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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 conflicting data items


Unfortunately, information about an item may be inconsistent throughout the corpus. Collision strategies are often domain-dependent, but one common way to manage this conflict is by simply storing all variations of the data. In this recipe, we will read a CSV file that contains information about musical artists and store all of the information about their songs and genres in a set.

Getting ready

Create a CSV input file with the following musical artists. The first column is for the name of the artist or band. The second column is the song name, and the third is the genre. Notice how some musicians have multiple songs or genres.

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 Set packages:

    import Text.CSV (parseCSV, Record)
    import Data.Map (fromListWith)
    import qualified Data.Set as S
  2. Define the Artist data type corresponding to the CSV input. For fields that may contain conflicting...

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