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

Accessing web services using Power BI

Power BI already has default features that allow you to access the data exposed by a web service into Power Query. There are two main modes:

  • Via the GUI (click on Get data, then Web, and then you can set advanced options if needed).
  • Through the M language, using the Web.Contents() function.

The use of the GUI is very cumbersome and almost always does not lead to the desired results. The only way to effectively connect to a web service using native Power BI features is to write M code. Writing code in M is not too difficult. However, there are some complications in using the Web.Contents() function that arise when publishing a report that makes use of it to the Power BI service. In short, it is necessary to be careful when you have to build the URL to use in the GET request in a dynamic way, making use of the relative path and the query options. If you do not use this particular construct, the service will not be able to refresh...