Interactive visualization and visual analytics tools have been designed and developed in the past and will be developed in the future as well. In each application domain in which data is measured, generated, and recorded we see a potential candidate for an interactive visualization tool with the goal to find insights and knowledge in the data. This knowledge can be found either visually by humans' interventions or algorithmically by the machine, in the best case by applying both concepts in combination as in visual analytics. One of the easiest ways to get an interactive visualization tool running is by means of dashboards, typically implemented as webpages that can run in a web browser and are accessible online, creating some kind of web-based solution.This book describes ways to design and implement dashboards based on the programming language Python, the graphics library Plotly, and Dash. The readers can use the provided dashboard codes as a starting point and extend the functionality and features on their desire.Technical topics discussed in the book include:Design in visualizationInteraction principles in information visualizationUser interface designLinking Python, Dash, and PlotlyCoding in PythonDashboard examples with Python code.

Michael Burch studied computer science and mathematics at the Saarland University in Saarbrücken, Germany. He received his PhD from the University of Trier in 2010 in the fields of information visualization and visual analytics. After 8 years of having been a PostDoc in the Visualization Research Center (VISUS) in Stuttgart, he moved to the Eindhoven University of Technology (TU/e) as an assistant professor for visual analytics. From October 2020 he has been working as a lecturer in visualization at the University of Applied Sciences in Chur, Switzerland. Michael Burch is on many international program committees and has published more than 190 conference papers and journal articles in the field of visualization. His main interests are in information visualization, visual analytics, eye tracking, and data science.Marco Schmid studied Natural Resource Science (with specialization in Renewable Resources and Sustainable Energy) at the School of Life Sciences and Facility Management (ZHAW) in Zurich, Switzerland. During his study he worked as a scientific research assistant at the Institute of Applied Simulation at ZHAW. Then he worked for 3 years in a start-up company focused on machine learning and predictive models before he moved to the University of Applied Sciences in Chur, Switzerland in 2019 where he works as a scientific researcher. His main fields of interest are data science and software development.