This aggregate function returns the smallest of the numbers in the reference column (the column to which min is applied) as all duplicate rows are collapsed into unique single rows. Excluding the column to which the min is being applied, all rows are examined column-by-column in order to find identical rows.
The counterpart to this function is max.
Example
The small dataset below will be used to show how min operates. All numbers are numeric values (not text) in order to illustrate behavior of this aggregate function.
| Column A | Column B | Column C |
|---|
| 1 | two | 5 |
| 1 | two | 6 |
| two | two | 7 |
| 1 | two | 4 |
Applying the min function to Column C reduces the row count from four to two. The value in the column Min of Column C shows the minimum of of the Column C values in the duplicate rows that were collapsed during the operation.
In the dataset that is returned by the min function (shown below) number 4 in the first row resulted from the set of numbers {4, 5, 6}. Each of these numbers exists in this set because each was a member of an identical row when Column A and Column B were examined. (Column C was excluded from this examination because it is the reference column.) In this set of three numbers, 4 is the smallest—therefore it became the value shown in the reference column.
The number 7 results from a set with a single number {7} because there were no duplicate rows that could contribute other numbers. Since 7 is both the minimum and maximum of the single-row set, the function returns a 7 for that row.
| Column A | Column B | Min of Column C |
|---|
| 1 | two | 4 |
| two | two | 7 |
日本語
