function does't return a list as indented, but returns only one listelement instead

For the sake of practice, I am trying to calculate the following mathematical expression:

The x-value in the parameter is supposed to be a number – an int or float
The y-value in the parameter is supposed to be a list of numbers.

The function is supposed to return a list of values in the same length as the list y in the parameter.

For some embarrassing reason, I only manage to make the function return only one list element, that comes from the first of the two equations in the function.

The code in question is:

def f(x ,y):

    list = []

    for i in y:
        if y[i] <= 0:
            list.append(4 * (x ** 3) * y[i] - 2 * x * y[i])
        if y[i] > 0:
            list.append(4 * (x ** 3) * y[i] + 2 * x * y[i])

        return list

x_value = 2
y_values = [1,-2, 3, -7]

print(f(x_value, y_values))

#wanted output: [28, -56, 85, -252]

#actual output: [-56]

My question is:

• How do you make this function return a list with all the calculations? Like for example
  [28, -56, 85, -252] instead of the current output which is [-56]

This is probably an easy fix, but for some reason I am stuck.

Is there anybody kind enough to help me sort this out?

>Solution :

First, when you have for i in y, i is the actual value in y, not the index, so you don’t use y[i], you use i directly. Second, you should return the final list after the for i in y loop is over, so it needs to be outside the loop. And finally, don’t use built-in names (such as list) as your own variable/function/class names, because it will overwrite the built-in names.

def f(x ,y):
    L = []

    for i in y:
        if i <= 0:
            L.append(4 * (x ** 3) * i - 2 * x * i)
        if i > 0:
            L.append(4 * (x ** 3) * i + 2 * x * i)

    return L

To use i as an index, you need to change the loop to for i in range(len(y)), and use y[i] as you did previously.

Also, if you use numpy, you can solve this as:

>>> import numpy as np

>>> x_value = 2
>>> y_values = np.array([1,-2, 3, -7])

>>> 4 * x_value**3 * y_values + 2 * x_value * np.where(y_values <= 0, -y_values, y_values)
array([  36,  -56,  108, -196])