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

Runs an expression against the values in a column.

**Syntax**

```
ColumnValues <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: Allowed values**

The following example rule checks whether each value in the specified column is in a set of allowed values (including null, empty, and strings with only whitespaces).

```
ColumnValues "Country" in [ "US", "CA", "UK", NULL, EMPTY, WHITESPACES_ONLY ]
ColumnValues "gender" in ["F", "M"] where "weightinkgs < 10"
```

**Example: Regular expression**

The following example rule checks the values in a column against a regular expression.

```
ColumnValues "First_Name" matches "[a-zA-Z]*"
```

**Example: Date values**

The following example rule checks the values in a date column against a date expression.

```
ColumnValues "Load_Date" > (now() - 3 days)
```

**Example: Numeric values**

The following example rule checks whether the column values match a certain numeric constraint.

```
ColumnValues "Customer_ID" between 1 and 2000
```

**Null behavior**

 For all `ColumnValues` rules (other than `!=` and `NOT IN`), `NULL` rows will fail the rule. If the rule fails due to a null value, the failure reason will display the following: 

```
Value: NULL does not meet the constraint requirement!
```

 The following example compound rule provides a way to explicitly allow for `NULL` values: 

```
(ColumnValues "Age" > 21) OR (ColumnValues "Age" = NULL)
```

 Negated ColumnValues rules using the `!=` and `not in` syntax will pass for `NULL` rows. For example: 

```
ColumnValues "Age" != 21
```

```
ColumnValues "Age" not in [21, 22, 23]
```

 The following examples provide a way to explicitly fail `NULL` values 

```
(ColumnValues "Age" != 21) AND (ColumnValues "Age" != NULL)
```

```
ColumnValues "Age" not in [21, 22, 23, NULL]
```