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Extending Power BI with Python and R
Extending Power BI with Python and R

Extending Power BI with Python and R: Perform advanced analysis using the power of analytical languages , Second Edition

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Extending Power BI with Python and R

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Key benefits

  • Discover best practices for using Python and R in Power BI by implementing non-trivial code
  • Enrich your Power BI dashboards using external APIs and machine learning models
  • Create any visualization, as complex as you want, using Python and R scripts

Description

The latest edition of this book delves deep into advanced analytics, focusing on enhancing Python and R proficiency within Power BI. New chapters cover optimizing Python and R settings, utilizing Intel's Math Kernel Library (MKL) for performance boosts, and addressing integration challenges. Techniques for managing large datasets beyond available RAM, employing the Parquet data format, and advanced fuzzy matching algorithms are explored. Additionally, it discusses leveraging SQL Server Language Extensions to overcome traditional Python and R limitations in Power BI. It also helps in crafting sophisticated visualizations using the Grammar of Graphics in both R and Python. This Power BI book will help you master data validation with regular expressions, import data from diverse sources, and apply advanced algorithms for transformation. You'll learn how to safeguard personal data in Power BI with techniques like pseudonymization, anonymization, and data masking. You'll also get to grips with the key statistical features of datasets by plotting multiple visual graphs in the process of building a machine learning model. The book will guide you on utilizing external APIs for enrichment, enhancing I/O performance, and leveraging Python and R for analysis. You'll reinforce your learning with questions at the end of each chapter.

Who is this book for?

This book is for business analysts, business intelligence professionals, and data scientists who already use Microsoft Power BI and want to add more value to their analysis using Python and R. Working knowledge of Power BI is required to make the most of this book. Basic knowledge of Python and R will also be helpful.

What you will learn

  • Configure optimal integration of Python and R with Power BI
  • Perform complex data manipulations not possible by default in Power BI
  • Boost Power BI logging and loading large datasets
  • Extract insights from your data using algorithms like linear optimization
  • Calculate string distances and learn how to use them for probabilistic fuzzy matching
  • Handle outliers and missing values for multivariate and time-series data
  • Apply Exploratory Data Analysis in Power BI with R
  • Learn to use Grammar of Graphics in Python

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Mar 29, 2024
Length: 814 pages
Edition : 2nd
Language : English
ISBN-13 : 9781837639533
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Languages :
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Product Details

Publication date : Mar 29, 2024
Length: 814 pages
Edition : 2nd
Language : English
ISBN-13 : 9781837639533
Category :
Languages :
Tools :

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Frequently bought together


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Table of Contents

24 Chapters
Where and How to Use R and Python Scripts in Power BI Chevron down icon Chevron up icon
Configuring R with Power BI Chevron down icon Chevron up icon
Configuring Python with Power BI Chevron down icon Chevron up icon
Solving Common Issues When Using Python and R in Power BI Chevron down icon Chevron up icon
Importing Unhandled Data Objects Chevron down icon Chevron up icon
Using Regular Expressions in Power BI Chevron down icon Chevron up icon
Anonymizing and Pseudonymizing Your Data in Power BI Chevron down icon Chevron up icon
Logging Data from Power BI to External Sources Chevron down icon Chevron up icon
Loading Large Datasets Beyond the Available RAM in Power BI Chevron down icon Chevron up icon
Boosting Data Loading Speed in Power BI with Parquet Format Chevron down icon Chevron up icon
Calling External APIs to Enrich Your Data Chevron down icon Chevron up icon
Calculating Columns Using Complex Algorithms: Distances Chevron down icon Chevron up icon
Calculating Columns Using Complex Algorithms: Fuzzy Matching Chevron down icon Chevron up icon
Calculating Columns Using Complex Algorithms: Optimization Problems Chevron down icon Chevron up icon
Adding Statistical Insights: Associations Chevron down icon Chevron up icon
Adding Statistical Insights: Outliers and Missing Values Chevron down icon Chevron up icon
Using Machine Learning without Premium or Embedded Capacity Chevron down icon Chevron up icon
Using SQL Server External Languages for Advanced Analytics and ML Integration in Power BI Chevron down icon Chevron up icon
Exploratory Data Analysis Chevron down icon Chevron up icon
Using the Grammar of Graphics in Python with plotnine Chevron down icon Chevron up icon
Advanced Visualizations Chevron down icon Chevron up icon
Interactive R Custom Visuals Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon

Customer reviews

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(30 Ratings)
5 star 96.7%
4 star 3.3%
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Joseph C. Seroski Apr 01, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book is a good reference to understand how you can use Python and R in Power BI. It has a good introduction to getting setup and some great examples as to how you can extend your reports and advance your skills using these two programming languages.I enjoyed this book brings a unique perspective that I haven't seen in many other Power BI books. I am looking forward to getting more into the Python language, and this book will be helpful, especially with all the functionality coming to Fabric. I recommend this book to add another feather to your cap.
Amazon Verified review Amazon
Thomas Rice Aug 03, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
"Extending Power BI with Python and R" is a comprehensive and practical guide for enhancing data analysis capabilities in Power BI. With detailed explanations, practical examples, and step-by-step instructions, this book is an essential resource for anyone looking to integrate R and Python into their Power BI workflows. Whether you're a beginner or an experienced user, this book provides valuable insights and practical tips for maximizing the potential of Power BI. As an avid book worm, having read more than 30 books on the Microsoft Power Platform, this one is a must for anyone that works with Power BI. Highly recommended guys!
Amazon Verified review Amazon
Arden Jul 26, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The book author has a strong hold over the Powerbi community and even the technology I believe this book is beneficial for people who have had a strong command over the Power BI, R and Python space because of the diversity it brings throughout the chapters, the most important thing is the journey of different libraries and how it has affected the whole space and how the case studies have been shared throughout the book. Congratulations to the authors for binding in a book of such quality!
Amazon Verified review Amazon
Sruthi Panikar Apr 16, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Excellent book for anyone interested in python and r at the same time loved the book its an amazing title!
Amazon Verified review Amazon
Brady Apr 03, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
A great resource for Power BI users aiming to bolster their analytical prowess. The authors offer well-explained and hands-on examples, leading readers through the intricacies of seamlessly integrating Python and R with Power BI.I was particularly drawn to the Python side of this book. I've often found using Python visuals or features in Power BI to be cumbersome. My visuals would load slowly, prompting me to revert to default visuals in Power BI and stick to traditional M query data transformations.This book opened up some possibilities I'd never considered where in the past I'd given up trying to implement. Python has much more appealing visuals and data capabilities but I didn't know how to use it without seemingly bogging down my entire report. As a heavy Power BI user, I got a lot of new ideas to consider from this book.
Amazon Verified review Amazon
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