000			03106nam a2200289uu 4500
005			20250710182907.0
008			250616s||||||||||||||||o||||||||||| |d
024	8	0	_a9781836205869
040			_aPACKT _cPACKT
041			_aen
044			_aGB
100	0		_aWilliam Ayd _eauthor.
700	0		_aMatthew Harrison _eauthor.
700	0		_aWes McKinney _eauthor.
710	2		_aPACKT
773	0		_tPandas Cookbook _dGB,Packt,2024-10-31 _h404
245	0	0	_aPandas Cookbook.
300			_a404.
377			_aen
260			_aGB: _bPackt, _c2024-10-31.
263			_a2024-10-31
264		1	_aGB: _bPackt,
520			_a<p><b>From fundamental techniques to advanced strategies for handling big data, visualization, and more, this book equips you with skills to excel in real-world data analysis projects. Bonus: Free PDF copy + join our Discord + code files</b></p><h4>Key Features</h4><ul><li>This book targets features in pandas 2.x and beyond</li><li>Practical, easy to implement recipes for quick solutions to common problems in data using pandas</li><li>Master the fundamentals of pandas to quickly begin exploring any dataset</li></ul><h4>Book Description</h4>Unlock the full power of pandas 2.x with this hands-on cookbook, designed for Python developers, data analysts, and data scientists who need fast, efficient solutions for real-world data challenges. This book provides practical, ready-to-use recipes to streamline your workflow. With step-by-step guidance, you'll master data wrangling, visualization, performance optimization, and scalable data analysis using pandas' most powerful features. From importing and merging large datasets to advanced time series analysis and SQL-like operations, this cookbook equips you with the tools to analyze, manipulate, and visualize data like a pro. Learn how to boost efficiency, optimize memory usage, and seamlessly integrate pandas with NumPy, PyArrow, and databases. This book will help you transform raw data into actionable insights with ease. <h4>What you will learn</h4><ul><li>The pandas type system and how to best navigate it</li><li>Import/export DataFrames to/from common data formats</li><li>Data exploration in pandas through dozens of practice problems</li><li>Grouping, aggregation, transformation, reshaping, and filtering data</li><li>Merge data from different sources through pandas SQL-like operations</li><li>Leverage the robust pandas time series functionality in advanced analyses</li><li>Scale pandas operations to get the most out of your system</li><li>The large ecosystem that pandas can coordinate with and supplement</li></ul><h4>Who this book is for</h4>This book is for Python developers, data scientists, engineers, and analysts. pandas is the ideal tool for manipulating structured data with Python and this book provides ample instruction and examples. Not only does it cover the basics required to be proficient, but it goes into the details of idiomatic pandas.
538			_aData in extended ASCII character set.
538			_aMode of access: Internet.
856	4	0	_uhttps://learning.packt.com/product/480483
999			_c16058 _d16058