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I think I'm having a idiot moment,

I have a list and I need to add 170 to each number

    list1[1,2,3,4,5,6,7,8......]

    list2[171,172,173......]
i love crysis
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    Note that if you'll be doing lots of numeric operations like these in Cpython, you'd be better off using `numpy`... Then it would be something like `array = np.array([1,2,3,4])`. Now you can add `170` elementwise by `array + 170`. – mgilson Jun 09 '13 at 02:44

2 Answers2

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Specific answer

With list comprehensions:

In [2]: list1 = [1,2,3,4,5,6]

In [3]: [x+170 for x in list1]
Out[3]: [171, 172, 173, 174, 175, 176]

With map:

In [5]: map(lambda x: x+170, list1)
Out[5]: [171, 172, 173, 174, 175, 176]

Turns out that the list comprehension is twice as fast:

$ python -m timeit 'list1=[1,2,3,4,5,6]' '[x+170 for x in list1]'
1000000 loops, best of 3: 0.793 usec per loop
$ python -m timeit 'list1=[1,2,3,4,5,6]' 'map(lambda x: x+170, list1)'
1000000 loops, best of 3: 1.74 usec per loop

Some bench-marking

After @mgilson posted the comment about numpy, I wondered how it stacked up. I found that for lists shorter than 50 or so elements, list comprehensions are faster, but numpy is faster beyond that.

benchmarks

Matthew Adams
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incremented_list = [x+170 for x in original_list]
Amber
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