| Record ID | ia:clojuredataanaly0000roch |
| Source | Internet Archive |
| Download MARC XML | https://archive.org/download/clojuredataanaly0000roch/clojuredataanaly0000roch_marc.xml |
| Download MARC binary | https://www.archive.org/download/clojuredataanaly0000roch/clojuredataanaly0000roch_meta.mrc |
LEADER: 06790cam 2200853Ii 4500
001 ocn903511543
003 OCoLC
005 20210912213131.0
008 150216s2015 enka o 001 0 eng d
006 m o d
007 cr cnu---unuuu
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019 $a902957606
020 $a9781784399955$q(electronic bk.)
020 $a1784399957$q(electronic bk.)
020 $z1784399957
020 $z1784390291
020 $z9781784390297
035 $a(OCoLC)903511543$z(OCoLC)902957606
050 4 $aQA76.73.J38
072 7 $aCOM$x051400$2bisacsh
082 04 $a005.2762$223
100 1 $aRochester, Eric,$eauthor.
245 10 $aClojure data analysis cookbook :$bdive into data analysis with Clojure through over 100 practical recipes for every stage of the analysis and collection process /$cEric Rochester.
250 $aSecond edition.
264 1 $aBirmingham, UK :$bPackt Publishing,$c2015.
300 $a1 online resource (1 volume) :$billustrations
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
588 0 $aOnline resource; title from cover (Safari, viewed February 10, 2015).
500 $a"Quick answers to common problems."
500 $aIncludes index.
505 0 $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; Querying RDF data with SPARQL; Aggregating data from different formats; Chapter 2: Cleaning and Validating Data.
505 8 $aIntroductionCleaning data with regular expressions; Maintaining consistency with synonym maps; Identifying and removing duplicate data; Regularizing numbers; Calculating relative values; Parsing 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.
505 8 $aMaintaining consistency with ensureIntroducing safe side effects into the STM; Maintaining data consistency with validators; Monitoring processing with watchers; Debugging concurrent programs with watchers; Recovering from errors in agents; Managing large inputs 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; Combining function calls with reducers.
505 8 $aParallelizing with reducersGenerating online summary statistics for data streams with reducers; Using type hints; Benchmarking with Criterium; Chapter 5: Distributed Data Processing with Cascalog; Introduction; Initializing Cascalog and Hadoop for distributed processing; Querying data with Cascalog; Distributing data with Apache HDFS; Parsing CSV files with Cascalog; Executing complex queries with Cascalog; Aggregating data with Cascalog; Defining new Cascalog operators; Composing Cascalog queries; Transforming data with Cascalog; Chapter 6: Working with Incanter Datasets; Introduction.
505 8 $aLoading Incanter's sample datasetsLoading 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: Statistical Data Analysis with Incanter; Introduction; Generating summary statistics with rollup; Working with changes in values; Scaling variables to simplify variable relationships.
520 $aThis book is for those with a basic knowledge of Clojure, who are looking to push the language to excel with data analysis.
588 0 $aPrint version record.
650 0 $aClojure (Computer program language)
650 0 $aJavaScript (Computer program language)
650 0 $aComputer programming.
650 0 $aApplication software$xDevelopment.
650 7 $aCOMPUTERS$xSoftware Development & Engineering$xGeneral.$2bisacsh
650 7 $aApplication software$xDevelopment.$2fast$0(OCoLC)fst00811707
650 7 $aClojure (Computer program language)$2fast$0(OCoLC)fst01893276
650 7 $aComputer programming.$2fast$0(OCoLC)fst00872390
650 7 $aJavaScript (Computer program language)$2fast$0(OCoLC)fst00982071
655 0 $aElectronic books.
655 4 $aElectronic books.
776 08 $iPrint version:$aRochester, Eric.$tClojure data analysis cookbook.$bSecond edition.$dBirmingham, UK : Packt Publishing, 2015$z9781784399955
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