Python For Data Analysis

Wes McKinney

ISBN 10: 1449319793 / ISBN 13: 9781449319793

Published by OReilly, 2014

About this Item

ISBN 9781449319793. Trade Paperback. Later printing of revised edition of 2013. Very slight wear to corners and edges; very slight dustsoiling to edges; otherwise tight, sound and unmarked in Very Good to Near Fine condition.

Seller Inventory # 4221161

Bibliographic Details

• Title: Python For Data Analysis
• Publisher: OReilly
• Publication Date: 2014
• ISBN 10: 1449319793
• ISBN 13: 9781449319793
• Binding: Paperback
• Edition: Later Edition.
• Condition: Very Good
• Dust Jacket Condition: No Dustjacket
• Signed: No Signature
• Seller catalogs:
  • Computers

About this title

Synopsis

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.

Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It’s ideal for analysts new to Python and for Python programmers new to scientific computing.

• 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

About the Author

Wes McKinney is the main author of pandas, the popular open source Python library for data analysis. Wes is an active speaker and participant 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.