.pyplot as plt
+
+# 设置中文显示
+plt.rcParams['font.sans-serif'] = ['SimHei']
+plt.rcParams['figure.figsize'] = (15, 5)  # 设置figure_size尺寸
+
+
+# x轴坐标
+x = df1["State"].values
+# y轴坐标
+y = df1["person"].values
+# 绘制柱状图
+plt.bar(x, y)
+# 设置x轴名称
+plt.xlabel("不同地区",fontsize=14)
+# 设置x轴名称
+plt.ylabel("确诊人数",fontsize=14)
+plt.show()
+