Python – Group Elements in Matrix
Last Updated :
10 Apr, 2023
Given a Matrix with two columns, group 2nd column elements on basis of 1st column.
Input : test_list = [[5, 8], [2, 0], [5, 4], [2, 3], [2, 9]]
Output : {5: [8, 4], 2: [0, 3, 9]}
Explanation : 8 and 4 are mapped to 5 in Matrix, all others to 2.
Input : test_list = [[2, 8], [2, 0], [2, 4], [2, 3], [2, 9]]
Output : {2: [8, 4, 0, 3, 9]}
Explanation : All mapped to 2.
Method #1 : Using dictionary comprehension + loop
This is one of the ways in which this task can be performed. In this, we construct the dictionary with empty list values from row 1 and then run a loop to assign values into it.
Step-by-step approach:
- Initialize the list of lists as the input list.
- Print the original list.
- Initialize an empty dictionary with default empty lists using dictionary comprehension. The keys are the first elements of the tuples in the input list.
- Loop through the input list and append the second element of each tuple to the list in the dictionary with the same key.
- Print the result, which is the dictionary with the grouped elements.
Below is the implementation of the above approach:
Python3
test_list = [[5, 8], [2, 0], [5, 4], [2, 3], [7, 9]]
print("The original list : " + str(test_list))
res = {idx[0]: [] for idx in test_list}
for idx in test_list:
res[idx[0]].append(idx[1])
print("The Grouped Matrix : " + str(res))
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Output
The original list : [[5, 8], [2, 0], [5, 4], [2, 3], [7, 9]]
The Grouped Matrix : {5: [8, 4], 2: [0, 3], 7: [9]}
Time complexity: O(n), where n is the length of the input list.
Auxiliary space: O(n), as a dictionary is created with n key-value pairs.
Method #2 : Using loop + defaultdict()
This is similar to above method. The difference being that initial empty mesh is created using defaultdict().
Python3
from collections import defaultdict
test_list = [[5, 8], [2, 0], [5, 4], [2, 3], [7, 9]]
print("The original list : " + str(test_list))
res = defaultdict(list)
for idx in test_list:
res[idx[0]].append(idx[1])
print("The Grouped Matrix : " + str(dict(res)))
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Output
The original list : [[5, 8], [2, 0], [5, 4], [2, 3], [7, 9]]
The Grouped Matrix : {5: [8, 4], 2: [0, 3], 7: [9]}
The time complexity of this code is O(n), where n is the number of elements in the input list.
The auxiliary space complexity of this code is also O(n), where n is the number of elements in the input list.
Method #3 : Using nested for loops
Approach
- Extracting the unique 0 index values from nested list
- Initiated a nested for loop to group similar first index elements
Python3
test_list = [[5, 8], [2, 0], [5, 4], [2, 3], [7, 9]]
print("The original list : " + str(test_list))
res=dict()
x=[]
for i in test_list:
if i[0] not in x:
x.append(i[0])
for i in x:
v=[]
for j in test_list:
if j[0]==i:
v.append(j[1])
res[i]=v
print("The Grouped Matrix : " + str(res))
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Output
The original list : [[5, 8], [2, 0], [5, 4], [2, 3], [7, 9]]
The Grouped Matrix : {5: [8, 4], 2: [0, 3], 7: [9]}
Time Complexity : O(n*n)
Auxiliary Space : O(n)
Method #4: Using itertools.groupby()
Use the itertools.groupby() function to group elements in the matrix based on their first value. This function takes an iterable and a key function as arguments, and returns an iterator that produces pairs of keys and groups of items that have the same key.
Python3
from itertools import groupby
test_list = [[5, 8], [2, 0], [5, 4], [2, 3], [7, 9]]
print("The original list : " + str(test_list))
test_list.sort()
groups = groupby(test_list, lambda x: x[0])
res = {k: [v[1] for v in group] for k, group in groups}
print("The Grouped Matrix : " + str(res))
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Output
The original list : [[5, 8], [2, 0], [5, 4], [2, 3], [7, 9]]
The Grouped Matrix : {2: [0, 3], 5: [4, 8], 7: [9]}
Time complexity: O(n log n) due to the use of the groupby() function, which requires the input to be sorted.
Auxiliary space: O(n), since we need to store the groups in a dictionary.
Method #5: Using list comprehension and set
This method uses list comprehension and set to group the elements in the matrix. The set function is used to get the unique elements of the first column of the matrix. Then, a dictionary comprehension is used to create a dictionary with the unique elements as keys and a list of the corresponding second column elements as values.
Python3
test_list = [[5, 8], [2, 0], [5, 4], [2, 3], [7, 9]]
print("The original list : " + str(test_list))
res = {i: [j[1] for j in test_list if j[0] == i] for i in set([k[0] for k in test_list])}
print("The Grouped Matrix : " + str(res))
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Output
The original list : [[5, 8], [2, 0], [5, 4], [2, 3], [7, 9]]
The Grouped Matrix : {2: [0, 3], 5: [8, 4], 7: [9]}
Time complexity: O(n^2), where n is the number of elements in the input list.
Auxiliary space: O(n^2), as the resulting dictionary contains a key-value pair for each unique element in the first column of the input list.
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