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Product typeBook
Published inSep 2015
Reading LevelIntermediate
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ISBN-139781784397180
Edition1st Edition
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Henry Garner
Henry Garner
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Henry Garner

Henry Garner is a graduate from the University of Oxford and an experienced developer, CTO, and coach. He started his technical career at Britain's largest telecoms provider, BT, working with a traditional data warehouse infrastructure. As a part of a small team for 3 years, he built sophisticated data models to derive insight from raw data and use web applications to present the results. These applications were used internally by senior executives and operatives to track both business and systems performance. He then went on to co-found Likely, a social media analytics start-up. As the CTO, he set the technical direction, leading to the introduction of an event-based append-only data pipeline modeled after the Lambda architecture. He adopted Clojure in 2011 and led a hybrid team of programmers and data scientists, building content recommendation engines based on collaborative filtering and clustering techniques. He developed a syllabus and copresented a series of evening classes from Likely's offices for professional developers who wanted to learn Clojure. Henry now works with growing businesses, consulting in both a development and technical leadership capacity. He presents regularly at seminars and Clojure meetups in and around London.
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Whole-graph analysis


Let's turn our attention away from the smaller graphs we've been working with towards the larger graph of followers provided by the twitter_combined.txt file. This contains over 2.4 million edges and will provide a more interesting sample to work with.

One of the simplest metrics to determine about a whole graph is its density. For directed graphs, this is defined as the number of edges |E|, over the number of vertices |V| multiplied by one less than itself.

For a connected graph (one where every vertex is connected to every other vertex by an edge), the density would be 1. By contrast, a disconnected graph (one with no edges) would have a density of 0. Loom implements graph density as the alg/density function. Let's calculate the density of the larger Twitter graph:

(defn ex-8-17 []
  (->> (load-edges "twitter_combined.txt")
       (apply loom/digraph)
       (alg/density)
       (double)))

;; 2.675E-4

This seems very sparse, but bear in mind that a value of 1 would...

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Clojure for Data Science
Published in: Sep 2015Publisher: ISBN-13: 9781784397180

Author (1)

author image
Henry Garner

Henry Garner is a graduate from the University of Oxford and an experienced developer, CTO, and coach. He started his technical career at Britain's largest telecoms provider, BT, working with a traditional data warehouse infrastructure. As a part of a small team for 3 years, he built sophisticated data models to derive insight from raw data and use web applications to present the results. These applications were used internally by senior executives and operatives to track both business and systems performance. He then went on to co-found Likely, a social media analytics start-up. As the CTO, he set the technical direction, leading to the introduction of an event-based append-only data pipeline modeled after the Lambda architecture. He adopted Clojure in 2011 and led a hybrid team of programmers and data scientists, building content recommendation engines based on collaborative filtering and clustering techniques. He developed a syllabus and copresented a series of evening classes from Likely's offices for professional developers who wanted to learn Clojure. Henry now works with growing businesses, consulting in both a development and technical leadership capacity. He presents regularly at seminars and Clojure meetups in and around London.
Read more about Henry Garner