Select a table column

Select a specific table column using a Table Column expression.

The name of column being selected.

Perform an analysis and select the output value

Perform data analysis with in-built algorithms using value macro expressions:

The name of the value macro, e.g., sleep_score for the Chronotype value macro.

Aggregate a table column

Aggregate a Table Column expression with respect to the group_by clause.

The specified aggregate function is applied to each and every group created by the group_by clause. The result set is N aggregated values where N is the number of groups.

Aggregate functionPython DSLJSON DSL
Minimum$EXPR.min(){ "aggregate": "min", "arg": $EXPR }
Maximum$EXPR.max(){ "aggregate": "max", "arg": $EXPR }
Mean$EXPR.mean(){ "aggregate": "mean", "arg": $EXPR }
Median$EXPR.median(){ "aggregate": "median", "arg": $EXPR }
Standard Deviation$EXPR.stddev(){ "aggregate": "stddev", "arg": $EXPR }
Count$EXPR.count(){ "aggregate": "count", "arg": $EXPR }
Oldest Value$EXPR.oldest(){ "aggregate": "oldest", "arg": $EXPR }
Newest Value$EXPR.newest(){ "aggregate": "newest", "arg": $EXPR }
Aggregate functionPython DSLJSON DSL
Sum$EXPR.sum(){ "aggregate": "sum", "arg": $EXPR }
  • the aggregation function name, e.g., sum; or
  • if the Split by Source mode is enabled — $FUNCTION_NAME.$SOURCE_COLUMN_NAME, e.g., mean.efficiency.

Select the Index Column

Select the primary datetime index of the table using the Index Column expression.

timestamp (constant).

Select the Group Key Columns

Select the Group Key Columns associated with the group_by clause.

You can select one specific group key column by offset, or select all group key columns with a * wildcard.

group_key.$OFFSET, where $OFFSET corresponds to the N-th expression of the group_by clause.