Learning Haskell Data Analysis

Analyze, manipulate, and process datasets of varying sizes efficiently using Haskell

About This Book

• Create portable databases using SQLite3 and use these databases to quickly pull large amounts of data into your Haskell programs.
• Visualize data using EasyPlot and create publication-ready charts
• An easy-to-follow guide to analyze real-world data using the most commonly used statistical techniques

Who This Book Is For

If you are a developer, analyst, or data scientist who wants to learn data analysis methods using Haskell and its libraries, then this book is for you. Prior experience with Haskell and a basic knowledge of data science will be beneficial.

What You Will Learn

• Learn the essential tools of Haskell needed to handle large data
• Migrate your data to a database and learn to interact with your data quickly
• Clean data with the power of Regular Expressions
• Plot data with the Gnuplot tool and the EasyPlot library
• Formulate a hypothesis test to evaluate the significance of your data
• Evaluate the variance between columns of data using a correlation statistic and perform regression analysis

In Detail

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.

使用Haskell高效地分析、操作和處理不同大小的數據集

關於本書
- 使用SQLite3創建可移植的數據庫，並使用這些數據庫快速提取大量數據到Haskell程序中
- 使用EasyPlot可視化數據並創建出版準備的圖表
- 透過最常用的統計技術，提供易於理解的指南，以分析現實世界的數據

本書適合對Haskell和基本的數據科學有一定了解的開發人員、分析師和數據科學家。

你將學到什麼
- 學習處理大數據所需的Haskell基本工具
- 將數據遷移到數據庫並學習快速與數據交互
- 使用正則表達式清理數據
- 使用Gnuplot工具和EasyPlot庫繪製數據
- 制定假設檢驗以評估數據的重要性
- 使用相關統計量評估數據列之間的變異性並進行回歸分析

詳細內容
Haskell在提供強大的數據科學平台方面正成為趨勢。本書將教授你處理大量數據的技能，即使數據處於不完美的狀態下也能應對。每一章節都將構建一個小型的代碼庫，用於解決該章節的問題。本書首先介紹如何從現有數據集創建數據庫，清理數據，並在Haskell中與數據庫進行交互，以便生成出版物的圖表。然後，本書將介紹一些理論概念，這些概念是入門數據分析的基礎，但是在真實世界的問題和數據背景下進行。隨著閱讀的進展，你將依賴前面章節的代碼來快速創建新的解決方案。通過本書的學習，你將能夠使用自己的Haskell庫來操作、查找和分析大型和小型數據集。