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Python for Data Analysis 3e: Data Wrangling with pandas, NumPy, and Jupyter by W

Description: Python for Data Analysis 3e by Wes McKinney Estimated delivery 3-12 business days Format Paperback Condition Brand New Description Updated for Python 3.10 and pandas 1.4, the third edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. Publisher Description Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.9 and pandas 1.2, the third edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. Youll learn the latest versions of pandas, NumPy, and Jupyter in the process. Its ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Author Biography Wes McKinney is an open source software developer focusing on data analysis tools. He created the Python pandas project and is a co-creator of Apache Arrow, his current development focus. He authored 2 editions of the reference book Python for Data Analysis. Wes is a Member of The Apache Software Foundation and also a PMC member for Apache Parquet. He is the director of Ursa Labs, an not-for-profit development group focused on data science tools for Python and R powered by Apache Arrow, built in partnership with RStudio. Previously, he worked for Two Sigma, Cloudera, and AQR Capital Management, and he was co-founder and CEO of the startup DataPad. Details ISBN 109810403X ISBN-13 9781098104030 Title Python for Data Analysis 3e Author Wes McKinney Format Paperback Year 2022 Pages 550 Edition 3rd Publisher OReilly Media GE_Item_ID:137192355; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. Returns If you wish to return an item, please consult our Returns Policy as below: Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted. Returns must be postmarked within 4 business days of authorisation and must be in resellable condition. Returns are shipped at the customer's risk. We cannot take responsibility for items which are lost or damaged in transit. For purchases where a shipping charge was paid, there will be no refund of the original shipping charge. Additional Questions If you have any questions please feel free to Contact Us. Categories Baby Books Electronics Fashion Games Health & Beauty Home, Garden & Pets Movies Music Sports & Outdoors Toys

Price: 65.94 USD

Location: Fairfield, Ohio

End Time: 2024-12-19T03:06:29.000Z

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Python for Data Analysis 3e: Data Wrangling with pandas, NumPy, and Jupyter by W

Item Specifics

Restocking Fee: No

Return shipping will be paid by: Buyer

All returns accepted: Returns Accepted

Item must be returned within: 30 Days

Refund will be given as: Money Back

ISBN-13: 9781098104030

Book Title: Python for Data Analysis 3e

Number of Pages: 550 Pages

Publication Name: Python for Data Analysis : Data Wrangling with Pandas, Numpy, and Jupyter

Language: English

Publisher: O'reilly Media, Incorporated

Publication Year: 2022

Subject: Data Visualization, Data Processing, Databases / Data Mining, Programming Languages / Python

Item Height: 1.2 in

Type: Textbook

Item Weight: 35.3 Oz

Subject Area: Computers

Author: Wes Mckinney

Item Length: 9.2 in

Item Width: 7.2 in

Format: Trade Paperback

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