Help with data

Data can be categorized into multiple ways, and Protoviewer makes educated guesses as to what your data columns may contain.


Number data, or quantitative measures, can be thought of as anything with which we can make sense of if we derive averages, medians, modes, etc. So for example, the temperature is a quantitative measure, as is age, income, number of miles driven, hours spent in front of the TV, etc. Zip codes, on the other hand, are not, because averages of zip codes don\'t really make sense.


Categorical data, or nominal measures, are data that can be divided into groups. For example, gender, educational level, hair color are categorical.


Date date contains dates. Dates are subsets of categorical data but has been extracted specifically for ease of use.

If you want to read more about the differences between data types, Stephen Few\'s article is a good read.