data = soup.find_all(name = 'script',attrs = {'id':'getListByCountryTypeService2true'})

As an AI language model, I cannot access the internet or run the code. However, I can explain what the code does.

The code uses the BeautifulSoup library to scrape data from a web page. Specifically, it finds all the script tags with an id attribute of "getListByCountryTypeService2true". This is likely a unique identifier for a particular set of data on the page.

Once the script tags are found, the data contained within them can be parsed and extracted, depending on the format of the data. It's possible that this data represents information on COVID-19 cases or another type of data related to a specific country.

相关问题

import requests import pandas as pd from bs4 import BeautifulSoup # 发送请求获取网页内容 url = "https://nba.hupu.com/stats/players" headers = { "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36", "Referer": "https://nba.hupu.com/stats/players" } response = requests.get(url, headers=headers) soup = BeautifulSoup(response.text, 'html.parser') # 解析数据并保存到Excel表格中 table = soup.find_all('table', attrs={'class': 'players_table'})[0] df = pd.read_html(str(table))[0] df.to_excel('player_stats.xlsx', index=False)给以上代码绘制一个雷达图

很抱歉，作为一个语言模型，我不能直接绘制雷达图。不过，您可以使用 Python 中的 matplotlib 库来绘制雷达图。

首先，您需要从 `player_stats.xlsx` 文件中读取数据，并选择您想要绘制的球员的数据。然后，将这些数据传递给雷达图的 `plot` 函数。以下是一个简单的例子：

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

# 读取数据
df = pd.read_excel('player_stats.xlsx', header=1)

# 选择球员
player_name = 'Stephen Curry'
player_data = df[df['球员'] == player_name].iloc[:, 2:].values[0]

# 绘制雷达图
categories = df.columns[2:]
N = len(categories)

angles = np.linspace(0, 2*np.pi, N, endpoint=False)
player_data = np.concatenate((player_data, [player_data[0]]))
angles = np.concatenate((angles, [angles[0]]))

fig = plt.figure()
ax = fig.add_subplot(111, polar=True)
ax.plot(angles, player_data, 'o-', linewidth=2)
ax.fill(angles, player_data, alpha=0.25)
ax.set_thetagrids(angles * 180/np.pi, categories)
ax.set_title(player_name)
ax.grid(True)
plt.show()

代码中，我们选择了 Stephen Curry 的数据，并绘制了一个雷达图。您只需要将 `player_name` 修改为您想要绘制的球员即可。同时，您也可以根据需要修改图表的标题、线条颜色、填充颜色等参数。

while True: if(relogin==False): self.username=input('输入学号\n') self.password=input('输入密码\n') #获取表单隐藏数据 soup=BeautifulSoup(r.content,'lxml') lt = soup.find(attrs={'name': 'lt'})['value'] execution=soup.find(attrs={'name':'execution'})['value'] login_data={ 'username':self.username, 'password':self.password, 'lt':lt, 'execution':execution, '_eventId':'submit', 'signin':'登录', }

这段代码是用来进行模拟登录的，它使用了BeautifulSoup库来解析登录页面的HTML代码，并从中提取出了表单隐藏数据。然后，它构造了一个包含用户名、密码和表单隐藏数据的字典对象，并将其作为参数提交给服务器，以此来模拟用户的登录行为。其中，"username"和"password"分别对应用户输入的学号和密码，"lt"和"execution"是表单隐藏数据，"_eventId"表示事件ID，"signin"表示登录按钮的名称。这段代码的作用是实现模拟登录的功能，以便后续进行相关操作。