Data & Analytics

R sentiment analysis with tidytext, syuzhet, sentimentr. Use for sentiment scoring and emotion detection.

R natural language processing packages. Use for text mining, sentiment analysis, topic modeling, tokenization, and text vectorization.

R ggraph package for network visualization. Use for grammar of graphics style network plots.

R network visualization with ggraph, visNetwork. Use for graph layouts and interactive networks.

R tsna package for temporal network analysis. Use for analyzing temporal paths and metrics in dynamic networks.

R networkDynamic package for temporal networks. Use for creating and manipulating dynamic/temporal networks.

R ndtv package for network animation. Use for visualizing and animating dynamic networks.

R dynamic/temporal networks with ndtv, networkDynamic, tsna. Use for time-varying networks and network evolution.

R tidygraph package for tidy graph manipulation. Use for dplyr-style operations on network data.

R statnet suite for network analysis. Use for statistical modeling of network data including ERGM.

R sna package for social network analysis. Use for network statistics and visualization with statnet.

R network package for network data. Use for creating and manipulating network objects.

R igraph package for network analysis. Use for graph creation, analysis, centrality, community detection, and visualization.

R network analysis with igraph, sna. Use for centrality, community detection, and network metrics.

R network analysis packages. Use for graph analysis, social network analysis, network visualization, and community detection.

R ranger package for random forests. Use for fast implementation of random forests for classification and regression.

R tree-based models. Use for random forests, decision trees, and ensemble methods with ranger, randomForest, rpart.

R tsibble package for tidy time series. Use for temporal data structures with tidyverse integration.

R prophet package for time series forecasting. Use for forecasting with seasonality, holidays, and trend changes.

R forecast package for time series forecasting. Use for ARIMA, ETS, and automatic forecasting.

R fable package for tidy time series forecasting. Use for modern forecasting with tsibble integration.

R time series forecasting. Use for prophet, forecast, fable, ARIMA, and exponential smoothing.

R survminer package for survival visualization. Use for publication-ready Kaplan-Meier plots and forest plots.

R survival package for survival analysis. Use for Kaplan-Meier curves, Cox regression, and time-to-event analysis.