Code Log - Day 10

Log

Today i solved a LeetCode exercise from the Top 150 Interview Questions list and worked on an assignment from my university.

LeetCode

The LeetCode exercise i chose was: Remove Duplicates from Sorted Array II. It requires a function that receive as input an integer array to remove in-place the numbers that already appeared more than two times and return the number of numbers left:

Given an integer array nums sorted in non-decreasing order, remove some duplicates in-place such that each unique element appears at most twice. The relative order of the elements should be kept the same. ... the first k elements of nums should hold the final result. Return k after placing the final result in the first k slots of nums.

The solution was basically the same as the Remove Duplicates from Sorted Array I, but with a number appearance count check:

class Solution {

public int removeDuplicates(int[] nums) {

    if (
        nums.length < 1 ||
        nums.length > 30000 ||
        nums[0] < -100 ||
        nums[nums.length - 1] > 100
    ) return 0;


    // starts with both idx 1 because the minimum arr.len is 1
    // and the comparison must be done using the previous number
    int len = 1;
    int dups = 0;

    for (int i = 1; i < nums.length; i++) {

        // compare i with i-1
        if (nums[i] != nums[i - 1]) {
            // nums[len] is the number after the last unique number
            nums[len] = nums[i];
            dups = 0;
            len++;
        } else if(nums[i] == nums[i - 1] && dups < 1){
            nums[len] = nums[i];
            dups++;
            len++;
        }

    }
    return len;
    }
}

Assignments

I finished the assignment from the Machine Learning class, where i had to demonstrate how to make a symbolic-numeric attribute conversion with python. To be more specific, the one that was missing is the symbolic-numeric attribute using pseudo-attributes, so i made a python dictionary with an unique data combination for each author, and then i mapped these objects to the pandas data frame.