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# -*- coding: utf-8 -*-
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# -*- coding: utf-8 -*-
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"""
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"""
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Created on Tue Dec 12 15:24:14 2023
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Created on Tue Dec 12 15:24:14 2023
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@author: Toon
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@author: Toon
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"""
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"""
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import requests
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import requests
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from lxml import etree
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from lxml import etree
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import csv
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import csv
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import pandas as pd
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import pandas as pd
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import matplotlib.pyplot as plt
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import matplotlib.pyplot as plt
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# 请求的url
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# 请求的url
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url = "https://www.bitpush.news/covid19/"
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url = "https://www.bitpush.news/covid19/"
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# 设置请求头信息
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# 设置请求头信息
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headers = {
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headers = {
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"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"
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"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"
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}
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}
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# 使用reqeusts模快发起 GET 请求
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# 使用reqeusts模快发起 GET 请求
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response = requests.get(url, headers=headers)
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response = requests.get(url, headers=headers)
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# 获取请求的返回结果
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# 获取请求的返回结果
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html = response.text
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html = response.text
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parse = etree.HTMLParser(encoding='utf-8') # 添加编码
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parse = etree.HTMLParser(encoding='utf-8') # 添加编码
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# 解析 requests 返回的响应结果
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# 解析 requests 返回的响应结果
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doc = etree.HTML(html)
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doc = etree.HTML(html)
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# 地区名称
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state = doc.xpath('//html/body/div/div/div[2]/div[2]/div/div/div/div//tbody/tr/td/span/text()')
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state = doc.xpath('//html/body/div/div/div[2]/div[2]/div/div/div/div//tbody/tr/td/span/text()')
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# 确诊人数
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# 确诊人数
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person = doc.xpath('//html/body/div/div/div[2]/div[2]/div/div/div/div//tbody/tr/td[2]/text()')
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person = doc.xpath('//html/body/div/div/div[2]/div[2]/div/div/div/div//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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# 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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person = [x.replace(",", "") for x in person]
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# 死亡人数
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# 死亡人数
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death = doc.xpath('//html/body/div/div/div[2]/div[2]/div/div/div/div//tbody/tr/td[3]/text()')
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death = doc.xpath('//html/body/div/div/div[2]/div[2]/div/div/div/div//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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# 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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death = [x.replace(",", "") for x in death]
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message = list(zip(state, person, death))
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message = list(zip(state, person, death))
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with open("content.csv", "w") as f:
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with open("content.csv", "w") as f:
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w = csv.writer(f)
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w = csv.writer(f)
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w.writerows(message)
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w.writerows(message)
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df = pd.read_csv("content.csv", names=["country", "person", "death"],encoding='gbk')
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df = pd.read_csv("content.csv", names=["country", "person", "death"],encoding='gbk')
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df.head()
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df.head()
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df.info()
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df.info()
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df1 = df.head(15)
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df1 = df.head(15)
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df1 = df1[::-1]
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df1 = df1[::-1]
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# 在jupyter中直接展示图像
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# 设置中文显示
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#%matplotlib inline
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plt.rcParams['font.sans-serif'] = ['SimHei']
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# 设置中文显示
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plt.rcParams['figure.figsize'] = (5,5) # 设置figure_size尺寸
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plt.rcParams['font.sans-serif'] = ['SimHei']
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plt.rcParams['figure.figsize'] = (5,5) # 设置figure_size尺寸
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#制作柱形图
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x = df1["country"].values
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#制作柱形图
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y = df1["person"].values
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x = df1["country"].values
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plt.barh(x, y)
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y = df1["person"].values
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plt.ylabel("国家",fontsize=14)
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plt.barh(x, y)
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plt.xlabel("确诊人数",fontsize=14)
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plt.ylabel("国家",fontsize=14)
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for x,y in zip(y,x):
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plt.xlabel("确诊人数",fontsize=14)
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plt.text(x, y,x, ha='left', va='center',color='r')
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for x,y in zip(y,x):
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plt.text(x, y,x, ha='left', va='center',color='r')
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plt.show()
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plt.show()
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