In general terms, a null value is a definition that points to nothing. A container for a value, such as a row-column combination or a variable, exists, but the container points to no actual value. |
NOTE: In the platform, null values are a subset of the category identifying missing values. For technical reasons, however, |
Implications:
ISMISSING
function returns true
for null and missing values.ISNULL
function returns true
for a null value and false
for a missing value. See below.For example, the following transform generates a column of null values, which are represented as missing values in the data quality bar.
Null values are displayed with missing values in the Missing values category of the data quality bar (in gray).
You can use the following transform to distinguish between null and missing values. This transform generates a new column of values, which are set to true
if the value in isActive
is a null value:
On import, if a column has a high enough percentage of null values, the platform may retype the column as a String
column, which may yield mismatched values in addition to the missing values that were imported from null values.
Functions:
Transforms:
If needed, you can write a null value to a set of data. In the following example, all missing values in a column are replaced by nulls, using the NULL
function.
NOTE: The |
The following example tests all columns in the range between column1
and column255
for whether a missing value is detected. If so, a null value is written. Otherwise, the column value is written back to the column:
The above transform writes null values, but these values are converted to missing values on export.