speedR: An R Package for Interactive Data Import, Filtering and Ready-to-Use Code Generation

Emerging technologies in the experimental sciences have opened the way for large-scale experiments. Such experiments generate ever growing amounts of data from which researchers need to extract relevant pieces for subsequent analysis. R offers a great environment for statistical analysis. However, d...

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Bibliographic Details
Main Authors: Ilhami Visne, Ahmet Yildez, Erkan Dilaveroglu, Klemens Vierlinger, Christa Nöhammer, Friedrich Leisch, Albert Kriegner
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2012-10-01
Series:Journal of Statistical Software
Subjects:
GUI
R
Online Access:http://www.jstatsoft.org/v51/i02/paper
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spelling doaj-1157cacb0cbf41b39d4ab0d4d35ba45c2020-11-24T23:23:47ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602012-10-01512speedR: An R Package for Interactive Data Import, Filtering and Ready-to-Use Code GenerationIlhami VisneAhmet YildezErkan DilaverogluKlemens VierlingerChrista NöhammerFriedrich LeischAlbert KriegnerEmerging technologies in the experimental sciences have opened the way for large-scale experiments. Such experiments generate ever growing amounts of data from which researchers need to extract relevant pieces for subsequent analysis. R offers a great environment for statistical analysis. However, due to the diversity of possible data sources and formats, data preprocessing and import can be time consuming especially with data that require user interaction such as editing, filtering or formatting. Writing a code for these tasks can be time-consuming, error prone and rather complex. We present speedR, an R-package for interactive data import, filtering and code generation in order to address these needs. Using speedR, researchers can import new data, make basic corrections, examine current R session objects, open them in the speedR environment for filtering (subsetting), put the filtered data back into R, and even create new R functions with applied import and filtering constraints to speed up their productivity.http://www.jstatsoft.org/v51/i02/paperlterimportinteractiveGUIRJavascript
collection DOAJ
language English
format Article
sources DOAJ
author Ilhami Visne
Ahmet Yildez
Erkan Dilaveroglu
Klemens Vierlinger
Christa Nöhammer
Friedrich Leisch
Albert Kriegner
spellingShingle Ilhami Visne
Ahmet Yildez
Erkan Dilaveroglu
Klemens Vierlinger
Christa Nöhammer
Friedrich Leisch
Albert Kriegner
speedR: An R Package for Interactive Data Import, Filtering and Ready-to-Use Code Generation
Journal of Statistical Software
lter
import
interactive
GUI
R
Java
script
author_facet Ilhami Visne
Ahmet Yildez
Erkan Dilaveroglu
Klemens Vierlinger
Christa Nöhammer
Friedrich Leisch
Albert Kriegner
author_sort Ilhami Visne
title speedR: An R Package for Interactive Data Import, Filtering and Ready-to-Use Code Generation
title_short speedR: An R Package for Interactive Data Import, Filtering and Ready-to-Use Code Generation
title_full speedR: An R Package for Interactive Data Import, Filtering and Ready-to-Use Code Generation
title_fullStr speedR: An R Package for Interactive Data Import, Filtering and Ready-to-Use Code Generation
title_full_unstemmed speedR: An R Package for Interactive Data Import, Filtering and Ready-to-Use Code Generation
title_sort speedr: an r package for interactive data import, filtering and ready-to-use code generation
publisher Foundation for Open Access Statistics
series Journal of Statistical Software
issn 1548-7660
publishDate 2012-10-01
description Emerging technologies in the experimental sciences have opened the way for large-scale experiments. Such experiments generate ever growing amounts of data from which researchers need to extract relevant pieces for subsequent analysis. R offers a great environment for statistical analysis. However, due to the diversity of possible data sources and formats, data preprocessing and import can be time consuming especially with data that require user interaction such as editing, filtering or formatting. Writing a code for these tasks can be time-consuming, error prone and rather complex. We present speedR, an R-package for interactive data import, filtering and code generation in order to address these needs. Using speedR, researchers can import new data, make basic corrections, examine current R session objects, open them in the speedR environment for filtering (subsetting), put the filtered data back into R, and even create new R functions with applied import and filtering constraints to speed up their productivity.
topic lter
import
interactive
GUI
R
Java
script
url http://www.jstatsoft.org/v51/i02/paper
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AT klemensvierlinger speedranrpackageforinteractivedataimportfilteringandreadytousecodegeneration
AT christanohammer speedranrpackageforinteractivedataimportfilteringandreadytousecodegeneration
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