Python Data Structures Coding Problems

Data structures form the backbone of efficient programming. Mastering arrays, strings, and lists is essential for coding interviews and problem-solving.

This tutorial provides real-world coding problems with optimized solutions to strengthen your understanding.

1. Array Problems

Problem 1: Find Second Largest Element

arr = list(set(map(int, input().split())))
arr.sort()
print(arr[-2])

Problem 2: Move Zeros to End

arr = list(map(int, input().split()))

result = [x for x in arr if x != 0] + [0]*arr.count(0)
print(result)

Problem 3: Find Missing Number

n = int(input())
arr = list(map(int, input().split()))

print(n*(n+1)//2 - sum(arr))

2. String Problems

Problem 4: Count Vowels and Consonants

s = input().lower()
vowels = 'aeiou'

v = sum(1 for c in s if c in vowels)
c = sum(1 for c in s if c.isalpha() and c not in vowels)

print("Vowels:", v, "Consonants:", c)

Problem 5: Anagram Check

s1 = input()
s2 = input()

print("Anagram" if sorted(s1) == sorted(s2) else "Not Anagram")

Problem 6: First Non-Repeating Character

s = input()

for c in s:
    if s.count(c) == 1:
        print(c)
        break

3. List Problems

Problem 7: Remove Duplicates

arr = list(map(int, input().split()))
print(list(set(arr)))

Problem 8: Rotate List

arr = list(map(int, input().split()))
k = int(input())

k = k % len(arr)
print(arr[-k:] + arr[:-k])

Problem 9: Flatten Nested List

nested = [[1,2],[3,4],[5]]
flat = [item for sublist in nested for item in sublist]
print(flat)

4. Interview-Level Problems

Problem 10: Two Sum Problem

arr = list(map(int, input().split()))
target = int(input())

seen = {}

for i, num in enumerate(arr):
    if target - num in seen:
        print(seen[target-num], i)
        break
    seen[num] = i

Problem 11: Longest Substring Without Repeating Characters

s = input()
char_set = set()
l = 0
max_len = 0

for r in range(len(s)):
    while s[r] in char_set:
        char_set.remove(s[l])
        l += 1
    char_set.add(s[r])
    max_len = max(max_len, r - l + 1)

print(max_len)

5. Optimization Tips

1. Use sets for faster lookup (O(1)).

2. Prefer list comprehensions for cleaner code.

3. Use built-in functions like sum(), max().

4. Optimize loops to reduce time complexity.

6. Practice Set

1. Find duplicates in array.

2. Merge two sorted arrays.

3. Check string rotation.

4. Find intersection of two arrays.

5. Kadane’s Algorithm (maximum subarray sum).

Conclusion

Mastering data structure problems in Python is essential for cracking coding interviews. Focus on understanding patterns and optimizing solutions.

Practice consistently and gradually move to more complex problems for best results.