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.

You'll learn:

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:

Either \Learn to Program: Python\ or \Learn to Program: Python\ and \Python for Research\ needed to attend this course. If you already have experience with programming, please check the topics covered in the \Learn to Program: Python\ and \Python for Research\ courses to ensure that you are familiar with the knowledge needed for this course.

For more information, please click here.