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DiagrammeR:Graph/Network Visualization
Build graph/network structures using functions for stepwise addition and deletion of nodes and edges. Work with data available in tables for bulk addition of nodes, edges, and associated metadata. Use graph selections and traversals to apply changes to specific nodes or edges. A wide selection of graph algorithms allow for the analysis of graphs. Visualize the graphs and take advantage of any aesthetic properties assigned to nodes and edges.
Maintained by Richard Iannone. Last updated 2 months ago.
graphgraph-functionsnetwork-graphproperty-graphvisualization
1.7k stars 15.29 score 3.8k scripts 86 dependentsropensci
drake:A Pipeline Toolkit for Reproducible Computation at Scale
A general-purpose computational engine for data analysis, drake rebuilds intermediate data objects when their dependencies change, and it skips work when the results are already up to date. Not every execution starts from scratch, there is native support for parallel and distributed computing, and completed projects have tangible evidence that they are reproducible. Extensive documentation, from beginner-friendly tutorials to practical examples and more, is available at the reference website <https://docs.ropensci.org/drake/> and the online manual <https://books.ropensci.org/drake/>.
Maintained by William Michael Landau. Last updated 4 months ago.
data-sciencedrakehigh-performance-computingmakefilepeer-reviewedpipelinereproducibilityreproducible-researchropensciworkflow
1.3k stars 11.49 score 1.7k scripts 1 dependents