Book Image

Extending Power BI with Python and R

By : Luca Zavarella
Book Image

Extending Power BI with Python and R

By: Luca Zavarella

Overview of this book

Python and R allow you to extend Power BI capabilities to simplify ingestion and transformation activities, enhance dashboards, and highlight insights. With this book, you'll be able to make your artifacts far more interesting and rich in insights using analytical languages. You'll start by learning how to configure your Power BI environment to use your Python and R scripts. The book then explores data ingestion and data transformation extensions, and advances to focus on data augmentation and data visualization. You'll understand how to import data from external sources and transform them using complex algorithms. The book helps you implement personal data de-identification methods such as pseudonymization, anonymization, and masking in Power BI. You'll be able to call external APIs to enrich your data much more quickly using Python programming and R programming. Later, you'll learn advanced Python and R techniques to perform in-depth analysis and extract valuable information using statistics and machine learning. You'll also understand the main statistical features of datasets by plotting multiple visual graphs in the process of creating a machine learning model. By the end of this book, you’ll be able to enrich your Power BI data models and visualizations using complex algorithms in Python and R.
Table of Contents (22 chapters)
1
Section 1: Best Practices for Using R and Python in Power BI
5
Section 2: Data Ingestion and Transformation with R and Python in Power BI
11
Section 3: Data Enrichment with R and Python in Power BI
17
Section 3: Data Visualization with R in Power BI

Packaging it all into a Power BI Custom Visual

Power BI Visual Tools (pbiviz) are the easiest way to build custom visuals in Power BI. They are written in JavaScript (using Node.js) and are used to compile the source code of .pbiviz packages. A .pbiviz package is a zipped version of the Power BI Visual Project, which in turn is a set of folders, scripts, and assets needed to create the custom visualization you want to implement. Generally, a standard Power BI Visual Project is created from a template thanks to the pbiviz command-line tools. The template contents depend on the method by which you want to create the custom visual (TypeScript, R visual, or R HTML).

Important Note

The pbiviz tools do not support any technology that uses Python behind the scenes, such as the ipywidget widgets.

In the light of this, it is worth learning R and ggplot a little more in order to be able to develop interesting custom visuals using the R visual and R HTML modes. In addition to this, as...