We (datavis folks) like to believe that one of the key advantages of charts over tables is that charts are much better at providing context, displaying patterns and so on, while a tables “merely” gives you the exact value.
Fortunately, life is not that simple. Many people dislike charts and a good table with the latest data is more than enough to get the insights they need. This kind of puzzles us. Haven’t they seen the light yet?
Is context overrated?
Let me put it this way: external visual context may be overrated.
Suppose you’re a programmer. You want to solve a very specific problem, like making a routine run faster. You search your favorite tips & tricks site and find what you were looking for. End of story. Your knowledge and experience provide all the context you need. Let’s call it internally supplied context.
If you are a beginner things are a bit different. You probably don’t even know that your routine can run faster. If you do, you don’t exactly know what to look for. And if you do, you don’t know how that new piece of code works and you need help. You need explicit externally supplied context.
Journalists and graphic designers love external context (hence they love charts) because they are not subject-matter experts. They work with other people’s data. If I say “an unemployment rate of 12.1%” a subject-matter expert can easily provide internal context, while the journalist (and her audience) need a more explicit external context.
Are patterns overrated?
I’d like to know more about table-based decision-making process, but I suspect that people are less aware of data patterns and more interested in some kind of fluctuation bands, and they compare data points against them. This is an interesting alternative data reduction technique.
The dangers of a consolidated knowledge
Internally supplied context and fluctuation bands are two by-products of a mature and consolidated knowledge. They can be very effective in decision-making and help seeing beyond short-term trends. On the other hand, in a rapidly changing environment they can (dis)miss relevant but unexpected changes.
So, what do we do?
We may not like it, but we must accept the fact that some people are less visual that others and that they can get the information they need from a table or a written report. They already know what they need to know and they can provide the necessary context to deal with a few data points. A chart is useless and redundant.
How can we convince them that a chart is a good thing? Well, try this:
- Don’t tell them quantitatively what they already know qualitatively.
- Show them more complex relationships.
- Try to find unexpected patterns.
- Try to find their pain points and solve them (all processes can be improved).
So, what do you think? How can you convince a table person to become a chart person?
9 thoughts on “Context comes in many ways and shapes”
Another point is make sure you’re right. I know people who prefer tables because they don’t trust other people’s data. They want the raw stuff to look at themselves.
And go beyond just presenting data. What does it mean? What insight can you take from a good chart that is difficult to get from tables of data?
A segment of the short course I offer is “Turning Tables into Graphs.” It’s often amazing to see the unexpected relationships one sees from the graphs that one misses from the tables alone. I was sitting with someone at a conference break who told me he preferred tables. I pulled out my laptop, showed him an example from that section of my course, and he was converted.
I often find it is better to have charts AND tables. Even better to have them linked interactively. Provides context for those who need it, a means of digging into the data for the more advanced user, and the nuts and bolts for those who know the context already.
Naomi, your keywords are “unexpected relationships”. Often charts just repeat what people already know from experience or by reading a table. If there is no added value, they become less interested in charts and are more likely to miss those unexpected relationships.
How about a visual table? I’m loving tables with heatmaps for some applications.
I produce reports read by a wide audience with varying levels of expertise. Our general rule is to provide both tables and relevant graphics. I agree that visual tables can sometimes be an excellent compromise.
There’s a fly in the ointment, the assumption that tables are only useful for conveying the precision of the values that they present.
One corollary of this is that the presentation of quantities in digit form conveys no quantitative comparison in the manner of other visualizations, e.g. quantity-proportionate bars.
This is untrue – the digit presentations of value do in fact directly represent relative quantity. For example, consider these quantities:
Clearly, at least to numerate people, which includes the majority of business people accustomed to tables, the quantities are (top-down) increasing, and it’s also clear that the middle value is roughly 10x the top value, and the bottom value is roughly 100x the middle value.
The discussions of the value of tables of numbers fail to recognize these visual properties of decimal-based numbers, and in so doing do a disservice to the discourse.
Anticipating, the inevitable argument: no, the decimal representations to not have the same granularity of discrimination between values as do precisely-proportioned bars (or other presentations). But so what? In many circumstances the rough comparison is good enough, particularly when coupled with the decimal numbers’ precision advantage.
Dang. My number examples would be more convincing if they were in a fixed width font and right-aligned. But I can’t edit the comment and the visual properties are there even so.
Chris, it depends on the data. I’m browsing a table of population by country and that property is clear. But if I switch to proportions it’s another story because the range is much smaller.
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