Column charts are a data visualization tool used to represent and display data in a graphical format. They are particularly effective for showing comparisons and trends in categorical data. In a column chart, data is presented using vertical columns, each column representing a specific category or data point. The height or length of each column is proportional to the value it represents, thus making it efficient and easy to compare different data points visually.
Some common types of column charts include:
- Clustered column chart – This chart displays multiple data series as clustered columns, allowing viewers to compare values within each category. It’s ideal for showcasing changes over time or comparing data categories.
- Stacked column chart – Stacked columns represent data as segments within a single column, illustrating the contribution of each segment to the whole. This helps visualize part-to-whole relationships and trends.
- 100% stacked column chart – Similar to the stacked column chart, this type represents data as percentages of the whole, enabling a clear comparison of relative proportions.
Column charts are commonly used to compare data categories, show changes over time and illustrate part-to-whole relationships.
Column charts are popular because they provide a visual way to communicate data patterns and insights, making it easier for viewers to grasp the information’s significance.
List of recommended resources #
For a broad overview #
Bar chart and column chart reference
This article by Google’s Looker Studio gives a guide on how to use and configure column and bar charts in Looker Studio.
This Google Cloud Guide gives a broad overview of the graphical tool of column charts and how to customize them.
Present your data in a column chart
This guide by Microsoft explains the step-by-step process of using column charts in Excel.
For in depth understanding #
Data Visualization: A Practical Introduction
This accessible primer by Kieran Healy explains how to create effective graphics from data. It explains what makes some graphs succeed while others fail and how to think about data visualization in an honest and effective way.
Storytelling with Data: A Data Visualization Guide for Business Professionals
This book by Cole Nussbaumer Knaflic teaches readers the fundamentals of data visualization and how to communicate effectively with data. Knaflic’s text is grounded in theory, but made accessible through various real-world examples demonstrating how data can be visualized and used to tell an engaging and informative story.
Case study #
Structuring Complex Results using Network Maps and Hierarchical Charts
This case study, by Chloe A. Lanters and Peter Fantke, uses hierarchical column charts for structuring results for four category levels: exposure pathways, population group, exposure environment and age group.
References #
https://www.displayr.com/what-is-a-column-chart/
https://www.mit.edu/~mbarker/formula1/f1help/11-ch-c4.htm
