Day 21

Advent of Code 2020 - 21.ipynb

@@ -0,0 +1,213 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import math"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "with open(r'C:\\Users\\stefa\\OneDrive\\Documents\\Python Scripts\\Problem 21 Input.txt') as f:\n",
+    "    lines = f.read().split('\\n')\n",
+    "lines = lines[:-1]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Part 1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for x in range(len(lines)):\n",
+    "    lines[x] = lines[x].replace('peanuts', 'peanuds')\n",
+    "    lines[x] = lines[x].replace('shellfish', 'shellfist')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ing_list =[]\n",
+    "aller_list = []\n",
+    "\n",
+    "for line in lines:\n",
+    "    \n",
+    "    ingred = line.split(\" (contains \")[0]\n",
+    "    aller = line.split(\" (contains \")[1][:-1]\n",
+    "    for x in ingred.split(\" \"):\n",
+    "        ing_list.append(x)\n",
+    "    for y in aller.split(\", \"):\n",
+    "        aller_list.append(y)\n",
+    "ing_list = list(set(ing_list))\n",
+    "aller_list = list(set(aller_list))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'fish': 'vhkj',\n",
+       " 'soy': 'dfzqlk',\n",
+       " 'peanuds': 'tvdvzd',\n",
+       " 'dairy': 'smfz',\n",
+       " 'sesame': 'lcb',\n",
+       " 'shellfist': 'lrqqqsg',\n",
+       " 'nuts': 'qzlmr',\n",
+       " 'wheat': 'shp'}"
+      ]
+     },
+     "execution_count": 60,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "aller_dict = {}\n",
+    "while len(aller_dict)<len(aller_list):\n",
+    "    for aller in aller_list:\n",
+    "        aller_line = [x for x in lines if aller in x]\n",
+    "        ing_list = [x for x in aller_line[0].split(\" (contains \")[0].split(' ')]\n",
+    "        for line in aller_line[1:]:\n",
+    "            ings = []\n",
+    "            ingred = line.split(\" (contains \")[0]\n",
+    "            for x in ingred.split(\" \"):\n",
+    "                if x not in aller_dict.values():\n",
+    "                    ings.append(x)\n",
+    "            ing_list = set(ing_list)&set(ings)\n",
+    "        if len(ing_list)==1:\n",
+    "            aller_dict[aller] = list(ing_list)[0]\n",
+    "        \n",
+    "aller_dict"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2302"
+      ]
+     },
+     "execution_count": 63,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "total_ing = 0\n",
+    "for x in range(len(lines)):\n",
+    "    line = lines[x].split(\" (contains \")[0]\n",
+    "    for ing in line.split(\" \"):\n",
+    "        if ing not in aller_dict.values():\n",
+    "            total_ing += 1\n",
+    "total_ing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "dict_values(['vhkj', 'dfzqlk', 'tvdvzd', 'smfz', 'lcb', 'lrqqqsg', 'qzlmr', 'shp'])"
+      ]
+     },
+     "execution_count": 62,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "aller_dict.values()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Part 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'smfz,vhkj,qzlmr,tvdvzd,lcb,lrqqqsg,dfzqlk,shp,'"
+      ]
+     },
+     "execution_count": 66,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "answer_list = ''\n",
+    "for i in sorted (aller_dict.keys()) :  \n",
+    "     answer_list = answer_list+(aller_dict.get(i))+',' \n",
+    "answer_list"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "[smfz,vhkj,qzlmr,tvdvzd,lcb,lrqqqsg,dfzqlk,shp]"
+   ]
+  }
+ ],
+ "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": "3.7.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}