{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Analyzing Ice Dance Scoring by Team and Judge Country\n",
    "\n",
    "This analysis builds off BuzzFeed News' prior work analzying figure skating scores, which you can find [here](../README.md). The code below calculates the percentage of times judges from any given country have scored each ice dance team above or below the average of the other judges for that performance at 17 high-level competitions between Oct. 2016 and Dec. 2017."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load Judge and Score Data\n",
    "\n",
    "*Note:* This section is a reproduction of the setup steps in the [`home-country-preference` notebook](./home-country-preference.ipynb). Please see that notebook for more details about the process."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "all_judges = pd.read_csv(\"../data/processed/judges.csv\")\n",
    "judge_nat = pd.read_csv(\"../data/processed/judge-country.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "judges = pd.merge(\n",
    "    all_judges,\n",
    "    judge_nat,\n",
    "    on=\"clean_judge_name\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def clean_judge_number(role):\n",
    "    return \"J\" + role.strip()[-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "judges[\"clean_role\"] = judges[\"role\"].apply(clean_judge_number)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load score data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1,726 performances\n",
      "23,932 aspects\n",
      "214,531 scores\n"
     ]
    }
   ],
   "source": [
    "performances = pd.read_csv(\"../data/raw/performances.csv\")\n",
    "print(\"{:,} performances\".format(len(performances)))\n",
    "\n",
    "aspects = pd.read_csv(\"../data/raw/judged-aspects.csv\")\n",
    "print(\"{:,} aspects\".format(len(aspects)))\n",
    "\n",
    "scores = pd.read_csv(\"../data/raw/judge-scores.csv\")\n",
    "print(\"{:,} scores\".format(len(scores)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "judge_goe = pd.read_csv(\"../data/processed/judge-goe.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "scores_with_context = scores.pipe(\n",
    "    pd.merge,\n",
    "    aspects,\n",
    "    on = \"aspect_id\",\n",
    "    how = \"left\"\n",
    ").pipe(\n",
    "    pd.merge,\n",
    "    performances,\n",
    "    on = \"performance_id\",\n",
    "    how = \"left\"\n",
    ").pipe(\n",
    "    pd.merge,\n",
    "    judge_goe,\n",
    "    on = [ \"aspect_id\", \"judge\" ],\n",
    "    how = \"left\"\n",
    ").assign(\n",
    "    is_junior = lambda x: x[\"program\"].str.contains(\"JUNIOR\"),\n",
    "    program_type = lambda x: x[\"program\"]\\\n",
    "        .apply(lambda x: \"short\" if \"SHORT\" in x else \"free\")\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "assert len(scores) == len(scores_with_context)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Set Up Data for Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "392"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "senior_scores = scores_with_context[\n",
    "    (scores_with_context[\"is_junior\"] == False) &\n",
    "    # Because we are only analyzing Ice Dance in this notebook\n",
    "    # we limit the scope of the scoring data to those programs\n",
    "    (scores_with_context[\"program\"].str.contains(\"ICE DANCE\"))\n",
    "].copy()\n",
    "\n",
    "senior_scores[\"performance_id\"].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def total_points(row):\n",
    "    if row[\"section\"] == \"elements\":\n",
    "        return round(row[\"base_value\"] + row[\"judge_goe\"], 2)\n",
    "    \n",
    "    elif row[\"section\"] == \"components\":\n",
    "        return round(row[\"factor\"] * row[\"score\"], 2)\n",
    "    \n",
    "    else:\n",
    "        print(\"Unknown section: {}\".format(row[\"section\"]))\n",
    "        return None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "senior_scores[\"total_points\"] = senior_scores.apply(total_points, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "perf_judge_grps = senior_scores[\n",
    "    ~senior_scores[\"total_points\"].isnull()\n",
    "].groupby([\"performance_id\", \"judge\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>performance_id</th>\n",
       "      <th>judge</th>\n",
       "      <th>competition</th>\n",
       "      <th>deductions</th>\n",
       "      <th>name</th>\n",
       "      <th>nation</th>\n",
       "      <th>points</th>\n",
       "      <th>program</th>\n",
       "      <th>program_type</th>\n",
       "      <th>final_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>00693b66b5</td>\n",
       "      <td>J1</td>\n",
       "      <td>ISU Four Continents Championships 2017</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Maia SHIBUTANI / Alex SHIBUTANI</td>\n",
       "      <td>USA</td>\n",
       "      <td>76.3</td>\n",
       "      <td>ICE DANCE SHORT DANCE</td>\n",
       "      <td>short</td>\n",
       "      <td>76.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>00693b66b5</td>\n",
       "      <td>J2</td>\n",
       "      <td>ISU Four Continents Championships 2017</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Maia SHIBUTANI / Alex SHIBUTANI</td>\n",
       "      <td>USA</td>\n",
       "      <td>76.6</td>\n",
       "      <td>ICE DANCE SHORT DANCE</td>\n",
       "      <td>short</td>\n",
       "      <td>76.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>00693b66b5</td>\n",
       "      <td>J3</td>\n",
       "      <td>ISU Four Continents Championships 2017</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Maia SHIBUTANI / Alex SHIBUTANI</td>\n",
       "      <td>USA</td>\n",
       "      <td>76.0</td>\n",
       "      <td>ICE DANCE SHORT DANCE</td>\n",
       "      <td>short</td>\n",
       "      <td>76.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>00693b66b5</td>\n",
       "      <td>J4</td>\n",
       "      <td>ISU Four Continents Championships 2017</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Maia SHIBUTANI / Alex SHIBUTANI</td>\n",
       "      <td>USA</td>\n",
       "      <td>77.9</td>\n",
       "      <td>ICE DANCE SHORT DANCE</td>\n",
       "      <td>short</td>\n",
       "      <td>77.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>00693b66b5</td>\n",
       "      <td>J5</td>\n",
       "      <td>ISU Four Continents Championships 2017</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Maia SHIBUTANI / Alex SHIBUTANI</td>\n",
       "      <td>USA</td>\n",
       "      <td>74.5</td>\n",
       "      <td>ICE DANCE SHORT DANCE</td>\n",
       "      <td>short</td>\n",
       "      <td>74.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  performance_id judge                             competition  deductions  \\\n",
       "0     00693b66b5    J1  ISU Four Continents Championships 2017         0.0   \n",
       "1     00693b66b5    J2  ISU Four Continents Championships 2017         0.0   \n",
       "2     00693b66b5    J3  ISU Four Continents Championships 2017         0.0   \n",
       "3     00693b66b5    J4  ISU Four Continents Championships 2017         0.0   \n",
       "4     00693b66b5    J5  ISU Four Continents Championships 2017         0.0   \n",
       "\n",
       "                              name nation  points                program  \\\n",
       "0  Maia SHIBUTANI / Alex SHIBUTANI    USA    76.3  ICE DANCE SHORT DANCE   \n",
       "1  Maia SHIBUTANI / Alex SHIBUTANI    USA    76.6  ICE DANCE SHORT DANCE   \n",
       "2  Maia SHIBUTANI / Alex SHIBUTANI    USA    76.0  ICE DANCE SHORT DANCE   \n",
       "3  Maia SHIBUTANI / Alex SHIBUTANI    USA    77.9  ICE DANCE SHORT DANCE   \n",
       "4  Maia SHIBUTANI / Alex SHIBUTANI    USA    74.5  ICE DANCE SHORT DANCE   \n",
       "\n",
       "  program_type  final_score  \n",
       "0        short         76.3  \n",
       "1        short         76.6  \n",
       "2        short         76.0  \n",
       "3        short         77.9  \n",
       "4        short         74.5  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "points_by_judge = pd.DataFrame({\n",
    "    \"points\": perf_judge_grps[\"total_points\"].sum(),\n",
