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49 lines
1.8 KiB
49 lines
1.8 KiB
import requests
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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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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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}
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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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# 获取请求的返回结果
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html = response.text
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# 导入 lxml
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from lxml import etree
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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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doc = etree.HTML(html)
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# 州名
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country = doc.xpath('//*[@id="main"]/div[2]/div/div/div/div/div[1]/table/tbody/tr/td/span/text()')
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# 确诊人数
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person = doc.xpath('//*[@id="main"]/div[2]/div/div/div/div/div[1]/table/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('//*[@id="main"]/div[2]/div/div/div/div/div[1]/table/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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# 打包数据之后将其转换成列表
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message = list(zip(country, person, death))
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message=message[:10]
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# 导入python中的内置模块csv
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import csv
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with open("content.csv", "w",encoding="utf-8") as f:
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w = csv.writer(f)
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w.writerows(message)
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import pandas as pd
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# 读取数据
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df = pd.read_csv("content.csv", names=["country", "person", "death"],encoding="utf-8")
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print(df)
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import matplotlib.pyplot as plt
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plt.rcParams['font.sans-serif'] = ['SimHei']
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plt.rcParams['axes.unicode_minus'] = False
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plt.rcParams['figure.figsize'] = (10, 5)
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x = df["country"]
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y = df["death"]
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plt.bar(x,y)
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plt.xlabel("美国州名",fontsize=14)
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plt.ylabel("死亡人数",fontsize=14)
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plt.show()
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