Interactively and as a dashboard, and finally compare them on specific features. With an overview of these libraries, give examples of how they can be used One, but for more advanced uses they begin to run into some quirks. It can be very easy to start out with either Libraries which offer projections in Python, it was only natural to try them outįor the aforementioned purposes. It is one of the few which combinesĮase of use with unmatched versatility. This is, of course, at the cost of flexibility and performance. That has some batteries included, and works in a single environment (like It is often better for small projects to use a toolchain Requiring a different programming background (R/Python, SQL/NoSQL, There are tools which fit at each point of the process:Īcquisition, processing, storage, serving, display, with each one often Another important caveat is theīreadth of knowledge required to take data from the conceptual phase to anĪpplication phase. To dedicate an entire department to the task. These also have something else in common: they are expensive andĭifficult to set up unless you are part of a Fortune 500 company and can afford
#Bokeh interactive plots professional#
There are many great tools out thereįor professional data aggregation and visualisation which are part of variousīusiness intelligence (BI) suites: think Tableau, Microsoft Power BI, Amazon Interactive figure is worth 1000 pictures. Proponent of data visualisation: a picture is worth 1000 words, but an The second use case is the construction of shareable dashboards.
Zooming, panning and rescaling were as easy as possible. Was therefore looking for something that can quickly generate a figure where Somewhat cumbersome to use, and requiring a large amount of boilerplate code. Jupyter widgets ( ipywidgets), I found them While there are interactive backends for Matplotlib, working in tandem with
While working in iPython or the Jupyter notebook, I wanted something that canĪllow me to quickly explore the data in a straight-forward, interactive way. There were two uses I had in mind for this kind of visualisation tool. Has their own strengths and weaknesses and after taking some time to work withīoth, I can honestly say that there’s no best option. Level of interactivity I was looking for, while being mature enough: There are essentially only two libraries which provide the high Meant that I needed a more powerful data visualisation than trusty old Over the last year, I’ve worked extensively with large datasets in Python, which Bokeh: Interactive Python Visualisation Pros and Cons tags: programming - python
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