자료유형 | E-Book |
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개인저자 | Rochester, Eric. |
서명/저자사항 | Clojure data analysis cookbook[electronic resource] :over 110 recipes to help you dive into the world of practical data analysis using Clojure /Eric Rochester. |
발행사항 | Birmingham, UK : Packt Publishing, c2013. |
형태사항 | 1 online resource : ill. |
ISBN | 9781782162650 (electronic bk.) 1782162658 (electronic bk.) |
일반주기 |
Includes index.
|
내용주기 | Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Importing Data for Analysis; Introduction; Creating a new project; Reading CSV data into Incanter datasets; Reading JSON data into Incanter datasets; Reading data from Excel with Incanter; Reading data from JDBC databases; Reading XML data into Incanter datasets; Scraping data from tables in web pages; Scraping textual data from web pages; Reading RDF data; Reading RDF data with SPARQL; Aggregating data from different formats; Chapter 2: Cleaning and Validating Data IntroductionCleaning data with regular expressions; Maintaining consistency with synonym maps; Identifying and removing duplicate data; Normalizing numbers; Rescaling values; Normalizing dates and times; Lazily processing very large data sets; Sampling from very large data sets; Fixing spelling errors; Parsing custom data formats; Validating data with Valip; Chapter 3: Managing Complexity with Concurrent Programming; Introduction; Managing program complexity with STM; Managing program complexity with agents; Getting better performance with commute; Combining agents and STM Maintaining consistency with ensureIntroducing safe side effects into the STM; Maintaining data consistency with validators; Tracking processing with watchers; Debugging concurrent programs with watchers; Recovering from errors in agents; Managing input with sized queues; Chapter 4: Improving Performance with Parallel Programming; Introduction; Parallelizing processing with pmap; Parallelizing processing with Incanter; Partitioning Monte Carlo simulations for better pmap performance; Finding the optimal partition size with simulated annealing; Parallelizing with reducers Generating online summary statistics with reducersHarnessing your GPU with OpenCL and Calx; Using type hints; Benchmarking with Criterium; Chapter 5: Distributed Data Processing with Cascalog; Introduction; Distributed processing with Cascalog and Hadoop; Querying data with Cascalog; Distributing data with Apache HDFS; Parsing CSV files with Cascalog; Complex queries with Cascalog; Aggregating data with Cascalog; Defining new Cascalog operators; Composing Cascalog queries; Handling errors in Cascalog workflows; Transforming data with Cascalog Executing Cascalog queries in the Cloud with PalletChapter 6: Working with Incanter Datasets; Introduction; Loading Incanter's sample datasets; Loading Clojure data structures into datasets; Viewing datasets interactively with view; Converting datasets to matrices; Using infix formulas in Incanter; Selecting columns with ; Selecting rows with ; Filtering datasets with where; Grouping data with group-by; Saving datasets to CSV and JSON; Projecting from multiple datasets with join; Chapter 7: Preparing for and Performing Statistical Data Analysis with Incanter; Introduction |
요약 | Full of practical tips, the ""Clojure Data Analysis Cookbook"" will help you fully utilize your data through a series of step-by-step, real world recipes covering every aspect of data analysis.Prior experience with Clojure and data analysis techniques and workflows will be beneficial, but not essential. |
일반주제명 | Clojure (Computer program language) JavaScript (Computer program language) Computer programming. Application software -- Development. COMPUTERS / Programming Languages / C#. COMPUTERS / Programming Languages / Java. COMPUTERS / Programming Languages / Pascal. |
언어 | 영어 |
기타형태 저록 | Original178216264X9781782162643 |
대출바로가기 | http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=562004 |
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