Interactive plots in PCA with Factoshiny

February 16, 2017
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(This article was first published on François Husson, and kindly contributed to R-bloggers)

A beautiful graph tells more than a lenghtly speach!!

So it is crucial to improve the graphs obtained by Principal Component Analysis or (Multiple) Correspondence Analysis. The package Factoshiny allows us to easily improve these graphs interactively.

The package Factoshiny makes interacting with R and FactoMineR simpler, thus facilitating selection and addition of supplementary information. The main advantage of this package is that you don’t need to know the lines of code, and moreover that you can modify the graphical options and see instantly how the graphs are improved. You can visualize this video to see how to use Factoshiny.

essai_gif

The interface allows us to define the parameters of the methods and to modify the graphical options. The results (the graphs and the indicators) are updated automatically. For instance, in the animation, individuals are colored in terms of the category they belong to, for a given qualitative variable. Then we modify the threshold to label the individuals according to their quality of representation in the plane. In such a way, individuals that are badly represented have transparent labels.

Once the “beautiful graphs” are done, you can download the plots but you can also obtain the lines of code to redo the analysis. It is also possible to save and then reuse the object resulting from Factoshiny in order to further modify the graphs, using the configuration described previously. The interface is re-opened as it was when we left it. So we can modify the parameters of the method or the graphical options.

 

To leave a comment for the author, please follow the link and comment on their blog: François Husson.

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