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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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Toc

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

Inspecting the data


The first task when confronted with a new dataset is to study it to ensure that we understand what it contains.

The all-london-2012-athletes.xlsx file is small enough that it's been provided with the sample code for this chapter. We can inspect the data with Incanter, as we did in Chapter 1, Statistics using the incanter.excel/read-xls and incanter.core/view functions:

(ns cljds.ch3.examples
  (:require [incanter.charts :as c]
            [incanter.core :as i]
            [incanter.excel :as xls]
            [incanter.stats :as s]))

(defn athlete-data []
  (-> (io/resource "all-london-2012-athletes.xlsx")
      (str)
      (xls/read-xls)))

(defn ex-3-1 []
  (i/view (athlete-data)))

If you run this code (either in the REPL or on the command line with lein run –e 3.1), you should see the following output:

We're fortunate that the data is clearly labeled in the columns and contains the following information:

  • Name of the athlete

  • Country for which they are competing

  • Age in years...

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