How to reduce the gap between the grouped bars in Domo card?

art_in_sky

I am currently building a grouped bar chart by year. I find the chart inappropriate with a lot of space between grouped bars making it look visually unappealing. How do I decrease the space between the grouped bars and make it look presentable?

DavidChurchman

It looks like you have a distinct set of categories for each cluster. The gap is a result of showing the null values for each category that a cluster does not contain. I count at least 15 different colors in your series, so the first cluster shows the values for all your "blues", and then 0s/nulls for all your greens and oranges. Your second cluster shows the values for all your greens and 0s/nulls for all your blues and oranges, and so on.

If you want tighter fit between your clusters, you need to standardize the series in some way so that it's the same (or same-ish) for each cluster. Like, the first bar in each cluster is "A", the second is "B", and so on. If that doesn't seem viable for your dataset, rather than a clustered bar, you might try a standard bar with a trellis using the category that is splitting up your clusters right now.

It's a little hard to talk in the abstract, but if you gave a sense of your dataset and what you're trying to show, you could get some more specific advice.

ColemenWilson

Chart properties > Bar settings > Width Percentage = 100

art_in_sky

@ColemenWilson This one I tried, however it adjusts the width of the bar but not the space between the grouped bars.

ColemenWilson

Could you share a screenshot? I am playing around with adjusting the percentage and it is impacting the space between the individual bars in the group AND the space between groupings.

art_in_sky

@ColemenWilson Here you go , I have set the bar width as 100 and this is how it looks

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ColemenWilson

Could you screenshot more of analyzer view so I can see what else is going on in the card?

DavidChurchman

It looks like you have a distinct set of categories for each cluster. The gap is a result of showing the null values for each category that a cluster does not contain. I count at least 15 different colors in your series, so the first cluster shows the values for all your "blues", and then 0s/nulls for all your greens and oranges. Your second cluster shows the values for all your greens and 0s/nulls for all your blues and oranges, and so on.

If you want tighter fit between your clusters, you need to standardize the series in some way so that it's the same (or same-ish) for each cluster. Like, the first bar in each cluster is "A", the second is "B", and so on. If that doesn't seem viable for your dataset, rather than a clustered bar, you might try a standard bar with a trellis using the category that is splitting up your clusters right now.

It's a little hard to talk in the abstract, but if you gave a sense of your dataset and what you're trying to show, you could get some more specific advice.