Official Numpy Documentation

Welcome to the official documentation for Numpy, the fundamental package for scientific computing with Python.

Overview

Numpy is the foundation for many high-level tools in Python for data analysis, including Pandas, SciPy, and Scikit-learn. It provides support for large, multi-dimensional arrays and matrices, along with a collection of mathematical functions to operate on these arrays.

Installation

To install Numpy, you can use pip:

pip install numpy

Getting Started

Basic Usage

Numpy arrays are fundamental to Numpy and are used in almost every program involving Numpy. They can be seen as a table of data with rows and columns or as a multi-dimensional container of items.

Here's a simple example:

import numpy as np

# Create a 1D array
a = np.array([1, 2, 3])

# Create a 2D array
b = np.array([[1, 2], [3, 4]])

Operations

Numpy provides a wide range of mathematical functions to operate on arrays.

Element-wise operations:
```
c = a + b
```
Broadcasting:
```
d = a * b[:, np.newaxis]
```