NumPy: Compute the covariance matrix of two given arrays
NumPy Statistics: Exercise-8 with Solution
Write a NumPy program to compute the covariance matrix of two given arrays.
import numpy as np x = np.array([0, 1, 2]) y = np.array([2, 1, 0]) print("\nOriginal array1:") print(x) print("\nOriginal array1:") print(y) print("\nCovariance matrix of the said arrays:\n",np.cov(x, y))
Original array1: [0 1 2] Original array1: [2 1 0] Covariance matrix of the said arrays: [[ 1. -1.] [-1. 1.]]
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Previous: Write a NumPy program to compute the mean, standard deviation, and variance of a given array along the second axis.
Next: Write a NumPy program to compute cross-correlation of two given arrays.
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Python: Tips of the Day
Returns the symmetric difference between two lists, after applying the provided function to each list element of both
def tips_symmetric_difference_by(p, q, fn): _p, _q = set(map(fn, p)), set(map(fn, q)) return [item for item in p if fn(item) not in _q] + [item for item in q if fn(item) not in _p] from math import floor print(tips_symmetric_difference_by([4.2, 2.4], [4.6, 6.8],floor))
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