<p><div><div><div><div data-show-faces="false" data-height="21" data-width="100" data-layout="button_count" data-send="true" data-href="https://www.r-bloggers.com/september-2017-new-package-picks/"></div></div><div></div></div><div></div></div>
<div>
(This article was first published on <strong><a href="https://rviews.rstudio.com/2017/10/25/september-17-top-40-packages/"> R Views</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p>There were so many interesting ideas among the 222 new packages that made it to CRAN in September that I found it exceptionally difficult to decide on the “Top 40” packages. In the end, I only managed to limit my selection to 40 by avoiding all packages that I would normally classify under “Data”: packages that are primarily intended to provide access to some data source. I hope to make up for this by providing a list of data packages sometime soon.</p>
<p>Below are my picks for September’s Top 40 in six categories: Computational Methods, Machine Learning, Science, Statistics, Utilities, and Visualizations.</p>
<div>
<h3>Computational Methods</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=DES" target="_blank">DES</a> v1.0.0: Implements an event-oriented approach to Discrete Event Simulation. There is a <a rel="nofollow" href="https://cran.rstudio.com/web/packages/DES/" target="_blank">tutorial</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=JuliaCall" target="_blank">JuliaCall</a> 0.9.3: Implements an interface to <a rel="nofollow" href="https://julialang.org/" target="_blank">Julia</a>. The <a rel="nofollow" href="https://cran.rstudio.com/web/packages/JuliaCall/vignettes/Gallery.html" target="_blank">vignette</a> illustrates basic usage.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=Rlinsolve" target="_blank">Rlinsolve</a> v0.1.1: Implements iterative solvers for sparse linear systems of equations, including basic stationary iterative solvers using Jacobi, Gauss-Seidel, Successive Over-Relaxation and SSOR methods and non-stationary, Krylov subspace methods. There is a <a rel="nofollow" href="https://cran.rstudio.com/web/packages/Rlinsolve/vignettes/Rlinsolve_basics.html" target="_blank">vignette</a> to get started. Detailed descriptions may be found in the <a rel="nofollow" href="http://epubs.siam.org/doi/book/10.1137/1.9780898718003" target="_blank">SIAM book</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=sdpt3r" target="_blank">sdpt3r</a> v0.1: Implements the <a rel="nofollow" href="http://www.tandfonline.com/doi/abs/10.1080/10556789908805762" target="_blank">SDPT3 method</a> of Toh, Todd, and Tutuncu to solve Semi-Definite Linear Programming problems. There are several vignettes illustrating the use of the package in various applications, including <a rel="nofollow" href="https://cran.rstudio.com/web/packages/sdpt3r/vignettes/doptimal.pdf" target="_blank">D-Optimal Experimental Design</a> and <a rel="nofollow" href="https://cran.rstudio.com/web/packages/sdpt3r/vignettes/dwd.pdf" target="_blank">Distance Weighted Discrimination</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=VeryLargeIntegers" target="_blank">VeryLargeIntegers</a> v0.1.4: Provides tools to work with arbitrarily large integers without loss of precision.</p>
</div>
<div>
<h3>Machine Learning</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=bnclassify" target="_blank">bnclassify</a> v0.3.3: Implements algorithms for learning discrete Bayesian network classifiers from data, including a number of those described in <a rel="nofollow" href="doi:10.1145/2576868" target="_blank">Bielza &amp; Larranaga</a>. There is an <a rel="nofollow" href="https://cran.rstudio.com/web/packages/bnclassify/vignettes/introduction.pdf" target="_blank">Introduction</a> and vignettes giving <a rel="nofollow" href="https://cran.rstudio.com/web/packages/bnclassify/vignettes/runtimes.pdf" target="_blank">Runtime Information</a> and additional <a rel="nofollow" href="https://cran.rstudio.com/web/packages/bnclassify/vignettes/technical.pdf" target="_blank">Technical Information</a>.</p>
<div>
<img src="https://i2.wp.com/rviews.rstudio.com/post/2017-10-19-Top-40_files/bnclassify.png?w=456&ssl=1" data-recalc-dims="1">
</div>
