Python Data Science Jobs & Interviews
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Your go-to hub for Python and Data Science—featuring questions, answers, quizzes, and interview tips to sharpen your skills and boost your career in the data-driven world.

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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

By: https://t.iss.one/DataScienceQ

**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 27 (Intermediate - List Operations):
What is the time complexity of the list.insert(0, item) operation in Python, and why?

A) O(1) - Constant time (like appending)
B) O(n) - Linear time (shifts all elements)
C) O(log n) - Logarithmic time (binary search)
D) O(n²) - Quadratic time (worst-case)

#Python #DataStructures #TimeComplexity #Lists

By: https://t.iss.one/DataScienceQ
In Python, lists are versatile mutable sequences with built-in methods for adding, removing, searching, sorting, and more—covering all common scenarios like dynamic data manipulation, queues, or stacks. Below is a complete breakdown of all list methods, each with syntax, an example, and output, plus key built-in functions for comprehensive use.

📚 Adding Elements
append(x): Adds a single element to the end.

  lst = [1, 2]
lst.append(3)
print(lst) # Output: [1, 2, 3]


extend(iterable): Adds all elements from an iterable to the end.

  lst = [1, 2]
lst.extend([3, 4])
print(lst) # Output: [1, 2, 3, 4]


insert(i, x): Inserts x at index i (shifts elements right).

  lst = [1, 3]
lst.insert(1, 2)
print(lst) # Output: [1, 2, 3]


📚 Removing Elements
remove(x): Removes the first occurrence of x (raises ValueError if not found).

  lst = [1, 2, 2]
lst.remove(2)
print(lst) # Output: [1, 2]


pop(i=-1): Removes and returns the element at index i (default: last).

  lst = [1, 2, 3]
item = lst.pop(1)
print(item, lst) # Output: 2 [1, 3]


clear(): Removes all elements.

  lst = [1, 2, 3]
lst.clear()
print(lst) # Output: []


📚 Searching and Counting
count(x): Returns the number of occurrences of x.

  lst = [1, 2, 2, 3]
print(lst.count(2)) # Output: 2


index(x[, start[, end]]): Returns the lowest index of x in the slice (raises ValueError if not found).

  lst = [1, 2, 3, 2]
print(lst.index(2)) # Output: 1


📚 Ordering and Copying
sort(key=None, reverse=False): Sorts the list in place (ascending by default; stable sort).

  lst = [3, 1, 2]
lst.sort()
print(lst) # Output: [1, 2, 3]


reverse(): Reverses the elements in place.

  lst = [1, 2, 3]
lst.reverse()
print(lst) # Output: [3, 2, 1]


copy(): Returns a shallow copy of the list.

  lst = [1, 2]
new_lst = lst.copy()
print(new_lst) # Output: [1, 2]


📚 Built-in Functions for Lists (Common Cases)
len(lst): Returns the number of elements.

  lst = [1, 2, 3]
print(len(lst)) # Output: 3


min(lst): Returns the smallest element (raises ValueError if empty).

  lst = [3, 1, 2]
print(min(lst)) # Output: 1


max(lst): Returns the largest element.

  lst = [3, 1, 2]
print(max(lst)) # Output: 3


sum(lst[, start=0]): Sums the elements (start adds an offset).

  lst = [1, 2, 3]
print(sum(lst)) # Output: 6


sorted(lst, key=None, reverse=False): Returns a new sorted list (non-destructive).

  lst = [3, 1, 2]
print(sorted(lst)) # Output: [1, 2, 3]


These cover all standard operations (O(1) for append/pop from end, O(n) for most others). Use slicing lst[start:end:step] for advanced extraction, like lst[1:3] outputs ``.

#python #lists #datastructures #methods #examples #programming

@DataScience4
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3
🧠 Quiz: Python

Q: Which of the following is the correct way to define an empty list in Python?

A) my_list = ()
B) my_list = []
C) my_list = {}
D) my_list = "None"

Correct answer: B
Explanation: In Python, lists are defined using square brackets []. An empty list is simply []. Parentheses () define a tuple, and curly braces {} define a set or dictionary.

#Python #DataStructures #Lists

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By: @DataScienceQ