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

Chapter 3: Configuring Python with Power BI

Just as in Chapter 2, Configuring R with Power BI, you had to install the R engines in order to interact with Power BI, in the same way you will also have to install the Python engines on your machine. You'll also see how to configure some IDEs so you can develop and test Python code comfortably before using it in Power BI. Therefore, similar to what we have already seen in Chapter 2, Configuring R with Power BI the following topics will be discussed in this chapter:

  • The available Python engines
  • Which Python engine should I install?
  • Installing an IDE for Python development
  • Configuring Power BI Desktop to work with Python
  • Configuring the Power BI service to work with Python
  • Limitations of Python visuals