Skills DirectoryData & Analytics
Data analysis, BI, visualization, datasets, statistics, and ML workflows
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Showing 10,849–10,872 of 13,063 skills
R DT package for interactive data tables. Use for creating searchable, sortable, paginated HTML tables.
R gganimate package for animated ggplot2 plots. Use for creating animated visualizations with transitions.
R animation with gganimate. Use for animated plots, transitions, and GIF/video export.
R visualization packages. Use for static plots (ggplot2, lattice), interactive visualizations (plotly, leaflet, DT), animations (gganimate), and HTML widgets.
R magrittr package for pipe operators. Use for %>% pipe and functional programming chains.
R syntax extensions and pipe operators. Use for magrittr pipes, functional programming, and syntax enhancements.
R tseries package for time series analysis. Use for time series tests and GARCH models.
R feasts package for time series features. Use for extracting features and visualizing time series.
R packages for time series analysis. Use for time series modeling, forecasting, and analysis.
R nloptr package for nonlinear optimization. Use for solving nonlinear optimization problems with various algorithms.
R lpSolve package for linear programming. Use for solving linear and integer programming problems.
R optimization with ROI, lpSolve, nloptr. Use for linear programming, nonlinear optimization, and constraint solving.
R ROI package for optimization infrastructure. Use for unified interface to various optimization solvers.
R zoo package for ordered observations. Use for irregular time series and ordered indexed observations.
R xts package for extensible time series. Use for creating and manipulating time series objects.
R quantmod package for quantitative financial modeling. Use for downloading stock data and technical analysis.
R TTR package for technical trading rules. Use for technical analysis indicators and trading signals.
R quantitative finance with quantmod, PerformanceAnalytics, tidyquant. Use for stock data, portfolio analysis, and technical indicators.
R PerformanceAnalytics package for portfolio analysis. Use for risk metrics, performance attribution, and portfolio analytics.
R rstanarm package for applied Bayesian regression. Use for easy Bayesian models with familiar R formula syntax.
R rstan package for Stan interface. Use for full Bayesian inference with Stan probabilistic programming.
R coda package for MCMC diagnostics. Use for analyzing and diagnosing MCMC output.
R brms package for Bayesian regression. Use for fitting Bayesian models with Stan backend.
R Bayesian analysis with Stan, brms, rjags. Use for MCMC, posterior inference, and hierarchical models.