One clean setup
Use one project folder and one Python environment for this track. It keeps your cleaning code, raw files, outputs, and dependency notes together.
pandas gives you DataFrames for table work. NumPy supports pandas and gives you arrays, missing-value sentinels, and fast vector operations.
What you need
For this track, your base stack is pandas 3.0.6 and NumPy 2.5.3. pandas is the main tool for loading, inspecting, cleaning, grouping, joining, and saving tabular data.
A DataFrame is pandas’ table object. Think of it like a spreadsheet or database table you can control with code.