The goal of 'readr' is to provide a fast and friendly way to read
rectangular data (like 'csv', 'tsv', and 'fwf'). It is designed to
flexibly parse many types of data found in the wild, while still
cleanly failing when data unexpectedly changes.
Simplifies the creation of Excel .xlsx files by providing a high level
interface to writing, styling and editing worksheets. Through the use
of 'Rcpp', read/write times are comparable to the 'xlsx' and
'XLConnect' packages with the added benefit of removing the dependency
on Java.
Tables with state-of-the-art layout elements such as row spanners,
column spanners, table spanners, zebra striping, and more. While
allowing advanced layout, the underlying css-structure is simple in
order to maximize compatibility with word processors such as 'MS Word'
or 'LibreOffice'. The package also contains a few text formatting
functions that help outputting text compatible with HTML/LaTeX.
Fast aggregation of large data (e.g. 100GB in RAM), fast ordered
joins, fast add/modify/delete of columns by group using no copies at
all, list columns, friendly and fast character-separated-value
read/write. Offers a natural and flexible syntax, for faster
development.
Configurable Progress bars, they may include percentage, elapsed time,
and/or the estimated completion time. They work in terminals, in
'Emacs' 'ESS', 'RStudio', 'Windows' 'Rgui' and the 'macOS' 'R.app'.
The package also provides a 'C++' 'API', that works with or without
'Rcpp'.
Contains many functions useful for data analysis, high-level graphics,
utility operations, functions for computing sample size and power,
importing and annotating datasets, imputing missing values, advanced
table making, variable clustering, character string manipulation,
conversion of R objects to LaTeX and html code, and recoding
variables.
Provides a %<-% operator to perform multiple, unpacking, and
destructuring assignment in R. The operator unpacks the right-hand
side of an assignment into multiple values and assigns these values to
variables on the left-hand side of the assignment.
Defines new notions of prototype and size that are used to provide
tools for consistent and well-founded type-coercion and
size-recycling, and are in turn connected to ideas of type- and
size-stability useful for analyzing function interfaces.
Summary statistics, two-sample tests, rank tests, generalised linear
models, cumulative link models, Cox models, loglinear models, and
general maximum pseudolikelihood estimation for multistage stratified,
cluster-sampled, unequally weighted survey samples. Variances by
Taylor series linearisation or replicate weights. Post-stratification,
calibration, and raking. Two-phase subsampling designs. Graphics. PPS
sampling without replacement. Principal components, factor analysis.
Functions to facilitate inference on the relative importance of
predictors in a linear or generalized linear model, and a couple of
useful Tcl/Tk widgets.
Helpers for reordering factor levels (including moving specified
levels to front, ordering by first appearance, reversing, and randomly
shuffling), and tools for modifying factor levels (including
collapsing rare levels into other, 'anonymising', and manually
'recoding').
Provides tools for determining estimability of linear functions of
regression coefficients, and 'epredict' methods that handle
non-estimable cases correctly. Estimability theory is discussed in
many linear-models textbooks including Chapter 3 of Monahan, JF
(2008), "A Primer on Linear Models", Chapman and Hall (ISBN
978-1-4200-6201-4).
The ellipsis is a powerful tool for extending functions. Unfortunately
this power comes at a cost: misspelled arguments will be silently
ignored. The ellipsis package provides a collection of functions to
catch problems and alert the user.
Functions introduced or changed since R v3.0.0 are re-implemented in
this package. The backports are conditionally exported in order to let
R resolve the function name to either the implemented backport, or the
respective base version, if available. Package developers can make use
of new functions or arguments by selectively importing specific
backports to support older installations.
Two nonparametric methods for multiple regression transform selection
are provided. The first, Alternative Conditional Expectations (ACE),
is an algorithm to find the fixed point of maximal correlation, i.e.
it finds a set of transformed response variables that maximizes R^2
using smoothing functions [see Breiman, L., and J.H. Friedman. 1985.
"Estimating Optimal Transformations for Multiple Regression and
Correlation". Journal of the American Statistical Association.
80:580-598. <doi:10.1080/01621459.1985.10478157>]. Also included is
the Additivity Variance Stabilization (AVAS) method which works better
than ACE when correlation is low [see Tibshirani, R.. 1986.
"Estimating Transformations for Regression via Additivity and Variance
Stabilization". Journal of the American Statistical Association.
83:394-405. <doi:10.1080/01621459.1988.10478610>]. A good introduction
to these two methods is in chapter 16 of Frank Harrel's "Regression
Modeling Strategies" in the Springer Series in Statistics.
Various utilities are provided that might be used in spatial
statistics and elsewhere. It delivers a method for solving linear
equations that checks the sparsity of the matrix before any algorithm
is used. Furthermore, it includes the Struve functions.
Infrastructure for extended formulas with multiple parts on the
right-hand side and/or multiple responses on the left-hand side (see
<DOI:10.18637/jss.v034.i01>).
Implementation of the 'viridis' - the default -, 'magma', 'plasma',
'inferno', and 'cividis' color maps for 'R'. 'viridis', 'magma',
'plasma', and 'inferno' are ported from 'matplotlib'
<http://matplotlib.org/>, a popular plotting library for 'python'.
'cividis', was developed by Jamie R. Nu<c3><b1>ez and Sean M. Colby.
These color maps are designed in such a way that they will
analytically be perfectly perceptually-uniform, both in regular form
and also when converted to black-and-white. They are also designed to
be perceived by readers with the most common form of color blindness
(all color maps in this package) and color vision deficiency
('cividis' only).
A set of functions to run code 'with' safely and temporarily modified
global state. Many of these functions were originally a part of the
'devtools' package, this provides a simple package with limited
dependencies to provide access to these functions.
A series of additional Tcl commands and Tk widgets with style and
various functions (under Windows: DDE exchange, access to the registry
and icon manipulation) to supplement the tcltk package
Streamlined data import and export by making assumptions that the user
is probably willing to make: 'import()' and 'export()' determine the
data structure from the file extension, reasonable defaults are used
for data import and export (e.g., 'stringsAsFactors=FALSE'), web-based
import is natively supported (including from SSL/HTTPS), compressed
files can be read directly without explicit decompression, and fast
import packages are used where appropriate. An additional convenience
function, 'convert()', provides a simple method for converting between
file types.
Tests and assertions to perform frequent argument checks. A
substantial part of the package was written in C to minimize any
worries about execution time overhead.
The software hasn't been updated since 2002 and is probably full
of security problems. Two packages were using it. (gpsdrive has a
newer version in wip.)
Not used in pkgsrc, needs quite unmaintained jasper library with lots
of security problems, and is harder to keep working with meson version
of gdk-pixbuf2.
