Showing 24 open source projects for "package installer linux"

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  • 1
    plotly

    plotly

    An interactive graphing library for R

    This part of the book teaches you how to leverage the plotly R package to create a variety of interactive graphics. 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...
    Downloads: 2 This Week
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  • 2
    gtsummary

    gtsummary

    Presentation-Ready Data Summary and Analytic Result Tables

    gtsummary is an R package for creating elegant, customizable, publication-ready summary tables of datasets and statistical models. It provides concise code to produce demographic tables (tbl_summary()), regression result tables, and more, with flexible styling options for reporting.
    Downloads: 9 This Week
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  • 3
    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...
    Downloads: 2 This Week
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  • 4
    clusterProfiler

    clusterProfiler

    A universal enrichment tool for interpreting omics data

    clusterProfiler is an R/Bioconductor package that provides a unified workflow for functional enrichment analysis to interpret high-throughput omics results. 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...
    Downloads: 2 This Week
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  • 5
    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...
    Downloads: 2 This Week
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  • 6
    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.
    Downloads: 0 This Week
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  • 7
    pointblank

    pointblank

    Data quality assessment and metadata reporting for data frames

    With the pointblank package it’s really easy to methodically validate your data whether in the form of data frames or as database tables. On top of the validation toolset, the package gives you the means to provide and keep up-to-date with the information that defines your tables. For table validation, the agent object works with a large collection of simple (yet powerful!) validation functions. We can enable much more sophisticated validation checks by using custom expressions, segmenting...
    Downloads: 0 This Week
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  • 8
    forecast

    forecast

    Forecasting Functions for Time Series and Linear Models

    The forecast package is a comprehensive R package for time series analysis and forecasting. It provides functions for building, assessing, and using univariate forecasting models (e.g. ARIMA, exponential smoothing, etc.), tools for automatic model selection, diagnostics, plotting, forecasting future values, etc. It's widely used in statistics, economics, business forecasting, environmental science, etc. Exponential smoothing state space models (ETS) including seasonal components. Residual...
    Downloads: 0 This Week
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  • 9
    tidyr

    tidyr

    Tidy Messy Data

    tidyr is a core tidyverse package designed to help reshape and clean messy datasets into tidy data—i.e., data frames where each variable is a column, each observation is a row, and each value is a cell.
    Downloads: 0 This Week
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  • 10
    ggpubr

    ggpubr

    'ggplot2' Based Publication Ready Plots

    ggpubr is an R package that provides easy-to-use wrapper functions around ggplot2 to create publication-ready visualizations with minimal code. It streamlines plot creation for researchers and analysts, allowing features such as statistical annotation, theme customization, and plot arrangement with fewer lines of code.
    Downloads: 0 This Week
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  • 11
    brms

    brms

    brms R package for Bayesian generalized multivariate models using Stan

    brms is an R package by Paul Bürkner which provides a high-level interface for fitting Bayesian multilevel (i.e. mixed effects) models, generalized linear / non-linear / multivariate models using Stan as the backend. It allows R users to specify complex Bayesian models using formula syntax similar to lme4 but with far more flexibility (distributions, link functions, hierarchical structure, nonlinear terms, etc.). It supports model diagnostics, posterior predictive checking, model comparison,...
    Downloads: 0 This Week
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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...
    Downloads: 1 This Week
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  • 13
    gganimate

    gganimate

    A Grammar of Animated Graphics

    gganimate extends the grammar of graphics as implemented by ggplot2 to include the description of animation. It does this by providing a range of new grammar classes that can be added to the plot object in order to customize how it should change with time. Here we take a simple boxplot of fuel consumption as a function of cylinders and let it transition between the number of gears available in the cars. As this is a discrete split (gear being best described as an ordered factor) we use...
    Downloads: 3 This Week
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  • 14
    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.
    Downloads: 0 This Week
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  • 15
    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.
    Downloads: 0 This Week
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  • 16
    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...
    Downloads: 0 This Week
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  • 17
    targets

    targets

    Function-oriented Make-like declarative workflows for R

    The targets package is a pipeline / workflow management tool in R, designed to coordinate multi‐step computational workflows in data science / statistics. It tracks dependencies between “targets” (computational steps), skips steps whose upstream data or code hasn’t changed, supports parallel computation, branching (dynamic generation of sub‐targets), file format abstractions, and encourages reproducible and efficient analyses. It’s something like GNU Make for R, but more integrated. Skipping...
    Downloads: 0 This Week
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  • 18
    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...
    Downloads: 0 This Week
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  • 19
    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...
    Downloads: 0 This Week
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  • 20
    hrbrthemes

    hrbrthemes

    Opinionated, typographic-centric ggplot2 themes and theme components

    hrbrthemes is a focused ggplot2 theme package with an emphasis on typography, layout precision, and visual polish. It includes themes like theme_ipsum and Font scales tailored for clean, high‑quality production graphics.
    Downloads: 0 This Week
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  • 21
    Harmony Data Integration

    Harmony Data Integration

    Fast, sensitive and accurate integration of single-cell data

    Harmony is a general-purpose R package with an efficient algorithm for integrating multiple data sets. It is especially useful for large single-cell datasets such as single-cell RNA-seq. Harmony has been tested on R versions =4. Please consult the DESCRIPTION file for more details on required R packages. Harmony has been tested on Linux, OS X, and Windows platforms.
    Downloads: 0 This Week
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  • 22
    ComplexHeatmap

    ComplexHeatmap

    Make Complex Heatmaps

    ComplexHeatmap is an R/Bioconductor package by Zuguang Gu et al. designed to create highly flexible, complex, richly annotated heatmaps and related visualizations. It allows arranging multiple heatmaps, adding annotations, combining heatmaps, customizing colors, layouts, and integrating other plots. Often used in genomics/bioinformatics to show expression, methylation, etc., with sidebars, annotations, clustering, etc. Highly customizable layout: combining different heatmaps, arranging and...
    Downloads: 4 This Week
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  • 23
    sf (Simple Features)

    sf (Simple Features)

    Simple Features for R

    sf is an R package that implements “simple features” (standardized vector spatial data) for R. It allows spatial vector data (points, lines, polygons etc.) to be represented as records in data frames (or tibbles) with geometry list columns, and performs spatial operations (geometry operations, coordinate reference system transformations, reading/writing spatial data, integration with spatial databases etc.). It interfaces to GDAL, GEOS, PROJ libraries for robust operations. Reading and...
    Downloads: 0 This Week
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  • 24
    circlize

    circlize

    Circular visualization in R

    circlize is an R package for creating circular visualizations (plots laid out in circular coordinate systems) in a very flexible way. It implements many types of plots using circular layouts: chord diagrams, circular heatmaps, arcs/links between sectors, genomic data visualization, etc. 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...
    Downloads: 0 This Week
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