📅 2023-03-29 — Session: Optimized Data Storage and Transformation Techniques

🕒 21:00–21:20
🏷️ Labels: Data Storage, Pandas, Categorical Data, JSON, Python
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to explore and implement efficient data storage and transformation techniques using Python’s pandas library.

Key Activities

  • Discussed efficient methods for storing data with low unique values, including sparse matrices, pivot tables, and databases.
  • Explored optimization of data storage by converting columns to categorical data types in Python using pandas.
  • Provided code snippets for converting DataFrame columns, concatenating DataFrames, and ensuring data type retention.
  • Demonstrated saving a DataFrame as a JSON file and implementing JSON data storage using Python.

Achievements

  • Clarified the methods for optimizing data storage using categorical types and Apache Parquet.
  • Successfully demonstrated the conversion of DataFrame columns to categorical types and data type retention.
  • Implemented JSON data storage techniques for efficient data management.

Pending Tasks

  • Further exploration of Apache Parquet for large datasets.
  • Investigate additional data storage techniques for mixed data types.