Count the frequency of a recurring list — inside a list of lists

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野趣味
野趣味 2021-01-19 20:30

I have a list of lists in python and I need to find how many times each sub-list has occurred. Here is a sample,

from collections import Counter
list1 = [[ 1         


        
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  • 2021-01-19 21:13

    Try this

    list1 = [[ 1., 4., 2.5], [ 1., 2.66666667, 1.33333333], 
             [ 1., 2., 2.], [ 1., 2.66666667, 1.33333333], [ 1., 4., 2.5],
             [ 1., 2.66666667, 1.33333333]]
    
    counter = {}
    for el in list1:
        el = str(el)     #This sorts your hashable part or use tuple(el)
        if el in counter:
            counter[el]+=1
        else:
            counter[el]=1
    
    print(counter)
    

    Should output

    {'[1.0, 2.0, 2.0]': 1, '[1.0, 2.66666667, 1.33333333]': 3, '[1.0, 4.0, 2.5]': 2}
    
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  • 2021-01-19 21:14

    Counter returns a dictionary like object which it's keys must be hashable. And since lists are not hashable you can convert them to tuple using map function:

    >>> Counter(map(tuple, list1))
    Counter({(1.0, 2.66666667, 1.33333333): 3, (1.0, 4.0, 2.5): 2, (1.0, 2.0, 2.0): 1})
    

    Note that using map will perform slightly better than a generator expression because by passing a generator expression to Counter() python will get the values from generator function by itself, since using built-in function map has more performance in terms of execution time1.

    # Use generator expression
    ~ $ python -m timeit --setup "list1 = [[ 1., 4., 2.5], [ 1., 2.66666667, 1.33333333],[ 1., 2., 2.], [ 1., 2.66666667, 1.33333333], [ 1., 4., 2.5],[ 1., 2.66666667, 1.33333333]] ;from collections import Counter" "Counter(tuple(x) for x in iter(list1))"
    100000 loops, best of 3: 9.86 usec per loop
    # Use map
    ~ $ python -m timeit --setup "list1 = [[ 1., 4., 2.5], [ 1., 2.66666667, 1.33333333],[ 1., 2., 2.], [ 1., 2.66666667, 1.33333333], [ 1., 4., 2.5],[ 1., 2.66666667, 1.33333333]] ;from collections import Counter" "Counter(map(tuple, list1))"
    100000 loops, best of 3: 7.92 usec per loop
    

    From PEP 0289 -- Generator Expressions:

    The semantics of a generator expression are equivalent to creating an anonymous generator function and calling it. For example:

    g = (x**2 for x in range(10))
    print g.next()
    

    is equivalent to:

    def __gen(exp):
        for x in exp:
            yield x**2
    g = __gen(iter(range(10)))
    print g.next()
    

    Note that since generator expressions are better in terms of memory use, if you are dealing with large data you'd better use generator expression instead of map function.

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  • 2021-01-19 21:16

    Just convert the lists to tuple:

    >>> c = Counter(tuple(x) for x in iter(list1))
    >>> c
    Counter({(1.0, 2.66666667, 1.33333333): 3, (1.0, 4.0, 2.5): 2, (1.0, 2.0, 2.0): 1})
    

    Remember to do the same for lookup:

    >>> c[tuple(list1[0])]
    2
    
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