3. Plotting Data

This week we are thinking about how to plot data in order to illustrate their key features -

• What is the shape of the data distribution?
• How does the data distribution differ between data categories (eg men/women, cars/towing/trucks, months of the year)
• What is the relationship between values in paired data (are they correlated, is there a systematic difference within pairs such as brothers taller than their sisters)

We will learn to produce plots with Python, using the packages matplotlib and seaborn

We will also think about how to make good choices when plotting data - choosing an appropriate type of plot and appropriate scaling, labeblling and settings

3.1. Tasks for this week

Conceptual material is covered in the lecture. In addition to the live lecture, you can find lecture videos on Canvas.

Please work through the guided exercises in this section (everything except the page labelled “Tutorial Exercises”) in advance of the computer-based tutorial session.

To complete the guided exercises you will need to either:

• open the pages in Google Colab (simply click the Colab button on each page), or
• download them as Jupyter Notbooks to your own computer and work with them locally (eg in Spyder)

If you find something difficult or have questions, you can discuss with your tutor in the computer-based tutoral session.