Earlier this month, Microsoft went over the feature roundup for Power BI Desktop for this month - discussing support for Windows 365, among other items. A couple of days before that, a new Tabular Model Definition Language (TMDL) was unveiled for the data analytics platform.
Previously, adding reports to Jupyter Notebooks would require either Power BI data to be exported first, or some separate tool to be utilized for the process. The new capability simply requires using the updated Power BI Client library for Jupyter, along with a few relevant models from the package. Once a dataframe has been created using the ubiquitous Pandas library, a couple of lines of code is all it takes to generate interactive visualizations that are customizable as well, as noted below:
# Create a Power BI report from your data PBI_visualize = QuickVisualize(get_dataset_config(df), auth=device_auth) # Render the new report PBI_visualize Once the report has been finalized, users can keep it in their notebook, or even manually save them to be shared with other relevant people. The saved reports can be loaded in other notebooks as well.
The updated Power BI Client for Jupyter can be downloaded here at PyPi, with the open-sourced Python package being available on GitHub along with complete documentation and demos.