# 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
| 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](https://help.qlik.com/en-US/sense/November2025/Subsystems/Hub/Content/Sense_Hub/ChartFunctions/define-aggregation-scope.htm) |
Example: Chart expressions
| Example | Result |
| --- | --- |
| `MissingCount(OrderNumber)` | Returns the number of missing values where `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. |
## Example - MissingCount fundamentals
[](https://help.qlik.com/en-US/sense/Subsystems/Hub/Content/Sense_Hub/ChartFunctions/CounterAggregationFunctions/missingcount.htm)
#### Chart expression
Overview
Open the Data load editor and add the load script below to a new section.
The load script contains:
* A dataset which is loaded into a data table called `Example`.
* The following fields in the data table:
* `Customer`
* `Product`
* `OrderNumber`
* `UnitSales`
* `UnitPrice`
Load script
```
Example:
LOAD * inline [
Customer, Product, OrderNumber, UnitSales, UnitPrice
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, BB,,4,16
Divadip, DD,3,,25
];
```
Results
Load the data and open a sheet. Create a new table and add this field as a dimension:
* `Customer`
Create the following measures:
* `=MissingCount(OrderNumber)`, to calculate the number of orders missing an `OrderNumber`.
* `=MissingCount(OrderNumber)/MissingCount ({1} Total [OrderNumber])`, to return the number of incomplete orders from the selected customer as a fraction of incomplete orders from all customers. To show this value as a percentage, under Number formatting, select Number > Formatting Simple > 12.34%.
Results table
| Customer | MissingCount(OrderNumber) | MissingCount(OrderNumber)/MissingCount ({1} Total [OrderNumber]) |
| --- | --- | --- |
| Totals | 4 | 100.00% |
| Astrida | 0 | 0.00% |
| Betacab | 1 | 25.00% |
| Canutility | 2 | 50.00% |
| Divadip | 1 | 25.00% |
In the first measure, the `MissingCount` function returns `4` because `4` of the `11` records in the `OrderNumber` field 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.
In the second measure, the output of the `MissingCount` function returns the number of incomplete orders from the selected customer as a percentage of incomplete orders from all customers. For example, if you select `Canutility` from the `Customer` dimension, the measure returns `50%` because half of all incomplete orders (`2` of `4`) are with this customer.
## Example - Using MissingCount to identify missing product data
[](https://help.qlik.com/en-US/sense/Subsystems/Hub/Content/Sense_Hub/ChartFunctions/CounterAggregationFunctions/missingcount.htm)
#### Chart expression
Overview
A dataset contains monthly key product indicater (KPI) data. A product manager wants to find out which KPIs have missing data.
Open the Data load editor and add the load script below to a new section.
The load script contains:
* A dataset which is loaded into a data table called `Example`.
* The following fields in the data table:
* `Month`
* `KPI`
* `Value`
Load script
```
Example:
Load * inline [
Month, KPI, Value
2024-01-01, Revenue, 5000
2024-02-01, Revenue,
2024-03-01, Revenue, 5500
2024-04-01, Revenue,
2024-01-01, Expenses, 3000
2024-02-01, Expenses, 3100
2024-03-01, Expenses,
2024-04-01, Expenses, 3200
2024-01-01,Customer Count, 200
2024-02-01,Customer Count, 210
2024-03-01,Customer Count,
2024-04-01,Customer Count,
];
```
Results
Load the data and open a sheet. Create a new table and add this field as a dimension:
* `KPI`
Create the following measure:
* `=MissingCount(Value)`, to calculate the number of missing values.
Results table
| KPI | MissingCount(Value) |
| --- | --- |
| Totals | 5 |
| Customer Count | 2 |
| Expenses | 1 |
| Revenue | 2 |
The results show that `5` records in the dataset have missing data as well as the KPI categories to which these records relate.