Company Ratings And Salary Dataset

This dataset contains structured company-related information collected through web scraping techniques and processed using Python. The data was extracted from multiple pages, cleaned, organized, and converted into CSV format for analytics, visualization, and machine learning applications.

The dataset includes valuable fields such as company names, ratings, reviews, salaries, interviews, job information, and benefits. The complete workflow involved automated HTTP requests, HTML parsing, data extraction, preprocessing, pagination handling, and DataFrame generation using libraries like requests, BeautifulSoup, pandas, and lxml.

The purpose of this project was to understand real-world data collection pipelines and demonstrate practical implementation of web scraping and dataset generation techniques. This dataset can be useful for data analysis, exploratory data analysis (EDA), machine learning projects, data preprocessing practice, visualization dashboards, and web scraping learning purposes.

The project also demonstrates handling of multi-page scraping workflows, structured data organization, and CSV dataset creation commonly used in data engineering and analytics environments.