How to Represent Data with Intelligent Use of the Coordinate System

The most widely used coordinate system to represent data is the Cartesian coordinates followed by Polar coordinates

Basically, Cartesian coordinate system uses a grid of straight lines while Polar coordinate system uses a grid of circles to represent data.

Let’s now look at a few examples where with the appropriate use of the systems discussed above, we will able to visualize different aspects of the data.

The standard graphic visualization for a categorical variable is bar charts. Bar charts are useful if you are dealing with a low number of categories within a variable.

The bar chart, above represents the App Launches by the Operating system.

Suppose, we need to check the App launches by various countries. In this case, there may be many categories as shown below:

The bar chart above makes inefficient use of space since there are many countries. In such a case, you could restrict the bars to the top 5 countries by App Launches, but you’ll end up sacrificing the information about other countries which could help you see a much bigger picture.

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What if we flip the coordinate system to Polar from Cartesian?

The above plot looks better than the bar chart on cartesian coordinate system. You can instantly draw the conclusion about the top countries by App Launches.

Well, things are getting better, but still we can’t make out the proportion accounted by the top contributors unless we also indicate the percentages along with the counts.

Now, lets look at another class of plots known as Tree Maps, which is plotted on the Cartesian coordinate system. A Tree map is shown in the form of a rectangle with each country shown as nested rectangles inside it. The area occupied by each rectangle is proportional to the count of the App Launches in each country to the total App Launches as shown below:

United States has the highest share of the App Launches since the area occupied by its rectangle is the highest.;

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