Python Pandas: Compute the Euclidean distance between two given series
Python Pandas: Data Series Exercise-31 with Solution
Write a Pandas program to compute the Euclidean distance between two given series.
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))
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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Previous: Write a Pandas program to filter words from a given series that contain atleast two vowels.
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
Python: Cache results with decorators
There is a great way to cache functions with decorators in Python. Caching will help save time and precious resources when there is an expensive function at hand.
Implementation is easy, just import lru_cache from functools library and decorate your function using @lru_cache.
from functools import lru_cache @lru_cache(maxsize=None) def fibo(a): if a <= 1: return a else: return fibo(a-1) + fibo(a-2) for i in range(20): print(fibo(i), end="|") print("\n\n", fibo.cache_info())
0|1|1|2|3|5|8|13|21|34|55|89|144|233|377|610|987|1597|2584|4181| CacheInfo(hits=36, misses=20, maxsize=None, currsize=20)
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