January 2019
Beginner to intermediate
670 pages
18h 32m
English
book
Tableau 2019.x Cookbook
by Dmitry Anoshin, Teodora Matic, Slaven Bogdanovic, Tania Lincoln, Dmitrii Shirokov
Content preview from Tableau 2019.x Cookbook
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How it works...
Correspondence analysis works similarly to PCA, which we covered in the first recipe, Discovering latent structure of the dataset, of this chapter. It reduces the number of dimensions that differentiate our cases (in this example, brands) so we have a clearer overview of how each of the brands is positioned. On the x and y axes, we plotted the first two dimensions extracted by correspondence analysis, which have the same function as the first two principal components in the principal components analysis.
Both the brands and the attributes describing them are plotted in the space created by the first two dimensions. We interpret the results, or read the map, by looking at the spatial relationship of attributes and brands. ...
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