# Completeness
<a name="dqdl-rule-types-Completeness"></a>

Checks the percentage of complete (non-null) values in a column against a given expression.

**Syntax**

```
Completeness <COL_NAME> <EXPRESSION>
```
+ **COL\$1NAME** – The name of the column that you want to evaluate the data quality rule against.

  **Supported column types**: Any column type
+ **EXPRESSION** – An expression to run against the rule type response in order to produce a Boolean value. For more information, see [Expressions](dqdl.md#dqdl-syntax-rule-expressions).

**Example: Null value percentage**

The following example rules check if more than 95 percent of the values in a column are complete.

```
Completeness "First_Name" > 0.95
Completeness "First_Name" > 0.95 where "weightinkgs > 10"
```

 **Sample dynamic rules** 
+ `Completeness "colA" between min(last(5)) - 1 and max(last(5)) + 1`
+ `Completeness "colA" <= avg(last(10))`

**Null behavior**

 Note on CSV Data Formats: Blank rows on CSV columns can display multiple behaviors. 
+  If a column is of `String` type, the blank row will be recognized as an empty string and will not fail the `Completeness` rule. 
+  If a column is of another data type like `Int`, the blank row will be recognized as `NULL` and will fail the `Completeness` rule.