📅 2025-03-12 — Session: Resolved resampling and alignment issues in Pandas
🕒 03:00–04:10
🏷️ Labels: Pandas, Data Alignment, Resampling, Python, Data Analysis
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The goal of this session was to address and resolve various issues related to resampling cumulative and financial data in Python using Pandas, ensuring data consistency and alignment.
Key Activities
- Resampling Cumulative Data: Implemented the use of
.last()to preserve the last observed value during resampling, preventing incorrect resets to zero. - Weekly Resampling Fixes: Ensured that all weeks are represented consistently with a Monday start, addressing issues in financial data resampling.
- Data Alignment: Aligned weekly resampling between datasets by sharing the same weekly index and reindexing.
- Avoiding NaNs: Provided solutions to avoid null values by using
.merge()instead of.reindex(). - Index Conversion: Converted PeriodIndex to DatetimeIndex for consistent data alignment in financial datasets.
Achievements
- Successfully resolved resampling issues for cumulative and financial data.
- Improved data alignment techniques in Pandas, ensuring consistency across datasets.
Pending Tasks
- Further testing of the implemented solutions in different datasets to ensure robustness and adaptability.