Numpy Fundamentals | 20/100 Days of Python Algo Trading

1. What is NumPy?

A) A Python library for advanced mathematical functions.

B) A Python library that provides support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.

C) A Python module that implements neural networks.

D) A Python-based data storage system.

2. How do NumPy arrays differ from Python lists?

A) NumPy arrays can only store numeric data.

B) NumPy arrays support element-wise operations, which Python lists do not.

C) NumPy arrays have a fixed size at creation, unlike Python lists that can grow dynamically.

D) All of the above.

3. What are common use cases of NumPy in algorithmic trading?

A) Data cleaning.

B) Statistical analysis.

C) Backtesting of trading strategies.

D) All of the above.

4. How can you create a NumPy array?

A) Using the np.array() function.

B) Using the np.create_array() method.

C) Using the array() function.

D) Using the new Array() constructor.

5. Which attribute of a NumPy array returns the number of array dimensions?

A) shape

B) type

C) ndim

D) dim

6. How do you change the datatype of a NumPy array?

A) np.change_type(array, dtype=np.float32)

B) array.astype(np.float32)

C) array.set_type(np.float32)

D) array.retype(np.float32)

7. What operation would you use to add two NumPy arrays?

A) np.add(array1, array2)

B) array1 + array2

C) Both A and B

D) array1.add(array2)

8. Which NumPy function would you use to calculate the mean across a single dimension of a multi-dimensional array?

A) np.mean(array, axis=1)

B) np.average(array)

C) array.mean(1)

D) Both A and C

9. How do you initialize a NumPy array of zeros with shape (3,4)?

A) np.zeros(3,4)

B) np.zeros([3,4])

C) np.array(3,4,0)

D) np.array([3,4],0)

10. What does the reshape method do to an array?

A) Changes the array data type.

B) Sorts the array.

C) Modifies the array shape without changing its data.

D) None of the above.

11. Which of the following operations is element-wise between two compatible NumPy arrays?

A) Multiplication

B) Addition

C) Subtraction

D) All of the above.

12. What error is raised when you attempt operations on arrays with incompatible shapes?

A) ValueError

B) TypeError

C) ShapeError

D) BroadcastError

13. Which function helps in joining a sequence of arrays along a new axis?

A) np.concatenate()

B) np.stack()

C) np.join()

D) np.merge()

14. How would you select elements from a NumPy array that are greater than 10?

A) array > 10

B) array[array > 10]

C) array.select(>10)

D) np.gt(array, 10)

15. What is the correct way to invert the values in a boolean array?

A) np.not(array)

B) array != True

C) ~array

D) array.inverse()

16. Which method explicitly broadcasts an array to a new shape?

A) array.broadcast(new_shape)

B) np.broadcast_to(array, new_shape)

C) array.reshape(new_shape)

D) np.shape(array, new_shape)

17. How do you check the memory usage of a NumPy array?

A) array.memory()

B) array.info()

C) array.nbytes

D) np.mem_usage(array)

18. Which method is used to flatten a multi-dimensional array into a single dimension?

A) array.flatten()

B) array.ravel()

C) Both A and B

D) array.unfold()

19. What would np.linspace(0, 10, 5) return?

A) An array of 5 evenly spaced points between 0 and 10.

B) An array of numbers from 0 to 10 with a step of 5.

C) An array of 5 random numbers between 0 and 10.

D) An error because the function parameters are incorrect.

20. Which function is used to save a NumPy array to a binary file in .npy format?

A) np.save('filename.npy', array)

B) np.savetxt('filename.npy', array)

C) np.to_file('filename.npy', array)

D) np.write('filename.npy', array)

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