Transforming XML with XSLT

I’ve done some work previously in XSLT to nicely format XML output within a browser.

Presently, some code I’m working with also does this transforming of an XML output via XSLT into a HTML file. I wanted to modify the XSLT, but found I’d made an error, so without having to pre-configure data and run the process every time every time in a more timeconsuming iterative debugging approach, I was able to do the following manually.

Having an XML file called example.xml and an XSLT file called example.xslt, by adding the second line below manually to the XML file I was able to then render the XML file in a Browser, which then reported the error enabling me to easily correct.

`



…
`

It would have been nice if the browser could accept this for the XML file without the need to manually modify it. There probably is a better way, or a more specify XML GUI tool, but the time to find this out, maybe next time.

Here is a Beginner XSLT reference.

Tagged with: General Web Development

Producing Alternative Means statistics with SQL

Producing Alternative Means statistics with SQL

MySQL’s built-in AVG() computes the arithmetic mean — the sum divided by the count. That is the right default for many questions, but it is not always the right measure of central tendency.

Extending MySQL Capabilities with UDFs, Plugins and Components

Extending MySQL Capabilities with UDFs, Plugins and Components

MySQL offers three different approaches to extending the SQL capabilities with the default product you download and install. These are: User Defined Function (UDF) MySQL Manual MySQL Plugin MySQL Manual MySQL Component MySQL Manual For the purposes of this post I will be using the current LTS version MySQL 8.

Producing One-Sample Z-Test statistics with SQL

Producing One-Sample Z-Test statistics with SQL

The one-sample Z-test determines whether a sample mean differs significantly from a known population mean when the population standard deviation is also known. It is the appropriate test when the population parameters are established — quality control benchmarks, national averages, long-run process measurements — and you want to evaluate whether a new sample is consistent with them.