TV, halftime shows, and the Big Game.ipynb

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   "source": [
    "#  Task 1: TV, halftime shows, and the Big Game\n",
    "   Import pandas under the alias pd.\n",
    "   \n",
    "   Load the dataset's CSV files.\n",
    "\n",
    "   Whether or not you like football, the Super Bowl is a spectacle. There's a little something for everyone at your Super Bowl party. Drama in the form of blowouts, comebacks, and controversy for the sports fan. There are the ridiculously expensive ads, some hilarious, others gut-wrenching, thought-provoking, and weird. The half-time shows with the biggest musicians in the world, sometimes riding giant mechanical tigers or leaping from the roof of the stadium. It's a show, baby. And in this notebook, we're going to find out how some of the elements of this show interact with each other. After exploring and cleaning our data a little, we're going to answer questions like:\n",
    "\n",
    "   What are the most extreme game outcomes?\n",
    "How does the game affect television viewership?\n",
    "How have viewership, TV ratings, and ad cost evolved over time?\n",
    "Who are the most prolific musicians in terms of halftime show performances?\n",
    "\n",
    "  The dataset we'll use was scraped and polished from Wikipedia. It is made up of three CSV files, one with game data, one with TV data, and one with halftime musician data for all 52 Super Bowls through 2018. Let's take a look, using display() instead of print() since its output is much prettier in Jupyter Notebooks."
   ]
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>super_bowl</th>\n",
       "      <th>venue</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>attendance</th>\n",
       "      <th>team_winner</th>\n",
       "      <th>winning_pts</th>\n",
       "      <th>qb_winner_1</th>\n",
       "      <th>qb_winner_2</th>\n",
       "      <th>coach_winner</th>\n",
       "      <th>team_loser</th>\n",
       "      <th>losing_pts</th>\n",
       "      <th>qb_loser_1</th>\n",
       "      <th>qb_loser_2</th>\n",
       "      <th>coach_loser</th>\n",
       "      <th>combined_pts</th>\n",
       "      <th>difference_pts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-02-04</td>\n",
       "      <td>52</td>\n",
       "      <td>U.S. Bank Stadium</td>\n",
       "      <td>Minneapolis</td>\n",
       "      <td>Minnesota</td>\n",
       "      <td>67612</td>\n",
       "      <td>Philadelphia Eagles</td>\n",
       "      <td>41</td>\n",
       "      <td>Nick Foles</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Doug Pederson</td>\n",
       "      <td>New England Patriots</td>\n",
       "      <td>33</td>\n",
       "      <td>Tom Brady</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bill Belichick</td>\n",
       "      <td>74</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017-02-05</td>\n",
       "      <td>51</td>\n",
       "      <td>NRG Stadium</td>\n",
       "      <td>Houston</td>\n",
       "      <td>Texas</td>\n",
       "      <td>70807</td>\n",
       "      <td>New England Patriots</td>\n",
       "      <td>34</td>\n",
       "      <td>Tom Brady</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bill Belichick</td>\n",
       "      <td>Atlanta Falcons</td>\n",
       "      <td>28</td>\n",
       "      <td>Matt Ryan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Dan Quinn</td>\n",
       "      <td>62</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016-02-07</td>\n",
       "      <td>50</td>\n",
       "      <td>Levi's Stadium</td>\n",
       "      <td>Santa Clara</td>\n",
       "      <td>California</td>\n",
       "      <td>71088</td>\n",
       "      <td>Denver Broncos</td>\n",
       "      <td>24</td>\n",
       "      <td>Peyton Manning</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Gary Kubiak</td>\n",
       "      <td>Carolina Panthers</td>\n",
       "      <td>10</td>\n",
       "      <td>Cam Newton</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ron Rivera</td>\n",
       "      <td>34</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015-02-01</td>\n",
       "      <td>49</td>\n",
       "      <td>University of Phoenix Stadium</td>\n",
       "      <td>Glendale</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>70288</td>\n",
       "      <td>New England Patriots</td>\n",
