Book Image

Learning Haskell Data Analysis

By : James Church
Book Image

Learning Haskell Data Analysis

By: James Church

Overview of this book

<p>Haskell is trending in the field of data science by providing a powerful platform for robust data science practices. This book provides you with the skills to handle large amounts of data, even if that data is in a less than perfect state. Each chapter in the book helps to build a small library of code that will be used to solve a problem for that chapter. The book starts with creating databases out of existing datasets, cleaning that data, and interacting with databases within Haskell in order to produce charts for publications. It then moves towards more theoretical concepts that are fundamental to introductory data analysis, but in a context of a real-world problem with real-world data. As you progress in the book, you will be relying on code from previous chapters in order to help create new solutions quickly. By the end of the book, you will be able to manipulate, find, and analyze large and small sets of data using your own Haskell libraries.</p>
Table of Contents (16 chapters)
Learning Haskell Data Analysis
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Chapter 2. Getting Our Feet Wet

This chapter looks at Haskell's type system by examining where it works in your favor as well as the common obstacles that you may be face when trying to understand it. We will also work with csv files, a common format that is used to store datasets. The csv file type is cumbersome to work with. So, we will spend the remainder of this chapter in learning how to convert csv files into SQLite3 databases.

In this chapter, we will cover the following:

  • Type is king—the implications of strict types in Haskell

  • Working with csv files

  • Converting csv files to the SQLite3 format