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Python – Flag None Element Rows in Matrix

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  • Last Updated : 02 Sep, 2020

Given a Matrix, return True for rows which contain a None Value, else return False.

Input : test_list = [[2, 4, None, 3], [3, 4, 1, None], [2, 4, 7, 4], [2, 8, None]]
Output : [True, True, False, True]
Explanation : 1, 2 and 4th index contain None occurrence.

Input : test_list = [[2, 4, None, 3], [3, 4, 1, None], [2, 4, None, 4], [2, 8, None]]
Output : [True, True, True, True]
Explanation : All rows have None.

Method #1 : Using List comprehension

In this, we iterate for each row and use in operator to check for None in these. If found, True is returned, else False is returned.

Python3




# Python3 code to demonstrate working of 
# Flag None Element Rows in Matrix
# Using list comprehension
  
# initializing list
test_list = [[2, 4, None, 3], [3, 4, 1, None], [2, 4, 7, 4], [2, 8]]
  
# printing original list
print("The original list is : " + str(test_list))
  
# in operator to check None value 
# True if any None is found 
res = [True if None in sub else False for sub in test_list]
  
# printing result 
print("None Flagged List : " + str(res))
Output
The original list is : [[2, 4, None, 3], [3, 4, 1, None], [2, 4, 7, 4], [2, 8]]
None Flagged List : [True, True, False, False]

Method #2 : Using all() + list comprehension

In this, we check for all values to be True using all(), if yes, its not flagged True and list comprehension is used to check for each row.

Python3




# Python3 code to demonstrate working of 
# Flag None Element Rows in Matrix
# Using all() + list comprehension
  
# initializing list
test_list = [[2, 4, None, 3], [3, 4, 1, None], [2, 4, 7, 4], [2, 8]]
  
# printing original list
print("The original list is : " + str(test_list))
  
# all() checks for all non none values  
res = [False if all(sub) else True for sub in test_list]
  
# printing result 
print("None Flagged List : " + str(res))
Output
The original list is : [[2, 4, None, 3], [3, 4, 1, None], [2, 4, 7, 4], [2, 8]]
None Flagged List : [True, True, False, False]

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