       "      <td>28</td>\n",
       "      <td>Tom Brady</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bill Belichick</td>\n",
       "      <td>Seattle Seahawks</td>\n",
       "      <td>24</td>\n",
       "      <td>Russell Wilson</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Pete Carroll</td>\n",
       "      <td>52</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014-02-02</td>\n",
       "      <td>48</td>\n",
       "      <td>MetLife Stadium</td>\n",
       "      <td>East Rutherford</td>\n",
       "      <td>New Jersey</td>\n",
       "      <td>82529</td>\n",
       "      <td>Seattle Seahawks</td>\n",
       "      <td>43</td>\n",
       "      <td>Russell Wilson</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Pete Carroll</td>\n",
       "      <td>Denver Broncos</td>\n",
       "      <td>8</td>\n",
       "      <td>Peyton Manning</td>\n",
       "      <td>NaN</td>\n",
       "      <td>John Fox</td>\n",
       "      <td>51</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "         date  super_bowl                          venue             city  \\\n",
       "0  2018-02-04          52              U.S. Bank Stadium      Minneapolis   \n",
       "1  2017-02-05          51                    NRG Stadium          Houston   \n",
       "2  2016-02-07          50                 Levi's Stadium      Santa Clara   \n",
       "3  2015-02-01          49  University of Phoenix Stadium         Glendale   \n",
       "4  2014-02-02          48                MetLife Stadium  East Rutherford   \n",
       "\n",
       "        state  attendance           team_winner  winning_pts     qb_winner_1  \\\n",
       "0   Minnesota       67612   Philadelphia Eagles           41      Nick Foles   \n",
       "1       Texas       70807  New England Patriots           34       Tom Brady   \n",
       "2  California       71088        Denver Broncos           24  Peyton Manning   \n",
       "3     Arizona       70288  New England Patriots           28       Tom Brady   \n",
       "4  New Jersey       82529      Seattle Seahawks           43  Russell Wilson   \n",
       "\n",
       "  qb_winner_2    coach_winner            team_loser  losing_pts  \\\n",
       "0         NaN   Doug Pederson  New England Patriots          33   \n",
       "1         NaN  Bill Belichick       Atlanta Falcons          28   \n",
       "2         NaN     Gary Kubiak     Carolina Panthers          10   \n",
       "3         NaN  Bill Belichick      Seattle Seahawks          24   \n",
       "4         NaN    Pete Carroll        Denver Broncos           8   \n",
       "\n",
       "       qb_loser_1 qb_loser_2     coach_loser  combined_pts  difference_pts  \n",
       "0       Tom Brady        NaN  Bill Belichick            74               8  \n",
       "1       Matt Ryan        NaN       Dan Quinn            62               6  \n",
       "2      Cam Newton        NaN      Ron Rivera            34              14  \n",
       "3  Russell Wilson        NaN    Pete Carroll            52               4  \n",
       "4  Peyton Manning        NaN        John Fox            51              35  "
      ]
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>super_bowl</th>\n",
       "      <th>network</th>\n",
       "      <th>avg_us_viewers</th>\n",
       "      <th>total_us_viewers</th>\n",
       "      <th>rating_household</th>\n",
       "      <th>share_household</th>\n",
       "      <th>rating_18_49</th>\n",
       "      <th>share_18_49</th>\n",
       "      <th>ad_cost</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>52</td>\n",
       "      <td>NBC</td>\n",
       "      <td>103390000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>43.1</td>\n",
       "      <td>68</td>\n",
       "      <td>33.4</td>\n",
       "      <td>78.0</td>\n",
       "      <td>5000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>51</td>\n",
       "      <td>Fox</td>\n",
       "      <td>111319000</td>\n",
       "      <td>172000000.0</td>\n",
       "      <td>45.3</td>\n",
       "      <td>73</td>\n",
       "      <td>37.1</td>\n",
       "      <td>79.0</td>\n",
       "      <td>5000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>50</td>\n",
       "      <td>CBS</td>\n",
       "      <td>111864000</td>\n",
       "      <td>167000000.0</td>\n",
       "      <td>46.6</td>\n",