<p><a rel="nofollow" href="https://cran.r-project.org/package=DMRnet" target="_blank">DMRnet</a> v0.1.0: Provides model selection algorithms for regression and classification, where the predictors can be numerical and categorical and the number of regressors exceeds the number of observations. See the papers by <a rel="nofollow" href="https://projecteuclid.org/euclid.ejs/1440507392" target="_blank">Maj-Kańska et al.</a> and <a rel="nofollow" href="http://www.jmlr.org/papers/volume16/pokarowski15a/pokarowski15a.pdf" target="_blank">Pokarowski and Mielniczuk</a> for the mathematical details.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=ELMSurv" target="_blank">ELMSurv</a> v0.4: Implements an <a rel="nofollow" href="https://en.wikipedia.org/wiki/Extreme_learning_machine" target="_blank">Extreme Learning Machine</a> for Survival Analysis. Look <a rel="nofollow" href="https://github.com/whcsu/ELMSurv/blob/master/elmsurv-revised.pdf" target="_blank">here</a> for details and <a rel="nofollow" href="https://cran.rstudio.com/web/packages/ELMSurv/vignettes/ELMSurv.html" target="_blank">here</a> to get started.</p>
<p><a rel="nofollow" href="https://rviews.rstudio.com/2017/10/25/september-17-top-40-packages/" target="_blank">fastrtext</a> v0.2.1: Provides an interface to Facebook’s <a rel="nofollow" href="https://github.com/facebookresearch/fastText" target="_blank">fastText</a> library for text representation and classification. There is a <a rel="nofollow" href="https://cran.rstudio.com/web/packages/fastrtext/vignettes/list_commands.html" target="_blank">List of Commands</a> and vignettes on <a rel="nofollow" href="https://cran.rstudio.com/web/packages/fastrtext/vignettes/supervised_learning.html" target="_blank">Supervised</a> and <a rel="nofollow" href="https://cran.rstudio.com/web/packages/fastrtext/vignettes/unsupervised_learning.html" target="_blank">Unsupervised</a> learning.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=FSelectorRcpp" target="_blank">FSelectorRcpp</a> v0.1.8: provides an <code>Rcpp</code>-based implementation of <code>FSelector</code> entropy-based feature selection algorithms based on an <a rel="nofollow" href="https://www.ijcai.org/Proceedings/93-2/Papers/022.pdf" target="_blank">Multi-Interval Discretization</a> with a sparse matrix support. There are vignettes on <a rel="nofollow" href="https://cran.rstudio.com/web/packages/FSelectorRcpp/vignettes/get_started.html" target="_blank">Getting Started</a> and <a rel="nofollow" href="https://cran.rstudio.com/web/packages/FSelectorRcpp/vignettes/benchmarks_discretize.html" target="_blank">Benchmarks</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=googleLanguageR" target="_blank">googleLanguageR</a> v0.1.0: Provides an interface to <a rel="nofollow" href="https://en.wikipedia.org/wiki/Google_Cloud_Platform" target="_blank">Google Cloud</a> machine-learning APIs for text and speech tasks. Call the <a rel="nofollow" href="https://cloud.google.com/translate/" target="_blank">Cloud Translation API</a> for detection and translation of text, the <a rel="nofollow" href="https://cloud.google.com/natural-language/" target="_blank">Natural Language API</a> to analyse text for sentiment, entities or syntax, and the <a rel="nofollow" href="https://cloud.google.com/speech/" target="_blank">Cloud Speech API</a> to transcribe sound files to text. There is an <a rel="nofollow" href="https://cran.rstudio.com/web/packages/googleLanguageR/vignettes/nlp.html" target="_blank">Introduction</a> and vignettes for the <a rel="nofollow" href="https://cran.rstudio.com/web/packages/googleLanguageR/vignettes/setup.html" target="_blank">NLP</a>, <a rel="nofollow" href="https://cran.rstudio.com/web/packages/googleLanguageR/vignettes/speech.html" target="_blank">Speech</a>, and <a rel="nofollow" href="https://cran.rstudio.com/web/packages/googleLanguageR/vignettes/translation.html" target="_blank">Translation</a> APIs.