Composition charts, such as pie charts, waterfall charts, and stacked bar charts, are data visualization tools used to represent different aspects of data. They are handy for displaying how various components or categories contribute to a whole or how data values change over time.
Some commonly used composition charts are:
- Pie chart – Pie charts are circular charts divided into slices, each representing a proportion or percentage of a whole. The size of each slice corresponds to the value it represents, and the entire pie chart represents 100%.
- Waterfall chart – A waterfall chart displays the cumulative effect of sequentially introduced positive or negative values. It is often employed in financial analysis to illustrate the components contributing to a final value, such as the breakdown of a company’s revenue or expenses.
- Stacked bar chart – These are a variation of the standard bar chart in which bars are divided into segments to show the contribution of different components to a whole. Each segment represents a category or a subcategory, and the height of the entire bar represents the total value.
- Stacked area chart: They are similar to stacked bar charts but use areas instead of bars to represent the data. It shows the changing composition of a dataset over time.
- Treemap: A treemap is a hierarchical chart that displays data in a nested structure of rectangles, with each rectangle representing a category or subcategory. The size and color of each rectangle can be used to convey information about the category’s contribution or value.
List of recommended resources #
For a broad overview #
A Complete Guide to Stacked Bar Charts
This Chartio data tutorial gives a broad overview of stacked bar charts, a type of composition charts used in data visualization.
How to choose the best chart or graph for your data
This data analytics blog on Google Cloud by Jill Hardy gives a broad overview of the different types of charts and graphs to show comparison, distribution, composition and relationship between data values. Hardy mentions donut and pie charts as the best choices to show composition especially when simple proportions are to be presented.
Tree Maps: A Tool for Structuring, Exploring and Summarising Qualitative Information
These notes prepared by RIck Davies give a brief overview of tree maps, its uses and the process of creating them.
For in depth understanding #
Better Data Visualizations: A Guide for Scholars, Researchers, and Wonks
This book by Jonathan Schwabish details essential strategies to create more effective data visualizations. Schwabish examines more than eighty visualization types, from horizon charts to histograms, choropleth maps to ridgeline plots, and explains how each has its place in the visual toolkit.
Effective Data Visualization: The Right Chart for the Right Data
Written by Stephanie D. H. Evergreen, this comprehensive how-to guide shows readers how to create Excel charts and graphs that best communicate their data findings.
Case study #
This paper studying air quality on the east coast of Peninsular Malaysia makes use of stacked bar charts, a type of composition chart, to show the average mass composition of water-soluble ions in aerosol collected at the Bachok research station and the percentage of non-sea-salt and sea salt fractions of Ca 2+ , K + , Na + and SO 2− 4.
Humidity driven nanoscale chemical separation in complex organic matter
This paper makes use of pie charts to illustrate the chemical composition with their typical mass proportion in a) urban and b) high alpine air.
References #
27 Types of QlikView Visualization – How to Create Visualization
Data Visualization Resources: Types of Charts and Graphs for Data Viz
