bokeh-notebooks | Interactive Web Plotting with Bokeh in IPython notebook | Data Visualization library
kandi X-RAY | bokeh-notebooks Summary
kandi X-RAY | bokeh-notebooks Summary
Welcome to [Bokeh] in Jupyter Notebooks!. Bokeh is a Python interactive visualization library for large datasets that natively uses the latest web technologies. Its goal is to provide elegant, concise construction of novel graphics in the style of Protovis/D3, while delivering high-performance interactivity over large data to thin clients. These Jupyter notebooks provide useful Bokeh examples and a tutorial to get started. You can download the repository and execute jupyter notebook from your terminal to try out the notebooks locally on your own machine. Alternatively, you can immediately launch live versions of the Tutorial notebooks in your browser on [mybinder.org] Please visit the [Bokeh web page] for more information and full documentation, and the [Bokeh Discourse] for community discussion.
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QUESTION
I want to create an interative Boxplot in Google Colab with Bokeh.
I use Bokeh lastest version 2.4.2:
...ANSWER
Answered 2021-Dec-20 at 17:55bokeh
ditched their high-level chart interface quite some time ago because it was too much to maintain. Instead they adopted a different package that provided a high level charting interface called Holoviews
Holoviews works with many different renderers, but bokeh
is the default, so you can have Holoviews create your plot objects, and then use bokeh
to tweak/fine tune them.
https://holoviews.org/gallery/demos/bokeh/boxplot_chart.html#demos-bokeh-gallery-boxplot-chart.
QUESTION
I am trying to teach myself to use Bokeh with the example on the Bokeh website shown below,
I have written the following code;
...ANSWER
Answered 2021-Mar-17 at 10:09You can either replace
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