What are the best data visualization techniques to show relationships between different data sets?

1 Scatter plots

Scatter plots are one of the simplest and most versatile data visualization techniques to show the relationship between two or more variables. They use dots or other symbols to represent the values of each data point on a Cartesian plane. Scatter plots are ideal for showing trends, outliers, clusters, and correlations in your data sets. You can also use different colors, shapes, or sizes to add more dimensions or categories to your scatter plots.

2 Line charts

Line charts are another classic data visualization technique to show the relationship between two variables over time. They use lines to connect the values of each data point on a horizontal and a vertical axis. Line charts are great for showing changes, patterns, and fluctuations in your data sets. You can also use multiple lines to compare different data sets or groups on the same scale.

3 Bar charts

Bar charts are a popular data visualization technique to show the relationship between a categorical variable and a numerical variable. They use bars of different lengths to represent the values of each category on a horizontal or a vertical axis. Bar charts are useful for showing comparisons, rankings, and proportions in your data sets. You can also use stacked or grouped bars to show subcategories or segments within your data sets.

4 Pie charts

Pie charts are a common data visualization technique to show the relationship between a categorical variable and a numerical variable as a percentage of a whole. They use slices of a circle to represent the values of each category. Pie charts are effective for showing relative sizes, shares, and distributions in your data sets. However, you should avoid using too many categories or slices, as they can make your pie charts hard to read and compare.

5 Heat maps

Heat maps are a modern data visualization technique to show the relationship between three variables using colors. They use a matrix or a grid to represent the values of two variables on a horizontal and a vertical axis, and use different shades or hues to represent the values of the third variable. Heat maps are powerful for showing patterns, contrasts, and intensities in your data sets. You can also use different color schemes or gradients to emphasize different aspects of your heat maps.

6 Network diagrams

Network diagrams are a complex data visualization technique to show the relationship between multiple entities or nodes using links or edges. They use shapes or icons to represent the entities, and use lines or curves to represent the connections or interactions between them. Network diagrams are impressive for showing structures, flows, and dependencies in your data sets. You can also use different colors, sizes, or styles to indicate different attributes or characteristics of your entities or links.

7 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?