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Version 1.3 (2010-12-28)
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NEW FEATURES
* new function `mutate` that works like transform to add new columns or
overwrite existing columns, but computes new columns iteratively so later
transformations can use columns created by earlier transformations. (It's
also about 10x faster) (Fixes #21)
BUG FIXES
* split column names are no longer coerced to valid R names.
* `quickdf` now adds names if missing
* `summarise` preserves variable names if explicit names not provided (Fixes
#17)
* `arrays` with names should be sorted correctly once again (also fixed a bug
in the test case that prevented me from catching this automatically)
* `m_ply` no longer possesses .parallel argument (mistakenly added)
* `ldply` (and hence `adply` and `ddply`) now correctly passes on .parallel
argument (Fixes #16)
* `id` uses a better strategy for converting to integers, making it possible
to use for cases with larger potential numbers of combinations
Version 1.2.1 (2010-09-10)
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* Fix bug in llply fast path that causes problems with ggplot2.
Version 1.2 (2010-09-09)
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NEW FEATURES
* l*ply, d*ply, a*ply and m*ply all gain a .parallel argument that when TRUE,
applies functions in parallel using a parallel backend registered with the
foreach package:
x <- seq_len(20)
wait <- function(i) Sys.sleep(0.1)
system.time(llply(x, wait))
# user system elapsed
# 0.007 0.005 2.005
library(doMC)
registerDoMC(2)
system.time(llply(x, wait, .parallel = TRUE))
# user system elapsed
# 0.020 0.011 1.038
This work has been generously supported by BD (Becton Dickinson).
MINOR CHANGES
* a*ply and m*ply gain an .expand argument that controls whether data frames
produce a single output dimension (one element for each row), or an output
dimension for each variable.
* new vaggregate (vector aggregate) function, which is equivalent to tapply,
but much faster (~ 10x), since it avoids copying the data.
* llply: for simple lists and vectors, with no progress bar, no extra info,
and no parallelisation, llply calls lapply directly to avoid all the
overhead associated with those unused extra features.
* llply: in serial case, for loop replaced with custom C function that takes
about 40% less time (or about 20% less time than lapply). Note that as a
whole, llply still has much more overhead than lapply.
* round_any now lives in plyr instead of reshape
BUG FIXES
* list_to_array works correct even when there are missing values in the array.
This is particularly important for daply.
Version 1.1 (2010-07-19)
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* *dply deals more gracefully with the case when all results are NULL
(fixes #10)
* *aply correctly orders output regardless of dimension names
(fixes #11)
* join gains type = "full" which preserves all x and y rows
Version 1.0 (2010-07-02)
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New functions:
* arrange, a new helper method for reordering a data frame.
* count, a version of table that returns data frames immediately and that is
much much faster for high-dimensional data.
* desc makes it easy to sort any vector in descending order
* join, works like merge but can be much faster and has a somewhat simpler
syntax drawing from SQL terminology
* rbind.fill.matrix is like rbind.fill but works for matrices, code
contributed by C. Beleites
Speed improvements
* experimental immutable data frame (idata.frame) that vastly speeds up
subsetting - for large datasets with large numbers of groups, this can yield
10-fold speed ups. See examples in ?idata.frame to see how to use it.
* rbind.fill rewritten again to increase speed and work with more data types
* d*ply now much faster with nested groups
This work has been generously supported by BD (Becton Dickinson).
New features:
* d*ply now accepts NULL for splitting variables, indicating that the data
should not be split
* plyr no longer exports internal functions, many of which were causing
clashes with other packages
* rbind.fill now works with data frame columns that are lists or matrices
* test suite ensures that plyr behaviour is correct and will remain correct
as I make future improvements.
Bug fixes:
* **ply: if zero splits, empty list(), data.frame() or logical() returned,
as appropriate for the output type
* **ply: leaving .fun as NULL now always returns list
(thanks to Stavros Macrakis for the bug report)
* a*ply: labels now respect options(stringAsFactors)
* each: scoping bug fixed, thanks to Yasuhisa Yoshida for the bug report
* list_to_dataframe is more consistent when processing a single data frame
* NAs preserved in more places
* progress bars: guaranteed to terminate even if **ply prematurely terminates
* progress bars: misspelling gives informative warning, instead of
uninformative error
* splitter_d: fixed ordering bug when .drop = FALSE
Version 0.1.9 (2009-06-23)
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* fix bug in rbind.fill when NULLs present in list
* improve each to recognise when all elements are numeric
* fix labelling bug in d*ply when .drop = FALSE
* additional methods for quoted objects
* add summarise helper - this function is like transform, but creates a new data frame rather than reusing the old (thanks to Brendan O'Connor for the neat idea)
Version 0.1.8 (2009-04-20)
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* made rbind a little faster (~20%) using an idea from Richard Raubertas
* daply now works correctly when splitting variables that contain empty factor levels
Version 0.1.7 (2009-04-15)
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* Version that rbind.fill copies attributes.
Version 0.1.6 (2009-04-15)
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Improvements:
* all ply functions deal more elegantly when given function names: can supply a vector of function names, and name is used as label in output
* failwith and each now work with function names as well as functions (i.e. "nrow" instead of nrow)
* each now accepts a list of functions or a vector of function names
* l*ply will use list names where present
* if .inform is TRUE, error messages will give you information about where errors within your data - hopefully this will make problems easier to track down
* d*ply no longer converts splitting variables to factors when drop = T (thanks to bug report from Charlotte Wickham)
Speed-ups
* massive speed ups for splitting large arrays
* fixed typo that was causing a 50% speed penalty for d*ply
* rewritten rbind.fill is considerably (> 4x) faster for many data frames
* colwise about twice as fast
Bug fixes:
* daply: now works when the data frame is split by multiple variables
* aaply: now works with vectors
* ddply: first variable now varies slowest as you'd expect
Version 0.1.5 (2009-02-23)
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* colwise now accepts a quoted list as its second argument. This allows you to specify the names of columns to work on: colwise(mean, .(lat, long))
* d_ply and a_ply now correctly pass ... to the function
Version 0.1.4 (2008-12-12)
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* Greatly improved speed (> 10x faster) and memory usage (50%) for splitting data frames with many combinations
* Splitting variables containing missing values now handled consistently
Version 0.1.3 (2008-11-19)
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* Fixed problem where when splitting by a variable that contained missing values, missing combinations would be drop, and labels wouldn't match up
Version 0.1.2 (2008-11-18)
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* a*ply now works correctly with array-lists
* drop. -> .drop
* r*ply now works with ...
* use inherits instead of is so method package doesn't need to be loaded
* fix bug with using formulas
Version 0.1.1 (2008-10-08)
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* argument names now start with . (instead of ending with it) - this should prevent name clashes with arguments of the called function
* return informative error if .fun is not a function
* use full names in all internal calls to avoid argument name clashes
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