April_1_Codeforces.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# April fool's Contest on Codeforces Analysis\n",
    "After ranking much higher on Fool's contest and noticing that tourist got top score even in the joke contest, I wanted to answer some interesting questions:\n",
    "1. Who participated in the contest (population)?\n",
    "2. Correlation between competitive rating and rank?\n",
    "\n",
    "Let's get to it!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First things first, let's pull up our data using [Codeforces API](https://codeforces.com/apiHelp/objects#Contest)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "import pandas as pd\n",
    "import json\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['status', 'result'])"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "contestId = 1331\n",
    "r = requests.get(f\"https://codeforces.com/api/contest.standings?contestId={contestId}\")\n",
    "parsed_data = json.loads(r.content)\n",
    "\n",
    "parsed_data.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11391"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(parsed_data['result']['rows'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's just find ranks for now. The rank 1 would be tourist, so he should be the first elem in the list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'party': {'contestId': 1331,\n",
       "  'members': [{'handle': 'tourist'}],\n",
       "  'participantType': 'CONTESTANT',\n",
       "  'ghost': False,\n",
       "  'startTimeSeconds': 1585751700},\n",
       " 'rank': 1,\n",
       " 'points': 8.0,\n",
       " 'penalty': 231,\n",
       " 'successfulHackCount': 0,\n",
       " 'unsuccessfulHackCount': 0,\n",
       " 'problemResults': [{'points': 1.0,\n",
       "   'rejectedAttemptCount': 0,\n",
       "   'type': 'FINAL',\n",
       "   'bestSubmissionTimeSeconds': 190},\n",
       "  {'points': 1.0,\n",
       "   'rejectedAttemptCount': 0,\n",
       "   'type': 'FINAL',\n",
       "   'bestSubmissionTimeSeconds': 3589},\n",
       "  {'points': 1.0,\n",
       "   'rejectedAttemptCount': 0,\n",
       "   'type': 'FINAL',\n",
       "   'bestSubmissionTimeSeconds': 1215},\n",
       "  {'points': 1.0,\n",
       "   'rejectedAttemptCount': 0,\n",
       "   'type': 'FINAL',\n",
       "   'bestSubmissionTimeSeconds': 1276},\n",
       "  {'points': 1.0,\n",
       "   'rejectedAttemptCount': 0,\n",
       "   'type': 'FINAL',\n",
       "   'bestSubmissionTimeSeconds': 1768},\n",
       "  {'points': 1.0,\n",
       "   'rejectedAttemptCount': 0,\n",
       "   'type': 'FINAL',\n",
       "   'bestSubmissionTimeSeconds': 486},\n",
       "  {'points': 1.0,\n",
       "   'rejectedAttemptCount': 0,\n",
       "   'type': 'FINAL',\n",
       "   'bestSubmissionTimeSeconds': 2206},\n",
       "  {'points': 1.0,\n",
       "   'rejectedAttemptCount': 0,\n",
       "   'type': 'FINAL',\n",
