{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "608c7b2a",
   "metadata": {},
   "source": [
    "# LEADERBOARD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e5396acf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                 w1     w2     w3     w4     w5     w6     w7     w8     w9    \n",
      "                  1 2 3  1 2 3  1 2 3  1 2 3  1 2 3  1 2 3  1 2 3  1 2 3  1 2 3\n",
      "         Jojo 26  ✓ ✓ ✓  ✓ ✓ ✓  ✓ ✓ ✓  ✓ ✓ ✓  ✓ ✓ ✓  ✓ ✓ ✗  ✓ ✓ ✓  ✓ ✓ ✓  ✓ ✓ ✓\n",
      "     PaulineS 25  ✓ ✓ ✓  ✓ ✓ ✓  ✓ ✓ ✓  ✓ ✓ ✓  ✗ ✓ ✓  ✓ ✓ ✗  ✓ ✓ ✓  ✓ ✓ ✓  ✓ ✓ ✓\n",
      "        David 25  ✓ ✓ ✓  ✓ ✗ ✓  ✓ ✓ ✓  ✗ ✓ ✓  ✓ ✓ ✓  ✓ ✓ ✓  ✓ ✓ ✓  ✓ ✓ ✓  ✓ ✓ ✓\n",
      " LeventeBuzga 21  ✓ ✓ ✓  ✓ ✓ ✓  - - -  ✓ ✓ ✓  ✓ ✓ ✓  ✓ ✓ ✓  ✓ ✓ ✓  - - -  ✓ ✓ ✓\n",
      "      AndrewK 19  ✗ ✓ ✓  ✗ ✓ ✓  ✓ ✓ ✓  ✓ ✓ ✓  ✗ ✓ ✓  ✗ ✓ ✓  ✓ ✓ ✓  ✓ ✓ ✗  - - -\n",
      "          pbn 17  ✓ ✓ ✗  ✗ ✓ ✗  ✗ ✓ ✓  ✗ ✓ ✓  ✓ ✓ ✓  ✗ ✓ ✗  ✓ ✓ ✓  ✓ ✓ ✓  - - -\n",
      "  SportySpice 16  ✓ ✓ ✗  ✗ ✗ ✗  ✓ ✓ ✓  ✓ ✓ ✓  ✓ ✓ ✓  ✓ ✓ ✗  ✗ ✗ ✗  ✓ ✓ ✓  - - -\n",
      "      Mathias 14  ✓ ✓ ✓  - - -  - - -  ✓ ✓ ✓  ✗ ✓ ✗  ✓ ✓ ✓  ✓ ✗ ✗  ✓ ✓ ✓  - - -\n",
      "       Rasmus 14  ✓ ✗ ✗  ✗ ✓ ✓  - - -  ✓ ✓ ✓  ✓ ✓ ✓  ✓ ✓ ✗  ✓ ✓ ✓  - - -  - - -\n",
      "Luca Saladino 13  ✓ ✓ ✓  - - -  ✓ ✗ ✓  ✓ ✓ ✓  ✓ ✓ ✓  ✓ ✗ ✗  ✓ ✗ ✗  - - -  - - -\n",
      "           mp 13  ✓ ✓ ✓  - - -  ✗ ✓ ✓  ✗ ✓ ✓  ✓ ✓ ✓  - - -  ✓ ✓ ✓  - - -  - - -\n",
      "     johnslim 11  ✗ ✓ ✓  - - -  ✓ ✓ ✓  ✓ ✓ ✓  ✓ ✓ ✓  - - -  - - -  - - -  - - -\n",
      "     andreama  9  ✓ ✗ ✗  ✗ ✗ ✗  ✗ ✗ ✗  ✓ ✓ ✓  ✗ ✓ ✗  ✓ ✗ ✗  ✓ ✓ ✓  ✗ ✗ ✗  - - -\n",
      "        vince  9  ✓ ✓ ✗  ✗ ✗ ✓  ✓ ✓ ✓  ✓ ✓ ✗  ✓ ✗ ✗  - - -  - - -  - - -  - - -\n",
      "      Anonyms  7  ✓ ✗ ✗  ✓ ✗ ✓  ✗ ✓ ✓  ✓ ✓ ✗  - - -  - - -  - - -  - - -  - - -\n",
      "Thomas Hornum  4  ✗ ✓ ✗  - - -  - - -  - - -  - - -  - - -  ✓ ✓ ✓  - - -  - - -\n",
      "   kathariner  3  ✗ ✗ ✓  - - -  - - -  ✓ ✓ ✗  - - -  - - -  - - -  - - -  - - -\n",
      "  KnudMondrup  2  ✓ ✓ ✗  - - -  - - -  - - -  - - -  - - -  - - -  - - -  - - -\n",
      "         Emil  2  ✓ ✓ ✗  - - -  - - -  - - -  - - -  - - -  - - -  - - -  - - -\n",
      "       Anna_E  2  ✓ ✗ ✓  - - -  - - -  - - -  - - -  - - -  - - -  - - -  - - -\n",
      "   kathariner  2  - - -  - - -  - - -  - - -  ✓ ✓ ✗  - - -  - - -  - - -  - - -\n",
      "        JensL  2  ✓ ✓ ✗  - - -  - - -  - - -  - - -  - - -  - - -  - - -  - - -\n",
      "     Joakim_P  2  ✓ ✗ ✗  - - -  - - -  - - -  ✗ ✓ ✗  - - -  - - -  - - -  - - -\n",
      "        Sofia  1  ✓ ✗ ✗  - - -  - - -  - - -  - - -  - - -  - - -  - - -  - - -\n",
      "  JBorregaard  1  ✗ ✓ ✗  - - -  - - -  - - -  - - -  - - -  - - -  - - -  - - -\n",
      "       snoopy  1  ✓ ✗ ✗  - - -  - - -  - - -  - - -  - - -  - - -  - - -  - - -\n",
      "        Ninna  1  ✗ ✗ ✓  - - -  - - -  - - -  - - -  - - -  - - -  - - -  - - -\n",
      " GenieVickery  1  ✓ ✗ ✗  - - -  - - -  - - -  - - -  - - -  - - -  - - -  - - -\n",
      "        Jerry  1  ✓ ✗ ✗  - - -  - - -  - - -  - - -  - - -  - - -  - - -  - - -\n",
      "          JWH  1  ✓ ✗ ✗  - - -  - - -  - - -  - - -  - - -  - - -  - - -  - - -\n",
      "     100rocks  0  ✗ ✗ ✗  - - -  - - -  - - -  - - -  - - -  - - -  - - -  - - -\n"
     ]
    }
   ],
   "source": [
    "import quizzes_helper as qh\n",
    "summary = qh.combine_weeks('_SUBMISSIONS/', week_list = [1, 2, 3, 4, 5, 6, 7, 8, 10])\n",
    "qh.print_leaderboard(summary)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ddf7eb78",
   "metadata": {},
   "source": [
    "# At the end of the course - finding the lucky quiz participant"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a0d98b67",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "qh.plot_overview(summary)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "65872a3f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " display name  from  to\n",
      "         Jojo     0  26\n",
      "     PaulineS    27  53\n",
      "        David    54  80\n",
      " LeventeBuzga    81 101\n",
      "      AndrewK   102 125\n",
      "          pbn   126 149\n",
      "  SportySpice   150 173\n",
      "      Mathias   174 191\n",
      "       Rasmus   192 209\n",
      "Luca Saladino   210 227\n",
      "           mp   228 242\n",
      "     johnslim   243 254\n",
      "     andreama   255 278\n",
      "        vince   279 293\n",
      "      Anonyms   294 305\n",
      "Thomas Hornum   306 311\n",
      "   kathariner   312 317\n",
      "  KnudMondrup   318 320\n",
      "         Emil   321 323\n",
      "       Anna_E   324 326\n",
      "   kathariner   327 329\n",
      "        JensL   330 332\n",
      "     Joakim_P   333 338\n",
      "        Sofia   339 341\n",
      "  JBorregaard   342 344\n",
      "       snoopy   345 347\n",
      "        Ninna   348 350\n",
      " GenieVickery   351 353\n",
      "        Jerry   354 356\n",
      "          JWH   357 359\n",
      "     100rocks   360 362\n"
     ]
    }
   ],
   "source": [
    "chance = summary[['display name']].copy()\n",
    "chance[['from', 'to']] = 0\n",
    "chance['to'] = summary.iloc[:, 2:].notna().sum(axis=1).cumsum()\n",
    "chance['from'] = chance['to'].shift(1).fillna(0).astype(int) \n",
    "chance['to'] = chance['to'] - 1\n",
    "print(chance.to_string(index=False, header=True))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4c14c648",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Random number is 178\n",
      "Lucky quiz participant is Mathias\n"
     ]
    }
   ],
   "source": [
    "import random\n",
    "import time\n",
    "random.seed(time.time())\n",
    "i = random.randint(0, chance['to'][-1])\n",
    "print(f'Random number is {i}')\n",
    "winner = (chance['from']<= i) & (chance['to']>= i)\n",
    "print(f'Lucky quiz participant is {chance[winner][\"display name\"].values[0]}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "feb044aa",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "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": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}