Learn NumPy Basics in Weekend

NumPy becomes especially useful when you can work confidently with arrays—not just create them, but select, reshape, compare, and transform their contents. Learn NumPy Basics in Weekend takes that hands-on route, introducing core array operations through compact explanations and practical numerical and image-based examples.

Learn NumPy by working with arrays

Hisham El-Amir starts with setup guidance for SciPy and the Python Imaging Library, then explores image resizing and flipping alongside NumPy concepts such as copies versus views. These examples give readers a way to see array behavior in action, rather than treating indexing as a list of rules to memorize.

Make sense of NumPy indexing

Fancy indexing, list-based indexing, Boolean indexing, and strides are among the techniques covered. The book also introduces broadcasting, a key idea for applying operations across arrays with compatible shapes. Together, these topics offer a focused look at how NumPy selects and manipulates data.

Put essential methods to work

Later chapters use problems such as summing Fibonacci numbers, finding prime factors, exploring palindromic numbers, and sieving integers to demonstrate practical methods. Power-law examples and trading simulations broaden the range of numerical scenarios in the book.

A focused weekend introduction

This first part of the Learn NumPy in Weekend series is suited to Python learners who want a compact, example-led introduction to array operations and commonly used NumPy techniques. Its progression from installation and indexing to applied numerical problems gives readers several different contexts in which to encounter the library.