Help with data
Data can be categorized into multiple ways, and Protoviewer makes educated guesses as to what your data columns may contain.
NumberNumber 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.
CategoriesCategorical data, or nominal measures, are data that can be divided into groups. For example, gender, educational level, hair color are categorical.
DateDate 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.