Book Image

Getting Started with Haskell Data Analysis

By : James Church
Book Image

Getting Started with Haskell Data Analysis

By: James Church

Overview of this book

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 will help you get up-to-speed with the basics of data analysis and approaches in the Haskell language. You'll learn about statistical computing, file formats (CSV and SQLite3), descriptive statistics, charts, and progress to more advanced concepts such as understanding the importance of normal distribution. While mathematics is a big part of data analysis, we've tried to keep this course simple and approachable so that you can apply what you learn to the real world. By the end of this book, you will have a thorough understanding of data analysis, and the different ways of analyzing data. You will have a mastery of all the tools and techniques in Haskell for effective data analysis.
Table of Contents (8 chapters)

Scatter plots

The financial data that we've used up to this point in this section is usually considered time series data. Time series data is simply sequential data that usually includes a date or a timestamp. Scatter plots don't have to be tied to sequential data. So, in this section, what we would like to do is develop an understanding of the share price of a stock, and how much that stock is traded in terms of volume. So, we're going to be comparing the stock price to the volume traded, with a relatively simple plot. You're going to see very quickly that this plot is insufficient to meet our needs of understanding the plot. So, we're going to be comparing that stock price with the log of the volume traded. So, what we would like to do in this section is to perform this analysis on Apple, Google, and Microsoft.

Let's go back to our notebook where...