Book Image

Clojure for Data Science

By : Garner
Book Image

Clojure for Data Science

By: Garner

Overview of this book

The term “data science” has been widely used to define this new profession that is expected to interpret vast datasets and translate them to improved decision-making and performance. Clojure is a powerful language that combines the interactivity of a scripting language with the speed of a compiled language. Together with its rich ecosystem of native libraries and an extremely simple and consistent functional approach to data manipulation, which maps closely to mathematical formula, it is an ideal, practical, and flexible language to meet a data scientist’s diverse needs. Taking you on a journey from simple summary statistics to sophisticated machine learning algorithms, this book shows how the Clojure programming language can be used to derive insights from data. Data scientists often forge a novel path, and you’ll see how to make use of Clojure’s Java interoperability capabilities to access libraries such as Mahout and Mllib for which Clojure wrappers don’t yet exist. Even seasoned Clojure developers will develop a deeper appreciation for their language’s flexibility! You’ll learn how to apply statistical thinking to your own data and use Clojure to explore, analyze, and visualize it in a technically and statistically robust way. You can also use Incanter for local data processing and ClojureScript to present interactive visualisations and understand how distributed platforms such as Hadoop sand Spark’s MapReduce and GraphX’s BSP solve the challenges of data analysis at scale, and how to explain algorithms using those programming models. Above all, by following the explanations in this book, you’ll learn not just how to be effective using the current state-of-the-art methods in data science, but why such methods work so that you can continue to be productive as the field evolves into the future.
Table of Contents (12 chapters)
11
Index

Conventions

In this book, you will find a number of text styles that distinguish between different kinds of information. Here are some examples of these styles and an explanation of their meaning.

Code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles are shown as follows: "Each example is a function in the cljds.ch1.examples namespace that can be run."

A block of code is set as follows:

(defmulti load-data identity)

(defmethod load-data :uk [_]
  (-> (io/resource "UK2010.xls")
      (str)
      (xls/read-xls)))

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

    (q/fill (fill-fn x y))
    (q/rect x-pos y-pos x-scale y-scale))
    (q/save "heatmap.png"))]
    (q/sketch :setup setup :size size))

Any command-line input or output is written as follows:

lein run –e 1.1

New terms and important words are shown in bold. Words that you see on the screen, for example, in menus or dialog boxes, appear in the text like this: "Each time the New Sample button is pressed, a pair of new samples from an exponential distribution with population means taken from the sliders are generated."

Note

Warnings or important notes appear in a box like this.

Tip

Tips and tricks appear like this.