       "   'bestSubmissionTimeSeconds': 3353}]}"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "parsed_data['result']['rows'][0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After taking a closer look at the data, we see that this object doesn't actually contain user's ranking. Since the contest was unrated, contest.ratingChanges also returns FAIL status, which is unfortunate since we cannot easily get their ranks. Two solutions to this that come to mind:\n",
    "\n",
    "1. Look up each users rating individually\n",
    "2. Look up last Div 1, 2, 3 contests, request contest.ratingChanges from them and remove users that didn't take one of them. We should get a pretty good approximation and, hopefully, a good portion of ratings.\n",
    "\n",
    "I'll try the second approach since I don't think that asking 11,391 requests is a good idea\n",
    "\n",
    "Edit: After reading API documentation, I've noticed the user.ratedList method - \"Returns the list users who have participated in at least one rated contest\". Good. If you suspect that you are reinventing a bicycle, you probably are. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "ra = requests.get(\"https://codeforces.com/api/user.ratedList?activeOnly=true\") #activeOnly=true shows users active this month\n",
    "ra_parsed_data = json.loads(ra.content)\n",
    "data = ra_parsed_data['result']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'lastName': 'Korotkevich',\n",
       " 'country': 'Belarus',\n",
       " 'lastOnlineTimeSeconds': 1585780139,\n",
       " 'city': 'Gomel',\n",
       " 'rating': 3669,\n",
       " 'friendOfCount': 24180,\n",
       " 'titlePhoto': '//userpic.codeforces.com/422/title/50a270ed4a722867.jpg',\n",
       " 'handle': 'tourist',\n",
       " 'avatar': '//userpic.codeforces.com/422/avatar/2b5dbe87f0d859a2.jpg',\n",
       " 'firstName': 'Gennady',\n",
       " 'contribution': 182,\n",
       " 'organization': 'ITMO University',\n",
       " 'rank': 'legendary grandmaster',\n",
       " 'maxRating': 3739,\n",
       " 'registrationTimeSeconds': 1265987288,\n",
       " 'maxRank': 'legendary grandmaster'}"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_active_users():\n",
    "    r = requests.get(\"https://codeforces.com/api/user.ratedList?activeOnly=true\")\n",
    "    parsed_data = json.loads(r.content)\n",
    "    \n",
    "    if parsed_data['status'] == \"OK\":\n",
    "        data = parsed_data['result']\n",
    "        cleaned_data = {}\n",
    "        for each in data:\n",
    "            handle = each['handle']\n",
    "            rating = each['rating']\n",
    "            cleaned_data[handle] = rating\n",
    "        return cleaned_data\n",
    "    else:\n",
    "        return -1\n",
    "\n",
    "cleaned_active = get_active_users()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_contest_scoreboard(contestId=1331):\n",
    "    r = requests.get(f\"https://codeforces.com/api/contest.standings?contestId={contestId}\")\n",
    "    parsed_data = json.loads(r.content)\n",
    "    \n",
    "    if parsed_data['status'] == \"OK\":\n",
    "        data = parsed_data['result']['rows']\n",
    "        cleaned_data = {}\n",
    "        for each in data:\n",
