Join Mike Chapple for an in-depth discussion in this video What is tidy data?, part of Cleaning Bad Data in R.
- [Instructor] The goal of this course is to help you use R…to transform your data sets…into a consistent format known as tidy data.…You do this through a process known as data wrangling.…Data wrangling is the art of taking messy data…and manipulating it into a format…that is well-suited for analysis.…It goes by many other names.…Some people call this work data cleaning,…data munging, or data preparation.…Whatever name you choose to use,…it's important to remember that this is not a one-time task.…
While it's true that most data projects…will involve a lot of data wrangling up front,…data wrangling is a continuous process.…And as you encounter new data sets, new problems,…and new ideas during the course of your project,…you'll likely return to perform some new data wrangling.…The term tidy data describes data…that has been put into a standardized format…that facilitates future analytic work.…Hadley Wickham, a data scientist…who is one of the key developers of the R language,…coined the term tidy data in this paper that he published…
Where possible, instructor Mike Chapple shows how to correct the issues using R, but the same principles can be applied to any statistical programing language.
- Missing data
- Duplicate rows and values
- Converting data
- Formatting data
- Working with tidy data
- Tidying data sets
- Dealing with suspicious data
Skill Level Beginner
1. Missing Data
2. Duplicated Data
3. Formatting Data
5. Tidy Data
6. Red Flags
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