D language manipulation of dataframe type structures

[Jay Norwood]

While the interactive exploratory aspects of the pandas are 
attractive,  in my case the interaction has just been a crutch to 
discover how to correctly use their api.

Once through that api learning curve, I'd mainly be interested in 
repeating the operations that worked correctly.  The execution 
speed would be more important to me at that point.

In the recent pandas documents, they describe some speed 
improvements available from using eval(expression_string) calls 
that get executed by a numexpr app.  Their testing shows it only 
improves execution time when table sizes go beyond about 10k 
rows.  Seems like this puts the improvements beyond the reach of 
my particular app.

ok, thanks.  I'll have to dig into it some more.