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Program 1

Mathematical Operation

1 D Array

import numpy as np

''' Create two 1D NumPy arrays '''
arr1 = np.array([1, 2, 3, 4, 5])
arr2 = np.array([5, 4, 3, 2, 1])

''' Element-wise addition '''
add_result = np.add(arr1, arr2)
print("\nElement-wise addition:", add_result)

''' Element-wise subtraction '''
sub_result = np.subtract(arr1, arr2)
print("\nElement-wise subtraction:", sub_result)

''' Element-wise multiplication '''
mul_result = np.multiply(arr1, arr2)
print("\nElement-wise multiplication:", mul_result)

''' Element-wise division '''
div_result = np.divide(arr1, arr2)
print("\nElement-wise division:", div_result)

''' Element-wise power '''
pow_result = np.power(arr1, arr2)
print("\nElement-wise power:", pow_result)

''' Square root of each element '''
sqrt_result = np.sqrt(arr1)
print("\nSquare root:", sqrt_result)

''' Exponential of each element '''
exp_result = np.exp(arr1)
print("\nExponential:", exp_result)

''' Natural logarithm of each element '''
log_result = np.log(arr1)
print("\nNatural log:", log_result)

''' Logarithm base 10 of each element '''
log10_result = np.log10(arr1)
print("\nLog base 10:", log10_result)

''' Absolute value of each element '''
abs_result = np.abs(np.array([-1, -2, -3, 4, 5]))
print("\nAbsolute values:", abs_result)

''' Trigonometric sine of each element '''
sin_result = np.sin(arr1)
print("\nSine of elements:", sin_result)

''' Trigonometric cosine of each element '''
cos_result = np.cos(arr1)
print("\nCosine of elements:", cos_result)

''' Trigonometric tangent of each element '''
tan_result = np.tan(arr1)
print("\nTangent of elements:", tan_result)

''' Hyperbolic sine of each element '''
sinh_result = np.sinh(arr1)
print("\nHyperbolic sine:", sinh_result)

''' Hyperbolic cosine of each element '''
cosh_result = np.cosh(arr1)
print("\nHyperbolic cosine:", cosh_result)

''' Hyperbolic tangent of each element '''
tanh_result = np.tanh(arr1)
print("\nHyperbolic tangent:", tanh_result)

Output 1

Program 2

Mathematical Operation

1D Array

import numpy as np

''' Create two 1D NumPy arrays '''
arr1 = np.array([1, 2, 3, 4, 5])
arr2 = np.array([5, 4, 3, 2, 1])

''' Floor of each element (round down to nearest integer) '''
arr3 = np.array([1.7, 2.3, 3.9, 4.5])
floor_result = np.floor(arr3)
print("\nFloor of elements:", floor_result)

''' Ceil of each element (round up to nearest integer) '''
ceil_result = np.ceil(arr3)
print("\nCeil of elements:", ceil_result)

''' Round each element to nearest integer '''
round_result = np.round(arr3)
print("\nRounded elements:", round_result)

''' Sum of all elements in the array '''
sum_result = np.sum(arr1)
print("\nSum of elements:", sum_result)

''' Product of all elements in the array '''
prod_result = np.prod(arr1)
print("\nProduct of elements:", prod_result)

''' Cumulative sum of array elements '''
cumsum_result = np.cumsum(arr1)
print("\nCumulative sum of elements:", cumsum_result)

''' Cumulative product of array elements '''
cumprod_result = np.cumprod(arr1)
print("\nCumulative product of elements:", cumprod_result)

''' Mean of all elements '''
mean_result = np.mean(arr1)
print("\nMean of elements:", mean_result)

''' Median of all elements '''
median_result = np.median(arr1)
print("\nMedian of elements:", median_result)

''' Variance of the elements '''
variance_result = np.var(arr1)
print("\nVariance of elements:", variance_result)

''' Standard deviation of the elements '''
std_result = np.std(arr1)
print("\nStandard deviation of elements:", std_result)

''' Maximum value in the array '''
max_result = np.max(arr1)
print("\nMaximum value:", max_result)

''' Minimum value in the array '''
min_result = np.min(arr1)
print("\nMinimum value:", min_result)

''' Dot product of two arrays '''
dot_result = np.dot(arr1, arr2)
print("\nDot product:", dot_result)

''' Modulus (remainder) of element-wise division '''
mod_result = np.mod(arr1, arr2)
print("\nModulus of elements:", mod_result)

''' Greatest common divisor (GCD) of elements '''
gcd_result = np.gcd(arr1, arr2)
print("\nGCD of elements:", gcd_result)

''' Least common multiple (LCM) of elements '''
lcm_result = np.lcm(arr1, arr2)
print("\nLCM of elements:", lcm_result)

''' Clip (limit) the values of the array '''
clipped_result = np.clip(arr1, 2, 4)
print("\nClipped array (values between 2 and 4):", clipped_result)

''' Remainder of division (modulo operation) '''
remainder_result = np.remainder(arr1, arr2)
print("\nRemainder of elements:", remainder_result)

Output 2

Program 3

Mathematical Operation

2D Array

import numpy as np

''' Create two 2D NumPy arrays '''
arr1 = np.array([[1, 2, 3], [4, 5, 6]])
arr2 = np.array([[6, 5, 4], [3, 2, 1]])

''' Element-wise addition '''
add_result = np.add(arr1, arr2)
print("\nElement-wise addition:\n", add_result)

''' Element-wise subtraction '''
sub_result = np.subtract(arr1, arr2)
print("\nElement-wise subtraction:\n", sub_result)

