La cultura actual de "competencias" y "prácticas" supone que a una persona se le enseñan algunos enfoques y recetas para resolver un conjunto de problemas. Al mismo tiempo, el momento de la relevancia de estas "recetas" está oculto detrás del marco y, de hecho, se convierten en un monolito, replicado por una persona durante años. A veces escuchamos dichos sobre "mejores prácticas" que ya tienen 30 años y durante este tiempo han pasado varios cambios de paradigma. Y con esta "mejor práctica" pareces estar en una cápsula del tiempo.
Sí, es mentalmente conveniente y ahorra la energía del "especialista". Sí, crea una sensación de estabilidad. Pero para un trabajo de alta calidad y eficiente, es necesario corregir y afinar constantemente la herramienta.
El 2020 R es muy diferente del 2018 R. En el código muy básico, se han realizado cambios significativos para mejorar la eficiencia y la estabilidad (velocidad y consumo de memoria). Pero la parte más dinámica del ecosistema son los paquetes. Es útil revisar su colección periódicamente para pasar a implementaciones más convenientes y eficientes. Desde la última publicación del "conjunto de paquetes R de Gentleman para automatizar las tareas comerciales" , los paquetes se han sometido a importantes actualizaciones y su rango se ha expandido significativamente y los líderes han cambiado de lugar muchas veces.
No es ningún secreto que la corriente principal no significa la máxima eficiencia y versatilidad. De acuerdo con la corriente principal, es muy fácil perder paquetes que son gemas. Es especialmente conveniente abrirlos en conferencias R UseR!, Rconf, eRum, etc.
A continuación se muestra una lista de paquetes de uso general que resultan muy útiles para las tareas cotidianas (paquetes x de> 10K en CRAN). A menudo resulta que muchos elementos nuevos son desconocidos para los interlocutores. Para una revisión resumida del corte para julio de 2020, lo publico como una compilación. Los enlaces, en la mayoría de los casos, conducen a una página de recopilación de características. Estoy seguro de que todos encontrarán algo útil para ellos.
R: EDA
- arsenal: un arsenal de funciones 'R' para resúmenes estadísticos a gran escala
- paquete compareGroups
- DataExplorer: Automate Data Exploration and Treatment
- diff & compare
- funModeling quick-start
- gtsummary: Presentation-Ready Data Summary and Analytic Result Tables
- XanderHorn/autoEDA: Automated exploratory data analysis
- ekstroem/dataMaid: An R package for data screening
- rolkra/explore: R package that makes basic data exploration radically simple (interactive data exploration, reproducible data science)
- skimr (rOpenSci): Compact and Flexible Summaries of Data
- inspectdf: Inspection, Comparison and Visualisation of Data Frames
- rspivot: View data frames as Shiny pivot tables
- summarytools: R Package for quickly and neatly summarizing vectors and dataframes
- visdat: Preliminary Visualisation of Data
R: data_pkg
- arrangements: Fast Generators and Iterators for Permutations, Combinations, Integer Partitions and Compositions
- Arrow R Package: Integration to Apache Arrow
- batchtools: Tools for Computation on Batch Systems
- bigreadr: Read Large Text Files
- bupaR: Business Process Analysis in R
- business-science
- anomalize: Tidy Anomaly Detection
- sweep: Tidy Tools for Forecasting
- tidyquant: Tidy Quantitative Financial Analysis
- timetk: A Tool Kit for Working with Time Series in R
- modeltime: The tidymodels extension for time series modeling
- correlationfunnel: Speed Up Exploratory Data Analysis (EDA) with the Correlation Funnel
- carbonate: Interact with carbon.js
- checkmate: Fast and Versatile Argument Checks
- crrri: An interface with headless Chromium/Chrome
- data.table: Extension of `data.frame`
- datapasta: R Tools for Data Copy-Pasta
- dm: Relational Data Models
- dplyr: A Grammar of Data Manipulation
- docxtractr: Extract Tables from Microsoft Word Documents with R
- drake (rOpenSci): A Pipeline Toolkit for Reproducible Computation at Scale
- fake data
- forcats: Tools for Working with Categorical Variables (Factors)
- friendlyeval: A friendly interface to the tidy eval framework
- fs: Cross-Platform File System Operations Based on libuv
- fst: Lightning Fast Serialization of Data Frames for R
- fuzzyjoin: Join Tables Together on Inexact Matching
- gargle: Utilities for Working with Google APIs
- glue: Interpreted String Literals
- goodpress: From R Markdown to WordPress with a Modern Stack
- hts: Hierarchical and Grouped Time Series
- httr: Tools for Working with URLs and HTTP
- igraph R package
- imputeTS: Time Series Missing Value Imputation
- infer: Tidy Statistical Inference
- inferr: Tools for Inferential Statistics
- ipaddress: This package provides classes for working with IP addresses
- janitor: Simple Tools for Examining and Cleaning Dirty Data
- labelled: Manipulating Labelled Data
