Convert multi-dimensional list to a 1D list in Python

前端 未结 7 666
萌比男神i
萌比男神i 2020-12-05 00:14

A multidimensional list like l=[[1,2],[3,4]] could be converted to a 1D one by doing sum(l,[]). Can anybody please explain how that happens?

<
相关标签:
7条回答
  • 2020-12-05 00:37

    sum adds a sequence together using the + operator. e.g sum([1,2,3]) == 6. The 2nd parameter is an optional start value which defaults to 0. e.g. sum([1,2,3], 10) == 16.

    In your example it does [] + [1,2] + [3,4] where + on 2 lists concatenates them together. Therefore the result is [1,2,3,4]

    The empty list is required as the 2nd paramter to sum because, as mentioned above, the default is for sum to add to 0 (i.e. 0 + [1,2] + [3,4]) which would result in unsupported operand type(s) for +: 'int' and 'list'

    This is the relevant section of the help for sum:

    sum(sequence[, start]) -> value

    Returns the sum of a sequence of numbers (NOT strings) plus the value of parameter 'start' (which defaults to 0).

    Note

    As wallacoloo comented this is not a general solution for flattening any multi dimensional list. It just works for a list of 1D lists due to the behavior described above.

    Update

    For a way to flatten 1 level of nesting see this recipe from the itertools page:

    def flatten(listOfLists):
        "Flatten one level of nesting"
        return chain.from_iterable(listOfLists)
    

    To flatten more deeply nested lists (including irregularly nested lists) see the accepted answer to this question (there are also some other questions linked to from that question itself.)

    Note that the recipe returns an itertools.chain object (which is iterable) and the other question's answer returns a generator object so you need to wrap either of these in a call to list if you want the full list rather than iterating over it. e.g. list(flatten(my_list_of_lists)).

    0 讨论(0)
  • 2020-12-05 00:39

    It looks to me more like you're looking for a final answer of:

    [3, 7]
    

    For that you're best off with a list comprehension

    >>> l=[[1,2],[3,4]]
    >>> [x+y for x,y in l]
    [3, 7]
    
    0 讨论(0)
  • 2020-12-05 00:42

    For any kind of multidiamentional array, this code will do flattening to one dimension :

    def flatten(l):
        try:
            return flatten(l[0]) + (flatten(l[1:]) if len(l) > 1 else []) if type(l) is list else [l]
        except IndexError:
            return []
    
    0 讨论(0)
  • 2020-12-05 00:46

    The + operator concatenates lists and the starting value is [] an empty list.

    0 讨论(0)
  • 2020-12-05 00:47

    I wrote a program to do multi-dimensional flattening using recursion. If anyone has comments on making the program better, you can always see me smiling:

    def flatten(l):
        lf=[]
        li=[]
        ll=[]
        p=0
        for i in l:
            if type(i).__name__=='list':
               li.append(i)
            else:
               lf.append(i)
        ll=[x for i in li for x in i]
        lf.extend(ll)
    
        for i in lf:
            if type(i).__name__ =='list':
               #not completely flattened
               flatten(lf)
            else:
               p=p+1
               continue
    
        if p==len(lf):
           print(lf)
    
    0 讨论(0)
  • 2020-12-05 00:52

    If your list nested is, as you say, "2D" (meaning that you only want to go one level down, and all 1-level-down items of nested are lists), a simple list comprehension:

    flat = [x for sublist in nested for x in sublist]
    

    is the approach I'd recommend -- much more efficient than summing would be (sum is intended for numbers -- it was just too much of a bother to somehow make it block all attempts to "sum" non-numbers... I was the original proposer and first implementer of sum in the Python standard library, so I guess I should know;-).

    If you want to go down "as deep as it takes" (for deeply nested lists), recursion is the simplest way, although by eliminating the recursion you can get higher performance (at the price of higher complication).

    This recipe suggests a recursive solution, a recursion elimination, and other approaches (all instructive, though none as simple as the one-liner I suggested earlier in this answer).

    0 讨论(0)
提交回复
热议问题