       "      <td>72</td>\n",
       "      <td>37.7</td>\n",
       "      <td>79.0</td>\n",
       "      <td>5000000</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>49</td>\n",
       "      <td>NBC</td>\n",
       "      <td>114442000</td>\n",
       "      <td>168000000.0</td>\n",
       "      <td>47.5</td>\n",
       "      <td>71</td>\n",
       "      <td>39.1</td>\n",
       "      <td>79.0</td>\n",
       "      <td>4500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>48</td>\n",
       "      <td>Fox</td>\n",
       "      <td>112191000</td>\n",
       "      <td>167000000.0</td>\n",
       "      <td>46.7</td>\n",
       "      <td>69</td>\n",
       "      <td>39.3</td>\n",
       "      <td>77.0</td>\n",
       "      <td>4000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "   super_bowl network  avg_us_viewers  total_us_viewers  rating_household  \\\n",
       "0          52     NBC       103390000               NaN              43.1   \n",
       "1          51     Fox       111319000       172000000.0              45.3   \n",
       "2          50     CBS       111864000       167000000.0              46.6   \n",
       "3          49     NBC       114442000       168000000.0              47.5   \n",
       "4          48     Fox       112191000       167000000.0              46.7   \n",
       "\n",
       "   share_household  rating_18_49  share_18_49  ad_cost  \n",
       "0               68          33.4         78.0  5000000  \n",
       "1               73          37.1         79.0  5000000  \n",
       "2               72          37.7         79.0  5000000  \n",
       "3               71          39.1         79.0  4500000  \n",
       "4               69          39.3         77.0  4000000  "
      ]
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>super_bowl</th>\n",
       "      <th>musician</th>\n",
       "      <th>num_songs</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>52</td>\n",
       "      <td>Justin Timberlake</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>52</td>\n",
       "      <td>University of Minnesota Marching Band</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>51</td>\n",
       "      <td>Lady Gaga</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>50</td>\n",
       "      <td>Coldplay</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>50</td>\n",
       "      <td>Beyoncé</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "   super_bowl                               musician  num_songs\n",
       "0          52                      Justin Timberlake       11.0\n",
       "1          52  University of Minnesota Marching Band        1.0\n",
       "2          51                              Lady Gaga        7.0\n",
       "3          50                               Coldplay        6.0\n",
       "4          50                                Beyoncé        3.0"
      ]
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   "source": [
    "# Import pandas\n",
    "import pandas as pd\n",
    "\n",
    "# Load the CSV data into DataFrames\n",
    "super_bowls = pd.read_csv('/users/CongZhang/Documents/Datacamp/TV_Project/super_bowls.txt')\n",
    "tv = pd.read_csv('/users/CongZhang/Documents/Datacamp/TV_Project/tv.txt')\n",
    "halftime_musicians = pd.read_csv('/users/CongZhang/Documents/Datacamp/TV_Project/halftime_musicians.txt')\n",
    "\n",
    "# Display the first five rows of each DataFrame\n",
    "display(super_bowls.head())\n",
    "display(tv.head())\n",
    "display(halftime_musicians.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Task 2. Taking note of dataset issues\n",
    "\n",
    "Display and inspect the summaries of the TV and halftime musician DataFrames for issues.\n",
    "\n",
    "For the Super Bowl game data, we can see the dataset appears whole except for missing values in the backup quarterback columns (qb_winner_2 and qb_loser_2), which make sense given most starting QBs in the Super Bowl (qb_winner_1 and qb_loser_1) play the entire game.\n",
    "\n",
    "From the visual inspection of TV and halftime musicians data, there is only one missing value displayed, but I've got a hunch there are more. The Super Bowl goes all the way back to 1967, and the more granular columns (e.g. the number of songs for halftime musicians) probably weren't tracked reliably over time. Wikipedia is great but not perfect.\n",
