Data Visualisation


This week, we investigate some simple data manipulation with numpy and then learn how to create graphs with the powerful Matplotlib library. This is followed by a quick look at Jupyter Notebook which you might find enjoyable to use because it allows you to write code and documentation in a single file in a web-browser. Jupyter Notebook is very useful for doing assignments and reports all-in-one.

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Example output from Matplotlib.






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Contents



Introduction

Task 1 – numpy

Task 2 – Jupyter Notebook, Markdown

Task 3 - Jupyter Notebook, Matplotlib

Task 4 - Jupyter Notebook, Matplotlib 3D

Conclusion


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Topics Covered in this Lab



1. numpy

2. numpy.mean()

3. Jupyter Notebook

4. Jupyter Notebook Installation

5. Markdown

6. Matplotlib

7. 2D Matplotlib Charts

8. 3D Matplotlib Charts



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Lab Key



Notes – #FF6F61

Videos – #34568B

Code Examples – #009B77

Downloads - #C3447A

Internal Link (University Resources) – #955251

External Link (Non-University Resources)– #EFC050

Other - #660099



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