How to Decide What Chart Type to Use

Introduction

Choosing the right chart type is crucial for effectively communicating data insights. Here are some criteria to consider when deciding on a chart type:

• Data Type: Determine if your data is categorical, continuous, or hierarchical.
• Comparison or Trend: Decide if you want to compare different items or show a trend over time.
• Data Volume: Consider the amount of data you need to display.
• Clarity: Ensure the chart type you choose will make the data easy to understand.
• Audience Familiarity: Choose a chart type that your audience can easily interpret.
• Purpose: Identify whether you aim to highlight relationships, distributions, or compositions.
• Context: Consider the context in which the data will be presented, such as reports, presentations, or dashboards.

There are many many types of charts for visualizing data, so we’ll focus on some of the most common ones.

Column Charts

Column charts are ideal for comparing discrete, categorical data. Each vertical bar represents a category, making it easy to compare values across different categories.

When to use:

• Comparing quantities across different categories.some text
  • Example: Comparing sales figures across different regions.*

• Tracking changes in discrete intervals.some text
  • Example: Showing monthly revenue over a year.*

This column chart shows life expectancy for eight countries, but is also superimposed with a line chart (see below) showing infant mortality in the came countries.

Bar Charts

Bar charts are similar to column charts but with horizontal bars. They are particularly useful when category names are long or when you have many categories.

When to use:

• Comparing quantities across different categories with long labels.some text
  • Example: Comparing survey responses.*
    
• Displaying data when you have many categories.some text
  • Example: Displaying the number of employees in different departments.*

This bar chart shows US military deaths in major wars.

Line Charts

Line charts are perfect for showing trends over time. They use points connected by lines to represent continuous data.

When to use:

• Visualizing data trends over continuous time periods.some text
  • Example: Tracking stock prices over months.*
    
• Highlighting patterns and changes over time.some text
  • Example: Showing temperature changes throughout the year.*

This line chart shows a specific measure of wealth distribution called the “Gini Index” for both Canada and the United States. A higher Gini number indicates that fewer people hold more wealth.

Area Charts

Area charts are similar to line charts but with the area below the line filled in. They are useful for showing the magnitude of change over time and for emphasizing the total value across a trend.

When to use:

• Illustrating the magnitude of change over time.some text
  • Example: Displaying cumulative sales over time.*
    
• Highlighting part-to-whole relationships in trends.some text
  • Example: Showing changes in population growth.*

This area chart compares HIV/AIDS Deaths with the projected number of deaths that were prevented due to antiretroviral therapy.

Pie Charts

Pie charts are used to show proportions of a whole. Each slice of the pie represents a category's contribution to the total.

When to use:

• Displaying the composition of a whole.some text
  • Example: Showing market share distribution.
    
• Comparing proportions within a single data set.some text
  • Example: Displaying the proportion of budget allocations.

This pie chart shows how college students spend their time.

Scatter Charts

Scatter charts display values for two variables as points on a grid. They are useful for identifying relationships or correlations between variables.

When to use:

• Identifying relationships between two variables.some text
  • Example: Examining the relationship between advertising spend and sales.*
    
• Highlighting patterns, clusters, or outliers.some text
  • Example: Analyzing the correlation between height and weight.*

This scatter chart shows the relationship between countries’ gross domestic product (GDP) and life expectancy for several countries.

Bubble Charts

Bubble charts are an extension of scatter charts where a third variable is represented by the size of the bubble. They are useful for visualizing multidimensional data.

When to use:

• Comparing three variables simultaneously.some text
  • Example: Comparing sales performance across different regions with varying market sizes.*
    
• Highlighting relationships and distributions with an additional dimension.some text
  • Example: Analyzing project budgets with different costs and durations.*

This bubble chart shows the same relationship between life expectancy and gross domestic product (GDP) as the scatter chart above, but adds color to indicate the world region of each country, and the size of the bubble to indicate population.

Pyramid Charts

Pyramid charts are used to represent hierarchical data. They are often used to show proportions or distributions in a population.

When to use:

• Illustrating hierarchical structures.some text
  • Example: Displaying age distribution in a population.*
    
• Showing proportional relationships in hierarchical data.some text
  • Example: Showing organizational structure.*

This pyramid chart compares the number of men and women in various age ranges in Canada.

Conclusion

Choosing the right chart type depends on your data and the story you want to tell. By understanding the strengths of each chart type, you can select the one that best communicates your insights clearly and effectively.