Learn to load, inspect, filter, clean, and manipulate structured datasets.
The official Pandas introductory tutorials teach tabular data handling using `DataFrame` and `Series` objects. You learn how to read CSV/Parquet files, select subsets of rows and columns, compute summary statistics, handle missing values, and prepare clean datasets for machine learning pipelines.
Course status is tracked independently from roadmap topic checkboxes so you can mark external courses without altering your topic mastery percentage.
Phase 0 Module 0.4 Data Handling Reference
Official open-source Pandas documentation and tutorials.
Status: Verified (2026-11-09)
Review these foundations before starting so you get the most out of this material:
In Phase 0: Programming Foundations
Study alongside Module 0.4 to practice loading, inspecting, filtering, and cleaning tabular CSV datasets.
Learn numerical arrays, broadcasting, vectorized computation, matrix operations, and scientific Python fundamentals.
Learn scientific plotting, mathematical visualization, and data visualization in Python.
Official scikit-learn getting started tutorials and user guide for classical supervised/unsupervised learning, preprocessing, cross-validation, and evaluation metrics.