Example of DataFrame:

>>> column_data = {'State': ['California', 'New Jersey', 'New York'],
... 'Capital': ['Sacramento', 'Trenton', 'Albany'],
... 'Timezone': ['PST', 'EST', 'EST']}

>>> frame = DataFrame(column_data, index = ['NY', 'CA', 'NJ'],
columns = ['State', 'Capital', 'Timezone'])

>>> frame
State Capital Timezone
NY California Sacramento PST
CA New Jersey Trenton EST
NJ New York Albany EST

[3 rows x 3 columns]

Here the column data is first stored in a Python dictionary, and then passed to the constructor for the DataFrame. Because dictionaries are unordered, we needed to pass the "columns" argument to the constructor, to tell it what order to sequence the columns in.

There are many constructors for DataFrame. Here we used one that was based on the column vectors. There is another one, for example, which takes a list of dictionaries as its argument, with each dictionary one row
of the table, as a tuple. So, that constructor reflects the relational perspective on data frames.