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MissingCount - chart function

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:  

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.

Defining the aggregation scope

Examples and results:  

Data
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
Examples and results
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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