Synopsis
A swift and practical introduction to building interactive data visualization apps in Python, known as dashboards. You've seen dashboards before; think election result visualizations you can update in real time, or population maps you can filter by demographic. With the Python Dash library you'll create analytic dashboards that present data in effective, usable, elegant ways in just a few lines of code. The book is fast-paced and caters to those entirely new to dashboards. It will talk you through the necessary software, then get straight into building the dashboards themselves. You'll learn the basic format of a Dash app by building a twitter analysis dashboard that maps the number of likes certain accounts gained over time. You'll build up skills through three more sophisticated projects. The first is a global analysis app that compares country data in three areas: the percentage of a population using the internet, percentage of parliament seats held by women, and CO2 emissions. You'll then build an investment portfolio dashboard, and an app that allows you to visualize and explore machine learning algorithms.
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About the Author
Adam Schroeder has been teaching Plotly Dash for over two years on YouTube as @CharmingData. His videos have over 60 thousand views per month. Adam is passionate about helping people learn data visualization. He has an M.A. in Government and Conflict Resolution and currently works at Plotly.
Christian Mayer has a PhD in computer science and is the founder of the popular Python site Finxter.com, an educational platform that helps more than 3 million people a year learn to code. He has published a number of books, including the Coffee Break Python series, and is the author of Python One-Liners (No Starch Press, 2020).
Ann Marie Ward is a Dash contributor and a moderator on the Dash community forum. Ann Marie has a BA in Economics and is a retired CEO. She discovered Dash when searching for a better way to analyze financial data and was so amazed by what's possible to create with Dash that she started to learn Python, JavaScript and R. Her contributions to Dash include improving documentation, fixing bugs, and adding features.
"About this title" may belong to another edition of this title.
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Paperback. Condition: new. Paperback. Create stunning interactive dashboard applications in Python with the Dash visualization and data analysis tool. Build interfaces that make sense of your data, and make it pretty.A swift and practical introduction to building interactive data visualization apps in Python, known as dashboards. You've seen dashboards before; think election result visualizations you can update in real time, or population maps you can filter by demographic. With the Python Dash library you'll create analytic dashboards that present data in effective, usable, elegant ways in just a few lines of code.The book is fast-paced and caters to those entirely new to dashboards. It will talk you through the necessary software, then get straight into building the dashboards themselves. You'll learn the basic format of a Dash app in a Twitter analysis dashboard that tracks numbers of likes over time. You'll then build up skills through three more sophisticated projects. The first compares world data in three areas- volume of internet usage, percentage of parliament seats held by women, and CO2 emissions; the second is a financial portfolio dashboard that models your investments; and the third is visualizesmachine learning algorithms. The final chapter sets you up with some useful final skills, like debugging your code and applying color themes.In this book you will-Create and run your first Dash appsUse the pandas library to manipulate and analyze social media and API dataCreate a variety of stunning and effective charts using PlotlyLearn to use bar charts, chloropleth maps, contour plots, and moreExamine and build on existing apps written by the prosDash combines several technologies to get you building dashboards quickly and efficiently. This book will do the same. "An introduction to building interactive data visualization apps in Python, known as dashboards. Covers how to build a Twitter analysis visualizer, an app that compares global data, an app that predicts the effectivity of variable investment portfolios, and a dashboard for visualizing machine learning algorithms"-- Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781718502222
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