Python | Filter the negative values from given dictionary

Given a dictionary, the task is to filter all the negative values from given dictionary. Let’s discuss few methods to do this task. 

Method #1: Using dict comprehension

Follow the below steps to implement:

• Initializing a dictionary named ini_dict with some key-value pairs.
• Print the initial dictionary using the print() function.
• Next, create a new dictionary named result using dictionary comprehension. Dictionary comprehension is a concise way to create dictionaries from other iterables like lists, tuples, and sets.
• In the dictionary comprehension, iterate over the key-value pairs of the ini_dict using the items() method.
• For each key-value pair, check if the value is greater than or equal to 0 using the if condition.
• If the condition is true, add the key-value pair to the new dictionary result.
• Finally, print the filtered dictionary result using the print() function.

Below is the implementation of the above approach:

Python3

# Python code to demonstrate
# return the filtered dictionary
# on certain criteria

# Initialising dictionary
ini_dict = {'a':1, 'b':-2, 'c':-3, 'd':7, 'e':0}

# printing initial dictionary
print ("initial lists", str(ini_dict))

# filter dictionary such that no value is greater than 0
result = dict((k, v) for k, v in ini_dict.items() if v >= 0)

print("resultant dictionary : ", str(result))

Output

initial lists {'a': 1, 'b': -2, 'c': -3, 'd': 7, 'e': 0}
resultant dictionary :  {'a': 1, 'd': 7, 'e': 0}

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

Method #2: Using lambda and filter

Python3

# Python code to demonstrate
# return the filtered dictionary
# on certain criteria
# Initialising dictionary
ini_dict = {'a':1, 'b':-2, 'c':-3, 'd':7, 'e':0}

# printing initial dictionary
print ("initial lists", str(ini_dict))

# filter dictionary such that no value is greater than 0
result = dict(filter(lambda x: x[1] >= 0.0, ini_dict.items()))
result = dict(result)

print("resultant dictionary : ", str(result))

Output

initial lists {'a': 1, 'b': -2, 'c': -3, 'd': 7, 'e': 0}
resultant dictionary :  {'a': 1, 'd': 7, 'e': 0}

Time Complexity: O(n) where n is the number of elements in the dictionary.
Auxiliary Space: O(n) as the size of the resultant dictionary can be equal to the number of elements in the initial dictionary.

Method #3 : Using find() method

Python3

# Python code to demonstrate
# return the filtered dictionary
# on certain criteria

# Initialising dictionary
ini_dict = {'a': 1, 'b': -2, 'c': -3, 'd': 7, 'e': 0}

# printing initial dictionary
print("initial lists", str(ini_dict))

# filter dictionary such that no value is greater than 0
res = dict()
for i in ini_dict:
    if(str(ini_dict[i]).find("-") != 0):
        res[i] = ini_dict[i]


print("resultant dictionary : ", str(res))

Output

initial lists {'a': 1, 'b': -2, 'c': -3, 'd': 7, 'e': 0}
resultant dictionary :  {'a': 1, 'd': 7, 'e': 0}

The time complexity of this code is O(n), where n is the number of items in the initial dictionary ini_dict. 

The auxiliary space used by this code is O(n).

Method #4 :  Using map() and a custom function

Here is an example of using map() and a custom function to filter negative values from a dictionary:

Python3

#If the value is negative, it returns None.
def filter_negative(item):
  key, value = item
  if value < 0:
    return
  return (key, value)

#Initialize the dictionary
ini_dict = {'a': 1, 'b': -2, 'c': -3, 'd': 7, 'e': 0}

#Use map to apply the filter_negative function to each item in the dictionary and return a map object
#Use filter to remove the None values from the map object
#Use dict to convert the map object to a dictionary
result = dict(filter(None, map(filter_negative, ini_dict.items())))

#Print the resulting dictionary
print(result)
#This code is contributed by Edula Vinay Kumar Reddy

Output

{'a': 1, 'd': 7, 'e': 0}

The filter_negative() function takes a tuple representing a key-value pair in the dictionary, and returns the tuple if the value is non-negative. If the value is negative, the function returns None, which is filtered out by the filter() function. The map() function applies filter_negative() to each item in the dictionary, producing a list of tuples. The filter() function then filters out any None values, and the resulting list is passed to dict() to create the final filtered dictionary.

Time complexity: O(n), where n is the number of items in the dictionary. T
Auxiliary Space: O(n), as the filtered dictionary will have a size equal to the number of non-negative values in the original dictionary.

Method #5 : Using startswith() method

Python3

# Python code to demonstrate
# return the filtered dictionary
# on certain criteria

# Initialising dictionary
ini_dict = {'a': 1, 'b': -2, 'c': -3, 'd': 7, 'e': 0}

# printing initial dictionary
print("initial lists", str(ini_dict))

# filter dictionary such that no value is greater than 0
res = dict()
for i in list(ini_dict.keys()):
    x=str(ini_dict[i])
    if(not x.startswith("-")):
        res[i]=ini_dict[i]

print("resultant dictionary : ", str(res))

Output

initial lists {'a': 1, 'b': -2, 'c': -3, 'd': 7, 'e': 0}
resultant dictionary :  {'a': 1, 'd': 7, 'e': 0}

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

Method #6: Using list comprehension and dict() constructor

Step-by-step approach:

• Initialize the dictionary ini_dict
• Print the initial dictionary ini_dict
• Use a list comprehension to filter the dictionary such that no value is greater than 0. Store the resulting key-value pairs as a list of tuples.
• Convert the list of tuples into a dictionary using the dict() constructor.
• Print the resultant dictionary result.
• Compute the time complexity and auxiliary space complexity.

Below is the implementation of the above approach:

Python3

# Python code to demonstrate
# return the filtered dictionary
# on certain criteria

# Initialising dictionary
ini_dict = {'a':1, 'b':-2, 'c':-3, 'd':7, 'e':0}

# printing initial dictionary
print ("initial dictionary:", ini_dict)

# using list comprehension and dict() constructor
result = dict([(k, v) for k, v in ini_dict.items() if v >= 0])

# printing resultant dictionary
print("resultant dictionary:", result)

# compute time complexity and auxiliary space
# time complexity: O(N)
# auxiliary space: O(N)

Output

initial dictionary: {'a': 1, 'b': -2, 'c': -3, 'd': 7, 'e': 0}
resultant dictionary: {'a': 1, 'd': 7, 'e': 0}

Time complexity: O(N) where N is the number of key-value pairs in the initial dictionary. 
Auxiliary space: O(N) because we’re creating a new list of tuples to store the filtered key-value pairs before converting it into a dictionary.