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Save and reuse settings of an analysis, example of Principal Component Analysis


Datasets for saving and reusing VBA codes

Two Excel workbooks with both the data and the results can be downloaded by clicking here. The data used is the process of food measurements samples.

Generating the settings to reuse

We are going to create a Principal component analysis template on one dataset and use it on the second.

Open the first file called Automation_1.xls.

Enabling advanced options

Once XLSTAT-Pro is activated, go to the menu Options, and in the tab Advanced enable the option named Show the advanced buttons in the dialog boxes.

Principal Component Analysis

Setting up an analysis - example of Principal Component Analysis

Then select the XLSTAT / Analyzing data / Principal components analysis command, or click on the corresponding button of the Analyzing Data toolbar (see below).

Principal Component AnalysisPrincipal Component Analysis software

In the General tab, set the following:

  • Observations/variables table: Columns B to G
  • Data format: Observations/variables table
  • PCA type: Pearson (n)
  • Variable labels: enabled
  • Observation labels: ticked and select the column A for the sample name
  • Sheet: chosen to display the results in a new sheet

Principal Component Analysis software

Go to the next tab Options. For the option Filter factors, choose Maximum number and set the value to six. This way all the components will be calculated.

Principal Component Analysis in Excel

Go to the tab Outputs. Here we want to get a synthetic report so we will only select the following:

  • Eigenvalues,
  • Factor Loadings,
  • Variables/Factors correlations,
  • Factor scores.

Principal Component Analysis package

Finally we are going to use all three plots that can be selected in the Charts tab:

  • Correlation charts
  • Observations charts
  • Biplots

Principal Component Analysis tools

Now we have specified all the settings we will save the code to be reused.

Generating and saving the settings to be reused

Click on the red button at the bottom left of the dialog box.

Principal Component Analysis with MS Excel

Save the code under a name that is easy for you to remember, for example in this case we use "PCArecipe1".

Principal Component Analysis PCA

Press OK to launch the analysis.

Results of the Principal Component Analysis

Choose the plot for the axes F1 and F2 by clicking Select, then change the selection to Abscissa F3 and Ordinates F4. Once you have completed this, simply click again on Select and then press Done.

Principal Component Analysis tutorial

Take a look at the biplot (shown below).

Principal Component Analysis software Excel

This process is usually to be stable so we can expect little variation. You can see that all the samples are centered tidily around the middle of the plot.

Reusing the settings

Now open the second file Automation_2.xls

Go to the menu Analyzing data / Principal Component Analysis and when the dialog box is open click on the blue button to load the code.

Principal Component Analysis

Select the code "PCArecipe1.txt".

The settings are automatically established. So now simply click on Continue and have a look at the biplot.

Principal Component Analysis biplot

This time one of the samples seems to be further away than the other samples. The sample 13 may be an outlier.

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