<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/april-2018-top-40-new-packages/"></div></div><div></div></div><div></div></div>
<div>
(This article was first published on <strong><a href="https://rviews.rstudio.com/2018/05/24/april-2018-top-40-new-packages/"> R Views</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p>Below are my “Top 40” picks from the approximately 212 new packages that made it to CRAN in April. They are organized into ten categories: Computational Methods, Data, Data Science, Machine Learning, Music, Science, Statistics, Time Series, Utilities, and Visualizations.</p>
<h3>Computational Methods</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=diffeqr" target="_blank">diffeqr</a> v0.1.1: Provides an interface to <a rel="nofollow" href="http://docs.juliadiffeq.org/latest/" target="_blank">DifferentialEquations.jl</a> which offers high performance methods for solving ordinary differential equations (ODE), stochastic differential equations (SDE), delay differential equations (DDE), differential-algebraic equations (DAE), and more. There are vignettes for solving <a rel="nofollow" href="https://cran.r-project.org/web/packages/diffeqr/vignettes/dae.html" target="_blank">differential algebraic equations</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/diffeqr/vignettes/dde.html" target="_blank">delay differential equations</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/diffeqr/vignettes/ode.html" target="_blank">ordinary differential equations</a>, and <a rel="nofollow" href="https://cran.r-project.org/web/packages/diffeqr/vignettes/sde.html" target="_blank">stochastic differential equations</a>.</p>
<p><img alt="" src="https://i2.wp.com/rviews.rstudio.com/post/2018-05-21-Rickert-AprilTop40_files/diffeqr.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=SimRepeat" target="_blank">SimRepeat</a> v0.1.0: Provides functions to simulate correlated systems of statistical equations with multiple variable types. There is a vignette describing the underlying <a rel="nofollow" href="https://cran.r-project.org/web/packages/SimRepeat/vignettes/Theory_Cont_System.html" target="_blank">theory</a>, as well as vignettes on systems with <a rel="nofollow" href="https://cran.r-project.org/web/packages/SimRepeat/vignettes/Corr_Cont_System.html" target="_blank">Continuous variables</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/SimRepeat/vignettes/Corr_MultiVarType_System.html" target="_blank">multiple variable types</a>, and <a rel="nofollow" href="https://cran.r-project.org/web/packages/SimRepeat/vignettes/HLM_Approach.html" target="_blank">hierarchical linear models</a>.</p>
<h3>Data</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=echor" target="_blank">echor</a> v0.1.0: Implements an interface to the United States Environmental Protection Agency (EPA) Environmental Compliance History Online <a rel="nofollow" href="https://echo.epa.gov/" target="_blank">ECHO</a> API. The <a rel="nofollow" href="https://cran.r-project.org/web/packages/echor/vignettes/introduction.html" target="_blank">vignette</a> shows how to use the package.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=essurvey" target="_blank">essurvey</a> v1.0.0: Provides an interface to download data from the <a rel="nofollow" href="http://www.europeansocialsurvey.org/" target="_blank">European Social Survey</a>. There is a <a rel="nofollow" href="https://cran.r-project.org/web/packages/essurvey/vignettes/intro_ess.html" target="_blank">vignette</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=malariaAtlas" target="_blank">malariaAtlas</a> v0.0.1: Provides a suite of tools to allow downloading all publicly available parasite rate survey points and raster surfaces from the <a rel="nofollow" href="https://map.ox.ac.uk/" target="_blank">Malaria Atlas Project</a> servers as well as utility functions for plotting the downloaded data. The <a rel="nofollow" href="https://cran.r-project.org/web/packages/malariaAtlas/vignettes/overview.htm" target="_blank">vignette</a> shows how to use the package.</p>
