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python data analysis v413hav

Type:: E-books
Files:: 3
Size:: 21.4 MB
Uploaded On:: Oct. 30, 2012, 7:34 a.m.
Added By:: V413HAV
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Info Hash:: 93F88A840B690632447672F65EFC2A578D405E3F

Python For Data Analysis V413HAV For More Quality Uploads : The Piratebay : https://thepiratebay.se/user/V413HAV/ Facebook Page Address And E-Mail ID In Read Me.txt Support The Developers. If You Like It, Buy It. || || ||||||| TM |||| || || || || || || || || || ||||||| |||||||||| || || || || || || || ||||||| Formats: EPUB, PDF E-Book On Amazon - http://www.amazon.com/Python-Data-Analysis-Wes-McKinney/dp/1449319793 Book Description Python for Data Analysis is concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python. It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you’ll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation language. - Use the IPython interactive shell as your primary development environment - Learn basic and advanced NumPy (Numerical Python) features - Get started with data analysis tools in the pandas library - Use high-performance tools to load, clean, transform, merge, and reshape data - Create scatter plots and static or interactive visualizations with matplotlib - Apply the pandas groupby facility to slice, dice, and summarize datasets - Measure data by points in time, whether it’s specific instances, fixed periods, or intervals - Learn how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples Table of Contents Chapter 1. Preliminaries Chapter 2. Introductory Examples Chapter 3. IPython: An Interactive Computing and Development Environment Chapter 4. NumPy Basics: Arrays and Vectorized Computation Chapter 5. Getting Started with pandas Chapter 6. Data Loading, Storage, and File Formats Chapter 7. Data Wrangling: Clean, Transform, Merge, Reshape Chapter 8. Plotting and Visualization Chapter 9. Data Aggregation and Group Operations Chapter 10. Time Series Chapter 11. Financial and Economic Data Applications Chapter 12. Advanced NumPy Book Details Paperback: 470 pages Publisher: O’Reilly Media (October 2012) Language: English ISBN-10: 1449319793 ISBN-13: 978-1449319793

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