Array operations in NumPy – Aggregate and Advanced Operations:

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               Arrays in numpy has variety of operations like element-wise arithmetic, Scalar Operations, Aggregate and advanced functions. The basic operations are already discussed. Now,we discuss about the aggregate and advanced functions.

Python Numpy Code for Aggregate and Advanced Operations:

              This code starts from importing Numpy library. First,create two arrays with elements. Next,Aggregate functions like sum of all elements,Mean value,max and min values are calculated with built-in functions.

Advanced functions like Dot product,square root and exponential are also calculated with built-in function.

Code:

 import numpy as np

# Let us Create two arrays

s_arr1 = np.array([1, 3, 5, 7])

s_arr2 = np.array([2, 4, 6, 8])

#Aggregate functions

print("Sum:", np.sum(s_arr1))                  

print("Mean:", np.mean(s_arr1))                

print("Max:", np.max(s_arr2))                  

print("Min:", np.min(s_arr2))                  

# Advanced operations

print("Dot product:", np.dot(s_arr1, s_arr2))    

print("Square root:", np.sqrt(s_arr1))         

print("Exponential:", np.exp(s_arr2))          

Output:

Sum: 16

Mean: 4.0

Max: 8

Min: 2

Dot product: 100

Square root: [1.         1.73205081 2.23606798 2.64575131]

Exponential: [   7.3890561    54.59815003  403.42879349 2980.95798704]

Broadcasting arrays:

              This method is used to add 1D array with 2D arrays. Here, is the sample code.

Code:

import numpy as np1

#2D array (matrix) creation

A = np1.array([[1, 2, 1],

              [4, 5, 3]])

#1D array (vector) creation

b = np1.array([11, 20, 15])

# Broadcasting addition

C_add = np1.add(A, b)

print("Broadcasted Addition:\n", C_add)

# Broadcasting multiplication

C_mul = np1.multiply(A, b)

print("Broadcasted Multiplication:\n", C_mul)

Output:

Broadcasted Addition:

 [[12 22 16]

 [15 25 18]]

Broadcasted Multiplication:

 [[ 11  40  15]

 [ 44 100  45]]

These are the ways to implement advanced functions and aggregate functions in Python using Numpy. Hope, you understood the concept. Keep Coding!!!

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