Data Processing with Python Pandas

Pandas is a popular software library for Python which includes a number of useful data processing tools. It is free and relatively easy to learn, with a community which provides support and documentation. It is more powerful than Excel and is able to produce high-quality figures.

Building on Introduction to Python for Researchers, this course teaches the beginnings of data processing in Python using the Pandas library. You will learn the basic commands of the package with hands-on examples using the Jupyter Notebook environment.

Syllabus:

• Why you might choose to use Pandas for data processing
• Selecting rows of data
• Selecting columns of data
• Cutting and joining data
• Reading and writing data
• Producing graphs from the data

This course is open to Research Degree Students, Postdocs & Research Fellows. Limited spaces available for wider Imperial community.

Learning Outcomes:

On completion of this workshop you will be able to:

• Use Jupyter notebooks to perform simple Pandas data analysis
• Apply fundamental components of Pandas syntax including data selection and grouping
• Create programs designed to process example data and display simple statistics
• Interpret common errors and use these to help debug a program

Prerequisites:

Introduction to Python for Researchers (Online Course) or equivalent prior learning

How to book

• Early Career Researchers (Research Degree Students, Postdocs, Research Fellows) should book via Inkpath using your Imperial Single-Sign-On.
• All other members of the Imperial community, should book here.

Please ensure you have read and understood ECRI’s cancellation policy before booking.