<p><img alt="" src="https://i2.wp.com/rviews.rstudio.com/post/2018-05-21-Rickert-AprilTop40_files/malariaAtlas.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=salesforcer" target="_blank">salesforcer</a> v0.1.2: Implements the <a rel="nofollow" href="https://developer.salesforce.com/page/Salesforce_API" target="_blank">Salesforce</a> Platform APIs (REST, SOAP, Bulk 1.0, Bulk 2.0, and Metadata). There is a <a rel="nofollow" href="https://cran.r-project.org/web/packages/salesforcer/vignettes/getting-started.html" target="_blank">Getting Started</a> guide, a vignette on <a rel="nofollow" href="https://cran.r-project.org/web/packages/salesforcer/vignettes/transitioning-from-RForcecom.html" target="_blank">Transitioning from RForecom</a> and another on <a rel="nofollow" href="https://cran.r-project.org/web/packages/salesforcer/vignettes/working-with-bulk-api.html" target="_blank">Working with Bulk API</a>.</p>
<h3>Data Science</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=mleap" target="_blank">mleap</a> v0.1.1: Provides a <a rel="nofollow" href="https://spark.rstudio.com/" target="_blank">sparklyr</a> extension to <a rel="nofollow" href="https://github.com/combust/mleap" target="_blank">MLeap</a>, an open source library that enables exporting and serving <code>Apache Spark</code> pipelines.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=rdfp" target="_blank">rdfp</a> v0.1.2: Implements Google’s <a rel="nofollow" href="https://developers.google.com/doubleclick-publishers/docs/start" target="_blank">DoubleClick for Publishers (DFP)</a> API. There are vignettes on <a rel="nofollow" href="https://cran.r-project.org/web/packages/rdfp/vignettes/ad-trafficking-setup.html" target="_blank">Ad trafficing setup</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/rdfp/vignettes/administrative-tasks.html" target="_blank">administrative tasks</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/rdfp/vignettes/checking-availability.html" target="_blank">checking availability</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/rdfp/vignettes/manipulating-orders-and-lineitems.html" target="_blank">manipulating orders and line items</a>, and <a rel="nofollow" href="https://cran.r-project.org/web/packages/rdfp/vignettes/pulling-reports.html" target="_blank">reporting</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=workflowr" target="_blank">workflowr</a> v1.0.1: Implements a framework for reproducible and collaborative data science. There is a <a rel="nofollow" href="https://cran.r-project.org/web/packages/workflowr/vignettes/wflow-01-getting-started.html" target="_blank">getting started guide</a>, and vignettes on <a rel="nofollow" href="https://cran.r-project.org/web/packages/workflowr/vignettes/wflow-02-customization.html" target="_blank">customizing a website</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/workflowr/vignettes/wflow-03-migrating.html" target="_blank">migrating projects</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/workflowr/vignettes/wflow-04-how-it-works.html" target="_blank">package details</a>, and <a rel="nofollow" href="https://cran.r-project.org/web/packages/workflowr/vignettes/wflow-05-faq.html" target="_blank">frequently asked questions</a>.</p>
<h3>Machine Learning</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=aws.translate" target="_blank">aws.translate</a> v0.1.3: Implements a client for <a rel="nofollow" href="https://aws.amazon.com/documentation/translate" target="_blank">AWS Translate</a>, a machine translation service that will convert a text input in one language into a text output in another.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=CBDA" target="_blank">CBDA</a> v1.0.0: Implements an ensemble predictor, a ‘SuperLearner’, using knockoff filtering and concepts from comprehensive sensing to classify Big Data. See the <a rel="nofollow" href="https://cran.r-project.org/web/packages/CBDA/vignettes/Guide-to-CBDA.html" target="_blank">Guide to Compressive Big Data Analytics (CBDA)</a>.</p>
