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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
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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

Implementing a Foldable instance for a tree


The idea of traversing a tree can be generalized by implementing a Foldable instance. Usually, folds are used on lists; for example, foldr1 (+) [1..10] traverses a list of numbers to produce a grand sum. Similarly, we can apply foldr1 (+) tree to find the sum of all nodes in a tree.

Getting ready

We will be folding through the following tree to obtain a sum of all node values.

How to do it...

  1. Import the following built-in packages:

    import Data.Monoid (mempty, mappend)
    import qualified Data.Foldable as F
    import Data.Foldable (Foldable, foldMap)
  2. The tree from Data.Tree already implements Foldable, so we will define our own tree data type for demonstration purposes:

    data Tree a = Node { value :: a
                       , children :: [Tree a] }
                       deriving Show
  3. Implement the foldMap function for the Foldable instance. This implementation will give us a post-order traversal of the tree:

    instance Foldable Tree where
      foldMap f Null = mempty
      foldMap...
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