WebDataRocks 1.3.1: Pivot with Django, Jupyter Notebook & amCharts
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We’re excited to announce some major upgrades to our pivot table component! Now you can seamlessly integrate WebDataRocks into your Python projects with Django and Jupyter Notebook.
The last update of WebDataRocks pivot table brought a lot of new tweaks that improved reporting a lot. It didn’t take long for us to prepare a new stack of features for flawless data visualization and analysis.
All along we’ve been working on extending our product’s integration opportunities, thus you will find new advancements to match new libraries and technologies. Being more specific, we made new integrations with Django, Jupyter Notebook & amCharts.
Get ready to learn more.
WebDataRocks Pivot Table with Python
We couldn’t overlook Python developers, as this language is so widely used for developing different web apps and software. It’s also the core for scientific reporting, statistical analysis, and far more. Thus, we made it possible to work with our web reporting tool.
We provide you with the two most common scenarios where we think the pivot table could be perfectly used.
Pivot Table for Django
It’s well-known how the Django framework is loved for its wide range of features and ease of programming. With this in mind we made the way to integrate the pivot table with Django as simple as the framework requires.
Our team prepared a guide and a ready-to-use sample on GitHub that can be run with a few code lines.
Now you can easily create configurable and interactive reports with pivot based on your business data and share it with users directly from your Django application.
Pivot Table for Jupyter Notebook
The Jupyter Notebook, a spin-off project from the IPython, is used for creating visualizations, calculations and analytics. Well, it sounds like a perfect match for WebDataRocks. Why don’t we use them both (WebdataRocks and Jupiter) to empower the visualization process and somehow to save your time for data aggregation? We offer a totally new but effective approach to render WebDataRocks Pivot Table in the Notebook’s cell to get the immediate result. No need for new code lines to manipulate data.
Yes, it’s that simple.
All you need is just go with the GitHub project we prepared and follow some steps. Then play with your data the way you want, results are on you.
WebDataRocks with amCharts
This charting library has caught our attention because of its stylish design and variety of charts it offers that could spice up nicely any report.
The other value that should be stressed out is that as input, some charts need to accept already aggregated data, here is where our component will especially come in handy. It works as follows: you take your dataset, then pivot, calculate it the way you need with WebDataRocks, and after – send prepared data to charts. All is done on the fly. It’s undoubtedly а win-win process.
Our JavaScript Pivot tool could be integrated with any charts but for the most used ones, we support our users with connectors to make the integration effortless. For integration with amCharts, we do the same. Now you can easily use both our libraries to create interactive and insightful reports, set up elegant dynamic dashboards, and visualize your data the way you see it.
We prepared the connector and detailed tutorial.
But first, let’s take a look at the demo:
See the Pen Dashboard with amCharts & WebDataRocks Pivot Table by WebDataRocks (@webdatarocks) on CodePen.
In hope, you will find it useful and these new features will cheer you up these days.
Stay tuned for further updates!
All you need to start using the latest version:
- How to integrate the pivot table with Django
- How to integrate the pivot table with Jupyter Notebook
- How to integrate the pivot table with the amCharts charting library.
