ArgMax / Aggregation Layer
Find row indices of maximum values in specified columns, similar to numpy argmax() or pandas idxmax(). Returns integer indices that can be used for reference or filtering.
Common applications:
- Finding peak timestamps in time series
- Identifying best-performing instances
- Locating maximum sensor readings
- Finding highest-value transactions
- Detecting extreme events
Note: For ties, returns the index of first occurrence of the maximum value.
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Select
[column, ...]Columns to analyze for maximum values. Each selected column must be sortable (numeric, string, datetime, etc.). Returns the row index (0-based) where the maximum value occurs.