PLEASE NOTE: Since we update Flexmonster Pivot with new features biweekly, the information might become outdated. Please check our latest news.
Readable, powerful and beginner-friendly. These are the main words that best describe Python.
This object-oriented programming language wins the hearts and minds of millions of developers around the world.
You may know Python as a programming language of choice for data science. But it’s not the only way to use it. It’s also a mighty tool for building web apps. You can even use it for creating enterprise software apps since it smoothly integrates with other languages.
Python syntax simplicity and elegance attracted our attention as well. That’s why we’ve decided to make Flexmonster available for Python developers. And the most reasonable choice was to start with Django – one of the most common frameworks for web development and Jupyter Notebook – a web-based interactive development environment for creating notebooks with code and data.
So, if you’re using Django, we have awesome news for you in a new 2.8 release.
Now you can empower your Django apps with interactive visualizations, namely pivot tables and pivot charts.
We prepared the Django with Flexmonster Pivot project that shows how you can handle data visualization on the app’s front end with Flexmonster.
Let us outline use cases examples you can benefit from:
Whether it’s you or your end-users, with Flexmonster, everyone can gain a deeper understanding of their data right in the Django app.
And here’s our cherry on top!
Jupyter Notebook is an essential arrow in the data analyst’s quiver. We believe it’s a must-have tool for statistical modeling and data visualization.
That’s why we decided to take a step closer to the data science community by taking care not only of web developers but also everyone who prefers doing data analysis in Jupyter Notebooks.
Instead of using the powerful method pivot_table of pandas library, we encourage you to try a new approach – render Flexmonster in the notebook’s cell and explore your data interactively. Each time you need to look differently at your data, there’s no need to write a new line of code. Just drag-and-drop. Save results. Gain insights. It’s simple.
Oh, and one more thing. You can also run Flexmonster in JupyterLab.
Go on, give it a go! ?