![]() ![]() ![]() Our GUI consists of two dropdowns and one scatter plot. In this example, we have explained how we can create an interactive GUI using bokeh widgets dropdown. Scatter Chart with Multi-Select (Multi-Choice)īelow, we have imported Python library bokeh and printed the version that we have used in our tutorial.Candlestick Chart with Date Range Slider.Scatter Plot with Dropdowns & Radio Buttons.Scatter Plot with Dropdowns & Checkboxes.It covers a detailed guide to bokeh for someone who is new to the library.īelow, we have listed important sections of tutorial to give an overview of the material covered. If you are someone who is new to creating charts using bokeh then please check below link. Tutorial uses python callbacks for making changes to charts when widget state changes instead of javascript callbacks. Tutorial explains different widgets like dropdowns, checkboxes, radio buttons, date pickers, sliders, etc with simple and easy-to-understand examples. What Can You Learn From This Article? ¶Īs a part of this tutorial, we have explained how we can create interactive GUIs by linking charts and widgets available from bokeh. It is commonly referred to as a dashboard. With the help of widgets, we can modify existing charts to analyze data from different perspectives rather than coding new charts for different combinations.Īdding widgets to our chart let us create interactive GUIs which we can deploy online for others to analyze data. When analyzing data from a different perspective we can add another level of interactivity by adding widgets to our chart. Python has a bunch of libraries (bokeh, plotly, altair, bqplot, etc.) that let us create interactive charts.īut just having simple interactivity like a tooltip, zooming, panning, etc are not enough all time. Simple Guide to use Bokeh Widgets (Interactive GUI / Apps) ¶ ![]()
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