ggally | R package that extends ggplot2 | Data Visualization library

Using ggplot, dplyr and tidyr you can try:

Not sure if your question asks for a line as in the example from GGally or if you want points as in the question. So have included both the line and point version you can just remove the line of ggplot code to get what you need.

Replace somClusters with clusters in the definition of the background color in the last plot. The main issue is that you defined somClusters to have three values, not 8. If you use that to index the vector of colors, it will only have three colors.

If you want to colour the points and produce a regression fitted line by group then you need to map the aesthetics to some variable.

In the general case you can add the mapping to the top level, and this will split all the panels by group.

TLDR: the first one listed, so "pearson"

A bit more info:

Line 8 specifies that method <- match.arg(method).

This means that if the user specified method="something" then "something" is used.

However, if the user does not specify the method argument, then the default method = c("pearson", "kendall", "spearman") is used. Ah, but then you will ask, which one? There's 3 listed there! The answer to that is in how the match.arg function works. See ?match.arg, which states that the first element is used.

So in this case, if you call cor(x, y) without specifying the method argument, it's the same as cor(x, y, method="pearson"). @missuse provides an example in the comments at the top, which I've copied here:

From what I can see, using iris.som$unit.classif & iris.som$grid is the way to go in isolating circles within the plotting grid. I have made an assumption that the classifier value matches the row index of iris.som$grid so this will need some more validation. Let me know if this helps your problem :)

Yup. You just have to be careful with the values. Remember how the factors are coded internally: they are just spicy integer variables with value labels (similar to names). You can losslessly cast it to character or to numeric. For the sake of plotting, you need numbers for line coordinates, so the factor-y nature of your variables will come at the end.

Remember that the quality of your visualisation and the information content depends on the order of your variables in you data set. For factors, labels are absolutely necessary. Help the reader by doing some completely custom improvements impossible in ggplot2 in small steps!

I wrote a custom function allowing anyone to add super-legible text on top of the values that are not so obvious to interpret. Give meaningful names, choose appropriate font size, pass all those extra parameters to the custom function as an ellipsis (...)!

Here you can see that most of the dead patients are female and most of the censored ones are males. Maybe adding some points with slight jitter will give the reader idea about the distributions of these variables.

Looks like your data columns get converted to a factor when adding the groupColumn. To prevent that you could exclude the groupColumn from the columns to be plotted:

BTW: Not sure about the general case. But at least for ggparcoord ggplotly works.

I'm not quite sure where the confusion is coming from, as your intuition seems totally correct to me. When I use the scale_colour_grey() is does exactly what you would expect and what you describe should be the outcome.