Excellent Numpy Test - 78+ MCQs: NumPy test: Evaluate Your Proficiency with NumPy Questions and Answers

1. What does the `np.where` function do in NumPy?

Returns the indices of elements that satisfy a given condition

Specifies the location of the NumPy library on disk

Identifies the dimensions of an array

Finds the maximum value in an array

2. What does the `np.linspace(0, 1, 5)` function do?

Creates an array with five evenly spaced values between 0 and 1

Generates an array with values [0, 1, 5]

Creates an array with values [0, 0.2, 0.4, 0.6, 0.8, 1]

Generates an array with five random values between 0 and 1

3. What does the `np.eye` function do in NumPy?

Creates an identity matrix

Generates an array with random values

Creates an array with ones on the diagonal

Generates an array filled with zeros

4. Explain the concept of masking in NumPy and provide an example.

Masking involves using boolean arrays to select elements from another array based on certain conditions. Example: `arr[arr > 5]` selects elements greater than 5 from the array `arr`.

Masking is not a feature in NumPy

Masking is only applicable to one-dimensional arrays

NumPy arrays do not support conditional selection

5. How can you create a NumPy array from a Python list?

Using `np.array(my_list)`

Converting the list to a tuple

NumPy arrays cannot be created from Python lists

By using the `array` method in Python

6. What is the purpose of the NumPy function 'np.meshgrid()'?

Generates a mesh plot of a 3D surface

Creates a grid from element-wise operations

Expands the dimensions of an array

Generates coordinate matrices from coordinate vectors

7. In NumPy, what does the 'np.pad()' function do?

Computes the padding required for a convolutional operation

Returns the padded array

Fills array elements with a specified value

Calculates the partial derivative of an array

8. What is the role of the `np.mean` function in NumPy?

Calculates the mean (average) of an array

Finds the median of an array

Counts the number of elements in an array

Calculates the standard deviation of an array

9. What is the primary purpose of NumPy in Python?

Data Visualization

Machine Learning

Numerical Computing

Web Development

10. How can you flatten a NumPy array?

arr.flatten()

np.flat(arr)

arr.flat()

np.reshape(arr, -1)

11. What is NumPy used for in Python?

Numerical computing and array manipulation

Web development

Natural language processing

Data visualization

12. How do you access the element at the 3rd index of a NumPy array named `my_array`?

Using `my_array[3]`

By using `my_array(3)`

It is not possible to access elements in NumPy arrays

By using `my_array.element(3)`

13. What is the purpose of the `np.zeros` function in NumPy?

To create an array filled with zeros

To generate an array with random numbers

To create an empty array

To create an array filled with ones

14. What is the purpose of the NumPy function 'np.ma.masked_where()'?

Creates a masked array where values meet a condition

Calculates the mean of a masked array

Fills masked elements with a specified value

Returns the indices of masked elements

15. What is the purpose of the `np.unique` function in NumPy?

Finds the unique elements in an array

Calculates the sum of all elements in an array

Counts the number of elements in an array

Generates an array with ones on the diagonal

16. What is the purpose of the NumPy function 'np.argsort()'?

Sorts array elements in ascending order

Returns the indices that would sort an array

Performs element-wise sorting

Finds the index of the minimum value in an array

17. Examine the purpose of the `np.histogram` function in NumPy.

Generates a histogram from an array of data

Counts the number of unique elements in an array

Calculates the mean of an array

Creates a scatter plot for two arrays

18. How do you calculate the element-wise square root of a NumPy array?

Using `np.sqrt(my_array)`

By applying the `my_array.square_root` method

Both A and B

NumPy does not support calculating the square root of array elements

19. How can you perform element-wise subtraction of two NumPy arrays?

np.subtract(arr1, arr2)

arr1 - arr2

np.sub(arr1, arr2)

arr1.subtract(arr2)

20. How can you create a diagonal matrix from a NumPy array?

np.diagonal_matrix(arr)

np.diag(arr)

arr.create_diagonal()

np.matrix_diag(arr)

21. Examine the purpose of the `np.interp` function in NumPy.

Performs linear interpolation on a one-dimensional array

Calculates the intersection points of two arrays

Creates an array with regularly spaced values

Finds the inverse of a matrix

22. In NumPy, what does the 'np.random.seed()' function do?

Sets the random seed for reproducibility

Generates a random seed array

Initializes the random number generator

Resets the random seed

23. What is the purpose of the NumPy function 'np.histogram()'?

Calculating the mean of an array

Creating a histogram from an array

Sorting array elements in ascending order

Counting occurrences of unique values in an array

24. What is NumPy and what is its primary purpose in Python?

NumPy is a numerical computing library for Python, designed for efficient array manipulation and mathematical operations

NumPy is a Python web framework for building web applications

NumPy is used for natural language processing in Python

NumPy is a Python library exclusively for data visualization

25. Explain the concept of NumPy broadcasting and provide an example.

NumPy broadcasting allows for element-wise operations on arrays of different shapes by implicitly expanding the smaller array. Example: Adding a scalar to a one-dimensional array.

Broadcasting is not a feature in NumPy

NumPy broadcasting is limited to addition and subtraction operations

Broadcasting is applicable only to two-dimensional arrays

26. What does the `np.clip` function do in NumPy?

Clips (limits) the values in an array to a specified range

Counts the occurrences of each unique element in an array

Concatenates two arrays along a specified axis

Calculates the cumulative sum of an array

27. How do you create a NumPy array with regularly spaced values between two numbers?

Using `np.linspace(start, stop, num)`

By using `np.range(start, stop, step)`

Both A and B

NumPy does not support creating arrays with regularly spaced values

28. What is the purpose of the `np.arange` function in NumPy?

Generates an array with regularly spaced values

Creates an array filled with ones

Calculates the mean of an array

Finds the maximum value in an array

29. How can you reshape a NumPy array?

Using the `reshape` method or the `np.reshape` function

Reshaping is not possible in NumPy

By converting the array to a Python list and then reshaping

Using the `resize` method

30. What is the result of the expression `np.arange(2, 10, 2)`?

An array with values [2, 4, 6, 8]

An array with values [2, 4, 8]

An array with values [2, 6, 10]

An array with values [2, 8]

NumPy MCQ Test 3