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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

Deduplication of nonconflicting data items


Duplication is a common problem when collecting large amounts of data. In this recipe, we will combine similar records in a way that ensures no information is lost.

Getting ready

Create an input.csv file with repeated data:

How to do it...

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

  1. We will be using the CSV, Map, and Maybe packages:

    import Text.CSV (parseCSV, Record)
    import Data.Map (fromListWith)
    import Control.Applicative ((<|>))
  2. Define the Item data type corresponding to the CSV input:

    data Item = Item   { name :: String
                       , color :: Maybe String
                       , cost :: Maybe Float
                       } deriving Show
  3. Get each record from CSV and put them in a map by calling our doWork function:

    main :: IO ()
    main = do
      let fileName = "input.csv"
      input <- readFile fileName
      let csv = parseCSV fileName input
      either handleError doWork csv
  4. If we're unable to parse CSV, print an error message...

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