Unpivoting

Unpivoting is a data transformation process that reshapes a table from a wide format to a long format. In a wide format, data values are spread across multiple columns, often representing different categories or time periods. Unpivoting converts these columns into rows, creating two new columns: one that stores the column headers (the original categories or time periods) and another that stores the corresponding values from those columns.

This transformation is particularly useful in data analysis and database management. When data is in a wide format, it can be challenging to perform operations like filtering, aggregation, or plotting by category. Unpivoting allows for easier querying and manipulation of the data, as each observation is represented by a single row. For example, a table showing sales figures for different products across several months in a wide format could be unpivoted. The original month columns would be transformed into a single 'Month' column, and the sales figures would populate a 'Sales' column. A new 'Product' column would retain the product names from the original row identifiers.

Many data analysis tools and programming languages offer functions to perform unpivoting. These functions typically require specifying the columns that will become the 'key' columns (which remain as identifiers) and the columns that will be unpivoted. The result is a more normalized and structured dataset, facilitating downstream analytical tasks.