Fractile() finds the value that corresponds to the fractile (quantile) of the aggregated data in the range given by the expression iterated over the chart dimensions.
Syntax:
Fractile([{SetExpression}] [DISTINCT] [TOTAL [<fld{, fld}>]] expr, fraction)
Return data type: numeric
Arguments:
| Argument | Description |
|---|---|
| expr | The expression or field containing the data to be measured. |
| 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. The TOTAL qualifier may be followed by a list of one or more field names within angle brackets <fld>. These field names should be a subset of the chart dimension variables. See also: Defining the aggregation scope |
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 |
|---|---|
| Fractile(Sales, 0.75) |
For a table including the dimension |
| Fractile(TOTAL Sales, 0.75)) | 71.75 for all values of Customer, because the TOTAL qualifier means that dimensions are disregarded. |
| Fractile(DISTINCT Sales, 0.75) | 70 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 * INLINE [
Month, 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 (Month, 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 '|');
To get the months to sort in the correct order, when you create your visualizations, go to the Sorting section of the properties panel, select Month and mark the checkbox Sort by expression. In the expression box write Monthnumber.
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