Python NumPy – Complete Study Notes
Introduction
NumPy (Numerical Python) is a fundamental library used for numerical computing in
Python. It provides powerful data structures and functions for handling large datasets
efficiently.
It is widely used in data science, machine learning, scientific computing, and financial
analysis.
NumPy serves as the backbone for many advanced libraries such as Pandas, TensorFlow,
and Scikit-learn.
Definition
NumPy is an open-source Python library that provides support for multi-dimensional
arrays and matrices.
It includes a wide range of mathematical functions to perform operations on these arrays
efficiently.
NumPy is optimized for performance and is significantly faster than Python lists for
numerical operations.
Installing and Importing NumPy
NumPy can be installed using pip: pip install numpy.
It is commonly imported as: import numpy as np.
This standard alias makes the code concise and easier to read.
NumPy Arrays
A NumPy array is a central data structure that stores elements of the same data type.
It allows fast and efficient computations compared to Python lists.
Example:
import numpy as np
arr = np.array([1,2,3,4])
print(arr)
