For instance, the following statement executed against an ADO Recordset object returns an error:. That's because ADO doesn't recognize the Is operator in this context. The ADO library supports the Equals and Inequality operators when searching for or excluding null values.
Fortunately, the correction is as simple as replacing the Is operator with the Equals operator:. You'll find Access a bit of an oddball on this issue. Many libraries use the Equals and Inequality operators instead of Is. If a non-native library returns an error when working with null values, this switch will probably do the trick. Not all aggregate functions consider null values. The good news is, there's a bit of reason to the inconsistency. An aggregate function that evaluates a field does not evaluate null values in its result.
However, Count , First , and Last do evaluate null values. It makes sense that they would--just because one field contains a null value doesn't negate the row's purpose within the context of the domain. If you want to exclude null values in a count, specify the field in the form Count field.
The result of both forms may or may not be the same. The point is, the field-specific form won't consider null values in its count. Otherwise, Jet excludes the row from the results. This behavior is inherent in the equality issue discussed in 3. Because Null doesn't equal anything, it can't satisfy a condition other than Is Null. For instance, the simple expression.
Now, that might be what you want, but it might not. If you want to include null values, include Is Null in the condition as follows:. Instead, Jet sorts null values to the top or the bottom of the result set, depending on the sort order.
For instance, the following query includes records where the Region field is Null:. The result isn't right or wrong, it just might not be what you want. You must explicitly exclude null values. There's no specific method for explicitly excluding null values. The statement's purpose will dictate the solution. A null value is an acceptable value. However, too many null values often point to an unnormalized table. For instance, if you store customer phone and fax numbers, you might end up with a lot of empty fax number fields.
Even if you have no null values, your table's still not normalized properly, in this case. To normalize the phone data, you'd add a table that includes three fields: the foreign key column that relates the phone record to its corresponding customer, the phone number type, and the phone number.
The phone number type would identify the phone number as an office, fax, home, cell, and so on. Then, you'd enter phone number records only when appropriate, eliminating null values. If the customer has no fax, there'd be no record for a fax number. Susan Sales Harkins is an IT consultant, specializing in desktop solutions. Previously, she was editor in chief for The Cobb Group, the world's largest publisher of technical journals. Editor's Picks. The best programming languages to learn in Check for Log4j vulnerabilities with this simple-to-use script.
TasksBoard is the kanban interface for Google Tasks you've been waiting for. Paging Zefram Cochrane: Humans have figured out how to make a warp bubble. Comment and share: 10 tricks for handling null values in Microsoft Access. Show Comments. Hide Comments. My Profile Log out. Join Discussion. Learn more. Asked 8 years, 3 months ago.
Active 5 years, 10 months ago. Viewed 48k times. ClientNumber, IIf h. ClientNumber ; I think the reason is that the check for null in the If operation is not written correctly. Improve this question. Mosh Feu CodeMed CodeMed Add a comment. Active Oldest Votes.
Improve this answer. Chris Rolliston Chris Rolliston 4, 1 1 gold badge 14 14 silver badges 19 19 bronze badges. And credit for the answer. Thank you for the quick and correct response. IIf IsNull GordThompson - why do you say 'more traditional'? But like I said, "If it works Sign up or log in Sign up using Google. Sign up using Facebook.
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