Data Visualisation with Seaborn with Parisa Gregg
We are very excited to announce that the NHS-R Community will be hosting its annual conference, including pre-conference online talks, online workshops and the main conference, during October 2023.
The online conference workshop will be hosted via Zoom and take place on the following date:
Over the last few decades, a plethora of Python packages have been developed to tackle a range of data visualisation problems. This tutorial will provide a hands-on introduction to Seaborn, a fantastic open-source plotting library that builds on the Matplotlib package. Seaborn allows complex data visualisations to be created simply and easily, whilst also improving on the default look and feel of Matplotlib figures.
This hands-on workshop will cover:
By the end, you will be able to:
No previous experience in Seaborn is necessary for this tutorial. However, basic familiarity with Pandas DataFrames and plotting with Matplotlib would be useful. This workshop will be run using an online environment with all the dependencies and libraries pre-installed.
By registering for this event, you will qualify for the following:
A Zoom link will be provided to you to attend the conference workshop virtually. Please note that if subtitles are used, they are likely to be generated by Zoom thus, may encounter some issues converting technical language and acronyms to text.
If you require any additional information or have any accessibility requests, please do not hesitate to contact the Conference Team via firstname.lastname@example.org.
Additional Conference Related Activities
Please note that the conference will also include the following separate activities:
Data Scientist and Trainer at Jumping Rivers
Parisa is a data scientist and trainer at Jumping Rivers. She enjoys using Python to visualise and extract information from data. She loves sharing her knowledge and has experience delivering courses on a variety of topics, from data visualisation to machine learning. Her enthusiasm for Python and data science developed during her PhD in Particle Physics.