Diagnoal Traverse

Author: Gaurav-pandey04

Arrays/Diagnoal_Traveres.ipynb

@@ -0,0 +1,85 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "d2398630",
+ "metadata": {},
+ "source": [
+ "# Diagnoal Traverse"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "0b663837",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[1, 2, 4, 7, 5, 3, 6, 8, 9]\n"
+ ]
+ }
+ ],
+ "source": [
+ "mat = [[1,2,3],[4,5,6],[7,8,9]]\n",
+ "\n",
+ "if not mat or not mat[0]:\n",
+ " print([])\n",
+ " \n",
+ "m, n = len(mat), len(mat[0])\n",
+ "res = []\n",
+ "row, col = 0, 0\n",
+ "up = True # direction flag\n",
+ "\n",
+ "for _ in range(m * n):\n",
+ " res.append(mat[row][col])\n",
+ " \n",
+ " if up: # moving up-right\n",
+ " if col == n - 1:\n",
+ " row += 1\n",
+ " up = False\n",
+ " elif row == 0:\n",
+ " col += 1\n",
+ " up = False\n",
+ " else:\n",
+ " row -= 1\n",
+ " col += 1\n",
+ " else: # moving down-left\n",
+ " if row == m - 1:\n",
+ " col += 1\n",
+ " up = True\n",
+ " elif col == 0:\n",
+ " row += 1\n",
+ " up = True\n",
+ " else:\n",
+ " row += 1\n",
+ " col -= 1\n",
+ "\n",
+ "print(res)"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.13.3"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

Arrays/Partition_array_into_k_parts.ipynb

@@ -0,0 +1,66 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "5a2ff0b4",
+ "metadata": {},
+ "source": [
+ "# Partition Array into K distinct parts"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "id": "dec09bb5",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "True\n"
+ ]
+ }
+ ],
+ "source": [
+ "from collections import Counter\n",
+ "\n",
+ "nums = [1,2,3,4]\n",
+ "k = 2\n",
+ "\n",
+ "if len(nums)%k != 0:\n",
+ " print(False)\n",
+ "\n",
+ "freq = Counter(nums)\n",
+ "groups = len(nums) // k\n",
+ "\n",
+ "for count in freq.values():\n",
+ " if count>groups:\n",
+ " print(False)\n",
+ "\n",
+ "print(True)"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.13.3"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

Maths/GCD_Odd_Even.ipynb

@@ -0,0 +1,60 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "294c6d05",
+ "metadata": {},
+ "source": [
+ "# GCD of N-th ODD & EVEN Number"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "id": "085c46ef",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "6"
+ ]
+ },
+ "execution_count": 9,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "n = 6\n",
+ "\n",
+ "def gcd(a, b):\n",
+ " while b:\n",
+ " a, b = b, a%b\n",
+ " return a\n",
+ "gcd(n**2, n*(n+1))"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.13.3"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}