[R-pkgs] Plyr 1.7

From: Hadley Wickham <hadley_at_rice.edu>
Date: Fri, 30 Dec 2011 08:30:47 -0600

# plyr

plyr is a set of tools for a common set of problems: you need to __split__ up a big data structure into homogeneous pieces, __apply__ a function to each piece and then __combine__ all the results back together. For example, you might want to:

It's already possible to do this with base R functions (like split and the apply family of functions), but plyr makes it all a bit easier with:

Considerable effort has been put into making plyr fast and memory efficient, and in many cases plyr is as fast as, or faster than, the built-in equivalents.

A detailed introduction to plyr has been published in JSS: "The Split-Apply-Combine Strategy for Data Analysis",

http://www.jstatsoft.org/v40/i01/. You can find out more at
http://had.co.nz/plyr/, or track development at
http://github.com/hadley/plyr. You can ask questions about plyr (and
data manipulation in general) on the plyr mailing list. Sign up at http://groups.google.com/group/manipulatr.
Version 1.7------------------------------------------------------------------------------
* `rbind.fill`: if a column contains both factors and characters (in different  inputs), the resulting column will be coerced to character * When there are more than 2^31 distinct combinations `id`, switches to a  slower fallback strategy using strings (inspired by `merge`) that guarantees  correct results. This fixes problems with `join` when joining across many  columns. (Fixes #63) * `split_indices` checks input more aggressively to prevent segfaults.    Fixes #43.
* fix small bug in `loop_apply` which lead to segfaults in certain circumstances. (Thanks to Pål Westermark for patch) * `itertools` and `iterators` moved to suggests from imports so that plyr now  only depends on base R.
Assistant Professor / Dobelman Family Junior Chair
Department of Statistics / Rice University

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Received on Sat 31 Dec 2011 - 01:33:37 EST

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