Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Clojure Data Analysis Cookbook - Second Edition

You're reading from   Clojure Data Analysis Cookbook - Second Edition Dive into data analysis with Clojure through over 100 practical recipes for every stage of the analysis and collection process

Arrow left icon
Product type Paperback
Published in Jan 2015
Publisher
ISBN-13 9781784390297
Length 372 pages
Edition 2nd Edition
Languages
Arrow right icon
Author (1):
Arrow left icon
Eric Richard Rochester Eric Richard Rochester
Author Profile Icon Eric Richard Rochester
Eric Richard Rochester
Arrow right icon
View More author details
Toc

Table of Contents (14) Chapters Close

Preface 1. Importing Data for Analysis FREE CHAPTER 2. Cleaning and Validating Data 3. Managing Complexity with Concurrent Programming 4. Improving Performance with Parallel Programming 5. Distributed Data Processing with Cascalog 6. Working with Incanter Datasets 7. Statistical Data Analysis with Incanter 8. Working with Mathematica and R 9. Clustering, Classifying, and Working with Weka 10. Working with Unstructured and Textual Data 11. Graphing in Incanter 12. Creating Charts for the Web Index

Maintaining data consistency with validators


Clojure has a number of tools to work with agents. One of them is validators. When an agent's message function returns a value, any validator functions assigned to that agent receive the agent's data before it does. If the validators return true, all is well. The agent is updated and processing continues. However, if any validator returns false or raises an error, an error is raised on the agent.

This can be a handy tool to make sure that the data assigned to your agent conforms to your expectations, and it can be an important check on the consistency and validity of your data.

For this recipe, we'll read data from a CSV file and convert the values in some of the columns to integers. We'll use a validator to ensure that this actually happens.

Getting ready

For this recipe, we'll use the dependencies and requirements that we did from the Managing program complexity with STM recipe. We'll also use the lazy-read-csv and with-header functions from that...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime