Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
Language: English
Published by O'Reilly Media, 2017
- First Edition
- Softcover
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2nd Edition, First Printing. Not price-clipped ($49.99 price intact). Published by O'Reilly, 2017. Quarto. Pictorial wraps. Book is like new; clean with no writing or names. Sharp corners and spine straight. Binding tight and pages crisp. Covers have very light shelf wear. A fine copy of this updated guide to python data analysis. 525 pages. ISBN: 9781491957660. 100% positive feedback. 30 day money back guarantee. NEXT DAY SHIPPING! Excellent customer service. Please email with any questions or if you would like a photo. All books packed carefully and ship with free delivery confirmation/tracking. All books come with free bookmarks. Ships from Southampton, New York. We Buy Books! Individual titles, libraries, collections. Message us if you have books to sell.
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- Title
- Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
- Author
- McKinney, William
- Publisher
- O'Reilly Media
- Publication year
- 2017
- Condition
- Like New
- Binding
- Trade Paperback
- Language
- English
- ISBN 10
- 1491957662
- ISBN 13
- 9781491957660
- Edition
- First Thus.
- Seller catalogs
- Reference
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.
- Use the IPython shell and Jupyter notebook for exploratory computing
- Learn basic and advanced features in NumPy (Numerical Python)
- Get started with data analysis tools in the pandas library
- Use flexible tools to load, clean, transform, merge, and reshape data
- Create informative visualizations with matplotlib
- Apply the pandas groupby facility to slice, dice, and summarize datasets
- Analyze and manipulate regular and irregular time series data
- Learn how to solve real-world data analysis problems with thorough, detailed examples
"Synopsis" may belong to another edition of this title.
About the Author
Wes McKinney is a New York?based software developer and entrepreneur. After finishing his undergraduate degree in mathematics at MIT in 2007, he went on to do quantitative finance work at AQR Capital Management in Greenwich, CT. Frustrated by cumbersome data analysis tools, he learned Python and started building what would later become the pandas project. He's now an active member of the Python data community and is an advocate for the use of Python in data analysis, finance, and statistical computing applications.
Wes was later the co-founder and CEO of DataPad, whose technology assets and team were acquired by Cloudera in 2014. He has since become involved in big data technology, joining the Project Management Committees for the Apache Arrow and Apache Parquet projects in the Apache Software Foundation. In 2016, he joined Two Sigma Investments in New York City, where he continues working to make data analysis faster and easier through open source software.
"About the title" may belong to another edition of this title.
Southampton Books
Sag Harbor, NY, U.S.A.
AbeBooks seller since August 1, 2012
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