How can you quickly choose the right chart for your data?

1 Purpose of your chart

The first thing you need to consider when choosing a chart is the purpose of your analysis. What are you trying to achieve with your chart? What question are you answering or what message are you conveying? Depending on your goal, you can choose a chart that is appropriate for one of these four common purposes: comparison, relationship, distribution, or composition. For example, if you want to compare the sales of different products, you can use a bar chart or a pie chart. If you want to show the relationship between two variables, such as price and demand, you can use a scatter plot or a line chart. If you want to show the distribution of a variable, such as customer satisfaction, you can use a histogram or a box plot. If you want to show the composition of a variable, such as revenue sources, you can use a stacked bar chart or a treemap.

2 Data type of your chart

The second thing you need to consider when choosing a chart is the data type of your analysis. What kind of data are you working with? Is it numerical or categorical? Is it continuous or discrete? Is it univariate, bivariate, or multivariate? Depending on your data type, you can choose a chart that is suitable for displaying the characteristics and patterns of your data. For example, if you have numerical and continuous data, such as temperature or time, you can use a line chart or an area chart. If you have categorical and discrete data, such as gender or region, you can use a bar chart or a pie chart. If you have multivariate data, such as multiple dimensions or measures, you can use a bubble chart or a heatmap.

3 Audience of your chart

The third thing you need to consider when choosing a chart is the audience of your analysis. Who are you presenting your chart to? What is their level of expertise and interest in your topic? How much detail and explanation do they need? Depending on your audience, you can choose a chart that is appropriate for their background and expectations. For example, if you have a technical and knowledgeable audience, such as data scientists or engineers, you can use a complex and sophisticated chart, such as a radar chart or a parallel coordinates plot. If you have a non-technical and general audience, such as managers or customers, you can use a simple and clear chart, such as a bar chart or a pie chart.

4 Tips and tricks for choosing a chart

When selecting a chart, there are a few tips and tricks that can help you make the decision faster and easier. For example, you can use a chart chooser tool such as the Data Viz Project or Chart Chooser to filter and browse through different chart types based on your criteria. Additionally, if you are using a programming language or software like Python, R, Excel, or Tableau, you can take advantage of chart libraries that provide templates and examples of different chart types. Lastly, be sure to follow basic design principles like the Data-Ink Ratio or the CRAP Principles to eliminate clutter and enhance clarity in your charts. By following these tips and tricks, you can quickly and effectively choose the best chart for your data, purpose, and audience.

5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?