how to add scraped information from a website to a dataframe in python

To add scraped information from a website to a dataframe in Python, you'll need to use a combination of web scraping libraries such as BeautifulSoup and requests, and data manipulation libraries such as pandas.

Here's a sample code that demonstrates how to scrape a website for data and add it to a pandas dataframe:


main.py
import requests
from bs4 import BeautifulSoup
import pandas as pd

url = 'https://www.example.com' # replace with the website you want to scrape
response = requests.get(url)
soup = BeautifulSoup(response.text, 'html.parser')

# find the HTML elements containing the data you want to scrape
data_list = soup.find_all('div', class_='data')

# create an empty dataframe to store the scraped data
df = pd.DataFrame(columns=['Column_Name_1', 'Column_Name_2'])

# loop through the scraped data and append it to the dataframe
for data in data_list:
    column_1 = data.find('span', class_='column-1').text
    column_2 = data.find('span', class_='column-2').text
    df = df.append({'Column_Name_1': column_1, 'Column_Name_2': column_2}, ignore_index=True)

# print the final dataframe
print(df)
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This code uses requests to get the HTML from the website, and BeautifulSoup to parse it and find the HTML elements containing the data you want to scrape. It then creates an empty pandas dataframe with the desired column names, and uses a for loop to append the scraped data to the dataframe row by row. Finally, the dataframe is printed to the console.

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