Python for Data Visualisation

Description:

This course will take place, from 1:30pm - 5:00pm (GMT), on the 28th of January. We have an early bird offer of £100, which runs until the 31st of December. The price is £125 thereafter.

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.

Course Outline

• 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.

• Faceting: 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, zooming and even full animations, excellent for presenting your data in a digital format such as a webpage or dashboard.

Learning Outcomes

By the end of the course, 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, boxplots and more.

Prior Knowledge

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.

Cost:

£100.00 - £125.00

Website and registration:

Register for this course

Region:

International

Keywords:

Quantitative Data Handling and Data Analysis, Programming , Python , data science , Visualisation

Related publications and presentations from our eprints archive:

Quantitative Data Handling and Data Analysis

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