This is the code repository for Getting Started with Haskell Data Analysis, published by Packt.
Put your data analysis techniques to work and generate publication-ready visualizations
Every business and organization that collects data is capable of tapping into its own data to gain insights how to improve. Haskell is a purely functional and lazy programming language, well-suited to handling large data analysis problems. This book will take you through the more difficult problems of data analysis in a hands-on manner.
This book covers the following exciting features:
- Learn to parse a CSV file and read data into the Haskell environment
- Create Haskell functions for common descriptive statistics functions
- Create an SQLite3 database using an existing CSV file
- Learn the versatility of SELECT queries for slicing data into smaller chunks
- Apply regular expressions in large-scale datasets using both CSV and SQLite3 files
If you feel this book is for you, get your copy today!
All of the code is organized into folders. For example, Chapter02.
The code will look like the following:
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import Text.CSV"
]
},
Following is what you need for this book: This book is intended for people who wish to expand their knowledge of statistics and data analysis via real-world examples. A basic understanding of the Haskell language is expected. If you are feeling brave, you can jump right into the functional programming style.
With the following software and hardware list you can run all code files present in the book (Chapter 1-6).
| Chapter | Software required | OS required |
|---|---|---|
| 1 | Haskell | Windows, Mac OS X, and Linux (Any) |
We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.
James Church lives in Clarksville, Tennessee, United States, where he enjoys teaching, programming, and playing board games with his wife, Michelle. He is an assistant professor of computer science at Austin Peay State University. He has consulted for various companies and a chemical laboratory for the purpose of performing data analysis work. James is the author of Learning Haskell Data Analysis.
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Simply click on the link to claim your free PDF.