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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

Coping with unexpected or missing input


Data sources often contain incomplete and unexpected data. One common approach to parsing such data in Haskell is using the Maybe data type.

Imagine designing a function to find the nth element in a list of characters. A naïve implementation may have the type Int -> [Char] -> Char. However, if the function is trying to access an index out of bounds, we should try to indicate that an error has occurred.

A common way to deal with these errors is by encapsulating the output Char into a Maybe context. Having the type Int -> [Char] -> Maybe Char allows for some better error handling. The constructors for Maybe are Just a or Nothing, which will become apparent by running GHCi and testing out the following commands:

$ ghci

Prelude> :type Just 'c'
Just 'c' :: Maybe Char

Prelude> :type Nothing
Nothing :: Maybe a

We will set each field as a Maybe data type so that whenever a field cannot be parsed, it will simply be represented as Nothing....

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