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Description of  Polars Cookbook: Over 60 Practical Recipes to Transform, Manipulate, and Analyze Your Data Using Python Polars

1805121154 EPUB Leverage a lightning fast DataFrame library for efficient data wrangling in Python Polars Cookbook is a complete guide that not only helps you get started with Python Polars but also gives you effective solutions to your day-to-day data problems. Dive into the world of Polars, a high-performance DataFrame library designed for efficient data processing and analysis. This cookbook takes a practical approach to unlocking the full potential of Polars through detailed, step-by-step recipes. Starting with installation and basic operations, this book guides you through data manipulation, advanced querying, and performance optimization techniques. You'll learn how to handle large datasets, perform complex transformations, and leverage Polars' powerful features for data science tasks. As you progress, you'll explore Polars' integration with other tools and libraries, and discover how to deploy Polars in both onpremises and cloud environments. You'll also explore use cases for data engineering, time series analysis, statistical analysis, and machine learning, providing essential strategies for securing and optimizing your Polars workflows. By the end of this book, you'll have acquired the knowledge and skills to build scalable, efficient, and reliable data processing solutions using Polars. What you will learnRead from different data sources and write to various files and databasesApply aggregations, window functions, and string manipulationsPerform common data tasks such as handling missing values and performing list and array operationsDiscover how to reshape and tidy your data by pivoting, joining, and concatenatingAnalyze your time series data in Python PolarsCreate better workflows with testing and debuggingWho this book is for This book is for data analysts, data scientists, and data engineers who want to learn how to use Polars in their workflows. Working knowledge of the Python programming language is required. Experience working with a DataFrame library such as pandas or PySpark will also be helpful. Table of ContentsGetting Started with Python PolarsReading and Writing FilesAn Introduction to Data Analysis in Python PolarsData Transformation TechniquesHandling Missing DataPerforming String ManipulationsWorking with Nested Data StructuresReshaping and Tidying dataTime Series AnalysisInteroperability with Other Python LibrariesWorking with Common Cloud Data SourcesTesting and Debugging in Polars