📅 2023-08-05 — Session: Enhanced DataFrame ID Generation and Saving Techniques

🕒 09:20–10:00
🏷️ Labels: Python, Dataframe, Id Generation, Data Saving, Code Optimization
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal:

The session aimed to enhance data manipulation techniques in Python, focusing on generating unique IDs for DataFrame rows and optimizing data saving processes.

Key Activities:

  • Generating Unique IDs: Explored methods to create unique IDs for DataFrame rows by combining random numbers with the last two digits of the year, using a set seed for reproducibility.
  • Seeding with File Size: Implemented a technique to use file size as a seed for random number generation, ensuring consistent ID generation across runs with the same file.
  • Inserting Columns: Demonstrated how to insert a new column in a DataFrame at a specified location using the insert function.
  • Saving DataFrames: Detailed the process of saving a DataFrame to a CSV file with the index included as a column, using pandas.
  • Efficiency Improvement: Reflected on code optimization by saving only predictions instead of both input data and predictions, enhancing memory efficiency.
  • Code Correction: Provided a corrected Python code for defining a list of dictionaries in the predict_save function, ensuring proper syntax.

Achievements:

  • Successfully implemented unique ID generation techniques and optimized data saving strategies.
  • Improved code efficiency and correctness in data handling tasks.

Pending Tasks:

  • Further exploration of additional methods for ID generation and data saving optimizations could be beneficial.