R Packages for Data Science
- Development
- Collection
- Storage
- Data Structure
- Databases
- Data Transformation
- Data Validation and Cleaning
- Data Inspection and Summary
- Visualization
- Feature Transformation
- Feature Filtering and Dimension Reduction
- Feature Selection and Importance
- Preprocessing
- Models and Statistics
- Resampling
- Hyperparameter Optimization
- Performance
- Interpretation
- Report and Deploy
- devtools: tools for package development
- usethis: automated package tasks
- pacman: package installation/loading utilities
- import: import single functions from a package
- packrat: reproducible development with local package installation
- jetpack: lightweight dependency management for projects and local installs
- checkpoint: install packages from a specific time and date
- config: configuration file management
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testthat:
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assertthat:
- butcher: remove unneeded data from a model
- insight: extract model parameters; see also other packages by the same author
- wrapr: operators and environments
- zeallot: destructuring assignment
- fastpipe: efficient pipe operators
- rio: universal import and export
- opendata: Task View
- tabulizer: pdf table scraping
- RData: native dataframe storage
- RDS: native R objects
- fst: a fast read/write format, like feather
- archivist: collections of objects for reproducibility
- base::data.frame: tabular data
- data.table: efficient data frames
- tibble: user-friendly data frames
- disk.frame: for mid-sized data sets too large to fit in RAM
- Matrix:
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base::ts:
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zoo:
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xts: comprehensive library for timeseries built on zoo
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tidyverts: tidy tools for time series
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tsbox: universal time series converter and utilites
- DBI: for database connections
- dbplyr: dplyr db interface
- rquery: query generator
- dplyr: piped data transformations
- dtplyr: `dplyr` interface to `data.table`
- seplyr: evaluation extensions for dplyr Quoted evaluation, evaluation partitioning.
- cdata: generalized pivots using data description
- forcats: categorical transformations
- stringr: string manipulation
- validate: powerful validation framework with error localization, imputation, and reporting
- janitor: common cleaning operations
- dataMaid: common checks and report generation
- OpenRefine: Java app for cleaning and formatting
- rrefine: R interface to OpenRefine
- assertr: similar to validate but more lightweight
- OfficialStatistics: CRAN view
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inspectdf: text summary and plots
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visdat: data visualization
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UpSetR: intersecting set visualization
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corrplot:
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base::head:
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utils::str:
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dplyr::glimpse:
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base::summary: summary statistics
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skimr: text summary
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HMisc::describe: text summary
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finalfit::ffglimpse: text summary
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DescTools: Abstract and Describe, text summary and plots
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DataExplorer: text summary and plots, reporting
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base:
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lattice:
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vcd: categorical plots in a lattice framework
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ggplot2: see here for a list of extensions
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cowplot: various extensions to ggplot, themes, formatting, gridplot of all classes
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GGally: various extensions to ggplot, model diagnostics, formatting, and more
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ggExtra: marginal plots for ggplot
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ggpmisc: various extensions, drawing on plots, time series with peaks and valleys , stat plots with embedded statistics
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WVPlots: explanatory and comparison plots in ggplot; "prescribed presentations"
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ggfortify: `autoplot` for a large number of packages
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ggRandomForests:
- naniar: (check out the vignettes, too)
- VIM: imputation of NA data and visualization its distribution
- mice: multiple imputation
- MissMech: tests for the nature of missingness
- finalfit: various plots and reports
- acepack: regression transform selection
- homals: optimal scaling transforms
- aspect: optimal scaling transforms
- vtreat: "y-aware" scaling
- factorMerger: factor response clustering
- vip: variable importance plots
- varImp: variable importance for random forests
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vtreat:
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recipes:
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mlrCPO:
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nns: nonlinear nonparametric statistics with partial moments; classification, clustering and regression, correlation and dependence, forecasting
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forecast:
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smooth:
- vtreat: has CV index generating functions
- sampler:
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mlrMBO:
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IRACE:
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mlr:
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dials:
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performance:
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plotmo: residuals, response, partial dependence
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visreg: regression plots
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car: regression plots
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gamlss::wp: wormplots
- DrWhy: comprehensive collection of tools for exploration and interpretation homepage github - a great resource; lots of interesting and useful packages Predictive Models: Explore, Explain, Debug - book by the authors of DrWhy
- DALEX: local and global interpretation of variables tutorial
- iml: local and global interpretation of variables with interaction support tutorial
- LIME: local interpretation of variables tutorial
- finalfit: creates formatted tables of many types
- dashR: R interface to plotly's Dash framework
- shiny: