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

1. 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

2. What is the purpose of the `np.ma.masked_array` function in NumPy?

Creates a masked array, allowing elements to be masked based on a specified condition

Finds the elements with the minimum value in an array

Calculates the mean of an array

Masks all elements in an array

3. What is the purpose of the `np.ma.masked_where` function in NumPy?

Creates a masked array based on a specified condition

Finds the elements with the maximum value in an array

Calculates the mean of an array

Masks all elements in an array

4. Examine the purpose of the `np.savez` function in NumPy.

Saves multiple NumPy arrays into a single compressed file

Saves a NumPy array to a text file

Counts the number of elements in a NumPy array

Creates a zip file containing multiple NumPy arrays

5. What does the function `np.arange(5)` do?

Creates an array with elements 0 to 4

Generates an array with elements 1 to 5

Creates an array with elements 0 to 5

Generates an array with elements 0 to 4

6. How do you perform element-wise multiplication of two NumPy arrays `arr1` and `arr2`?

By using the expression `arr1 * arr2`

Using the `np.multiply` function

Both A and B

NumPy does not support element-wise multiplication

7. What is broadcasting in NumPy, and how does it work?

Broadcasting is a mechanism that allows NumPy to perform operations on arrays of different shapes, by implicitly expanding the smaller array

Broadcasting is only applicable to one-dimensional arrays

NumPy does not support broadcasting

Broadcasting is limited to addition and subtraction operations

8. What is the purpose of the `np.fft.fft` function in NumPy?

Computes the one-dimensional discrete Fourier Transform

Finds the factorial of each element in an array

Calculates the eigenvalues of a matrix

Finds the maximum value in an array

9. 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

10. 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

11. 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

12. 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

13. Explain the concept of a NumPy structured array.

A structured array allows the definition of multiple fields with different data types, similar to a table with named columns.

Structured arrays are not supported in NumPy

A structured array is an array with a fixed structure and cannot have different data types

Structured arrays are only applicable to one-dimensional arrays

14. How do you apply a function element-wise to a NumPy array?

Using the `np.vectorize` function

Applying functions element-wise is not supported in NumPy

By using a for loop

Using the `np.apply_along_axis` function

15. What is the purpose of the NumPy function 'np.linalg.inv()'?

Computing the dot product of two arrays

Calculating the inverse of a matrix

Finding the eigenvalues of a matrix

Performing element-wise matrix multiplication

16. How can you perform element-wise multiplication of two NumPy arrays?

np.multiply(arr1, arr2)

arr1 * arr2

np.mult(arr1, arr2)

np.dot(arr1, arr2)

17. 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]

18. 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)

19. 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

20. How can you perform element-wise addition of two NumPy arrays `arr1` and `arr2`?

By using the expression `arr1 + arr2`

Using the `np.add` function

Both A and B

NumPy does not support element-wise addition

21. What does the `np.std` function calculate in NumPy?

The standard deviation of an array

The sum of all elements in an array

The variance of an array

The mean of an array

22. How can you calculate the mean of a NumPy array along a specific axis?

np.mean(arr, axis=1)

np.average(arr, axis=0)

arr.mean(axis=2)

np.compute_mean(arr, axis=1)

23. How can you find the sum of all elements in a NumPy array?

Using `np.sum(my_array)`

By applying the `my_array.total` attribute

Both A and B

NumPy does not support calculating the sum of array elements

24. How do you calculate the inverse of a matrix in NumPy?

Using the `np.linalg.inv` function

Inverting matrices is not possible in NumPy

By applying the `np.matrix_inverse` method

Using the `np.inverse` function

25. How do you find the unique elements in a NumPy array?

Using `np.unique(my_array)`

By applying the `my_array.distinct` method

Both A and B

NumPy does not support finding unique elements in arrays

26. What is the purpose of the `np.save` and `np.load` functions in NumPy?

To save and load NumPy arrays to and from disk

To check the memory usage of NumPy arrays

Saving and loading arrays is not possible in NumPy

To compress NumPy arrays for storage

27. What is NumPy used for in Python?

Numerical computing and array manipulation

Web development

Natural language processing

Data visualization

28. What is the purpose of the NumPy function 'np.fft.fft()'?

Calculating the fast Fourier transform

Finding the first occurrence of a value

Flattening a multidimensional array

Performing a fuzzy string match

29. What is the purpose of the `np.eye` function 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

30. 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)`

31. 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

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

np.subtract(arr1, arr2)

arr1 - arr2

np.sub(arr1, arr2)

arr1.subtract(arr2)

33. What does the NumPy function 'np.unravel_index()' do?

Reshapes a flattened array to its original shape

Converts an array of indices to Cartesian coordinates

Returns the indices of the minimum values along an axis

Splits an array into multiple sub-arrays

34. How can you flatten a NumPy array?

arr.flatten()

np.flat(arr)

arr.flat()

np.reshape(arr, -1)

35. How can you perform matrix multiplication in NumPy?

np.matmul(arr1, arr2)

arr1 @ arr2

np.mult_matrix(arr1, arr2)

arr1.matrix_mult(arr2)

36. 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

37. How can you find the index of the maximum value in a NumPy array?

Using `np.argmax`

By using the `max_index` attribute

Both A and B

It is not possible to find the index of the maximum value in NumPy

38. 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

39. How can you calculate the dot product of two NumPy arrays?

np.dot_product(arr1, arr2)

np.dot(arr1, arr2)

arr1 * arr2

np.multiply(arr1, arr2)

40. How can you concatenate two NumPy arrays vertically?

np.append(arr1, arr2, axis=0)

np.concat(arr1, arr2, axis=0)

np.vstack((arr1, arr2))

np.merge_vertical(arr1, arr2)

NumPy MCQ Test 2