Benjamin Goudey <[EMAIL PROTECTED]> writes:
> For example, if my original list is [0,0,1,2,1,0,0] I would like to
> produce the lists [1,2,1] (the non zero values) and [2,3,4] (indices
> of where the non-zero values used to be). Removing non-zero values
> is very easy but determining the indicies is where I'm having
> difficulty.
The built-in 'enumerate' function is made for this. Creating the new
list can be done efficiently and clearly with a list comprehension.
Further, presumably you want to do further operations on these new
series of data; wouldn't it be better to have the values and original
indices actually correlated together?
This code produces a two-element tuple for each original non-zero
value:
>>> sparse_data = [0, 0, 1, 2, 1, 0, 0]
>>> nonzero_data = [(index, value)
... for (index, value) in enumerate(sparse_data)
... if value != 0]
>>> nonzero_data
[(2, 1), (3, 2), (4, 1)]
>>> for (index, value) in nonzero_data:
... print "Value %(value)r was originally at index %(index)r" % vars()
...
Value 1 was originally at index 2
Value 2 was originally at index 3
Value 1 was originally at index 4
--
\ “Experience is that marvelous thing that enables you to |
`\ recognize a mistake when you make it again.” —Franklin P. Jones |
_o__) |
Ben Finney
--
http://mail.python.org/mailman/listinfo/python-list
