Python itertools.pairwise() Function

The Pythonitertools.pairwise() function is used to create an iterator that returns consecutive overlapping pairs from an iterable. It is useful for analyzing sequential relationships between elements in a dataset.

This function is equivalent to using thezip function with a slice of the original iterable.

Syntax

Following is the syntax of the Python itertools.pairwise() function −

itertools.pairwise(iterable)

Parameters

This function accepts the input iterable as a parameter from which consecutive pairs will be extracted.

Return Value

This function returns an iterator that yields tuples containing consecutive elements from the input iterable.

Example 1

Following is an example of the Python itertools.pairwise() function. Here, we extract consecutive pairs from a list of numbers −

import itertoolsnumbers = [1, 2, 3, 4, 5]pairs = itertools.pairwise(numbers)for pair in pairs:   print(pair)

Following is the output of the above code −

(1, 2)(2, 3)(3, 4)(4, 5)

Example 2

Here, we use itertools.pairwise() function on a string to generate consecutive character pairs −

import itertoolstext = "HELLO"pairs = itertools.pairwise(text)for pair in pairs:   print(pair)

Output of the above code is as follows −

('H', 'E')('E', 'L')('L', 'L')('L', 'O')

Example 3

Now, we use itertools.pairwise() function to analyze temperature differences between consecutive days −

import itertoolstemperatures = [72, 75, 78, 74, 70, 69]differences = [(b - a) for a, b in itertools.pairwise(temperatures)]print(differences)

The result obtained is as shown below −

[3, 3, -4, -4, -1]

Example 4

We can also use the itertools.pairwise() function to check for increasing trends in stock prices −

import itertoolsstock_prices = [100, 102, 101, 105, 107, 106]increasing_trend = [b > a for a, b in itertools.pairwise(stock_prices)]print(increasing_trend)

The result produced is as follows −

[True, False, True, True, False]