Prototyping Python Dashboards for Scientists and Engineers: Build and Deploy a Complete Dashboard with Python

Table of Contents....6

About the Author....17

About the Technical Reviewer....18

Acknowledgments....19

Introduction....20

Chapter 1: Working with Python....33

Coding Design: Python and OOD....33

Python Data Types....36

Lists, Tuples, and Sets....38

Dictionaries....41

Series....43

Dataframes....44

Building Dataframes....45

Accessing Dataframe Rows and Columns....50

Using loc[ ] and iloc[ ] to Access by Position....52

Filtering – Extracting Elements by Value....54

The Spyder IDE....57

Summary....59

Chapter 2: Reactive Programming with PLOTLY and DASH....59

Getting Started with PLOTLY....59

Getting Started with DASH....65

Summary....71

Chapter 3: Working with Online Data....72

About the ATADS Dataset....72

ATADS Screen Scraping....78

Converting Excel to CSV with Data Cleanup....81

Managing and Keeping Our Files Up to Date....82

Summary....84

Chapter 4: Planning the Dashboard Prototype....84

Overview....84

Project Tasks....88

Trends and Forecasts....90

Other Design Considerations....92

Summary....93

Chapter 5: Our First Dashboard....94

The atads.py File....95

The atads_layout Class....98

The atads_figures Class....101

Initialization....101

Variable Name Management....102

Miscellaneous Variable Initialization....104

Class Methods....104

I/O and Variable Name Utilities....105

The update_mainchart() Method....106

Methods for Drawing Raw and Smoothed Data....108

Methods to Enhance Chart Visual Appeal....110

Methods to Add Polynomial Curve Fits....112

Fine-Tuning with CSS....117

Summary....121

Chapter 6: Dashboard Enhancements....122

Adding the Banner and the Instruction Panels....125

Monthly and Weekday Histogram Panels....129

The Spectrum Panel....134

Quantifying Weekly and Seasonal Effects....139

The Final ATADS Dashboard....148

Summary....149

Chapter 7: Hosting an Application on a UNIX Server....150

Creating the Python Environment....152

Running a Flask Application....155

Using uWSGI....157

Using GUNICORN....159

Summary....160

Chapter 8: Deploying Your Project As a UNIX Service....160

Creating a Hello World System Service....162

Using NGINX to Share Your Hello World App....164

Adding the Dashboard Project to Your Server....167

Creating the Dashboard System Service and Deploying with NGINX....169

Securing Your Server....172

Summary....174

Chapter 9: The BTS T100 Dataset: Interacting Controls and Tables....174

The BTS T100dm Dataset....175

Prototyping a T100dm Display....175

Managing Modes and Interacting Menus....181

Figures and Tables....184

Summary....187

Chapter 10: Creating a Web Portal....187

Troubleshooting WordPress....193

Summary....200

Chapter 11: Using Our Dashboard for Data Visualization and Analysis....200

Airport Type, Trends, and Location....201

Airshows and Seasonal – Using Spectra....203

Incorporating Models....210

Media, Presentations, Reports, and Projects....214

Summary....218

Chapter 12: Afterword....218

Appendix A: Utilities for Managing ATADS Data....220

Notes....231

Data Update Process....232

Index....232

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.