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Scrape website Data

Project Objective

Scrape data from cars.com and store the data in a spreadsheet.

The data scraped is Name, Mileage, Dealer Name, Ratings, Number of reviews, Price.Python and Jupyter Notebook was used this project. The libraries used are BeautifulSoup,Pandas, Requests and Openpyxl.I have applied 3 filters, certified BMW cars for a particular Zipcode to limit the data scraped for this project

image

Why is data scraping important

Data scraping, or web scraping, is important for:

  1. Business Intelligence: Gathering market data, competitor analysis, and customer insights.

  2. Market Research: Understanding customer preferences and behavior.

  3. Lead Generation: Collecting contact information for potential customers.

  4. Price Monitoring: Tracking competitor prices and optimizing pricing strategies.

  5. Content Aggregation: Gathering relevant content for marketing and trend analysis.

  6. Academic Research: Gathering large datasets for analysis and study.

  7. Government and Public Data Analysis: Analyzing public datasets and social media data for policy-making and trend identification.

Scraped_data_excel

The fields scraped from the website are saved into a Pandas dataframe and it is saved to excel using the Openpyxl library.