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=leabRa" target="_blank">leabRa</a> v0.1.0: Implements the <a rel="nofollow" href="https://grey.colorado.edu/emergent/index.php/Leabra" target="_blank">Leabra</a> (local, error-driven and associative, biologically realistic algorithm) that allows for the construction of artificial neural networks that are biologically realistic, and balances supervised and unsupervised learning within a single framework. See the <a rel="nofollow" href="https://cran.rstudio.com/web/packages/leabRa/vignettes/leabRa.html" target="_blank">vignette</a> to get started and look <a rel="nofollow" target="_blank">here</a> for details.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=lime" target="_blank">lime</a> v0.3.0: Is a port of the <a rel="nofollow" href="https://pypi.python.org/pypi/lime" target="_blank">Python</a> package, which attempts to explain the outcome of black-box models by fitting local models around the points of interest. Look <a rel="nofollow" href="arxiv:1602.04938" target="_blank">here</a> for details. There is a <a rel="nofollow" href="https://cran.rstudio.com/web/packages/lime/vignettes/Understanding_lime.html" target="_blank">vignette</a> to get you started.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=slowraker" target="_blank">slowraker</a> v0.1.0: Implements the <a rel="nofollow" href="doi:10.1002/9780470689646.ch1" target="_blank">RAKE algorithm</a>, which can be used to extract keywords from documents without any training data. There is a <a rel="nofollow" href="https://cran.rstudio.com/web/packages/slowraker/vignettes/getting-started.html" target="_blank">Getting Started</a> vignette and a list of <a rel="nofollow" href="https://cran.rstudio.com/web/packages/slowraker/vignettes/faqs.html" target="_blank">FAQs</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=udpipe" target="_blank">udpipe</a> v0.1.1: Provides a natural-language-processing toolkit for tokenization, parts-of-speech tagging, lemmatization, and dependency parsing of raw text. For details, see this <a rel="nofollow" href="doi:10.18653/v1/K17-3009" target="_blank">paper</a> and the vignettes on <a rel="nofollow" href="https://cran.rstudio.com/web/packages/udpipe/vignettes/udpipe-annotation.html" target="_blank">Annotating Text</a> and <a rel="nofollow" href="https://cran.rstudio.com/web/packages/udpipe/vignettes/udpipe-train.html" target="_blank">Model Building</a>.</p>
<div>
<img src="https://i1.wp.com/rviews.rstudio.com/post/2017-10-19-Top-40_files/udpipe.png?w=456&ssl=1" data-recalc-dims="1">
</div>
</div>
<div>
<h3>Science</h3>
<p><a rel="nofollow" href="https://rviews.rstudio.com/2017/10/25/september-17-top-40-packages/" target="_blank">afpt</a> v1.0.0: Implements the aerodynamic power model described in <a rel="nofollow" href="doi:10.1098/rspa.2014.0952" target="_blank">Klein Heerenbrink et al.</a>, and allows estimation and modelling of flight costs in vertebrate animal flight. There are vignettes on <a rel="nofollow" href="https://cran.rstudio.com/web/packages/afpt/vignettes/afpt-basic-usage.html" target="_blank">Basic Usage</a>, the underlying <a rel="nofollow" href="https://cran.rstudio.com/web/packages/afpt/vignettes/afpt-aerodynamic-model.html" target="_blank">Aerodynamic Model</a>, and <a rel="nofollow" href="https://cran.rstudio.com/web/packages/afpt/vignettes/afpt-multiple-birds.htm" target="_blank">Multiple Birds</a>.</p>
<div>
<img src="https://i1.wp.com/rviews.rstudio.com/post/2017-10-19-Top-40_files/afpt.png?w=456&ssl=1" data-recalc-dims="1">
</div>
<p><a rel="nofollow" href="https://cran.r-project.org/package=soundgen" target="_blank">soundgen</a> v1.1.O: Tools for sound synthesis and acoustic analysis. There are vignettes on <a rel="nofollow" href="https://cran.rstudio.com/web/packages/soundgen/vignettes/acoustic_analysis.html" target="_blank">Acoustic Analysis</a> and <a rel="nofollow" href="https://cran.rstudio.com/web/packages/soundgen/vignettes/sound_generation.html" target="_blank">Sound Generation</a>.</p>
</div>
<div>
<h3>Statistics</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=cr17" target="_blank">cr17</a> v0.1.0: Provides tools for analyzing competing-risks models, including testing differences between groups (<a rel="nofollow" href="doi:10.1214/aos/1176350951" target="_blank">Gray</a> and <a rel="nofollow" href="doi:10.2307/2670170" target="_blank">Fine and Gray</a>) and visualizations of survival and cumulative incidence curves. The <a rel="nofollow" href="https://cran.rstudio.com/web/packages/cr17/vignettes/vignette.html" target="_blank">vignette</a> gives examples.</p>
