If there are too many data points too close together in an image, it can look pretty choppy.


In this case, we are tracking number of data points over time; eg 500 per minute, 500 per minute, etc.

Are there any guidelines about how dense your datapoints can/should be in a chart?

  • Although I'm not sure exactly what data you're displaying and where it's being used, a useful way of packing high-density charts into small areas is to go with Sparklines.
    – JonW
    Feb 23, 2012 at 12:20
  • One thing to consider is that if the users care about slope, that will be most legible and comparable where the axes are scaled in an optimal way so that slopes are closest to 45 degrees as possible, I believe. Can't seem to find the attribution for that - I think it's Tufte. Feb 23, 2012 at 18:32
  • Jon W: The sparklines shown there don't have the same problem I'm having of super jagged peaks and valleys. Feb 23, 2012 at 20:30

1 Answer 1


As ever, it depends, and really this question is unanswerable without knowing more.

It depends on what your users want to take away from the graph. Some may be concerned about the spikes (which would otherwise be lost if data points were too widespread), where as others may interested in an overview in which case something like the following may suit better - calculated as a rolling average, while yet again others may be interested in a flat-line average.

enter image description here

As a generalisation, compare for example the needs of technical, marketing and management. Tech might be interested in spikes; Marketing in variations at time of day; Management in the comparison between this time yesterday or last week.

So your data points depend entirely on what your users need to know. If your users have different needs then provide that via different sets of information - either different graphs or overlaying as appropriate (like in the example above), but always do as much work as is necessary for your users to see the takeaways without having to manually process the information. This may include providing actual numbers (max, min, average, total, comparison with other time period etc etc).

Remember - graphs are not there just for the sake of being there - filling a gap and looking pretty - they should serve the purpose of communicating required information easily to the user.

  • Youtibe (and google analytical tools in general) has a nice way of dealing with this; in data-over-time charts they usually let you pick whether each point is a day, week or month, giving you a nice range of granularity. By-month charts are very smooth but by-day charts show the peaks and valleys.
    – Ben Brocka
    Apr 18, 2013 at 15:58

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