    "    \"deductions\": perf_judge_grps[\"total_deductions\"].first(),\n",
    "    \"name\": perf_judge_grps[\"name\"].first(),\n",
    "    \"nation\": perf_judge_grps[\"nation\"].first(),\n",
    "    \"program\": perf_judge_grps[\"program\"].first(),\n",
    "    \"program_type\": perf_judge_grps[\"program_type\"].first(),\n",
    "    \"competition\": perf_judge_grps[\"competition\"].first()\n",
    "}).reset_index()\n",
    "points_by_judge[\"final_score\"] = points_by_judge[\"points\"] - points_by_judge[\"deductions\"]\n",
    "\n",
    "points_by_judge.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "perf_grps = points_by_judge.groupby([\"performance_id\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "perfs = pd.DataFrame({\n",
    "    \"total_points\": perf_grps[\"final_score\"].sum(),\n",
    "    \"total_judges\": perf_grps.size()\n",
    "}).reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>performance_id</th>\n",
       "      <th>judge</th>\n",
       "      <th>competition</th>\n",
       "      <th>deductions</th>\n",
       "      <th>name</th>\n",
       "      <th>nation</th>\n",
       "      <th>points</th>\n",
       "      <th>program</th>\n",
       "      <th>program_type</th>\n",
       "      <th>final_score</th>\n",
       "      <th>total_judges</th>\n",
       "      <th>total_points</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>00693b66b5</td>\n",
       "      <td>J1</td>\n",
       "      <td>ISU Four Continents Championships 2017</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Maia SHIBUTANI / Alex SHIBUTANI</td>\n",
       "      <td>USA</td>\n",
       "      <td>76.3</td>\n",
       "      <td>ICE DANCE SHORT DANCE</td>\n",
       "      <td>short</td>\n",
       "      <td>76.3</td>\n",
       "      <td>9</td>\n",
       "      <td>689.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>00693b66b5</td>\n",
       "      <td>J2</td>\n",
       "      <td>ISU Four Continents Championships 2017</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Maia SHIBUTANI / Alex SHIBUTANI</td>\n",
       "      <td>USA</td>\n",
       "      <td>76.6</td>\n",
       "      <td>ICE DANCE SHORT DANCE</td>\n",
       "      <td>short</td>\n",
       "      <td>76.6</td>\n",
       "      <td>9</td>\n",
       "      <td>689.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>00693b66b5</td>\n",
       "      <td>J3</td>\n",
       "      <td>ISU Four Continents Championships 2017</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Maia SHIBUTANI / Alex SHIBUTANI</td>\n",
       "      <td>USA</td>\n",
       "      <td>76.0</td>\n",
       "      <td>ICE DANCE SHORT DANCE</td>\n",
       "      <td>short</td>\n",
       "      <td>76.0</td>\n",
       "      <td>9</td>\n",
       "      <td>689.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>00693b66b5</td>\n",
       "      <td>J4</td>\n",
       "      <td>ISU Four Continents Championships 2017</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Maia SHIBUTANI / Alex SHIBUTANI</td>\n",
       "      <td>USA</td>\n",
       "      <td>77.9</td>\n",
       "      <td>ICE DANCE SHORT DANCE</td>\n",
       "      <td>short</td>\n",
       "      <td>77.9</td>\n",
       "      <td>9</td>\n",
       "      <td>689.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>00693b66b5</td>\n",
       "      <td>J5</td>\n",
       "      <td>ISU Four Continents Championships 2017</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Maia SHIBUTANI / Alex SHIBUTANI</td>\n",
       "      <td>USA</td>\n",
       "      <td>74.5</td>\n",
       "      <td>ICE DANCE SHORT DANCE</td>\n",
       "      <td>short</td>\n",
       "      <td>74.5</td>\n",
       "      <td>9</td>\n",
       "      <td>689.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  performance_id judge                             competition  deductions  \\\n",
       "0     00693b66b5    J1  ISU Four Continents Championships 2017         0.0   \n",
       "1     00693b66b5    J2  ISU Four Continents Championships 2017         0.0   \n",
       "2     00693b66b5    J3  ISU Four Continents Championships 2017         0.0   \n",
       "3     00693b66b5    J4  ISU Four Continents Championships 2017         0.0   \n",
       "4     00693b66b5    J5  ISU Four Continents Championships 2017         0.0   \n",
       "\n",
       "                              name nation  points                program  \\\n",
       "0  Maia SHIBUTANI / Alex SHIBUTANI    USA    76.3  ICE DANCE SHORT DANCE   \n",
       "1  Maia SHIBUTANI / Alex SHIBUTANI    USA    76.6  ICE DANCE SHORT DANCE   \n",
       "2  Maia SHIBUTANI / Alex SHIBUTANI    USA    76.0  ICE DANCE SHORT DANCE   \n",
       "3  Maia SHIBUTANI / Alex SHIBUTANI    USA    77.9  ICE DANCE SHORT DANCE   \n",
       "4  Maia SHIBUTANI / Alex SHIBUTANI    USA    74.5  ICE DANCE SHORT DANCE   \n",
       "\n",
       "  program_type  final_score  total_judges  total_points  \n",
       "0        short         76.3             9         689.2  \n",
       "1        short         76.6             9         689.2  \n",
       "2        short         76.0             9         689.2  \n",
       "3        short         77.9             9         689.2  \n",
       "4        short         74.5             9         689.2  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "points_with_comparison = pd.merge(\n",
    "    points_by_judge,\n",
    "    perfs,\n",
    "    how = \"left\",\n",
    "    on = \"performance_id\"\n",
    ")\n",
    "\n",
    "points_with_comparison.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "points_with_comparison[\"avg_without_judge\"] = points_with_comparison\\\n",
    "    .apply(lambda x: (x[\"total_points\"] - x[\"final_score\"]) / (x[\"total_judges\"] - 1), axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "points_with_comparison[\"points_vs_avg\"] = points_with_comparison[\"final_score\"] - \\\n",
    "    points_with_comparison[\"avg_without_judge\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
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       "        text-align: right;\n",
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       "    .dataframe thead th {\n",
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       "    }\n",
       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>performance_id</th>\n",
       "      <th>judge</th>\n",
       "      <th>competition</th>\n",
       "      <th>deductions</th>\n",
       "      <th>name</th>\n",
       "      <th>nation</th>\n",
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       "      <th>program</th>\n",
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       "      <th>final_score</th>\n",
       "      <th>total_judges</th>\n",
       "      <th>total_points</th>\n",
       "      <th>avg_without_judge</th>\n",
       "      <th>points_vs_avg</th>\n",
       "      <th>segment_category</th>\n",
       "      <th>clean_judge_name</th>\n",
       "      <th>judge_country</th>\n",
       "      <th>clean_role</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>00693b66b5</td>\n",
       "      <td>J1</td>\n",
       "      <td>ISU Four Continents Championships 2017</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Maia SHIBUTANI / Alex SHIBUTANI</td>\n",
       "      <td>USA</td>\n",
       "      <td>76.3</td>\n",
       "      <td>ICE DANCE SHORT DANCE</td>\n",
       "      <td>short</td>\n",
       "      <td>76.3</td>\n",
       "      <td>9</td>\n",
       "      <td>689.2</td>\n",
       "      <td>76.6125</td>\n",
       "      <td>-0.3125</td>\n",
       "      <td>Short Dance|Ice Dance</td>\n",
       "      <td>Tianyi ZHANG</td>\n",
       "      <td>CHN</td>\n",
       "      <td>J1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>00693b66b5</td>\n",
       "      <td>J2</td>\n",
       "      <td>ISU Four Continents Championships 2017</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Maia SHIBUTANI / Alex SHIBUTANI</td>\n",
       "      <td>USA</td>\n",
       "      <td>76.6</td>\n",
       "      <td>ICE DANCE SHORT DANCE</td>\n",
       "      <td>short</td>\n",
       "      <td>76.6</td>\n",
