In this chapter, we installed the sqlite3 command-line utility and installed the necessary SQLite3 libraries for working with data in the IHaskell environment. Most data doesn't come in SQLite3 format, but in CSV format. So, we covered how to convert a CSV file into an SQLite3 table. We explored the versatility of SELECT queries in SQLite3 by means of the WHERE clause, the ORDER BY clause, and the LIMIT clause. We also explored how to create our own custom module of descriptive statistics, and then we used that module in order to study earthquake data in the IHaskell environment. In our next chapter, we're going to take a look at regular expressions in Haskell.
Getting Started with Haskell Data Analysis
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Getting Started with Haskell Data Analysis
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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.
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Current Title:
Getting Started with Haskell Data Analysis
Table of Contents (8 chapters)
Preface
Free Chapter
Descriptive Statistics
SQLite3
Regular Expressions
Visualizations
Kernel Density Estimation
Course Review
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Customer Reviews