<div>
<img src="https://i1.wp.com/rviews.rstudio.com/post/2017-10-19-Top-40_files/cr17.png?w=456&ssl=1" data-recalc-dims="1">
</div>
<p><a rel="nofollow" href="https://cran.r-project.org/package=EAinference" target="_blank">EAinference</a> v0.2.1: Provides estimator augmentation methods for statistical inference on high-dimensional data, as described in <a rel="nofollow" href="arxiv:1401.4425v2" target="_blank">Zho</a> and <a rel="nofollow" href="doi:10.1214/17-EJS1309" target="_blank">Zhou and Min</a>. The <a rel="nofollow" href="https://cran.rstudio.com/web/packages/EAinference/vignettes/EAlasso.html" target="_blank">vignette</a> describes how to use the package.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=fdANOVA" target="_blank">fdAnova</a> v0.1.0: Provides functions to perform analysis of variance testing procedures for univariate and multivariate functional data. See <a rel="nofollow" href="doi:10.1007/s11749-010-0185-3" target="_blank">Cuesta-Albertos and Febrero-Bande</a>. There is a comprehensive <a rel="nofollow" href="https://cran.rstudio.com/web/packages/fdANOVA/vignettes/fdANOVA.pdf" target="_blank">vignette</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=geex" target="_blank">geex</a> v1.0.3: Provides a general, flexible framework for estimating parameters and empirical sandwich variance estimator from a set of unbiased estimating equations. See M-estimation as in <a rel="nofollow" href="doi:10.1198/000313002753631330" target="_blank">Stefanski &amp; Boos</a>. There is an <a rel="nofollow" href="https://cran.rstudio.com/web/packages/geex/vignettes/v00_geex_intro.html" target="_blank">Introduction</a>, as well as vignettes on <a rel="nofollow" href="https://cran.rstudio.com/web/packages/geex/vignettes/v01_additional_examples.html" target="_blank">M-estimation</a>, <a rel="nofollow" href="https://cran.rstudio.com/web/packages/geex/vignettes/v03_root_solvers.html" target="_blank">Custom root solvers</a>, <a rel="nofollow" href="https://cran.rstudio.com/web/packages/geex/vignettes/v06_causal_example.html" target="_blank">Parameter Estimation</a>, <a rel="nofollow" href="https://cran.rstudio.com/web/packages/geex/vignettes/v07_geex_design.html" target="_blank">Software Design</a>, and more.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=mosaicModel" target="_blank">mosaicModel</a> v0.3.0: Provides functions for evaluating, displaying, and interpreting statistical models with the goal of abstracting the operations on models from the particular architecture of the model. The <a rel="nofollow" href="https://cran.rstudio.com/web/packages/mosaicModel/vignettes/Basics.html" target="_blank">vignette</a> shows how to use the package.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=odr" target="_blank">odr</a> v0.3.2: Provides methods for calculating the optimal sample allocation that minimizes variance of treatment effects in a multilevel randomized trial under fixed budget and cost structure, and for performing power analyses with and without accommodating costs and budget. There is a <a rel="nofollow" href="https://cran.rstudio.com/web/packages/odr/vignettes/odr.html" target="_blank">vignette</a>.</p>
<div>
<img src="https://i0.wp.com/rviews.rstudio.com/post/2017-10-19-Top-40_files/odr.png?w=456&ssl=1" data-recalc-dims="1">
</div>
<p><a rel="nofollow" href="https://cran.r-project.org/package=mvord" target="_blank">mvord</a> v0.1.0: Provides a flexible framework for fitting multivariate ordinal regression models with composite likelihood methods. The <a rel="nofollow" href="https://cran.rstudio.com/web/packages/mvord/vignettes/vignette_mvord.pdf" target="_blank">vignette</a> gives the details.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=OutliersO3" target="_blank">OultiersO3</a> v0.2.1: Provides methods for identifying potential outliers for all combinations of a dataset’s variables. The <a rel="nofollow" href="https://cran.rstudio.com/web/packages/OutliersO3/vignettes/O3-vignette.html" target="_blank">vignette</a> shows how to use the package.</p>
<div>
<img src="https://i0.wp.com/rviews.rstudio.com/post/2017-10-19-Top-40_files/OutliersO3.png?w=456&ssl=1" data-recalc-dims="1">
