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Polars Cookbook

You're reading from   Polars Cookbook Over 60 practical recipes to transform, manipulate, and analyze your data using Python Polars 1.x

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Product type Paperback
Published in Aug 2024
Publisher Packt
ISBN-13 9781805121152
Length 394 pages
Edition 1st Edition
Languages
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Author (1):
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Yuki Kakegawa Yuki Kakegawa
Author Profile Icon Yuki Kakegawa
Yuki Kakegawa
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Toc

Table of Contents (15) Chapters Close

Preface 1. Chapter 1: Getting Started with Python Polars FREE CHAPTER 2. Chapter 2: Reading and Writing Files 3. Chapter 3: An Introduction to Data Analysis in Python Polars 4. Chapter 4: Data Transformation Techniques 5. Chapter 5: Handling Missing Data 6. Chapter 6: Performing String Manipulations 7. Chapter 7: Working with Nested Data Structures 8. Chapter 8: Reshaping and Tidying Data 9. Chapter 9: Time Series Analysis 10. Chapter 10: Interoperability with Other Python Libraries 11. Chapter 11: Working with Common Cloud Data Sources 12. Chapter 12: Testing and Debugging in Polars 13. Index 14. Other Books You May Enjoy

Index

As this ebook edition doesn't have fixed pagination, the page numbers below are hyperlinked for reference only, based on the printed edition of this book.

Symbols

.agg() method 88, 220-222

.approx_n_unique() method 78

.collect_all() method 62

.describe() method 70

.dt.year() method 108

.estimated_size() method 70

.fetch() method 241

.filter() method 99

.from_pandas() method 275

.glimpse() method 70

.group_by_dynamic() method 263

.group_by() method 62, 88, 220-263

.head() method 70

.hstack() method 234

.is_duplicated() method 77

.join() method 229

.len_bytes() method 154

.len_chars() method 154

.map_batches() method 125

.map_element() method 125, 255

.map_elements() method

.map_groups() method 125

.map_rows() method 125

.null_count() method 71

.over() method 120

.partition_by() method 237

.pipe() method

using 344

.pivot() method 217, 220-222

.read_database...

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