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What about radar charts? One application of radar charts is the control of quality improvement to display the performance metrics of any ongoing program. They are also being used in sports to chart players' strengths and weaknesses, where they are usually called spider charts. Here's a nice example.


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This is a pretty difficult question to answer, so I think the best thing is to give you some ideas to think about. The process of designing interfaces for the purpose of data visualization is a whole subject area in itself, although you'll find plenty of good areas to start with from the likes of Edward Tufte and Stephen Few. So some areas you want to ...


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The total estimate you are giving is a huge number of colors for the user to be able to recall and even distinguish to make any sensible overview of the data they are seeing. And I don't think that at any one time you will have more than, say, 20 colors in one graph in most use cases. And if you will, the graph will become illegible anyways, so what is the ...


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If the chart type doesn't depend on the data provided in 1) and 2), then selecting the chart type first won't be a problem. The problem arises when you can rule out certain types of data after the first steps, as this would lead to an error if the "wrong" data gets provided in later steps. It of course also depends on your target audience. Experienced chart ...


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The first problem is to show the course of a single day in a form the reader can easily grasp; the second is to relate your data series to this picture. Although "time of day" is a simple one-dimensional parameter, we associate a structure with it (workday, evening, lunchtime etc.) which can cause a certain dissonance when we see it plotted in linear form ...


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Keep it simple, and as conventional as possible. Rectangular charts are the most common. Label the axes and pay attention to typography. Maybe use military time. Maybe emphasize (darken) the hour lines on the points of the clock (12, 3, 6, 9...). There's tons of existing charts of this nature out there, I'd spend some time exploring them to glean some ...


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Another alternative for the Y axis label suggested by statistician Naomi Robbins is to place the label above the Y axis. This has the advantage of not having to read the vertical text and does not waste as much space. See the example in the top right chart. IMO the non-centered X axis in your mock up looks fine to me.


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I think that it's pretty standard to place an axis label centered with respect to the corresponding axis. So, your chart's Y axis label looks fine to me, but the X axis label should be centered, in my opinion.


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A few thoughts: Time-multiplex the data. You can cycle through the sets of statistics, displaying each set for about 10 seconds. That way, you can use the entire screen to show only one set. This is only good if it’s not particularly important for users to see every statistic all the time (e.g., the TV is intended to provide an occasional motivation boost ...


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I think a stacked bar would not work in this case, because one value could cancel out another. Since you are measuring the same thing (calories), how about using a pair of bars for each day? Calories in and calories out. Guides or a line chart on top could plot goal numbers to see where the bars SHOULD fall if you are following the diet and exercise plan.


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A histogram might be what you are looking for. A histogram is different from a bar chart. A simple bar chart uses the height to represent the value, but a histogram uses the total area to represent the value. In your case, you can overlay the input and output histogram, and highlight the difference in their area to indicate the total (net) value. A rough ...


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I would change "total" to Net Value, since I guess that's more important. My chart would look like the following.


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Generally speaking, there are 3 main types of data analysis- comparison, transition and composition. For comparisons, Bar and Column charts are the best. For transitions, Line and Area charts work well. For compositions, Pie charts work well. This infographic further explains when to use which chart: ...



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