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Computers are mostly used to store information and extract information from it. Python is one of the most powerful programming languages. We can use Python to get computers to do most of the routine processes. This blog is all about how we can calculate Euclidean distance in Python.
How Can You Calculate Euclidean distance in Python?
In Python, utilize numpy.sqrt() to calculate Euclidean distance. In Python, you can measure Euclidean distance utilizing numpy.sqrt(). It’s very simple to use. Let us take a look at an example of this:
import numpy as np
arr1 = np.array((7,8,9))
arr2 = np.array((4, 5, 6))
temp = arr1-arr2
dist = np.sqrt(np.dot(temp.T, temp))
print(dist)
Result:
5.196152422706632
In Python, utilize math.dist() to calculate Euclidean distance. In Python, you can also measure Euclidean distance utilizing math.dist(). It’s very simple to use. Let us take a look at an example of this:
from math import dist
arr1 = (7,8,9)
arr2 = (4, 5, 6)
print(dist(arr1,arr2))
Result:
5.196152422706632
1) Utilize numpy.sqrt()
In Python, you can measure Euclidean distance utilizing numpy.sqrt(). It’s very simple to use. Let us take a look at an example of this:
import numpy as np
arr1 = np.array((7,8,9))
arr2 = np.array((4, 5, 6))
temp = arr1-arr2
dist = np.sqrt(np.dot(temp.T, temp))
print(dist)
Result:
5.196152422706632
2) Utilize math.dist()
In Python, you can also measure Euclidean distance utilizing math.dist(). It’s very simple to use. Let us take a look at an example of this:
from math import dist
arr1 = (7,8,9)
arr2 = (4, 5, 6)
print(dist(arr1,arr2))
Result:
5.196152422706632
3) Utilize numpy.sum()
In Python, you can measure Euclidean distance utilizing numpy.sqrt(). It’s very simple to use.
Let read more here https://ittutoria.net/how-to-calculate-euclidean-distance-in-python/
Conclusion
Calculating Euclidean distance in Python is a confusing problem. We hope this blog has helped clear the air around how to do it. If you have more questions about this topic, please leave a comment below. Thank you for reading; we are always excited when one of our posts can provide useful information on a topic like this!
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