Module 1: An Introduction to Data Literacy and Data Visualization

Different Types of Data Visualizations

If you’ve decided that you want to represent your data visually, you’ll also need to think about which type of data visualization would best represent your data. Choosing the right kind of visualization depends on many factors:

  • What kind of data do you have?
  • Are there patterns in the data? Do they change over time?
  • What is the purpose of your data visualization?
  • Who is your intended audience?

Keep reading for an introduction to some basic types of data visualizations.

Bar Chart

A bar chart (also known as a bar graph or a column graph) is a good option for making comparisons between different groups of things and for identifying patterns. Typically, a bar chart uses either vertical or horizontal bars to show numerical comparisons across categories. One axis of the chart shows the categories being compared and the other axis displays the value scale of the numbers that are being compared. Bar charts with a large number of bars can become difficult to read as the labels for the categories will be more difficult to display clearly. (See Figure 1.3[1] below for an example.)

A bar chart showing populations (0-900) of 9 grizzly bear species in Canada (see source for details).
Figure 1.3. Populations of various Canadian grizzly bear species.

Key Takeaways

A bar graph is good for making comparisons and identifying patterns.

Pie Chart

A pie chart is a good option for displaying the composition of a whole or the proportional distribution of the data. A pie chart consists of a circle that is divided into proportional segments, with the full circle representing the total sum of the data. (See Figure 1.4[2] below for an example.)

A pie chart showing Canadian grizzly bear viability is far greater than threatened and extirpated (see source for details).
Figure 1.4. Viability of Canadian grizzly bear species in 2015.

Key Takeaways

A pie chart is: good for making comparisons, indicating proportional representation and showing part-to-a-whole

Line Graph

A line graph is used to display quantitative values over a time period or other continuous interval, and is usually used to display trends and portray change over time. A line graph can also be used for comparison when grouped with other lines; this can, however, become cluttered and difficult to read if you are using more than 3-4 lines per graph. (See Figure 1.5[3] below for an example.)

A line graph of an overall increasing trend, though the value of fresh is much lower than processed or total mushrooms.
Figure 1.5. Value of processed and fresh mushrooms, plus the total value of those mushrooms  together in Canadian Dollars (CAD), 2016-2020.

Key Takeaways

A line graph is good for identifying patterns, showing data over time and making comparisons (when the lines are grouped in a single graph).

Scatterplot

A scatter plot (also known as a scatter graph, scatter chart, point graph or X-Y plot) uses a collection of points to display values from two variables. By displaying the values in each axis, you can detect if a correlation or relationship exists between the two variables. (See Figure 1.6[4] below for an example.)

A scatter plot showing an increasing trend 2016-2019 and a decreasing trend 2019-2020 of fresh mushroom sales.
Figure 1.6. Fresh mushrooms sold in Canada by year, 2016-2020.

Key Takeaways

A scatterplot is good for identifying patterns and relationships.

Maps

A map can display data in many different ways. Maps can display divided geographical areas that are coloured, shaded or patterned in relation to a data variable. Maps can also be used to detect spatial patterns or the distribution of data over a geographical region using a gradient colour scheme. (See Figure 1.7[5] below for an example, where each province is a different colour representing its raspberry production.)

A map graph showing that provinces produce different amounts of raspberries, with higher amounts produced in darker areas.
Figure 1.7. The amount of raspberries produced in Canada by province in 2020.

Key Takeaways

A map is good for mapping distribution, identifying patterns, and making comparisons.

Infographic

An infographic consists of several data visualizations, and combines information and graphics (as the name suggests) to tell a clear data story. (See Figure 1.8[6] below for an example.)

An infographic using various visual elements to present the data (boxes, graphics, charts, headings and fonts).
Figure 1.8. Overview of the Canadian fruit industry in 2020 by labour statistics, types of fruit produced and their comparative value.

Key Takeaways

An infographic is good for telling a comprehensive data story.

Dashboard

A dashboard is when several data visualizations are put together. Dashboards can use tables, charts and graphics to display information, often to inform business decisions. Dashboards are usually updated regularly and show changes over time. (See Figure 1.9[7] below for an example, which includes a pie chart and a bar chart presented under a header that describes their relation to each other.)

A dashboard showing a pie chart of production by province and a bar chart of beds in Ontario and British Columbia.
Figure 1.9. The dashboard displays Canadian mushroom production and sales for 2020 using a pie chart and a bar chart.

Key Takeaways

A dashboard is very versatile and is often used in a variety of ways to inform decision making.

Exercises

Take a moment to test your understanding of the different types of data visualization. In the activity below, you’ll find a series of scenarios. Match the type of data visualization to the most appropriate use.

Deeper Dive

Want to learn more about different types of data visualizations? Check out the Data Visualization Catalogue.

 

  1. Government of British Columbia. Grizzly Bear Population Units. Retrieved January 8th, 2022. URL: https://open.canada.ca/data/en/dataset/caa22f7a-87df-4f31-89e0-d5295ec5c725 Government of British Columbia, Contains information licensed under the Open Government Licence – British Columbia. https://www2.gov.bc.ca/gov/content/data/open-data/open-government-licence-bc ↵
  2. Government of British Columbia. Grizzly Bear Population Units. Retrieved January 8th, 2022. URL: https://open.canada.ca/data/en/dataset/caa22f7a-87df-4f31-89e0-d5295ec5c725 Government of British Columbia, Contains information licensed under the Open Government Licence – British Columbia. https://www2.gov.bc.ca/gov/content/data/open-data/open-government-licence-bc ↵
  3. Statistics Canada. Table 32-10-0356-01 Area, production and sales of mushrooms. Data is reproduced and distributed on an "as is" basis with the permission of Statistics Canada. Retrieved January 9th, 2022. DOI: https://doi.org/10.25318/3210035601-eng. Statistics Canada Open Licence: https://www.statcan.gc.ca/en/reference/licence ↵
  4. Statistics Canada. Table 32-10-0356-01 Area, production and sales of mushrooms. Data is reproduced and distributed on an "as is" basis with the permission of Statistics Canada. Retrieved January 9th, 2022. DOI: https://doi.org/10.25318/3210035601-eng. Statistics Canada Open Licence: https://www.statcan.gc.ca/en/reference/licence ↵
  5. Statistics Canada. Table 32-10-0364-01 Area, production and farm gate value of marketed fruits. Data is reproduced and distributed on an "as is" basis with the permission of Statistics Canada. Retrieved January 9th, 2022. DOI: https://doi.org/10.25318/3210036401-eng. Statistics Canada Open Licence: https://www.statcan.gc.ca/en/reference/licence ↵
  6. Statistics Canada. Table 32-10-0364-01 Area, production and farm gate value of marketed fruits. Data is reproduced and distributed on an "as is" basis with the permission of Statistics Canada. Retrieved January 9th, 2022. DOI: https://doi.org/10.25318/3210036401-eng. Statistics Canada Open Licence: https://www.statcan.gc.ca/en/reference/licence ↵
  7. Statistics Canada. Table 32-10-0356-01 Area, production and sales of mushrooms. Data is reproduced and distributed on an "as is" basis with the permission of Statistics Canada. Retrieved January 9th, 2022. DOI: https://doi.org/10.25318/3210035601-eng. Statistics Canada Open Licence: https://www.statcan.gc.ca/en/reference/licence ↵

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Critical Data Literacy Copyright © 2022 by Nora Mulvaney and Audrey Wubbenhorst and Amtoj Kaur is licensed under a Creative Commons Attribution 4.0 International License, except where otherwise noted.

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