       "      <td>9</td>\n",
       "      <td>689.2</td>\n",
       "      <td>76.5750</td>\n",
       "      <td>0.0250</td>\n",
       "      <td>Short Dance|Ice Dance</td>\n",
       "      <td>Marta OLOZAGARRE</td>\n",
       "      <td>ESP</td>\n",
       "      <td>J2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>00693b66b5</td>\n",
       "      <td>J3</td>\n",
       "      <td>ISU Four Continents Championships 2017</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Maia SHIBUTANI / Alex SHIBUTANI</td>\n",
       "      <td>USA</td>\n",
       "      <td>76.0</td>\n",
       "      <td>ICE DANCE SHORT DANCE</td>\n",
       "      <td>short</td>\n",
       "      <td>76.0</td>\n",
       "      <td>9</td>\n",
       "      <td>689.2</td>\n",
       "      <td>76.6500</td>\n",
       "      <td>-0.6500</td>\n",
       "      <td>Short Dance|Ice Dance</td>\n",
       "      <td>Mayumi KATO</td>\n",
       "      <td>JPN</td>\n",
       "      <td>J3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>00693b66b5</td>\n",
       "      <td>J4</td>\n",
       "      <td>ISU Four Continents Championships 2017</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Maia SHIBUTANI / Alex SHIBUTANI</td>\n",
       "      <td>USA</td>\n",
       "      <td>77.9</td>\n",
       "      <td>ICE DANCE SHORT DANCE</td>\n",
       "      <td>short</td>\n",
       "      <td>77.9</td>\n",
       "      <td>9</td>\n",
       "      <td>689.2</td>\n",
       "      <td>76.4125</td>\n",
       "      <td>1.4875</td>\n",
       "      <td>Short Dance|Ice Dance</td>\n",
       "      <td>Mark STORTON</td>\n",
       "      <td>AUS</td>\n",
       "      <td>J4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>00693b66b5</td>\n",
       "      <td>J5</td>\n",
       "      <td>ISU Four Continents Championships 2017</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Maia SHIBUTANI / Alex SHIBUTANI</td>\n",
       "      <td>USA</td>\n",
       "      <td>74.5</td>\n",
       "      <td>ICE DANCE SHORT DANCE</td>\n",
       "      <td>short</td>\n",
       "      <td>74.5</td>\n",
       "      <td>9</td>\n",
       "      <td>689.2</td>\n",
       "      <td>76.8375</td>\n",
       "      <td>-2.3375</td>\n",
       "      <td>Short Dance|Ice Dance</td>\n",
       "      <td>Andre-Marc ALLAIN</td>\n",
       "      <td>CAN</td>\n",
       "      <td>J5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  performance_id judge                             competition  deductions  \\\n",
       "0     00693b66b5    J1  ISU Four Continents Championships 2017         0.0   \n",
       "1     00693b66b5    J2  ISU Four Continents Championships 2017         0.0   \n",
       "2     00693b66b5    J3  ISU Four Continents Championships 2017         0.0   \n",
       "3     00693b66b5    J4  ISU Four Continents Championships 2017         0.0   \n",
       "4     00693b66b5    J5  ISU Four Continents Championships 2017         0.0   \n",
       "\n",
       "                              name nation  points                program  \\\n",
       "0  Maia SHIBUTANI / Alex SHIBUTANI    USA    76.3  ICE DANCE SHORT DANCE   \n",
       "1  Maia SHIBUTANI / Alex SHIBUTANI    USA    76.6  ICE DANCE SHORT DANCE   \n",
       "2  Maia SHIBUTANI / Alex SHIBUTANI    USA    76.0  ICE DANCE SHORT DANCE   \n",
       "3  Maia SHIBUTANI / Alex SHIBUTANI    USA    77.9  ICE DANCE SHORT DANCE   \n",
       "4  Maia SHIBUTANI / Alex SHIBUTANI    USA    74.5  ICE DANCE SHORT DANCE   \n",
       "\n",
       "  program_type  final_score  total_judges  total_points  avg_without_judge  \\\n",
       "0        short         76.3             9         689.2            76.6125   \n",
       "1        short         76.6             9         689.2            76.5750   \n",
       "2        short         76.0             9         689.2            76.6500   \n",
       "3        short         77.9             9         689.2            76.4125   \n",
       "4        short         74.5             9         689.2            76.8375   \n",
       "\n",
       "   points_vs_avg       segment_category   clean_judge_name judge_country  \\\n",
       "0        -0.3125  Short Dance|Ice Dance       Tianyi ZHANG           CHN   \n",
       "1         0.0250  Short Dance|Ice Dance   Marta OLOZAGARRE           ESP   \n",
       "2        -0.6500  Short Dance|Ice Dance        Mayumi KATO           JPN   \n",
       "3         1.4875  Short Dance|Ice Dance       Mark STORTON           AUS   \n",
       "4        -2.3375  Short Dance|Ice Dance  Andre-Marc ALLAIN           CAN   \n",
       "\n",
       "  clean_role  \n",
       "0         J1  \n",
       "1         J2  \n",
       "2         J3  \n",
       "3         J4  \n",
       "4         J5  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "judge_points = pd.merge(\n",
    "    points_with_comparison,\n",
    "    judges[[\n",
    "        \"program\", \"competition\", \"segment_category\",\n",
    "        \"clean_judge_name\", \"judge_country\", \"clean_role\"\n",
    "    ]],\n",
    "    left_on=[ \"program\", \"competition\", \"judge\" ],\n",
    "    right_on=[ \"program\", \"competition\", \"clean_role\" ],\n",
    "    how=\"left\"\n",
    ").dropna(subset=[\"judge_country\"])\n",
    "\n",
    "judge_points.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analyze Ice Dance Competition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def compare_scores_by_judge_country(skater_name):\n",
    "    \n",
    "    skater_scores = judge_points[\n",
    "        judge_points[\"name\"] == skater_name\n",
    "    ]\n",
    "    \n",
    "    country_grps = skater_scores.groupby(\"judge_country\")\n",
    "    \n",
    "    country_df = pd.DataFrame({\n",
    "        \"scores_above_average\": country_grps.apply(lambda x: len(x[x[\"points_vs_avg\"] > 0])),\n",
    "        \"scores_below_average\": country_grps.apply(lambda x: len(x[x[\"points_vs_avg\"] < 0])),\n",
    "        \"scores_exactly_average\": country_grps.apply(lambda x: len(x[x[\"points_vs_avg\"] == 0])),\n",
    "        \"total_scores\": country_grps.size(),\n",
    "        \"pct_above_average\": round(country_grps.apply(lambda x: len(x[x[\"points_vs_avg\"] > 0])) / \\\n",
    "            country_grps.size() * 100, 2),\n",
    "        \"pct_below_average\": round(country_grps.apply(lambda x: len(x[x[\"points_vs_avg\"] < 0])) / \\\n",
    "            country_grps.size() * 100, 2)\n",
    "    })\n",
    "    \n",
    "    return country_df[\n",
    "        country_df[\"total_scores\"] >= 5\n",
    "    ].sort_values(\"pct_above_average\", ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Gold Medal Contenders"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Results for Virtue/Moir (Canada)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pct_above_average</th>\n",
       "      <th>pct_below_average</th>\n",
       "      <th>scores_above_average</th>\n",
       "      <th>scores_below_average</th>\n",
       "      <th>scores_exactly_average</th>\n",
       "      <th>total_scores</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>judge_country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CAN</th>\n",
       "      <td>100.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JPN</th>\n",
       "      <td>83.33</td>\n",
       "      <td>16.67</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KOR</th>\n",
       "      <td>83.33</td>\n",
       "      <td>16.67</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GER</th>\n",
       "      <td>71.43</td>\n",
       "      <td>28.57</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHN</th>\n",
       "      <td>70.00</td>\n",
       "      <td>30.00</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RUS</th>\n",
       "      <td>56.25</td>\n",
       "      <td>43.75</td>\n",
       "      <td>9</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AUS</th>\n",
       "      <td>50.00</td>\n",
       "      <td>50.00</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ESP</th>\n",
       "      <td>30.00</td>\n",
       "      <td>70.00</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ITA</th>\n",
