Mean of Tuple List - Python

We are give list of tuples we need to find the mean of each tuples. For example, a = [(1, 2, 3), (4, 5, 6), (7, 8, 9)] we need to find mean of each tuples so that output should be (4.0, 5.0, 6.0).

Using sum() and len()

We can find the mean of a tuple list by summing corresponding elements using sum() and dividing by the number of tuples using len(). This is done element-wise to compute the mean for each position in the tuples.

a = [(1, 2, 3), (4, 5, 6), (7, 8, 9)]

# Compute mean of each tuple position
m = tuple(sum(col) / len(col) for col in zip(*a))
print(m)

(4.0, 5.0, 6.0)

Explanation:

• zip(*a) groups corresponding elements from all tuples, and sum(col) / len(col) calculates the mean for each position.
• Result is stored as a tuple ensuring the mean values maintain the same structure as the original tuples.

Using numpy

We can use NumPy to compute the mean of a tuple list efficiently by converting it into an array and applying numpy.mean() along desired axis. This returns a tuple with mean of each position in original tuples.

import numpy as np

# Compute mean using numpy
a = [(1, 2, 3), (4, 5, 6), (7, 8, 9)]
m = tuple(map(float, np.mean(a, axis=0))) 
print(m)

(4.0, 5.0, 6.0)

Explanation:

• np.mean(a, axis=0) computes the mean of each corresponding element in tuples by treating a as a NumPy array and averaging along columns.
• tuple(map(float, ...)) converts NumPy array of means into a tuple of floats for consistent output formatting.

Using statistics.mean()

statistics.mean() function can be used to compute mean of each position in a tuple list by applying it to corresponding elements grouped using zip(). This ensures an element-wise mean calculation returning a tuple of mean values.

from statistics import mean

# Compute mean using statistics.mean()
a = [(1, 2, 3), (4, 5, 6), (7, 8, 9)]
m = tuple(map(mean, zip(*a)))
print(m) 

(4, 5, 6)

Explanation:

• zip(*a) groups corresponding elements from all tuples creating separate iterables for each position.
• map(mean, zip(*a)) applies statistics.mean() to each group computing mean for each position and returning a tuple of mean values.