    "\n",
    "An inspection of the .info() output for tv and halftime_musicians shows us that there are multiple columns with null values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 53 entries, 0 to 52\n",
      "Data columns (total 9 columns):\n",
      " #   Column            Non-Null Count  Dtype  \n",
      "---  ------            --------------  -----  \n",
      " 0   super_bowl        53 non-null     int64  \n",
      " 1   network           53 non-null     object \n",
      " 2   avg_us_viewers    53 non-null     int64  \n",
      " 3   total_us_viewers  15 non-null     float64\n",
      " 4   rating_household  53 non-null     float64\n",
      " 5   share_household   53 non-null     int64  \n",
      " 6   rating_18_49      15 non-null     float64\n",
      " 7   share_18_49       6 non-null      float64\n",
      " 8   ad_cost           53 non-null     int64  \n",
      "dtypes: float64(4), int64(4), object(1)\n",
      "memory usage: 3.9+ KB\n",
      "\n",
      "\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 134 entries, 0 to 133\n",
      "Data columns (total 3 columns):\n",
      " #   Column      Non-Null Count  Dtype  \n",
      "---  ------      --------------  -----  \n",
      " 0   super_bowl  134 non-null    int64  \n",
      " 1   musician    134 non-null    object \n",
      " 2   num_songs   88 non-null     float64\n",
      "dtypes: float64(1), int64(1), object(1)\n",
      "memory usage: 3.3+ KB\n"
     ]
    }
   ],
   "source": [
    "# Summary of the TV data to inspect\n",
    "tv.info()\n",
    "\n",
    "print('\\n')\n",
    "\n",
    "# Summary of the halftime musician data to inspect\n",
    "halftime_musicians.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Task 3: Combined points distribution\n",
    "Plot a histogram of combined points then display the rows with the most extreme combined point outcomes.\n",
    "\n",
    "For the TV data, the following columns have missing values and a lot of them:\n",
    "\n",
    "total_us_viewers (amount of U.S. viewers who watched at least some part of the broadcast)\n",
    "rating_18_49 (average % of U.S. adults 18-49 who live in a household with a TV that were watching for the entire broadcast)\n",
    "share_18_49 (average % of U.S. adults 18-49 who live in a household with a TV in use that were watching for the entire broadcast)\n",
    "For the halftime musician data, there are missing numbers of songs performed (num_songs) for about a third of the performances.\n",
    "\n",
    "There are a lot of potential reasons for these missing values. Was the data ever tracked? Was it lost in history? Is the research effort to make this data whole worth it? Maybe. Watching every Super Bowl halftime show to get song counts would be pretty fun. But we don't have the time to do that kind of stuff now! Let's take note of where the dataset isn't perfect and start uncovering some insights.\n",
    "\n",
    "Let's start by looking at combined points for each Super Bowl by visualizing the distribution. Let's also **pinpoint** the Super Bowls with the highest and lowest scores.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>super_bowl</th>\n",
       "      <th>venue</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>attendance</th>\n",
       "      <th>team_winner</th>\n",
       "      <th>winning_pts</th>\n",
       "      <th>qb_winner_1</th>\n",
       "      <th>qb_winner_2</th>\n",
       "      <th>coach_winner</th>\n",
       "      <th>team_loser</th>\n",
       "      <th>losing_pts</th>\n",
       "      <th>qb_loser_1</th>\n",
       "      <th>qb_loser_2</th>\n",
       "      <th>coach_loser</th>\n",
       "      <th>combined_pts</th>\n",
       "      <th>difference_pts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-02-04</td>\n",
       "      <td>52</td>\n",
       "      <td>U.S. Bank Stadium</td>\n",
       "      <td>Minneapolis</td>\n",
       "      <td>Minnesota</td>\n",
       "      <td>67612</td>\n",
       "      <td>Philadelphia Eagles</td>\n",
       "      <td>41</td>\n",
       "      <td>Nick Foles</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Doug Pederson</td>\n",
       "      <td>New England Patriots</td>\n",
       "      <td>33</td>\n",
       "      <td>Tom Brady</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bill Belichick</td>\n",
