Lab Work @ Visual Analysis 👨🏻‍💻

Table of contents

• Introduction
• About the course
• Labs
  • Lab 01 - Web Scrapping via Beautiful Soup
  • Lab 02 - Data Visualisation with Altair
  • Lab 03 - Interaction in Visualization with Altair
  • Lab 04 - Basic charts with d3.js
  • Lab 05 - Basic charts with d3.js (continue)
  • Lab 06 - Events, Interactivity, and Animation with d3.js
• Setup
  • Create new enviornment
  • Setup pre-commit hooks

1. Introduction

Data drives the world. Nowadays, most of the data (structured or unstructured) can be analysed via several techniques. Although, most of the data pipelines are being automated, there arises a key need to keep human in the loop.

One of the fundamental ways to keep human-machine interaction more viable is to analyse data visually (to aid the human as much as possible). Visual Analysis introduces some techniques and tools for analyzing and visualizing data.

2. About the course

During this course, we will be introduced to techniques and tools for analyzing and visualizing data. It emphasizes how to combine computation and visualization to perform effective analysis. The course consists of two parts: a series of lectures on analytics and a series of lectures on visualization. Both parts will include hands-on tutorials during which you will work on analysis problems and start to build your own tools.

3. Labs

The main aim of this repository is to keep track of the work we have done in Visual Analysis (VA) labs.

3.1. Lab 01 - Web Scrapping via Beautiful Soup

Web Scrapping via Beautiful Soup is a Python package for the scraping data from the internet.

Please checkout lab's details here

3.2. Lab 02 - Data Visualisation with Altair

Vega-Altair is a declarative statistical visualization library for Python, based on Vega and Vega-Lite.

Please checkout lab's details here

3.3. Lab 03 - Interaction in Visualization with Altair

Vega-Altair is a declarative statistical visualization library for Python, based on Vega and Vega-Lite. In this lab, we will see how to use interactions with visualisation with Vega-Altair.

Please checkout lab's details here

3.4. Lab 04 - Basic charts with d3.js

D3.js is a producing dynamic, interactive data visualizations in web browsers. It makes use of Scalable Vector Graphics, HTML5, and Cascading Style Sheets standards.

Please checkout lab's details here

3.5. Lab 05 - Basic charts with d3.js (continue)

D3.js is a producing dynamic, interactive data visualizations in web browsers. It makes use of Scalable Vector Graphics (SVG), HTML5, and Cascading Style Sheets (CSS) standards.

Please checkout lab's details here

3.6. Lab 06 - Events, Interactivity, and Animation with d3.js

D3.js is a producing dynamic, interactive data visualizations in web browsers. It makes use of Scalable Vector Graphics (SVG), HTML5, and Cascading Style Sheets (CSS) standards.

Please checkout lab's details here

4. Setup

If you want to follow along with the lab exercises, make sure to clone and cd to the relevant lab's directory:

git clone https://github.com/mohammadzainabbas/VA-Lab.git
cd VA-Lab/src/<lab-of-your-choice>

For e.g: if you want to practice lab # 1, then you should do cd VA-Lab/src/lab1.

4.1. Create new enviornment

Before starting, you may have to create new enviornment for the lab. Kindly, checkout the documentation for creating an new environment.

Once, you have activated your new enviornment, we may have to install all the dependencies for a given lab (kindly check if requirements.txt file exists for a given lab before running the below command):

pip install -r requirements.txt

4.2. Setup pre-commit hooks

In order to setup pre-commit hooks, please refer to the documentation.