About the course
This Data Visualisation with Python training course is a practical two-day workshop designed to enhance the visual presentation and storytelling skills of Python analysts.
You'll be introduced to the theory and best practices of data visualisation before progressing through a systematic exploration of Python’s foundational plotting libraries including Matplotlib, Pandas plotting, and Seaborn.
As the course unfolds, you will advance to more sophisticated tools such as Plotly and GeoPandas, extending your capabilities for creating dynamic and geospatial visualisations.
The training will culminate in a practical project where attendees will learn to deploy their visualisations using Streamlit, enabling them to share insights and empower their audience to drill-down and explore the data further in an interactive web-based environment.
Throughout the course, engaging examples and exercises based on the Gapminder dataset of world indicators will reinforce learning, ensuring that theoretical concepts and technical skills are consolidated with hands-on experience of applying these to real-world data.
This Data Vis course is aimed at those already familiar with Pandas, who are looking to elevate their data presentation and storytelling skills.
Online and in-house face-to-face options are available - as part of a wider customised training programme, or as a standalone workshop, on-site at your offices or at one of many flexible meeting spaces in the UK and around the World.
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- Learn data visualisation theory and best practice
- Build expertise in Python’s foundational visualisation tools: Matplotlib, Pandas plotting and Seaborn
- Extend your skills with advanced visualisations using tools such as Plotly and Geopandas
- Deploy your visualisations using Streamlit for interactive exploration
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Python Analysts: Ideal for analysts looking to elevate their data presentation skills.
Data Scientists: Suitable for professionals aiming to improve storytelling through data.
Business Intelligence Professionals: BI specialists seeking to enhance their visualization capabilities for better insights.
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Familiarity with Python: Basic knowledge of Python programming is essential.
Experience with Pandas: Prior experience with the Pandas library is required.
Interest in Data Storytelling: An interest in developing skills for visual data storytelling.
Environment: students should have jupyterlab and a code editor such as VSCode or PyCharm installed.
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This Data Visualisation course is available for private / custom delivery for your team - as an in-house face-to-face workshop at your location of choice, or as online instructor-led training via MS Teams (or your own preferred platform).
Get in touch to find out how we can deliver tailored training which focuses on your project requirements and learning goals.
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Day 1: Foundation and Core Visualisation Tools
Introduction to Data Visualisation
Basic theories and principles of data visualisation
Best practices in visual storytelling
Getting Started with Python's Core Plotting Libraries
Introduction to Matplotlib
Basic plotting functions
Customizing plots using the axes API
Exploring Pandas plotting
Quick visualisation directly from DataFrames
Overview of Seaborn
Statistical data visualisation with Seaborn
Creating complex data visualisations with less code
Hands-On Practice with Core Libraries
Interactive exercises using the Gapminder dataset, creating a variety of charts and incorporating best visualisation practices
Day 2: Advanced Tools and Interactive Web-Based Visualisation
Advanced Visualisation with Plotly and GeoPandas
Advanced dynamic visualisations with Plotly
Interactive plots and dashboards
Introduction to GeoPandas
Handling geospatial data
Creating maps and spatial plots
Building Interactive Web Applications with Streamlit
Overview of Streamlit
Deploying visualisations with Streamlit
Building an interactive web app
Allowing users to explore data through interactive widgets
Capstone Project
Participants apply what they've learned in a comprehensive project using all tools from the course to create a data-driven story
Peer reviews and group discussions on the projects
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jupyterlab - IDE for code, data and notebooks
VSCode - popular Microsoft code editor
PyCharm - popular Python IDE
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