The goal of this project is to create a Python-based scraper that can extract information from Google and enrich existing CSV files with this data. The scraper will take in a CSV file and use the information contained within to search Google for relevant data. This data will then be appended to the appropriate rows in the original CSV file, adding additional information and context to the existing data.
The end result of this project were a fully functional Python scraper that can extract data from Google and enrich CSV files with this information.The enriched CSV file can then be used for a variety of purposes, such as data analysis, machine learning, or data visualization. This project will leverage the power of both Python and Google to provide valuable insights into the data contained within the CSV file.
An efficient and automated process for enriching CSV files with data obtained from Google.
Enhanced data sets with additional context and insights that can be used for a variety of purposes, such as data analysis, machine learning, and data visualization.
Increased productivity and accuracy compared to manual data collection and data entry methods.
A valuable tool for the end user that can save time and effort in data collection and preparation.