    "            handle = each['party']['members'][0]['handle']\n",
    "            rank = each['rank']\n",
    "            cleaned_data[handle] = rank\n",
    "        return cleaned_data\n",
    "    else:\n",
    "        return -1\n",
    "\n",
    "cleaned_scoreboard = get_contest_scoreboard()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "36818"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(cleaned_active)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1715"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cleaned_active['RMILKA']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11391"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(cleaned_scoreboard)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "390"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cleaned_scoreboard['RMILKA']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Good. My rating is indeed 1715, and I got 390th place in the contest, so matches out. Notice that during last month we had 36818 users, and 11391 participated in the last contest. Let's see how many of those participated"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8597"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(set(cleaned_active.keys()).intersection(set(cleaned_scoreboard.keys())))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Not bad, we have rating info for 8597 out of 11391 users"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "good_handles = set(cleaned_active.keys()).intersection(set(cleaned_scoreboard.keys()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "combined = []\n",
    "for handle in good_handles:\n",
    "    combined.append({'handle': handle,\n",
    "                    'rating':cleaned_active[handle],\n",
    "                    'rank':cleaned_scoreboard[handle]})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame(data=combined)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x11c3d5690>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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MAMD0RDEAANMTxQAATE8UAwAwPVEMAMD0RDEAANM7pm+0AwA4Gd730BNr8rjf98qz1+Rx2fycKQYAYHqiGACA6bl8Atgy/LkVgOMligE2EGEPsD5cPgEAwPScKWbdOTMGAKw3Z4oBAJieKAYAYHoun4AFcAkIAGxuzhQDADA9UQwAwPRcPgHApuJyJWAtiGKm4B9RFsF/RwBbl8snAACYnjPFa8yZJQCAjc+ZYgAApieKAQCYnigGAGB6rikGkrj+HYC5ieJNTsgAAJw4UQybhP8BAoC1I4oBJuJ/rgBenDfaAQAwPVEMAMD0RDEAANMTxQAATE8UAwAwPVEMAMD0fCQbAJxkPhoPNp7po9gvJgCOtBX+bdgKrwFOpqNGcVW9NMkfJjl1rH9zd7+tqs5P8p4kZyW5J8kPdPfnq+rUJDcm+aYkn0ryj7r7E2u0/ZwEfrECx8LvDGAzWs01xX+Z5HXd/Y1JXpXk9VV1cZK3J3lHd39dkmeSXD3WvzrJM2P8HWM9AADYsI56pri7O8mfj9mvGLdO8rok/3iM70/y00muS7JnTCfJzUl+uapqPA4wMWcQAdioVvXpE1V1SlXdm+TpJLcn+ViSZ7v7+bHK40l2jeldSR5LkrH8uSxfYgEAABvSqqK4u/+qu1+V5Jwkr0ny9Sf6xFW1r6oOVNWBpaWlE304AAA4bsf0OcXd/WySO5N8c5LtVXX48otzkhwa04eSnJskY/npWX7D3ZGPdX137+7u3Tt27DjOzQcAgBN31Ciuqh1VtX1MvyzJdyR5MMtx/Iax2t4kt4zpW8d8xvIPuJ4YAICNbDWfU3x2kv1VdUqWI/qm7n5/VT2Q5D1V9e+SfCjJDWP9G5L8RlUdTPLpJFeswXYDAMDCrObTJ+5L8uoXGX8ky9cXHzn+F0neuJCtAwCAk+CYrikGAICtSBQDADC91VxTDADwAr6Mh63GmWIAAKbnTDEAwBpwNn1zcaYYAIDpiWIAAKbn8gkAYEoub2AlZ4oBAJieKAYAYHqiGACA6YliAACmJ4oBAJieKAYAYHqiGACA6YliAACmJ4oBAJieKAYAYHq+5hkAYJPyVdWL40wxAADTE8UAAExPFAMAMD1RDADA9EQxAADTE8UAAExPFAMAMD1RDADA9EQxAADTE8UAAExPFAMAMD1RDADA9EQxAADTE8UAAExPFAMAMD1RDADA9EQxAADTE8UAAExPFAMAMD1RDADA9EQxAADTO2oUV9W5VXVnVT1QVR+pqh8Z42dW1e1V9fD4ecYYr6q6tqoOVtV9VXXRWr8IAAA4Eas5U/x8kn/V3RcmuTjJW6rqwiTXJLmjuy9IcseYT5JLk1wwbvuSXLfwrQYAgAU6ahR39xPd/cEx/WdJHkyyK8meJPvHavuTXD6m9yS5sZfdlWR7VZ298C0HAIAFOaZriqvqvCSvTnJ3kp3d/cRY9GSSnWN6V5LHVtzt8TEGAAAb0qqjuKq+MsnvJPnR7v7MymXd3Un6WJ64qvZV1YGqOrC0tHQsdwUAgIVaVRRX1VdkOYh/s7vfN4afOnxZxPj59Bg/lOTcFXc/Z4y9QHdf3927u3v3jh07jnf7AQDghK3m0ycqyQ1JHuzuX1ix6NYke8f03iS3rBi/cnwKxcVJnltxmQUAAGw421axzmuT/ECSD1fVvWPs3yT52SQ3VdXVSR5N8qax7LYklyU5mORzSa5a6BYDAMCCHTWKu/uPktSXWXzJi6zfSd5ygtsFAAAnjW+0AwBgeqIYAIDpiWIAAKYnigEAmJ4oBgBgeqIYAIDpiWIAAKYnigEAmJ4oBgBgeqIYAIDpiWIAAKYnigEAmJ4oBgBgeqIYAIDpiWIAAKYnigEAmJ4oBgBgeqIYAIDpiWIAAKYnigEAmJ4oBgBgeqIYAIDpiWIAAKYnigEAmJ4oBgBgeqIYAIDpiWIAAKYnigEAmJ4oBgBgeqIYAIDpiWIAAKYnigEAmJ4oBgBgeqIYAIDpiWIAAKYnigEAmJ4oBgBgeqIYAIDpiWIAAKYnigEAmJ4oBgBgekeN4qp6V1U9XVX3rxg7s6pur6qHx88zxnhV1bVVdbCq7quqi9Zy4wEAYBFWc6b4PyZ5/RFj1yS5o7svSHLHmE+SS5NcMG77kly3mM0EAIC1c9Qo7u4/TPLpI4b3JNk/pvcnuXzF+I297K4k26vq7EVtLAAArIXjvaZ4Z3c/MaafTLJzTO9K8tiK9R4fY/+fqtpXVQeq6sDS0tJxbgYAAJy4E36jXXd3kj6O+13f3bu7e/eOHTtOdDMAAOC4HW8UP3X4sojx8+kxfijJuSvWO2eMAQDAhnW8UXxrkr1jem+SW1aMXzk+heLiJM+tuMwCAAA2pG1HW6Gq3p3k25K8oqoeT/K2JD+b5KaqujrJo0neNFa/LcllSQ4m+VySq9ZgmwEAYKGOGsXd/eYvs+iSF1m3k7zlRDcKAABOJt9oBwDA9EQxAADTE8UAAExPFAMAMD1RDADA9EQxAADTE8UAAExPFAMAMD1RDADA9EQxAADTE8UAAExPFAMAMD1RDADA9EQxAADTE8UAAExPFAMAMD1RDADA9EQxAADTE8UAAExPFAMAMD1RDADA9EQxAADTE8UAAExPFAMAMD1RDADA9EQxAADTE8UAAExPFAMAMD1RDADA9EQxAADTE8UAAExPFAMAMD1RDADA9EQxAADTE8UAAExPFAMAMD1RDADA9EQxAADTE8UAAExPFAMAML01ieKqen1VPVRVB6vqmrV4DgAAWJSFR3FVnZLkV5JcmuTCJG+uqgsX/TwAALAoa3Gm+DVJDnb3I939+STvSbJnDZ4HAAAWYi2ieFeSx1bMPz7GAABgQ9q2Xk9cVfuS7Buzf15VD53kTXhFkj89yc/J2rNfty77dmuyX7cm+3Vr2ir79WtebHAtovhQknNXzJ8zxl6gu69Pcv0aPP+qVNWB7t69Xs/P2rBfty77dmuyX7cm+3Vr2ur7dS0un/jjJBdU1flV9ZIkVyS5dQ2eBwAAFmLhZ4q7+/mq+uEkv5/klCTv6u6PLPp5AABgUdbkmuLuvi3JbWvx2Au0bpdusKbs163Lvt2a7NetyX7dmrb0fq3uXu9tAACAdeVrngEAmN6UUexrqDeXqjq3qu6sqgeq6iNV9SNj/Myqur2qHh4/zxjjVVXXjv17X1VdtOKx9o71H66qvev1mviSqjqlqj5UVe8f8+dX1d1j/713vGE3VXXqmD84lp+34jF+cow/VFXftT6vhMOqantV3VxVH62qB6vqmx2vm19V/dj4HXx/Vb27ql7qeN2cqupdVfV0Vd2/Ymxhx2hVfVNVfXjc59qqqpP7Co9Td091y/Kb/z6W5GuTvCTJ/05y4Xpvl9vfuM/OTnLRmP6qJH+S5a8Q/7kk14zxa5K8fUxfluS/JKkkFye5e4yfmeSR8fOMMX3Ger++2W9J3prkt5K8f8zflOSKMf2rSf7ZmP7nSX51TF+R5L1j+sJxHJ+a5PxxfJ+y3q9r5luS/Ul+aEy/JMl2x+vmvmX5S7g+nuRlY/6mJD/oeN2ctyTfmuSiJPevGFvYMZrkf411a9z30vV+zau5zXim2NdQbzLd/UR3f3BM/1mSB7P8C3pPlv/xzfh5+Zjek+TGXnZXku1VdXaS70pye3d/urufSXJ7ktefxJfCEarqnCTfneSdY76SvC7JzWOVI/fr4f19c5JLxvp7krynu/+yuz+e5GCWj3PWQVWdnuV/cG9Iku7+fHc/G8frVrAtycuqaluSlyd5Io7XTam7/zDJp48YXsgxOpb97e6+q5cL+cYVj7WhzRjFvoZ6Ext/gnt1kruT7OzuJ8aiJ5PsHNNfbh/b9xvPLyb58SR/PebPSvJsdz8/5lfuoy/uv7H8ubG+/bqxnJ9kKcmvj8ti3llVp8Xxuql196EkP5/kk1mO4eeS3BPH61ayqGN015g+cnzDmzGK2aSq6iuT/E6SH+3uz6xcNv5v1EepbCJV9T1Jnu7ue9Z7W1iobVn+s+x13f3qJJ/N8p9iv8jxuvmM60v3ZPl/er46yWlx5n7LmvUYnTGKV/U11GwsVfUVWQ7i3+zu943hp8afaTJ+Pj3Gv9w+tu83ltcm+d6q+kSWL2N6XZJfyvKf5g5/hvrKffTF/TeWn57kU7FfN5rHkzze3XeP+ZuzHMmO183t25N8vLuXuvsLSd6X5WPY8bp1LOoYPTSmjxzf8GaMYl9DvcmM69BuSPJgd//CikW3Jjn8bte9SW5ZMX7leMfsxUmeG38S+v0k31lVZ4yzHt85xlgH3f2T3X1Od5+X5ePwA939/UnuTPKGsdqR+/Xw/n7DWL/H+BXj3e7nJ7kgy2/yYB1095NJHquqV46hS5I8EMfrZvfJJBdX1cvH7+TD+9XxunUs5Bgdyz5TVReP/1auXPFYG9t6v9NvPW5Zfifln2T5Xa8/td7b43bU/fUtWf4zzn1J7h23y7J8fdodSR5O8t+SnDnWryS/Mvbvh5PsXvFY/yTLb+w4mOSq9X5tbl/cL9+WL336xNdm+R/Jg0l+O8mpY/ylY/7gWP61K+7/U2N/P5RN8i7nrXxL8qokB8Yx+5+z/M50x+smvyX5mSQfTXJ/kt/I8idIOF434S3Ju7N8bfgXsvzXnasXeYwm2T3+O/lYkl/O+LK4jX7zjXYAAExvxssnAADgBUQxAADTE8UAAExPFAMAMD1RDADA9EQxAADTE8UAAExPFAMAML3/B+bQxKRsiLjWAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.hist(column='rank', bins=25, grid=False, figsize=(12,8), color='#add8e6', zorder=2, rwidth=0.9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x1149c4790>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAswAAAHiCAYAAAD8n5rBAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAcm0lEQVR4nO3df/BldX3f8de7oCRVE1C2BPkR0EFTtelGt8RM1NnGRpF2grZOCu0EYkw2NjIk03Qat2mrScPQ/CDO7NTiYKVgfqAmxko7pIYYiZNOUBezwQUlLIrDblfYSNQkZqjgu398z+J12f2w+733+2N3H4+ZO99zP/fc8z3fz9y5PDl77rnV3QEAAA7ub631DgAAwHommAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzwDGmqt5eVf9hrfcD4FhRrsMMcPSqqh9O8qPd/ZK13heAY5UjzADrWFWduNb7AHC8E8wA60xV3VdVP1NVdyT566r691V1b1X9ZVXdVVWvmdb7u0nenuR7quqvquqL0/j1VfUL0/LmqtpdVT9dVQ9W1d6qet3M73pGVf3PqvpyVX28qn6hqv5oDf5sgHVLMAOsT5ck+cdJTk5yd5KXJvnWJD+X5Ner6vTu/lSSNyT54+5+aneffIhtfdv03DOSvD7J26rqlOmxtyX562mdy6YbADMEM8D6tK277+/uv+nu3+ru/9vdX+vu9yS5J8n5R7Ctryb5+e7+anffnOSvkjy3qk5I8s+SvLm7v9LddyW5YeF/CcBRTjADrE/371+oqkurakdVfXE67eIFSU49gm19obsfmbn/lSRPTbIhyYmzv+uAZQAimAHWq06Sqvr2JO9IcnmSZ0ynXexMUrPrLdO+JI8kOXNm7Kw5tgdwTBLMAOvbU7IUxfuSZPrA3gtmHn8gyZlV9eQj3XB3P5rkd5K8par+dlV9R5JL599lgGOLYAZYx6bziq9O8sdZiuO/l+T/zKzyB0nuTPL5qvrzZfyKy7P0gcDPJ/m1JDcmeXiefQY41vjiEgAeU1W/mOTbutvVMgAmjjADHMeq6juq6jtryflZuuzc+9d6vwDWE98gBXB8e1qWTsN4ZpZO+bg6yQfWdI8A1hmnZAAAwIBTMgAAYEAwAwDAwLo/h/nUU0/tc845Z613AwCAY9jtt9/+59294WCPrftgPuecc7J9+/a13g0AAI5hVfW5Qz3mlAwAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAADghkAAAYEMwAADAhmAAAYeMJgrqrrqurBqto5M/aeqtox3e6rqh3T+DlV9Tczj7195jkvqqpPVtWuqtpWVbUyfxIAACzOiYexzvVJ/kuSd+0f6O5/vn+5qq5O8qWZ9e/t7o0H2c41SX4syUeT3JzkgiS/e+S7DAAAq+cJg7m7P1JV5xzsseko8Q8m+b7RNqrq9CTf0t23TfffleTVEcxwTLjq1m0L2c7WzVcsZDsAsEjznsP80iQPdPc9M2PnVtWfVNUfVtVLp7EzkuyeWWf3NHZQVbWlqrZX1fZ9+/bNuYsAALB88wbzJUlunLm/N8nZ3f1dSf51kt+sqm850o1297Xdvam7N23YsGHOXQQAgOU7nHOYD6qqTkzyT5O8aP9Ydz+c5OFp+faqujfJc5LsSXLmzNPPnMYAAGBdm+cI8z9K8unufuxUi6raUFUnTMvPSnJeks90994kX66qF0/nPV+a5ANz/G4AAFgVh3NZuRuT/HGS51bV7qp6/fTQxfnG0zGS5GVJ7pguM/fbSd7Q3Q9Nj/1Ekv+WZFeSe+MDfwAAHAUO5yoZlxxi/IcPMva+JO87xPrbk7zgCPcPAADWlG/6AwCAAcEMAAADghkAAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAADghkAAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAgScM5qq6rqoerKqdM2Nvqao9VbVjul0489jWqtpVVXdX1Stnxi+YxnZV1ZsW/6cAAMDiHc4R5uuTXHCQ8bd298bpdnOSVNXzklyc5PnTc/5rVZ1QVSckeVuSVyV5XpJLpnUBAGBdO/GJVujuj1TVOYe5vYuSvLu7H07y2araleT86bFd3f2ZJKmqd0/r3nXEewwAAKtonnOYL6+qO6ZTNk6Zxs5Icv/MOrunsUONAwDAurbcYL4mybOTbEyyN8nVC9ujJFW1paq2V9X2ffv2LXLTAABwRJYVzN39QHc/2t1fS