A list comprehension would also work:

>>> lst = [2,3,-3,-2]
>>> [abs(x) for x in lst]
[2, 3, 3, 2]
>>>

Try :

import numpy as np

array= ...

np.abs(np.array(array))

numpy is very powerful and fast, learn to use it asap.

EDIT since the problem is how to do a function on each element of a list and wrap those results in a list of the same length :

Two solutions come to mind :

• hardcore python style :

[x if x<0 else -x for x in array]

the brackets say I want a list, inside I write the function and I say where to find the parameters to my function.

[abs(x) for x in array]
[f(x) for x in array] # for any defined f that can handle every element of array

• map(lambda x : f(x), array)

you create a mapping on the elements of array. To those elements, you apply lambda. lambda is a way to define a function locally, very locally.

list(map(lambda x : abs(x),array))

finally you make a list from the mapping, to retrieve the result. If you don't, it will stay as an abstract, the definition of a relation between array and something that is yet to be instantiated.

a = ['2.40', '1970-1990', 'Austria'] #your old list (with the extra [] removed, they seem not to have a point... If you need them you can easily edit the code appropriately)
b = [] #a new list with the absolute values
for i in range(0, len(a)): #going through each of the values in a
     try:
          b += [abs(float(a[i]))] #trying to take the absolute value and put it in the new list (I have the float() because it appears that your 2.40 is a string. If you have it as an actual integer or float (such as 2.40 instead of '2.40') you can just use abs(a[i])
     except:
          b += [a[i]] #if taking the absolute value doesn't work it returns the value on its own.
print(b)