【2015新书】 Learning Haskell Data Analysis

Book 图书名称： Learning Haskell Data Analysis
Author 作者： James Church
Publisher 出版社： Packt Publishing
Page 页数： 194
Publishing Date 出版时间： May 28, 2015                         
Language 语言：English
Size 大小： 2 MB
Format 格式： pdf 文字版
ISBN: 178439470X, 9781784394707
Edition: 第1版 搜索过论坛，没有该文档


Analyze, manipulate, and process datasets of varying sizes efficiently using Haskell
About This BookCreate 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 chartsAn easy-to-follow guide to analyze real-world data using the most commonly used statistical techniquesWho 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.

== Table of contents ==
n/a


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