<p><img alt="" src="https://i2.wp.com/rviews.rstudio.com/post/2018-05-21-Rickert-AprilTop40_files/CBDA.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=featurefinder" target="_blank">featurefinder</a> v1.0: Implements a method to find model features through a detailed analysis of model residuals using <code>rpart</code> classification and regression trees. See <a rel="nofollow" href="doi:10.1002/0470055464" target="_blank">Chatterjee and Hadi (2006)</a> and the <a rel="nofollow" href="https://cran.r-project.org/web/packages/featurefinder/vignettes/featurefinder.html" target="_blank">vignette</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=iilasso" target="_blank">iilassso</a> v0.0.1: Implements efficient algorithms for fitting linear / logistic regression models with an independently interpretable Lasso. See <a rel="nofollow" href="http://proceedings.mlr.press/v84/takada18a/takada18a.pdf" target="_blank">Takada et al. (2018)</a> and the <a rel="nofollow" href="https://cran.r-project.org/web/packages/iilasso/vignettes/introduction.html" target="_blank">vignette</a>.</p>
<p><img alt="" src="https://i1.wp.com/rviews.rstudio.com/post/2018-05-21-Rickert-AprilTop40_files/iilasso.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=live" target="_blank">live</a> v1.5.4: Implements a methodology for interpreting a complex machine learning model by understanding the key factors. This is achieved through local approximations based on additive regression or CART like models that allow for higher interactions. See <a rel="nofollow" href="doi:10.1145/2939672.2939778" target="_blank">Ribeiro et al. (2016)</a> and <a rel="nofollow" href="arxiv:1804.01955" target="_blank">Staniak and Biecek (2018)</a> for details. The <a rel="nofollow" href="https://cran.r-project.org/web/packages/live/vignettes/wine_quality.html" target="_blank">vignette</a> offers a case study.</p>
<p><img alt="" src="https://i0.wp.com/rviews.rstudio.com/post/2018-05-21-Rickert-AprilTop40_files/live.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=mlrCPO" target="_blank">mlrCPO</a> v0.3.3: Provides a tool set that enriches the <a rel="nofollow" href="https://cran.r-project.org/package=mlr" target="_blank">mlr</a> with a diverse set of composable preprocessing operators (CPOs). There are several vignettes including <a rel="nofollow" href="https://cran.r-project.org/web/packages/mlrCPO/vignettes/a_1_getting_started.html" target="_blank">First Steps</a>, the <a rel="nofollow" href="https://cran.r-project.org/web/packages/mlrCPO/vignettes/a_2_mlrCPO_core.html" target="_blank">mlrCPO Core</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/mlrCPO/vignettes/a_3_all_CPOs.html" target="_blank">Built-in CPOs</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/mlrCPO/vignettes/a_4_custom_CPOs.html" target="_blank">Custom CPOs</a> and more.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=varrank" target="_blank">varrank</a> v0.1: Provides a computational toolbox of heuristic approaches for performing variable ranking and feature selection based on mutual information adapted for multivariate system epidemiology datasets. The core function is a general implementation of the minimum redundancy maximum relevance model: <a rel="nofollow" href="doi:10.1109/72.298224" target="_blank">Battiti (1994)</a>. The <a rel="nofollow" href="https://cran.r-project.org/web/packages/varrank/vignettes/varrank.html" target="_blank">vignette</a> is informative.</p>
<h3>Music</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=tabr" target="_blank">tabr</a> v0.2.0: Provides functions to creates guitar tablature from R code using <a rel="nofollow" href="http://lilypond.org/" target="_blank">LilyPond</a>, open source music engraving software for generating high quality sheet music based on markup language. <code>tabr</code> also offers nominal MIDI file support. There are several vignettes: <a rel="nofollow" href="https://cran.r-project.org/web/packages/tabr/vignettes/tabr-basics.html" target="_blank">Basic