- lubridate: Make Dealing with Dates a Little Easier
- magrittr: A Forward-Pipe Operator for R
- naniar: Data Structures, Summaries, and Visualisations for Missing Data
- officedown: Enhanced R Markdown Format for Word and PowerPoint
- officer: Manipulation of Microsoft Word and PowerPoint Documents
- openxlsx: Read, Write and Edit xlsx Files
- palmerpenguins: Palmer Station LTER Penguins Data
- panelr: Regression Models and Utilities for Repeated Measures and Panel Data
- parsnip: A Common API to Modeling and Analysis Functions
- pillar: Coloured Formatting for Columns
- pointblank: Validation of Local and Remote Data Tables
- polite: Be Nice on the Web
- poorman: A copy of dplyr verbs using only base R
- purrr: Functional Programming Tools
- qdapRegex: A collection of regular expression tools associated with the qdap package
- qs: Quick serialization of R objects
- R6: Encapsulated Classes with Reference Semantics
- rainette: The Reinert Method for Textual Data Clustering
- rbin: Tools for Binning Data
- RcppSimdJSON: Rcpp Bindings for the simdjson Header Library
- re2r: Regular Expressions with re2
- readr: Read Rectangular Text Data
- readxl: Read Excel Files
- reprex: Prepare Reproducible Example Code via the Clipboard
- santoku: A Versatile Cutting Tool for R
- slider: Sliding Window Functions
- stringi: THE R package for… string/text processing
- stringr: Simple, Consistent Wrappers for Common String Operations
- text2vec
- tibble: Simple Data Frames
- tidyfast: Fast Tidying of Data based on data.table
- tidyfst: Tidy Verbs for Fast Data Manipulation
- tidylog: Logging for 'dplyr' and 'tidyr' Functions
- tidync: A Tidy Approach to NetCDF Data Exploration and Extraction
- tidyverts
- Ttidyverts Landing
- tidyverts/fable: Forecasting Models for Tidy Time Series
- fabletools: Core Tools for Packages in the fable Framework
- tidyverts/feasts: Feature Extraction and Statistics for Time Series
- tidyverts/tsibble: Tidy Temporal Data Frames and Tools
- tidyverts/tsibbledata: Example datasets for tsibble
- sugrrants: Supporting Graphs for Analysing Time Series
- tidyxl: Read Untidy Excel Files
- tidyr: Tidy Messy Data
- tidyselect: Select from a Set of Strings
- trimmer: toolkit to trim R objects
- tsbox: Class-Agnostic Time Series
- usethis: Automate Package and Project Setup
- vctrs: Vector Helpers
- vroom: Read and Write Rectangular Text Data Quickly
- vtreat: A Statistically Sound data.frame Processor/Conditioner
- withr: Run Code With Temporarily Modified Global State
- ymlthis: Write YAML for R Markdown, bookdown, blogdown, and More
- xslt (rOpenSci): Extensible Style-Sheet Language Transformations
- xml2: Parse XML
R: algo_pkg
- bayesAB: Fast Bayesian Methods for AB Testing
- broom: Convert Statistical Objects into Tidy Tibbles
- bupaR: Business Process Analysis in R
- caracas: Computer Algebra
- DrWhy: Explain, Explore and Debug Predictive Machine Learning Models
- easystats
- bayestestR: Understand and Describe Bayesian Models and Posterior Distributions
- estimate: Estimate Effects, Contrasts and Means
- insight: Easy Access to Model Information for Various Model Objects
- parameters: Processing of Model Parameters
- performance: Assessment of Regression Models Performance
- report: Automated reporting of statistical models in R
- see: Visualisation Toolbox for easystats and Extra Geoms, Themes and Color Palettes for ggplot2
- gratia: An R package for working with generalized additive models • gratia
- greta: Simple and Scalable Statistical Modelling in R
- ML
- breakDown: Model Agnostic Explainers for Individual Predictions
- C50: C5.0 Decision Trees and Rule-Based Models
- The caret Package
- DALEX: moDel Agnostic Language for Exploration and eXplanation
- keras: R Interface to 'Keras'
- lime: Local Interpretable Model-Agnostic Explanations
- mlr3: Machine Learning in R
- TensorFlow for R: TensorFlow for R Blog
- modelr: Modelling Functions that Work with the Pipe
- precisely: Estimate Sample Size Based on Precision Rather than Power
- propro: Build Probabilistic Process Models Using MCMC
- quanteda: Quantitative Analysis of Textual Data
- R: Optimisations in data.table
- sbmr: Fit and investigate Stochastic Block Models in R
- simmer: Discrete-Event Simulation for R
- stats
- tidybayes: Tidy Data and Geoms for Bayesian Models
- jonathan-g/datafsm: Learning Finite State Machine Models from Data with a Genetic Algorithm
- tidymodels
- Tidymodels landing
- embed: Extra Recipes for Encoding Categorical Predictors
- corrr: Correlations in R
- hardhat: Construct Modeling Packages
- recipes: Preprocessing Tools to Create Design Matrices
- rsample: General Resampling Infrastructure
- rules: Model Wrappers for Rule-Based Models
- tune: Tidy Tuning Tools
- yardstick: Tidy Characterizations of Model Performance
R: vis_pkg
- Tables
- ggplot2 themes & colours
- ggthemes: Function reference
- ggthemes: demo
- cttobin/ggthemr: Themes for ggplot2.
