Tidy Data 论文

2014Journal of Statistical Software引用 887顶会
Big Data Technologies and ApplicationsAnomaly Detection Techniques and ApplicationsPrivacy-Preserving Technologies in Data

详细信息

发表期刊/会议
Journal of Statistical Software
发表日期
2014-01-01
发表年份
2014

关键词

Big Data Technologies and ApplicationsAnomaly Detection Techniques and ApplicationsPrivacy-Preserving Technologies in Data

摘要

A huge amount of effort is spent cleaning data to get it ready for analysis, but there has been little research on how to make data cleaning as easy and effective as possible. This paper tackles a small, but important, component of data cleaning: data tidying. Tidy datasets are easy to manipulate, model and visualize, and have a specific structure: each variable is a column, each observation is a row, and each type of observational unit is a table. This framework makes it easy to tidy messy datasets because only a small set of tools are needed to deal with a wide range of un-tidy datasets. This structure also makes it easier to develop tidy tools for data analysis, tools that both input and output tidy datasets. The advantages of a consistent data structure and matching tools are demonstrated with a case study free from mundane data manipulation chores.