       "      <td>25.00</td>\n",
       "      <td>66.67</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>USA</th>\n",
       "      <td>25.00</td>\n",
       "      <td>75.00</td>\n",
       "      <td>4</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FRA</th>\n",
       "      <td>11.11</td>\n",
       "      <td>88.89</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               pct_above_average  pct_below_average  scores_above_average  \\\n",
       "judge_country                                                               \n",
       "CAN                       100.00               0.00                    16   \n",
       "JPN                        83.33              16.67                    10   \n",
       "KOR                        83.33              16.67                     5   \n",
       "GER                        71.43              28.57                     5   \n",
       "CHN                        70.00              30.00                     7   \n",
       "RUS                        56.25              43.75                     9   \n",
       "AUS                        50.00              50.00                     3   \n",
       "ESP                        30.00              70.00                     3   \n",
       "ITA                        25.00              66.67                     3   \n",
       "USA                        25.00              75.00                     4   \n",
       "FRA                        11.11              88.89                     1   \n",
       "\n",
       "               scores_below_average  scores_exactly_average  total_scores  \n",
       "judge_country                                                              \n",
       "CAN                               0                       0            16  \n",
       "JPN                               2                       0            12  \n",
       "KOR                               1                       0             6  \n",
       "GER                               2                       0             7  \n",
       "CHN                               3                       0            10  \n",
       "RUS                               7                       0            16  \n",
       "AUS                               3                       0             6  \n",
       "ESP                               7                       0            10  \n",
       "ITA                               8                       1            12  \n",
       "USA                              12                       0            16  \n",
       "FRA                               8                       0             9  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compare_scores_by_judge_country(\"Tessa VIRTUE / Scott MOIR\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Results for Papadakis/Cizeron (France)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pct_above_average</th>\n",
       "      <th>pct_below_average</th>\n",
       "      <th>scores_above_average</th>\n",
       "      <th>scores_below_average</th>\n",
       "      <th>scores_exactly_average</th>\n",
       "      <th>total_scores</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>judge_country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>FRA</th>\n",
       "      <td>92.31</td>\n",
       "      <td>7.69</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>USA</th>\n",
       "      <td>85.71</td>\n",
       "      <td>14.29</td>\n",
       "      <td>12</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHN</th>\n",
       "      <td>83.33</td>\n",
       "      <td>16.67</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ESP</th>\n",
       "      <td>71.43</td>\n",
       "      <td>28.57</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ISR</th>\n",
       "      <td>66.67</td>\n",
       "      <td>33.33</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ITA</th>\n",
       "      <td>50.00</td>\n",
       "      <td>50.00</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JPN</th>\n",
       "      <td>50.00</td>\n",
       "      <td>50.00</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KOR</th>\n",
       "      <td>50.00</td>\n",
       "      <td>50.00</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GER</th>\n",
       "      <td>42.86</td>\n",
       "      <td>57.14</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RUS</th>\n",
       "      <td>28.57</td>\n",
       "      <td>71.43</td>\n",
       "      <td>4</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CZE</th>\n",
       "      <td>22.22</td>\n",
       "      <td>77.78</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CAN</th>\n",
       "      <td>21.43</td>\n",
       "      <td>78.57</td>\n",
       "      <td>3</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>POL</th>\n",
       "      <td>20.00</td>\n",
       "      <td>80.00</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UKR</th>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               pct_above_average  pct_below_average  scores_above_average  \\\n",
       "judge_country                                                               \n",
       "FRA                        92.31               7.69                    12   \n",
       "USA                        85.71              14.29                    12   \n",
       "CHN                        83.33              16.67                     5   \n",
       "ESP                        71.43              28.57                     5   \n",
       "ISR                        66.67              33.33                     4   \n",
       "ITA                        50.00              50.00                     5   \n",
       "JPN                        50.00              50.00                     3   \n",
       "KOR                        50.00              50.00                     3   \n",
       "GER                        42.86              57.14                     3   \n",
       "RUS                        28.57              71.43                     4   \n",
       "CZE                        22.22              77.78                     2   \n",
       "CAN                        21.43              78.57                     3   \n",
       "POL                        20.00              80.00                     1   \n",
       "UKR                         0.00             100.00                     0   \n",
       "\n",
       "               scores_below_average  scores_exactly_average  total_scores  \n",
       "judge_country                                                              \n",
       "FRA                               1                       0            13  \n",
       "USA                               2                       0            14  \n",
       "CHN                               1                       0             6  \n",
       "ESP                               2                       0             7  \n",
       "ISR                               2                       0             6  \n",
       "ITA                               5                       0            10  \n",
       "JPN                               3                       0             6  \n",
       "KOR                               3                       0             6  \n",
       "GER                               4                       0             7  \n",
       "RUS                              10                       0            14  \n",
       "CZE                               7                       0             9  \n",
       "CAN                              11                       0            14  \n",
       "POL                               4                       0             5  \n",
       "UKR                               5                       0             5  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compare_scores_by_judge_country(\"Gabriella PAPADAKIS / Guillaume CIZERON\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Comparing results for the two teams**\n",
    "\n",
    "(Includes only countries whose judges scored, in the dataset, at least five performances of each team.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pct_above_average_canada</th>\n",
