How to loop over my data series and return a list instead of an individual value?

Question

I have been trying to create a function that loops over my data, standardizes the values, and finally, puts the new values into a list. Here is what I am trying:

def standardize( num_list):
    s = np.std(num_list)
    Xmean = np.mean(num_list)
    for i in num_list:
        Xstd = (i - Xmean)/s
        
        
    return Xstd

The function I have created only returns a single value. Next I tried this:

def standardize( num_list):
    s = np.std(num_list)
    Xmean = np.mean(num_list)
    for i in num_list:
        Xstd = (i - Xmean)/s
        list = print(Xstd)
    return

This is printing all the values I want, however, it is not placing them in a list. What am I missing to create a list?

Answer 1

Append them to a list:

def standardize(num_list):
    s = np.std(num_list)
    Xmean = np.mean(num_list)
    lst = []
    for i in num_list:
        Xstd = (i - Xmean)/s
        lst.append(Xstd)
        
    return lst

This could also be done with a list comprehension (although more complicated computations cannot be):

def standardize(num_list):
    s = np.std(num_list)
    Xmean = np.mean(num_list)
    return [(i - Xmean) / s for i in num_list]

Answer 2

In your example

def standardize( num_list):
    s = np.std(num_list)
    Xmean = np.mean(num_list)
    for i in num_list:
        Xstd = (i - Xmean)/s
        
        
    return Xstd

The loop assigns the variable each time and then when it goes to return it is giving you the last value it assigned.

Try define a list, adding to it, then returning the list like

def standardize( num_list):
    s = np.std(num_list)
    Xmean = np.mean(num_list)
    return_list = []
    for i in num_list:
        Xstd = (i - Xmean)/s
        return_list.append(Xstd)
        
    return return_list

Not tested