Exploring Comparisons across Dimensional Items

Before diving into chart making, it is important to differentiate between dimensions and measures.

Every column that is present in some data has a data type associated with it, such as string, integer, or date. Also, every column that exists in some data is either a dimension or a measure. Dimensions are qualitative or categorical data, such as names, regions, dates, or geographical data, and the columns have categories of distinct values. Measures, on the other hand, are quantitative values that can be aggregated.

Consider the following: a Country column has country names such as Canada, India, and Spain. Can you sum the regions? Would a sum of Canada, India, and Spain make any sense? No, it wouldn't, so a region is a dimension. Similarly, data to which you can apply mathematical functions, such as sum, average, min/max, and so on, are measures. Hence, the rule of thumb is as follows: columns to which you can apply a...