Write the necessary code to initialize a numpy array (5,3,3) as follows: [[[6 2 6] [6 2 6] [6 2 6]] [[666] [666] [666]] [[666] [333] [666]] [[666] [666] [666]] [[7 6 6] [6 7 6] [667]]]

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
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**Lab Exercise: Working with Numpy Arrays in Python**

**Objective:** This exercise aims to help you understand and implement operations on Numpy arrays using Python. 

### Task 1: Initialize a 3D Numpy Array

- **Instructions:** Open PyCharm on your PC and create a Python file named `Lab6.py`.
- **Goal:** Write the necessary code to initialize a numpy array with the shape (5, 3, 3) as shown below:

  ```python
  [
    [[6, 2, 6],
     [6, 2, 6],
     [6, 2, 6]],

    [[6, 6, 6],
     [6, 6, 6],
     [6, 6, 6]],

    [[6, 6, 6],
     [3, 3, 3],
     [6, 6, 6]],

    [[6, 6, 6],
     [6, 6, 6],
     [6, 6, 6]],

    [[7, 6, 6],
     [7, 6, 6],
     [6, 6, 7]]
  ]
  ```

### Task 2: Analyze a 2D Numpy Array

- **Instructions:** Generate a (7, 7) numpy array that consists of integer random values between 10 and 50. Answer the following:

  a. What is the minimum value in each column?

  b. What is the mean for each row?

  c. Generate the cumulative product of each column.

  d. Count the number of elements in the array whose values are greater than 30 and smaller than 40.

  e. Display the elements in the arrays that equal 20.

  f. Multiply by 5 the elements whose value is less than 30.

  g. Display the largest 5 elements in the array.

### Task 3: Compare Two 1D Numpy Arrays

- **Instructions:** Define two numpy 1D arrays, `X` and `Y`. Initialize them with random numbers between 0 and 100. Print the elements in `X` that do not exist in `Y`.

**Outcome:** By completing these tasks, you will gain hands-on experience with numpy array operations, allowing you to manipulate and analyze data effectively using Python.
Transcribed Image Text:**Lab Exercise: Working with Numpy Arrays in Python** **Objective:** This exercise aims to help you understand and implement operations on Numpy arrays using Python. ### Task 1: Initialize a 3D Numpy Array - **Instructions:** Open PyCharm on your PC and create a Python file named `Lab6.py`. - **Goal:** Write the necessary code to initialize a numpy array with the shape (5, 3, 3) as shown below: ```python [ [[6, 2, 6], [6, 2, 6], [6, 2, 6]], [[6, 6, 6], [6, 6, 6], [6, 6, 6]], [[6, 6, 6], [3, 3, 3], [6, 6, 6]], [[6, 6, 6], [6, 6, 6], [6, 6, 6]], [[7, 6, 6], [7, 6, 6], [6, 6, 7]] ] ``` ### Task 2: Analyze a 2D Numpy Array - **Instructions:** Generate a (7, 7) numpy array that consists of integer random values between 10 and 50. Answer the following: a. What is the minimum value in each column? b. What is the mean for each row? c. Generate the cumulative product of each column. d. Count the number of elements in the array whose values are greater than 30 and smaller than 40. e. Display the elements in the arrays that equal 20. f. Multiply by 5 the elements whose value is less than 30. g. Display the largest 5 elements in the array. ### Task 3: Compare Two 1D Numpy Arrays - **Instructions:** Define two numpy 1D arrays, `X` and `Y`. Initialize them with random numbers between 0 and 100. Print the elements in `X` that do not exist in `Y`. **Outcome:** By completing these tasks, you will gain hands-on experience with numpy array operations, allowing you to manipulate and analyze data effectively using Python.
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