What is NumPy?
NumPy (Numerical Python) is a powerful library for numerical computing in Python. It supports large, multi-dimensional arrays and matrices and a collection of mathematical functions to operate on these data structures.
NumPy is the foundation for many scientific computing libraries in Python, such as SciPy, Pandas, and Matplotlib.
It is widely used in data analysis, scientific research, machine learning, and engineering.
Key Features of NumPy
- Efficient Data Handling: NumPy arrays (ndarrays) allow for efficient storage and manipulation of large datasets.
- Mathematical Functions: Provides a wide range of mathematical functions for operations on arrays.
- Broadcasting: Enables operations on arrays of different shapes without creating large intermediate arrays.
- Integration: Seamlessly integrates with other scientific libraries like SciPy, Pandas, and Matplotlib.
Installing NumPy
To use NumPy, you need to install it first. You can install NumPy using pip, Python’s package installer. Open your command prompt or terminal and run the following command:
pip install numpy
If you are using a Jupyter Notebook, you can install NumPy directly from a cell by running:
!pip install numpy
Verifying the Installation
After installing NumPy, you can verify the installation by importing NumPy and printing its version.
import numpy as np
print(np.__version__)
If the installation is successful, you will see the version number of NumPy printed in the output.
Conclusion
In this chapter, we learn about NumPy and how to install it. In the next chapter, we will cover how to create arrays using NumPy and explore different methods for creating arrays, including from lists, using built-in functions, and generating arrays with random values.