{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ce4c1a2b",
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "import sqlite3\n",
    "con = sqlite3.connect(\"../orl.db\")\n",
    "cur = con.cursor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "b61785f6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([6.000e+00, 8.000e+00, 1.000e+01, 2.500e+01, 4.800e+01, 8.000e+01,\n",
       "        1.330e+02, 2.510e+02, 4.070e+02, 6.340e+02, 9.270e+02, 1.653e+03,\n",
       "        2.344e+03, 2.964e+03, 3.524e+03, 3.923e+03, 4.410e+03, 4.982e+03,\n",
       "        5.410e+03, 5.938e+03, 6.165e+03, 6.587e+03, 6.639e+03, 6.679e+03,\n",
       "        6.897e+03, 6.475e+03, 6.246e+03, 5.848e+03, 5.276e+03, 4.648e+03,\n",
       "        3.870e+03, 3.248e+03, 2.602e+03, 2.033e+03, 1.537e+03, 1.106e+03,\n",
       "        8.500e+02, 6.380e+02, 3.910e+02, 2.890e+02, 2.070e+02, 1.410e+02,\n",
       "        7.900e+01, 5.100e+01, 3.100e+01, 1.900e+01, 9.000e+00, 3.000e+00,\n",
       "        0.000e+00, 2.000e+00]),\n",
       " array([ 328.26643517,  373.24823537,  418.23003557,  463.21183577,\n",
       "         508.19363597,  553.17543618,  598.15723638,  643.13903658,\n",
       "         688.12083678,  733.10263698,  778.08443718,  823.06623738,\n",
       "         868.04803758,  913.02983778,  958.01163798, 1002.99343819,\n",
       "        1047.97523839, 1092.95703859, 1137.93883879, 1182.92063899,\n",
       "        1227.90243919, 1272.88423939, 1317.86603959, 1362.84783979,\n",
       "        1407.82963999, 1452.81144019, 1497.7932404 , 1542.7750406 ,\n",
       "        1587.7568408 , 1632.738641  , 1677.7204412 , 1722.7022414 ,\n",
       "        1767.6840416 , 1812.6658418 , 1857.647642  , 1902.6294422 ,\n",
       "        1947.61124241, 1992.59304261, 2037.57484281, 2082.55664301,\n",
       "        2127.53844321, 2172.52024341, 2217.50204361, 2262.48384381,\n",
       "        2307.46564401, 2352.44744421, 2397.42924442, 2442.41104462,\n",
       "        2487.39284482, 2532.37464502, 2577.35644522]),\n",
       " <BarContainer object of 50 artists>)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "users = cur.execute(\"SELECT elo FROM user, rating WHERE sig < 100 AND user.user_id = rating.user_id\")\n",
    "elos = []\n",
    "for u in users:\n",
    "    elos.append(u[0])\n",
    "\n",
    "plt.hist(elos, bins=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "236fa172",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.12.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}