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              Transpose means changing column into rows and rows into columns. It can be implemented in python with or without Numpy. There are three methods to implement as follows. ·        Using Numpy ·        Using Zip ·        Manual Loops Using Numpy:               Numpy is predefined. It has many built-in functions. Pyhon code: import numpy as np1 # Step 1: create a 4X4 matrix X = np1.array([[1, 2, 3, 6],               [4, 5, 6, 10],               [7, 8, 9, 2],               [3, 6, 4, 8]]) # Step 2: Transpose the matrix X X_T = X.T print("The Original Matrix:\n", X) print("Here is the Transposed Matrix:\n", X_T) Output: The Original Matrix:  [[ 1...

             Identify Matrix has the rows and columns in equal manner. It has ones on the diagonal and zeros in other places. This can be done two different ways as follows… ·        Using Numpy ·        Using Plain Python Code 1.Using Numpy:               This method uses the ‘Numpy’ to create object and calling built-in functions. Implementation: ·        It uses Numpy built-in file and creates the object. It calls the ‘identity()’ function to build the identity matrix. ·        Finally,prints the identity matrix. Code: #Using Numpy import numpy as np1 # Create a 4x4 identity matrix I = np1.identity(4) print("Here is the Identity Matrix using Numpy:") print(I) Output: Here is the Identity Matrix using Numpy: [[1. 0. 0. 0.]  [0...

              Mathematical operations on array uses matrices. It uses Numpy to perform element-wise arithmetic, aggregate functions and linear algebra functions in effective ways. ·        This program starts with including numpy object. ·        Create two arrays for input purpose. ·        Next,element wise operations like Addition, Subtraction ,Multiplication and Division. ·        A scalar function is done by multiplying the array elements with 5. ·        Aggregate functions like sum, min, max and mean are done using built-in functions. ·        The advanced functions like square root and exponential are also done. Python Code: import numpy as np # Create arrays s_arr1 = np.array([1, 2, 3, 4]) s_arr2 = np.array([10, 20, 30, 40]) print("The origina...

               You have created an array. you want to reshape the array without altering data, this is method for you. Here, built-in method reshape() is used in Numpy. Let us do this for 1D and 2D array. Reshaping a 1D array into 2D array:               This code starts from importing numpy and its object. A single dimensional array is created with elements. The array is reshaped with 3 rows and 2 columns by the use of reshape() function. Original array and reshaped array is printed as output. Python Code: import numpy as np1 # Create a 1D array with elements s_arr = np1.array([11, 22, 33, 44, 55, 66]) # Let us Reshape into 3 rows and 2 columns reshaped_arr = s_arr.reshape(3, 2) print("Original array:", s_arr) print("Reshaped array:\n", reshaped_arr) Output: This is the output for the above program Original array: [11 22 33 44 55 66] Reshaped array:...

               Array is a collection of similar data elements. It may be a single dimensional, two dimensional or more.. Let us create an array of elements and read inputs from the user. For this purpose, let us use the built-in functions like input(), split() and map(). Based on the data type, you can use these functions. Numpy directly converts the list into array. Python Program to read inputs from the user for 1D array:               1D array has a set of elements arranged in sequential manner. Let us create and read the input. Code: import numpy as np1 # Read the number of elements no = int(input("Enter the number of elements: ")) # Read the array of elements s_arr = list(map(int, input(f"Enter {no} numbers separated by space: ").split())) # Let us Convert to NumPy array s_arr = np1.array(s_arr) print("Array:", s_arr) Output: Enter the number of ele...

          This program adds the elements from beginning to end. It can be done by built-in functions or using loop. Let us discuss many methods as follows… 1D array elements: The methods are ·        Using built-in method sum () ·        Using loops ·        Using numpy Using built-in method sum (): #create an array of elements n_array = [100, 200, 300, 400, 500] #find the total from the sum() a_total = sum(n_array) #print the sum print("Sum of the elements in the array:", a_total) Output: Sum of the elements in the array: 1500 Using loops: #Array creation n_array = [11, 22, 33, 44, 55] a_total = 0 #using a for loop to find the sum for no in n_array:     a_total += no #Print the sum print("Sum of the elements are:", a_total) Output: Sum of the elements are: 165 Using Numpy:      ...

              2D array has rows and columns. The data is stored in row wise. Let us create a 2D array as follows. Python code to create a 2D array of elements: #import the built-in file numpy and develop an object np1 import numpy as np1 # Create a 2D array of elements with 2 rows and 2 columns arr_2d = np1.arange(1, 5).reshape(2, 2) #print the elements print("2D Array elements are:\n", arr_2d) here, is the output. 2D Array elements are:   [[1 2]   [3 4]] If you want to change the rows and columns to 3. Use the below code… arr_2d = np1.arange(1, 10).reshape(3, 3) It gives you the output as follows. 2D Array elements are:   [[1 2 3]   [4 5 6]   [7 8 9]] If you want to print 4 rows and columns. Let this code helps… arr_2d = np1.arange(1, 17).reshape(4, 4) The output is   2D Array elements are:   [[ 1   2   3   4]   [ 5   6   7   8] ...

               1D(single Dimensional) array is a collection of similar elements. Let us create a 1D array of elements in python as follows…. Creation of 1D array from 1 to 20: This program starts from import the built-in file “numpy” and create an object for numpy as np. Create an array as s_arr. Using the function “arange()” to assign the size. Here, we set the range as 20 members. Finally, print the array elements using print() function. Python Code: import numpy as np # Create a 1D(single dimensional) array from 1 to 20 s_arr = np.arange(1, 21) print("Here is the 1D Array:\n", s_arr) Output: Here is the 1D Array:   [ 1   2   3   4   5   6   7   8   9 10 11 12 13 14 15 16 17 18 19 20] Print Even numbers in the array:               This program imports the numpy, the built-in file. It creates the object for n...

              An array is a basic data structure that can be implemented easily. The data is stored is of same data type. Let us implement the array in python. It can be done by three ways listed as follows…. ·        Using array module ·        Using Lists ·        Using NumPy arrays Let us create the coding samples in python. Using ‘array’ module:   This method is useful for homogeneous data. It is memory-efficient and easy to implement. ·        First import the array module. ·        An integer array   is created with elements. ·        Using ‘append’ function, add the data. ·        Using ‘remove’ function, you can able to delete the data. ·        Finally,display the data in the array....