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Data Analysis with Open Source Tools: A Hands-On Guide for Programmers and Data Scientists
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Data Analysis with Open Source Tools: A Hands-On Guide for Programmers and Data Scientists

4.08  ·  Rating details ·  308 ratings  ·  16 reviews
Collecting data is relatively easy, but turning raw information into something useful requires that you know how to extract precisely what you need. With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contain ...more
Paperback, 509 pages
Published December 14th 2010 by O'Reilly Media (first published 2010)
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Dec 26, 2010 rated it it was amazing
This is a book that is how to think about data analysis, not only how to perform data analysis. Like a good data analysis, Janert's book is about insight and comprehension, not computation. And because of this it should be a part of any analysts bookshelf, set apart from all the books that merely teach tools and techniques.

The practice of data analysis can get a bad rap, especially by those who think that data analysis is only statistics. Most books on data analysis don’t help because they focus
John Orman
Jan 31, 2013 rated it really liked it
I used this book in my online Data Analysis class, in which we used the open source language R. The book also mentions Octave, a clone of Matlab. I used Octave for my online Machine Learning class.
Python and Java are also given a brief description.
The reader is also asked to investigate Perl, Ruby, regular expressions, databases, and Unix.

This book has some very good sections on graphical analysis of data. Also includes probability modeling, and an interesting chapter on using statistics in myth
Mar 26, 2016 rated it really liked it
Shelves: data-science, math
Book is focused not on tools (mostly outdated by now), but on methods, skills and underlying math, with many examples of applications in real-life context. I really liked this approach, even though some equations were a bit too hard and some examples are too far from my area of interest.
Oct 23, 2015 rated it it was amazing
Shelves: d_s_general
Les reproches faits à ce livre sont de deux ordres. Le premier porte sur sa structure -- voire son contenu -- qui n'est pas conventionnelle pour un livre intitulé Data analysis. C'est vrai que l'on s'attend à suivre une méthodologie, à être guidé et il faut bien reconnaître que ce n'est pas le cas. Si vous cherchez ce type d'ouvrage, je vous conseille de vous plonger dans [Book: Practical Data Science with R] qui est un excellent ouvrage tout à fait dans ce registre. Cette approche non conventio ...more
Dec 31, 2012 rated it it was amazing
Shelves: data-analysis
Author keeps placing emphasis on insights instead of numbers while working with data. The ultimate goal of data analysis is to understand how the system works, not to show off how proficient you are at Math. That's the true spirit of professionalism. Some annoying jargon are well explained in a plain manner. Little sections on R. ...more
Sweemeng Ng
Jul 13, 2012 rated it it was amazing
This book focuses on methods and experience, using tools only for demonstrating on the topic.

Where many books already cover tools, this book covers what many don't, insights and experience. While many topics with enough explanation on the method and where to use it.

Highly recommended
Donn Lee
Oct 12, 2016 rated it it was amazing
I love most O'Reilly books and this one doesn't disappoint. There is plenty of great material in here for [aspiring] data scientists; very nicely chapterised with a nice mix of tools. Was doing a forecasting project and had this book constantly by my side for inspiration - wonderful reference. ...more
Matt Heavner
May 16, 2011 rated it really liked it
This is a good thought provoking read. It is a reminder of lots of techniques I've already "learned" -- but a great practical review and refresher. ...more
Apr 04, 2012 rated it really liked it
Good refresher on data analysis for more detailed work
Feb 05, 2015 rated it liked it
Good in its time. Outdated now.
Dec 02, 2013 rated it really liked it
Data analysis book using Python/R and focusing on more methods in a not math-heavy way, rather than implementation details.
Andries Burger
May 05, 2011 rated it really liked it  ·  review of another edition
Just started on this book. Have lots of data to turn into information. Some obscure, some blatant.

Will add to this review as I work my way through the book...
Emily Leathers
Mar 29, 2011 rated it liked it
Recommends it for: Analysis Team
I haven't touched this for a while, so it seemed more appropriate to move it to the on-hold category. I was really intrigued by the sections that I did read though, so I plan to get back to it soon. ...more
Jan 18, 2016 rated it really liked it
Pleasantly focussed on methods, so that the somewhat dated view on technologies doesn't hurt too much. ...more
Delhi Irc
Location: ND5 IRC
Accession no: DL026845
Vuk Trifkovic
Feb 08, 2011 rated it really liked it
Shelves: o-reilly, tech
Very good. Focus is firmly on the methods, but with just enough tooling or practical data. I'd start from this, and then dive into specific toolsets, say R or some Python libs.. ...more
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