</div>
<p><a rel="nofollow" href="https://cran.r-project.org/package=powerlmm" target="_blank">powerlmm</a> v0.1.0: Implements both analytical and simulation methods to calculate power for two- and three-level multilevel longitudinal studies with missing data. The analytical calculations extends the method described in <a rel="nofollow" href="doi:10.1016/S0197-2456(02)00205-2" target="_blank">Galbraith et al.</a> to three-level models. There are tutorials on <a rel="nofollow" href="https://cran.rstudio.com/web/packages/powerlmm/vignettes/simulations.html" target="_blank">Model Evaluation via Monte Carclo Simulation</a>, <a rel="nofollow" href="https://cran.rstudio.com/web/packages/powerlmm/vignettes/two-level.html" target="_blank">Two-level Longitudinal Power Analysis</a>, <a rel="nofollow" href="https://cran.rstudio.com/web/packages/powerlmm/vignettes/three-level.html" target="_blank">Three-level Longitudinal Power Analysis</a>, and a vignette on the <a rel="nofollow" href="https://cran.rstudio.com/web/packages/powerlmm/vignettes/technical.pdf" target="_blank">Details of Power Calculations</a>.</p>
<div>
<img src="https://i1.wp.com/rviews.rstudio.com/post/2017-10-19-Top-40_files/powerlmm.png?w=456&ssl=1" data-recalc-dims="1">
</div>
<p><a rel="nofollow" href="https://cran.r-project.org/package=randnet" target="_blank">randnet</a> v0.1: Facilitates model-selection and parameter-tuning procedures for a class of random network models. Model selection can be done by a general cross-validation framework called <a rel="nofollow" href="arxiv:1612.04717" target="_blank">ECV</a>, <a rel="nofollow" href="arxiv:1411.1715" target="_blank">NCV</a>, a <a rel="nofollow" href="arxiv:1502.02069" target="_blank">likelihood ratio method</a>, and <a rel="nofollow" href="arxiv:1507.00827" target="_blank">spectral methods</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=threshr" target="_blank">threshr</a> v1.0.0: Provides functions for the selection of thresholds for use in extreme value models, based mainly on the methodology in <a rel="nofollow" href="doi:10.1111/rssc.12159" target="_blank">Northrop, Attalides and Jonathan</a>. There is a <a rel="nofollow" href="https://cran.rstudio.com/web/packages/threshr/vignettes/threshr-vignette.html" target="_blank">vignette</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=tscount" target="_blank">tscount</a> v1.4.0: Implements likelihood-based methods for model fitting and assessment, prediction, and intervention analysis of count time series following generalized linear models. The <a rel="nofollow" href="https://cran.rstudio.com/web/packages/tscount/vignettes/tsglm.pdf" target="_blank">vignette</a> provides the details.</p>
</div>
<div>
<h3>Utilities</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=basictabler" target="_blank">basictabler</a> v0.1.0: Provides functions to create tables from data frames and matrices, manipulate tables row-by-row, column-by-column or cell-by-cell, and then publish them using <code>HTML</code>, <code>HTML widgets</code> or <code>Excel</code>. There is an <a rel="nofollow" href="https://cran.rstudio.com/web/packages/basictabler/vignettes/v01-introduction.html" target="_blank">Introduction</a> and vignettes on <a rel="nofollow" href="https://cran.rstudio.com/web/packages/basictabler/vignettes/v02-workingwithcells.html" target="_blank">Working with Cells</a>, <a rel="nofollow" href="https://cran.rstudio.com/web/packages/basictabler/vignettes/v03-outputs.html" target="_blank">Outputs</a>, <a rel="nofollow" href="https://cran.rstudio.com/web/packages/basictabler/vignettes/v04-styling.html" target="_blank">Styling</a>, <a rel="nofollow" href="https://cran.rstudio.com/web/packages/basictabler/vignettes/v05-findingandformatting.html" target="_blank">Formatting</a>, <a rel="nofollow" href="https://cran.rstudio.com/web/packages/basictabler/vignettes/v06-shiny.html" target="_blank">Shiny</a>, and <a rel="nofollow" href="https://cran.rstudio.com/web/packages/basictabler/vignettes/v07-excelexport.html" target="_blank">Excel</a>.</p>
<div>
<img src="https://i0.wp.com/rviews.rstudio.com/post/2017-10-19-Top-40_files/basictabler..png?w=456&ssl=1" data-recalc-dims="1">
</div>
