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

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"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

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User Review  - encephalical -

This has the flavor of an O'Reilly Nutshell book because it's mostly a tour of pandas features. Most of the examples are unmotivated and use random numbers instead of real data. If you're looking for ... Read full 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


Chapter 1 Preliminaries
Chapter 2 Introductory Examples
An Interactive Computing and Development Environment
Arrays and Vectorized Computation
Chapter 5 Getting Started with pandas
Chapter 6 Data Loading Storage and File Formats
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
Appendix Python Language Essentials

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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.

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