Earlier this month, Microsoft finished the feature roundup for Power BI Desktop for the month – discussing support for Windows 365, among other things. A few days ago, a new Tabular Model Definition Language (TMDL) was unveiled for the data analytics platform.
Previously, adding reports to Jupyter Notebooks required either exporting the Power BI data first, or using some separate tool for the process. The new capability requires using the updated Power BI client library for Jupyter, along with a few related package models. Once a data frame is created using the ubiquitous pandas library, it only takes a couple of lines of code to create interactive visualizations that are also customizable, as described 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
After finalizing the report, users can keep it in their notebook, or even manually save it to share with other relevant people. Saved reports can also be loaded into other notebooks.
There may be an updated Power BI client for Jupyter. Downloaded here on PyPi.With the open source Python package Available on GitHub. With full documentation and demos.