Search Results for "javascript open source" - Page 2

Showing 110 open source projects for "javascript open source"

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  • 1
    dplyr

    dplyr

    dplyr: A grammar of data manipulation

    dplyr is an R package that provides a consistent and intuitive grammar for data manipulation, enabling users to filter, arrange, summarize, and transform data efficiently. Part of the tidyverse ecosystem, dplyr simplifies complex data operations through a clear and readable syntax, whether working with data frames, tibbles, or databases. It is widely used in data science and statistical analysis workflows.
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  • 2
    workflowr

    workflowr

    Organize your project into a research website

    workflowr is an R package that helps researchers organize, version, and share their data science projects in a reproducible and transparent manner. It combines R Markdown, Git, and a structured file system to create a research website that tracks analysis, results, and code changes over time. It’s ideal for academic and collaborative research workflows.
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  • 3
    golem

    golem

    A Framework for Building Robust Shiny Apps

    golem is an opinionated framework for developing production-grade Shiny applications in R, treating the app like a full R package. It scaffolds project structure, testing, documentation, CI/CD, and supports containerization—streamlining the build-to-deploy pipeline while enforcing clean architecture and maintainability.
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  • 4
    ggforce

    ggforce

    Accelerating ggplot2

    ggforce is an extension package for ggplot2 that introduces specialized statistical transforms, geoms, and layout utilities to enhance and complement the built-in ggplot2 offerings. It enables more advanced visualization techniques such as faceting enhancements, hulls, annotation marks, and novel layouts for network data and marked regions.
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  • 5
    performance

    performance

    Models' quality and performance metrics (R2, ICC, LOO, AIC, BF, ...)

    performance is part of the easystats ecosystem and offers model quality assessment tools for R. It computes metrics like R², RMSE, ICC, and conducts diagnostics such as overdispersion, zero‑inflation, convergence, and singularity checks, complementing model workflows with comprehensive evaluation.
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  • 6
    lintr

    lintr

    Static Code Analysis for R

    lintr is a static code analysis tool for R that identifies syntax errors, style inconsistencies, and other potential issues in R scripts and packages. It supports customizable lint rules and integrates with many editors to provide realtime feedback and enforce coding standards (e.g., tidyverse style).
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  • 7
    caret

    caret

    caret (Classification And Regression Training) R package

    The caret (Classification And Regression Training) R package streamlines the process of building predictive machine learning models. It provides uniform interfaces for model training, tuning, evaluation, preprocessing, and variable importance. With support for over 200 models, caret is foundational for R workflows in modeling and machine learning.
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  • 8
    sparklyr

    sparklyr

    R interface for Apache Spark

    sparklyr is an R package that provides seamless interfacing with Apache Spark clusters—either local or remote—while letting users write code in familiar R paradigms. It supplies a dplyr-compatible backend, Spark machine learning pipelines, SQL integration, and I/O utilities to manipulate and analyze large datasets distributed across cluster environments.
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  • 9
    broom

    broom

    Convert statistical analysis objects from R into tidy format

    broom is part of the tidymodels ecosystem that converts statistical model outputs (e.g. from lm, glm, t.test, lme4, etc.) into tidy tibbles — standardized data frames — using functions tidy(), glance(), and augment(). These are easier to manipulate, visualize, and report programmatically.
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  • 10
    blogdown

    blogdown

    Create Blogs and Websites with R Markdown

    blogdown is an R package that enables the creation and maintenance of static websites and blogs using R Markdown and Hugo (or other static-site generators). Developed by Yihui Xie and team, it provides functions to initialize sites, write posts, manage themes, and deploy with minimal fuss. It seamlessly blends R code chunks and web content, ideal for data storytellers and technical bloggers.
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  • 11
    FriendsDon'tLetFriends

