TreeMap Chart: A Data Visualization Technique
Treemapping is a data visualization technique that is used to display hierarchical data using nested rectangles. Also, The treemap chart is created based on this technique of data visualization. Here, Charting facilitates the desired analysis only when data is usually visualized on the right type of chart.
It is utilized for representing hierarchical data in a tree-like structure. Here, Data is organized as branches and sub-branches. Further, it is represented using rectangles. Based on the quantitative variables associated with each rectangle, The dimensions and plot colors of it are calculated. Here, each rectangle represents two numerical values. Also, You can drill down within the data to, theoretically, an unlimited number of levels if needed. So this makes it an at-a-glance snapshot distinguishing between categories and data values very easy.
Now, Let’s Take a look at the chart sample shown below:
If in case you’ve worked with data visualization extensively, you’d know that this varies not just the only the basis of your data. but it also depends on the kind of analysis you want to facilitate.
Ideal use cases for a Treemap
Like every other chart type and data visualization technique, It work well only if it can be used in situations that justify its use case. Now, Let’s take a look at what are the ideal use instances that warrant the use of a treemap:
1. Studying of data w.r.t two quantitative values
The data which you have needs to be analyzed w.r.t 2 quantitative values. Here, Each rectangle (node) in the treemap showcases the values for two quantitative values. Like said above, the measurements of the rectangles in the sample treemap (above) represent the models sold for a model in the current year. And, the color represents the development in sales w.r.t the previous year sales.
2. A large amount of hierarchical data but with a space constraint
For suppose, You have a very large amount of hierarchical data and a space constraint. In this case, Treemap are equipped to be able to plot more than tens of thousands of data points. There are other charts that can be used for plotting hierarchical data. Two charts that quickly come to mind are and the drag-node chart & multi-level pie chart. However, these charts present an area constraint as the number of data points increases beyond a certain limit. Additionally, the multi-level pie chart is definitely circular while the treemap can be linear. Therefore, a linear chart is certainly easier to read and understand than a circular one.
3. To identify the trends and patterns between the node
Do you like to see high-level summary data of anomalies & similarities within 1 category as well as between 2 groups?. Then, based on the numerical values assigned to each node, The dimensions and colors of the rectangles (nodes) in a treemap are configured. So this makes it easy to identify the trends and patterns between the nodes of all the classes plotted on the chart as well between your nodes of a single category. For example, Honda-manufactured bikes have done better in the Street category than in any other category.
4. For detailed study & representation of data
Your data can be organized at several amounts. Here, Treemap charts support the drill-down feature. Tree chart users can simply drill down to do a detailed study of data at many granular levels.
5. To showcases data in a better & meaningful way
For example, It showcases region-wise literacy rates and population predicated on the info collected for a period of one year. Here, The size of each rectangle represents the population, the color represents the literacy rate.
Limitations of a Treemap
The treemap poses the following limitations:
1. You cannot display data that varies in magnitude.
2. Out of the two quantitative variables that a rectangle represents, the variable standing for the size of the rectangle cannot have a negative value.
3. From the area of the rectangle, one of the values a rectangle stands for is to be gauged. In fact, this is slightly difficult when compared to other charts where you can gauge values from the length of the data plot.
4. Within the parent node of treemap charts, the rectangles are automatically ordered by area. It does not provide for any more sorting options.
5. Treemaps having a large number of data factors on a single level are very unsuitable for print.
6. Treemap charts need a significant amount of effort when you are creating one. However, once you’ve figured them out, then there aren’t many charts that can pack as much a punch as these charts for showcasing hierarchical data.
Therefore, To represent hierarchical data in a tree-like format, always use Treemap charts. Usually, in Treemaps, Data is always organized as branches & sub-branches. Further, Parent-child hierarchies can be represented in an efficient way by using elements of treemap & they are readily organized.