       "      <td>74</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1995-01-29</td>\n",
       "      <td>29</td>\n",
       "      <td>Joe Robbie Stadium</td>\n",
       "      <td>Miami Gardens</td>\n",
       "      <td>Florida</td>\n",
       "      <td>74107</td>\n",
       "      <td>San Francisco 49ers</td>\n",
       "      <td>49</td>\n",
       "      <td>Steve Young</td>\n",
       "      <td>NaN</td>\n",
       "      <td>George Seifert</td>\n",
       "      <td>San Diego Chargers</td>\n",
       "      <td>26</td>\n",
       "      <td>Stan Humphreys</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bobby Ross</td>\n",
       "      <td>75</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          date  super_bowl               venue           city      state  \\\n",
       "0   2018-02-04          52   U.S. Bank Stadium    Minneapolis  Minnesota   \n",
       "23  1995-01-29          29  Joe Robbie Stadium  Miami Gardens    Florida   \n",
       "\n",
       "    attendance          team_winner  winning_pts  qb_winner_1 qb_winner_2  \\\n",
       "0        67612  Philadelphia Eagles           41   Nick Foles         NaN   \n",
       "23       74107  San Francisco 49ers           49  Steve Young         NaN   \n",
       "\n",
       "      coach_winner            team_loser  losing_pts      qb_loser_1  \\\n",
       "0    Doug Pederson  New England Patriots          33       Tom Brady   \n",
       "23  George Seifert    San Diego Chargers          26  Stan Humphreys   \n",
       "\n",
       "   qb_loser_2     coach_loser  combined_pts  difference_pts  \n",
       "0         NaN  Bill Belichick            74               8  \n",
       "23        NaN      Bobby Ross            75              23  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>super_bowl</th>\n",
       "      <th>venue</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>attendance</th>\n",
       "      <th>team_winner</th>\n",
       "      <th>winning_pts</th>\n",
       "      <th>qb_winner_1</th>\n",
       "      <th>qb_winner_2</th>\n",
       "      <th>coach_winner</th>\n",
       "      <th>team_loser</th>\n",
       "      <th>losing_pts</th>\n",
       "      <th>qb_loser_1</th>\n",
       "      <th>qb_loser_2</th>\n",
       "      <th>coach_loser</th>\n",
       "      <th>combined_pts</th>\n",
       "      <th>difference_pts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>1975-01-12</td>\n",
       "      <td>9</td>\n",
       "      <td>Tulane Stadium</td>\n",
       "      <td>New Orleans</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>80997</td>\n",
       "      <td>Pittsburgh Steelers</td>\n",
       "      <td>16</td>\n",
       "      <td>Terry Bradshaw</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Chuck Noll</td>\n",
       "      <td>Minnesota Vikings</td>\n",
       "      <td>6</td>\n",
       "      <td>Fran Tarkenton</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bud Grant</td>\n",
       "      <td>22</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>1973-01-14</td>\n",
       "      <td>7</td>\n",
       "      <td>Memorial Coliseum</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "      <td>90182</td>\n",
       "      <td>Miami Dolphins</td>\n",
       "      <td>14</td>\n",
       "      <td>Bob Griese</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Don Shula</td>\n",
       "      <td>Washington Redskins</td>\n",
       "      <td>7</td>\n",
       "      <td>Bill Kilmer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>George Allen</td>\n",
       "      <td>21</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>1969-01-12</td>\n",
       "      <td>3</td>\n",
       "      <td>Orange Bowl</td>\n",
       "      <td>Miami</td>\n",
       "      <td>Florida</td>\n",
       "      <td>75389</td>\n",
       "      <td>New York Jets</td>\n",
       "      <td>16</td>\n",
       "      <td>Joe Namath</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Weeb Ewbank</td>\n",
       "      <td>Baltimore Colts</td>\n",
       "      <td>7</td>\n",
       "      <td>Earl Morrall</td>\n",
       "      <td>Johnny Unitas</td>\n",
       "      <td>Don Shula</td>\n",
       "      <td>23</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          date  super_bowl              venue         city       state  \\\n",
