Visualising data with Python
It's not just Matplotlib any more... there are more options than ever for creating graphs and visualisations in Python. Libraries now come with beautiful styling, data-friendly colour schemes, interactive plots, Jupyter integration, online hosting and more. Seaborn, ggplot, bokeh, plotly.... where should a newbie start? Is it worth the effort of switching from your current favourite to something new? In this talk I'll outline the strengths and capabilities of some popular libraries.
Clare began life in computational physics before moving into genomics. She is now a researcher at Melbourne Bioinformatics at the University of Melbourne, with a particular interest in algorithms and in the application of machine learning to genomics.