MissingCount() is used to aggregate the number of missing values in each chart dimension. Missing values are all non-numeric values.
Syntax:
MissingCount({[SetExpression] [DISTINCT] [TOTAL [<fld {,fld}>]]} expr)
Return data type: integer
Arguments:
| Argument | Description |
|---|---|
| expr | The expression or field containing the data to be measured. |
| 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. |
Examples and results:
| Customer | Product | OrderNumber | UnitSales | Unit Price |
|---|---|---|---|---|
| Astrida | AA | 1 | 4 | 16 |
| Astrida | AA | 7 | 10 | 15 |
| Astrida | BB | 4 | 9 | 9 |
| Betacab | BB | 6 | 5 | 10 |
| Betacab | CC | 5 | 2 | 20 |
| Betacab | DD | 25 | ||
| Canutility | AA | 15 | ||
| Canutility | CC | 19 | ||
| Divadip | AA | 2 | 4 | 16 |
| Divadip | DD | 3 | 25 |
| Example | Result |
|---|---|
| MissingCount([OrderNumber]) |
3 because 3 of the 10 OrderNumber fields are empty Information note"0" counts as a value and not an empty cell. However, if a measure aggregates to 0 for a dimension, that dimension will not be included in charts.
|
| MissingCount ([OrderNumber])/MissingCount ({1} Total [OrderNumber]) | The expression returns the number of incomplete orders from the selected customer as a fraction of incomplete orders from all customers. There is a total of 3 missing values for OrderNumber for all customers. So, for each Customer that has a missing value for Product the result is 1/3. |
Data used in example:
Temp:
LOAD * inline [
Customer|Product|OrderNumber|UnitSales|UnitPrice
Astrida|AA|1|4|16
Astrida|AA|7|10|15
Astrida|BB|4|9|9
Betacab|CC|6|5|10
Betacab|AA|5|2|20
Betacab|BB||| 25
Canutility|AA|||15
Canutility|CC| ||19
Divadip|CC|2|4|16
Divadip|DD|3|1|25
] (delimiter is '|');
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