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I have dataset include about 100 observations, say all of them are in (x,y) format, all of y is in integer format. I need proc sgplot to make a graphic about them. The range about my y is from 1 to 150. I hope I can force the graphic to show every corresponding y value on the y-axis instead of automatically reducing the ticks to a small number in order to show them clearly. For example, if the first five value of my y is (1,3,4,6,7,....), I hope the y tick shows exactly (1,3,4,6,7,....) instead (1,5,...).
I tried

yaxis value=(1 to 150 by 1) valueshint display=all;

It does not work as maybe I have too many observations. I know the result maybe overwhelming, but I just want to see the result. Thanks.

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1 Answers

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You don't say if you're using SAS/GRAPH or ODS GRAPHICS (SGPLOT etc.), so I'll answer the latter which is what I know; the answer should be useful for both in concept.

You likely cannot get SAS to plot so much on the axis unless the axis is very large itself. This means you have two options.

  • Raise the size of the graphic produced a lot in terms of pixels(and then shrink that to a usable size via image physical size, or using an external tool). Not necessarily usable in all cases, but produces a very high resolution plot (which is very big size-wise). This page explains how to do that for ODS graphics (use image_dpi as a high number, and width and height in inches as a normal number), and this page explains for SAS/GRAPH. You may need to make your font small to make it work (if you're adding numbers, which I assume you are), or you may need to make an initially large plot first and then go into paint/photoshop/gimp/etc. and make it smaller.
  • Use annotate to create the axis marks. This is fairly easy if you know how to use annotate, as you're just writing to the location of the axis (y) and the item (x), and then a bit below that for the text. This will make it very easy to make a total garbage plot, but it will likely work ultimately.

These likely work in both SAS/GRAPH and ODS GRAPHICS, and I can't test either as you don't post any code or simulated data to test with, but I think both approaches have some merit (as does the approach of "don't do this", but you've thought that through).