Visualisation

Aim

Learn/recall the basics of data visualisations using Seaborn and Python.

You'll need an IDE such as Spyder or Jupyter Notebook to work with your Python programs.

Basic Foundation Needed

It is assumed you already know the basics of Python before progressing into this topic. You can check out here to pick up Python basics otherwise

Why Seaborn for Visualisation?

From an article in AnalyticsVidya:

Seaborn is a popular data visualisation library for Python.

By giving us the capabilities to create amplified data visuals, we can understand the data through visual context to unearth any hidden correlations between variables and trends that might not be obvious initially. Seaborn has a high-level interface as compared to the low level of Matplotlib.

Topics:

The basic concepts you'll need using seaborn for basic data visualisations are organised in the following chapters:

1. Introduction to Seaborn
2. Line Charts
3. Bar Charts and Heatmaps
4. Scatter Plots
5. Distributions
6. Choosing Plot Types and Custom Styles

Reference source

Lessons in the notebook were adapted from various sources including Kaggle, and the book: McKinney, W. (2018). Python for Data Analysis (2nd ed). O'Reilly.