Ass2.py

# Question 1
def create_and_read_file():
    
    with open("example.txt", "w") as file:
        file.write("This is a sample text.\nIt contains multiple lines for testing purposes.\n")
    
    
    with open("example.txt", "r") as file:
        content = file.read()
    print("Content of 'example.txt':\n", content)

# Question 2
def read_specified_characters():
   
    with open("sample.txt", "w") as file:
        file.write("This is a test file for reading specific characters.\n")

    
    num_chars = int(input("Enter the number of characters to read: "))
    
    
    with open("sample.txt", "r") as file:
        content = file.read(num_chars)
    print("First {num_chars} characters of 'sample.txt':\n", content)

# Question 3
def append_and_read_file():
    
    with open("sample.txt", "a") as file:
        file.write("This is an appended line.\n")
    
    
    with open("sample.txt", "r") as file:
        content = file.read()
    print("Updated content of 'sample.txt':\n", content)

# Question 4
def count_lines_not_starting_with_t():
    
    count = 0
    with open("text.txt", "r") as file:
        for line in file:
            if not line.lstrip().startswith("T"):
                count += 1
    print(f"Number of lines not starting with 'T': {count}")

# Question 5
def copy_file_content():
    
    with open("source.txt", "r") as source_file:
        content = source_file.read()

    
    with open("destination.txt", "w") as dest_file:
        dest_file.write(content)

    print("Content copied to 'destination.txt' successfully.")

import numpy as np

# Question 6
def transpose_and_flatten_matrix():
    
    rows = int(input("Enter the number of rows: "))
    cols = int(input("Enter the number of columns: "))
    print("Enter the matrix elements row by row (space-separated):")
    matrix = []
    for i in range(rows):
        for j in range(cols):
            matrix[i][j]=int(input("Enter the matrix element"))
    matrix = np.array(matrix)

    
    print("Transpose of the matrix:\n", matrix.T)

    
    print("Flattened version of the matrix:\n", matrix.flatten())

# Question 7
def array_properties():
    
    array = np.array([[10, 16, 71, 9], [71, 91, 31, 51]])

    
    print("Dimension of the array:", array.ndim)
    print("Shape of the array:", array.shape)
    print("Size (total elements) of the array:", array.size)

# Question 8
def random_array_operations():
   
    array1 = np.random.randint(1, 10, (3, 3))
    array2 = np.random.randint(1, 10, (3, 3))
    print("Array 1:\n", array1)
    print("Array 2:\n", array2)

   
    concatenated = np.concatenate((array1, array2), axis=0)
    print("Concatenated array:\n", concatenated)

    
    print("Sorted Array 1:\n", np.sort(array1))
    print("Sorted Array 2:\n", np.sort(array2))

    
    print("Element-wise addition:\n", array1 + array2)
    print("Element-wise subtraction:\n", array1 - array2)
    print("Element-wise multiplication:\n", array1 * array2)
    print("Element-wise division:\n", np.divide(array1, array2, where=array2 != 0))

# Question 9
def matrix_min_max():
    
    matrix = np.random.randint(1, 100, (8, 7))
    print("Random matrix (8x7):\n", matrix)

    
    max_values = matrix.max(axis=0)
    min_values = matrix.min(axis=0)
    print("Maximum values in each column:\n", max_values)
    print("Minimum values in each column:\n", min_values)

# Question 10
def numpy_tasks():
    
    matrix = np.arange(1, 21).reshape(4, 5)
    print("4x5 matrix:\n", matrix)

    
    zeros = np.zeros(10)
    ones = np.ones(10,1)
    fives = np.full(10, 5)
    print("Array of 10 zeros:", zeros)
    print("Array of 10 ones:", ones)
    print("Array of 10 fives:", fives)

   
    even_numbers = np.arange(10, 51, 2)
    print("Even integers from 10 to 50:\n", even_numbers)

    
    random_number = np.random.rand()
    print("Random number between 0 and 1:", random_number)

    
    np.savetxt("matrix.txt", matrix, fmt="%d")
    loaded_matrix = np.loadtxt("matrix.txt", dtype=int)
    print("Matrix loaded from 'matrix.txt':\n", loaded_matrix)