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Chapter 2 Creating and Opening Files 33
Importing Data
SELECT AVG(OCT) FROM Solubil WHERE LABELS LIKE ‘%OL’
Note: When using aggregate functions, the column names in the resulting JMP data table are
Expr1000, Expr1001, and so on. You’ll probably want to rename them after the fetch is completed.
The GROUP BY and HAVING Commands
The GROUP BY and HAVING commands are especially useful with the aggregate functions. They enable
you to execute the aggregate function multiple times based on the value of a field in the data set.
For example, you might want to count the number of records in the data table that have ETH=0,
ETH=1, and so on, for each value of ETH.
• SELECT COUNT(ETH) FROM Solubil GROUP BY (ETH) returns a single column of data, with
each entry corresponding to one level of ETH.
• SELECT COUNT(ETH) FROM Solubil GROUP BY (ETH) WHERE OCT > 0 does the same thing
as the above statement, but only for rows where OCT > 0.
When using GROUP BY with an aggregate function of a column, include the column itself in the
SELECT statement. For example,
SELECT ETH, COUNT(ETH) FROM Solubil GROUP BY (ETH)
returns a column containing the levels of ETH in addition to the counts.
2 Creating and Opening Files
Using Subqueries
Aggregate functions are also useful for computing values to use in a WHERE statement. For example, you
might want to fetch all values that have greater-than-average values of ETH. In other words, you want to
find the average value of ETH, and then select only those records that have values greater than this
average. Remember that SELECT AVG(ETH) FROM Solubil fetches the average you are interested in.
So, the appropriate SQL command uses this statement in the WHERE conditional:
SELECT * FROM Solubil WHERE ETH > (SELECT AVG(ETH) FROM Solubil)
Saving and Loading SQL Queries
After constructing a query, you might want to repeat the query at a later time. You do not have to
hand-type the query each time you want to use it. Instead, you can export the query to an external file.
To do this, click the Export SQL button in the window shown in Figure 2.12. This brings up a window
that lets you save your SQL query as a text file.
To load a saved query, click the Import SQL button in the window shown in Figure 2.12. This brings
up a window that lets you navigate to your saved query. When you open the query, it is loaded into the
window.
Using the WHERE Clause Editor
JMP provides help building WHERE clauses for SQL queries during ODBC import. It provides a WHERE
clause editor that helps you build basic expressions using common SQL features, allowing
vendor-specific functions. For example, you do not need to know whether SQL uses ‘=’ or ‘==’ for
comparison, or avg() or average() for averaging.