example</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/tabr/vignettes/tabr-chords.html" target="_blank">Chords</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/tabr/vignettes/tabr-engraving.html" target="_blank">Engraving</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/tabr/vignettes/tabr-helpers.html" target="_blank">Phrase Helpers</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/tabr/vignettes/tabr-phrases.html" target="_blank">Musical Phrases</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/tabr/vignettes/tabr-repeats.html" target="_blank">Repeats</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/tabr/vignettes/tabr-tracks-scores.html" target="_blank">Tracks and Scores</a>, and<br>
<a rel="nofollow" href="https://cran.r-project.org/web/packages/tabr/vignettes/tabr-tunings.html" target="_blank">Non-standard Tuning</a>.</p>
<p><img alt="" src="https://i1.wp.com/rviews.rstudio.com/post/2018-05-21-Rickert-AprilTop40_files/tabr.png?w=456&ssl=1" data-recalc-dims="1"></p>
<h3>Science</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=DrInsight" target="_blank">DrInsight</a> v0.1.1: Implements a connectivity mapping-based drug repurposing tool that identifies drugs that can potentially reverse query disease phenotype or have similar functions with query drugs. The <a rel="nofollow" href="https://cran.r-project.org/web/packages/DrInsight/vignettes/my-vignette.html" target="_blank">vignette</a> provides an example.</p>
<p><img alt="" src="https://i0.wp.com/rviews.rstudio.com/post/2018-05-21-Rickert-AprilTop40_files/DrInsight.png?w=456&ssl=1" data-recalc-dims="1"></p>
<h3>Statistics</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=cultevo" target="_blank">cultevo</a> v1.0.2: Provides tools for measuring the composition of signalling systems: in particular, the information-theoretic measure due to <a rel="nofollow" href="http://hdl.handle.net/1842/25930" target="_blank">Spike (2016)</a> and the Mantel test for distance matrix correlation <a rel="nofollow" href="doi:10.1093/sysbio/32.1.21" target="_blank">Dietz (1983)</a> as well as an implementation of the Page test for monotonicity of ranks <a rel="nofollow" href="doi:10.1080/01621459.1963.10500843" target="_blank">Page (1963)</a>. The <a rel="nofollow" href="https://cran.r-project.org/web/packages/cultevo/vignettes/page.test.html" target="_blank">vignette</a> provides and example.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=indirect" target="_blank">indirect</a> v0.2.0: Provides functions to facilitate prior elicitation for Bayesian generalized linear models using independent conditional means priors. Various methodologies for eliciting fractiles are supported, including versions of the approach of <a rel="nofollow" href="doi:10.1016/j.ress.2017.06.011" target="_blank">Hosack et al. (2017)</a>. The <a rel="nofollow" href="https://cran.r-project.org/web/packages/indirect/vignettes/indirect.pdf" target="_blank">vignette</a> describes the methodology.</p>
<p><img alt="" src="https://i1.wp.com/rviews.rstudio.com/post/2018-05-21-Rickert-AprilTop40_files/ibdirect.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=konfound" target="_blank">konfound</a> v0.1.0: Implements methods that reflect recent developments in sensitivity analysis including functions to calculate robustness indices. See <a rel="nofollow" href="doi:10.1177/0049124100029002001" target="_blank">Frank (2000)</a> and <a rel="nofollow" href="doi:10.3102/0162373713493129" target="_blank">Frank et al. (2013)</a> for details and the <a rel="nofollow" href="https://cran.r-project.org/web/packages/konfound/vignettes/Introduction_to_konfound.html" target="_blank">vignette</a> for an introduction to the package.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=mgc" target="_blank">mgc</a> v1.0.1: Implements Multiscale Graph Correlation (MGC), a framework developed by <a rel="nofollow" href="arxiv:1609.05148" target="_blank">Shen et al. (2017)</a>, that extends global correlation procedures to be multiscale. There are vignettes on the <a rel="nofollow" href="https://cran.r-project.org/web/packages/mgc/vignettes/Discriminability.html" target="_blank">Discriminability</a> statistic, the <a rel="nofollow" href="https://cran.r-project.org/web/packages/mgc/vignettes/MGC.html" target="_blank">mgc</a> statistic, and <a rel="nofollow" href="https://cran.r-project.org/web/packages/mgc/vignettes/simulations.html" target="_blank">Canonical Dependence Simulations</a>.</p>
