import requests
from lxml import etree
import csv
import pandas as pd
import matplotlib.pyplot as plt
# 步骤一（替换sans-serif字体）
plt.rcParams['font.sans-serif'] = ['SimHei'] 
# 步骤二（解决坐标轴负数的负号显示问题）
plt.rcParams['axes.unicode_minus'] = False
# 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"
}

url = "https://www.bitpush.news/covid19/"

try:
    # 发起 GET 请求
    response = requests.get(url, headers=headers)
    response.raise_for_status()
    response.encoding = response.apparent_encoding  # 确保编码正确
    html = response.text
except requests.RequestException as e:
    print(f"请求出错: {e}")
    html = ""

if html:
    # 解析 HTML
    doc = etree.HTML(html)

    # 获取国家名称
    country= doc.xpath('//div[@class="table_container"]//tbody/tr/td/span/text()')
    # 获取确诊人数
    person = doc.xpath('//div[@class="table_container"]//tbody/tr/td[2]/text()')
    person = [x.replace(",", "") for x in person]
    # 获取死亡人数
    death = doc.xpath('//div[@class="table_container"]//tbody/tr/td[3]/text()')
    death = [x.replace(",", "") for x in death]

    # 组合数据
    message = list(zip(country, person, death))
    # 按死亡人数排序
    message1 = sorted(message, key=lambda x: int(x[-1]), reverse=True)

    # 保存数据到CSV文件
    with open("content1.csv", "w", newline='', encoding='utf-8') as f:
        w = csv.writer(f)
        w.writerow(["country", "person", "death"])  # 添加表头
        w.writerows(message1)

    # 读取数据
    df = pd.read_csv("content1.csv")
    df1 = df.head(10)

    # 绘制柱状图
    plt.figure(figsize=(12, 6))
    plt.bar(df1["country"], df1["death"].astype(int))
    plt.xlabel("国家", fontsize=14)
    plt.ylabel("死亡人数", fontsize=14)
    plt.title("COVID-19死亡人数前10的国家", fontsize=16)

    # 显示每个柱的数值
    for i, v in enumerate(df1["death"].astype(int)):
        plt.text(i, v + 0.02 * max(df1["death"].astype(int)), str(v), ha='center', fontsize=12)

    plt.xticks(rotation=45)
    plt.tight_layout()
    plt.show()
    # 按确诊人数排序
    message2 = sorted(message, key=lambda x: int(x[-2]), reverse=True)

    # 保存数据到CSV文件
    with open("content2.csv", "w", newline='', encoding='utf-8') as f:
        w = csv.writer(f)
        w.writerow(["country", "person", "death"])  # 添加表头
        w.writerows(message2)

    # 读取数据
    df = pd.read_csv("content2.csv")
    df2 = df.head(10)

    # 绘制柱状图
    plt.figure(figsize=(12, 6))
    plt.bar(df2["country"], df2["person"].astype(int))
    plt.xlabel("国家", fontsize=14)
    plt.ylabel("确诊人数", fontsize=14)
    plt.title("COVID-19确诊人数前10的国家", fontsize=16)

    # 显示每个柱的数值
    for i, v in enumerate(df2["person"].astype(int)):
        plt.text(i, v + 0.02 * max(df2["death"].astype(int)), str(v), ha='center', fontsize=12)

    plt.xticks(rotation=45)
    plt.tight_layout()
    plt.show()
    # 获取州的名称
    a=country.index('加州')
    zhou=country[a:]
    # 获取确诊人数
    person1=person[a:]
     # 获取死亡人数
    death1=death[a:]
    #组合数据
    message0=list(zip(zhou,person1,death1))
    # 按死亡人数排序
    message3=sorted(message0, key=lambda x: int(x[-1]), reverse=True)
    # 保存数据到CSV文件
    with open("content3.csv", "w", newline='', encoding='utf-8') as f:
        w = csv.writer(f)
        w.writerow(["zhou", "person1", "death1"])  # 添加表头
        w.writerows(message3)
    # 读取数据
    df = pd.read_csv("content3.csv")
    df3 = df.head(10)
    # 绘制折线图
    plt.figure(figsize=(12, 6))
    plt.plot(df3["zhou"], df3["death1"].astype(int), marker='o')
    plt.xlabel("州", fontsize=14)
    plt.ylabel("死亡人数", fontsize=14)
    plt.title("美国COVID9死亡人数前十的州", fontsize=16)
    # 显示每个点的数值
    for i, v in enumerate(df3["death1"].astype(int)):
        plt.text(i, v + 0.02 * max(df3["death1"].astype(int)), str(v), ha='center', fontsize=12)
    # 按确诊人数排序
    message4=sorted(message0, key=lambda x: int(x[-2]), reverse=True)
    # 保存数据到CSV文件
    with open("content4.csv", "w", newline='', encoding='utf-8') as f:
        w = csv.writer(f)
        w.writerow(["zhou", "person1", "death1"])  # 添加表头
        w.writerows(message4)
    # 读取数据
    df = pd.read_csv("content4.csv")
    df4 = df.head(10)
    # 绘制折线图
    plt.figure(figsize=(12, 6))
    plt.plot(df3["zhou"], df3["person1"].astype(int), marker='o')
    plt.xlabel("州", fontsize=14)
    plt.ylabel("确诊人数", fontsize=14)
    plt.title("美国COVID9确诊人数前十的州", fontsize=16)
     # 显示每个点的数值
    for i, v in enumerate(df3["person1"].astype(int)):
        plt.text(i, v + 0.02 * max(df3["death1"].astype(int)), str(v), ha='center', fontsize=12)