xiaoa6435's Stars
lysyi3m/macos-terminal-themes
Color schemes for default macOS Terminal.app
tidyverse/dplyr
dplyr: A grammar of data manipulation
Rdatatable/data.table
R's data.table package extends data.frame:
rstudio/blogdown
Create Blogs and Websites with R Markdown
posit-dev/py-shiny
Shiny for Python
sparklyr/sparklyr
R interface for Apache Spark
r-wasm/webr
The statistical language R compiled to WebAssembly via Emscripten, for use in web browsers and Node.
MrSyee/pg-is-all-you-need
Policy Gradient is all you need! A step-by-step tutorial for well-known PG methods.
HappyZ/dpt-tools
dpt systems study and enhancement
japila-books/spark-sql-internals
The Internals of Spark SQL
extendr/extendr
R extension library for rust designed to be familiar to R users.
asg017/dataflow
An experimental self-hosted Observable notebook editor, with support for FileAttachments, Secrets, custom standard libraries, and more!
cosname/cosx.org
统计之都主站
kosukeimai/MatchIt
R package MatchIt
posit-dev/shinylive
Run Shiny on Python and R (compiled to wasm) in the browser
posit-dev/r-shinylive
quarto-ext/shinylive
Quarto extension to embed Shinylive for Python applications
DeclareDesign/estimatr
estimatr: Fast Estimators for Design-Based Inference
georgestagg/shiny-standalone-webr-demo
Demonstration of using a JavaScript ServiceWorker to communicate with a running Shiny/httpuv session in webR.
r-wasm/rwasm
Build R packages for WebAssembly and create a CRAN-like repo for distribution.
Toniiiio/imageclipr
RStudio Addin: Copy Image from Clipboard into RMarkdown .Rmd file
yaooqinn/itachi
A library that brings useful functions from various modern database management systems to Apache Spark
cisco/oraf
Optimized RAndom Forests
elanmart/rust-pgbart
cran/BART
:exclamation: This is a read-only mirror of the CRAN R package repository. BART — Bayesian Additive Regression Trees
cran/uplift
:exclamation: This is a read-only mirror of the CRAN R package repository. uplift — Uplift Modeling
FyZyX/llmfuncs
Dynamically generate JSON Schema from Python code. Great for OpenAI function calls!
mozjay0619/pyqreg
Fast implementation of the quantile regression using the interior point method, with support for iid, robust, and cluster standard errors.