如何将列表中的元素类型存储在 Python 的字典中？

Question

How can I store the types of elements from a list in a dictionary? for example to make the output like this:

datatype_statistic([1,'2',3.5, 0.5, None, (1,1)]) = {
        'int': 1,
        'str': 1,
        'float': 2,
        'None'：1,
        'tuple': 1
    }

This is what I did till now but I just do not know what is the method that I should apply to acheive the above:

def datatype_statistic(ls):
     my_list=len(ls)
     print("There are "+str(my_list)+" elements in this list" )
     for item in ls:
        print(type(item))
datatype_statistic([1,'2',3.5, 0.5, None, (1,1)]) 

Answer 1

You can use collections.defaultdict :

from collections import defaultdict

def datatypes(lst):
    ret = defaultdict(int)
    for x in lst:
        ret[type(x).__name__] += 1
    return dict(ret)

print(datatypes([1, '2', 3.5, 0.5, None, (1, 1)]))

Or, without imports:

def datatypes(lst):
    ret = {}
    for x in lst:
        ret[type(x).__name__] = ret.get(type(x).__name__, 0) + 1
    return ret

print(datatypes([1, '2', 3.5, 0.5, None, (1, 1)]))

Output: {'int': 1, 'str': 1, 'float': 2, 'NoneType': 1, 'tuple': 1}

Answer 2

collections.Counter is specifically made for this kind of task:

from collections import Counter

ls = [1,'2',3.5, 0.5, None, (1,1)]

def datatype_statistic(ls):
    type_names = [type(elem).__name__ for elem in ls]
    return dict(Counter(type_names))

print(datatype_statistic(ls))

Output:

{'int': 1, 'str': 1, 'float': 2, 'NoneType': 1, 'tuple': 1}

I first use a list comprehension to get the type names from the list elements. Then I just apply the Counter . Finally I cast to dict to get the output in the requested form.

Side notes

Note that the calls to .__name__ and dict() are only there to shoe-horn the result to fit the example given for a desired result. You need to know yourself if you actually need them.

The type of None is NoneType , so that's what I print. You can special-case this if needed.

Answer 3

jake_list = [1, '2', 3.5, 0.5, None, (1, 1)]
datatype_statistic = dict()

for i in jake_list:
    tmp_type = type(i).__name__
    datatype_statistic[tmp_type] = datatype_statistic.get(tmp_type, 0) + 1

# {'int': 1, 'str': 1, 'float': 2, 'NoneType': 1, 'tuple': 1}

Answer 4

You would have to employ some form of counter to solve this, which you have not used in your code.

def type_counter_list(list_1):
    count_type = dict()
    for _ in list_1:
        x = type(_)
    if _ in count_type.keys():
        count_type[x]+=1
    else:
        count_type[x]=1
    return count_type

This is not a code, but I guess you are a beginner. This is a blueprint for you to develop your code on.

Answer 5

You can achieve this by using some built-in methods in Python such as map , list.count , and type

This is the solution for me:

your_list = [1,'2',3.5, 0.5, None, (1,1)]
x = list(map(lambda j: type(j), your_list))
types_dict = {i.__name__:x.count(i) for i in x} # A dict comprehension
# types_dict value sould be: {'int': 1, 'str': 1, 'float': 2, 'NoneType': 1, 'tuple': 1}