How to Prepare Datasets for Analysis

6 Lessons Learned Tidy Data

In Tidy Data Hadley Wickham outlines a series of principles those working with data can employ to do so more effectively.

Original notes these lessons are from.

1. Tidy Data is a Framework

Lesson Learned

2. Formatting of Tidy Data

  1. Each variable forms a column.
  2. Each observation forms a row.
  3. Each type of observational unit forms a table

Lesson Learned

3. Get the Most out of R Using Tidy Data

Lesson Learned

4. Four Fundamental Verbs of Data Manipulation

Transform: adding or modifying variables. These modifications can involve either a single variable (e.g., log-transformation), or multiple variables (e.g., computing density from weight and volume).

Aggregate: collapsing multiple values into a single value (e.g., by summing or taking means).

Sort: changing the order of observations.

Lesson Learned

5. Manipulating Data in R

Lesson Learned

6. Tidy visualisation tools only need to be input-tidy as their output is visual.

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Originally published at on December 23, 2020.



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Steven L. Miller

Steven L. Miller


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