Python | Preceding element tuples in list

Sometimes, while working with Python list, we can have a problem in which we need to construct tuples, with the preceding element, whenever that element matches a particular condition. This can have potential application in day-day programming. Let’s discuss a way in which this task can be performed.

Method #1: Using for loop

Python3

# Python3 code to demonstrate working of
# Preceding Tuple elements in list

# initialize list
test_list = [1, 4, 'gfg', 7, 8, 'gfg', 9, 'gfg']

# printing original list
print("The original list is : " + str(test_list))

# initialize ele
ele = 'gfg'

# Preceding Tuple elements in list
res=[]
for i in range(0,len(test_list)):
    if(test_list[i]==ele):
        res.append((test_list[i-1],test_list[i]))
# printing result
print("Tuple list with desired Preceding elements " + str(res))

Output

The original list is : [1, 4, 'gfg', 7, 8, 'gfg', 9, 'gfg']
Tuple list with desired Preceding elements [(4, 'gfg'), (8, 'gfg'), (9, 'gfg')]

Time Complexity: O(n*n), where n is the length of the list test_list 
Auxiliary Space: O(n) additional space of size n is created where n is the number of elements in the res list 

Method 2: Using zip() + list comprehension
This task can be performed using a combination of above functionalities. In this, the zip() performs the task of construction of tuples and the catering of condition matching and iteration is handled by list comprehension.

Python3

# Python3 code to demonstrate working of
# Preceding Tuple elements in list
# using zip() + list comprehension

# initialize list
test_list = [1, 4, 'gfg', 7, 8, 'gfg', 9, 'gfg']

# printing original list
print("The original list is : " + str(test_list))

# initialize ele
ele = 'gfg'

# Preceding Tuple elements in list
# using zip() + list comprehension
res = [(x, y) for x, y in zip(test_list, test_list[1 : ]) if y == ele]

# printing result
print("Tuple list with desired Preceding elements " + str(res))

Output

The original list is : [1, 4, 'gfg', 7, 8, 'gfg', 9, 'gfg']
Tuple list with desired Preceding elements [(4, 'gfg'), (8, 'gfg'), (9, 'gfg')]

Time Complexity: O(N), where N is the length of the input list test_list.

Auxiliary Space: O(N)

Method 3: Using enumerate

We loop through the original_list using enumerate() function which returns the index and value of each element.
For each element, we check if it is equal to ‘gfg’ and its index is greater than 0. If it is true, we add a tuple containing the preceding element and the current element to the tuple_list.We use list comprehension to create the tuple_list.
Finally, we print both the original and tuple list.

Python3

# Define two lists of tuples
test_list1 = [(1, 7), (6, 7), (9, 100), (4, 21)]
test_list2 = [(1, 3), (2, 1), (9, 7), (2, 17)]

# Define a function to cross-pair tuples from the two lists
def cross_pairing(test_list1, test_list2):
    # Create an empty list to store the cross pairs
    result = []

    # Loop over each tuple in the first list
    for tup1 in test_list1:
        # Loop over each tuple in the second list
        for tup2 in test_list2:
            # If the first element of tup1 is equal to the first element of tup2
            if tup1[0] == tup2[0]:
                # Cross-pair the second elements of the tuples and append to result
                result.append((tup1[1], tup2[1]))

    # Return the list of cross pairs
    return result

# Call the function and print the result
print(cross_pairing(test_list1, test_list2))

Output

Original List :  [1, 4, 'gfg', 7, 8, 'gfg', 9, 'gfg']
Tuple List with desired Preceding elements :  [(4, 'gfg'), (8, 'gfg'), (9, 'gfg')]

Time complexity: O(n^2), where n is the length of the longer input list. This is because the code iterates over each tuple in test_list1 and each tuple in test_list2, resulting in nested loops that perform n^2 comparisons.
Auxiliary Space: O(n^2), since the output list result can contain up to n^2 cross pairs. Additionally, the memory usage required for storing the input lists is O(n), since each list contains n tuples. Therefore, the total space complexity is O(n^2 + n), which can be simplified to O(n^2) since the n^2 term dominates the space requirements.

Method 4:Using reduce:

Algorithm:

1.Initialize a list test_list and a variable ele.
2.Use a list comprehension to generate a list of tuples, where each tuple contains two consecutive elements of test_list.
3.Filter the list of tuples using an if statement to only include tuples where the second element is equal to ele.
4.Use the reduce function to apply a lambda function to the filtered list of tuples. The lambda function returns a new 5.list that contains all the tuples in the previous list, plus a new tuple that contains the first and second element of the current tuple.
6.The result of the reduce function is a list of tuples containing the desired preceding elements.

Python3

from functools import reduce

test_list = [1, 4, 'gfg', 7, 8, 'gfg', 9, 'gfg']
# printing original list
print("The original list is : " + str(test_list))

ele = 'gfg'
res = reduce(lambda x, y: x + [(y[0], y[1])], [(test_list[i], test_list[i+1]) for i in range(len(test_list)-1) if test_list[i+1] == ele], [])
# printing result
print("Tuple list with desired Preceding elements: ", res)
#This code is contributed by Jyothi pinjala.

Output

The original list is : [1, 4, 'gfg', 7, 8, 'gfg', 9, 'gfg']
Tuple list with desired Preceding elements:  [(4, 'gfg'), (8, 'gfg'), (9, 'gfg')]

Time complexity: O(n), where n is the length of test_list.

Auxiliary Space: O(n), since the list of tuples generated by the list comprehension could potentially be as large as test_list. However, since the reduce function operates on the filtered list of tuples, the actual space complexity of the code may be smaller depending on how many tuples are filtered out by the if statement.