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Extending Power BI with Python and R: Perform advanced analysis using the power of analytical languages
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Extending Power BI with Python and R: Perform advanced analysis using the power of analytical languages
Extending Power BI with Python and R: Perform advanced analysis using the power of analytical languages
제품번호 #: 87481123

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

제품번호 #: 87481123

KRW 77195

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Shop Extending Power BI with Python and R: Perform advanced analysis using the power of analytical languages online at a best price in South Korea. 1837639531
  • Ingest, transform, manipulate, and visualize your data beyond Power BI's capabilities.Purchase of the print or Kindle book includes a free eBook in PDF format.Key FeaturesDiscover best practices for using Python and R in Power BI by implementing non-trivial codeEnrich your Power BI dashboards using external APIs and machine learning modelsCreate any visualization, as complex as you want, using Python and R scriptsBook DescriptionThe 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.What you will learnConfigure optimal integration of Python and R with Power BIPerform complex data manipulations not possible by default in Power BIBoost Power BI logging and loading large datasetsExtract insights from your data using algorithms like linear optimizationCalculate string distances and learn how to use them for probabilistic fuzzy matchingHandle outliers and missing values for multivariate and time-series dataApply Exploratory Data Analysis in Power BI with RLearn to use Grammar of Graphics in PythonWho this book is forThis 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.Table of ContentsWhere and How to Use R and Python Scripts in Power BIConfiguring R with Power BIConfiguring Python with Power BISolving Common Issues When Using Python and R in Power BIImporting Unhandled Data ObjectsUsing Regular Expressions in Power BIAnonymizing and Pseudonymizing your Data in Power BILogging Data from Power BI to External SourcesLoading Large Datasets Also Beyond the Available RAM in Power BIBoosting Data Loading Speed in Power BI with Parquet FormatCalling External APIs To Enrich Your DataCalculating Columns Using Complex Algorithms: DistancesCalculating Columns Using Complex Algorithms: Fuzzy MatchingCalculating Columns Using Complex Algorithms: Optimization ProblemsAdding Statistics Insights: AssociationsAdding Statistics Insights: Outliers and Missing Values(N.B. Please use the Look Inside option to see further chapters)
Publisher Packt Publishing
Publication date March 29, 2024
Edition 2nd ed.
Language English
Print length 814 pages
ISBN-10 1837639531
ISBN-13 978-1837639533
Item Weight 3.02 pounds (1.37 kg)
Dimensions 7.5 x 1.84 x 9.25 inches (19.1 x 4.7 x 23.5 cm)

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