Click on the numbered tabs to navigate this lesson.
Data visualisation types
Data visualisations, such as graphs and maps, provide a way to understand your data visually, and give your data context.
For example, graphs can show comparisons and correlations in your data, while maps can show where data are most interesting or relevant. In many cases, visual presentations make it easier to understand a large volume of data quickly.
As before, you should begin a data visualisation with a question: what do you want to learn from your data, and which variables are most relevant?
Your starting question guides your choice of which type of visualization and which data variables to use.
Data visualisations can also be used to tell stories, but in this lesson we will examine them as an analytical tool.
Types of visualisation
Line charts are helpful for understanding trends and relationships in continuous variables, such as age, temperature, spending, economic growth, emissions, or time.
Scatterplots are helpful for understanding correlations between continuous variables, as well as identifying outliers. Scatterplots serve much the same purpose as the CORREL function described in the previous topic.
Maps are good for understanding spatial relationships in data. Choropleth maps use color and shading to present data aggregated to a regional level. Dot maps use coordinates to display exact locations.
Creating a data visualisation
You can create basic visualisations easily in Google Sheets.
Start by identifying the data you want to visualise. Sometimes this will be a pivot table, or summary data from an analysis of the original data. In most cases, the first row should contain variable names and the first column should contain record or category names.
Next, drag to select the data you want to visualise, including the variable and category names.
Select Chart from the Insert menu to display a default chart for the selected data. You may now select different chart types and options using the Chart Editor. Experiment with different types, keeping in mind that your data may be more appropriate for some chart types and less appropriate for others.
We’ll cover more tools and visualisation techniques in Telling stories with data.
Test your knowledge
An introduction to data visualisation
0 of 1 questions completed
You have already completed the quiz before. Hence you can not start it again.
Quiz is loading...
You must sign in or sign up to start the quiz.
You must first complete the following:
0 of 1 questions answered correctly
Time has elapsed
You have reached 0 of 0 point(s), (0)
Earned Point(s): 0 of 0, (0)
0 Essay(s) Pending (Possible Point(s): 0)
Question 1 of 1
Which type of chart is most appropriate for showing changes in data over time?CorrectIncorrect