wrangling 开源项目推荐（139 个）

pbeshai /tidy

Tidy up your data with JavaScript, inspired by dplyr and the tidyverse

easystats /datawizard

魔法药水清理和转换你的数据 🧙

VorTECHsa /refinery

Refinery is a tool to extract and transform semi-structured data from Excel spreadsheets of different layouts in a declarative way.

nrwade0 /edX

Data Science courses in R from HarvardX

ropensci /datefixR

🗓 Standardize messy date data into consistent, machine-readable, formats

autonomio /autonomio

Core functionality for the Autonomio augmented intelligence workbench.

oliviergimenez /intro_tidyverse

Slides of my introduction to the Tidyverse

autonomio /wrangle

Prepare scientific data with native Polars, YAML protocols, a readable CLI and reproducible evidence.

caerbannogwhite /preludio

Preludio is a data wrangling language based on PRQL and written in Go.

viraltux /DataWrangler.jl

Data transformation tools for analytics

mkearney /wibble

Web Data Frames

ubco-mds-2021-labs /capstone-project-googletrends_capstone

Nowcasting macroeconomic indicators using Google Trends

anjalisilva /IntroductionToR

Teaching Material: 'Data Science Certificate: Introduction to R' course at Data Sciences Institute University of Toronto (Summer & Fall 2022). The vast amount of data produced by evolving information technology requires tools and skills. R is a free, open-source language and an environment that could be used for data sciences.

hawkfish /textform

A data transformation pipeline library based on Potter's Wheel.

energy-monitor /explore

Codebase for data wrangling and analyis of https://energie.wifo.ac.at

CWWhitney /teaching_R

🎓 Uni-Bonn Collection of tools for teaching R

1965Eric /HarvardX-PH125.6x-Data-Science-Wrangling

HarvardX: PH125.6x | Data Science: Wrangling

mpavanetti /logCollector

Python Agent for Extract, Transform and load Talend Remote Engine log files into Elasticsearch + Kibana Dashboards

mkearney /qualtricks

📝🤡🛠 Tools for Working with Qualtrics Data

sashahafner /CCPDA

This short free book provides a concise introduction to data analysis meant to address common problems faced by graduate students in engineering and science.