Many times while working in data science domain we need to get the list of all the indices which are Non None, so that they can be easily be prepossessed. This is quite a popular problem and solution to it comes quite handy. Let’s discuss certain ways in which this can be done.
Method #1 : Using list comprehension + range()
In this method we just check for each index using the range function and store the index if we find that index is Not None.
# Python3 code to demonstrate# Non-None elements indices# using list comprehension + enumerate # initializing list test_list = [1, None, 4, None, None, 5] # printing original listprint("The original list : " + str(test_list)) # using list comprehension + enumerate# Non-None elements indices res = [i for i in range(len(test_list)) if test_list[i] != None] # print resultprint("The Non None indices list is : " + str(res)) |
The original list : [1, None, 4, None, None, 5] The Non None indices list is : [0, 2, 5]
Method #2 : Using list comprehension + enumerate()
The enumerate function can be used to iterate together the key and value pair and list comprehension can be used to bind all this logic in one line.
# Python3 code to demonstrate# Non-None elements indices # using list comprehension + enumerate # initializing list test_list = [1, None, 4, None, None, 5] # printing original listprint("The original list : " + str(test_list)) # using list comprehension + enumerate# Non-None elements indicesres = [i for i, val in enumerate(test_list) if val != None] # print resultprint("The Non None indices list is : " + str(res)) |
The original list : [1, None, 4, None, None, 5] The Non None indices list is : [0, 2, 5]
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