       "      <th>pct_above_average_france</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>judge_country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CAN</th>\n",
       "      <td>100.00</td>\n",
       "      <td>21.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JPN</th>\n",
       "      <td>83.33</td>\n",
       "      <td>50.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KOR</th>\n",
       "      <td>83.33</td>\n",
       "      <td>50.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GER</th>\n",
       "      <td>71.43</td>\n",
       "      <td>42.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHN</th>\n",
       "      <td>70.00</td>\n",
       "      <td>83.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RUS</th>\n",
       "      <td>56.25</td>\n",
       "      <td>28.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ESP</th>\n",
       "      <td>30.00</td>\n",
       "      <td>71.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ITA</th>\n",
       "      <td>25.00</td>\n",
       "      <td>50.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>USA</th>\n",
       "      <td>25.00</td>\n",
       "      <td>85.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FRA</th>\n",
       "      <td>11.11</td>\n",
       "      <td>92.31</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               pct_above_average_canada  pct_above_average_france\n",
       "judge_country                                                    \n",
       "CAN                              100.00                     21.43\n",
       "JPN                               83.33                     50.00\n",
       "KOR                               83.33                     50.00\n",
       "GER                               71.43                     42.86\n",
       "CHN                               70.00                     83.33\n",
       "RUS                               56.25                     28.57\n",
       "ESP                               30.00                     71.43\n",
       "ITA                               25.00                     50.00\n",
       "USA                               25.00                     85.71\n",
       "FRA                               11.11                     92.31"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compare_scores_by_judge_country(\"Tessa VIRTUE / Scott MOIR\")\\\n",
    "    .join(\n",
    "        compare_scores_by_judge_country(\"Gabriella PAPADAKIS / Guillaume CIZERON\"), \n",
    "        lsuffix=\"_canada\", \n",
    "        rsuffix=\"_france\")\\\n",
    "    .dropna()[[\"pct_above_average_canada\", \"pct_above_average_france\"]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bronze Medal Contenders"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Results for Bobrova/Soloviev (Russia)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pct_above_average</th>\n",
       "      <th>pct_below_average</th>\n",
       "      <th>scores_above_average</th>\n",
       "      <th>scores_below_average</th>\n",
       "      <th>scores_exactly_average</th>\n",
       "      <th>total_scores</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>judge_country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>RUS</th>\n",
       "      <td>100.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TUR</th>\n",
       "      <td>100.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ESP</th>\n",
       "      <td>71.43</td>\n",
       "      <td>28.57</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ISR</th>\n",
       "      <td>62.50</td>\n",
       "      <td>37.50</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CZE</th>\n",
       "      <td>57.14</td>\n",
       "      <td>42.86</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CAN</th>\n",
       "      <td>50.00</td>\n",
       "      <td>50.00</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KOR</th>\n",
       "      <td>50.00</td>\n",
       "      <td>50.00</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FRA</th>\n",
       "      <td>28.57</td>\n",
       "      <td>71.43</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ITA</th>\n",
       "      <td>20.00</td>\n",
       "      <td>80.00</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>USA</th>\n",
       "      <td>16.67</td>\n",
       "      <td>83.33</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               pct_above_average  pct_below_average  scores_above_average  \\\n",
       "judge_country                                                               \n",
       "RUS                       100.00               0.00                    12   \n",
       "TUR                       100.00               0.00                     9   \n",
       "ESP                        71.43              28.57                     5   \n",
       "ISR                        62.50              37.50                     5   \n",
       "CZE                        57.14              42.86                     4   \n",
       "CAN                        50.00              50.00                     6   \n",
       "KOR                        50.00              50.00                     3   \n",
       "FRA                        28.57              71.43                     2   \n",
       "ITA                        20.00              80.00                     2   \n",
       "USA                        16.67              83.33                     2   \n",
       "\n",
       "               scores_below_average  scores_exactly_average  total_scores  \n",
       "judge_country                                                              \n",
       "RUS                               0                       0            12  \n",
       "TUR                               0                       0             9  \n",
       "ESP                               2                       0             7  \n",
       "ISR                               3                       0             8  \n",
       "CZE                               3                       0             7  \n",
       "CAN                               6                       0            12  \n",
       "KOR                               3                       0             6  \n",
       "FRA                               5                       0             7  \n",
       "ITA                               8                       0            10  \n",
       "USA                              10                       0            12  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compare_scores_by_judge_country(\"Ekaterina BOBROVA / Dmitri SOLOVIEV\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Results for Chock/Bates (USA)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pct_above_average</th>\n",
       "      <th>pct_below_average</th>\n",
       "      <th>scores_above_average</th>\n",
       "      <th>scores_below_average</th>\n",
       "      <th>scores_exactly_average</th>\n",
       "      <th>total_scores</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>judge_country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>USA</th>\n",
       "      <td>100.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JPN</th>\n",
       "      <td>87.50</td>\n",
       "      <td>12.50</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHN</th>\n",
       "      <td>80.00</td>\n",
       "      <td>20.00</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ESP</th>\n",
       "      <td>70.00</td>\n",
       "      <td>30.00</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FRA</th>\n",
       "      <td>55.56</td>\n",
       "      <td>44.44</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KOR</th>\n",
       "      <td>50.00</td>\n",
       "      <td>50.00</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GER</th>\n",
       "      <td>40.00</td>\n",
       "      <td>60.00</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ISR</th>\n",
       "      <td>40.00</td>\n",
       "      <td>60.00</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CZE</th>\n",
