There are two main ways to store data in R: textual and binary formats. Textual formats are more readable and can be edited, but they are not as space-efficient. Binary formats are more space-efficient, but they are not as readable.
The intermediate textual format is a compromise between these two extremes. It is more readable than a binary format, but it is also more space-efficient than a simple text file. This format is created by using the dput() or dump() functions.
These functions are useful because they preserve the metadata of the data object. This means that the class of each column of a table or the levels of a factor variable are preserved. This can be useful for version control and for debugging.
However, the intermediate textual format is not as space-efficient as a binary format. It is also not as readable as a simple text file. In some cases, it might be preferable to have the data stored in a CSV file and then have a separate code file that specifies the metadata.
Here are some of the pros and cons of using textual and binary formats for storing data in R:
Textual formats
Pros:
- More readable
- Can be edited
- Adheres to the Unix philosophy
Cons:
- Not as space-efficient
- Only partially readable
Binary formats
Pros:
- More space-efficient
- More readable than a simple text file
Cons:
- Not as readable as a textual format
The best format to use for storing data in R depends on the specific needs of the project. If readability is important, then a textual format might be the best choice. If space efficiency is important, then a binary format might be the best choice.
