Top 10 Map Types in Data Visualization

Published in

Towards Data Science

7 min readAug 1, 2019

Why does everyone like to use different maps types to visualize information in news media or data analysis reports?

In addition to the high efficiency of transmitting information, there is another important reason, that is, aesthetics. No matter how boring the content is, as long as it is equipped with a cool map, it will be eye-catching.

Map visualization is used to analyze and display the geographically related data and present it in the form of maps. This kind of data expression is clearer and more intuitive. We can visually see the distribution or proportion of data in each region. It is convenient for everyone to mine deeper information and make better decisions.

There are many types in map visualization, such as administrative maps, heatmaps, statistical maps, trajectory maps, bubble maps, etc. And maps can be divided into 2D maps, 3D maps or static maps, dynamic maps, interactive maps… They are often used in combination with points, lines, bubbles, and more. In this article, you will find examples of the top 10 map types in data visualization!

(NOTE: all the map types in the article are made with FineReport, and the personal download is completely free.)

1. Point Map

Point maps are straightforward, especially for displaying data with a wide distribution of geographic information. For example, some companies have a wide range of business. If the company wants to view the data of each site (specific location) in a certain area, it will be more complicated to implement with general maps, and the accuracy is not high. Then you can use the point map for precise and fast positioning.

Use scenarios: distribution of point events. Point maps can also realize special recognition of big events. Like the accident tracking map above, it can identify relatively serious events with picture, text or dynamic effects.

2. Line Map

You may not use line maps often, because they are relatively difficult to draw. However, the line map sometimes contains not only space but also time. For the analysis of special scenes, its application value is particularly high.

Use scenarios: route distribution for riding or driving, bus or subway line distribution, such as the taxi route of New York City on the map above.

3. Regional Map

A regional map is also called a filling map. It can be displayed by country, province, city, district or even some customized maps. You can know data sizes through shades of color or different colors on the map.

Use scenarios: distribution of some feature in different regions. It can realize the step-by-step drilling from the province to the city. And it can use different colors or labels for different characteristics. For example, in the above picture, we can drill down the data from the province to the city to view the sales. The larger the sales are, the darker the color is.

4. Flow Map

Flow maps are often used to visualize origin-destination flow data. The origin and destination can be points or surfaces. The interaction data between the origin and the destination is usually expressed by a line that connects the geometric center of gravity of the space unit. The width or color of the line indicates the flow direction value between the origin and the destination. Each spatial location can be either a origin or a destination.

Use scenarios: inter-regional trade, traffic flow, population migration, shopping consumption behavior, communication information flow, aviation routes, etc.

5. Heatmap

The heatmap is used to indicate the weight of each point in the geographical range. It is usually displayed in a special highlight. As shown in the figure below, it is a haze map. The darker the color of the area, the worse the air quality of the area.

Use scenarios: PM 2.5 distribution, registration date and age distribution, product preference distribution, etc.

6. Heat Point Map

The heat point map is a comprehensive application of the heat map and the point map. Compared with the heat map, its accuracy of recognition can be higher. And compared with the point map, its point is actually a circle, and the circles overlap each other, which is more layered.

Use scenarios: display of the weight of each complex point within the geographic extent. For example, in the above bus station usage map, the more people there are, the bigger the point is, and the darker the color is. It is also possible to identify the maximum and minimum number of people.

7. Time Space Distribution Map

Such maps visualize the trajectory distribution with both temporal and spatial information. They can record time and spatial distribution of each point.

Use scenarios: GPS geographic tracking, etc.

8. Data Space Distribution Map

We use a concrete example to explain this map. The picture below is a spatial distribution map of passenger flow in rail transit. Different colors identify different lines (more intuitive), and the thickness of the line indicates the traffic volume of different stations (similar to the heat point). The thicker the line is, the larger the traffic is. It can also indicate the direction of the track line.

Use scenarios: through this kind of visualization effect, the operator can clearly know the distribution of passenger flow in a certain period of time, so as to rationally arrange operations (such as the number of employees, etc.).

9. Three-dimensional Rectangular Map

This type of map is an upgraded version of the point map. Points can vary in all shapes, including such three-dimensional rectangles.

Use scenarios: all scenarios of the point map. It focuses more on the geographical distribution of specific objects, such as real estate construction projects.

10. Custom Map

A custom map is a map visualization of your own design. It can meet any use scenario, but it requires some data analysis and visual design basis. So I won’t go on about it, just show you two custom maps I made.

At Last

Reading here, you may ask what tools you should use to make map visualizations. I don’t think it’s necessary to emphasize the choice of tools. Excel, D3, and even PS can do what you want. You should think more about the main purpose of your use of these tools.

If you just want to show the processed data, you can choose Excel. Or maybe you have all kinds of data, but you don’t understand data modeling, programming, or data cleaning, or even SQL optimization, then you need an easy-to-use data visualization tool like FineReport and Tableau. The maps I made in this article may seem a bit difficult to draw, but I actually used the built-in map templates of FineReport. With a simple drag and drop operation, data can be easily visualized.

In short, all the tools mentioned above have the function of map visualization, but there are differences. You should choose the visualization tool that suits you according to your needs.