       "      <td>25.00</td>\n",
       "      <td>75.00</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ITA</th>\n",
       "      <td>20.00</td>\n",
       "      <td>80.00</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RUS</th>\n",
       "      <td>18.75</td>\n",
       "      <td>81.25</td>\n",
       "      <td>3</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CAN</th>\n",
       "      <td>12.50</td>\n",
       "      <td>87.50</td>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               pct_above_average  pct_below_average  scores_above_average  \\\n",
       "judge_country                                                               \n",
       "USA                       100.00               0.00                    16   \n",
       "JPN                        87.50              12.50                     7   \n",
       "CHN                        80.00              20.00                     8   \n",
       "ESP                        70.00              30.00                     7   \n",
       "FRA                        55.56              44.44                     5   \n",
       "KOR                        50.00              50.00                     4   \n",
       "GER                        40.00              60.00                     2   \n",
       "ISR                        40.00              60.00                     2   \n",
       "CZE                        25.00              75.00                     2   \n",
       "ITA                        20.00              80.00                     2   \n",
       "RUS                        18.75              81.25                     3   \n",
       "CAN                        12.50              87.50                     2   \n",
       "\n",
       "               scores_below_average  scores_exactly_average  total_scores  \n",
       "judge_country                                                              \n",
       "USA                               0                       0            16  \n",
       "JPN                               1                       0             8  \n",
       "CHN                               2                       0            10  \n",
       "ESP                               3                       0            10  \n",
       "FRA                               4                       0             9  \n",
       "KOR                               4                       0             8  \n",
       "GER                               3                       0             5  \n",
       "ISR                               3                       0             5  \n",
       "CZE                               6                       0             8  \n",
       "ITA                               8                       0            10  \n",
       "RUS                              13                       0            16  \n",
       "CAN                              14                       0            16  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compare_scores_by_judge_country(\"Madison CHOCK / Evan BATES\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Results for Shibutani/Shibutani (USA)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pct_above_average</th>\n",
       "      <th>pct_below_average</th>\n",
       "      <th>scores_above_average</th>\n",
       "      <th>scores_below_average</th>\n",
       "      <th>scores_exactly_average</th>\n",
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       "      <th>judge_country</th>\n",
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       "  <tbody>\n",
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       "      <th>USA</th>\n",
       "      <td>100.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ESP</th>\n",
       "      <td>80.00</td>\n",
       "      <td>20.00</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ITA</th>\n",
       "      <td>80.00</td>\n",
       "      <td>20.00</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHN</th>\n",
       "      <td>60.00</td>\n",
       "      <td>40.00</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CAN</th>\n",
       "      <td>43.75</td>\n",
       "      <td>56.25</td>\n",
       "      <td>7</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FRA</th>\n",
       "      <td>42.86</td>\n",
       "      <td>57.14</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JPN</th>\n",
       "      <td>40.00</td>\n",
       "      <td>60.00</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KOR</th>\n",
       "      <td>33.33</td>\n",
       "      <td>66.67</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RUS</th>\n",
       "      <td>31.25</td>\n",
       "      <td>68.75</td>\n",
       "      <td>5</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ISR</th>\n",
       "      <td>28.57</td>\n",
       "      <td>71.43</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CZE</th>\n",
       "      <td>16.67</td>\n",
       "      <td>83.33</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GER</th>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TUR</th>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               pct_above_average  pct_below_average  scores_above_average  \\\n",
       "judge_country                                                               \n",
       "USA                       100.00               0.00                    16   \n",
       "ESP                        80.00              20.00                     8   \n",
       "ITA                        80.00              20.00                     8   \n",
       "CHN                        60.00              40.00                     6   \n",
       "CAN                        43.75              56.25                     7   \n",
       "FRA                        42.86              57.14                     3   \n",
       "JPN                        40.00              60.00                     4   \n",
       "KOR                        33.33              66.67                     2   \n",
       "RUS                        31.25              68.75                     5   \n",
       "ISR                        28.57              71.43                     2   \n",
       "CZE                        16.67              83.33                     1   \n",
       "GER                         0.00             100.00                     0   \n",
       "TUR                         0.00             100.00                     0   \n",
       "\n",
       "               scores_below_average  scores_exactly_average  total_scores  \n",
       "judge_country                                                              \n",
       "USA                               0                       0            16  \n",
       "ESP                               2                       0            10  \n",
       "ITA                               2                       0            10  \n",
       "CHN                               4                       0            10  \n",
       "CAN                               9                       0            16  \n",
       "FRA                               4                       0             7  \n",
       "JPN                               6                       0            10  \n",
       "KOR                               4                       0             6  \n",
       "RUS                              11                       0            16  \n",
       "ISR                               5                       0             7  \n",
       "CZE                               5                       0             6  \n",
       "GER                               5                       0             5  \n",
       "TUR                               5                       0             5  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compare_scores_by_judge_country(\"Maia SHIBUTANI / Alex SHIBUTANI\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Results for Hubbell/Donohue (USA)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
       "      <th>pct_above_average</th>\n",
       "      <th>pct_below_average</th>\n",
       "      <th>scores_above_average</th>\n",
