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Haskell Data Analysis cookbook

You're reading from   Haskell Data Analysis cookbook Explore intuitive data analysis techniques and powerful machine learning methods using over 130 practical recipes

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Product type Paperback
Published in Jun 2014
Publisher
ISBN-13 9781783286331
Length 334 pages
Edition 1st Edition
Languages
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Author (1):
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Nishant Shukla Nishant Shukla
Author Profile Icon Nishant Shukla
Nishant Shukla
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Toc

Table of Contents (14) Chapters Close

Preface 1. The Hunt for Data FREE CHAPTER 2. Integrity and Inspection 3. The Science of Words 4. Data Hashing 5. The Dance with Trees 6. Graph Fundamentals 7. Statistics and Analysis 8. Clustering and Classification 9. Parallel and Concurrent Design 10. Real-time Data 11. Visualizing Data 12. Exporting and Presenting Index

Exporting data as JSON

A convenient way to store data that may not adhere to a strict schema is through JSON. To accomplish this, we will use a painless JSON library called Yocto. It sacrifices performance for readability and small size.

In this recipe, we will export a list of points as JSON.

Getting ready

Install the Yocto JSON encoder and decoder from cabal using the following command:

$ cabal install yocto

How to do it…

Start by creating a new file, which we call Main.hs and perform the following steps:

  1. Import the relevant data structures, as shown in the following code:
    import Text.JSON.Yocto
    import qualified Data.Map as M
  2. Define a data structure for 2D points:
    data Point = Point Rational Rational
  3. Convert a Point data type into a JSON object, as shown in the following code:
    pointObject (Point x y) = 
      Object $ M.fromList [ ("x", Number x)
                          , ("y", Number y)]
  4. Create the points and construct a JSON array out of them:
    main = do
      let points = [ Point...
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