# Python program to find common array elements

While considering the multi-dimensional arrays as an example, there is a method that is capable of finding the common elements present within a multi-dimensional array - intersection_update().

This method is used in order to find the common or intersecting elements present within the same array which is multi-dimensional in nature. Let us consider an input output scenario and then proceed with a program.

### Input Output Scenarios

Consider a 2D array which is multi-dimensional in nature.

arr = [[1, 2, 3, 4], [3, 4, 5, 6], [7, 8, 3, 4], [4, 9, 8, 3], [4, 3, 10, 12]]

• The above array consists of 5 sub arrays.

• We can clearly observe that the elements “ 3 ” and “ 4 ” are present all the sub arrays of “ arr ”.

• So, the elements “ 3 ” and “ 4 ” are considered to be the common elements of the 2D array arr.

### Example

In this example, we are going to find the common elements present within a multi dimensional array using the method intersection_update().

• Consider a two dimensional array from which the common elements can be found.

• Declare a parameterized method which can find the common elements taking the 2D array as a parameter.

• Within the method, initiate the set array with 0 and assign the value to a variable.

• Traverse the elements of the array using a loop.

• With the help of the method intersection_update(), find the common elements one after another while traversing.

def common_elements(arr):
result = set(arr[0])
for x in arr[1:]:
result.intersection_update(x)
return list(result)
# main section
if __name__ == "__main__":

arr = [[1, 2, 3, 4], [3, 4, 5, 6], [7, 8, 3, 4], [4, 9, 8, 3], [4, 3, 10, 12]]
res = common_elements(arr)
if len(res) > 0:
print ("The common elements present within the array are: ",res)

else:
print ("There are no common elements present within the array !!")


### Output

The output of the above program is as follows −

The common elements present within the array are:  [3, 4]


## Finding Common Elements in two Different Arrays

The NumPy intersect1d() method can be used to find the common elements of two one-dimensional arrays. This is similar to the intersect_update() method, which deals with multi-dimensional arrays. To better understand this concept, let's look at an example.

### Input Output Scenarios

Consider two arrays which are one dimensional in nature.

arr1 = [1, 2, 3, 4]
arr2 = [3, 4, 5, 6]

• We can clearly see that the elements “ 3 ” and “ 4 ” are present in both arrays arr1 and arr2.

• So, we can conclude that the common elements of the arrays arr1 and arr2 are 3 and 4.

### Example

In the following example, we are going to find the common elements present within multiple one dimensional arrays using the method intersect1d() of the numpy module.

import numpy as n
arr1 = [1, 2, 3, 4]
print("The first array is: ")
print(arr1)
arr2 = [3, 4, 5, 6]
print("The second array is: ")
print(arr2)
narr1 = n.array(arr1)
narr2 = n.array(arr2)
print("The common elements within the given arrays are: ")
print(n.intersect1d(narr1, narr2))


### Output

The output of the above program is as follows −

The first array is:
[1, 2, 3, 4]
The second array is:
[3, 4, 5, 6]
The common elements within the given arrays are:
[3 4]


In this way, depending on the type of arrays, the procedure can be followed. If the array considered is a multi-dimensional array, then the procedure followed in the first program will be followed.

If the arrays considered are one-dimensional arrays, then the procedure followed in the second program will be followed. This is how the common elements of one or more arrays are found.

Updated on: 05-May-2023

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