NumPyHub

Welcome to NumPyHub! This repository provides a collection of essential NumPy code snippets and tutorials designed to help you master the basics of NumPy.

Table of Contents

1. NumPy Intro
2. Array Indexing and Slicing
3. NumPy Data Types
4. Handling NaN Values
5. Statistical Operations
6. Shape, Reshape, Ravel, Flatten
7. Creating Arrays
8. Conditional Selection
9. Concatenation and Sorting

1) NumPy Intro

This section provides an introduction to NumPy and its basics.

2) Array Indexing and Slicing

Learn how to index and slice NumPy arrays effectively. Examples cover single-element access, slicing, and advanced indexing techniques.

3) NumPy Data Types

Explore the different data types supported by NumPy arrays. Understand type conversion and how to handle various types of data.

4) Handling NaN Values

Understand how to work with NaN (Not a Number) values in NumPy arrays. This includes detecting, replacing, and managing NaN values.

5) Statistical Operations

Discover how to perform statistical operations using NumPy. Topics include mean, median, variance, standard deviation, and more.

6) Shape, Reshape, Ravel, Flatten

Learn how to manipulate the shape of NumPy arrays. This section covers reshaping arrays, raveling, and flattening.

7) Creating Arrays

Explore different methods for creating NumPy arrays, including arange, linspace, range, random, zeros, and ones.

8) Conditional Selection

Understand how to use the where function for conditional selection and filtering within NumPy arrays.

9) Concatenation and Sorting

Learn how to concatenate and sort NumPy arrays. Examples include horizontal and vertical stacking, as well as sorting operations.

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