Consider the following python methods, available in naive python, or numpy library: C-1. len() C-2. str.replace()...

  

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Consider the following python methods, available in naive python, or numpy library: C-1. len() C-2. str.replace() C-3. str.join() C-4. np.random.randint() C-5. np.random.rand() C-6. np.sort() C-7. np.argsort() C-8. array.copy( C-9. array.reshape() C-10. np.argmin() Answer the following questions for each of the above methods: State the purpose/usage of the method. List all the arguments of the method. Classify the arguments as positional or keyword arguments. Write the default values for each of the keyword arguments. Answer the following questions: D-1. Create a random integer numpy nd-array of size 5x8, where the integer values range from 10 to 90. Set the random generator seed to be 211. Call the nd-array as M. D-2. Subtract 5 from all the elements of M. D-3. Subtract 5 from all the third-row elements of M. D-4. Subtract 5 from all the fifth column elements of M. D-5. Divide all the row 2 and 3 elements of M with 10. D-6. Create a copy of M, as M1. In M1, update each element as follows: if the element's value is <50, then update it to 0; otherwise, update the value to 100. Print both arrays (M and MI). D-7. Split M into two nd-arrays of size 3x8 and 2x8. D-8. Create a list of 8 random integers whose value ranges from 1 to 5. Append (attach) the list as the sixth row to M. D-9. Create a list of 5 random integers whose value ranges from 1 to 5. Append (attach) the list as the ninth column to M. D-10. Execute the following cells, and explain your observations: list1 = [1,2,3,4] print((lambda x: x * 3 )(list1)) array1 = np.array([1,2,3,4]) print((lambda x: x * 3 )(array1)) Consider the following python methods, available in naive python, or numpy library: C-1. len() C-2. str.replace() C-3. str.join() C-4. np.random.randint() C-5. np.random.rand() C-6. np.sort() C-7. np.argsort() C-8. array.copy( C-9. array.reshape() C-10. np.argmin() Answer the following questions for each of the above methods: State the purpose/usage of the method. List all the arguments of the method. Classify the arguments as positional or keyword arguments. Write the default values for each of the keyword arguments. Answer the following questions: D-1. Create a random integer numpy nd-array of size 5x8, where the integer values range from 10 to 90. Set the random generator seed to be 211. Call the nd-array as M. D-2. Subtract 5 from all the elements of M. D-3. Subtract 5 from all the third-row elements of M. D-4. Subtract 5 from all the fifth column elements of M. D-5. Divide all the row 2 and 3 elements of M with 10. D-6. Create a copy of M, as M1. In M1, update each element as follows: if the element's value is <50, then update it to 0; otherwise, update the value to 100. Print both arrays (M and MI). D-7. Split M into two nd-arrays of size 3x8 and 2x8. D-8. Create a list of 8 random integers whose value ranges from 1 to 5. Append (attach) the list as the sixth row to M. D-9. Create a list of 5 random integers whose value ranges from 1 to 5. Append (attach) the list as the ninth column to M. D-10. Execute the following cells, and explain your observations: list1 = [1,2,3,4] print((lambda x: x * 3 )(list1)) array1 = np.array([1,2,3,4]) print((lambda x: x * 3 )(array1))

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Q1 Sure here are the answers to your questions for each of the mentioned Python methods including whether they are available in naive Python or the NumPy library C1 len PurposeUsage Determines the cou... View the full answer