The expression is passed directly to a running analytics extension service instance. Returns a string result from the specified expression. SCRIPT_REAL("return map(lambda x : x * 0.5, _arg1)", SUM()) SCRIPT_STR SCRIPT_REAL('library(udunits2) ud.convert(.arg1, "celsius", "degree_fahrenheit")',AVG()) The next example converts temperature values from Celsius to Fahrenheit. arg n (with a leading period) to reference parameters (.arg1. Returns a real result from the specified expression. SCRIPT_INT("return map(lambda x : int(x * 5), _arg1)", SUM()) SCRIPT_REAL In the next example, k-means clustering is used to create three clusters: Returns an integer result from the specified expression. SCRIPT_BOOL("return map(lambda x : x > 0, _arg1)", SUM()) SCRIPT_INT arg1, perl=TRUE)',ATTR())Ī command for Python would take this form: This example could be the definition for a calculated field titled IsStoreInWA. The next example returns True for store IDs in Washington state, and False otherwise. In Python expressions, use _arg n (with a leading underscore). Returns a Boolean result from the specified expression. Partition, the result is a running average of the sales values forĬomputes the running average of SUM(Profit). When RUNNING_AVG(SUM() is computed within the Date RUNNING_AVG(expression)Īverage of the given expression, from the first row in the partition to With this function, the set of values (6, 9, 9, 14) would be ranked (4, 2, 3, 1).įor information on different ranking options, see Rank calculation. Use the optional 'asc' | 'desc' argument to specify ascending or descending order. Identical values are assigned different ranks. Returns the unique rank for the current row in the partition. With this function, the set of values (6, 9, 9, 14) would be ranked (0.00, 0.67, 0.67, 1.00).įor information on different ranking options, see Rank calculation. Returns the percentile rank for the current row in the partition. With this function, the set of values (6, 9, 9, 14) would be ranked (4, 3, 3, 1).įor information on different ranking options, see Rank calculation. Identical values are assigned an identical rank. Returns the modified competition rank for the current row in the partition. With this function, the set of values (6, 9, 9, 14) would be ranked (3, 2, 2, 1).įor information on different ranking options, see Rank calculation. Identical values are assigned an identical rank, but no gaps are inserted into the number sequence. Returns the dense rank for the current row in the partition. The remaining columns show the effect of each rank function on the set of age values, always assuming the default order (ascending or descending) for the function. The data set contains information on 14 students (StudentA through StudentN) the Age column shows the current age of each student (all students are between 17 and 20 years of age). The following image shows the effect of the various ranking functions (RANK, RANK_DENSE, RANK_MODIFIED, RANK_PERCENTILE, and RANK_UNIQUE) on a set of values. They are not numbered and they do not count against the total number of records in percentile rank calculations.įor information on different ranking options, see Rank calculation. With this function, the set of values (6, 9, 9, 14) would be ranked (4, 2, 2, 1). Returns the standard competition rank for the current row in the partition.
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