Python | Remove False row from matrix

Sometimes, while handling data, especially in Machine Learning domain, we need to go through a lot of incomplete or empty data. We sometimes need to eliminate the rows which do not contain a value in any of the columns. Let’s discuss certain ways to remove the rows that have all False values as list columns.

Method #1 : Using list comprehension + `count() + len()`

We can perform this particular task using the list comprehension recipe, partnered with the combination of len and count function to check for similarity element counter equating to the length of list.

 `# Python3 code to demonstrate ` `# removing False rows in matrix  ` `# using list comprehension + count() + len() ` ` `  `# initializing matrix ` `test_list ``=` `[[``1``, ``True``, ``2``], [``False``, ``False``, ``3``], ` `            ``[``False``, ``False``, ``False``], [``1``, ``0``, ``1``]] ` ` `  `# printing original list ` `print``(``"The original list : "` `+` `str``(test_list)) ` ` `  `# using list comprehension + count() + len() ` `# removing False rows in matrix ` `res ``=` `[sub ``for` `sub ``in` `test_list  ` `       ``if` `sub.count(``False``) !``=` `len``(sub)] ` ` `  `# print result ` `print``(``"The list after removal of False rows : "` `+` `str``(res)) `

Output :

The original list : [[1, True, 2], [False, False, 3], [False, False, False], [1, 0, 1]]
The list after removal of False rows : [[1, True, 2], [False, False, 3], [1, 0, 1]]

Method #2 : Using list comprehension + `set()`

This particular task can also be performed by converting the entire row into a set and then checking for the single value False set for equality and removing if a match is found.

 `# Python3 code to demonstrate ` `# removing False rows in matrix  ` `# using list comprehension + set() ` ` `  `# initializing matrix ` `test_list ``=` `[[``1``, ``True``, ``2``], [``False``, ``False``, ``3``], ` `            ``[``False``, ``False``, ``False``], [``1``, ``0``, ``1``]] ` ` `  `# printing original list ` `print``(``"The original list : "` `+` `str``(test_list)) ` ` `  `# using list comprehension + set() ` `# removing False rows in matrix ` `res ``=` `[sub ``for` `sub ``in` `test_list ``if` `set``(sub) !``=` `{``False``}] ` ` `  `# print result ` `print``(``"The list after removal of False rows : "` `+` `str``(res)) `

Output :

The original list : [[1, True, 2], [False, False, 3], [False, False, False], [1, 0, 1]]
The list after removal of False rows : [[1, True, 2], [False, False, 3], [1, 0, 1]]

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