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107507754
Polars Cookbook: Over 60 practical recipes to transform, manipulate, and analyze your data using Python Polars 1.x
Item #:
107507754
NZD 124
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What Stands Out
Diverse Recipes
Offers over 60 practical recipes, catering to various data manipulation and analysis tasks, making it suitable for both beginners and experienced users looking to enhance their skills in Python Polars.
Data Transformation
Focuses on transforming and analyzing data efficiently, addressing common problems faced by data analysts and developers, providing ready-to-use solutions for real-world applications.
User-Friendly Guide
Designed as a cookbook, it simplifies learning, allowing users to easily follow instructions and implement solutions, enhancing their understanding of Polars in a hands-on manner.
Product Details
- Leverage Polars, a lightning-fast DataFrame library, to transform your Python-based data science projects with efficient data wrangling and manipulation Key FeaturesUnlock the power of Python Polars for faster and more efficient data analysis workflowsMaster the fundamentals of Python Polars with step-by-step recipesDiscover data manipulation techniques to apply across multiple data problemsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionThe Polars Cookbook is a comprehensive, hands-on guide to Python Polars, one of the first resources dedicated to this powerful data processing library. Written by Yuki Kakegawa, a seasoned data analytics consultant who has worked with industry leaders like Microsoft and Stanford Health Care, this book offers targeted, real-world solutions to data processing, manipulation, and analysis challenges. The book also includes a foreword by Marco Gorelli, a core contributor to Polars, ensuring expert insights into Polars' applications. From installation to advanced data operations, you’ll be guided through data manipulation, advanced querying, and performance optimization techniques. You’ll learn to work with large datasets, conduct sophisticated transformations, leverage powerful features like chaining, and understand its caveats. This book also shows you how to integrate Polars with other Python libraries such as pandas, numpy, and PyArrow, and explore deployment strategies for both on-premises and cloud environments like AWS, BigQuery, GCS, Snowflake, and S3. With use cases spanning data engineering, time series analysis, statistical analysis, and machine learning, Polars Cookbook provides essential techniques for optimizing and securing your workflows. By the end of this book, you'll possess the skills to design scalable, efficient, and reliable data processing solutions with 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 forThis 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
| Publisher | Packt Publishing |
| Publication date | 23 Aug. 2024 |
| Language | English |
| Print length | 394 pages |
| ISBN-10 | 1805121154 |
| ISBN-13 | 978-1805121152 |
| Item weight | 676 g |
| Dimensions | 19.05 x 2.26 x 23.5 cm |
Who Should Buy?
-
Data Analysts
Analysts seeking a practical guide to efficiently manipulate and analyze large datasets using Python Polars will benefit greatly.
-
Machine Learning Engineers
Engineers needing to preprocess datasets quickly for machine learning projects will find useful patterns and recipes in this cookbook.
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Python Developers
Developers wanting to deepen data handling skills with Python Polars will gain hands-on experience through diverse examples and recipes.
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Beginner Programmers
Beginner programmers without prior Python or data manipulation knowledge may struggle with the concepts presented in this cookbook.
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Data Mining Editorial Review
Polars Cookbook: Over 60 Practical Recipes To Transform, Manipulate, And Analyze Your Data Using Python Polars 1.x offers insightful guidance on efficiently handling data with Python. The book, published by Packt Publishing and featuring 394 pages of content, provides over 60 practical recipes tailored for effective data analysis using the Polars library. Readers will benefit from well-structured examples that promote a better understanding of data manipulation. This comprehensive resource covers important aspects of data transformation while being accessible to both beginners and experienced users. It's a valuable addition to any data analyst's library, contributing to their toolkit in data science.
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Pros
- Over 60 practical recipes for data analysis
- Clear examples for beginners and experts
- Comprehensive guide on data manipulation
- Written by reputable publishing house
- Extensive print length for detailed coverage
Cons
- No digital version mentioned, only print availability
Product Price History
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NZD 124
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Features & Benefits
- Over 60 practical recipes for data transformation and analysis.
- Detailed, step-by-step guidance for mastering Python Polars.
- Learn data manipulation techniques applicable across various problems.
- Explore Polars' integration with other tools and deployment options.
- Acquire skills for scalable, efficient data processing solutions.
- Ideal for data analysts, scientists, and engineers familiar with Python.
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