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To count the duplicates in an array:Copied! const arr = ['one', 'two', 'one', 'one', 'two', 'three']; const count = {}; arr. forEach(element => { count[element] = (count[element] || 0) + 1; }); // 👇️ {one: 3, two: 2, three: 1} console.
Method3 : Using collections. from collections import Counter MyList = ["a", "b", "a", "c", "c", "a", "c"] duplicate_dict = Counter(MyList) print(duplicate_dict)#to get occurence of each of the element. print(duplicate_dict['a'])# to get occurence of specific element.
The method len() returns the number of elements in the list.
Syntax:
len(myArray)
Eg:
myArray = [1, 2, 3]
len(myArray)
Output:
3
len is a built-in function that calls the given container object's __len__ member function to get the number of elements in the object.
Functions encased with double underscores are usually "special methods" implementing one of the standard interfaces in Python (container, number, etc). Special methods are used via syntactic sugar (object creation, container indexing and slicing, attribute access, built-in functions, etc.).
Using obj.__len__() wouldn't be the correct way of using the special method, but I don't see why the others were modded down so much.
If you have a multi-dimensional array, len() might not give you the value you are looking for. For instance:
import numpy as np
a = np.arange(10).reshape(2, 5)
print len(a) == 2
This code block will return true, telling you the size of the array is 2. However, there are in fact 10 elements in this 2D array. In the case of multi-dimensional arrays, len() gives you the length of the first dimension of the array i.e.
import numpy as np
len(a) == np.shape(a)[0]
To get the number of elements in a multi-dimensional array of arbitrary shape:
import numpy as np
size = 1
for dim in np.shape(a): size *= dim
Or,
myArray.__len__()
if you want to be oopy; "len(myArray)" is a lot easier to type! :)
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