- ghibli: Studio Ghibli Colour Palettes
- HCL Wizard — Somewhere over the Rainbow
- olorspace: Function reference
- Polychrome: Plots of Many Colors
- ggtext: Function reference
- ggplot2 extensions
- ggsci: Scientific Journal and Sci-Fi Themed Color Palettes for ggplot2
- hrbrthemes: Additional Themes, Theme Components and Utilities for 'ggplot2'
- paletteer: Comprehensive Collection of Color Palettes
- scico: Palettes for R based on the Scientific Colour-Maps
- Tol Color Schemes — The USGS OWI blog
- ceramic: Download Online Imagery Tiles
- cowplot: Streamlined Plot Theme and Plot Annotations for 'ggplot2'
- dataui: dataui and reactable
- daranzolin/d3rain: An htmlwidget bringing D3 drip to R
- DiagrammeR: Graph/Network Visualization
- DiagrammeR — Documentation
- echarts4r: Create Interactive Graphs with 'Echarts JavaScript' Version 4
- factoextra: Extract and Visualize the Results of Multivariate Data Analyses
- farver: High Performance Colour Space Manipulation
- ggalluvial: Alluvial Plots in ggplot2
- GGally: Extension to ggplot2
- ggalt: Extra Coordinate Systems, 'Geoms', Statistical Transformations, Scales and Fonts for 'ggplot2'
- gganimate: A Grammar of Animated Graphics
- ggchicklet: Create Chicklet (Rounded Segmented Column) Charts
- ggExtra: Add marginal histograms to ggplot2, and more ggplot2 enhancements
- gghighlight: Highlight Lines and Points in ggplot2
- ggiraph: Make ggplot2 Graphics Interactive
- ggfittext: Fit Text Inside a Box in ggplot2
- ggforce: Accelerating ggplot2
- gghdr: Visualisation of Highest Density Regions (HDR) using ggplot2
- ggnet2: network visualization with ggplot2
- ggnewscale: Multiple Fill and Colour Scales in ggplot2
- ggpage: Creates Page Layout Visualizations
- ggparty: Graphic Partying
- ggplot2: Create Elegant Data Visualisations Using the Grammar of Graphics
- ggpubr: ggplot2 Based Publication Ready Plots
- ggrepel: Automatically Position Non-Overlapping Text Labels with ggplot2
- ggridges: Ridgeline Plots in 'ggplot2'
- ggrough: Convert ggplot2 charts to roughjs
- ggsignif: Easily add significance brackets to your ggplots
- ggtextures: Drawing textured rectangles and bars with ggplot
- Highcharter
- Leaflet for R — Introduction
- mschart: Chart Generation for 'Microsoft Word' and 'Microsoft PowerPoint' Documents
- parcats: Interactive Parallel Categories Diagrams for easyalluvial
- patchwork: The Composer of Plots
- practicalgg: Practical ggplot2
- prettyunits: Pretty, human readable formatting of quantities
- processanimateR: Process Map Token Replay Animation
- r2d3: Interface to 'D3' Visualizations
- ragg: Graphic Devices Based on AGG
- rayshader: Create Maps and Visualize Data in 2D and 3D
- scales: Scale Functions for Visualization
- showtext: Using Fonts More Easily in R Graphs
- streamgraph: htmlwidgtet R Package
- trelliscopejs: Create Interactive Trelliscope Displays
- vega-lite
- volcano3D: Interactive Plotting of Three-Way Differential Expression Analysis
- raivokolde/pheatmap: Pretty heatmaps
- A 'Bootstrap 4' Version of 'shinydashboard' • bs4Dash
- The R Graph Gallery – Inspiration and Help with R Graphics
- gallery.htmlwidgets.org
- From data to Viz | Find the graphic you need
- tabplot: Visualization of large datasets
- JohnCoene/grapher: ️ Interactive graphs
R: sys_pkg
- datadrivencv: An R package for building your CV with data
- R Documentation and manuals | R Documentation
- attempt: Tools for Defensive Programming
- bench: High Precision Timing of R Expressions
- callr: Call R from R
- conflicted: An Alternative Conflict Resolution Strategy
- r-lib/covr: Test coverage reports for R
- lrberge/dreamerr: Error Handling Made Easy, in R
- ellipsis: Tools for Working with ...