<p><img alt="" src="https://i2.wp.com/rviews.rstudio.com/post/2018-05-21-Rickert-AprilTop40_files/mgc.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=netregR" target="_blank">netregR</a> v0.3.1: Provides functions to regress network responses (both directed and undirected) onto covariates of interest that may be actor, relation, or network-valued, and compute principled variance estimates of the coefficients. For details see <a rel="nofollow" href="arxiv:1701.05530" target="_blank">Marrs et al. (2017)</a> and the <a rel="nofollow" href="https://cran.r-project.org/web/packages/netregR/vignettes/netregR_vignette_single.html" target="_blank">vignette</a>.</p>
<p><img alt="" src="https://i1.wp.com/rviews.rstudio.com/post/2018-05-21-Rickert-AprilTop40_files/netregR.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=RNGforGPD" target="_blank">RNGforGPD</a> v1.0: Provides functions to generate univariate and multivariate data that follow the generalized Poisson distribution. See <a rel="nofollow" href="doi:10.1080/03610918.2014.968725" target="_blank">Demirtas (2017)</a> for the details, and the <a rel="nofollow" href="https://cran.r-project.org/web/packages/RNGforGPD/vignettes/RNGforGPD_vignette.html" target="_blank">vignette</a> for an example.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=SmartEDA" target="_blank">SmartEDA</a> v0.2.0: Provides functions that automatically describe the structure and relationships in data to facilitate exploratory data analysis. There is an <a rel="nofollow" href="https://cran.r-project.org/web/packages/SmartEDA/vignettes/Report_r1.html" target="_blank">Introduction</a> to the package and a <a rel="nofollow" href="https://cran.r-project.org/web/packages/SmartEDA/vignettes/CustomTable.html" target="_blank">vignette</a> on building custom tables.</p>
<p><img alt="" src="https://i1.wp.com/rviews.rstudio.com/post/2018-05-21-Rickert-AprilTop40_files/SmartEDA.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=stratifyR" target="_blank">stratifyR</a> 1.0-1: Implements stratified sampling designs for univariate populations using the method of <a rel="nofollow" href="doi:10.1177/0008068320020518" target="_blank">Khan et al. (2002)</a>, <a rel="nofollow" href="http://www.statcan.gc.ca/pub/12-001-x/2008002/article/10761-eng.pdf" target="_blank">Khan et al. (2008)</a> and <a rel="nofollow" href="doi:10.1080/02664763.2015.1018674" target="_blank">Khan et al. (2015)</a>. The <a rel="nofollow" href="https://cran.r-project.org/web/packages/stratifyR/vignettes/stratifyR-vignette.html" target="_blank">vignette</a> goes through the math.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=WeMix" target="_blank">WeMix</a> v1.0.1: Provides functions to run mixed-effects models that include weights at every level. Models are fit using adaptive quadrature following the methodology of <a rel="nofollow" href="doi:10.1111/j.1467-985X.2006.00426.x" target="_blank">Rabe-Hesketh et. al (2006)</a>. There is a <a rel="nofollow" href="https://cran.r-project.org/web/packages/WeMix/vignettes/WeightedMixedModels.html" target="_blank">vignette</a>.</p>
<h3>Time Series</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=anomalize" target="_blank">anomalize</a> v0.1.1: Implements a “tidy” workflow for detecting anomalies in time series data. Functions decompose time series, detect anomalies, and create bands separating the “normal” data from the anomalous data for multiple time series. There is a <a rel="nofollow" href="https://cran.r-project.org/web/packages/anomalize/vignettes/anomalize_quick_start_guide.html" target="_blank">Quick Start Guide</a> and a vignette on <a rel="nofollow" href="https://cran.r-project.org/web/packages/anomalize/vignettes/anomalize_methods.html" target="_blank">Methods</a>.</p>
