The Split-Apply-Combine Strategy for Data Analysis
H. Wickham. Journal of Statistical Software, 40 (1):
1--29(апреля 2011)
Аннотация
Many data analysis problems involve the application of a split-apply-combine strategy, where you break up a big problem into manageable pieces, operate on each piece independently and then put all the pieces back together. This insight gives rise to a new R package that allows you to smoothly apply this strategy, without having to worry about the type of structure in which your data is stored.</p> <p>The paper includes two case studies showing how these insights make it easier to work with batting records for veteran baseball players and a large 3d array of spatio-temporal ozone measurements.
%0 Journal Article
%1 citeulike:10560365
%A Wickham, Hadley
%D 2011
%J Journal of Statistical Software
%K r statistics
%N 1
%P 1--29
%T The Split-Apply-Combine Strategy for Data Analysis
%U http://www.jstatsoft.org/v40/i01
%V 40
%X Many data analysis problems involve the application of a split-apply-combine strategy, where you break up a big problem into manageable pieces, operate on each piece independently and then put all the pieces back together. This insight gives rise to a new R package that allows you to smoothly apply this strategy, without having to worry about the type of structure in which your data is stored.</p> <p>The paper includes two case studies showing how these insights make it easier to work with batting records for veteran baseball players and a large 3d array of spatio-temporal ozone measurements.
@article{citeulike:10560365,
abstract = {{Many data analysis problems involve the application of a split-apply-combine strategy, where you break up a big problem into manageable pieces, operate on each piece independently and then put all the pieces back together. This insight gives rise to a new R package that allows you to smoothly apply this strategy, without having to worry about the type of structure in which your data is stored.</p> <p>The paper includes two case studies showing how these insights make it easier to work with batting records for veteran baseball players and a large 3d array of spatio-temporal ozone measurements.}},
added-at = {2019-06-18T20:47:03.000+0200},
author = {Wickham, Hadley},
biburl = {https://www.bibsonomy.org/bibtex/23b78443226279af78c60a5677ceda249/alexv},
citeulike-article-id = {10560365},
citeulike-linkout-0 = {http://www.jstatsoft.org/v40/i01},
citeulike-linkout-1 = {http://www.jstatsoft.org/v40/i01/paper},
interhash = {3318bd38b85ae56071089788def21323},
intrahash = {3b78443226279af78c60a5677ceda249},
issn = {1548-7660},
journal = {Journal of Statistical Software},
keywords = {r statistics},
month = apr,
number = 1,
pages = {1--29},
posted-at = {2012-04-12 18:42:33},
priority = {0},
timestamp = {2019-08-23T23:54:01.000+0200},
title = {{The Split-Apply-Combine Strategy for Data Analysis}},
url = {http://www.jstatsoft.org/v40/i01},
volume = 40,
year = 2011
}