安德鲁·阿贝拉(Dr. Andrew Abela)
Comparison: This is when we want to compare the different categorical values or attributes within the data with each other. There are some variants, depending on the data. For example: Does the data include the time variable? How many time periods? How many variables and categories does the data present?
Composition: This is when we want to know how the data is composed, that is, what general characteristics are present in the data set. There are some variants, depending on the data. For example: Are there changes over time? How many time periods are there? In static data, do you have values that accumulate?
Distribution: This is when we want to understand how the individual data points are distributed within the entire data set. Depending on the number of variables in which we want to analyze the distribution, we can choose bar charts, line charts or scatter charts.
Relationship: In this case, we are interested in knowing how the values and attributes are related to each other. To relate the values, scatter charts are usually used when two variables are involved, and bubble charts are used when three variables are involved.