In 2DegreesInvesting/ds-incubator: Share best practices in coding

2020-04-08: Tidying data

Comparing gather to pivot_longer and spread to pivot_wider (GitHub issue)

\@cjyetman run a live example, answered questions, and lead the discussion (recording; code).

You may like this content if you use tidyverse packages to analyze tidy data (as defined here and here). This includes 2DII folks and beyond.

Tidy datasets are easy to manipulate, model and visualise, 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. -- https://vita.had.co.nz/papers/tidy-data.pdf

2DegreesInvesting/ds-incubator documentation built on Oct. 13, 2021, 10:09 a.m.