Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases now! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
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

Arrow left icon
Product type Paperback
Published in Jun 2014
Publisher
ISBN-13 9781783286331
Length 334 pages
Edition 1st Edition
Languages
Arrow right icon
Author (1):
Arrow left icon
Nishant Shukla Nishant Shukla
Author Profile Icon Nishant Shukla
Nishant Shukla
Arrow right icon
View More author details
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

Exporting data to a CSV file

Sometimes, it's more convenient to view data using a spreadsheet program such as LibreOffice, Microsoft Office Excel, or Apple Numbers. A standard way to export and import simple spreadsheet tables is through Comma Separated Values (CSVs).

In this recipe, we will use the cassava package to easily encode a CSV file out of a data structure.

Getting ready

Install the Cassava CSV package from cabal, using the following command line:

$ cabal install cassava

How to do it…

  1. Import the relevant packages using the following code:
    import Data.Csv
    import qualified Data.ByteString.Lazy as BSL
  2. Define an association list of data that will be exported as CSV. For this recipe, we will pair letters and numbers together, as shown in the following code:
    myData :: [(Char, Int)]
    myData = zip ['A'..'Z'] [1..]
  3. Run the encode function to convert the data structure into a lazy ByteString CSV representation, as shown in the following code:
    main = BSL.writeFile &quot...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime