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Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second 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. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process.
Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub.
About the Author: Wes McKinney is the main author of pandas, the popular open sourcePython library for data analysis. Wes is an active speaker andparticipant in the Python and open source communities. He worked as a quantitative analyst at AQR Capital Management and Python consultant before founding DataPad, a data analytics company, in 2013. He graduated from MIT with an S.B. in Mathematics.
Title: Python for Data Analysis: Data Wrangling ...
Publisher: O'Reilly Media
Publication Date: 2017
Binding: paperback
Condition: Acceptable
Edition: 2nd Edition
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Seller: Bookmans, Tucson, AZ, U.S.A.
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Seller: HPB-Red, Dallas, TX, U.S.A.
Paperback. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority! Seller Inventory # S_420679294
Seller: World of Books (was SecondSale), Montgomery, IL, U.S.A.
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Seller: -OnTimeBooks-, Phoenix, AZ, U.S.A.
Condition: very_good. Gently read. May have name of previous ownership, or ex-library edition. Binding tight; spine straight and smooth, with no creasing; covers clean and crisp. Minimal signs of handling or shelving. 100% GUARANTEE! Shipped with delivery confirmation, if you're not satisfied with purchase please return item for full refund. Ships USPS Media Mail. Seller Inventory # OTV.1491957662.VG