As I understand, Cramer's V method of counting correlation between categorical variables may find correlations between symmetrical data. I searched a ton of sites, but the only thing I found was that it may lead to loss of information. But why is that? Also, may the danger of symmetrical data lead us to choose Theil's U method of finding correlations? Does it perhaps mean that Theil's U method is more safe: we definitely won't have any loss and it's better compared to Cramer's V?
So, in the end, it leads me to the question when is it better to use each method? If both are OK, what must I look for when, for example, comparing heatmaps via Cramer and Theil? What will be the difference between them?
I don't want to dive in the mathematical part of the problem yet and only understand the logic behind it. Also, please, when answering consider describing an example of the data (maybe fictional).