<p><img alt="" src="https://i2.wp.com/rviews.rstudio.com/post/2018-05-21-Rickert-AprilTop40_files/anomalize.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=LPWC" target="_blank">LPWC</a> v0.99.2: Provides functions to compute a time series distance measure for clustering based on weighted correlation and introduction of lags. See <a rel="nofollow" href="doi:10.1101/292615" target="_blank">Chandereng and Gitter (2018)</a> and the <a rel="nofollow" href="https://cran.r-project.org/web/packages/LPWC/vignettes/LPWC.html" target="_blank">vignette</a>.</p>
<h3>Utilities</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=table1" target="_blank">table1</a> v1.0: Provides functions to create HTML tables of descriptive statistics, as one would expect to see as the first table (i.e. “Table 1”) in a medical/epidemiological journal article. There is a <a rel="nofollow" href="https://cran.r-project.org/web/packages/table1/vignettes/table1-examples.html" target="_blank">vignette</a> that shows how to create a table of descriptive statistics.</p>
<p><img alt="" src="https://i0.wp.com/rviews.rstudio.com/post/2018-05-21-Rickert-AprilTop40_files/table1.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=foolbox" target="_blank">foolbox</a> v0.1.0: Provides a framework for manipulating functions and translating them with metaprogramming. There is a <a rel="nofollow" href="https://rviews.rstudio.com/2018/05/24/april-2018-top-40-new-packages/Foolbox%20tutorial" target="_blank">tutorial</a> and vignettes on <a rel="nofollow" href="https://cran.r-project.org/web/packages/foolbox/vignettes/partial-evaluation.html" target="_blank">Partial Evaluation</a> and <a rel="nofollow" href="https://cran.r-project.org/web/packages/foolbox/vignettes/transforming-functions-with-foolbox.html" target="_blank">Transforming Functions</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=graphframes" target="_blank">graphframes</a> v0.1.0: Implements a <a rel="nofollow" href="https://spark.rstudio.com/" target="_blank">sparklyr</a> extension that interfaces to <a rel="nofollow" href="https://graphframes.github.io/" target="_blank">GraphFrames</a>, an <code>Apache Spark</code> package that provides a DataFrame-based API for working with graphs. See <a rel="nofollow" href="https://cran.r-project.org/web/packages/graphframes/README.html" target="_blank">README</a> for some details.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=komaletter" target="_blank">komaletter</a> v0.2.0: Offers a versatile R Markdown template for writing letters, using the <code>KOMA-Script</code> letter class <code>scrlttr2</code> and an adaptation of the <code>pandoc-letter</code> template. There is an <a rel="nofollow" href="https://cran.r-project.org/web/packages/komaletter/vignettes/intro.html" target="_blank">Introduction</a> as well as three letter templates: <a rel="nofollow" href="https://cran.r-project.org/web/packages/komaletter/vignettes/letter_example1.pdf" target="_blank">letter1</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/komaletter/vignettes/letter_example2.pdf" target="_blank">letter2</a>, and <a rel="nofollow" href="https://cran.r-project.org/web/packages/komaletter/vignettes/letter_example3.pdf" target="_blank">letter3</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=pkgnet" target="_blank">pkgnet</a> v0.2.0: Uses tools from graph theory to analyze the dependencies between functions in an R package and between its imported packages and quantify their complexity and vulnerability to failure. There is a <a rel="nofollow" href="https://cran.r-project.org/web/packages/pkgnet/vignettes/pkgnet-intro.html" target="_blank">vignette</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=promises" target="_blank">promises</a> v1.0.1: Provides fundamental abstractions for doing asynchronous programming in R using promises. There are several vignettes: <a rel="nofollow" href="https://cran.r-project.org/web/packages/promises/vignettes/motivation.html" target="_blank">1. Why use promises?