When visualizing a linear correlation between two continuous variables, one uses a scatter plot, usually in combination with the Pearson product-moment correlation coefficient. When doing the same for a discrete variable and a continuous variable, one can use a dot plot, in combination with an Intraclass correlation. What would be the best visualization for a correlation (or association) between two discrete variables estimated with Cramér's V?
My default for this situation is to use a mosaic plot. I'll admit this is in part because they are convenient to make in R. One possible drawback of mosaic plots is that they are not symmetrical. It is clearly the case that one variable is the 'independent-ish' variable and the other is the 'dependent-esque' variable. So mosaic plots are a great choice for data that might be analyzed with logistic regression, for example. But if you are thinking about Cramer's V purely as a measure of association, it isn't quite as good. Another option would be a sieve plot, but I find them ugly. I think the nicest option is what seems to be called a dynamic pressure plot. I have an example in my question here: Alternative to sieve / mosaic plots for contingency tables, and @Glen_b works up a couple examples in his answer here: Graph for relationship between two ordinal variables.