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

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

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

User ratings

5 stars
5
4 stars
5
3 stars
2
2 stars
0
1 star
0

Review: Python for Data Analysis

User Review  - Goodreads

Good for familiarizing with python tools numpy, matplotlib, and pandas. But not that great for applying the tools to do any analysis. Though it did have a few examples of analysis using the tools. I will still keep the book around for reference as I get more familiar w/ pandas. Read full review

Review: Python for Data Analysis

User Review  - Goodreads

Pandas has advanced since the book, so I'm looking forward to vol2. The book itself is very terse it's a reference more than a how-to. Read full review

Contents

Chapter 1 Preliminaries
1
Chapter 2 Introductory Examples
17
An Interactive Computing and Development Environment
45
Arrays and Vectorized Computation
79
Chapter 5 Getting Started with pandas
111
Chapter 6 Data Loading Storage and File Formats
155
Clean Transform Merge Reshape
177
Chapter 8 Plotting and Visualization
219
Chapter 9 Data Aggregation and Group Operations
251
Chapter 10 Time Series
289
Chapter 11 Financial and Economic Data Applications
329
Chapter 12 Advanced NumPy
353
Appendix Python Language Essentials
385
Index
433
Copyright

Common terms and phrases

About the author (2012)

Wes McKinney is the main author of pandas, the popular open sourcePython library for data analysis. Wes is an active speaker andparticipant in the Python and open source communities. He worked as aquantitative analyst at AQR Capital Management and Python consultantbefore founding DataPad, a data analytics company, in 2013. Hegraduated from MIT with an S.B. in Mathematics.

Bibliographic information