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       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>USA</th>\n",
       "      <td>100.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
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       "    <tr>\n",
       "      <th>ESP</th>\n",
       "      <td>80.00</td>\n",
       "      <td>20.00</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
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       "    <tr>\n",
       "      <th>FRA</th>\n",
       "      <td>77.78</td>\n",
       "      <td>22.22</td>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KOR</th>\n",
       "      <td>66.67</td>\n",
       "      <td>33.33</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
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       "    <tr>\n",
       "      <th>CHN</th>\n",
       "      <td>62.50</td>\n",
       "      <td>37.50</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JPN</th>\n",
       "      <td>60.00</td>\n",
       "      <td>40.00</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TUR</th>\n",
       "      <td>60.00</td>\n",
       "      <td>40.00</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UKR</th>\n",
       "      <td>60.00</td>\n",
       "      <td>40.00</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CAN</th>\n",
       "      <td>31.25</td>\n",
       "      <td>68.75</td>\n",
       "      <td>5</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GER</th>\n",
       "      <td>20.00</td>\n",
       "      <td>80.00</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RUS</th>\n",
       "      <td>18.75</td>\n",
       "      <td>81.25</td>\n",
       "      <td>3</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CZE</th>\n",
       "      <td>16.67</td>\n",
       "      <td>83.33</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ISR</th>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ITA</th>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               pct_above_average  pct_below_average  scores_above_average  \\\n",
       "judge_country                                                               \n",
       "USA                       100.00               0.00                    16   \n",
       "ESP                        80.00              20.00                     8   \n",
       "FRA                        77.78              22.22                     7   \n",
       "KOR                        66.67              33.33                     4   \n",
       "CHN                        62.50              37.50                     5   \n",
       "JPN                        60.00              40.00                     6   \n",
       "TUR                        60.00              40.00                     3   \n",
       "UKR                        60.00              40.00                     3   \n",
       "CAN                        31.25              68.75                     5   \n",
       "GER                        20.00              80.00                     1   \n",
       "RUS                        18.75              81.25                     3   \n",
       "CZE                        16.67              83.33                     1   \n",
       "ISR                         0.00             100.00                     0   \n",
       "ITA                         0.00             100.00                     0   \n",
       "\n",
       "               scores_below_average  scores_exactly_average  total_scores  \n",
       "judge_country                                                              \n",
       "USA                               0                       0            16  \n",
       "ESP                               2                       0            10  \n",
       "FRA                               2                       0             9  \n",
       "KOR                               2                       0             6  \n",
       "CHN                               3                       0             8  \n",
       "JPN                               4                       0            10  \n",
       "TUR                               2                       0             5  \n",
       "UKR                               2                       0             5  \n",
       "CAN                              11                       0            16  \n",
       "GER                               4                       0             5  \n",
       "RUS                              13                       0            16  \n",
       "CZE                               5                       0             6  \n",
       "ISR                               7                       0             7  \n",
       "ITA                              10                       0            10  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compare_scores_by_judge_country(\"Madison HUBBELL / Zachary DONOHUE\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Results for Cappellini/Lanotte (Italy)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pct_above_average</th>\n",
       "      <th>pct_below_average</th>\n",
       "      <th>scores_above_average</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ITA</th>\n",
       "      <td>100.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <th>JPN</th>\n",
       "      <td>100.00</td>\n",
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       "      <td>10</td>\n",
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       "      <th>CHN</th>\n",
       "      <td>75.00</td>\n",
       "      <td>25.00</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UKR</th>\n",
       "      <td>60.00</td>\n",
       "      <td>40.00</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ESP</th>\n",
       "      <td>57.14</td>\n",
       "      <td>42.86</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FRA</th>\n",
       "      <td>28.57</td>\n",
       "      <td>71.43</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
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       "      <th>CAN</th>\n",
       "      <td>25.00</td>\n",
       "      <td>75.00</td>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
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       "    <tr>\n",
       "      <th>RUS</th>\n",
       "      <td>25.00</td>\n",
       "      <td>75.00</td>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
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       "    <tr>\n",
       "      <th>ISR</th>\n",
       "      <td>16.67</td>\n",
       "      <td>83.33</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KOR</th>\n",
       "      <td>16.67</td>\n",
       "      <td>83.33</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>USA</th>\n",
       "      <td>16.67</td>\n",
       "      <td>83.33</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               pct_above_average  pct_below_average  scores_above_average  \\\n",
       "judge_country                                                               \n",
       "ITA                       100.00               0.00                    12   \n",
       "JPN                       100.00               0.00                    10   \n",
       "CHN                        75.00              25.00                     6   \n",
       "UKR                        60.00              40.00                     3   \n",
       "ESP                        57.14              42.86                     4   \n",
       "FRA                        28.57              71.43                     2   \n",
       "CAN                        25.00              75.00                     3   \n",
       "RUS                        25.00              75.00                     3   \n",
       "ISR                        16.67              83.33                     1   \n",
       "KOR                        16.67              83.33                     1   \n",
       "USA                        16.67              83.33                     2   \n",
       "\n",
       "               scores_below_average  scores_exactly_average  total_scores  \n",
