Fastest way to count number of occurrences in a Python list

Question

I have a Python list and I want to know what s the quickest way to count the number of occurrences of the item   1  in this list  In my actual case  the item can occur tens of thousands of times which is why I want a fast way     1    1    1    1    1    1    2    2    2    2    7    7    7    10    10     Which approach   count or collections Counter is likely more optimized

User · Answer

You can convert list in string with elements seperated by space and split it based on number/char to be searched..

Will be clean and fast for large list..

>>>L = [2,1,1,2,1,3]
>>>strL = " ".join(str(x) for x in L)
>>>strL
2 1 1 2 1 3
>>>count=len(strL.split(" 1"))-1
>>>count
3

User · Answer

By the use of Counter dictionary counting the occurrences of all element as well as most common element in python list with its occurrence value in most efficient way   If our python list is -  l   1    1    1    1    1    1    2    2    2    2    7    7    7    10    10     To find occurrence of every items in the python list use following -    gt  gt from collections import Counter    gt  gt c Counter l     gt  gt print c  Counter   1   6   2   4   7   3   10   2     To find most highest occurrence of items in the python list -    gt  gt k c most common      gt  gt k     1   6     2   4     7   3     10   2     For Highest one -    gt  gt k 0  1   6   For the item just use k 0  0     gt  gt k 0  0    1    For nth highest item and its no of occurrence in the list use follow -    for n 2       gt  gt print k n-1  0    For item  2    gt  gt print k n-1  1    For value  4

User · Answer

You can use pandas  by transforming the list to a pd Series then simply use  value counts    import pandas as pd a     1    1    1    1    1    1    2    2    2    2    7    7    7    10    10   a cnts   pd Series a  value counts   to dict    Input   gt  gt  a cnts  1    a cnts  10   Output  gt  gt   6  2

User · Answer

a     1    1    1    1    1    1    2    2    2    2    7    7    7    10    10   print a count  1     It s probably optimized heavily at the C level   Edit  I randomly generated a large list    In  8   len a  Out 8   6339347  In  9    timeit a count  1   10 loops  best of 3  86 4 ms per loop   Edit edit  This could be done with collections Counter   a   Counter your list  print a  1     Using the same list in my last timing example  In  17    timeit Counter a   1   1 loops  best of 3  1 52 s per loop   My timing is simplistic and conditional on many different factors  but it gives you a good clue as to performance   Here is some profiling  In  24   profile run  a count  1              3 function calls in 0 091 seconds     Ordered by  standard name     ncalls  tottime  percall  cumtime  percall filename lineno function          1    0 000    0 000    0 091    0 091  lt string gt  1  lt module gt           1    0 091    0 091    0 091    0 091  method  count  of  list  objects           1    0 000    0 000    0 000    0 000  method  disable  of   lsprof Prof iler  objects     In  25   profile run  b   Counter a   b  1              6339356 function calls in 2 143 seconds     Ordered by  standard name     ncalls  tottime  percall  cumtime  percall filename lineno function          1    0 000    0 000    2 143    2 143  lt string gt  1  lt module gt           2    0 000    0 000    0 000    0 000  weakrefset py 68   contains            1    0 000    0 000    0 000    0 000 abc py 128   instancecheck            1    0 000    0 000    2 143    2 143 collections py 407   init            1    1 788    1 788    2 143    2 143 collections py 470 update          1    0 000    0 000    0 000    0 000  getattr          1    0 000    0 000    0 000    0 000  isinstance          1    0 000    0 000    0 000    0 000  method  disable  of   lsprof Prof iler  objects    6339347    0 356    0 000    0 356    0 000  method  get  of  dict  objects

User · Answer

Combination of lambda and map function can also do the job   list      a    b    b    c   sum map lambda x  x   b   list     2

[python] Fastest way to count number of occurrences in a Python list

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