Aggregation Functions
PantherFlow aggregation functions
PantherFlow is in open beta starting with Panther version 1.110, and is available to all customers. Please share any bug reports and feature requests with your Panther support team.
agg.avg()
agg.avg()
agg.avg(column: any) -> float
Returns the average of the values in the aggregation.
Example:
agg.count()
agg.count()
agg.count([column: any]) -> int
Returns the number of values in the aggregation.
Example:
agg.count_distinct()
agg.count_distinct()
agg.count_distinct(column: any) -> int
Returns the number of unique values in the aggregation.
Example:
agg.make_set()
agg.make_set()
agg.make_set(column: any) -> any
Returns a set of unique values from the column.
Example:
agg.max()
agg.max()
agg.max(column: any) -> float
Returns the maximum value in the aggregation.
Example:
agg.min()
agg.min()
agg.min(column: any) -> float
Returns the minimum value in the aggregation.
Example:
agg.percentile_cont()
agg.percentile_cont()
agg.percentile_cont(column: [any], percentile: number) -> float
For a given percentile
value between 0.0 and 1.0, return the value of the input column
based on a continuous distribution of rows. If no input row lies exactly at the desired percentile, the result is calculated using linear interpolation of the two nearest input values. If a group contains only one value, then that value will be returned for any specified percentile (e.g., both percentile 0.0 and percentile 1.0 will return that one row).
Example:
agg.stddev()
agg.stddev()
agg.stddev(column: [number]) -> float
Returns the sample standard deviation (square root of sample variance) of non-null values.
Example:
agg.sum()
agg.sum()
agg.sum(column: [any]) -> float
Returns the sum of the values in the aggregation.
Example:
agg.take_any()
agg.take_any()
agg.take_any(column: [any]) -> any
Returns any value from the aggregation.
Example:
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