Visualizing matrix with high numerosity? I have a matrix with many rows (>18000) and few columns (6), where five are numerical and one is a binary factor and i'd like to find an efficient and simple way to visualize the relationship between the factor and the other variables.
I want to find out how observations with, for example,  categorical value = 1 correlates with each numerical variable.
I tried a pca and visualized the result as a biplot and it kinda works, but i would like to try other solution possibly.
Do you guys have any idea ?

How about a logistic regression, where you predict the categorical based on the numerical columns. You can also do this regression for subsets, find the R^2 / explanatory value for each subset, to see which numerical values are useful. For nonlinear relationships, doing the same thing with a random forest, or even just a single decision tree, can be very effective.