/KOfP20iz1JzppZ9cxp7FDjh9r+td29qbs3bdiwYTm7CAAAC/GE5zAfTFWd3t17p7uvSbL/Cho3JfnNqvrVJM9Mcl6SjyWpJOdV1blZCuWLk/yLeXYcWJ6rbt22sG1t3XzFwrYFAOvVEwZzVd2YZHOSU6tqd5I3J9lcVRuTdJL7kvx4knT3nVX13ix9mO+RJG/s7ken7Vye5INJTkhyXXffufC/BgAAFuxwrpJxyUGG3zlY/8okVx5k/OYkNx/R3gEAwBrzTX8AADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAADghkAAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAADghkAAAYEMwAADAhmAAAYEMwAADAgmAEAYOAJg7mqrquqB6tq58zYL1fVp6vqjqp6f1WdPI2fU1V/U1U7ptvbZ57zoqr6ZFXtqqptVVUr8ycBAMDiHM4R5uuTXHDA2C1JXtDd35nkz5JsnXns3u7eON3eMDN+TZIfS3LedDtwmwAAsO48YTB390eSPHTA2O919yPT3duSnDnaRlWdnuRbuvu27u4k70ry6uXtMgAArJ5FnMP8I0l+d+b+uVX1J1X1h1X10mnsjCS7Z9bZPY0BAMC6duI8T66qn03ySJLfmIb2Jjm7u79QVS9K8j+q6vnL2O6WJFuS5Oyzz55nFwEAYC7LPsJcVT+c5J8k+ZfTaRbp7oe7+wvT8u1J7k3ynCR78o2nbZw5jR1Ud1/b3Zu6e9OGDRuWu4sAADC3ZQVzVV2Q5N8m+YHu/srM+IaqOmFaflaWPtz3me7em+TLVfXi6eoYlyb5wNx7DwAAK+wJT8moqhuTbE5yalXtTvLmLF0V46Qkt0xXh7ttuiLGy5L8fFV9NcnXkryhu/d/YPAnsnTFjW/O0jnPs+c9AwDAuvSEwdzdlxxk+J2HWPd9Sd53iMe2J3nBEe0dAACsMd/0BwAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAADghkAAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGTlzrHQA40FW3blvIdrZuvmIh2wHg+OYIMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAADhxXMVXVdVT1YVTtnxp5eVbdU1T3Tz1Om8aqqbVW1q6ruqKoXzjznsmn9e6rqssX/OQAAsFiHe4T5+iQXHDD2piQf6u7zknxoup8kr0py3nTbkuSaZCmwk7w5yXcnOT/Jm/dHNgAArFeHFczd/ZEkDx0wfFGSG6blG5K8emb8Xb3ktiQnV9XpSV6Z5Jbufqi7/yLJLXl8hAMAwLoyzznMp3X33mn580lOm5bPSHL/zHq7p7FDjQMAwLq1kA/9dXcn6UVsK0mqaktVba+q7fv27VvUZgEA4IjNE8wPTKdaZPr54DS+J8lZM+udOY0davxxuvva7t7U3Zs2bNgwxy4CAMB85gnmm5Lsv9LFZUk+MDN+6XS1jBcn+dJ06sYHk7yiqk6ZPuz3imkMAADWrRMPZ6WqujHJ5iSnVtXuLF3t4j8neW9VvT7J55L84LT6zUkuTLIryVeSvC5JuvuhqvpPST4+rffz3X3gBwmBA1x167aFbGfr5isWsh0AON4cVjB39yWHeOjlB1m3k7zxENu5Lsl1h713AACwxnzTHwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAADghkAAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAADghkAAAYEMwAADAhmAAAYWHYwV9Vzq2rHzO3LVfVTVfWWqtozM37hzHO2VtWuqrq7ql65mD8BAABWzonLfWJ3351kY5JU1QlJ9iR5f5LXJXlrd//K7PpV9bwkFyd5fpJnJvn9qnpOdz+63H0AAICVtqhTMl6e5N7u/txgnYuSvLu7H+7uzybZleT8Bf1+AABYEYsK5ouT3Dhz//KquqOqrquqU6axM5LcP7PO7mkMAADWrbmDuaqenOQHkvzWNHRNkmdn6XSNvUmuXsY2t1TV9qravm/fvnl3EQAAlm0RR5hfleQT3f1AknT3A939aHd/Lck78vXTLvYkOWvmeWdOY4/T3dd296bu3rRhw4YF7CIAACzPIoL5ksycjlFVp8889pokO6flm5JcXFUnVdW5Sc5L8rEF/H4AAFgxy75KRpJU1VOSfH+SH58Z/qWq2pikk9y3/7HuvrOq3pvkriSPJHmjK2QAALDezRXM3f3XSZ5xwNgPDda/MsmV8/xOAABYTb7pDwAABgQzAAAMCGYAABiY6xxmgKPBVbduW9i2tm6+YmHbAuDo4AgzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAADghkAAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwcOJa7wAca666ddtCtrN18xUL2Q4AMB9HmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMuKwcwDK4fCDA8cMRZgAAGBDMAAAwIJgBAGBg7mCuqvuq6pNVtaOqtk9jT6+qW6rqnunnKdN4VdW2qtpVVXdU1Qvn/f0AALCSFnWE+R9298bu3jTdf1OSD3X3eUk+NN1PklclOW+6bUlyzYJ+PwAArIiVOiXjoiQ3TMs3JHn1zPi7esltSU6uqtNXaB8AAGBuiwjmTvJ7VXV7VW2Zxk7r7r3T8ueTnDYtn5Hk/pnn7p7GAABgXVrEdZhf0t17qurvJLmlqj49+2B3d1X1kWxwCu8tSXL22WcvYBcBAGB55j7C3N17pp8PJnl/kvOTPLD/VIvp54PT6nuSnDXz9DOnsQO3eW13b+ruTRs2bJh3FwEAYNnmCuaqekpVPW3/cpJXJNmZ5KYkl02rXZbkA9PyTUkuna6W8eIkX5o5dQMAANadeU/JOC3J+6tq/7Z+s7v/d1V9PMl