- emayili: Send email messages
- Environments: Reproducible Environments
- fastmap: Fast Implementation of a Key-Value Store
- fledge: Wings for Your R Packages
- git2r (rOpenSci): programmatic access to Git repositories
- here: A Simpler Way to Find Your Files
- r-lib/itdepends: itdepends provides tools to assess usage, measure weights, visualize proportions and assist removal of dependencies
- stedolan/jq: Wiki FAQ
- r-lib/later: Schedule an R function or formula to run after a specified period of time.
- lgr: A Fully Featured Logging Framework
- jimhester/lintr: Static Code Analysis for R
- loadtest: This package is to make load testing of APIs
- lobstr: Visualize R Data Structures with Trees
- logger: A Lightweight, Modern and Flexible Logging Utility
- pak: Another Approach to Package Installation
- pander: An R Pandoc Writer
- parallel computing
- HenrikBengtsson/doFuture: R package: doFuture — A Universal Foreach Parallel Adaptor using the Future API of the 'future' Package
- furrr: Apply Mapping Functions in Parallel using Futures
- HenrikBengtsson/future: R package: future: Unified Parallel and Distributed Processing in R for Everyone
- r-lib/progress: Progress bar in your R terminal
- progressr: An Inclusive, Unifying API for Progress Updates
- pins: Pin, Discover and Share Resources
- plumber: An API Generator for R
- precommit: Pre-commit Hooks for R
- processx: Execute and Control System Processes
- proffer: Profile R Code and Visualize with Pprof
- profvis: Interactive Visualizations for Profiling R Code
- projmgr: Task Tracking and Project Management with GitHub
- ps: List, Query, Manipulate System Processes
- rco: The R Code Optimizer
- remotes: R Package Installation from Remote Repositories, Including 'GitHub'
- redoc: Reversible Reproducible Documents
- renv: Project Environments
- reticulate: Interface to Python
- rcmdcheck: Run R CMD check from R and collect the results
- rlang: Functions for Base Types and Core R and Tidyverse Features
- rprojroot: Finding Files in Project Subdirectories
- styler: Non-Invasive Pretty Printing of R Code
- testthat: Unit Testing for R
- tinytest: A lightweight, no-dependency, but full-featured package for unit testing in R
- usethis: Automate Package and Project Setup
- r-lib/vdiffr: Visual regression testing and graphical diffing with testthat
- r-lib/waldo: Find Differences Between R Objects
R: shiny+Rmarkdown
- bootstraplib: Tools for styling shiny and rmarkdown from R via Bootstrap (3 or 4) Sass
- colourpicker: A colour picker tool for Shiny and for selecting colours in plots (in R)
- dreamRs/colorscale: Create a color scale from a single color
- details: Create Details HTML Tag for Markdown and Package Documentation
- excelR: A Wrapper of the 'JavaScript' Library 'jExcel'
- ezknitr (rOpenSci): Avoid the Typical Working Directory Pain When Using knitr
- flair: Highlight, Annotate, and Format your R Source Code
- golem: A Framework for Robust Shiny Applications
- grillade: Grid System for the Web
- metathis: HTML Metadata Tags for R Markdown and Shiny
- namer: The goal of namer is to name the chunks of R Markdown files
- reactR: React Helpers
- reactlog: Reactivity Visualizer for 'shiny'
- RinteRface
- rintrojs: Wrapper for the 'Intro.js' Library
- sass: Syntactically Awesome Style Sheets (Sass)
- shiny: R package that makes it easy to build interactive web apps straight from R
- datacamp/shinybones: A highly opinionated framework for building shiny dashboards.
- shinyglide: Glide Component for Shiny Applications
- shinyjqui: jQuery UI Interactions and Effects for Shiny
- shinymeta: Record and Expose Shiny App Logic using Metaprogramming
- shinytest: Test Shiny Apps
- sortable: Drag-and-Drop in shiny Apps with SortableJS
- thematic: Unified and Automatic Theming of ggplot2, lattice, and base R Graphics
- xaringanthemer: Custom xaringan CSS Themes
- JohnCoene/marker: Dynamically Highlight Text in Shiny
- CRAN — Package dqshiny
- CRAN — Package shinyFiles
- The YAML Fieldguide
- ymlthis: Escribe YAML para R Markdown, bookdown, blogdown y más
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