A stacked graph is a type of data visualization that displays the contribution of different components to a whole over time or across categories. It builds on the basic area or bar chart by layering data series on top of each other, allowing viewers to compare both overall trends and the relative size of each part.
Types of Stacked Graphs #
Stacked graphs are generally of two types:
- Stacked Bar Graphs: They use horizontal or vertical bars segmented into different colors or patterns to show categories within each bar.
- Stacked Area Graphs: They use layered areas to show how quantities change over time, with each area representing a part of the total.
When to Use a Stacked Graph? #
Stacked graphs are especially useful when the focus is on showing how individual parts contribute to a total and how that total evolves. For example, in project evaluation, one might use a stacked graph to display budget allocations across departments over multiple years or to compare the reach of different program components over time.
What are the Advantages of Stacked Graphs? #
Stacked graphs:
- clearly show part-to-whole relationships.
- are useful for comparing cumulative values.
- are effective for displaying trends across categories.
What are the Limitations of Stacked Graphs? #
- It can be difficult to read when too many categories are included.
- Comparing individual segment sizes becomes harder the further up the stack they are.
- They may obscure small changes or variations within categories.
A stacked graph is an effective tool for presenting complex, layered data in a visual format that highlights both totals and the contribution of individual components, making it ideal for monitoring and evaluation work.
List of recommended resources #
For a broad overview #
A Complete Guide to Stacked Bar Charts
This blog post by Mike Yi for Atlassian gives an overview of stacked bar charts, when to use them, as well as best practices for using a stacked bar chart. The post also delineates common misuse of using stacked bar charts and also briefs on the common stacked bar chart options available.
How to Create a Stacked Bar Chart in Excel: Step-by-Step Guide
This video tutorial on YouTube by Spreadsheet Point gives an introduction to stacked bar charts, explains how to set up the data, create and customize the stacked bar chart as well as provides further resources for study.
For in-depth understanding #
This post on inforiver gives an in-depth understanding of the different types of stacked charts available for use. Each stacked chart-stacked area chart, stacked column chart, stacked bar chart, diverging bar chart, waterfall chart- is explained along with their use as well as a practical example for better understanding.
This article by Alex Velez for storytelling with data gives an in-depth explanation of stacked bar charts, when to use them and when not to use them, the different variations of stacked bars, as well as the best practices for designing stacked bars along with visual graphs for better understanding.
Case study #
Hierarchically stacked graph convolution for emotion recognition in conversation
This research paper proposes a novel Hierarchically Stacked Graph Convolution Framework (HSGCF), which leverages hierarchical structure to extract emotional discriminative features. The proposed HSGCF uses five graph convolution layers connected hierarchically to establish a more discriminative emotional feature extractor. In simpler terms, a graph structure has been applied to explicitly capture the self and inter-dependencies of speakers in the conversation.
Optimal layout of stacked graph for visualizing multidimensional financial time series data
This paper by Yutian He and Hongjun Li construct the minimum cumulative variance rule to determine the stacking order of each dimension, as well as adopt the width priority principle and the color complementary principle to determine the label placement positioning and text coloring in order to present visually appealing and easy-to-read stacked graphs.
References #