<p><a rel="nofollow" href="https://cran.r-project.org/package=bigstatsr" target="_blank">bigstatsr</a> v0.2.2: Uses file-backed matrices to provide scalable statistical tools.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=keyring" target="_blank">keyring</a> v1.0.0: Provides a platform-independent API to access the operating system’s credential store. It currently supports: <code>Keychain</code> on <code>macOS</code>, The Credential Store on <code>Windows</code>, the <a rel="nofollow" href="https://standards.freedesktop.org/secret-service/" target="_blank">Secret Service</a> API on <code>Linux</code>, and a simple, platform-independent store implemented with environment variables.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=pinp" target="_blank">pinp</a> v0.0.2: Offers a <code>PNAS</code>-like style for <code>rmarkdown</code> derived from the <a rel="nofollow" href="https://www.pnas.org/" target="_blank">Proceedings of the National Academy of Sciences of the United States of America</a>. The <a rel="nofollow" href="https://cran.rstudio.com/web/packages/pinp/vignettes/pinp.pdf" target="_blank">vignette</a> shows how to get started.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=re2r" target="_blank">re2r</a> v0.2.0: Provides an interface to Google’s deterministic finite-automaton-based <a rel="nofollow" href="https://github.com/google/re2" target="_blank">regular expression engine</a> that is very fast at matching large amounts of text. There is an <a rel="nofollow" href="https://cran.rstudio.com/web/packages/re2r/vignettes/re2r-intro.html" target="_blank">Introduction</a> and a vignette on <a rel="nofollow" href="https://cran.rstudio.com/web/packages/re2r/vignettes/re2r-syntax.html" target="_blank">Syntax</a>.</p>
<div>
<img src="https://i2.wp.com/rviews.rstudio.com/post/2017-10-19-Top-40_files/re2r.png?w=456&ssl=1" data-recalc-dims="1">
</div>
<p><a rel="nofollow" href="https://cran.r-project.org/package=spiderbar" target="_blank">spiderbar</a> v0.2.0: Provides a wrapper for the <a rel="nofollow" href="https://github.com/seomoz/rep-cpp" target="_blank">rep-cpp</a> C++ library for processing <code>robots.txt</code> files in accordance with the The <a rel="nofollow" href="http://www.robotstxt.org/orig.html" target="_blank">Robots Exclusion Protocol</a>, a set of standards for allowing or excluding robot/spider crawling of different areas of site content. Look in the <a rel="nofollow" href="https://cran.rstudio.com/web/packages/spiderbar/README.html" target="_blank">README</a> for an example of how to use the package.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=tibbletime" target="_blank">tibbletime</a> v0.0.2: Is an extension of the <code>tibble</code> package that allows for the creation of time-aware tibbles. Some immediate advantages include: the ability to perform time-based subsetting on tibbles, quickly summarising and aggregating results by time periods, and calling functions similar in spirit to the <code>map</code> family from <code>purrr</code> on time-based tibbles. There is an <a rel="nofollow" href="https://cran.rstudio.com/web/packages/tibbletime/vignettes/TT-00-intro-to-tibbletime.html" target="_blank">Introduction</a> and vignettes on <a rel="nofollow" href="https://cran.rstudio.com/web/packages/tibbletime/vignettes/TT-01-time-based-filtering.html" target="_blank">Time-based Filtering</a>, <a rel="nofollow" href="https://cran.rstudio.com/web/packages/tibbletime/vignettes/TT-02-changing-time-periods.html" target="_blank">Changing Periodicity</a>, and <a rel="nofollow" href="https://cran.rstudio.com/web/packages/tibbletime/vignettes/TT-03-rollify-for-rolling-analysis.html" target="_blank">Rolling Calculaions</a>.</p>
</div>
<div>
<h3>Visualizations</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=egg" target="_blank">egg</a> v0.2.0: Provides miscellaneous functions to customize <code>ggplot2</code> plots, including high-level functions to post-process layouts and allow alignment between plot panels, as well as setting panel sizes to fixed values. There is an <a rel="nofollow" href="https://cran.rstudio.com/web/packages/egg/vignettes/Overview.html" target="_blank">Overview</a> and a <a rel="nofollow" href="https://cran.rstudio.com/web/packages/egg/vignettes/Ecosystem.html" target="_blank">vignette</a> for laying out multiple plots on a page.</p>
