How to ensure a list is blanked-CodePudding

I am using colab. I have a list with these values:

cents=[[5.4, 3.9, 1.3, 0.4], [5.8, 2.6, 4.0, 1.2], [7.7, 2.8, 6.7, 2.0]]

I established this list in my second block of code.

Now, further into my code, I want to clear this list and change the values to the average of values from another list. Here is my code for this:

cents=[]
def avg_and_assign(list_1, list_2, list_3):
 alc1=np.array(list_1)
 alc2=np.array(list_2)
 alc3=np.array(list_3)
 alc1_mean=np.mean(alc1, axis=0)
 alc2_mean=np.mean(alc2, axis=0)
 alc3_mean=np.mean(alc3, axis=0)
 alc1_mean1=alc1_mean[0:4]
 alc2_mean1=alc2_mean[0:4]
 alc3_mean1=alc3_mean[0:4]
 cent1=np.ndarray.tolist(alc1_mean1)
 cent2=np.ndarray.tolist(alc2_mean1)
 cent3=np.ndarray.tolist(alc3_mean1)
 cents.append(cent1)
 cents.append(cent2)
 cents.append(cent3)
cents=[cent1,cent2,cent3]
cent_array=np.array(cents)

print(cents)

avg_and_assign(avg_list_cent1, avg_list_cent2, avg_list_cent3)

print(cents)

Here are my outputs:

[[5.4, 3.9, 1.3, 0.4], [5.8, 2.6, 4.0, 1.2], [7.7, 2.8, 6.7, 2.0]]
[[5.4, 3.9, 1.3, 0.4], [5.8, 2.6, 4.0, 1.2], [7.7, 2.8, 6.7, 2.0], [5.005999999999999, 3.4180000000000006, 1.464, 0.2439999999999999], [5.971830985915493, 2.7845070422535207, 4.50281690140845, 1.4901408450704228], [6.972413793103449, 3.0862068965517238, 5.893103448275861, 2.1310344827586207]]

Why isn't my cents list becoming empty when I assign it empty? Can this only work in the same code block?

My function can append the average to the list, but I wanted cents to become a blank list first.

Thanks.

CodePudding user response：

Don't Repeat Yourself ("DRY"). Use a loop to do your repetitive tasks. Then, return the final list instead of trying to use globals.

def avg_and_assign(*lists):
    cents = []
    for lst in lists:
        alc = np.array(lst)
        alc_mean = np.mean(alc, axis=0)[:4]
        cents.append( np.ndarray.tolist(alc_mean) )
    return cents

cents=[cent1,cent2,cent3]
print(cents)

cents = avg_and_assign(avg_list_cent1, avg_list_cent2, avg_list_cent3)
print(cents)

It's not clear to me why you keep converting to and from numpy arrays. In particular, why return a list of lists instead of a list of ndarrays?