Data Visualisation with Python: Seaborn and Scatter Plots (FutureLearn)

On this course, you’ll look at Python for beginners in data analytics. Python is one of the most widely used, and easiest to use programming languages, powering the back-ends of some of the world’s biggest online companies, including Google, Dropbox and Instagram.
You’ll learn how a Python programmer uses data to create graphical representations that can be easily analysed and examined.

Learn how to use Seaborn in Python
This course will also introduce you to Seaborn, a data-visualisation library in Python. Seaborn combines aesthetic appeal with the powerful technical insights of the programming language.
You’ll learn how to identify a scatter plot, line plot, and other relational plots, as well as how to understand the differences between them.

Understand quantitative and categorical variables
What are quantitative and categorical variables used for in Python? You’ll see how the programming language visualises categorical data (which has a fixed length) and quantitative data (which can be measured).
You’ll also find out how to categorise plots and other quantitative variables of data visualisation.

Examine uncertainty in data and visualisation workflows
The final section of the course will teach you the basics of uncertainty within visualisations. You’ll examine uncertainty in data, point estimate intervals, and confidence bands.
Using your new knowledge, you’ll be able to confidently display uncertainty in data and walk through creating a workflow of a visualisation based on exploring a dataset.

What topics will you cover?

• Python
• Seaborn Package
• Static visualisations
• Static plots: design and visualisation best practice

What will you achieve?
By the end of the course, you‘ll be able to...

• Explain the architecture and objects of Seaborn Package
• Create Static Visualisations using Seaborn
• Customise the Seaborn plots
• Apply design and visualisation best practices to static plots

Who is the course for?
This course is designed for professionals looking to grow their confidence in using Python to produce exploratory and explanatory visualisations and build dashboards, as well as better communicate their insights.
If you want to further your knowledge, you may be interested in these courses, from the same provider, that share the same subject and overall learning outcomes:

• Data Visualisation with Python: Matplotlib and Visual Analysis
• Data Visualisation with Python: Bokeh and Advanced Layouts