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Showing 113 open source projects for "source"
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R Source
Read-only mirror of R source code
The wch/r-source repository is a read-only mirror of the official R language source code, maintained to reflect the upstream Subversion (SVN) R core development tree. This mirror provides public visibility into R’s internals—everything from the interpreter, base and recommended packages, documentation, and C/Fortran code under the hood. It is updated hourly to stay in sync with the upstream SVN. -
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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... -
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ggplot2
An implementation of the Grammar of Graphics in R
ggplot2 is a system written in R for declaratively creating graphics. It is based on The Grammar of Graphics, which focuses on following a layered approach to describe and construct visualizations or graphics in a structured manner. With ggplot2 you simply provide the data, tell ggplot2 how to map variables to aesthetics, what graphical primitives to use, and it will take care of the rest. ggplot2 is over 10 years old and is used by hundreds of thousands of people all over the world for... -
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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... -
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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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rmarkdown
Dynamic Documents for R
R Markdown is an R package for creating dynamic, reproducible documents that combine code (R, Python, SQL, etc.), results (figures, tables), and narrative text. Built on Knitr and Pandoc, it supports generating HTML, PDF, Word, slideshows, dashboards, and more. It’s widely used in data science and reproducible reporting workflows. -
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httr
httr: a friendly http package for R
httr is superseded: only changes necessary to keep it on CRAN will be made. We recommend using httr2 instead. The aim of httr is to provide a wrapper for the curl package, customized to the demands of modern web APIs. Functions for the most important http verbs: GET(), HEAD(), PATCH(), PUT(), DELETE() and POST(). Automatic connection sharing across requests to the same website (by default, curl handles are managed automatically), cookies are maintained across requests, and an up-to-date... -
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Readr
Read flat files (csv, tsv, fwf) into R
readr is an R package that provides a fast and friendly way to read rectangular data, such as CSV and TSV files. Part of the Tidyverse, it simplifies data import and parsing tasks in R. -
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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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Shiny
Build interactive web apps directly from R with Shiny framework
Shiny is an R package from RStudio that enables users to build interactive web applications using R without requiring knowledge of JavaScript, HTML, or CSS. It allows statisticians and data scientists to turn their analyses into fully functional web dashboards with reactive elements, data inputs, visualizations, and controls, making data communication more effective and dynamic. -
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DiagrammeR
Graph and network visualization using tabular data in R
DiagrammeR is an R package to create, manipulate, and visualize network graphs, flowcharts, diagrams, and more using Graphviz and Mermaid syntax. Integrates with RMarkdown and Shiny apps, supports node/edge traversal, and graph analysis algorithms, making it ideal for documenting processes, causal relationships, or data pipelines. -
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RStudio Cheatsheets
Curated collection of official cheat sheets for data science tools
...Each cheat sheet is a single (or double) page PDF that condenses important syntax, functions, workflows, and best practices into a visually organized format ideal for quick reference. The repository contains source files (R Markdown or LaTeX) that generate the cheat sheets, version history, and metadata (title, author, description) for each. It covers topics such as data wrangling, data import, modeling, visualization, RStudio IDE shortcuts, Shiny development, and the tidyverse suite (dplyr, ggplot2, tidyr, purrr). These cheat sheets are widely used by R learners, educators, and practitioners as quick reference tools, and they often ship with RStudio by default or are linked from RStudio’s help/documentation pages. ... -
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Introduction to Zig
An open, technical and introductory book for the Zig programming lang
This is the official repository for the book "Introduction to Zig: a project-based Book", written by Pedro Duarte Faria. To know more about the book, check out the About this book section below. You can read the current version of the book in your web browser. The book is built using the publishing system Quarto in conjunction with a little bit of R code (zig_engine.R), which is responsible for calling the Zig compiler to compile and run the Zig code examples. -
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rollama
Wrap the Ollama API, which allows you to run different LLMs
rollama is an R package that provides a convenient interface for interacting with local large language models through the Ollama API, bringing modern AI capabilities into the R ecosystem. It is designed to make LLM usage accessible to data scientists and researchers who work primarily in R, allowing them to generate text, analyze data, and create embeddings without relying on external cloud services. The package emphasizes reproducibility and privacy by enabling local execution of models,... -
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NYC Taxi Data
Import public NYC taxi and for-hire vehicle (Uber, Lyft)
The nyc-taxi-data repository is a rich dataset and exploratory project around New York City taxi trip records. It collects and preprocesses large-scale trip datasets (fares, pickup/dropoff, timestamps, locations, passenger counts) to enable data analysis, modeling, and visualization efforts. The project includes scripts and notebooks for cleaning and filtering the raw data, memory-efficient processing for large CSV/Parquet files, and aggregation workflows (e.g. trips per hour, heatmaps of... -
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data.table
Extends base R’s data for high-performance data manipulation
data.table is an R package that extends base R’s data.frame for high-performance data manipulation. It offers concise syntax, blazing speed, and memory-efficient operations. It supports fast file reading/writing, joins, grouping, reshaping, and updates by reference. It is heavily used in large data workflows, big data in R, production pipelines, etc. Extremely efficient grouping/aggregation/summarization; can handle very large datasets (hundreds of millions to billions of rows) in memory (if... -
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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. -
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magrittr
Improve the readability of R code with the pipe
magrittr introduces the pipe operator (%>%) and related functional utilities into R. It underlies the powerful piped syntax widely adopted in tidyverse workflows by enabling left-hand argument passing and providing helpers like compound assignment pipes and exposition pipes. -
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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. -
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purrr
A functional programming toolkit for R
purrr enhances R’s functional programming capabilities by providing a consistent set of tools for working with lists and vectors, enabling safer and more expressive iteration compared to base R’s loop functions. -
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janitor
Simple tools for data cleaning in R
janitor provides simple, convenient tools for data cleaning, formatting, and exploration in R. It is especially useful for cleaning messy data frames, removing duplicates, formatting column names, and producing frequency tables in a tidy workflow. -
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plumber
Turn your R code into a web API
plumber is an R package that enables rapid creation of HTTP APIs by decorating existing R functions with special roxygen-style comments. It transforms R scripts into RESTful web services with minimal setup and integrates easily with RStudio or CI environments. -
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renv
renv: Project environments for R
renv is an R dependency management toolkit that enables project-level library isolation and reproducibility. It tracks package versions in a lockfile and can restore exact library states across machines or over time, making R projects portable and consistent. -
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easystats
The R easystats-project
easystats is a meta‑package that installs and unifies a suite of R packages for post‑processing statistical models. It delivers a consistent API to assess model performance, effect sizes, parameters, and to generate reports and visualizations, all with minimal dependencies and maximum clarity. -
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devtools
Tools to make an R developer's life easier
devtools is an R package designed to simplify R package development by providing functions for creating, building, testing, and installing packages from various sources (e.g., CRAN, GitHub). It integrates with usethis, roxygen2, testthat, and simplifies workflows for developers and contributors to the R ecosystem.
