In this part of the data visualization project, we will review charts that help find similarities and differences between various categories of data and discuss their purposes and specifics.
But firstly, let’s sort out what a discrete data is.
Data is discrete if you can answer affirmatively on the following questions about it:
Discrete data can contain only a finite number of values. One of its notable properties is that, unlike continuous data, it can’t be measured, only counted.
Examples of discrete data: the number of players in a team, the number of planets in the Solar System.Examples of non-discrete (continuous) data: height, weight, length, income, temperature.
The simplest and the most popular type of chart. It displays grouped data using rectangular bars with lengths that are proportional to the values. Bar charts are broadly used in marketing and finance.
Purpose
Use it to compare data points that are spread across categories with each other.
Pros
Recommendation
Examples and variations
A stacked bar chart is composed of multiple bar series stacked horizontally one after the other. This modification of the bar chart makes it easier to track the variation in the individual values and their total value.
Purpose
Use it if you are interested in the proportional contributions either of categories to the total or of values within each category.
Pros
Recommendation
Example
It’s constructed the same way as a bar chart but with a vertical axis for categories and a horizontal — for their values.
Purpose
It helps track changes in values over time by comparing total column lengths.
Pros
Recommendation
Examples and variations
A stacked column chart is composed of multiple column data series stacked on top of one another.
Purpose
The stacked column chart is designed to compare totals and notice changes at the item level that are likely to have the most impact on changes in totals.
Pros
Examples
A bullet chart is a modification of a bar chart adapted by modern business needs. It can be displayed both vertical and horizontal. The chart consists of a target marker that represents the target value, an achievement bar that represents the current value of a metric and a comparison range.
Purpose
It was designed by Stephen Few for tracking progress toward a goal and measuring how far you are from the target.
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Example
Usual meaning: the lighter the background, the better the result. However, in the case of “Expenses”, according to its negative sense, you can reverse the quantitative scale.
In this chart, each variable’s axis starts from the center point. Axes are arranged radially around it. The value is presented by an anchor on the axis. This data point is connected with the axis by a line. It’s the process of plotting a polygon. As you may notice, it reminds a spider web; hence the name. Equivalent names are ‘polar chart’, ‘web chat’, ‘radar chart’, and ‘star plot’.
Purpose
It’s designed for comparing multivariate data that has three or more quantitative variables.
Pros
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Examples
We truly hope this overview will help you decide which charts are best suited for your data and get a general idea about how you can compare discrete groups of data graphically.
Stay tuned for further updates!
Originally published at www.webdatarocks.com.