ISMISSING Function
The ISMISSING
function tests whether a column of values is missing or null. For input column references, this function returns true
or false
.
You can define a conditional test in a single step for valid values. See IFMISSING Function.
Missing values are different from null values. To test for the presence of null values exclusively, see ISNULL Function.
Wrangle vs. SQL: This function is part of Wrangle, a proprietary data transformation language. Wrangle is not SQL. For more information, see Wrangle Language.
Basic Usage
ismissing(Qty)
Output: Returns true
if the value in the Qty
column is missing.
Syntax and Arguments
ismissing(column_string)
Argument | Required? | Data Type | Description |
---|---|---|---|
column_string | Y | string | Name of column or string literal to be applied to the function |
For more information on syntax standards, see Language Documentation Syntax Notes.
column_string
Name of the column or string literal to be tested for missing values.
Missing literals or column values generate missing string results.
Multiple columns are supported.
Wildcards are not supported.
Usage Notes:
Required? | Data Type | Example Value |
---|---|---|
Yes | String literal or column reference | myColumn |
Examples
ヒント
For additional examples, see Common Tasks.
Example - Type check functions
This example illustrates how various type checking functions can be applied to your data.
Functions:
Item | Description |
---|---|
VALID Function | Tests whether a set of values is valid for a specified data type and is not a null value. |
ISMISMATCHED Function | Tests whether a set of values is not valid for a specified data type. |
ISMISSING Function | The |
ISNULL Function | The |
NULL Function | The |
Source:
Some source values that should match the State and Integer data types:
State | Qty |
---|---|
CA | 10 |
OR | -10 |
WA | 2.5 |
ZZ | 15 |
ID | |
4 |
Transformation:
Invalid State values: You can test for invalid values for State using the following:
Transformation Name | |
---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | ISMISMATCHED (State, 'State') |
The above transform flags rows 4 and 6 as mismatched.
注記
A missing value is not valid for a type, including String type.
Invalid Integer values: You can test for valid matches for Qty using the following:
Transformation Name | |
---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | (ISVALID (Qty, 'Integer') && (Qty > 0)) |
Parameter: New column name | 'valid_Qty' |
The above transform flags as valid all rows where theQty
column is a valid integer that is greater than zero.
Missing values: The following transform tests for the presence of missing values in either column:
Transformation Name | |
---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | (ISMISSING(State) || ISMISSING(Qty)) |
Parameter: New column name | 'missing_State_Qty' |
After re-organizing the columns using the move
transform, the dataset should now look like the following:
State | Qty | mismatched_State | valid_Qty | missing_State_Qty |
---|---|---|---|---|
CA | 10 | false | true | false |
OR | -10 | false | false | false |
WA | 2.5 | false | false | false |
ZZ | 15 | true | true | false |
ID | false | false | true | |
4 | false | true | true |
Since the data does not contain null values, the following transform generates null values based on the preceding criteria:
Transformation Name | |
---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | ((mismatched_State == 'true') || (valid_Qty == 'false') || (missing_State_Qty == 'true')) ? NULL() : 'ok' |
Parameter: New column name | 'status' |
You can then use the ISNULL
check to remove the rows that fail the above test:
Transformation Name | |
---|---|
Parameter: Condition | Custom formula |
Parameter: Type of formula | Custom single |
Parameter: Condition | ISNULL('status') |
Parameter: Action | Delete matching rows |
Results:
Based on the above tests, the output dataset contains one row:
State | Qty | mismatched_State | valid_Qty | missing_State_Qty | status |
---|---|---|---|---|---|
CA | 10 | false | true | false | ok |