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Clojure data analysis cookbook- [electronic resource] : over 110 recipes to help you dive into the world of practical data analysis using Clojure
Clojure data analysis cookbook- [electronic resource] : over 110 recipes to help you dive into the world of practical data analysis using Clojure
상세정보
- 자료유형
- 단행본
- International Standard Book Number
- 9781782162650 (electronic bk.)
- International Standard Book Number
- 1782162658 (electronic bk.)
- International Standard Book Number
- 178216264X
- International Standard Book Number
- 9781782162643
- Library of Congress Call Number
- QA76.73.J38
- Dewey Decimal Classification Number
- 005.133-23
- Main Entry-Personal Name
- Rochester, Eric.
- Publication, Distribution, etc. (Imprint
- Birmingham, UK : Packt Publishing, c2013
- Physical Description
- 1 online resource : ill.
- General Note
- Includes index.
- Formatted Contents Note
- 완전내용Cover; 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
- Formatted Contents Note
- 완전내용IntroductionCleaning 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
- Formatted Contents Note
- 완전내용Maintaining 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
- Formatted Contents Note
- 완전내용Generating 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
- Formatted Contents Note
- 완전내용Executing 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
- Summary, Etc.
- 요약Full 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.
- Subject Added Entry-Topical Term
- Clojure (Computer program language)
- Subject Added Entry-Topical Term
- JavaScript (Computer program language)
- Subject Added Entry-Topical Term
- Computer programming
- Subject Added Entry-Topical Term
- Application software Development
- Subject Added Entry-Topical Term
- COMPUTERS / Programming Languages / C#.
- Subject Added Entry-Topical Term
- COMPUTERS / Programming Languages / Java.
- Subject Added Entry-Topical Term
- COMPUTERS / Programming Languages / Pascal.
- Additional Physical Form Entry
- . Original. 178216264X. 9781782162643. (OCoLC)834978161
- Electronic Location and Access
- 로그인을 한후 보실 수 있는 자료입니다.
- Control Number
- joongbu:423056
MARC
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■500 ▼aIncludes index.
■5050 ▼aCover; 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
■5058 ▼aIntroductionCleaning 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
■5058 ▼aMaintaining 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
■5058 ▼aGenerating 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
■5058 ▼aExecuting 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
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■588 ▼aTitle from PDF title page (viewed Apr. 26, 2013)
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