Based on NumPy
Q1: Questions on Basic NumPy Array
(a) Reverse the NumPy array: arr = np.array([1, 2, 3, 6, 4, 5])
(b) Flatten the NumPy arr: array1 = np.array([[1, 2, 3], [2, 4, 5], [1, 2, 3]]) using any two NumPy in-built methods
(c) Compare the following numpy arrays:
arr1 = np.array([[1, 2], [3, 4]]) arr2 = np.array([[1, 2], [3, 4]])
(d) Find the most frequent value and their indice(s) in the following arrays:
i. x = np.array([1,2,3,4,5,1,2,1,1,1])
ii. y = np.array([1, 1, 1, 2, 3, 4, 2, 4, 3, 3, ])
(e) For the array gfg = np.matrix('[4, 1, 9; 12, 3, 1; 4, 5, 6]'), find
i. Sum of all elements
ii. Sum of all elements row-wise
iii. Sum of all elements column-wise
(f) For the matrix: n_array = np.array([[55, 25, 15],[30, 44, 2],[11, 45, 77]]), find
i. Sum of diagonal elements
ii. Eigen values of matrix
iii. Eigen vectors of matrix iv. Inverse of matrix
v. Determinant of matrix
(g) Multiply the following matrices and also find covariance between matrices using NumPy: i. p = [[1, 2], [2, 3]] q = [[4, 5], [6, 7]]
ii. p = [[1, 2], [2, 3], [4, 5]] q = [[4, 5, 1], [6, 7, 2]]
(h) For the matrices: x = np.array([[2, 3, 4], [3, 2, 9]]); y = np.array([[1, 5, 0], [5, 10, 3]]), find inner, outer and cartesian product?
Q2: Based on NumPy Mathematics and Statistics
(a) For the array: array = np.array([[1, -2, 3],[-4, 5, -6]])
i. Find element-wise absolute value
ii. Find the 25th, 50th, and 75th percentile of flattened array, for each column, for each row. iii. Mean, Median and Standard Deviation of flattened array, of each column, and each row
(b) For the array: a = np.array([-1.8, -1.6, -0.5, 0.5,1.6, 1.8, 3.0]). Find floor, ceiling and truncated value, rounded values
Q3: Based on Searching and Sorting
(a) For the array: array = np.array([10, 52, 62, 16, 16, 54, 453]), find
i. Sorted array
ii. Indices of sorted array
iii. 4 smallest elements
iv. 5 largest elements
(b) For the array: array = np.array([1.0, 1.2, 2.2, 2.0, 3.0, 2.0]), find
i. Integer elements only
ii. Float elements only
Q4:
(a) Write a function named img_to_array(path) that reads an image from a specified path and save it as text file on local machine? (Note: use separate cases for RGB and Grey Scale images)
(b) Load the saved file into jupyter notebook?
