Enhanced Python Functions for Data Processing

2 min read

📅 2024-08-12 — Session: Enhanced Python Functions for Data Processing

🕒 00:20–23:30
🏷️ Labels: Python, Data Processing, Fuzzy Matching, File Management, Versioning
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to enhance Python functions for data processing tasks, focusing on file handling, version management, and fuzzy matching techniques.

Key Activities

  • Updated run_predict_save Function: Added an overwrite argument to manage file creation and loading, with explanations and examples.
  • Handled Scikit-learn Version Inconsistencies: Addressed warnings related to version inconsistencies, providing strategies for resolution.
  • Inverted Matcher Datasets: Developed a script to invert matcher datasets using Python, comparing DataFrames and saving results to CSV.
  • Custom Merging Strategy with Fuzzy Matching: Implemented a strategy using Levenshtein distance and rapidfuzz for merging DataFrames with slight name differences.
  • Implemented Threshold in Fuzzy Matching: Modified find_best_match function to include a threshold for valid matches.
  • Fuzzy Matching with Chunk Processing: Used fuzzywuzzy to process data in chunks, saving intermediate results.
  • Avoided SettingWithCopyWarning in Pandas: Demonstrated safe DataFrame modifications using .copy() and .loc[].

Achievements

  • Successfully updated and documented Python functions for enhanced data processing capabilities.
  • Resolved versioning issues in scikit-learn and improved data merging strategies.

Pending Tasks

  • Further testing of the updated functions in different scenarios to ensure robustness.
  • Optimization of chunk processing for large datasets.

Graph View

Backlinks