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...
Main Authors: | , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Foundation for Open Access Statistics
2012-10-01
|
Series: | Journal of Statistical Software |
Subjects: | |
Online Access: | http://www.jstatsoft.org/v51/i02/paper |
id |
doaj-1157cacb0cbf41b39d4ab0d4d35ba45c |
---|---|
record_format |
Article |
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 |
work_keys_str_mv |
AT ilhamivisne speedranrpackageforinteractivedataimportfilteringandreadytousecodegeneration AT ahmetyildez speedranrpackageforinteractivedataimportfilteringandreadytousecodegeneration AT erkandilaveroglu speedranrpackageforinteractivedataimportfilteringandreadytousecodegeneration AT klemensvierlinger speedranrpackageforinteractivedataimportfilteringandreadytousecodegeneration AT christanohammer speedranrpackageforinteractivedataimportfilteringandreadytousecodegeneration AT friedrichleisch speedranrpackageforinteractivedataimportfilteringandreadytousecodegeneration AT albertkriegner speedranrpackageforinteractivedataimportfilteringandreadytousecodegeneration |
_version_ |
1725563656491499520 |