How to take the log of all elements of a list

numpy will do that for you.

import numpy
numpy.log10(mat)

Note

mat does not have to be a numpy array for this to work, and numpy should be faster than using a list comprehension as other answers suggest.

import math
x = [1500, 1049.8, 34, 351]
y = [math.log10(num) for num in x]

This is called a list comprehension. What it is doing is creating a new list whose elements are the results of applying math.log10 to the corresponding element in the original list, which is not an array, btw.

The simpliest way is to use a list comprehension

Example:

>>> x = [1500, 1049.8, 34, 351]
>>> import math
>>> [math.log10(i) for i in x]
[3.1760912590556813, 3.021106568432122, 1.5314789170422551, 2.545307116465824]
>>> 

Another way is to use the map function

Example:

>>> map(math.log10, x)
[3.1760912590556813, 3.021106568432122, 1.5314789170422551, 2.545307116465824]
>>> 

You could also use the map builtin function:

import math
new_list = map(math.log10, old_list)

This will probably be insignificantly faster than the list comprehension. I add it here mainly to show the similarity between the two.

EDIT (in response to the comment by @HankGay)

To prove that map is slightly faster in this case, I’ve written a small benchmark:

import timeit

for i in range(10):
    t=timeit.timeit("map(math.log10,a)",setup="import math; a=range(1,100)")
    print "map",t
    t=timeit.timeit("[math.log10(x) for x in a]",setup="import math; a=range(1,100)")
    print "list-comp",t

Here are the results on my laptop (OS-X 10.5.8, CPython 2.6):

map 24.5870189667
list-comp 32.556563139
map 23.2616219521
list-comp 32.0040669441
map 23.9995992184
list-comp 33.2653431892
map 24.1171340942
list-comp 33.0399811268
map 24.3114480972
list-comp 33.5015368462
map 24.296754837
list-comp 33.5107491016
map 24.0294749737
list-comp 33.5332789421
map 23.7013399601
list-comp 33.1543111801
map 24.41685009
list-comp 32.9259850979
map 24.1111209393
list-comp 32.9298729897

It is important to realize that speed isn’t everything though. “readability matters”. If map creates something that is harder to read, definitely go for a list comprehension.