Google Data Analytics Professional Certification Practice Test

Which of the following describes a key feature of Tidy data in R?

1. Each variable forms a column

2. All data is stored in one file

3. Data must be sorted alphabetically

4. Data types cannot be mixed

The correct answer is: Each variable forms a column

Tidy data is a foundational concept in data analysis using R, and a key feature is that each variable forms a column. This structure allows for clarity and ease of manipulation when conducting analyses or visualizations. By organizing data in this manner, it becomes easier to apply functions and workflows that expect data to be in a tidy format, where each row represents an observation, and each column corresponds to a variable. This organization also facilitates common tasks in data analysis, like summarizing or filtering data. When data is structured this way, it becomes more straightforward to implement data transformations and leverage the full capabilities of R's packages designed for analysis and visualization, such as dplyr and ggplot2. The other options, while they might describe different aspects of data organization or storage, do not capture the essence of what defines tidy data in the context of R. For example, the requirement that all data must be stored in one file is not a defining characteristic of tidy data; data can be tidy even if it is contained in multiple files, as long as the structure of each individual dataset adheres to the tidy principles. Similarly, sorting data alphabetically and restrictions on mixing data types are not intrinsic characteristics of tidy data. Tidy data prioritizes the organization of