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Clojure for Data Science

You're reading from   Clojure for Data Science Statistics, big data, and machine learning for Clojure programmers

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Product type Paperback
Published in Sep 2015
Publisher
ISBN-13 9781784397180
Length 608 pages
Edition 1st Edition
Languages
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Author (1):
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Henry Garner Henry Garner
Author Profile Icon Henry Garner
Henry Garner
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Table of Contents (12) Chapters Close

Preface 1. Statistics FREE CHAPTER 2. Inference 3. Correlation 4. Classification 5. Big Data 6. Clustering 7. Recommender Systems 8. Network Analysis 9. Time Series 10. Visualization Index

Visualizing the dwell times

We can plot a histogram of dwell times by simply extracting the :dwell-time column with i/$:

(defn ex-2-2 []
  (-> (i/$ :dwell-time (load-data "dwell-times.tsv"))
      (c/histogram :x-label "Dwell time (s)"
                   :nbins 50)
      (i/view)))

The earlier code generates the following histogram:

Visualizing the dwell times

This is clearly not a normally distributed data, nor even a very skewed normal distribution. There is no tail to the left of the peak (a visitor clearly can't be on our site for less than zero seconds). While the data tails off steeply to the right at first, it extends much further along the x axis than we would expect from normally distributed data.

When confronted with distributions like this, where values are mostly small but occasionally extreme, it can be useful to plot the y axis as a log scale. Log scales are used to represent events that cover a very large range. Chart axes are ordinarily linear and they partition a range into...

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