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)
Section 1: Best Practices for Using R and Python in Power BI
Section 2: Data Ingestion and Transformation with R and Python in Power BI
Section 3: Data Enrichment with R and Python in Power BI
Section 3: Data Visualization with R in Power BI

Exploiting the interactivity provided by HTML widgets

HTML widgets are R packages that allow you to build interactive web pages. These packages are generated by a framework used to create a binding between R and JavaScript libraries. This framework is made available by the htmlwidgets package developed by RStudio. HTML widgets are always hosted within an R package, including the source code and dependencies, in order to make sure that the widgets are fully reproducible even without being able to access the internet. For more details on how to develop an HTML widget from scratch, take a look at the references.

In addition to being able to embed HTML widgets in RMarkdown files (dynamic documents with R) or Shiny applications (interactive web apps built directly from R), the htmlwidgets package allows you to save them also in standalone web page files thanks to the saveWidget() function.

That said, there are hundreds of R packages that expose their functionalities in HTML widgets...