# FractileExc - chart function

FractileExc() finds the value that corresponds to the exclusive fractile (quantile) of the aggregated data in the range given by the expression iterated over the chart dimensions.

Tip: You can use Fractile - chart function to calculate the inclusive fractile.

Syntax:

FractileExc([{SetExpression}] [DISTINCT] [TOTAL [<fld{, fld}>]] expr, fraction)

Return data type: numeric

The function returns the value corresponding to the rank as defined by rank = fraction * (N+1) where N is the number of values in expr. If rank is a non-integer number, an interpolation is made between the two closest values.

Arguments:

Argument Description
expr The expression or field containing the data to use when calculating the fractile.
fraction A number between 0 and 1 corresponding to the fractile (quantile expressed as a fraction) to be calculated.
SetExpression By default, the aggregation function will aggregate over the set of possible records defined by the selection. An alternative set of records can be defined by a set analysis expression.
DISTINCT If the word DISTINCT occurs before the function arguments, duplicates resulting from the evaluation of the function arguments are disregarded.
TOTAL

If the word TOTAL occurs before the function arguments, the calculation is made over all possible values given the current selections, and not just those that pertain to the current dimensional value, that is, it disregards the chart dimensions.

By using TOTAL [<fld {.fld}>], where the TOTAL qualifier is followed by a list of one or more field names as a subset of the chart dimension variables, you create a subset of the total possible values.

Limitations:

The expression must not contain aggregation functions, unless these inner aggregations contain the TOTAL qualifier. For more advanced nested aggregations, use the advanced aggregation function Aggr, in combination with calculated dimensions.

Examples and results:

Customer Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Astrida 46 60 70 13 78 20 45 65 78 12 78 22
Betacab 65 56 22 79 12 56 45 24 32 78 55 15
Canutility 77 68 34 91 24 68 57 36 44 90 67 27
Divadip 57 36 44 90 67 27 57 68 47 90 80 94
Example Result
FractileExc(Sales, 0.75)

For a table including the dimension `Customer` and the measure Fractile([Sales]), if Totals are shown, the result is 71.25. This is the point in the distribution of values of Sales that 75% of the values fall beneath.

FractileExc(TOTAL Sales, 0.75)) 71.25 for all values of Customer, because the TOTAL qualifier means that dimensions are disregarded.
FractileExc(DISTINCT Sales, 0.75) 73.50 for the total, because using the DISTINCT qualifier means only unique values in Sales for each Customer are evaluated.

Data used in examples:

Monthnames: LOAD *, Dual(MonthText,MonthNumber) as Month INLINE [ MonthText, MonthNumber Jan, 1 Feb, 2 Mar, 3 Apr, 4 May, 5 Jun, 6 Jul, 7 Aug, 8 Sep, 9 Oct, 10 Nov, 11 Dec, 12 ]; Sales2013: Crosstable (MonthText, Sales) LOAD * inline [ Customer|Jan|Feb|Mar|Apr|May|Jun|Jul|Aug|Sep|Oct|Nov|Dec Astrida|46|60|70|13|78|20|45|65|78|12|78|22 Betacab|65|56|22|79|12|56|45|24|32|78|55|15 Canutility|77|68|34|91|24|68|57|36|44|90|67|27 Divadip|57|36|44|90|67|27|57|68|47|90|80|94 ] (delimiter is '|');