14.10.2024 - 16.10.2024
Certificate of Participation
Dr. Dina Deifallah
Recognized as Bildungszeit
INTERACTIVE DATA VISUALISATION
14.10.2024 – 16.10.2024
Data Visualisation plays a crucial role in transforming complex datasets into easily understandable and insightful representations. It allows individuals, businesses and researchers to uncover patterns, trends, and relationships within their data. Proficiency in Data Visualisation not only improves one’s analytical capabilities but also increases their capacity to convey insights in a visually compelling manner, ultimately contributing to more informed decision-making and successful outcomes in various professional contexts.
Learning goalsIn this course, participants will learn how to create a wide variety of visualisations, from basic line charts to intricate choropleth plots, using Plotly, a powerful Python graphing library that enables the creation of interactive, professional-quality graphs and charts. Participants will also learn how to customise visualisations in terms of layout, colour palette, interactivity and more. Finally, participants will get introduced to Dash, a Python framework built on top of Plotly, designed for building intuitive and customisable web-based dashboards.
ContentInteractive Data Visualisation with Plotly
- Plotly installation
- Basic Structure of Plotly Figures
- Plotly Express versus Figure Objects
- Bar and Pie Charts
- Line, Scatter, Bubble and Multi-faceted Plots
- Customising Traces, Axes, Legends, Tooltip, Colour
- Colour Palette Generation Tools
- Colour palette generation tools
- Adding annotations
- Install Dash and Jupyter-Dash
- Structure and creation of a Dash Application
- Dash HTML Layouts
- Adding Plotly Visualisations
- Adding Interactivity with Dropdowns, Checklists and Sliders
- Adding Interactivity with DatePickerSingle and DatePickerRange
- Dash Callback Functions
- Styling HTML Components
Throughout the course participants will use several public datasets and class exercises.
Target groupThis course is targeted to professionals and researchers who work frequently with data and want to learn how to create high quality and impactful interactive data visualisations with open source free software.
This course is recognized as Bildungszeit according to paragraph § 10 (5) of the Berliner Bildungszeitgesetz (BiZeitG).
- English level of at least B1 (according to the European Framework)
- Experience with Python programming (especially data manipulation with pandas)
- Laptop (no specific operating system required) + working installation of Python + headset with microphone
DatesOctober, 14 – 16, 2024 from 10:00 - 18:00 (CET) on-site in Berlin.
Dr. Dina Deifallah is a Data Science and Analytics lecturer in the International University of Applied Sciences (IUBH). She is a guest lecturer in the Summer and Winter School of the Technische Universität Berlin as well as the University of Europe. She also worked as a Data Scientist and Data Science coach in multiple startups in Europe since 2018. She has a Ph.D. in Communication Engineering with a focus on AI optimization algorithms and 15+ years of experience in academic teaching.