''' Element-wise multiplication '''
mul_result = np.multiply(arr1, arr2)
print("\nElement-wise multiplication:\n", mul_result)

''' Element-wise division '''
div_result = np.divide(arr1, arr2)
print("\nElement-wise division:\n", div_result)

''' Element-wise power '''
pow_result = np.power(arr1, arr2)
print("\nElement-wise power:\n", pow_result)

''' Square root of each element '''
sqrt_result = np.sqrt(arr1)
print("\nSquare root:\n", sqrt_result)

''' Exponential of each element '''
exp_result = np.exp(arr1)
print("\nExponential:\n", exp_result)

''' Natural logarithm of each element '''
log_result = np.log(arr1 + 1)  # Added 1 to avoid log(0)
print("\nNatural log:\n", log_result)

''' Logarithm base 10 of each element '''
log10_result = np.log10(arr1 + 1)  # Added 1 to avoid log10(0)
print("\nLog base 10:\n", log10_result)

''' Absolute value of each element '''
abs_result = np.abs(np.array([[-1, -2, -3], [4, -5, 6]]))
print("\nAbsolute values:\n", abs_result)

''' Trigonometric sine of each element '''
sin_result = np.sin(arr1)
print("\nSine of elements:\n", sin_result)

''' Trigonometric cosine of each element '''
cos_result = np.cos(arr1)
print("\nCosine of elements:\n", cos_result)

''' Trigonometric tangent of each element '''
tan_result = np.tan(arr1)
print("\nTangent of elements:\n", tan_result)

''' Hyperbolic sine of each element '''
sinh_result = np.sinh(arr1)
print("\nHyperbolic sine:\n", sinh_result)

''' Hyperbolic cosine of each element '''
cosh_result = np.cosh(arr1)
print("\nHyperbolic cosine:\n", cosh_result)

''' Hyperbolic tangent of each element '''
tanh_result = np.tanh(arr1)
print("\nHyperbolic tangent:\n", tanh_result)

Output 3

Program 4

Mathematical Operation

2D Array

import numpy as np

''' Create two 2D NumPy arrays '''
arr1 = np.array([[1, 2, 3, 8, 9], [4, 5, 6, 3, 1]])
arr2 = np.array([[6, 5, 4, 3, 2], [3, 2, 1, -1, -4]])

''' Floor of each element (round down to nearest integer) '''
arr3 = np.array([[1.7, 2.3, 3.9, 4.2, 4.9], [4.5, 5.6, 6.1, 7.8, 5.2]])
floor_result = np.floor(arr3)
print("\nFloor of elements:\n", floor_result)

''' Ceil of each element (round up to nearest integer) '''
ceil_result = np.ceil(arr3)
print("\nCeil of elements:\n", ceil_result)

''' Round each element to nearest integer '''
round_result = np.round(arr3)
print("\nRounded elements:\n", round_result)

''' Sum of all elements in the 2D array '''
sum_result = np.sum(arr1)
print("\nSum of elements:", sum_result)

''' Sum along each row '''
sum_along_rows = np.sum(arr1, axis=1)
print("\nSum along rows:", sum_along_rows)

''' Sum along each column '''
sum_along_cols = np.sum(arr1, axis=0)
print("\nSum along columns:", sum_along_cols)

''' Product of all elements in the 2D array '''
prod_result = np.prod(arr1)
print("\nProduct of elements:", prod_result)

''' Cumulative sum of elements '''
cumsum_result = np.cumsum(arr1)
print("\nCumulative sum of elements:", cumsum_result)

''' Mean of all elements in the array '''
mean_result = np.mean(arr1)
print("\nMean of elements:", mean_result)

''' Median of all elements in the array '''
median_result = np.median(arr1)
print("\nMedian of elements:", median_result)

''' Variance of the elements '''
variance_result = np.var(arr1)
print("\nVariance of elements:", variance_result)

''' Standard deviation of the elements '''
std_result = np.std(arr1)
print("\nStandard deviation of elements:", std_result)

''' Maximum value in the 2D array '''
max_result = np.max(arr1)
print("\nMaximum value:", max_result)

''' Minimum value in the 2D array '''
min_result = np.min(arr1)
print("\nMinimum value:", min_result)

''' Maximum value along each row '''
max_along_rows = np.max(arr1, axis=1)
print("\nMaximum value along rows:", max_along_rows)

''' Maximum value along each column '''
max_along_cols = np.max(arr1, axis=0)
print("\nMaximum value along columns:", max_along_cols)

''' Dot product of two 2D arrays (matrix multiplication) '''
dot_result = np.dot(arr1, arr2.T)
print("\nDot product (matrix multiplication):\n", dot_result)

''' Modulus (remainder) of element-wise division '''
mod_result = np.mod(arr1, arr2)
print("\nModulus of elements:\n", mod_result)

''' Greatest common divisor (GCD) of elements '''
gcd_result = np.gcd(arr1, arr2)
print("\nGCD of elements:\n", gcd_result)

''' Least common multiple (LCM) of elements '''
lcm_result = np.lcm(arr1, arr2)
print("\nLCM of elements:\n", lcm_result)

''' Clip (limit) the values of the array '''
clipped_result = np.clip(arr1, 2, 4)
print("\nClipped array (values between 2 and 4):\n", clipped_result)

''' Flatten the 2D array into a 1D array '''
flatten_result = arr1.flatten()
print("\nFlattened array:", flatten_result)

Output 4

Introduction to Numpy

Mathematical Operation

Mathematical Operation

Mathematical Operation

Mathematical Operation