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I am seeking any guidance and hopefully published research for guidance about line density in line graphs.

Here is a hypothetical example: I want to show a line graph depicting frequency of code commits by user name over a period of time. How many users (lines) can be shown in a full screen size graph, without the lines becoming an incomprehensible jumble of spaghetti?

My intuition and plotting sample graphs tells me more than 12-15 or so color-coded lines quickly become indecipherable, but I would really like to find some research to back this up with explicit conclusions and numbers.

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It depends on what you need to show. Usually those graphs will not be needed to identify all twenty or more individual members at the same time. They will be mostly be used in two ways:

  1. to spot deviations from the trend (the outliers, the extremes, the lines that go up as others go down, etc.) For this, you only need to be able to distinguish a line, and on the outsides, this is usually easy. You can use hover- or click-effects to then highligth that individual line (color one, make the others lighter and less saturated), and also provide some information (like the member name)

  2. watch how some individual member compares to others. You could do this by providing a selection (by name or something) and once again, make this line stand out against the others.

You could of course also apply this technique to small selections: highlight and colourcode a few lines. (I think the optimal number of members for such a group will be much smaller than 15, more likely to be the 7+-2 capacity of short-term memory.)

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