wsumBy

The wsumBy groups the data column according to groupByColumns and computes the weighted sum using weightColumn for the rest of the fields.

If the weight column is a floating point type, all result columns will be doubles. If the weight column is an integral type, all integral input columns will have long results and all floating point input columns will have double results.

Syntax

table.wsumBy(weightColumn)
table.wsumBy(weightColumn, groupByColumns...)
table.wsumBy(weightColumn, groupByColumns)

Parameters

ParameterTypeDescription
weightColumnString

The column to use as the weight for the calculation.

groupByColumnsString...

The column(s) by which to group data.

  • NULL returns the weighted sum for all non-key columns.
  • "X" will output the weighted sum of each group in column X.
  • "X", "Y" will output the weighted sum of each group designated from the X and Y columns.
groupByColumnsColumnName...

The column(s) by which to group data.

  • NULL returns the weighted sum for all non-key columns.
  • "X" will output the weighted sum of each group in column X.
  • "X", "Y" will output the weighted sum of each group designated from the X and Y columns.
groupByColumnsCollection<String>

The column(s) by which to group data.

  • NULL returns the weighted sum for all non-key columns.
  • "X" will output the weighted sum of each group in column X.
  • "X", "Y" will output the weighted sum of each group designated from the X and Y columns.

Returns

A new table containing the weighted sum of the data column, grouped by the specified columns.

Examples

In this example, wsumBy returns the weighted sum of the Num1 column, with no grouping columns.

source = newTable(
    intCol("Num1", 1, 2, 3, 4, 5, 6, 7, 8, 9, 10),
    intCol("Num2", 5, 4, 3, 2, 1, 1, 1, 1, 1, 1)
)

result = source.wsumBy("Num2")

In this example, wsumBy returns the weighted sum of the Num1 column, grouped by the Letter column.

source = newTable(
    stringCol("Letter", "A", "B", "A", "B", "A", "B", "A", "B", "A", "B"),
    intCol("Num1", 1, 2, 3, 4, 5, 6, 7, 8, 9, 10),
    intCol("Num2", 5, 4, 3, 2, 1, 1, 1, 1, 1, 1)
)

result = source.wsumBy("Num2", "Letter")