Deduplicating Python Dictionaries

In Python, dictionaries are a very common data type consisting of a set of “keys” and corresponding “values.” Since keys must be unique, deduplicating key values in a dictionary requires special handling. Next, we’ll introduce several methods for deduplicating dictionaries in Python.

Method 1: Leveraging the Uniqueness of Dictionary Keys

Since dictionary keys must be unique, we can use this property to deduplicate data.

Sample Code:

original_dict = {"a": 1, "b": 2, "c": 3, "d": 2, "e": 4, "f": 3}
new_dict = {}

for key, value in original_dict.items():
new_dict[value] = key

output_dict = {}

for value, key in new_dict.items():
output_dict[key] = value

print(output_dict)

Output:

{‘a’: 1, ‘b’: 2, ‘c’: 3, ‘e’: 4}

Here, we create a new, empty dictionary, new_dict, and use the values from the original dictionary, original_dict, as the keys in the new dictionary. Due to the uniqueness of dictionary keys, only one duplicate key is retained. Finally, we swap the keys and values in the dictionary new_dict and save it to the output dictionary output_dict.

Method 2: Using the set() Function

The set() function in Python returns a set without duplicate elements. Therefore, we can use the set() function to deduplicate a dictionary.

Sample Code:

original_dict = {"a": 1, "b": 2, "c": 3, "d": 2, "e": 4, "f": 3}

new_dict = {}
for key, value in original_dict.items():
new_dict[value] = key

output_dict = {value: key for key, value in new_dict.items()}

print(output_dict)

Output:

{1: ‘a’, 2: ‘b’, 3: ‘f’, 4: ‘e’}

Here, we use dictionary comprehensions and take advantage of the set() function to store the values of the original_dict dictionary in a set to remove duplicates. Finally, we use dictionary comprehensions to reconstruct the deduplicated keys and values into a dictionary.

Method 3: Using the collections module

Python’s collections module provides an OrderedDict class, which is an ordered dictionary that returns elements in the order they were inserted.

Sample Code:

from collections import OrderedDict

original_dict = {"a": 1, "b": 2, "c": 3, "d": 2, "e": 4, "f": 3}

output_dict = OrderedDict()
for key, value in original_dict.items():
output_dict[value] = key

print(output_dict)

Output:

OrderedDict([(1, ‘a’), (2, ‘b’), (3, ‘c’), (4, ‘e’)])

Here, we first import the OrderedDict class from the collections module, then create an ordered dictionary, output_dict. We then iterate over the original dictionary, original_dict, and store the values as keys and the keys as values in the ordered dictionary, output_dict. The resulting output_dict is the deduplicated dictionary.

Method 4: Using the Pandas Library

In addition to native Python methods, another convenient way to deduplicate data is using the drop_duplicates() method in the Pandas library.

Sample code:

import pandas as pd

original_dict = {"a": 1, "b": 2, "c": 3, "d": 2, "e": 4, "f": 3}

df = pd.DataFrame(original_dict.items(), columns=["key", "value"])
df = df.drop_duplicates("value", keep="last")
output_dict = dict(zip(df.key, df.value))

print(output_dict)

Output:

{‘a’: 1, ‘b’: 2, ‘e’: 4, ‘f’: 3}

Here, we first convert the original dictionary to a Pandas DataFrame, then use the drop_duplicates() method to remove duplicates. Finally, we convert the deduplicated DataFrame back to a dictionary format for output.

Conclusion

This article introduced four methods for deduplicating dictionaries in Python: leveraging the uniqueness of dictionary keys, the set() function, the collections module, and the Pandas library. Each method has its own advantages and disadvantages, and the choice should be based on your specific situation.