Master 70 Essential NumPy Exercises: From Basics to Advanced Techniques

This article presents a collection of 70 NumPy exercises ranging from basic array creation and indexing to advanced operations such as reshaping, broadcasting, statistical calculations, and data preprocessing.

Each problem includes a clear description, the required input code wrapped in code tags, and the expected output, providing a ready‑to‑run reference for learners.

Importing NumPy and checking its version

Creating 1‑D and 2‑D arrays, reshaping, vertical and horizontal stacking

Boolean masking, conditional replacement, and slicing

Statistical measures: mean, median, standard deviation, percentiles, softmax

Handling missing values, one‑hot encoding, sorting, and grouping

Distance calculations, nearest‑neighbor sampling, and moving averages

All examples are designed to run in Python with NumPy, making this set a practical reference for both beginners and experienced developers.