Join Mike Chapple for an in-depth discussion in this video Wide vs. long data sets, part of Cleaning Bad Data in R.
- [Instructor] There are many different ways…that you can present the same dataset to the world.…Let's take a look at one of the most important…and fundamental distinctions,…whether a dataset is wide or long.…The difference between wide and long datasets boils down…to whether we prefer to have more columns…in our dataset or more rows.…A dataset that emphasizes putting additional data…about a single subject in columns is called a wide dataset…because, as we add more columns, the dataset becomes wider.…
Similarly, a dataset that emphasizes…including additional data about a subject in rows…is called a long dataset…because, as we add more rows, the dataset becomes longer.…It's important to point out that there's nothing…inherently good or bad about wide or long data.…In the world of data wrangling,…we sometimes need to make a long dataset wider,…and we sometimes need to make a wide dataset longer.…However, it is true that, as a general rule,…data scientists who embrace the concept of tidy data…usually prefer longer datasets over wider ones…
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
What's next?1m 5s
- Mark as unwatched
- Mark all as unwatched
Are you sure you want to mark all the videos in this course as unwatched?
This will not affect your course history, your reports, or your certificates of completion for this course.Cancel
Take notes with your new membership!
Type in the entry box, then click Enter to save your note.
1:30Press on any video thumbnail to jump immediately to the timecode shown.
Notes are saved with you account but can also be exported as plain text, MS Word, PDF, Google Doc, or Evernote.