Python for Data Analysis

Great introduction to IPython.


There are plenty of tools and programming languages focusing on data analysis and machine learning. I recently discovered that some programming languages and tools, e.g. F# and Julia, can be leveraged through IPython allowing one to work in a single environment instead of having to switch tools for different tasks. My first encounter with IPython was through the excellent book Mining the Social Web by Matthew A. Russell, O’Reilly Media. This book is backed by an outstanding IPython experience. My main interest in Python for Data Analysis is to learn more about IPython.

book cover


Since I am a novice python hacker I really appreciated the appendix on Python Language Essentials. This chapter got me up and running with basic Python knowledge in no time.

The chapter about IPython walks you through basic topics like tab completion, introspection, keyboard shortcuts, and magic commands. More advanced features like interaction with OS and interactive debugging are also covered. Most of this can also be found in on-line tutorials but I prefer to have a reference book available for off-line scenarios. There is also a short section about profiles and configurations which turns out to be quite useful information for integrating other programming languages into IPython.


The code examples in the book are based on the Enthought Python Distribution. This makes the setup quite easy. However I believe that the extra time spend on using the build-in Python (at least on Mac enabled systems) would have been better allowing for easier integration with other Python projects.

To test my newly acquired knowledge about IPython and profiles I decided to install IJulie which is a Julia back-end combined with the interactive environment for IPython. Being able to mix multiple languages is really useful for explanatory data analysis.

I will definitely recommend Python for Data Analysis for getting up to speed quickly using IPython.


I review for the O’Reilly Reader Review Program and I want to be transparent about my reviews so you should know that I received a free copy of this ebook in exchange of my review.

I review for the O'Reilly Reader Review Program

Book details

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

Author: Wes McKinney

Publisher: O’Reilly Media

ISBN-10: 1449319793

Release Date: October 2012

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Content of this blog by Carsten Jørgensen is licensed under a Creative Commons Attribution 4.0 International License.