Remove tuples having duplicate first value from given list of tuples in Python

When removing tuples with duplicate first values from a list of tuples, you can use a set to track visited first elements. This approach preserves the first occurrence of each unique first value.

Using Set to Track First Values

The most efficient approach uses a set to remember which first values have been seen ?

tuples_list = [(45.324, 'Hi Jane, how are you'),
               (34252.85832, 'Hope you are good'), 
               (45.324, 'You are the best.')]

visited_data = set()
result = []

for first, second in tuples_list:
    if first not in visited_data:
        visited_data.add(first)
        result.append((first, second))

print("Original list of tuples:")
print(tuples_list)
print("After removing duplicates:")
print(result)

Original list of tuples:
[(45.324, 'Hi Jane, how are you'), (34252.85832, 'Hope you are good'), (45.324, 'You are the best.')]
After removing duplicates:
[(45.324, 'Hi Jane, how are you'), (34252.85832, 'Hope you are good')]

Using Dictionary (Alternative Method)

You can also use a dictionary to store the first occurrence of each first value ?

tuples_list = [(1, 'apple'), (2, 'banana'), (1, 'orange'), (3, 'grape')]

unique_dict = {}
for first, second in tuples_list:
    if first not in unique_dict:
        unique_dict[first] = second

result = list(unique_dict.items())
print("Original list:", tuples_list)
print("Unique tuples:", result)

Original list: [(1, 'apple'), (2, 'banana'), (1, 'orange'), (3, 'grape')]
Unique tuples: [(1, 'apple'), (2, 'banana'), (3, 'grape')]

How It Works

• The set visited_data keeps track of first values already seen
• For each tuple, we check if its first element is in the visited set
• If not seen before, we add it to both the set and result list
• This preserves only the first occurrence of each unique first value

Comparison

where n = total tuples, k = unique first values

Conclusion

Use a set to efficiently track visited first values when removing tuple duplicates. This approach has O(n) time complexity and preserves the first occurrence of each unique tuple.