📅 2023-01-23 — Session: Optimized Census Data Processing with Dask
🕒 01:45–03:00
🏷️ Labels: Dask, Data Processing, Optimization, Python, Census Data
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to optimize the processing of census data using Dask and Python, focusing on loading, filtering, and merging datasets efficiently.
Key Activities
- Data Loading: Utilized Dask and pandas to load and filter census data from CSV files, specifically targeting housing, households, and individual datasets.
- Data Processing: Implemented workflows using Dask for handling large datasets, including merging, sampling, and computing ratios based on population projections.
- Code Correction: Corrected Python code for Dask DataFrames to ensure the use of the
compute()function for accurate data retrieval. - Optimization: Discussed and implemented optimizations such as pre-computation before merging and using
with ProgressBar():for tracking operations.
Achievements
- Successfully loaded and filtered large datasets using Dask and pandas.
- Improved data processing efficiency by optimizing code for merging operations and reducing unnecessary computations.
Pending Tasks
- Further optimization of data processing workflows to enhance performance.
- Exploration of additional Dask features for better handling of large datasets.