<div>
<img src="https://i1.wp.com/rviews.rstudio.com/post/2017-10-19-Top-40_files/egg.png?w=456&ssl=1" data-recalc-dims="1">
</div>
<p><a rel="nofollow" href="https://cran.r-project.org/package=ggridges" target="_blank">ggridges</a> v0.4.1: Extends <code>ggplot2</code> to enable ridgeline plots, which are a way of visualizing changes in distributions over time or space. There is an <a rel="nofollow" href="https://cran.rstudio.com/web/packages/ggridges/vignettes/introduction.html" target="_blank">introduction</a> and a <a rel="nofollow" href="https://cran.rstudio.com/web/packages/ggridges/vignettes/gallery.html" target="_blank">gallery</a> of examples.</p>
<div>
<img src="https://i0.wp.com/rviews.rstudio.com/post/2017-10-19-Top-40_files/ggridges.png?w=456&ssl=1" data-recalc-dims="1">
</div>
<p><a rel="nofollow" href="https://cran.r-project.org/package=linemap" target="_blank">linemap</a> v0.1.0: Provides functions to create maps from lines. The <a rel="nofollow" href="https://cran.rstudio.com/web/packages/linemap/README.html" target="_blank">README</a> file shows examples.</p>
<div>
<img src="https://i0.wp.com/rviews.rstudio.com/post/2017-10-19-Top-40_files/linemap.png?w=456&ssl=1" data-recalc-dims="1">
</div>
</div>
<p> </p>
	<p>
<div>
<div>To <strong>leave a comment</strong> for the author, please follow the link and comment on their blog: <strong><a href="https://rviews.rstudio.com/2017/10/25/september-17-top-40-packages/"> R Views</a></strong>.</div>
<hr>
<a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers.com</a> offers <strong><a rel="nofollow" href="https://feedburner.google.com/fb/a/mailverify?uri=RBloggers">daily e-mail updates</a></strong> about <a rel="nofollow" href="https://www.r-project.org/" title="The R Project for Statistical Computing">R</a> news and <a rel="nofollow" href="https://www.r-bloggers.com/search/tutorial" title="R tutorials">tutorials</a> on topics such as: <a rel="nofollow" href="https://www.r-bloggers.com/search/data%20science" title="Data science">Data science</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/Big%20Data" title="Big Data">Big Data, <a rel="nofollow" href="https://www.r-users.com/" title="R jobs">R jobs</a>, visualization (<a rel="nofollow" href="https://www.r-bloggers.com/search/ggplot2" title="ggplot and ggplot2 tutorials">ggplot2</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/boxplot" title="Boxplots using lattice and ggplot2 tutorials">Boxplots</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/map" title="Maps and gis">maps</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/animation" title="Animation in R">animation</a>), programming (<a rel="nofollow" href="https://www.r-bloggers.com/search/RStudio" title="RStudio IDE for R">RStudio</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/sweave" title="Sweave and literate programming">Sweave</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/LaTeX" title="LaTeX in R">LaTeX</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/SQL" title="SQL and databases">SQL</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/eclipse" title="Eclipse IDE for R">Eclipse</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/git" title="git and github, Version Control System">git</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/hadoop" title="Large data in R using Hadoop">hadoop</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/Web+Scraping" title="Web Scraping of google, facebook, yahoo, twitter and more using R">Web Scraping</a>) statistics (<a rel="nofollow" href="https://www.r-bloggers.com/search/regression" title="Regressions and ANOVA analysis tutorials">regression</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/PCA" title="principal component analysis tutorial">PCA</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/time+series" title="Time series">time series</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/trading" title="finance trading">trading</a>) and more...
<img width="1" alt="" src="http://feeds.feedburner.com/~r/RBloggers/~4/a_y7nuOff58" height="1"></a></div>