Hello leetcoders,
This might be underrated post but very useful, i have added all heavily used DS for Java.
- Map 2. ArrayList 3. Array[ ] 4. Stack 5. Queue / PriorityQueue 6. String 7. Set
Basic Idea to understand :
Map -> V get(k1)
- get : method,
- k1 : accept key as an value,
- V : return datatype
1. Map // collection
1. Definition ->Map<K, V> map = new HashMap<>();
2. insert / update -> V put(k1, v1); // TC: O(1)
3. delete -> V remove(k1); // TC: O(1)
4. get -> V get(k1); // TC: O(1)
5. size -> int size(); // TC: O(1)
6. check for Empty -> boolean isEmpty(); // TC: O(1)
7. value present -> boolean containsKey(k1); // TC: O(1)
8. remove all map values -> clear(); // TC: O(2n + 1) -> O(n) (n-key, n-value, 1 for map itself)
2. ArrayList // Collection
1. Definition -> ArrayList list = new ArrayList<>();
2. insert -> boolean add(t) [TC: O(1)] / add(int index, T) [TC: O(n)]
3. delete -> T remove(int index); // TC: O(n) as you have to shuffle the elements above that point
4. set/update index value -> T set(int index, T); // TC: O(1)
5. get index-> T get(int index); // TC: O(1)
6. size -> int list.size(); // TC: O(1)
7. clear elements -> void clear(); // TC: O(n) & removeAll : O(n^2).
8. check for Empty -> boolean isEmpty(); // TC: O(1)
9. value contain check -> boolean contains(t); // TC: O(n)
10. get Index of value -> int indexOf(t); // TC: O(n), checking each element one by one
11. non premitive to premitive list -> toArray(); // TC: O(n)
12. Sorting for List ->
- Collections.sort(list, (a, b) -> a - b); // ascending , TC: O(nlogn)
- Collections.sort(list, (a, b) -> b - a); // descnding , TC: O(nlogn)
3. Array
1. Definition ->T arr [ ]= new T[N]; // N: static size , T : datatype
2. insert -> arr[index] = v1; // TC: O(1)
3. update -> arr[index] = v2; // TC: O(1)
4. get -> T arr[index] // TC: O(1)
5. size -> int arr.length // TC: O(1)
6. Arrays.fill(arr, 0); // filled array with value=0, TC: O(n)
7. Sorting -> TC: O(nlogn)
- premitive (int[] ..)
- Arrays.sort(arr); // default ascending,
- non-premetive (Integer[] ..)
- Arrays.sort(arr); // default ascending
- Arrays.sort(arr, (a,b) -> b-a); // descening
4. Stack // Collection
1. Definition ->Stack st = new Stack<>();
2. insert -> T push(t); // TC: O(1)
3. size -> int size(); // TC: O(1)
4. look up for head element -> T peek(); // TC: O(1)
5. remove head element -> T pop(); // TC: O(1)
6. check for Empty -> boolean isEmpty(); // TC: O(1)
5. Queue // Collection
1. Definition -> Queue queue = new LinkedList<>();
2. insert -> boolean add(t); // TC: O(1)
3. size -> int size(); // TC: O(1)
4. look up for head element -> T peek(); // TC: O(1)
5. remove head element -> T poll(); // TC: O(1)
6. check for Empty -> boolean isEmpty(); // TC: O(1)
7. points to remember :
- queue poll vs stack pop
- queue add vs stack push
- we can define queue via LinkedList, PriorityQueue based on use case
6. String / StringBuilder
1. Definition -> String str = new String();
2. size -> int length();// TC: O(1)
3. convert to char Array -> toCharArray(); // TC: O(n)
4. value for specific index -> charAt(int index); // TC: O(1)
5. substring from string -> substring [a,b) // a : inclusive, b: Exclusive, TC: O(n)
6. transform to Lowercase -> toLowerCase(); // TC: O(n)
7. transform to UpperCase -> toUpperCase(); // TC: O(n)
8. replace all characters in string -> replaceAll(from, to) // TC: O(n)
9. Some useful Character properties
- Character.isLetter();
- Character.isAlphabetic();
- Character.isUpperCase();
- Character.isLowerCase();
- Character.isDigit();
- Concatenation
- T str1 + str2
- StringBuilder ->
- new StringBuilder() / new StringBuilder(int)
- append("adding string") // better way to do
- toString() // converting back to string
7. HashSet // Collection
1. Definition ->Set set = new HashSet<>();
2. insert / update -> boolean add(t); // TC: O(1)
3. delete -> boolean remove(t); // TC: O(1)
4. get -> boolean contains(t); // TC: O(1)
5. size -> int size(); // TC: O(1)
6. check for Empty -> boolean isEmpty(); // TC: O(1)
7. remove all set values -> clear(); // TC: O(n)
Helpful? Let me know if i missed anything
Update: Please read comment section too, people are awesome :)
Please upvote!
Happy Coding :)
Helpful link for Time Complexity(TC).