Python - Factors Frequency Dictionary
Last Updated :
04 May, 2023
Given a list with elements, construct a dictionary with frequency of factors.
Input : test_list = [2, 4, 6, 8] Output : {1: 4, 2: 4, 3: 1, 4: 2, 5: 0, 6: 1, 7: 0, 8: 1} Explanation : All factors count mapped, e.g 2 is divisible by all 4 values, hence mapped with 4. Input : test_list = [1, 2] Output : {1: 2, 2 : 1} Explanation : Similar as above, 1 is factor of all.
Method #1 : Using loop
This is brute way in which this task can be performed. In this, the elements are iterated and required number is checked for being a factor, if yes, its frequency is increased in dictionary corresponding to its key.
Python3
# Python3 code to demonstrate working of
# Factors Frequency Dictionary
# Using loop
# initializing list
test_list = [2, 4, 6, 8, 3, 9, 12, 15, 16, 18]
# printing original list
print("The original list : " + str(test_list))
res = dict()
# iterating till max element
for idx in range(1, max(test_list)):
res[idx] = 0
for key in test_list:
# checking for factor
if key % idx == 0:
res[idx] += 1
# printing result
print("The constructed dictionary : " + str(res))
OutputThe original list : [2, 4, 6, 8, 3, 9, 12, 15, 16, 18]
The constructed dictionary : {1: 10, 2: 7, 3: 6, 4: 4, 5: 1, 6: 3, 7: 0, 8: 2, 9: 2, 10: 0, 11: 0, 12: 1, 13: 0, 14: 0, 15: 1, 16: 1, 17: 0}
Time Complexity: O(n*n), where n is the elements of dictionary
Auxiliary Space: O(n), where n is the size of dictionary
Method #2 : Using sum() + loop
This is almost similar approach to above problem. The difference being sum() is used for summation rather than a manual loop for solving problem.
Python3
# Python3 code to demonstrate working of
# Factors Frequency Dictionary
# Using sum() + loop
# initializing list
test_list = [2, 4, 6, 8, 3, 9, 12, 15, 16, 18]
# printing original list
print("The original list : " + str(test_list))
res = dict()
for idx in range(1, max(test_list)):
# using sum() instead of loop for sum computation
res[idx] = sum(key % idx == 0 for key in test_list)
# printing result
print("The constructed dictionary : " + str(res))
OutputThe original list : [2, 4, 6, 8, 3, 9, 12, 15, 16, 18]
The constructed dictionary : {1: 10, 2: 7, 3: 6, 4: 4, 5: 1, 6: 3, 7: 0, 8: 2, 9: 2, 10: 0, 11: 0, 12: 1, 13: 0, 14: 0, 15: 1, 16: 1, 17: 0}
Time Complexity: O(n*n) where n is the number of elements in the list “test_list”.
Auxiliary Space: O(n) where n is the number of elements in the list “test_list”.
Method #3: Using collections.Counter() and itertools.chain()
Import the collections module.
Initialize a dictionary res with all the keys as integers from 1 to the maximum value in the test_list.
Convert the test_list into a list of factors using a nested list comprehension.
Flatten the list of factors into a single list using the itertools.chain() method.
Count the frequency of each factor using the collections.Counter() method and store the result in res.
Print the resulting dictionary res.
Python3
import collections
import itertools
# initializing list
test_list = [2, 4, 6, 8, 3, 9, 12, 15, 16, 18]
# printing original list
print("The original list : " + str(test_list))
# using collections.Counter() and itertools.chain() to construct frequency dictionary
res = {i: collections.Counter(itertools.chain(*[[j for j in range(1, i+1) if key % j == 0] for key in test_list]))[i] for i in range(1, max(test_list)+1)}
# printing result
print("The constructed dictionary : " + str(res))
OutputThe original list : [2, 4, 6, 8, 3, 9, 12, 15, 16, 18]
The constructed dictionary : {1: 10, 2: 7, 3: 6, 4: 4, 5: 1, 6: 3, 7: 0, 8: 2, 9: 2, 10: 0, 11: 0, 12: 1, 13: 0, 14: 0, 15: 1, 16: 1, 17: 0, 18: 1}
The time complexity O(n^2), where n is the length of the test_list.
