Altering duplicate values from a given Python list

Working with information in Python frequently includes controlling records, which are basic information structures. In any case, managing duplicate values inside a list can display challenges. Whereas evacuating duplicates may be a common errand, there are circumstances where altering duplicate values and protecting the large structure of the list becomes necessary.

In this article, we'll investigate different approaches to handle this particular issue. Instead of evacuating copy values, we'll center on changing them. Modifying copy values can be valuable in different scenarios, such as recognizing between unique and copy passages or following the recurrence of copies.

Altering Duplicate Values in Python

Duplicate values in Python refer to the occurrence of the same element at different times inside a list or another collection. They need to be altered due to the following reasons −

• Ensuring Data Accuracy −

  Duplicate values distort the precision of information investigation and calculations. When computing measurements like midpoints or amassing information, each event of a copy is checked independently, driving to skew comes about. Altering duplicate values guarantees that each one of a kind esteem is spoken to precisely, empowering exact information examination and calculations.

• Improving Algorithm Efficiency −

  Calculations working on records can be adversely affected by duplicate values. Looking for particular esteem in a list with copies requires extra iterations, abating down the look prepare. By altering duplicate values, the look space is decreased, driving to make strides in calculation effectiveness and speedier execution times.

• Enhancing Program Performance −

  Duplicate values in a list can significantly affect program execution, particularly when managing huge datasets. Operations such as sorting, sifting, or amassing information ended up being less proficient due to excess values. By altering duplicate values, program execution is improved by decreasing information estimates and killing superfluous reiterations, coming about in speedier and more responsive programs.

Approach 1: Using a Set

The first approach involves utilizing the unique property of sets to remove duplicate elements from a list. The set data structure in Python is designed to store unique elements. By converting the list to a set and then back to a list, duplicate values are automatically removed. Here's a step-by-step algorithm for this approach −

Algorithm

• Step 1 − Initialize an empty set.

• Step 2 − Iterate through the list, checking each element −

  • If the element is not present in the set, add it.

  • If the element is already present, alter the duplicate value.

• Step 3 − Print the modified list.

Example

def alter_duplicates(lst):
   unique_set = set()
   for i in range(len(lst)):
      if lst[i] not in unique_set:
         unique_set.add(lst[i])
      else:
         lst[i] = f"Altered"
   return lst
# Example usage
my_list = [1, 2, 3, 2, 4, 1, 5, 1]
altered_list = alter_duplicates(my_list)
print(altered_list)

Output

 [1, 2, 3, 'Altered', 4, 'Altered', 5, 'Altered']

Approach 2: Using a Dictionary

The second approach involves using a dictionary to filter out duplicate values from the list. A dictionary can be employed to filter out duplicate values from a list. By assigning duplicate values as keys in the dictionary, their uniqueness is automatically enforced. Converting the dictionary keys back to a list provides a list with altered duplicate values.

Algorithm

• Step 1 − Initialize an empty dictionary.

• Step 2 − Iterate through the list, checking each element −

  • If the element is not present in the dictionary, add it as a key with a value of 1.

  • If the element is already present in the dictionary, increment its value by 1.

• Step 3 − Iterate through the list again, altering duplicate values −

  • Check if the value corresponding to the current element in the dictionary is

    greater than 1.

  • If so, alter the duplicate value.

• Step 4 − Print the modified list.

Example

def alter_duplicates(lst):
   count_dict = {}
   for element in lst:
      if element not in count_dict:
         count_dict[element] = 1
      else:
         count_dict[element] += 1
   for i in range(len(lst)):
      if count_dict[lst[i]] > 1:
         lst[i] = f"Altered"
   return lst

# Example usage
my_list = [1, 2, 3, 2, 4, 1, 5, 1]
altered_list = alter_duplicates(my_list)
print(altered_list)

Output

['Altered', 'Altered', 3, 'Altered', 4, 'Altered', 5, 'Altered']

Conclusion

In conclusion, we investigated three distinctive approaches to altering duplicate values in a Python list. By utilizing a lexicon, a set, or list comprehension, we were able to adjust copy values whereas protecting the general structure of the list. Depending on the particular prerequisites of your errand, you'll select the approach that best suits your needs. Testing with these procedures will improve your capacity to work with records and handle copy values viably in Python.