Data Processing and Enrichment in Python

📅 2025-06-22 — Session: Data Processing and Enrichment in Python

🕒 20:25–21:00
🏷️ Labels: Data Cleaning, Data Enrichment, Pandas, Python, Data Processing
📂 Project: Dev
⭐ Priority: MEDIUM

The session aimed to address various data processing challenges, including data cleaning, enrichment, and merging using Python and Pandas.

Diagnosed and fixed issues with empty columns in the DataFrame df_scraped after loading a JSONL file.
Enriched articles using master_ref.csv, constructing keys and merging data.
Debugged key mismatches in DataFrame merges, ensuring consistent data types and validating key existence.
Resolved a KeyError in DataFrame processing due to missing columns by constructing necessary keys.
Finalized data merge in the pipeline with scraped_data using index_id.
Handled NaN values in DataFrame columns using regex safely.
Optimized DataFrame merge in Pandas to avoid column duplication.

Successfully addressed multiple data processing issues, ensuring data integrity and enhancing the data pipeline.

No major pending tasks, but continued monitoring and optimization of data processes are recommended.