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[Lens] Use different grouping order for non continuous data/charts #54589
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Pinging @elastic/kibana-app (Team:KibanaApp) |
@timroes I think this should be clarified in the UI with a better approach, than just with assumptions, hidden defaults modes.
For the
For the
I think that UX could be implemented providing some nice drop areas with a text that shows what will happen in a position or another: If the user just drop the field on the visualization itself, we can display an opaque overlay on the chart showing the options: drop as a child group/split or drop as an overall aggregation. That's just an idea, we can also fix the From a point of view of defaults:
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I think this is a larger problem that needs to be broken down into smaller problems.
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I am closing this as we have separate issues for tracking the different problems described here |
If you currently have a terms split on the x-axis and then drag in a second field, you'll break down by that 2nd field and group "overall" instead of "per bucket" by default.
I think we should make this decision based on whether the data/chart on the x-axis is "continuous" or not. So I would suggest something like: as long as the type is bar chart and the x-axis is not a date field, we want to use "per bucket" grouping by default, and "overall" otherwise.
Reasoning: If you have non continuous data like strings in a bar chart, it's likely that the bars itself has nothing to do with each other, and if you break down you want to break down each bar individually. As an example, I ran very often into that, when e.g. splitting bars by country/city/airport and then want the top 5 whatever... I usually always want them per country/city/airport and not the top 5 overall. I think you only want the top 5 overall usually if the data you're drawing at the x-axis is continuous, why I would use above distinction as a separation for this decision.
I also feel it's a bit confusing or not very intuitive for non continuous data, because we let the user say: they want the top 3 cities on the x-axis, and break down by (in the following example) top 3 weathers, and they suddenly see potentially more then 3 bars on the x-axis:
@monfera @markov00 What are your feelings towards this?
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