ADD file via upload

新冠疫情各国死亡人数爬虫.py

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+# -*- coding: utf-8 -*-
+"""
+Created on Wed Jun  5 19:22:56 2024
+
+@author: 44665
+"""
+
+import requests
+from lxml import etree
+import csv
+import pandas as pd
+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"
+}
+
+try:
+    response = requests.get(url, headers=headers)
+    response.raise_for_status()  # 检查是否请求成功
+except requests.exceptions.RequestException as e:
+    print("请求错误:", e)
+    exit()
+
+html = response.text
+
+parse = etree.HTMLParser(encoding='utf-8')
+doc = etree.HTML(html)
+
+# 解析国家、确诊人数和死亡人数
+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()')
+a = country.index('加州')
+state = country[a:]
+state_person = person[a:]
+state_death = death[a:]
+
+
+# 去除确诊人数和死亡人数中的逗号，并转换为整数
+person = [int(x.replace(",", "")) for x in person]
+death = [int(x.replace(",", "")) for x in death]
+state_person = [int(x.replace(",", "")) for x in state_person]
+state_death = [int(x.replace(",", "")) for x in state_death]
+# 将数据存储到列表中
+message = list(zip(country, person, death))
+message = sorted(message, key=lambda x: x[-1], reverse=True)
+
+# 将数据写入 CSV 文件
+with open("content.csv", "w", newline='', encoding='utf-8') as f:
+    w = csv.writer(f)
+    w.writerows(message)
+
+# 读取 CSV 文件并创建 DataFrame
+df = pd.read_csv("content.csv", names=["country", "person", "death"])
+df = df.drop(0)
+df = df.head(10)
+
+# 绘制柱状图
+plt.rcParams['font.sans-serif'] = ['SimHei']
+plt.rcParams['figure.figsize'] = (10, 5)
+
+x = df["country"].values
+y = df["death"].values
+z = df['person'].values
+
+colors=['red','green','blue','cyan','grey','black','yellow','orange','pink','purple']
+plt.bar(x, y,color=colors)
+plt.xlabel("国家", fontsize=14)
+plt.ylabel("死亡人数", fontsize=14)
+plt.title("COVID-19 死亡人数排名前十国家", fontsize=16)
+for i,j in zip(x,y):
+    plt.text(i,j,j,ha='center')
+plt.xticks(rotation=45)  # x轴标签旋转45度，防止重叠
+plt.show()
+#绘制饼图
+plt.rcParams['figure.figsize'] = (15, 10)
+colors1=['maroon','crimson','yellow','olive','cyan','lavender','purple','teal','pink','magenta']
+explode=[0.1,0,0,0,0,0,0,0,0,0]
+labels=['美国','巴西','印度','俄罗斯','墨西哥','秘鲁','英国','印尼','意大利','伊朗']
+plt.pie(y,explode=explode,labels=labels,colors=colors1,shadow=True,autopct='%.2f%%')
+plt.legend()
+plt.title('COVID-19 死亡人数排名前十国家')
+plt.show()        
+
+
+#将数据重新存储一个列表
+message = list(zip(country, person, death))
+message = sorted(message, key=lambda x: x[-2], reverse=True)
+
+# 将数据写入 CSV 文件
+with open("content.csv", "w", newline='', encoding='utf-8') as f:
+    w = csv.writer(f)
+    w.writerows(message)
+
+# 读取 CSV 文件并创建 DataFrame
+df = pd.read_csv("content.csv", names=["country", "person", "death"])
+df = df.drop(0)
+df = df.head(20)
+
+# 绘制两幅折线图
+plt.rcParams['font.sans-serif'] = ['SimHei']
+plt.rcParams['figure.figsize'] = (15, 12)
+
+x = df["country"].values
+y = df["death"].values
+z = df['person'].values
+
+plt.subplot(211)
+plt.plot(x,z,color='crimson',marker='*',linestyle='--',label='确诊人数')
+plt.legend(loc='upper right')
+plt.xlabel("国家", fontsize=14)
+plt.ylabel("确诊人数", fontsize=14)
+plt.xticks(rotation=45)  # x轴标签旋转45度，防止重叠
+plt.title("COVID-19 确诊人数排名前二十国家确诊人数与死亡人数对比", fontsize=16)
+plt.subplot(212)
+plt.plot(x,y,color='teal',linestyle='-',marker='D',label='死亡人数')
+plt.xlabel("国家", fontsize=14)
+plt.ylabel("死亡人数", fontsize=14)
+plt.legend(loc='upper right')
+plt.xticks(rotation=45)  # x轴标签旋转45度，防止重叠
+plt.show()
+
+#将州数据再写进列表
+state_message = list(zip(state, state_person, state_death))
+state_message = sorted(state_message, key=lambda x: x[-1], reverse=True)
+# 将数据写入 CSV 文件
+with open("state_content.csv", "w", newline='', encoding='utf-8') as f:
+    w = csv.writer(f)
+    w.writerows(state_message)
+
+# 读取 CSV 文件并创建 DataFrame
+df1 = pd.read_csv("state_content.csv", names=["state", "state_person", "state_death"])
+df1 = df1.drop(0)
+df1 = df1.head(10)
+#绘制柱状图
+plt.rcParams['font.sans-serif'] = ['SimHei']
+plt.rcParams['figure.figsize'] = (10, 5)
+
+colors1=['maroon','crimson','yellow','olive','cyan','lavender','purple','teal','pink','magenta']
+x = df1["state"].values
+y = df1["state_death"].values
+plt.barh(x,y,height=0.8,color=colors1)
+plt.xlabel('死亡人数')
+plt.ylabel('州')
+plt.title('美国COVID-19 死亡人数排名前十的州')
+plt.show()