Question 13 (Intermediate):
In NumPy, what is the difference between np.array([1, 2, 3]) and np.array([[1, 2, 3]])?

A) The first is a 1D array, the second is a 2D row vector
B) The first is faster to compute
C) The second automatically transposes the data
D) They are identical in memory usage

#Python #NumPy #Arrays #DataScience

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Question 1 (Advanced):
When using Python's multiprocessing module, why is if __name__ == '__main__': required for Windows but often optional for Linux/macOS?

A) Windows lacks proper fork() implementation
B) Linux handles memory management differently
C) macOS has better garbage collection
D) Windows requires explicit process naming

#Python #Multiprocessing #ParallelComputing #Advanced

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Question 2 (Expert):
In Python's GIL (Global Interpreter Lock), what is the primary reason it allows only one thread to execute Python bytecode at a time, even on multi-core systems?

A) To prevent race conditions in memory management
B) To simplify the CPython implementation
C) To reduce power consumption
D) To improve single-thread performance

#Python #GIL #Concurrency #CPython

✅ By: https://t.iss.one/DataScienceQ

Question 3 (Intermediate):
In Tkinter, what is the correct way to make a widget expand to fill available space in its parent container?

A) widget.pack(expand=True)
B) widget.grid(sticky='nsew')
C) widget.place(relwidth=1.0)
D) All of the above

#Python #Tkinter #GUI #Widgets

✅ By: https://t.iss.one/DataScienceQ

Question 4 (Intermediate):
In scikit-learn's KMeans implementation, what is the purpose of the n_init parameter?

A) Number of initial centroid configurations to try
B) Number of iterations for each run
C) Number of features to initialize
D) Number of CPU cores to use

#Python #KMeans #Clustering #MachineLearning

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Question 20 (Beginner):
What is the output of this Python code?

x = [1, 2, 3]
y = x
y.append(4)
print(x)

A) [1, 2, 3]
B) [1, 2, 3, 4]
C) [4, 3, 2, 1]
D) Raises an error

#Python #Lists #Variables #Beginner

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✅ **Correct answer: B) `[1, 2, 3, 4]`**

*Explanation:
- `y = x` creates a reference to the same list object
- Modifying `y` affects `x` because they point to the same memory location
- To create an independent copy, use y = x.copy() or y = list(x)*

Question 21 (Beginner):
What is the correct way to check the Python version installed on your system using the command line?

A) python --version
B) python -v
C) python --v
D) python version

#Python #Basics #Programming #Beginner

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Question 22 (Interview-Level):
Explain the difference between deepcopy and regular assignment (=) in Python with a practical example. Then modify the example to show how deepcopy solves the problem.

import copy

# Original Problem
original = [[1, 2], [3, 4]]
shallow_copy = original.copy()
shallow_copy[0][0] = 99
print(original)  # What happens here?

# Solution with deepcopy
deep_copied = copy.deepcopy(original)
deep_copied[1][0] = 77
print(original)  # What happens now?

Options:
A) Both modify the original list
B) copy() creates fully independent copies
C) Shallow copy affects nested objects, deepcopy doesn't
D) deepcopy is slower but creates true copies

#Python #Interview #DeepCopy #MemoryManagement

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Question 23 (Advanced):
How does Python's "Name Mangling" (double underscore prefix) work in class attribute names, and what's its practical purpose?

class Test:
    def __init__(self):
        self.public = 10
        self._protected = 20
        self.__private = 30  # Name mangling

obj = Test()
print(dir(obj))  # What happens to __private?

Options:
A) Completely hides the attribute
B) Renames it to _Test__private
C) Makes it immutable
D) Converts it to a method

#Python #OOP #NameMangling #Advanced

✅ By: https://t.iss.one/DataScienceQ