Python for data analyis and visualisation University of St Andrews

Overview

Through the Python for data analyis and visualisation course from University of St Andrews you will learn about good practices of developing Python code for working with data through the following topics:

• Structuring Python code: functions, classes, exceptions, modules.

• Software engineering practices: testing, debugging, profiling, documenting, organising, storing under version control.

• Using Python for data analytics: collecting data (API interaction, web scraping, interfacing databases) and using popular Python libraries (numpy, pandas, matplotlib) for their processing and visualisation

Python code is supplied and explained for each topic. Your key learning outcomes are:

• Master concepts of modelling, design, and programming in Python and gain practical skills in applying these concepts

• Be confident with effective documentation, layout, debugging and testing

• Be able to use Python programming and development tools

• Be able to load into Python data from standard formats and perform some descriptive data analysis.

This course is suitable for those who are competent in programming using Python (including notebooks, packages, data manipulation, design and use of pipelines, model evaluation functions) but are not expert programmers.