![]() ![]() output_file: This method is used to output your plot as an HTML file and can be used as illustrated in the following code:.There are two methods you can use to render your plot: Widgets: Widgets in Bokeh are the sliders, drop-down menus, and other small tools that you can embed into your plot to add some interactivity.Server: The Bokeh server is used to share and publish interactive plots and apps to an audience of your choice.Glyphs: Glyphs are the building blocks of Bokeh, and they are the lines, circles, rectangles, and other shapes that you see on a Bokeh plot.Application: The Bokeh application is a rendered Bokeh document that runs in the browser.The following are some key definitions related to Bokeh: While going through this book, you will come across some terms that are fundamental to understanding the Bokeh package. Key concepts and the building blocks of Bokeh You will have gone 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. Finally you will use all the concepts that you have learned in the previous chapters to create your very own Bokeh application from scratch.īy the end of the book you will be able to create your very own Bokeh application. ![]() You will also learn how to leverage Bokeh using some advanced concepts such as plotting with spatial and geo data. You then use a real world data set which uses stock data from Kaggle to create interactive and visually stunning plots. 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. This book gets you up to speed with Bokeh - a popular Python library for interactive data visualization. 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. Adding a layer of interactivity to your plots and converting these plots into applications hold immense value in the field of data science. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |