# Posts published in “Hashtable”

Two strings are considered close if you can attain one from the other using the following operations:

• Operation 1: Swap any two existing characters.
• For example, abcde -> aecdb
• Operation 2: Transform every occurrence of one existing character into another existing character, and do the same with the other character.
• For example, aacabb -> bbcbaa (all a‘s turn into b‘s, and all b‘s turn into a‘s)

You can use the operations on either string as many times as necessary.

Given two strings, word1 and word2, return true if word1 and word2 are close, and false otherwise.

Example 1:

Input: word1 = "abc", word2 = "bca"
Output: true
Explanation: You can attain word2 from word1 in 2 operations.
Apply Operation 1: "abc" -> "acb"
Apply Operation 1: "acb" -> "bca"


Example 2:

Input: word1 = "a", word2 = "aa"
Output: false
Explanation: It is impossible to attain word2 from word1, or vice versa, in any number of operations.


Example 3:

Input: word1 = "cabbba", word2 = "abbccc"
Output: true
Explanation: You can attain word2 from word1 in 3 operations.
Apply Operation 1: "cabbba" -> "caabbb"
Apply Operation 2: "caabbb" -> "baaccc"
Apply Operation 2: "baaccc" -> "abbccc"


Example 4:

Input: word1 = "cabbba", word2 = "aabbss"
Output: false
Explanation: It is impossible to attain word2 from word1, or vice versa, in any amount of operations.


Constraints:

• 1 <= word1.length, word2.length <= 105
• word1 and word2 contain only lowercase English letters.

## Solution: Hashtable

Two strings are close:
1. Have the same length, ccabbb => 6 == aabccc => 6
2. Have the same char set, ccabbb => (a, b, c) == aabccc => (a, b, c)
3. Have the same sorted char counts ccabbb => (1, 2, 3) == aabccc => (1, 2, 3)

Time complexity: O(n)
Space complexity: O(1)

## Python3

A string s is called good if there are no two different characters in s that have the same frequency.

Given a string s, return the minimum number of characters you need to delete to make s good.

The frequency of a character in a string is the number of times it appears in the string. For example, in the string "aab", the frequency of 'a' is 2, while the frequency of 'b' is 1.

Example 1:

Input: s = "aab"
Output: 0
Explanation: s is already good.


Example 2:

Input: s = "aaabbbcc"
Output: 2
Explanation: You can delete two 'b's resulting in the good string "aaabcc".
Another way it to delete one 'b' and one 'c' resulting in the good string "aaabbc".

Example 3:

Input: s = "ceabaacb"
Output: 2
Explanation: You can delete both 'c's resulting in the good string "eabaab".
Note that we only care about characters that are still in the string at the end (i.e. frequency of 0 is ignored).


Constraints:

• 1 <= s.length <= 105
• s contains only lowercase English letters.

## Solution: Hashtable

The deletion order doesn’t matter, we can process from ‘a’ to ‘z’. Use a hashtable to store the “final frequency” so far, for each char, decrease its frequency until it becomes unique in the final frequency hashtable.

Time complexity: O(n + 26^2)
Space complexity: O(26)

## C++

You are given an array of distinct integers arr and an array of integer arrays pieces, where the integers in pieces are distinct. Your goal is to form arr by concatenating the arrays in pieces in any order. However, you are not allowed to reorder the integers in each array pieces[i].

Return true if it is possible to form the array arr from pieces. Otherwise, return false.

Example 1:

Input: arr = [85], pieces = [[85]]
Output: true


Example 2:

Input: arr = [15,88], pieces = [[88],[15]]
Output: true
Explanation: Concatenate [15] then [88]


Example 3:

Input: arr = [49,18,16], pieces = [[16,18,49]]
Output: false
Explanation: Even though the numbers match, we cannot reorder pieces[0].


Example 4:

Input: arr = [91,4,64,78], pieces = [[78],[4,64],[91]]
Output: true
Explanation: Concatenate [91] then [4,64] then [78]

Example 5:

Input: arr = [1,3,5,7], pieces = [[2,4,6,8]]
Output: false


Constraints:

• 1 <= pieces.length <= arr.length <= 100
• sum(pieces[i].length) == arr.length
• 1 <= pieces[i].length <= arr.length
• 1 <= arr[i], pieces[i][j] <= 100
• The integers in arr are distinct.
• The integers in pieces are distinct (i.e., If we flatten pieces in a 1D array, all the integers in this array are distinct).

## Solution: Hashtable

Store the index of the first number of each piece, for each number a in arr, concat the entire piece array whose first element equals to a.

Time complexity: O(n)
Space complexity: O(n)

## C++

Given an array of integers nums, sort the array in increasing order based on the frequency of the values. If multiple values have the same frequency, sort them in decreasing order.

Return the sorted array.

Example 1:

Input: nums = [1,1,2,2,2,3]
Output: [3,1,1,2,2,2]
Explanation: '3' has a frequency of 1, '1' has a frequency of 2, and '2' has a frequency of 3.


Example 2:

Input: nums = [2,3,1,3,2]
Output: [1,3,3,2,2]
Explanation: '2' and '3' both have a frequency of 2, so they are sorted in decreasing order.


Example 3:

Input: nums = [-1,1,-6,4,5,-6,1,4,1]
Output: [5,-1,4,4,-6,-6,1,1,1]

Constraints:

• 1 <= nums.length <= 100
• -100 <= nums[i] <= 100

## Solution: Hashtable + Sorting

Use a hashtable to track the frequency of each number.

Time complexity: O(nlogn)
Space complexity: O(n)

## C++

Given a string s, return the length of the longest substring between two equal characters, excluding the two characters. If there is no such substring return -1.

substring is a contiguous sequence of characters within a string.

Example 1:

Input: s = "aa"
Output: 0
Explanation: The optimal substring here is an empty substring between the two 'a's.

Example 2:

Input: s = "abca"
Output: 2
Explanation: The optimal substring here is "bc".


Example 3:

Input: s = "cbzxy"
Output: -1
Explanation: There are no characters that appear twice in s.


Example 4:

Input: s = "cabbac"
Output: 4
Explanation: The optimal substring here is "abba". Other non-optimal substrings include "bb" and "".


Constraints:

• 1 <= s.length <= 300
• s contains only lowercase English letters.

## Solution: Hashtable

Remember the first position each letter occurs.

Time complexity: O(n)
Space complexity: O(26)

## C++

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