On: Fantastic DSLs and where to find them

[Chris2048]

I believe the dot product for an array is a.dot(b) ?

Would a.mult(b) be terrible for the first example?

I assume the third example is R-style:

  df[df['foo'] < 10 ] ?

I don't believe I can ovveride 'is', or 'instanceof', plus df has to pre-exist:

  foo = make_df()[foo['col'] > 10]

why does it have to be R-style? is that necessarily more powerful than something more pythonic?

  df.filt(lambda x: x > 10, ['foo'])

or even

  df.filt(lambda x, y: (x > 10) and (y > 10), ['foo', 'bar'])

  new_tbl = make_df().filt(lambda x, y: (x > 10) and (y > 10), ['foo', 'bar'])

vs

  df[(df['foo'] < 10) & (df['bar'] < 10)]

also, I believe James Powell does a talk wrt the inconsistencies of pandas/numpy interface.