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Clojure Data Analysis Cookbook

Clojure Data Analysis Cookbook [Kindle Edition]

Eric Rochester

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In Detail

Data is everywhere and it's increasingly important to be able to gain insights that we can act on. Using Clojure for data analysis and collection, this book will show you how to gain fresh insights and perspectives from your data with an essential collection of practical, structured recipes.

"The Clojure Data Analysis Cookbook" presents recipes for every stage of the data analysis process. Whether scraping data off a web page, performing data mining, or creating graphs for the web, this book has something for the task at hand.

You'll learn how to acquire data, clean it up, and transform it into useful graphs which can then be analyzed and published to the Internet. Coverage includes advanced topics like processing data concurrently, applying powerful statistical techniques like Bayesian modelling, and even data mining algorithms such as K-means clustering, neural networks, and association rules.


Full of practical tips, the "Clojure Data Analysis Cookbook" will help you fully utilize your data through a series of step-by-step, real world recipes covering every aspect of data analysis.

Who this book is for

Prior experience with Clojure and data analysis techniques and workflows will be beneficial, but not essential.

About the Author

Eric Rochester

Eric Rochester enjoys reading, writing, and spending time with his wife and kids. When he's not doing those things, he programs in a variety of languages and platforms, including websites and systems in Python and libraries for linguistics and statistics in C#. Currently, he's exploring functional programming languages, including Clojure and Haskell. He works at the Scholars' Lab in the library at the University of Virginia, helping humanities professors and graduate students realize their digitally informed research agendas.

Product details

  • Format: Kindle Edition
  • File Size: 2290 KB
  • Print Length: 342 pages
  • Publisher: Packt Publishing (25 Mar 2013)
  • Sold by: Amazon Media EU S.à r.l.
  • Language: English
  • Text-to-Speech: Enabled
  • X-Ray:
  • Amazon Bestsellers Rank: #295,253 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
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Most Helpful Customer Reviews on (beta) 4.4 out of 5 stars  7 reviews
8 of 9 people found the following review helpful
5.0 out of 5 stars A bag of tricks for Data Analysis in Clojure 24 April 2013
By Dmitri Sotnikov - Published on
Data analysis happens to one of the major niches where Clojure has been gaining popularity. However, the documentation on the subject is far from focused.

The book provides a collection of recipes for accomplishing common tasks associated with analyzing different types of data sets. It starts out by showing how to read data from a variety of sources such as JSON, CSV, and JDBC. The next chapter provides a number of examples of how to sanitize the collected data and sample large data sets. After covering loading and sanitizing the data, the book discusses a number of different strategies for processing it.

Some of the highlights include using the Clojure STM, parallel processing of the data, including useful tricks for partitioning, using reducers, and distributed processing with Hadoop and Casalog.

I found the sections on handling large amounts of data particularly interesting. Often times, it's easy to come up with a solution that works for a small data set, but doesn't scale to handle large amounts of data. One of the techniques the book discusses is the use of lazy sequences. Another example is using heuristics to decide how to partition large data sets data sets effectively.

The book closes with a chapter dealing with the presentation the processed data. First, it covers using Incanter charts and then shows how to display the results in the browser with ClojureScript and NVD3.

For the most part, the book is very much example oriented. The examples are accompanied by explantation of how they all fit together. If you're like me and like to get hands on experience then I think you'll like the style of the book.

The examples are short in size and easy to understand. I found that the best way to work through the book was by following along with a REPL session open.

The book also introduces the reader to a number of libraries. Some, such as Incanter are well known, others like parse-ez less so. In my experience, the documentation for many Clojure libraries is often lacking. The recipes in the book serve as a good reference for how to make the most of the tools available.

I would say one missed opportunity in the book is that the examples don't seem to build on each other. You'll see many examples of doing specific tasks, but they will tend to be self contained and don't build up to anything more substantial.

I suspect this was done in order to keep content accessible so that the reader can look at any section without having to have read the others. Conversely, don't expect to see examples of how to structure your projects and build applications end to end.

