{"product_id":"python-for-data-analysis-data-wrangling-with-pandas-numpy","title":"Python for Data Analysis: Data Wrangling with pandas, NumPy","description":"\u003cp\u003eIn this review of Python for Data Analysis, readers get a practical, hands-on handbook aimed at anyone who wants to manipulate and clean real-world datasets in Python. Written by Wes McKinney, the creator of pandas, the third edition focuses on modern tooling-updated for Python 3.10 and pandas 1.4-and delivers clear, example-driven instruction that makes complex data tasks accessible. The single biggest reason to buy is the direct, authoritatitive guidance on using \u003cstrong\u003epandas\u003c\/strong\u003e, \u003cstrong\u003eNumPy\u003c\/strong\u003e and \u003cstrong\u003eJupyter\u003c\/strong\u003e together for everyday data work.\u003c\/p\u003e\u003ch2\u003eKey Features\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eUpdated coverage:\u003c\/strong\u003e The book demonstrates techniques using Python 3.10 and pandas 1.4 so readers learn current idioms and APIs for data manipulation.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAuthor expertise:\u003c\/strong\u003e Written by the creator of the pandas project, the text provides insight into the library's design and best practices for efficient data wrangling.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003ePractical case studies:\u003c\/strong\u003e A range of real-world examples shows how to solve common analysis problems from data cleaning to aggregation and reshaping.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eInteractive workflow:\u003c\/strong\u003e Emphasis on Jupyter notebook and IPython shell supports exploratory computing and rapid iteration when inspecting datasets.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eCompanion materials:\u003c\/strong\u003e Data files and related notebooks are available on GitHub so readers can follow along with reproducible examples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eWho It's For\u003c\/h2\u003e\u003cp\u003eThe book is ideal for analysts who are new to Python and need a practical introduction to tools for data manipulation, as well as for Python developers who want to move into data science or scientific computing. The combined focus on \u003cstrong\u003edata wrangling\u003c\/strong\u003e and interactive workflows makes it useful for those working with tabular data, CSVs, or time series.\u003c\/p\u003e\u003cp\u003eThose seeking a textbook with end-of-chapter exercises for classroom use or a color-illustrated reference may look elsewhere, since some readers note the learning material is mixed and the printing is in black and white rather than color.\u003c\/p\u003e\u003ch2\u003ePros \u0026amp; Cons\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003ePros\u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eComprehensive, practical coverage of pandas and NumPy for real data tasks.\u003c\/li\u003e\n\u003cli\u003eAuthoritative guidance from the creator of the pandas project improves trust in recommendations.\u003c\/li\u003e\n\u003cli\u003eWorks well with Jupyter notebooks and includes downloadable data files for hands-on practice.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003cstrong\u003eCons\u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eSome readers report the learning material is uneven, with fewer end-of-chapter exercises than expected.\u003c\/li\u003e\n\u003cli\u003eThe print is black-and-white, which can make some illustrations less clear for visual learners.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eSpecifications\u003c\/h2\u003e\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003eTitle\u003c\/td\u003e\n\u003ctd\u003ePython for Data Analysis: Data Wrangling with pandas, NumPy, and Jupyter\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAuthor\u003c\/td\u003e\n\u003ctd\u003eWes McKinney\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eEdition updates\u003c\/td\u003e\n\u003ctd\u003eUpdated for Python 3.10 and pandas 1.4\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFocus\u003c\/td\u003e\n\u003ctd\u003ePractical data manipulation, cleaning, and processing\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eTools covered\u003c\/td\u003e\n\u003ctd\u003epandas, NumPy, Jupyter, IPython\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eCompanion materials\u003c\/td\u003e\n\u003ctd\u003eData files and notebooks available on GitHub\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e\u003ch2\u003eOur Verdict\u003c\/h2\u003e\u003cp\u003ePython for Data Analysis is a high-value, practical resource for analysts and Python programmers entering data science. Its authoritative, example-focused approach teaches current pandas and NumPy workflows and pairs well with Jupyter for exploratory work. It may not serve as a color-illustrated textbook or a workbook with many exercises, but for hands-on data wrangling guidance from the creator of pandas it is a smart buy.\u003c\/p\u003e\u003ch2\u003eFrequently Asked Questions\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eDoes this edition cover the latest pandas and Python?\u003c\/strong\u003e\u003cbr\u003eYes. This third edition is updated for Python 3.10 and pandas 1.4 so examples use current APIs.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eAre there materials to practice with?\u003c\/strong\u003e\u003cbr\u003eYes. Data files and related Jupyter notebooks are available on GitHub so you can follow the examples directly.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eIs the book suitable for beginners?\u003c\/strong\u003e\u003cbr\u003eIt suits analysts new to Python and Python programmers new to data science, though some readers note fewer formal exercises than in a classroom textbook.\u003c\/p\u003e","brand":"Wes McKinney","offers":[{"title":"Default Title","offer_id":48605274505435,"sku":"109810403X","price":43.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0724\/1043\/1707\/files\/91QBEYSpnLL._SL1500.jpg?v=1778582744","url":"https:\/\/gearmusthave.com\/products\/python-for-data-analysis-data-wrangling-with-pandas-numpy","provider":"GearMustHave","version":"1.0","type":"link"}