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A hands-on Jupyter notebook that uses Python’s re library to extract and organize key info, money, dates, emails, citations, transaction codes, from five real-world texts: financial reports, academic papers, audit logs, customer messages, and long-form journalism.

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Text-analysis

Python re Module Project

This repository explores and demonstrates the use of the re module in Python, which provides support for working with regular expressions. The goal of this project is to showcase various functionalities of the module, including pattern matching, search, and substitution within strings. By experimenting with different regex patterns and functions, this repository helps users understand how to efficiently manipulate and extract data from text using Python's built-in regular expression tools.

Key features include:

  1. Pattern matching using re.match(), re.search(), and re.findall()
  2. String replacement with re.sub()
  3. Compiling and using regular expression patterns for efficiency
  4. Practical examples and use cases

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A hands-on Jupyter notebook that uses Python’s re library to extract and organize key info, money, dates, emails, citations, transaction codes, from five real-world texts: financial reports, academic papers, audit logs, customer messages, and long-form journalism.

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