Overall, I would say this book is aimed at somebody who is already comfortable using Clojure and would like to learn some of the more advanced techinques for working with data processing and analysis. If you're thinking of using Clojure for analyzing your data sets this book will likely save you a lot of time and serve as a handy reference down the road.
4 of 5 people found the following review helpful
4.0 out of 5 stars A good book for developers 6 May 2013
By gahlberg - Published on
I read the PDF version and I love the book already from the beginning.

Most books will show you "How to read data" and go through a trivial parse string sample. This book does this well, as well as a thorough step by step guide for JDBC, XML, JSON, web scraping, RDF and SPARQL. The labor that the author gone through is impressive. Also, a brief introduction statistics terms too. When to use different statistic tools is also included. Use "this method when you want that" is very nice and helpful.

The book states that it is not for beginners. I agree with that, some understanding of programming is required. But it would be interesting to see what would happen to a complete stranger to Clojure would think. I think the author is wrong. The book is both for the beginner and the intermediate Clojure programmer.
4 of 5 people found the following review helpful
5.0 out of 5 stars All set to do research & analysis 13 April 2013
By can arel - Published on
Format:Kindle Edition|Verified Purchase
A great introduction to most of the topics related to data analysis. If you are into Clojure and you need a brief yet sufficient overview of what Clojure has to offer then you should buy this book immmediatelly.

You should have some knowledge about Clojure, especially how to interact with the repl, load & create projects.

I have taken giant steps in my own projects thanks to this book. I have been too lazy to dig into all the great libraries that Clojure has to offer but now all that has changed.
Clojure is a great tool for data analysis!

Can Arel, Stockholm
1 of 1 people found the following review helpful
4.0 out of 5 stars Book delivers exactly what TOC promises. 6 May 2013
By J. McCrary - Published on
Format:Kindle Edition
I spent the last week reading the Clojure Data Analysis Cookbook by Eric Rochester. As you may expect from the name, this book follows a traditional cookbook format. Each section presents a goal and then some code which achieves the goal.

The text covers a variety of data analysis topics. Some include reading data from files, machine learning, graphing, and interfacing with other analysis tools. I particularly enjoyed the section on lazily processing large data sets. I find this is an area of frustration for many and this should serve as a reference to point them towards.

The examples are fairly easy to follow. Many of the examples use `require` to alias dependent namespaces. I think this is key when presenting Clojure examples. Having to prefix calls to library functions causes them to stand out from uses of core Clojure functions. It also lets readers know from which library each function comes from. I would have liked to see all of the examples use `require` instead of `use` for pulling in dependencies because of the clarity it brings.

I do have a sort of nit-picky negative about this (in particular, the PDF I received from the Packt Publishing website) book. While the vast majority of the code examples were well formatted every once in a while one would be poorly formatted. Poorly formatted code in a book all about showing code is disappointing and interrupts the flow of reading a recipe. One example of this is found in the first step of chapter 3's "Combining agents and STM" recipe.


Would I recommend getting this book? If any section in the table of contents sounds useful to you then yes, you should buy the book. It will be a useful reference.

Would I recommend reading this book front to back? Probably not. I would recommend reading sections that interest you and skimming others.

Just like a food cookbook's purpose (usually) isn't to teach you how to cook, this book will not teach you how to write Clojure. It will help you become better at specific tasks. It is best used as a reference.
3.0 out of 5 stars Kindle formatting stinks for books. 4 Dec 2013
By Keith Rowland - Published on
Format:Kindle Edition
Again, this is a review of the kindle format of the book and not the book itself. However, the book is almost indigestible in the kindle format and that really is a show stopper for technical books with charts, tables, and graphs. I chose to buy the ebook from the publisher in PDF format in which typography can be used to create a usable and sometimes beautiful document. Oreilly provides their book in 4 different ebook formats and I can download all formats if I need to. Amazon, please start offering ebooks in PDF format in addition to the kindle format and I'll buy technical ebooks from you again.
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