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

Front Cover
"O'Reilly Media, Inc.", Oct 8, 2012 - Computers - 466 pages

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
 

What people are saying - Write a review

LibraryThing Review

User Review  - trilliams - LibraryThing

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. Read full review

Helpful

User Review  - OstkUser894211 - Overstock.com

Great book to work through. Read full review

Contents

Chapter 1 Preliminaries
1
Chapter 2 Introductory Examples
13
An Interactive Computing and Development Environment
41
Arrays and Vectorized Computation
75
Chapter 5 Getting Started with pandas
107
Chapter 6 Data Loading Storage and File Formats
153
Clean Transform Merge Reshape
175
Chapter 8 Plotting and Visualization
217
Chapter 9 Data Aggregation and Group Operations
249
Chapter 10 Time Series
285
Chapter 11 Financial and Economic Data Applications
325
Chapter 12 Advanced NumPy
349
Appendix Python Language Essentials
381
Index
429
Copyright

Other editions - View all

Common terms and phrases

About the author (2012)

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 before founding an enterprise data analysis company, Lambda Foundry, in 2012. He graduated from MIT with an S.B. in Mathematics.

Bibliographic information