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Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython by [McKinney, Wes]
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Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython 2nd Edition, Kindle Edition

4.0 out of 5 stars 1 customer review

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Length: 522 pages Enhanced Typesetting: Enabled Page Flip: Enabled
Language: English

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Product description

Product Description

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

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.


Product details

  • Format: Kindle Edition
  • File Size: 11200 KB
  • Print Length: 550 pages
  • Simultaneous Device Usage: Unlimited
  • Publisher: O'Reilly Media; 2 edition (25 September 2017)
  • Sold by: Amazon Australia Services, Inc.
  • Language: English
  • ASIN: B075X4LT6K
  • Text-to-Speech: Enabled
  • X-Ray:
  • Word Wise: Not Enabled
  • Enhanced Typesetting: Enabled
  • Average Customer Review: 4.0 out of 5 stars 1 customer review
  • Amazon Bestsellers Rank: #66,368 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
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27 December 2018
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Amazon.com: 4.2 out of 5 stars 81 reviews
Ocean Horizon
5.0 out of 5 starsProvides the Python tools for implementing machine learning algorithms...
8 January 2018 - Published on Amazon.com
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27 people found this helpful
Ocean State Prime
3.0 out of 5 starsless than what I had hoped
31 July 2018 - Published on Amazon.com
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23 people found this helpful
Saurabh
1.0 out of 5 starspoor explanations and uses random numbers for examples
17 April 2018 - Published on Amazon.com
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28 people found this helpful
Lucas
5.0 out of 5 starsVery simple ,well designed practical book. Recommend to beginners and Intermediates
7 December 2017 - Published on Amazon.com
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26 people found this helpful
Christopher
5.0 out of 5 starsAwesome Book to Gain Practical Data Skills with Python
5 April 2019 - Published on Amazon.com
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5 people found this helpful