Bokeh

4.7
(3)

Bokeh is a Python based interactive visualization library.

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Bokeh review by Prabhu D.
Prabhu D.
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"Data Visualization with the help of Bokeh"

What do you like best?

Data visualization is the most important part for the data science and the one who do data scientist. So this might be a much useful library for those. This ultimately, targets the web browser to make more presentable to the user. Bokeh is available in many programming language. But with the power of python implementation can be done in short way.

Let me explain how Bokeh present into the browser. Whenever the term browser comes, there is one hidden word JS – javascript. So first, output of Bokeh goes into the Bokehjs and then it present on the canvas of the browser.

What do you dislike?

See, now with the pros, cons also are there. No doubt about that Bokeh gives amazing visualization on the web. But in terms of degree of interactivity is less.

Recommendations to others considering the product

The only recommendation for the readers is that go through the perfect documentation of the Bokeh and then go for the implementing it.

What business problems are you solving with the product? What benefits have you realized?

In my many personal projects as well as my assigned task of the industrial projects I used Bokeh for the data visualization. Because it helps in make the product better.

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Bokeh review by Karan M.
Karan M.
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"Best Visualization Tool Around the World"

What do you like best?

Bokeh provides a variety of graphs that can be plotted from simple bar charts to pie charts.

It is very simple to apply on any kind of data. Even very easy to integrate to any kind of python application.

Also learning it is not a big deal. We organized a small workshop for 2-3 days for our employees and everyone was able to use it with very less or no major issues.

What do you dislike?

No major issues for visualizations but I have found out an issue, the quality of the print is not as goog as other such tools like seaborn or matplotlib.

Recommendations to others considering the product:

I would recommend every indusrty as well as individual around the world to use bokeh for visualization. As everyone knows data understanding is essential for improving business growth. This understanding can be easily achieved using Bokeh which provides high-level and good quality visualization.

What problems are you solving with the product? What benefits have you realized?

We have a lot of data for different projects where we need to visualize data for analysis perspective.

Even our customers also sometimes ask for different visualizations on the data they have. We use Bokeh to meet the needs and provide them with various reports.

Bokeh has proved very useful in business, with the help of Bokeh we were able to visualize data which in turn helped to understand it.

What Data Visualization solution do you use?

Thanks for letting us know!
Bokeh review by User in Computer Networking
User in Computer Networking
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"Great python library for more advanced data visualizations"

What do you like best?

Python is my THE go-to programming language for visualizing data, and Bokeh makes it better. It allows developers and data scientists to quickly create data visuals that go beyond the capabilities of out of the box BI tools. It is great at making interactive visuals attainable relatively quickly.

What do you dislike?

With all of the tools on the market, Bokeh can be kind of slow to build. The complexity of the output means that you're building the viz one piece at a time. The flip side of this, of course, is that your end product is so much more compelling. But it does take time.

Recommendations to others considering the product:

If you take the time to learn to use it, you will be able to create better visualizations.

What problems are you solving with the product? What benefits have you realized?

Bokeh allows me to create more interactive data visualizations, which is not possible with the standard tools of the trade (Tableau, Power BI). It tells more compelling data stories.

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