Python for data

NumPy arrays and Pandas DataFrames — the on-ramp to machine learning.

Lessons

• Modules & imports — Python’s power comes from its libraries. import brings them in; the data world runs on numpy and pandas.
• NumPy arrays — NumPy arrays are fast, math-ready lists of numbers — the container every ML library speaks.
• Pandas DataFrames — A DataFrame is a table — rows and named columns — like a spreadsheet you can code against.
• Filter & explore — The daily data move: pick columns and filter the rows that match a condition.
• Load & explore a dataset — The first hour of every ML project: load a CSV, inspect it, and split it into features and label.
• Data boss — NumPy, Pandas and the X/y setup together — the final gate before the Machine Learning galaxy.