       "judge_country                                                              \n",
       "ITA                               0                       0            12  \n",
       "JPN                               0                       0            10  \n",
       "CHN                               2                       0             8  \n",
       "UKR                               2                       0             5  \n",
       "ESP                               3                       0             7  \n",
       "FRA                               5                       0             7  \n",
       "CAN                               9                       0            12  \n",
       "RUS                               9                       0            12  \n",
       "ISR                               5                       0             6  \n",
       "KOR                               5                       0             6  \n",
       "USA                              10                       0            12  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compare_scores_by_judge_country(\"Anna CAPPELLINI / Luca LANOTTE\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Comparing results for the four teams**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>name</th>\n",
       "      <th>Anna CAPPELLINI / Luca LANOTTE</th>\n",
       "      <th>Ekaterina BOBROVA / Dmitri SOLOVIEV</th>\n",
       "      <th>Madison CHOCK / Evan BATES</th>\n",
       "      <th>Maia SHIBUTANI / Alex SHIBUTANI</th>\n",
       "      <th>Anna CAPPELLINI / Luca LANOTTE</th>\n",
       "      <th>Ekaterina BOBROVA / Dmitri SOLOVIEV</th>\n",
       "      <th>Madison CHOCK / Evan BATES</th>\n",
       "      <th>Maia SHIBUTANI / Alex SHIBUTANI</th>\n",
       "      <th>Anna CAPPELLINI / Luca LANOTTE</th>\n",
       "      <th>Ekaterina BOBROVA / Dmitri SOLOVIEV</th>\n",
       "      <th>Madison CHOCK / Evan BATES</th>\n",
       "      <th>Maia SHIBUTANI / Alex SHIBUTANI</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>judge_country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>RUS</th>\n",
       "      <td>25.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>18.75</td>\n",
       "      <td>31.25</td>\n",
       "      <td>3</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JPN</th>\n",
       "      <td>100.00</td>\n",
       "      <td>25.00</td>\n",
       "      <td>87.50</td>\n",
       "      <td>40.00</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ITA</th>\n",
       "      <td>100.00</td>\n",
       "      <td>20.00</td>\n",
       "      <td>20.00</td>\n",
       "      <td>80.00</td>\n",
       "      <td>12</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>USA</th>\n",
       "      <td>16.67</td>\n",
       "      <td>16.67</td>\n",
       "      <td>100.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           pct_above_average  \\\n",
       "name          Anna CAPPELLINI / Luca LANOTTE   \n",
       "judge_country                                  \n",
       "RUS                                    25.00   \n",
       "JPN                                   100.00   \n",
       "ITA                                   100.00   \n",
       "USA                                    16.67   \n",
       "\n",
       "                                                                              \\\n",
       "name          Ekaterina BOBROVA / Dmitri SOLOVIEV Madison CHOCK / Evan BATES   \n",
       "judge_country                                                                  \n",
       "RUS                                        100.00                      18.75   \n",
       "JPN                                         25.00                      87.50   \n",
       "ITA                                         20.00                      20.00   \n",
       "USA                                         16.67                     100.00   \n",
       "\n",
       "                                                        scores_above_average  \\\n",
       "name          Maia SHIBUTANI / Alex SHIBUTANI Anna CAPPELLINI / Luca LANOTTE   \n",
       "judge_country                                                                  \n",
       "RUS                                     31.25                              3   \n",
       "JPN                                     40.00                             10   \n",
       "ITA                                     80.00                             12   \n",
       "USA                                    100.00                              2   \n",
       "\n",
       "                                                                              \\\n",
       "name          Ekaterina BOBROVA / Dmitri SOLOVIEV Madison CHOCK / Evan BATES   \n",
       "judge_country                                                                  \n",
       "RUS                                            12                          3   \n",
       "JPN                                             1                          7   \n",
       "ITA                                             2                          2   \n",
       "USA                                             2                         16   \n",
       "\n",
       "                                                                total_scores  \\\n",
       "name          Maia SHIBUTANI / Alex SHIBUTANI Anna CAPPELLINI / Luca LANOTTE   \n",
       "judge_country                                                                  \n",
       "RUS                                         5                             12   \n",
       "JPN                                         4                             10   \n",
       "ITA                                         8                             12   \n",
       "USA                                        16                             12   \n",
       "\n",
       "                                                                              \\\n",
       "name          Ekaterina BOBROVA / Dmitri SOLOVIEV Madison CHOCK / Evan BATES   \n",
       "judge_country                                                                  \n",
       "RUS                                            12                         16   \n",
       "JPN                                             4                          8   \n",
       "ITA                                            10                         10   \n",
       "USA                                            12                         16   \n",
       "\n",
       "                                               \n",
       "name          Maia SHIBUTANI / Alex SHIBUTANI  \n",
       "judge_country                                  \n",
       "RUS                                        16  \n",
       "JPN                                        10  \n",
       "ITA                                        10  \n",
       "USA                                        16  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "team_scores = judge_points[\n",
    "    (\n",
    "        judge_points[\"name\"].isin([\n",
    "            \"Ekaterina BOBROVA / Dmitri SOLOVIEV\",\n",
    "            \"Madison CHOCK / Evan BATES\",\n",
    "            \"Maia SHIBUTANI / Alex SHIBUTANI\",\n",
    "            \"Anna CAPPELLINI / Luca LANOTTE\"\n",
    "        ])) &\n",
    "    (\n",
    "        judge_points[\"judge_country\"].isin([\n",
    "            \"ITA\", \"RUS\", \"USA\", \"JPN\"\n",
    "        ]))\n",
    "]\n",
    "    \n",
    "grps = team_scores.groupby([\"judge_country\",\"name\"])\n",
    "    \n",
    "team_df = pd.DataFrame({\n",
    "    \"scores_above_average\": grps.apply(lambda x: len(x[x[\"points_vs_avg\"] > 0])),\n",
    "    \"total_scores\": grps.size(),\n",
    "    \"pct_above_average\": round(grps.apply(lambda x: len(x[x[\"points_vs_avg\"] > 0])) / \\\n",
    "        grps.size() * 100, 2)\n",
    "}).unstack()\n",
    "    \n",
    "team_df.sort_values((\"pct_above_average\", \"Ekaterina BOBROVA / Dmitri SOLOVIEV\"), ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "---\n",
    "\n",
    "---"
   ]
  }
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