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

McKinney, Wes

ISBN 10: 1449319793 / ISBN 13: 9781449319793

Published by O'Reilly Media, 2012

About this Item

The book is in good condition with all pages and cover intact, including the dust jacket if originally issued. The spine may show light wear. Pages may contain some notes or highlighting, and there might be a "From the library of" label. Boxed set packaging, shrink wrap, or included media like CDs may be missing.

Seller Inventory # BSM.MOPU

Bibliographic Details

• Title: Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
• Publisher: O'Reilly Media
• Publication Date: 2012
• Language: English
• ISBN 10: 1449319793
• ISBN 13: 9781449319793
• Binding: Soft cover
• Condition: good

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.