Python for Data Visualisation
Python has a number of packages for the effective creation of graphics to communicate your data insights. This one day course will examine a range of packages for building impactful visualisations. During the training session, we’ll cover the main Python plotting libraries: plotly, matplotlib and seaborn. Additionally, we discuss how to effectively use faceting and layers in a graphic.
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- Matplotlib: Introduction to one of the go to visualisation libraries for Python that integrates well with the prominently used Pandas package data structures.
- Plot building: Create more complex plots built up of separate layers or multiple plot panels.
- Seaborn: Seaborn is a very useful graphics package built on top of Matplotlib to aid in easy creation of beautiful statistical graphs.
- Facetting: Create insight in data structure with easy creation of plot facets.
- Plotly: Plotly is a very exciting graphics package which makes it trivial to add interactive elements, such as hover information, tooltips, zomming and even full animations, excellent for presenting your data in a digital format such as a webpage or dashboard.
By the end of the day, participants will be able to…
- use a range of techniques for communicating their data insights
- create beautiful, interactive graphics
- compose complex visualisations as well as standard displays such as scatter plots, histograms, barcharts and boxplots and more.
This course assumes you have some basic familiarity with Python programming and data structures including Pandas data objects. Completion of the Introduction to Python two day course or similar experience would be sufficient.