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.

Sample Solution:-

Python Code:

import numpy as np
x = np.array([0, 1, 2])
y = np.array([2, 1, 0])
print("\nOriginal array1:")
print("\nOriginal array1:")
print("\nCovariance matrix of the said arrays:\n",np.cov(x, y))

Sample Output:

Original array1:
[0 1 2]

Original array1:
[2 1 0]

Covariance matrix of the said arrays:
 [[ 1. -1.]
 [-1.  1.]]

Python Code Editor:

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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))


[2.4, 6.8]