Python DSA (Data Structures and Algorithms) Syllabus
Python DSA (Data Structures and Algorithms) Notes 1. Introduction to DSA in Python Data Structure: Organizes data for efficient operations. Algorithm: A set of steps to solve a problem. Why DSA? Improves efficiency and optimizes performance. 2. Time and Space Complexity Big-O Notation: Measures algorithm performance. Common Complexities: O(1) – Constant Time O(log n) – Logarithmic Time O(n) – Linear Time O(n log n) – Log-Linear Time O(n²) – Quadratic Time O(2ⁿ) – Exponential Time Example: def constant_time ( arr ): return arr[ 0 ] # O(1) def linear_time ( arr ): for item in arr: # O(n) print (item) 3. Lists and Strings Lists (Dynamic Arrays) Declaration: arr = [1, 2, 3, 4] Operations: arr.append( 5 ) # O(1) arr.insert( 1 , 10 ) # O(n) arr.remove( 3 ) # O(n) arr.pop() # O(1) Strings Immutable in Python Common Operations: s = "Hello" print (s[ 0 ]) # Accessing character print (s[::- 1 ]) # Reversing string print (s.upper()) # C...