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Pandas Data Series: Compute the Euclidean distance between two given series

 

Pandas: Data Series Exercise-31 with Solution

Write a Pandas program to compute the Euclidean distance between two given series.

Euclidean distance
From Wikipedia, In mathematics, the Euclidean distance or Euclidean metric is the "ordinary" straight-line distance between two points in Euclidean space. With this distance, Euclidean space becomes a metric space. The associated norm is called the Euclidean norm.

Sample Solution :

Python Code :

import pandas as pd
import numpy as np
x = pd.Series([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
y = pd.Series([11, 8, 7, 5, 6, 5, 3, 4, 7, 1])
print("Original series:")
print(x)
print(y)
print("\nEuclidean distance between two said series:")
print(np.linalg.norm(x-y))

Sample Output:

Original series:
0     1
1     2
2     3
3     4
4     5
5     6
6     7
7     8
8     9
9    10
dtype: int64
0    11
1     8
2     7
3     5
4     6
5     5
6     3
7     4
8     7
9     1
dtype: int64

Euclidean distance between two said series:
16.492422502470642

Python Code Editor:


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Next: Write a Pandas program to find the positions of the values neighboured by smaller values on both sides in a given series.

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Python: Tips of the Day

Function argument unpacking in Python.

Example:

def tips_func(x, y, z):
  print(x, y, z)
  
tuple_val = (2, 0, 2)
dict_val = {'x': 3, 'y': 2, 'z': 1}
tips_func(*tuple_val)
tips_func(**dict_val)

Output:

2 0 2
3 2 1