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# -*- coding: utf-8 -*-
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"""
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Created on Thu May 26 16:41:59 2022
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@author: 张舒心 保婧芝
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"""
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import csv #用于把爬取的数据存储为csv格式，可以excel直接打开的
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import time #用于对请求加延时，爬取速度太快容易被反爬
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from time import sleep #同上
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import random #用于对延时设置随机数，尽量模拟人的行为
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import requests #用于向网站发送请求
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from lxml import etree #lxml为第三方网页解析库，强大且速度快
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import pandas as pd
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import matplotlib.pyplot as plt
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url='https://www.bitpush.news/covid19/'
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headers={'User-Agent': "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/101.0.4951.64 Safari/537.36 Edg/101.0.1210.53"}
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response = requests.get(url, headers=headers,timeout=10)
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html=response.text
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parse = etree.HTMLParser(encoding='utf-8')
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doc = etree.HTML(html)
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continent = doc.xpath('//div[@class="table_container"]//tbody/tr/td/span/text()')
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# 确诊人数
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person = doc.xpath('//div[@class="table_container"]//tbody/tr/td[2]/text()')
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# 由于确诊人数中有逗号，我们使用列表推导式删除
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person = [x.replace(",", "") for x in person]
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# 死亡人数
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death = doc.xpath('//div[@class="table_container"]//tbody/tr/td[3]/text()')
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# 同样使用列表推导式删除逗号
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death = [x.replace(",", "") for x in death]
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message = list(zip(continent, person, death))
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message
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with open("pandemic.csv", "w") as f:
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w = csv.writer(f)
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w.writerows(message)
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df = pd.read_csv("pandemic.csv", names=["continent", "person", "death"],encoding='gbk')
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df.info()
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df1 = df.drop(0).tail(58)
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df1=df1.head(15)
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print(df1)
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# 在jupyter中直接展示图像
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%matplotlib inline
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# 设置中文显示
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plt.rcParams['font.sans-serif'] = ['SimHei']
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plt.rcParams['figure.figsize'] = (10, 5) # 设置figure_size尺寸
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# x轴坐标
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x = df1["continent"].values
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# y轴坐标
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y = df1["person"].values
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# 绘制柱状图
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plt.bar(x, y)
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# 设置x轴名称
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plt.xlabel("地区",fontsize=14)
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# 设置x轴名称
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plt.ylabel("确诊人数",fontsize=14)
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plt.show()
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