Developed text processing and data manipulation functions

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Developed text processing and data manipulation functions

  • Day: 2023-11-11
  • Time: 03:00 to 04:40
  • Project: Dev
  • Workspace: WP 2: Operational
  • Status: Completed
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: Python, Text Processing, Data Manipulation, NLP, Automation

Description

Session Goal

The session aimed to develop and refine functions for text processing and data manipulation using Python, focusing on cleaning, formatting, and analyzing text data.

Key Activities

  • Implemented a Python function to merge invalid text sections into valid ones, enhancing data integrity.
  • Utilized Python’s random.sample for random sampling from tuples, addressing common errors with np.random.choice.
  • Outlined a structured approach for semantic analysis, covering objectives, data preparation, and analysis techniques.
  • Developed Python rules for fixing parsing errors using str.replace() and regular expressions.
  • Created functions for text cleaning and standardization, focusing on punctuation, spacing, and spelling corrections.
  • Applied cleaning functions to merged sections and regenerated them from original data after a disconnection.
  • Converted cleaned text data into a Pandas DataFrame for further analysis.
  • Counted word frequencies in Spanish text using NLTK, excluding stopwords.

Achievements

  • Successfully developed and tested multiple text processing functions, improving data quality and consistency.
  • Enhanced data manipulation capabilities with Pandas, facilitating structured data analysis.
  • Established a framework for semantic analysis, setting the stage for future NLP tasks.

Pending Tasks

  • Re-upload the original text file or raw text to regenerate lost merged_sections due to a disconnection.
  • Further refine text cleaning functions to handle more complex inconsistencies.
  • Explore additional NLP techniques for deeper semantic analysis.

Evidence

  • source_file=2023-11-11.sessions.jsonl, line_number=0, event_count=0, session_id=e4d09dbeead97cfb5d233140eb9c5795326f3718fe520e57d24f514ac32572a9
  • event_ids: []

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