Introduction
As mentioned in the previous article, the area chart (Area Chart) is based on the line chart and fills the area below the line with color, mainly for displaying values on continuous intervals or time spans. Today we are going to talk about the Stacked Area Chart , which is a special area chart that can be used to compare multiple variables in an interval.
The difference between a stacked area chart and an area chart
The difference between a stacked area chart and an area chart is that the starting point of each data series in a stacked area chart is drawn based on the previous data series, that is, each row of measurement must fill the area between the rows.
Stacked area charts and area charts are both used to represent trends in data over time, categories, etc., but they have some differences and have their advantages in different data analysis scenarios:
(1) Data display methods are different: an area chart usually draws a separate set of data in a coordinate system, which can display the proportion of each data point, while a stacked area chart superimposes and displays multiple data sets in order, which can Show the proportional relationship between each data set.
(2) Data interpretation methods are different: area charts are more suitable for emphasizing trends and changes in a single dataset, while stacked area charts are more suitable for comparing trends and changes between different datasets.
(3) Readability and ease of use are different: stacked area charts are more readable when the data set is small, but as the number of data sets increases, the chart will become crowded and difficult to read and understand; area charts usually Easier to read and understand, even with large datasets.
Common Application Scenarios
The stacked area chart is suitable for displaying the accumulation or proportion of multiple categories or multiple variables. It can clearly show the proportion of each category or variable in the total, and can compare between different categories or variables. . Common application scenarios include:
(1) It is necessary to compare the proportion and change trend of multiple variables in the population;
(2) need to highlight the relative size and change between different variables;
(3) It is necessary to show the sum of multiple variables and the contribution of each variable.
To give a few examples, such as:
(1) Show the proportion of multiple products or services in the market, and their changing trends over time.
(2) Display the proportion of multiple sales channels in terms of sales or sales volume, and their changing trends in different time periods.
(3) Display the proportion of multiple cost items in the total cost and their changing trends in different time periods.
(4) Show the proportion of multiple groups of people in the total population and their changing trends over time, such as the proportion of population in different age groups, the proportion of different occupational groups, etc.
Through the stacked area chart, you can intuitively see the proportion and change trend of each category or variable in the total, which is conducive to analysis and decision-making.
Advantages Disadvantages
A stacked area chart is a common type of data visualization chart used to compare the proportion of multiple variables in a population and the relationship between variables. Compared with the simple area chart, the stacked area chart stacks different variables together in a certain order, making the area occupied by different variables clearer, and the size relationship and trend between variables can be compared more intuitively.
Advantages of stacked area charts include:
(1) It can visually display the proportion and trend among multiple variables;
(2) can highlight the relative size and change between different variables;
(3) The sum of multiple variables and the contribution of each variable can be displayed at the same time.
Disadvantages of stacked area charts include:
(1) When the number of stacked variables is large, it may cause the chart to be too complicated and difficult to read and understand;
(2) When there is mutual influence and overlap between stacked variables, it may lead to ambiguity and misinterpretation of the graph.
To learn more about visual components, refer to the tutorial on the official website of Shanhaijing Visualization ~
