In This Article, You Will Learn About Python Numpy Set.
Python Numpy Set – Before moving ahead, let’s know a bit of Python Numpy Hyperbolic Functions
Table of Contents
Set
Set – It is collection of unordered and unindexed elements.
Sets are used on its method, difference(), intersection(), and isdisjoint() etc.
Create Sets in NumPy
To create a set from unique elements in Numpy, use Numpy’s unique() method.
Note: Use only 1d array.
Example – Create a set from unique elements of an array.
import numpy as np
array = np.array([11, 12, 12, 13, 13, 13, 15])
x = np.unique(array)
print(x)
Output -
[11 12 13 15]
As shown above, it returned a set of unique elements.
Finding Union
To create a set from the set of two arrays of unique elements in Numpy, use Numpy’s union1d() method.
Example – Create a set from unique elements of an array.
import numpy as np
array_1 = np.array([1, 2, 3, 4, 4, 4, 5])
array_2 = np.array([6, 6, 7, 8, 8, 9])
array_set = np.union1d(array_1, array_2)
print(array_set)
Output -
[1 2 3 4 5 6 7 8 9]
As a result, it returned a set of unique elements.
Finding Intersection
To create a set from common elements presented in both arrays, use intersect1d() method.
Example – Create a set from common elements of both arrays.
import numpy as np
array_1 = np.array([1, 1, 2, 3, 5])
array_2 = np.array([2, 5, 7, 1, 1])
array_set = np.intersect1d(array_1, array_2, assume_unique=True)
print(array_set)
Output -
[1 2]
As shown above, it returned a set of common unique elements.
Finding Difference
To create a set from elements presented only in an array first, not in array second, use setdiff1d() method.
Example – Create a set from elements presented in only first array.
import numpy as np
array_1 = np.array([1, 0, 2, 3, 5])
array_2 = np.array([4, 2, 3, 5, 6])
array_set = np.setdiff1d(array_1, array_2, assume_unique=True)
print(array_set)
Output -
[1 0]
As shown above, it returned a set of unique elements of first array.
Example – Create a set from elements presented in only second array.
import numpy as np
array_1 = np.array([1, 0, 2, 3, 5])
array_2 = np.array([4, 2, 8, 5, 8])
array_set = np.setdiff1d(array_2, array_1, assume_unique=True)
print(array_set)
As can be seen, it returned a set of unique elements of second array.
Finding Boolean Value
To create a set of Boolean values based on elements that are presented both arrays, use in1d() method.
import numpy as np
array_1 = np.array([1, 0, 2, 3, 5])
array_2 = np.array([4, 2, 6, 5, 6])
array_set = np.in1d(array_1, array_2, assume_unique=True)
print(array_set)
Output -
[False False True False True]
As shown above, it returned a set of Boolean values based on unique elements.
Finding Symmetric Difference
To create a set from elements that are not presented in both array, use setxor1d() method.
Example – Create a set from elements not presented in both array.
import numpy as np
array_1 = np.array([1, 0, 2])
array_2 = np.array([4, 2, 3])
array_set = np.setxor1d(array_1, array_2, assume_unique=True)
print(array_set)
Output -
[0 1 4 3]
As has been noted, it returned a set of unique elements that are not presented in both sets.
If you find anything incorrect in the above-discussed topic and have any further questions, please comment below.
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