Python | Subgroups of i’th index size in list
Sometimes we need to group elements and grouping techniques and requirements vary accordingly. One such way to group the elements is by the i’th size in list which stores the dictionary of index keys with values as list elements of subsequent size i.
Input : [4, 7, 8, 10, 12, 15, 13, 17, 14, 5] Output: {1: [4], 2: [7, 8], 3: [10, 12, 15], 4: [13, 17, 14, 5]}
Let’s discuss certain ways in which this can be done. Method #1 : Using islice() + dictionary comprehension The slice method can be used to group the chunks of list required to be made as values of the dictionaries which are then assigned to their destined index key using the dictionary comprehension.
Python3
from itertools import islice
test_list = [ 4 , 7 , 8 , 10 , 12 , 15 , 13 , 17 , 14 , 5 ]
print ("The original list : " + str (test_list))
temp = iter (test_list)
res = {key: val for key, val in ((i, list (islice(temp, i)))
for i in range ( 1 , len (test_list))) if val}
print ("The grouped dictionary is : " + str (res))
|
Time Complexity: O(N2)
Space Complexity: O(N2)
Output :
The original list : [4, 7, 8, 10, 12, 15, 13, 17, 14, 5] The grouped dictionary is : {1: [4], 2: [7, 8], 3: [10, 12, 15], 4: [13, 17, 14, 5]}
Method #2 : Using itemgetter() + takewhile() + islice() In order to increase the computation speed, we introduce new functions to perform this particular task, takewhile and itemgetter functions which performs the task of grouping the sliced values.
Python3
from itertools import islice, takewhile
from operator import itemgetter
test_list = [ 4 , 7 , 8 , 10 , 12 , 15 , 13 , 17 , 14 , 5 ]
print ("The original list : " + str (test_list))
temp = iter (test_list)
res = {key: val for key, val in
takewhile(itemgetter( 1 ), ((i, list (islice(temp, i)))
for i in range ( 1 , len (test_list))))}
print ("The grouped dictionary is : " + str (res))
|
Time Complexity: O(N2)
Space Complexity: O(N)
Output :
The original list : [4, 7, 8, 10, 12, 15, 13, 17, 14, 5] The grouped dictionary is : {1: [4], 2: [7, 8], 3: [10, 12, 15], 4: [13, 17, 14, 5]}
Last Updated :
14 Mar, 2023
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