NumPy Arrays
Explore the fundamental concepts of NumPy arrays, including one- and two-dimensional arrays, and learn to create arrays using Python lists, tuples, and NumPy functions. Understand key built-in methods like arange, linspace, zeros, ones, and how to generate random numbers with NumPy. This lesson equips you with essential skills to use NumPy arrays effectively for data analysis and scientific computing in Python.
We'll cover the following...
NumPy
NumPy is a fundamental package for scientific computing, so it’s essential to have an excellent understanding of this powerful library. It provides foundational tools for mathematical, scientific, engineering, and data science programming within the Python ecosystem. NumPy is useful because:
- It’s a linear algebra library.
- It’s powerful and incredibly fast.
- It integrates C/C++ and Fortran code. In this lesson, we’ll cover the key concepts of NumPy, which we’ll frequently use in this course. Let’s start with NumPy arrays, along with some important built-in methods and attributes that are related to these arrays.
Note: For complete documentation of NumPy and to explore more on NumPy, visit its official website.
The main object in NumPy is a homogeneous multidimensional array. It serves as a building block of most of the PyData ecosystem libraries. Once ...