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
Data scraping, or web scraping, is important for:
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Business Intelligence: Gathering market data, competitor analysis, and customer insights.
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Market Research: Understanding customer preferences and behavior.
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Lead Generation: Collecting contact information for potential customers.
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Price Monitoring: Tracking competitor prices and optimizing pricing strategies.
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Content Aggregation: Gathering relevant content for marketing and trend analysis.
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Academic Research: Gathering large datasets for analysis and study.
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Government and Public Data Analysis: Analyzing public datasets and social media data for policy-making and trend identification.
The fields scraped from the website are saved into a Pandas dataframe and it is saved to excel using the Openpyxl library.