Numpy Tutorial

Numpy is a powerful library for numerical computing in Python. It provides support for large, multi-dimensional arrays and matrices, along with a collection of mathematical functions to operate on these arrays efficiently.

Key Features

Arrays: Numpy provides support for arrays of different types and dimensions.
Operations: It offers a wide range of mathematical operations on arrays.
Efficiency: Numpy is optimized for performance and can handle large arrays efficiently.

Getting Started

To get started with Numpy, you can install it using pip:

pip install numpy

Example

Here is a simple example of creating a Numpy array and performing some operations:

import numpy as np

# Create a 1D array
array1 = np.array([1, 2, 3, 4, 5])

# Display the array
print(array1)

# Perform some operations
sum_array = np.sum(array1)
mean_array = np.mean(array1)

print(f"Sum of array: {sum_array}")
print(f"Mean of array: {mean_array}")

More Resources

For more information and tutorials on Numpy, you can visit the official Numpy documentation.