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Python for Data Analysis: Data Wrangling…

Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython

by Wes McKinney

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A better title for this book might be Pandas and NumPy in Action

As the creator of the pandas project, a Python data analysis framework, [a:Wes McKinney|6007417|Wes McKinney|http://www.goodreads.com/assets/nophoto/nophoto-U-50x66-347709e8e0c4cd87940bf10aebee7a1c.jpg] is well placed to write this book. His experience and vision for the pandas framework is clear, and he is able to explain the main function and inner workings of both pandas and another package, NumPy, very well.

Although the title of the book suggests a broad look at the Python language for data analysis, McKinney almost exclusively focuses on an in-depth exploration of pandas. The book started with a great deal of promise, but as McKinney delved into the detail of NumPy and pandas, the ideas and examples of data analysis are replaced with random number datasets.

The book became a tiresome parade of pandas feature after pandas feature. Each example was stripped of meaning without any real world basis. It would have been great to see more real world cases drawn from McKinney's experience as a day to day user of pandas and Python for data analysis.

This book would be ideal if you're using, or thinking about using NumPy or pandas. If you're looking for a broader introduction to Data Analysis with Python, this might not be the book for you. ( )
  Beniaminus | Nov 1, 2017 |
452 p.
  BmoreMetroCouncil | Feb 9, 2017 |
A great handbook for anyone looking to do break down data sets in Python. This won't teach you what to look for or how to do data analysis, but it will show you all the tools to get it done. ( )
  trilliams | May 30, 2015 |
Good introduction to the Python programming language for those who have experience in other ones like Matlab or R and want to take advantage of the Python technology. Although it is mainly focused on the pandas library, the numpy chapters and of course the annex that summarizes the Python syntax are very useful resources. After reading this book I feel ready to go. ( )
  pablosuau | Feb 13, 2014 |
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Serves as an introduction to Python for data-intensive applications.

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