7q+r1ST6X5Aen9W9OcmGSXUm+kuR1c/5+AABYUXMFc3d/JsnfP8j4F5K8/CDjneSN8/xOAABYTb7pDwAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAADghkAAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAADJ671DgCQXHXrtoVsZ+vmKxayHQC+zhFmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABhYdjBX1VlV9eGququq7qyqn5zG31JVe6pqx3S7cOY5W6tqV1XdXVWvXMQfAAAAK2mer8Z+JMlPd/cnquppSW6vqlumx97a3b8yu3JVPS/JxUmen+SZSX6/qp7T3Y/OsQ8AALCiln2Eubv3dvcnpuW/TPKpJGcMnnJRknd398Pd/dkku5Kcv9zfDwAAq2GeI8yPqapzknxXko8m+d4kl1fVpUm2Z+ko9F9kKaZvm3na7owDG4BluurWbQvb1tbNVyxsWwBHo7k/9FdVT03yviQ/1d1fTnJNkmcn2Zhkb5Krl7HNLVW1vaq279u3b95dBACAZZvrCHNVPSlLsfwb3f07SdLdD8w8/o4k/2u6uyfJWTNPP3Mae5zuvjbJtUmyadOmnmcfYWRRR+EcgQOAY9c8V8moJO9M8qnu/tWZ8dNnVntNkp3T8k1JLq6qk6rq3CTnJfnYcn8/AACshnmOMH9vkh9K8smq2jGN/bskl1TVxiSd5L4kP54k3X1nVb03yV1ZusLGG10hAwCA9W7Zwdzdf5SkDvLQzYPnXJnkyuX+TgAAWG2+6Q8AAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMLPursQE4vlx167aFbGfr5isWsh2A1eIIMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAM+KY/ANaEbw4EjhaOMAMAwIBgBgCAAcEMAAADghkAAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgG/646jim8EAgNXmCDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAADghkAAAYEMwAADPimPwCOCYv6JtDEt4EC38gRZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAVfJAIBDWNSVN1x1A45ugpkV4xJPAMCxQDADwCpxIAGOTs5hBgCAgVUP5qq6oKrurqpdVfWm1f79AABwJFb1lIyqOiHJ25J8f5LdST5eVTd1912ruR8AcKzwwURYeat9DvP5SXZ192eSpKreneSiJIJ5HfCmC8Ci/1vgvG2OBasdzGckuX/m/u4k373K+3BYjoZ4PBr2EQAWbb1Gvf+eHruqu1fvl1W9NskF3f2j0/0fSvLd3X35AettSbJluvvcJHcfxuZPTfLnC9xdlpjXlWFeF8+crgzzujLM68owryvjeJnXb+/uDQd7YLWPMO9JctbM/TOnsW/Q3dcmufZINlxV27t703y7x4HM68owr4tnTleGeV0Z5nVlmNeVYV5X/yoZH09yXlWdW1VPTnJxkptWeR8AAOCwreoR5u5+pKouT/LBJCckua6771zNfQAAgCOx6t/01903J7l5BTZ9RKdwcNjM68owr4tnTleGeV0Z5nVlmNeVcdzP66p+6A8AAI42vhobAAAGjvpg9lXb86mq+6rqk1W1o6q2T2NPr6pbquqe6ecp03hV1bZpru+oqheu7d6vH1V1XVU9WFU7Z8aOeB6r6rJp/Xuq6rK1+FvWk0PM61uqas/0mt1RVRfOPLZ1mte7q+qVM+PeJyZVdVZVfbiq7qqqO6vqJ6dxr9c5DObV63UOVfVNVfWxqvrTaV5/bho/t6o+Os3Re6YLCaSqTpru75oeP2dmWwed7+PRYF6vr6rPzrxeN07j3ge6+6i9ZemDg/cmeVaSJyf50yTPW+v9OppuSe5LcuoBY7+U5E3T8puS/OK0fGGS301SSV6c5KNrvf/r5ZbkZUlemGTncucxydOTfGb6ecq0fMpa/23rcF7fkuTfHGTd503vASclOXd6bzjB+8Tj5un0JC+clp+W5M+mufN6XZl59Xqdb14ryVOn5Scl+ej0Onxvkoun8bcn+VfT8k8kefu0fHGS94zme63/vnU4r9cnee1B1j/u3weO9iPMj33Vdnf/vyT7v2qb+VyU5IZp+YYkr54Zf1cvuS3JyVV1+lrs4HrT3R9J8tABw0c6j69Mckt3P9Tdf5HkliQXrPzer1+HmNdDuSjJu7v74e7+bJJdWXqP8D4xo7v3dvcnpuW/TPKpLH0Lq9frHAbzeiher4dhet391XT3SdOtk3xfkt+exg98ve5/Hf92kpdXVeXQ831cGszroRz37wNHezAf7Ku2R29QPF4n+b2qur2WvmExSU7r7r3T8ueTnDYtm+8jc6TzaH4P3+XTPwtet//UgZjXIzb9c/V3Zenoktfrghwwr4nX61yq6oSq2pHkwSwF2b1Jvtjdj0yrzM7RY/M3Pf6lJM+IeX2cA+e1u/e/Xq+cXq9vraqTprHj/vV6tAcz83tJd78wyauSvLGqXjb7YC/9m4tLqczJPC7UNUmenWRjkr1Jrl7b3Tk6VdVTk7wvyU9195dnH/N6Xb6DzKvX65y6+9Hu3pilbwc+P8l3rPEuHRMOnNeqekGSrVma33+QpdMsfmYNd3FdOdqD+bC+aptD6+49088Hk7w/S29GD+w/1WL6+eC0uvk+Mkc6j+b3MHT3A9Mb/deSvCNf/2dV83qYqupJWYq63+ju35mGvV7ndLB59XpdnO7+YpIPJ/meLJ0SsP+7JGbn6LH5mx7/1iRfiHk9pJl5vWA6tai7++Ek/z1er4852oPZV23PoaqeUlVP27+c5BVJdmZpDvd/0vWyJB+Ylm9Kcun0adkXJ/nSzD/h8nhHOo8fTPKKqjpl+mfbV0xjzDjgvPnXZOk1myzN68XTp+TPTXJeko/F+8Q3mM7nfGeST3X3r8485PU6h0PNq9frfKpqQ1WdPC1/c5Lvz9L54R9O8tpptQNfr/tfx69N8gfTv5gcar6PS4eY10/P/E9zZem88NnX6/H9PrCanzBciVuWPrn5Z1k6p+ln13p/jqZblj6F/afT7c7985el870+lOSeJL+f5OnTeCV52zTXn0yyaa3/hvVyS3Jjlv659atZOofr9cuZxyQ/kqUPo+xK8rq1/rvW+naIef21ad7uyNKb+Okz6//sNK93J3nVzLj3ia/PxUuydLrFHUl2TLcLvV5XbF69Xueb1+9M8ifT/O1M8h+n8WdlKXh3JfmtJCdN49803d81Pf6sJ5rv4/E2mNc/mF6vO5P8er5+JY3j/n3AN/0BAMDA0X5KBgAArCjBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwMD/B6dOD1NGunCsAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.hist(column='rating', bins=30, grid=False, figsize=(12,8), color='#86bf91', zorder=2, rwidth=0.9)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Looks good. \n",
    "Now let's find correlation coefficient. And visualize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11ef82750>"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot.scatter(x='rating', y='rank', ylim=(11000,-500), \n",
    "                s=8, marker='o', color='orange', grid=False, figsize=(12,8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.40823313359351604\n"
     ]
    }
   ],
   "source": [
    "column_1 = -df[\"rating\"]  # negative rating to make positive correlation (like on the plot)\n",
    "column_2 = df[\"rank\"]\n",
    "correlation = column_1.corr(column_2)\n",
    "print(correlation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.41343970806563\n"
     ]
    }
   ],
   "source": [
    "selected = df[df[\"rank\"] < 1000]  # Top 1000 in the contest\n",
    "\n",
    "column_1 = -selected[\"rating\"]  # negative rating to make positive correlation (like on the plot)\n",
    "column_2 = selected[\"rank\"]\n",
    "correlation = column_1.corr(column_2)\n",
    "print(correlation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.20462939928887686\n"
     ]
    }
   ],
   "source": [
    "selected = df[df[\"rating\"] > 1500] # People with rating more than 1500\n",
    "\n",
    "column_1 = -selected[\"rating\"]  # negative rating to make positive correlation (like on the plot)\n",
    "column_2 = selected[\"rank\"]\n",
    "correlation = column_1.corr(column_2)\n",
    "print(correlation)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Hold on!\n",
    "#### Something surprising\n",
    "So the overall correlation between the rank and rating is weak-moderate with correlation of about ~0.41\n",
    "Also if we look at the correlation for top 1000 people on the leaderboard, they also have the same correlation ~0.41\n",
    "HOWEVER, if we limit to only those with rating >1500, the correlation becomes very weak! Which means that once you are at least decent at CP, you were on the same level field as people \n",
    "you contest performance \n",
    "meant almost nothing for April Fool's contest.\n",
    "\n",
    "This will be the end of my analysis, feel free to try things out and lmk if u find anything interesting!\n",
    "\n",
    "Cheers!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
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    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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