I can see what Royce was getting at with his circle charts, but I feel that the information might have been related more effectively in an additive bar chart. Looking at the data in the circle chart, at first, gives the viewer the illusion that the data is almost negligible between the city, district, and census tract; only when are the numbers more carefully considered does the difference begin to show itself. If they were in a bar chart where the numbers built on each other, the impact of this data might be more clear.
This is a very astute observation, Beth. Royce, the donut chart might not be the best tool here, since you are not just trying to articulate what all makes up the whole, but actually trying to draw comparisons both within and across your three charts. It is worth trying a full-on pie chart, which showcases areas of difference, or maybe even better, a stacked bar chart—all at the same scale—as Beth recommends.
2) Is the chart or graph type that has been designed the best way to represent this data? Can you recommend an alternate representation (or a different data set) that might be more effective?
Once again I love the use of the donut graph. In this presentation it even takes one more step to show all three scales which correlate with the size of the pie chart. It also has yet another layer of data with the amount of the percentage of the donut graph representing people commuting by car and then the color representing income.
The graphs documenting the phenomenon is a good study in various ways to show the same information. While you can clearly see the findings are nearly identical at Red Hook Houses and Monarch Luggage lofts. I feel like the combination bar chart may have been more useful if it showed the two data sets separately instead of the averages that way you would be able to see how similar they are.
Chris obliquely gets at a question I have: Royce, you’re setting up comparison between Monarch and Red Hook Houses, but what should I get from the comparison? The numbers are almost identical. I also don’t know what the other differences are between these two areas. Why should they be compared?
And Chris also notes that you’ve presented the same data in multiple ways, which is fine for an exercise, but you’ll want to decide on a single approach for your data once you determine what the point is you’d like it to make.
[How well do the new slides communicate context, hierarchy and balance? How well do they use grids, color, typography and the other key concepts we’ve discussed in class?]
A lot of thought has been paid here to typography, and it pays off. The text is legible, the differences in size and use of bold typeface keep things interesting, the colors are consistent and attractive. Dividing the first two slides in half helps tell the story by giving a clear order to the concepts. Overall the data comes through neat and tight. Keep it coming!
I agree. A lot of care has been taken here in structure, layout and type and color palettes, from the sketches through execution. Good work, Royce.
My further notes:
+ Would still be useful to see a context map to place us.
+ Maybe you should just call these three types of cars ‘New, Maintained and Aged’, and eliminate the A, B and C? Would make it easier when you refer to them later; otherwise, I have to keep track of it, or you have to remind me what they mean. That might throw off your icons though, so you should decide. On Slide 3, I need a reminder of definitions; if you stick with your current scheme, maybe Slide 3 uses your icons/definitions from Slide 1 again.
+ Your headlines are too agnostic. Direct me as a viewer to the point you’re trying to make. On Slide 5, for example, it might (for example) be “CT 59 has many mid-income car commuters.” And then I’d ask you to make sure that the slide is laid out/set up to communicate that point clearly. Right now, what is the point you’re trying to make?
+ On Slide 5, it’s hard to understand what your percentages add up to—after some reflection, it seems to me it’s all car commuters in each of the geographical zones? Maybe your labels here need to be clearer.
+ Icon is good, clean, legible even at small scale.
+ On Slide 5, it seems as if you are trying to call attention to the lower income brackets, since everything else is in grayscale. Is this the case? If not, you might consider making all of the income colors tints of the same color, which become more intense as the numbers increase?
+ Percentages might not be very useful here for comparing numbers of cars sighted when the sample is so manageable. Perhaps better would be to either keep your bars and label them with straight-up numbers or to make something like a count chart, which arrays icons that represent each instance.
+ The pie charts on Slide 8 do not seem very useful.
+ Great to see all your sketches and notes. As you work out what the message of each slide is, your layout will continue to change, but it’s good to see you thinking so carefully about the information you’re presenting.
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