Python - Filter dictionary values in heterogeneous dictionary

Sometimes, while working with Python dictionaries, we can have a problem in which we need to filter out certain values based on certain conditions on a particular type, e.g all values smaller than K. This task becomes complex when dictionary values can be heterogeneous. This kind of problem can have applications across many domains. Let's discuss certain ways in which this task can be performed.

Input : test_dict = {'Gfg' : 10, 'for' : 'geeks'} 
Output : {'Gfg': 10, 'for': 'geeks'}

Input : test_dict = {'Gfg' : 'geeks'} 
Output : {'Gfg': 'geeks'} 

Method #1 : Using type() + dictionary comprehension
The combination of above functions can be used to perform this task. In this, we check for integral type using type() and filter the data in dictionary comprehension. 

Step-by-step approach

• Use dictionary comprehension to create a new dictionary res.
• Iterate over the items of test_dict using the items() method.
• For each item, check if the value is not an integer (type(val) != int) or if it is greater than K (val > K).
• If the condition is true, add the key-value pair to the new dictionary res.
• Print the new dictionary res using the print() function.

Below is the implementation of the above approach:

The original dictionary : {'Gfg': 4, 'for': 'geeks', 'is': 2, 'best': 3}
Values greater than K : {'Gfg': 4, 'for': 'geeks'}

Time Complexity: O(n)
Auxiliary Space: O(n)

Method #2 : Using isinstance() + dictionary comprehension
The combination of above functions can also be used to solve this problem. In this, we perform this task similar to above, but the difference being that type test is done by isinstance() rather than type().

The original dictionary : {'Gfg': 4, 'for': 'geeks', 'is': 2, 'best': 3}
Values greater than K : {'Gfg': 4, 'for': 'geeks'}

Time complexity: O(n), where n is the number of items in the dictionary.
Auxiliary space: O(k), where k is the number of items in the resulting dictionary after filtering.

Method 3: Using a for loop and conditional statements:

Step-by-step approach:

• Initialize a dictionary test_dict with some key-value pairs.
• Print the original dictionary using print("The original dictionary : " + str(test_dict)).
• Initialize an integer K with value 3.
• Create an empty dictionary res to store the filtered values.
• Loop through the key-value pairs of the dictionary using for key, val in test_dict.items()
  • Use a conditional statement to filter the dictionary values. If the value is not an integer or it is greater than K, we add it to the res dictionary using res[key] = val.
• Print the filtered dictionary using print("Values greater than K : " + str(res)).

Below is the implementation of the above approach:

The original dictionary : {'Gfg': 4, 'is': 2, 'best': 3, 'for': 'geeks'}
Values greater than K : {'Gfg': 4, 'for': 'geeks'}

Time complexity: O(n), where n is the number of key-value pairs in the dictionary.
Auxiliary space: O(n), where n is the number of key-value pairs in the dictionary.

Method #4: Using a dictionary comprehension with if condition:

Step-by-step approach:

• Initialize a dictionary test_dict with some key-value pairs.
• Initialize a variable K with a value to compare against dictionary values.
• Use dictionary comprehension to filter out the items from the dictionary.
• Loop through each key-value pair in the dictionary and check if the value is either non-integer or greater than K.
• If the value satisfies the condition, add the key-value pair to the result dictionary.
• Return the filtered dictionary.

Below is the implementation of the above approach:

Values greater than K : {'Gfg': 4, 'for': 'geeks'}

 Time complexity: O(n) as it loops through all the items in the dictionary once. 
Auxiliary space: O(n) as it creates a new dictionary to store the filtered items.

Method #5: Using filter() function with lambda function

Step-by-step approach:

• Initialize a variable K with a value of 3.
• Use the filter() function to filter the items in the test_dict dictionary using a lambda function. The lambda function checks if an item's value is not an integer or is greater than K.
• Convert the filtered items into a dictionary using the dict() function.
• Assign the filtered dictionary to a variable named res.
• Print the filtered dictionary using the print() function.

Below is the implementation of the above approach:

The original dictionary : {'Gfg': 4, 'is': 2, 'best': 3, 'for': 'geeks'}
Values greater than K : {'Gfg': 4, 'for': 'geeks'}

Time Complexity: O(n), where n is the size of the input dictionary
Auxiliary Space: O(n), where n is the size of the input dictionary. This is the space required to store the filtered dictionary.