PSLine2000Documentation/Queries/MachineNames_Crosstab1.md

MachineNames_Crosstab1

Analysis generated on: 4/2/2025 10:01:54 AM

SQL Statement

TRANSFORM Count([WC2]) AS [The Value]
SELECT [MachineName], Count([WC2]) AS [Row Summary]
FROM MachineNames
GROUP BY [MachineName]
PIVOT [WC2];

Dependencies

• Tables/MachineNames

Parameters

• None

What it does

SQL Code Explanation

Table Structure and Data Assumptions

This SQL code is assumed to be part of a larger query that operates on a database table named MachineNames. The table contains columns related to machine names, including at least one column named [WC2], which is used as the input for a pivot operation.

Code Breakdown

---

1. TRANSFORM Count([WC2]) AS [The Value]

This line transforms the count of values in the [WC2] column into a new value with the alias [The Value]. This step prepares the data for the pivot operation by aggregating the counts.

2. SELECT [MachineName], Count([WC2]) AS [Row Summary] FROM MachineNames GROUP BY [MachineName]

This section selects the MachineName column and aggregates the count of values in the [WC2] column using the GROUP BY clause. The resulting data is then filtered to only include unique machine names.

3. PIVOT [WC2];

Finally, this line pivots the aggregated counts for each machine name into separate columns based on the original [WC2] values. However, there seems to be a discrepancy in the code - it should be PIVOT [The Value] instead of [WC2]. Assuming the correct code is used:

• The pivot operation transforms the aggregated counts into separate column headers.
• Each machine name becomes a new row with its corresponding values as separate columns.

Example Output

Assuming the original data in MachineNames table looks like this:

MachineName	WC2
Mach1	10
Mach2	20
Mach3	30

The transformed output would look something like this:

MachineName	Mach1	Mach2	Mach3
Mach1	10	NULL	NULL
Mach2	NULL	20	NULL
Mach3	NULL	NULL	30

In this example, the pivot operation has transformed each machine name into a separate row with its corresponding values as separate columns.