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Showing 15 open source projects for "can"
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1
plotly
An interactive graphing library for R
...There are two main ways to creating a plotly object: either by transforming a ggplot2 object (via ggplotly()) into a plotly object or by directly initializing a plotly object with plot_ly()/plot_geo()/plot_mapbox(). Both approaches have somewhat complementary strengths and weaknesses, so it can pay off to learn both approaches. Moreover, both approaches are an implementation of the Grammar of Graphics and both are powered by the JavaScript graphing library plotly.js, so many of the same concepts and tools that you learn for one interface can be reused in the other. Any graph made with the plotly R package is powered by the JavaScript library plotly.js. ... -
2
ggrepel
epel overlapping text labels away from each other in your ggplot2
ggrepel is an R package that provides “smart” repulsion for text and label geoms in ggplot2. When placing text labels on a plot (e.g. labeling points), the labels can often overlap; ggrepel ensures labels don’t overlap (or overlap less) by repelling labels / pushing them away, adding connecting lines or nudges, etc. It improves the readability of plots, especially when many labels are present. Support for point and segment geoms (so labels can be connected by lines when moved). Supports both plotting of labels inside or outside plot area, with trimming/clipping etc. -
3
pointblank
Data quality assessment and metadata reporting for data frames
...For that, we can use an informant object plus associated functions to help define the metadata entries and present it as a data dictionary. -
4
gt R
Easily generate information-rich, publication-quality tables from R
With the gt package, anyone can make wonderful-looking tables using the R programming language. The gt philosophy: we can construct a wide variety of useful tables with a cohesive set of table parts. These include the table header, the stub, the column labels and spanner column labels, the table body, and the table footer. It all begins with table data (be it a tibble or a data frame). -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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5
rayshader
R Package for 2D and 3D mapping and data visualization
...The package can export models to 3D formats like STL or OBJ for 3D printing or external rendering. -
6
nichenetr
NicheNet: predict active ligand-target links between interacting cells
...This allows to predict ligand-receptor interactions that might drive gene expression changes in cells of interest. This model of prior information on potential ligand-target links can then be used to infer active ligand-target links between interacting cells. NicheNet prioritizes ligands according to their activity (i.e., how well they predict observed changes in gene expression in the receiver cell) and looks for affected targets with high potential to be regulated by these prioritized ligands. -
7
clusterProfiler
A universal enrichment tool for interpreting omics data
...It supports both over-representation analysis and gene set enrichment analysis, letting you work with unranked gene lists or ranked statistics from differential pipelines. The package connects to multiple knowledge bases—such as Gene Ontology, KEGG, Reactome, Disease Ontology, MeSH and others—through a consistent interface so you can query different biological lenses without rewriting code. It is designed for breadth, covering coding and non-coding features and thousands of organisms by leveraging continuously updated annotations. Results are returned in tidy, manipulation-friendly structures and pair naturally with rich visualization functions (via companion tooling) to summarize pathways, terms, and gene–set relationships. -
8
esquisse
RStudio add-in to make plots interactively with ggplot2
The purpose of this add-in is to let you explore your data quickly to extract the information they hold. You can create visualization with {ggplot2}, filter data with {dplyr} and retrieve generated code. This addin allows you to interactively explore your data by visualizing it with the ggplot2 package. It allows you to draw bar plots, curves, scatter plots, histograms, boxplot and sf objects, then export the graph or retrieve the code to reproduce the graph. -
9
JuliaConnectoR
A functionally oriented interface for calling Julia from R
...The results of function calls are likewise translated back to R. Complex Julia structures can either be used by reference via proxy objects in R or fully translated to R data structures. -
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10
targets
Function-oriented Make-like declarative workflows for R
...It’s something like GNU Make for R, but more integrated. Skipping computation for up-to-date targets so that unchanged parts of the workflow are not recomputed. Targets can represent files or R objects, and tracking file changes etc is incorporated. -
11
gganimate
A Grammar of Animated Graphics
...We define that when a box appears it should fade into view, whereas it should shrink away when it disappears. Lastly, we decide to use a sinusoidal easing for all our aesthetics (here, only y is changing) gganimate is available on CRAN and can be installed with install.packages('gganimate'). -
12
ggstatsplot
Enhancing {ggplot2} plots with statistical analysis
...In a typical exploratory data analysis workflow, data visualization and statistical modeling are two different phases: visualization informs modeling, and modeling in its turn can suggest a different visualization method, and so on and so forth. Bayesian hypothesis-testing. The central idea of {ggstatsplot} is simple: combine these two phases into one in the form of graphics with statistical details, which makes data exploration simpler and faster. Summary of statistical tests and effect sizes. -
13
see
Visualisation toolbox for beautiful and publication-ready figures
see is an R package that serves as the visualization component of the easystats ecosystem, providing plotting utilities to produce publication-ready visualizations of statistical model parameters, diagnostics, predictions, and performance metrics. It works in conjunction with other easystats packages (such as parameters, performance, modelbased, bayestestR, etc.) to convert model outputs or summary objects into visual forms (dot-and-whisker plots, diagnostic plots, residual plots, etc.). It... -
14
Wes Anderson Palettes
A Wes Anderson color palette for R
Tired of generic mass produced palettes for your plots? Short of adding an owl and dressing up your plot in a bowler hat, here’s the most indie thing you can do to one. The first round of palettes derived from the amazing Tumblr blog Wes Anderson Palettes. -
15
circlize
Circular visualization in R
...It provides low-level drawing functions as well as high-level functions to build complex visualizations. It’s often used in genomics, network analysis, or other fields where relationships among categories or entities can be nicely displayed in a circular fashion. Support for circular heatmaps, multiple tracks (rings), for showing multiple layers of data per sector. Good performance and stable codebase, detailed documentation including a book on usage examples.
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