If you measure n variables (each of a different type) of a single object of observation, then you get a table with n columns for each object row. If there are m observations, then we have m rows of data. For example, given the student grades as data, you might want to know "compute the average grade for each socioeconomic group", where grade and socioeconomic group are both columns in the table, and there is one row per student.

The DataFrame is the most natural representation to work with such a (m x n) table of data. They are similar to pandas DataFrames in Python or data.frame in R. A DataFrame is a more specialized tool than a normal array for working with tabular and statistical data, and it is defined in the DataFrames package, a popular Julia library for statistical work. Install it in your environment by typing in Pkg.add("DataFrames") in the REPL. Then, import it into your current workspace with using DataFrames. Do the same for the packages DataArrays and RDatasets...