Textbook in PDF format

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.
In this book, we are going to describe this interesting topic with various Python code examples. We briefly introduce the visualization pipeline combined with interaction techniques before we step into the ingredients required to develop dashboards. For the unfamiliar ones, we are going to introduce the programming language Python with the major concepts to build running programs with already quite a lot of functionality. The Python code is needed to allow some kind of variability in a dashboard, starting from data reading, parsing, and transformations, finally, leading to preprocessed data that builds the core ingredient for interactive and scalable visualizations placed in a user interface, in our case, coming in the form of a dashboard. Application examples round up the book by showcasing larger running examples that can be tried out by the readers, even be manipulated or modified to get the code running for one’s own application examples. Finally, the experiences of the human observers play a crucial role in the entire development process. Since we do not know such prior knowledge of our readers, we try to describe all of the required concepts from the perspective of nonexperts in computer science, data science, programming, visualization, and user evaluation.
The remainder of the book is as follows: Chapter 1 starts with introducing the general problem and tries to show the bridges between all of the related fields. Chapter 2 makes an attempt to describe the data-to-visualization mapping with respect to dashboards, while also perceptual and cognitive issues related to visual and interface design are taken into account. In Chapter 3, we are going to explain the major programming ingredients to create dashboards for interactive visualization, while Chapter 4 builds the basis from an implementation perspective focusing on the programming language Python. Applications are provided in Chapter 5 coming with code examples as well as their visual outputs in the form of dashboards. The book is completed with many discussions on scalability issues and limitations which can be found in Chapter 6, before concluding the book in Chapter 7. A general remark on the book’s reading strategy is that it can be studied in its entirety, starting from the beginning, page by page, or each chapter can be read individually since it builds its own learning unit. This means that an experienced reader in programming might skip the chapter on programming and might focus on chapters including visualization, interaction, or design aspects.
Technical topics discussed in the book include:
Design in visualization
Interaction principles in information visualization
User interface design
Linking Python, Dash, and Plotly
Coding in Python
Dashboard examples with Python code.
Preface
Introduction
Creating Powerful Dashboards
Python, Dash, Plotly, and More
Coding in Python
Dashboard Examples
Challenges and Limitations
Conclusion