calculate mean of new list of number with old mean

Question

I have a requirement to update the existing mean when new set of data is coming.
For example,
Say I have already calculated mean of a list of numbers and kept.

from statistics import mean
l1=[1,0,1,0,0,0,0,1,1,1,0,1]
m1=mean(l1)
print(m1)
0.5

Then say I get a new list of numbers

l2=[1,0,1,1,1,1,1,1,1,0,0,0,1,0,0,0,0,1,1,1,0,1]
m2=mean(l2)
print(m2)
0.5909090909090909

Now if I take the mean of m1 & m2 w.r.t the lists separately , they are different.

m3=mean([m1,m2])
print(m3)
0.5454545454545454
m3=mean(l1+l2)
print(m3)
0.5588235294117647

So, basically, how do I calculate new correct mean m3 only by using length of l1 , m1 & l2 ? (I do not have the contents of l1 any more. But, I can get the length)

Asked By: Johnson Francis

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Source

Answer 1

You can use the extend function to add the items in l2 to l1 and find the mean of the updated l1 which includes all items from l2.

l3 = l1.extend(l2)
m3 = mean(l3)

Answered By: hareko

Answer 2

You can do it easily if you know the length l1 and l2

from statistics import mean

l1 = [1,0,1,0,0,0,0,1,1,1,0,1]
m1 = mean(l1)
len1 = len(l1)

l2 = [1,0,1,1,1,1,1,1,1,0,0,0,1,0,0,0,0,1,1,1,0,1]
m2 = mean(l2)
len2 = len(l2)

m3 = (len1*m1 + len2*m2) / (len1+len2)
print(m3)

Output:

0.5588235294117647

Answered By: Marko Borković

calculate mean of new list of number with old mean

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