Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython (Google eBook)

Front Cover
"O'Reilly Media, Inc.", Oct 8, 2012 - Computers - 470 pages
20 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 youíll 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. Itís 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 itís 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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Review: Python for Data Analysis

User Review  - Michael - Goodreads

I've used Python for a few years and have recently started implementing it at work. We used to have Matlab for basic scripting, plotting, and analysis and recently dropped it due to their ridiculous ... Read full review

Review: Python for Data Analysis

User Review  - James Williams - Goodreads

In my office, we spend a lot of time in the database. As such, we tend to become fairly adept at analyzing data with SQL: join some tables on interesting columns, group by other interesting columns ... 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

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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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