NumPy Set Operations
What is a Set
A set in mathematics is a collection of unique elements.
Sets are used for operations involving frequent intersection, union and difference operations.
Create Sets in NumPy
We can use NumPy'sunique() method to find unique elements from any array.E.g. create a set array, but remember that the set arrays should only be 1-D arrays.
Example
Convert following array with repeated elements to a set:
arr = np.array([1, 1, 1, 2, 3, 4, 5, 5, 6, 7])
x = np.unique(arr)
print(x)
Finding Union
To find the unique values of two arrays, use theunion1d() method.
Example
Find union of the following two set arrays:
arr1 = np.array([1, 2, 3, 4])
arr2 = np.array([3, 4, 5, 6])
newarr = np.union1d(arr1, arr2)
print(newarr)
Finding Intersection
To find only the values that are present in both arrays, use theintersect1d() method.
Example
Find intersection of the following two set arrays:
arr1 = np.array([1, 2, 3, 4])
arr2 = np.array([3, 4, 5, 6])
newarr = np.intersect1d(arr1, arr2, assume_unique=True)
print(newarr)
Note: theintersect1d() method takes an optional argumentassume_unique, which if set to True can speed up computation. It should always be set to True when dealing with sets.
Finding Difference
To find only the values in the first set that is NOT present in the seconds set, use thesetdiff1d() method.
Example
Find the difference of the set1 from set2:
set1 = np.array([1, 2, 3, 4])
set2 = np.array([3, 4, 5, 6])
newarr = np.setdiff1d(set1, set2, assume_unique=True)
print(newarr)
Note: thesetdiff1d() method takes an optional argumentassume_unique, which if set to True can speed up computation. It should always be set to True when dealing with sets.
Finding Symmetric Difference
To find only the values that are NOT present in BOTH sets, use thesetxor1d() method.
Example
Find the symmetric difference of the set1 and set2:
set1 = np.array([1, 2, 3, 4])
set2 = np.array([3, 4, 5, 6])
newarr = np.setxor1d(set1, set2, assume_unique=True)
print(newarr)
Note: thesetxor1d() method takes an optional argumentassume_unique, which if set to True can speed up computation. It should always be set to True when dealing with sets.
