rapply2d

<code>rapply2d</code> is a recursive version of <code>lapply</code> with three differences to <code><a href="/link/rapply?package=collapse&version=1.8.9" data-mini-rdoc="collapse::rapply">rapply</a></code>:
<ol>
<li>data frames (or other list-based objects specified in <code>classes</code>) are considered as atomic, not as (sub-)lists</li>
<li><code>FUN</code> is applied to all 'atomic' objects in the nested list</li>
<li>the result is not simplified / unlisted.</li>
</ol>

manip

list

A C/C++ based package for advanced data transformation and
statistical computing in R that is extremely fast, class-agnostic,
and programmer friendly through a flexible and parsimonious syntax.
It is well integrated with base R, 'dplyr' / (grouped) 'tibble',
'data.table', 'sf', 'plm' (panel-series and data frames), and
non-destructively handles other matrix or data frame based classes (like
'ts', 'xts' / 'zoo', 'tsibble', ...)
--- Key Features: ---
(1) Advanced statistical programming: A full set of fast statistical functions
supporting grouped and weighted computations on vectors, matrices and
data frames. Fast and programmable grouping, ordering, unique values/rows,
factor generation and interactions. Fast and flexible functions for data
manipulation, data object conversions, and memory efficient R programming.
(2) Advanced aggregation: Fast and easy multi-data-type, multi-function, weighted
and parallelized data aggregation.
(3) Advanced transformations: Fast row/column arithmetic, (grouped) replacing
and sweeping out of statistics (by reference), (grouped, weighted) scaling/standardizing,
(higher-dimensional) between (averaging) and (quasi-)within (demeaning) transformations,
linear prediction, model fitting and testing exclusion restrictions.
(4) Advanced time-computations: Fast and flexible indexed time series and panel data classes.
Fast (sequences of) lags/leads, and  (lagged/leaded, iterated, quasi-, log-)
differences and (compounded) growth rates on (irregular) time series and panels.
Multivariate auto-, partial- and cross-correlation functions for panel data.
Panel data to (ts-)array conversions.
(5) List processing: Recursive list search, splitting,
extraction/subsetting, apply, and generalized row-binding / unlisting to data frame.
(6) Advanced data exploration: Fast (grouped, weighted, panel-decomposed)
summary statistics and descriptive tools.

Sebastian Krantz

collapse

Advanced and Fast Data Transformation

Matt Dowle

Arun Srinivasan

Morgan Jacob

Dirk Eddelbuettel

Laurent Berge

Kevin Tappe

R Core Team and contributors worldwide 

Martyn Plummer

1999-2016 The R Core Team 

rapply2d function

<dl> <dt>l</dt>
<dd>a list.</dd> <dt>FUN</dt>
<dd>a function that can be applied to all 'atomic' elements in l.</dd> <dt>...</dt>
<dd>additional elements passed to FUN.</dd> <dt>classes</dt>
<dd>character. Classes of list-based objects inside <code>l</code> that should be considered as atomic.</dd></dl>

Arguments

<code>rapply2d</code> is a recursive version of <code>lapply</code> with three differences to <code><a href='https://rdrr.io/r/base/rapply.html'>rapply</a></code>:
<ol>
<li>data frames (or other list-based objects specified in <code>classes</code>) are considered as atomic, not as (sub-)lists</li>
<li><code>FUN</code> is applied to all 'atomic' objects in the nested list</li>
<li>the result is not simplified / unlisted.</li>
</ol>

Recursively Apply a Function to a List of Data Objects — rapply2d

<dl>

 <dt>l</dt>
<dd>a list.</dd>

 <dt>FUN</dt>
<dd>a function that can be applied to all 'atomic' elements in l.</dd>

 <dt>...</dt>
<dd>additional elements passed to FUN.</dd>

 <dt>classes</dt>
<dd>character. Classes of list-based objects inside <code>l</code> that should be considered as atomic.</dd>

</dl>

rapply2d: Recursively Apply a Function to a List of Data Objects

Description

Usage

Value

Arguments

See Also

Examples