![]() ![]() If you are COUNTing, you need to make NULL the thing that your are not counting. Just so know the error I get when importing at the moment is syntax error at or about "CASE WHEN sopOrder_0.SooParentOrderRefer" (10713)Ĭount distinct on the SooOrderNumber or the SooParentOrderReference, whichever makes more sense for you. I have tried using the following line but it errors on me when importing:, Count(DISTINCT CASE WHEN SopOrder_0.SooParentOrderReference LIKE 'INT%' THEN SopOrder_0.SooParentOrderReference ELSE 0 END) AS 'INT' SopOrder_0.SopOrderID = SopOrderItem_0.SopOrderIDĪND Company_0.CompanyID = SopOrder_0.CompanyID , SUM(CASE WHEN SopOrder_0.SooParentOrderReference LIKE 'WEB%' THEN 1 ELSE 0 END) AS 'WEB' , SUM(CASE WHEN SopOrder_0.SooParentOrderReference LIKE 'INT%' THEN 1 ELSE 0 END) AS 'INT' , SUM(SopOrderItem_0.SoiValue) AS 'Order Value' , SUM(CASE WHEN SopOrder_0.SooOrderNumber IS NOT NULL THEN 1 ELSE 0 END) AS 'Order Items' , Count(DISTINCT SopOrder_0.SooOrderNumber) AS 'Orders' Unfortunately I do not have SSMS and Microsoft Query is just useless. This pull from a Progress V10 ODBC that I connect through Excel. This is why I think I need a Count Distinct Case When. Now it is not a hard and fast rule that it is always doubled up. What currently comes out Company Name Order Date Order Items Orders Value WEB INTĪs you can see from my current result it is counting every line even though it is the same reference. How I expect it to be: Company Name Order Date Order Items Orders Value WEB INT Original data looks like: Company Name Order Date Order Items Orders Value REF Please see below where I have broken down what it is doing and how I expect it to be. From research I have tried creating a Count Distinct Case When statement to provide me with the results. I have been able to split this out so it does the count of how many times they appear but unfortunately it is not providing me with the intended result. ![]() I have two unique Ids that identify if and order is Internal or Web. In other words, you can remove duplicate values in the calculation.įor examples of this see How to Remove Duplicates from SQLite Count() Results.I have been building up a query today and I have got stuck. You can add the DISTINCT keyword to count only distinct values. One handy use case for count() is to use it in conjunction with the GROUP BY clause, so that multiple rows are returned – each one representing a group – with a count of the rows in that group. SELECT count(Fax)īut you can do something like this instead: SELECT count(Fax) The result is not calculated after any LIMIT clause. So we can see that only rows 1 and 5 have non-NULL values in the Fax column. Here’s what the results look like with columns returned (and without using the count() function). In this case, there were only two non-NULL values in the Fax column within the result set. The result of count() is calculated after any WHERE clauses. In other words, 47 rows contain a NULL value in the Fax column. In this case, the Fax column has 12 non-NULL values. In this example, I pass the name of a specific column of the table. I ran this query on the Chinook sample database, and so it turns out that there are 59 rows in the Customer table. Here’s a basic example to demonstrate the asterisk (*) syntax to return the number of rows in a table. ![]() So in this case, X could be the name of a column, and the asterisk ( *) wildcard is used to specify the total number of rows in the group. If you provide the name of a column, it will return the number of times that column is not NULL. If you pass in the asterisk ( *) wildcard character, it will return the total number of rows in the group. It can also be used to return the number of times a given column is not NULL in the result set. The SQLite count() function can be used to return the number of rows in a result set. ![]()
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