Revised for …. Skip to main content. Start your free trial. Book description Learn how to create interactive and visually aesthetic plots using the Bokeh package in Python About This Book A step by step approach to creating interactive plots with Bokeh Go from nstallation all the way to deploying your very own Bokeh application Work with a real time datasets to practice and create your very own plots and applications Who This Book Is For This book is well suited for data scientists and data analysts who want to perform interactive data visualization on their web browsers using Bokeh.
What You Will Learn Installing Bokeh and understanding its key concepts Creating plots using glyphs, the fundamental building blocks of Bokeh Creating plots using different data structures like NumPy and Pandas Using layouts and widgets to visually enhance your plots and add a layer of interactivity Building and hosting applications on the Bokeh server Creating advanced plots using spatial data In Detail Adding a layer of interactivity to your plots and converting these plots into applications hold immense value in the field of data science.
Style and approach This books take you through a step by step process that starts with understanding what Bokeh actually is and ends with building your very own Bokeh application filled with interactive and visually aesthetic plots that will amaze your users. Following is what you need for this book: This book is well suited for data scientists and data analysts who want to perform interactive data visualization on their web browsers using Bokeh. Some exposure to Python programming will be helpful, but prior experience with Bokeh is not required.
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This book aims to equip you with a sound knowledge of Python in conjunction with the concepts you need to master to succeed as a data visualization expert. The book starts with a brief introduction to the world of data visualization and talks about why it is important, the history of visualization, and the capabilities it offers.
You will learn how to do simple Python-based visualization with examples with progressive complexity of key features. The book starts with Matplotlib and explores the power of data visualization with over 50 examples. It then explores the power of data visualization using one of the popular exploratory data analysis-oriented libraries, Pandas.
The book talks about statistically inclined data visualization libraries such as Seaborn. Adding a layer of interactivity to your plots and converting these plots into applications hold immense value in the field of data science. The standard approach to adding interactivity would be to use paid software such as Tableau, but the Bokeh package in Python offers users a way to create both interactive and visually aesthetic plots for free.
This book gets you up to speed with Bokeh - a popular Python library for interactive data visualization. The book starts out by helping you understand how Bokeh works internally and how you can set up and install the package in your local machine. You then use a real world data set which uses stock data from Kaggle to create interactive and visually stunning plots. You will also learn how to leverage Bokeh using some advanced concepts such as plotting with spatial and geo data.
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