</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/promises/vignettes/intro.html" target="_blank">2. An informal introduction to async programming</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/promises/vignettes/overview.html" target="_blank">3. Working with promises in R</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/promises/vignettes/futures.html" target="_blank">4. Launching tasks with future</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/promises/vignettes/shiny.html" target="_blank">5. Using promises with Shiny</a>, and <a rel="nofollow" href="https://cran.r-project.org/web/packages/promises/vignettes/combining.html" target="_blank">6. Combining promises</a>.</p>
<h3>Visualization</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=ERSA" target="_blank">ERSA</a> v0.1.0: Provides functions for displaying the results of a regression calculation, packaged together as a <code>shiny</code> app. See the <a rel="nofollow" href="https://cran.r-project.org/web/packages/ERSA/vignettes/ERSA.html" target="_blank">Vignette</a></p>
<p><img alt="" src="https://i0.wp.com/rviews.rstudio.com/post/2018-05-21-Rickert-AprilTop40_files/ERSA.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=ggplotify" target="_blank">ggplotify</a> v0.0.2: Provides the means to convert plot function calls to <code>grob</code> or <code>ggplot</code> enabling users to align plots produced by <code>base</code> graphics, <code>grid</code>, <code>lattice</code> and <code>vcd</code> functions. See the <a rel="nofollow" href="https://cran.r-project.org/web/packages/ggplotify/vignettes/ggplotify.html" target="_blank">vignette</a>.</p>
<p><img alt="" src="https://i0.wp.com/rviews.rstudio.com/post/2018-05-21-Rickert-AprilTop40_files/ggplotify.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=ggstatsplot" target="_blank">ggstatsplot</a> v0.0.3: Extends <code>ggplot2</code> to produce graphics with details from statistical tests. There are vignettes for producing publication ready <a rel="nofollow" href="https://cran.r-project.org/web/packages/ggstatsplot/vignettes/ggbetweenstats.html" target="_blank">violin plots</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/ggstatsplot/vignettes/ggcorrmat.html" target="_blank">correlation plots</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/ggstatsplot/vignettes/gghistostats.html" target="_blank">histograms</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/ggstatsplot/vignettes/ggpiestats.html" target="_blank">pie charts</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/ggstatsplot/vignettes/ggscatterstats.html" target="_blank">scatter plots</a> as well as vignettes describing the <a rel="nofollow" href="https://cran.r-project.org/web/packages/ggstatsplot/vignettes/theme_mprl.html" target="_blank">default theme</a> and showing how to <a rel="nofollow" href="https://cran.r-project.org/web/packages/ggstatsplot/vignettes/combine_plots.html" target="_blank">combine plots</a>.</p>
<p><img alt="" src="https://i0.wp.com/rviews.rstudio.com/post/2018-05-21-Rickert-AprilTop40_files/ggstatsplot.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=panelView" target="_blank">panelView</a> v1.0.1: Provides functions to visualize panel data with dichotomous treatments. Look <a rel="nofollow" href="http://yiqingxu.org/software/panelView/panelView.html" target="_blank">here</a> for details.</p>
<p><img alt="" src="https://i1.wp.com/rviews.rstudio.com/post/2018-05-21-Rickert-AprilTop40_files/panelView.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=prepplot" target="_blank">prepplot</a> v0.7: Contains a single function to prepare a figure region for base graphics that makes it easy to produce customized graphics and produce <code>ggplot2</code> like plots. The <a rel="nofollow" href="https://cran.r-project.org/web/packages/prepplot/vignettes/prepplotOverview.pdf" target="_blank">vignette</a> explains how.</p>
<p><img alt="" src="https://i2.wp.com/rviews.rstudio.com/post/2018-05-21-Rickert-AprilTop40_files/prepplot.png?w=456&ssl=1" data-recalc-dims="1"></p>
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