Create interactive and data-driven dashboards using Python. This hands-on guide is a practical resource for those (with modest programming skills) in scientific and engineering fields looking to leverage Python's power for data visualization and analysis in a user-friendly dashboard format. You’ll begin by gaining a fundamental understanding of Python programming, including data types, lists, dictionaries, and data structures. The book then delves into the world of reactive programming with Plotly and Dash, offering a hands-on approach to building interactive web-based dashboards. Next, you’ll see how to work with online data, how to scrape and clean datasets, and keep files up-to-date. The book also guides you through planning a dashboard prototype, outlining project tasks, trends, forecasts, spectra, and other design considerations. It concludes with a discussion of how the dashboard can be used for data visualization of real data, explaining the usefulness of tools such as spectra. By providing detailed examples for download and customization, Prototyping Python Dashboards for Scientists and Engineers will equip you with the skills needed to jumpstart your own development efforts. What You’ll Learn Design a dashboard with Python Convert and filter Excel formatted files to produce CSV files Create browser-served graphics with PLOTLY Generate polynomial trend lines for forecasting Build a Unix service to share your dashboard Who This Book Is For Scientists, engineers, students, programmers, and data enthusiasts who aspire to harness Python's potential for data visualization and analysis through the creation of interactive dashboards. Many will be pragmatic programmers with modest skills and limited resources who mainly want to see a working solution they could emulate. Table of Contents About the Author About the Technical Reviewer Acknowledgments Introduction Chapter 1: Working with Python Coding Design: Python and OOD Python Data Types Lists, Tuples, and Sets Dictionaries Series Dataframes Building Dataframes Accessing Dataframe Rows and Columns Using loc[ ] and iloc[ ] to Access by Position Filtering – Extracting Elements by Value The Spyder IDE Summary Chapter 2: Reactive Programming with PLOTLY and DASH Getting Started with PLOTLY Getting Started with DASH Summary Chapter 3: Working with Online Data About the ATADS Dataset ATADS Screen Scraping Converting Excel to CSV with Data Cleanup Managing and Keeping Our Files Up to Date Summary Chapter 4: Planning the Dashboard Prototype Overview Project Tasks Trends and Forecasts Other Design Considerations Summary Chapter 5: Our First Dashboard The atads.py File The atads_layout Class The atads_figures Class Initialization Variable Name Management Miscellaneous Variable Initialization Class Methods I/O and Variable Name Utilities The update_mainchart() Method Methods for Drawing Raw and Smoothed Data Methods to Enhance Chart Visual Appeal Methods to Add Polynomial Curve Fits Fine-Tuning with CSS Summary Chapter 6: Dashboard Enhancements Adding the Banner and the Instruction Panels Monthly and Weekday Histogram Panels The Spectrum Panel Quantifying Weekly and Seasonal Effects The Final ATADS Dashboard Summary Chapter 7: Hosting an Application on a UNIX Server Creating the Python Environment Running a Flask Application Using uWSGI Using GUNICORN Summary Chapter 8: Deploying Your Project As a UNIX Service Creating a Hello World System Service Using NGINX to Share Your Hello World App Adding the Dashboard Project to Your Server Creating the Dashboard System Service and Deploying with NGINX Securing Your Server Summary Chapter 9: The BTS T100 Dataset: Interacting Controls and Tables The BTS T100dm Dataset Prototyping a T100dm Display Managing Modes and Interacting Menus Figures and Tables Summary Chapter 10: Creating a Web Portal Troubleshooting WordPress Summary Chapter 11: Using Our Dashboard for Data Visualization and Analysis Airport Type, Trends, and Location Airshows and Seasonal – Using Spectra Incorporating Models Media, Presentations, Reports, and Projects Summary Chapter 12: Afterword Appendix A: Utilities for Managing ATADS Data Notes Data Update Process Index
