Determine the type of data you have: The type of data you have will often determine the best chart to use. For example, if you have categorical data, you might consider using a bar chart, or if you have continuous data, a line chart might work better.
Identify the relationship between variables: The relationship between the variables in your data can also guide your choice of chart. If you want to show the relationship between two variables, a scatter plot might be the best choice, while if you want to compare the values of different categories, a bar chart might be more suitable.
Consider the purpose of the chart: The purpose of the chart can also guide your choice. If you want to show the composition of a whole, a pie chart might be useful, while if you want to show the distribution of data, a histogram might be more appropriate.
Evaluate the data size and complexity: The size and complexity of your data can also influence your choice of chart. For example, if you have a large dataset, a heat map might be more useful than a scatter plot, while if you have multiple variables, a stacked bar chart might be more appropriate.
Be aware of chart limitations: Finally, it's important to be aware of the limitations of different chart types. For example, a pie chart can be difficult to read for small data sets, and a line chart might not be appropriate for data that doesn't have a clear trend over time.
Composition Visualizations highlight how parts are related to the whole, while comparison visualizations highlight differences between values
You will notice that some visualization types appear in different categories because their utility can be expanded.
Comparison
Distribution
Composition
Procedural
Motion
Patterns
