Adding values to a new array

Question

I have an existing python array instantiated with zeros. How do I iterate through and change the values?

I can't iterate through and change elements of a Python array?

num_list = [1,2,3,3,4,5,]
mu = np.mean(num_list)
sigma = np.std(num_list)
std_array = np.zeros(len(num_list))

for i in std_array:
        temp_num = ((i-mu)/sigma)
        std_array[i]=temp_num

This the error: only integers, slices (:), ellipsis (...), numpy.newaxis (None) and integer or boolean arrays are valid indices

Can you print this statement? I would like to see what it returns. np.zeros(len(num_list)) — Patriots299
– Patriots299, Commented Feb 19, 2019 at 0:35

jyalim · Accepted Answer · 2019-02-19 18:08:35Z

4

In your code you are iterating over the elements of the numpy.array std_array, but then using these elements as indices to dereference std_array. An easy solution would be the following.

num_arr = np.array(num_list)
for i,element in enumerate(num_arr):
    temp_num = (element-mu)/sigma
    std_array[i]=temp_num

where I am assuming you wanted to use the value of the num_list in the first line of the loop when computing temp_num. Notice that I created a new numpy.array called num_arr though. This is because rather than looping, we can use alternative solution that takes advantage of broadcasting:

std_array = (num_arr-mu)/sigma

This is equivalent to the loop, but faster to execute and simpler.

edited Feb 19, 2019 at 18:08

answered Feb 19, 2019 at 0:39

jyalim

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Chris · Accepted Answer · 2019-02-19 00:41:12Z

0

You i is an element from std_array, which is float. Numpy is therefore complaining that you are trying slicing with float where:

only integers, slices (:), ellipsis (...), numpy.newaxis (None) and integer or boolean arrays are valid indices

If you don't have to use for, then numpy can broadcast the calculations for you:

(std_array - mu)/sigma
# array([-2.32379001, -2.32379001, -2.32379001, -2.32379001, -2.32379001,
   -2.32379001])

answered Feb 19, 2019 at 0:41

Chris

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