The auxiliary space O(n^2), since we are creating a list of factors for each element in test_list, and then flattening it into a single list.
Method #4 : Using list(),set() and count() methods
Approach
- Find the factors of each number of test_list using nested for loops and append them to an empty list x
- Remove the duplicates from x using list(),set() and store it in y, create an empty dictionary res
- Initiate a for loop over list y and initialise the dictionary with elements of y as keys and count of these elements in x as values
- Display res
Python3
# Python3 code to demonstrate working of
# Factors Frequency Dictionary
# Using loop
# initializing list
test_list = [2, 4, 6, 8, 3, 9, 12, 15, 16, 18]
# printing original list
print("The original list : " + str(test_list))
# iterating till max element
x=[]
for i in range(1, max(test_list)):
for key in test_list:
if key % i == 0:
x.append(i)
y=list(set(x))
res=dict()
for i in y:
res[i]=x.count(i)
# printing result
print("The constructed dictionary : " + str(res))
OutputThe original list : [2, 4, 6, 8, 3, 9, 12, 15, 16, 18]
The constructed dictionary : {1: 10, 2: 7, 3: 6, 4: 4, 5: 1, 6: 3, 8: 2, 9: 2, 12: 1, 15: 1, 16: 1}
Time Complexity : O(M*N) M - length of range 1 to max(test_list) N - length of test_list
Auxiliary Space : O(N) N - length of res dictionary
Similar Reads
Python - Frequency Grouping Dictionary
Sometimes, while working with Python dictionaries, we can have a problem in which we need to perform the grouping of dictionary data, in a way in which we need to group all the similar dictionaries key with its frequency. This kind of problem has its application in web development domain. Let's disc
4 min read
Odd Frequency Characters - Python
The task of finding characters with odd frequencies in a string in Python involves identifying which characters appear an odd number of times. For example, in the string "geekforgeeks," characters like 'r', 'o', 'f', and 's' appear an odd number of times. The output will be a list of these character
3 min read
Python - Convert Frequency dictionary to list
When we convert a frequency dictionary to a list, we are transforming the dictionary into a list of key-value or just the keys/values, depending on needs. We can convert a frequency dictionary to a list using methods such as list comprehension, loops, extend() method and itertools.chain() function.F
3 min read
Python - Successive Characters Frequency
Sometimes, while working with Python strings, we can have a problem in which we need to find the frequency of next character of a particular word in string. This is quite unique problem and has the potential for application in day-day programming and web development. Let's discuss certain ways in wh
6 min read
Python - Concatenate Dynamic Frequency
Given List of elements, perform concatenation with frequency dynamically, i.e each element is concatenated with its frequency till its index. Input : test_list = ['z', 'z', 'e', 'f', 'f'] Output : ['1z', '2z', '1e', '1f', '2f'] Explanation : As occurrence increase, concat number is increased. Input
7 min read
Get the First Key in Dictionary - Python
We are given a dictionary and our task is to find the first key in the dictionary. Since dictionaries in Python 3.7+ maintain insertion order, the first key is the one that was added first to the dictionary. For example, if we have the dictionary {'a': 10, 'b': 20, 'c': 30}, the first key is 'a'.Usi
2 min read
Consecutive characters frequency - Python
This problem involves identifying characters that appear consecutively and counting how many times they appear together. Here, we will explore different methods to calculate the frequency of consecutive characters in a string.Using regular expressionsWe can use the re module to efficiently count con
3 min read
Python Iterate Dictionary Key, Value
In Python, a Dictionary is a data structure that stores the data in the form of key-value pairs. It is a mutable (which means once created we modify or update its value later on) and unordered data structure in Python. There is a thing to keep in mind while creating a dictionary every key in the dic
3 min read
Python | K modulo on each Dictionary Key
Sometimes, while working with dictionaries, we might come across a problem in which we require to perform a particular operation on each value of keys like K modulo on each key. This type of problem can occur in web development domain. Letâs discuss certain ways in which this task can be performed.
4 min read
Python | Extract filtered Dictionary Values
While working with Python dictionaries, there can be cases in which we are just concerned about getting the filtered values list and donât care about keys. This is yet another essential utility and solution to it should be known and discussed. Letâs perform this task through certain methods. Method
4 min read