Developed Python scripts for web scraping and NLP

• Day: 2023-11-19
• Time: 03:00 to 07:00
• Project: Business
• Workspace: WP 2: Operational
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Python, Web Scraping, NLP, Financial Services, Political Analysis

Description

Session Goal: The session aimed to develop and refine Python scripts for web scraping and natural language processing (NLP) tasks related to political speech analysis and financial account management.

Key Activities:

• Explored scenarios where financial services like Wise may change account details, focusing on customer notifications and transaction impacts.
• Drafted an inquiry template for contacting Wise customer support about account detail changes.
• Proposed innovative project ideas for analyzing political speeches using web scraping and AI, emphasizing thematic organization and educational resources.
• Developed a Python script for scraping links from the CFK Argentina website, covering data from 2007 to 2023, with error handling and compliance considerations.
• Customized URL handling in the web scraping script for specific years using a dictionary.
• Created a Python script to extract and concatenate text from URLs using requests and BeautifulSoup, with network error handling.
• Implemented a script to concatenate speeches, preprocess text, and count word frequencies in Spanish using the NLTK library.

Achievements:

• Successfully developed and tested multiple Python scripts for web scraping and text processing.
• Generated actionable insights and templates for both financial account management and political speech analysis.

Pending Tasks:

• Further refinement of the web scraping scripts to enhance efficiency and accuracy.
• Exploration of additional NLP techniques for deeper analysis of political speeches.

Evidence

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• event_ids: []