A tree is a less general structure than a network (which is
tree that allows any node to be connected to any other node).

However, it's probably more useful to have the data structure
reflect structure of the particular data rather than consider
abstract properties of data structures.

Tabular data is widely useful, particularly for experimentally-generated
data and data that benefits from ordering (like names and addresses
or prices of equities over time).

I find higher-dimensional data (more than 2-D) particularly intriguing
if somewhat hard to visualize directly; however, J is good at helping
us view this kind of data indirectly.

On 4/6/07, Terrence Brannon <[EMAIL PROTECTED]> wrote:

I was sitting here in front of an Excel spreadsheet, thinking, "you
know this is an array" ... not too long ago I was looking at a
database table and thinking the same thing.

HOWEVER. isn't a tree the most general data structure? You can make
lists out of trees and make arrays out of lists. Therefore the most
fundamental and broadly applicable data structure is a tree and not an
array.

Any feedback on why J is an array processing language and how it might
handle tree/hierarchical data is appreciated.

And how good is J with infinite data structures/streams?
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--
Devon McCormick, CFA
^me^ at acm.
org is my
preferred e-mail
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