Enhanced Python DataFrame ID Generation and Saving

• Day: 2023-08-05
• Time: 09:25 to 10:00
• Project: Dev
• Workspace: WP 2: Operational
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Python, Dataframe, Unique Id, Code Optimization, Data Saving

Description

Session Goal:

The goal of this session was to explore methods for generating unique IDs in a Python DataFrame and efficiently saving this data.

Key Activities:

• Generated unique IDs for DataFrame rows by combining random numbers with the last two digits of the year, ensuring reproducibility with a set seed.
• Used file size as a seed for random number generation to maintain ID consistency across runs with the same file.
• Inserted a new ‘ID’ column in a DataFrame at a specified location using the insert function.
• Saved the DataFrame to a CSV file, including the index as a column, and named the index column using pandas.
• Improved efficiency by modifying code to save only predictions, enhancing memory efficiency and storage.
• Corrected Python code for defining a list of dictionaries in the predict_save function, ensuring proper syntax.

Achievements:

• Successfully implemented a reproducible method for generating unique IDs in DataFrames.
• Improved data saving efficiency by focusing on predictions.
• Corrected and optimized Python code for better performance.

Pending Tasks:

• Further explore optimization techniques for large-scale data handling in Python.

Evidence

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• event_ids: []