Skip to main content
Version: Java (Groovy)

wavgBy

The wavgBy method returns a new table with a column containing the weighted average of a table's data column, grouped by the specified columns.

Syntax​

table.wavgBy(weightColumn)
table.wavgBy(weightColumn, groupByColumns...)
table.wavgBy(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 average for all non-key columns.
  • "X" will output the weighted average of each group in column X.
  • "X", "Y" will output the weighted average of each group designated from the X and Y columns.
groupByColumnsColumnName...

The column(s) by which to group data.

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

The column(s) by which to group data.

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

Returns​

A new table with a column containing the weighted average of the data column, grouped by the specified columns.

Examples​

In this example, wavgBy returns the weighted average 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.wavgBy("Num2")

In this example, wavgBy returns the weighted average 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.wavgBy("Num2", "Letter")