Demystifying Data Visualization
Demystifying Data Visualization
Different types of data visualization are used to analyze distributions, comparisons, relationships, or trends. Learn what type is appropriate for your use case!
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My last article focused on the importance of creating intuitive dashboards. In this article, we will outline some of the charts to be used in a dashboard. Note that aside from the below charts, you can find several others — but these are some of the most widely employed charts in dashboards that help keep panels uncluttered. The same data can be displayed in one or more ways. It all depends on the business objectives and what the audience wants to see. It's essential to have the end users of the dashboard in mind when preparing dashboards.
The distribution of data shows all the possible values (or intervals) of the data and how often they occur. This is an univariate analysis of the data, and the charts help you understand if there are any outliers and help you understand the data, the normal tendency, and the range of information in your values.
For analyzing the data distribution, we can use one of the below graphs:
Histograms and bar charts: Histograms allow you to quickly assess shape, centering, and spread of distribution for a continuous data set. For categorical (nominal or ordinal) variables, bar charts are often used.
Line charts: Line charts are the most frequently used charts and are used for continuous data sets. They are well accommodated for trend-based visualizations of data when the number of data points is very high.
Most of the time, there are requirements when comparing two or more different attributes. We can use any of these types of graphs:
Bar graphs/column graphs: Both can be used for analyzing data happening at a static point in time. Bar graphs are easily evaluated by examining the length of the bars. However, their difference lies in their orientation. A column chart is oriented vertically whereas a bar chart is oriented horizontally.
Line charts can be used to display data or information that changes continuously. Line graphs allow us to compare how the data for different attributes changes over a period of time.
Pie charts are used to compare the parts of a whole. The graph is divided into several sectors, and the area in each sector shows the proportion they represent from the whole.
Relationship charts are well-suited for cases where we want to study the relationships between different variables. These type of charts can show how an attribute has positive, negative, or no effect on other characteristics. To establish such kinds of relationships, we can go with any of the below charts:
Scatter plots show how much one variable is affected by another. The relationship between two variables is called their correlation.
Bubble charts are a variation of a scatter plot in which the data points are substituted with bubbles. The size of the bubbles can form a new dimension of the data.
Line charts can also be used for analyzing the relationships over a period of time.
Trend graphs are used to analyze the tendency of data over a period. Trend graphs have a time dimension and give us information about how a particular attribute is performing during a specific period of time.
Line charts can accommodate the time component in an axis; it is useful for analyzing the trends of data over a period and useful for facilitating trend analyses.
Dual-axis line: A special category of line charts. There are two independent axes that are layered on top of each other. These are useful when you have two measures that have different scales.
Area chart: Same as line charts; however, the area below the plotted lines is filled with color.
Now you know the best way to visualize different types of data!
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