This repository contains the code from the hands-on blog posts at iSquared. The website mainly revolves around the visual explanation of many different phenomena. There are two main parts: blogs and visualizations.

The blog posts are longer and more detailed texts covering some interesting topics. They include explanations, intuition, theory, and visual perception of the discussed subject. Morever an open-source implementation is provided for a fully-featured experience. The blog posts are summarized below:

The blog post points why the interactive visualization is important and how it can help us in the process of data exploration and interpretation. It also includes a hands-on experience using the JavaScript library D3, to code an interactive Parallel Coordinates plot augmented with a dynamic table to search laptops easily.

Code: Interactive Dataviz

Dataset: Laptop Prices

A series of 4 blog posts, each discovering a different set of JavaScript visualization tools: charting, graphs, maps and 3D.

The first part covers the charting libraries with a hands-on experience with NVD3, ApexCharts JS and Plotly JS.

Code: JavaScript Charting Libraries

Dataset: Life Expectancy

The second part covers the graph visualization libraries with a hands-on experience with Cytoscape JS. We discuss the different graph data formats, data repositories, different JavaScript libraries and out-of-the=box tools.

Code: JavaScript Graph Visualization Libraries

Data: Class Dependency Network of JDK 1.6.0.7

A series of blog posts dedicated to the random processes simulation and animated visualization using the Python numerical libraries.

Introduction of the simple random walk, simulation and animated visualization.

Code: Random Walk Animation Pyhton Notebook

Introduction of the Brownian Motion, how to construct it using the simple random walk and animated visualization of this principle.

Code: Brownian Motion Animation Pyhton Notebook

Extending the bare Brownian Motion with volatility and drift. We illustrate these two proparties with an animated visualization using Matplotlib's Animation API. Source code:

Code: Drifted Brownian Motion

Transforming the Drifted Brownian Motion from a process with additive increments to a process with multiplicative increments. This is well suited for modelling stock price data. We analyze and animate one interesting property of the process: for certain conditions, it has zero mean and infinite variance.

Code: Geometric Brownian Motion

A series of blog posts dedicated to the numerical integration with animated visualizations in Python.

Introduction to the simplest form of Integration using the Riemann sums. We illustrate the numerical integration process using Matplotlib's Animation API.

Code: Riemann Sums

Introduction to the Riemann-Stieltjes Integral which is a generalization of the Riemann Integral. We provide some intuitive illustrations to explain and understand this type of integral.

Code: Riemann-Stieltjes Sums

Intro to cellular automata. Implementation of the elementary cellular automata and animation of the evolution of one automaton using Matplotlib.

Code: Cellular Automata

Tutorial on how to use the HiPlot library to find the best hyperparameters for a simple Keras model.

Code: Hyperparameter Search

Tutorial on how to use CodeCarbon Python library for tracking the CO2 emissions of a neural network training process.

Code: Code Carbon

Experimenting with snakeviz, line_profiler, memory_profiler and pyinstrument.

Code: Profilers Experiments

The visualization part offers very short and simple explanation of some big ideas where the main focus is put on the visualizations and how to create them. For completeness, the open-source implementation is provided here. The list of visualizations is summarized below:

How to calculate the area of the circle numerically. What is the visual interpretation behind it?

Find the source code here

Amazing properties of the Mandelbrot sets and an animated visualization using Matplotlib as it converges.

Find the source code here

How to construct perfect snowflakes using the Koch Curve. It only takes a simple math.

Find the source code here

Analyzing Julia Set with an animated illistration.

Find the source code here

Visualizing the chaotic bifurcation diagram getting created from a seemingly simple dynamical system.

Find the source code here

Visualizing and animating the zeros of the Riemann Zeta function, which are still not mathematically proven to hold in all cases.

Find the source code here

Animated visualization of the Sierpinski triangle, which resembles a Christmass tree.

Find the source code here

Generating and plotting a Barnsley Fern Fractal.

Find the source code here

How to plot data using the Altair Python library.

Find the source code here