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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 frequency table using Data.List


A frequency map of values is often useful to detect outliers. We can use it to identify frequencies that seem out of the ordinary. In this recipe, we will be counting the number of different colors in a list.

How to do it...

Create a new file, which we will call Main.hs, and perform the following steps:

  1. We will use the group and sort functions from Data.List:

    import Data.List (group, sort)
  2. Define a simple data type for colors:

    data Color = Red | Green | Blue deriving (Show, Ord, Eq)
  3. Create a list of these colors:

    main :: IO ()
    main = do
      let items = [Red, Green, Green, Blue, Red, Green, Green]
  4. Implement the frequency map and print it out:

      let freq = 
         map (\x -> (head x, length x)) . group . sort $ items
      print freq

How it works...

Grouping identical items after sorting the list is the central idea.

See the following step-by-step evaluation in ghci:

Prelude> sort items

[Red,Red,Green,Green,Green,Green,Blue]
Prelude> group it

[[Red,Red...
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