aloalgo.comIntroduction to Arrays
An array is the most fundamental data structure in programming. It stores elements in contiguous memory locations, allowing direct access to any element using its index. Arrays are the building block for many other data structures and algorithms.What is an Array?
An array is a collection of elements stored at contiguous memory locations. Each element can be accessed directly using its index, starting from 0.Basic Array Operations
Accessing Elements
Array access is O(1) because elements are stored contiguously. The memory address of any element can be calculated directly from the base address and index.Modifying Elements
Modifying an element at a known index is also O(1).Adding Elements
Adding to the end is O(1) amortized, but inserting at a specific position requires shifting elements, making it O(n).Removing Elements
Like insertion, removal from the end is O(1), but removal from elsewhere is O(n) due to shifting.Iterating Over Arrays
Slicing Arrays
Python provides powerful slicing syntax to extract portions of arrays.Common Array Patterns
Finding Min/Max
Summing and Counting
Searching
Time Complexity Reference
| Operation | Time Complexity | Notes |
|---|---|---|
| Access by index | O(1) | arr[i] |
| Modify by index | O(1) | arr[i] = x |
| Append to end | O(1)* | Amortized |
| Pop from end | O(1) | arr.pop() |
| Insert at index | O(n) | Shifts elements |
| Delete at index | O(n) | Shifts elements |
| Search by value | O(n) | Linear search |
| Length | O(1) | len(arr) |
Common Interview Tips
- Consider edge cases: Empty array, single element, duplicates, negative numbers.
- Watch for off-by-one errors: Remember arrays are 0-indexed and slicing end indices are exclusive.
- Think about in-place vs. extra space: Many problems can be solved both ways with different trade-offs.
- Know your time complexity: Nested loops are O(n²), sorting is O(n log n), single pass is O(n).
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