Data Manipulation and Visualisation in Python at UTS Online

Explore DataFrames in depth, and learn about Data Manipulation and Data Visualisation in Python using the pandas, matplotlib and seaborn libraries.

Important:

This course takes place over multi-sessions. The dates and times are as follows:

• Session 1: Wednesday, March 18 from 09:30 AM to 12:30 PM AEDT
• Session 2: Thursday, March 19 from 09:30 AM to 12:30 PM AEDT

Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you’d expect of a modern programming language, and also a rich set of libraries for working with data.

In this workshop, you will explore DataFrames in depth (using the pandas library), learn how to manipulate, explore and get insights from your data (Data Manipulation), as well as how to deal with missing values and how to combine multiple datasets. You will also explore different types of graphs and learn how to customise them using two of the most popular plotting libraries in Python, matplotlib and seaborn (Data Visualisation).

We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research.

Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation.

• Working with pandas DataFrames
• Indexing, slicing and subsetting in pandas DataFrames
• Missing data values
• Combine multiple pandas DataFrames
• Using the Grammar of Graphics to convert data into figures using the seaborn and matplotlib libraries
• Configuring plot elements within seaborn and matplotlib
• Exploring different types of plots using seaborn

Prerequisites:

The fundamental programming concepts taught in our Learn to Program: Python course is assumed knowledge for participating in this course. If you already have experience with programming, please check the topics covered in the Learn to Program: Python course to ensure that you are familiar with the knowledge needed for this course.