Wide and narrow data
Wide and narrow (sometimes un-stacked and stacked, or wide and tall) are terms used to describe two different presentations for tabular data.[1][2]
Wide
[edit]Wide, or unstacked data is presented with each different data variable in a separate column.
| Person | Age | Weight | Height |
|---|---|---|---|
| Bob | 32 | 168 | 180 |
| Alice | 24 | 150 | 175 |
| Steve | 64 | 144 | 165 |
Narrow
[edit]Narrow, stacked, or long data is presented with one column containing all the values and another column listing the context of the value
| Person | Variable | Value |
|---|---|---|
| Bob | Age | 32 |
| Bob | Weight | 168 |
| Bob | Height | 180 |
| Alice | Age | 24 |
| Alice | Weight | 150 |
| Alice | Height | 175 |
| Steve | Age | 64 |
| Steve | Weight | 144 |
| Steve | Height | 165 |
This is often easier to implement; addition of a new field does not require any changes to the structure of the table, however it can be harder for people to understand.
Implementations
[edit]Many statistical and data processing systems have functions to convert between these two presentations, for instance the R programming language has several packages such as the tidyr package. The pandas package in Python implements this operation as "melt" function which converts a wide table to a narrow one. The process of converting a narrow table to wide table is generally referred to as "pivoting" in the context of data transformations. The "pandas" python package provides a "pivot" method which provides for a narrow to wide transformation.
See also
[edit]- Abstract data type
- Pivot table
- Table (information)
- Information graphics
- Row (database)
- Table (database)
- Table (HTML)
References
[edit]- ^ Thompson, M. E. (1997), Theory of sample surveys, Chapman & Hall, London. ISBN 0-412-31780-X
- ^ Chantala, K. (2006) "Using STATA to Analyze data from a Sample Survey". 1-10-2001. UNC Chapel Hill, Carolina Population Center. 10-1-2006.
External links
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