    FriendsDon'tLetFriends

    Friends don't let friends make certain types of data visualization

    Friends don't let friends make certain types of data visualization - What are they and why are they bad.
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  • 12
    ggstatsplot

    ggstatsplot

    Enhancing {ggplot2} plots with statistical analysis

    {ggstatsplot} is an extension of {ggplot2} package for creating graphics with details from statistical tests included in the information-rich plots themselves. 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...
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  • 13
    reticulate

    reticulate

    R Interface to Python

    reticulate is an R package from Posit that creates seamless interoperability between R and Python. It lets you call Python modules, classes, and functions from within R, automatically translating between R and Python data structures. Useful for combining Python tooling with R projects, data analysis, and RMarkdown reports.
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  • 14
    pagedown

    pagedown

    Paginate the HTML Output of R Markdown with CSS for Print

    Paginate the HTML Output of R Markdown with CSS for Print. You only need a modern web browser (e.g., Google Chrome or Microsoft Edge) to generate PDF. No need to install LaTeX to get beautiful PDFs. This R package stands on the shoulders of two giants to support typesetting with CSS for R Markdown documents: Paged.js and ReLaXed (we only borrowed some CSS from the ReLaXed repo and didn't really use the Node package).
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  • 15
    esquisse

    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. This addin allows you to...
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  • 16
    Huxtable

    Huxtable

    An R package to create styled tables in multiple output formats

    Huxtable is an R package to create LaTeX and HTML tables, with a friendly, modern interface. Features include control over text styling, number format, background color, borders, padding, and alignment. Cells can span multiple rows and/or columns. Tables can be manipulated with standard R subsetting or dplyr functions.
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  • 17
    JuliaConnectoR

    JuliaConnectoR

    A functionally oriented interface for calling Julia from R

    This R-package provides a functionally oriented interface between R and Julia. The goal is to call functions from Julia packages directly as R functions. Julia functions imported via the JuliaConnectoR can accept and return R variables. It is also possible to pass R functions as arguments in place of Julia functions, which allows callbacks from Julia to R. From a technical perspective, R data structures are serialized with an optimized custom streaming format, sent to a (local) Julia TCP...
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  • 18
    CausalImpact

    CausalImpact

    An R package for causal inference in time series

    The CausalImpact repository houses an R package that implements causal inference in time series using Bayesian structural time series models. Its goal is to estimate the effect of an intervention (e.g. a marketing campaign, policy change) on a time series outcome by predicting what would have happened in a counterfactual “no intervention” world. The package requires as input a response time series plus one or more control (covariate) time series that are assumed unaffected by the...
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  • 19
    paletteer

    paletteer

    Collection of most color palettes in a single R package

    paletteer is an R package by Emil Hvitfeldt that aggregates color palettes from many other R packages, providing a unified, streamlined interface to access discrete, continuous, and dynamic palettes. It is intended to simplify choosing color schemes when plotting, remove the friction of remembering different palette package APIs, and make high‐quality color aesthetics more accessible. Some palettes change depending on the number of colors requested; the ability to reverse palettes. Support...
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  • 20
    gt R

    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). You then decide how to compose your gt table with the elements and formatting you need for the task at...
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  • 21
    see

    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...
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  • 22
    ggrepel

    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...
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  • 23
    nichenetr

    nichenetr

    NicheNet: predict active ligand-target links between interacting cells

    nichenetr: the R implementation of the NicheNet method. The goal of NicheNet is to study intercellular communication from a computational perspective. NicheNet uses human or mouse gene expression data of interacting cells as input and combines this with a prior model that integrates existing knowledge on ligand-to-target signaling paths. This allows to predict ligand-receptor interactions that might drive gene expression changes in cells of interest. This model of prior information on...
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  • 24
    Paper2GUI

    Paper2GUI

    Convert AI papers to GUI

    Convert AI papers to GUI,Make it easy and convenient for everyone to use artificial intelligence technology。让每个人都简单方便的使用前沿人工智能技术 Paper2GUI: An AI desktop APP toolbox for ordinary people. It can be used immediately without installation. It already supports 40+ AI models, covering AI painting, speech synthesis, video frame complementing, video super-resolution, object detection, and image stylization. , OCR recognition and other fields. Support Windows, Mac, Linux systems. Paper2GUI:...
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  • 25
    reprex

    reprex

    Render bits of R code for sharing, e.g., on GitHub or StackOverflow

    reprex is an R package (from the tidyverse / Posit ecosystem) that helps users make reproducible examples (reprexes) of R code: self-contained, shareable, minimal examples capturing an issue or showing desired behavior. It formats code and its output nicely (often using Markdown or syntax appropriate to posting on forums, GitHub, StackOverflow etc.), handles dependencies, session info, etc. The goal is to make debugging, asking for help, or demonstrating code easier through rigorous...
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