       "43  1975-01-12           9     Tulane Stadium  New Orleans   Louisiana   \n",
       "45  1973-01-14           7  Memorial Coliseum  Los Angeles  California   \n",
       "49  1969-01-12           3        Orange Bowl        Miami     Florida   \n",
       "\n",
       "    attendance          team_winner  winning_pts     qb_winner_1 qb_winner_2  \\\n",
       "43       80997  Pittsburgh Steelers           16  Terry Bradshaw         NaN   \n",
       "45       90182       Miami Dolphins           14      Bob Griese         NaN   \n",
       "49       75389        New York Jets           16      Joe Namath         NaN   \n",
       "\n",
       "   coach_winner           team_loser  losing_pts      qb_loser_1  \\\n",
       "43   Chuck Noll    Minnesota Vikings           6  Fran Tarkenton   \n",
       "45    Don Shula  Washington Redskins           7     Bill Kilmer   \n",
       "49  Weeb Ewbank      Baltimore Colts           7    Earl Morrall   \n",
       "\n",
       "       qb_loser_2   coach_loser  combined_pts  difference_pts  \n",
       "43            NaN     Bud Grant            22              10  \n",
       "45            NaN  George Allen            21               7  \n",
       "49  Johnny Unitas     Don Shula            23               9  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Import matplotlib and set plotting style\n",
    "from matplotlib import pyplot as plt\n",
    "%matplotlib inline\n",
    "plt.style.use('seaborn')\n",
    "\n",
    "# Plot a histogram of combined points\n",
    "# ... YOUR CODE FOR TASK 3 ...\n",
    "plt.hist(super_bowls['combined_pts'])\n",
    "plt.xlabel('Combined Points')\n",
    "plt.ylabel('Number of Super Bowls')\n",
    "plt.show()\n",
    "\n",
    "# Display the Super Bowls with the highest and lowest combined scores\n",
    "display(super_bowls[super_bowls['combined_pts'] > 70])\n",
    "print('\\n')\n",
    "display(super_bowls[super_bowls['combined_pts'] < 25])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Task 4: Point difference distribution\n",
    "\n",
    "### Modify and display the histogram of point differences, then display the rows with the most extreme point difference outcomes.\n",
    "\n",
    "Most combined scores are around 40-50 points, with the extremes being roughly equal distance away in opposite directions. Going up to the highest combined scores at 74 and 75, we find two games featuring dominant quarterback performances. One even happened recently in 2018's Super Bowl LII where Tom Brady's Patriots lost to Nick Foles' underdog Eagles 41-33 for a combined score of 74.\n",
    "\n",
    "Going down to the lowest combined scores, we have Super Bowl III and VII, which featured tough defenses that dominated. We also have Super Bowl IX in New Orleans in 1975, whose 16-6 score can be attributed to inclement weather. The field was slick from overnight rain, and it was cold at 46 °F (8 °C), making it hard for the Steelers and Vikings to do much offensively. This was the second-coldest Super Bowl ever and the last to be played in inclement weather for over 30 years. The NFL realized people like points, I guess.\n",
    "\n",
    "UPDATE: In Super Bowl LIII in 2019, the Patriots and Rams broke the record for the lowest-scoring Super Bowl with a combined score of 16 points (13-3 for the Patriots).\n",
    "\n",
    "Let's take a look at point difference now."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>super_bowl</th>\n",
       "      <th>venue</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>attendance</th>\n",
       "      <th>team_winner</th>\n",
       "      <th>winning_pts</th>\n",
       "      <th>qb_winner_1</th>\n",
       "      <th>qb_winner_2</th>\n",
       "      <th>coach_winner</th>\n",
       "      <th>team_loser</th>\n",
       "      <th>losing_pts</th>\n",
       "      <th>qb_loser_1</th>\n",
       "      <th>qb_loser_2</th>\n",
       "      <th>coach_loser</th>\n",
       "      <th>combined_pts</th>\n",
       "      <th>difference_pts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1991-01-27</td>\n",
       "      <td>25</td>\n",
       "      <td>Tampa Stadium</td>\n",
       "      <td>Tampa</td>\n",
       "      <td>Florida</td>\n",
       "      <td>73813</td>\n",
       "      <td>New York Giants</td>\n",
       "      <td>20</td>\n",
       "      <td>Jeff Hostetler</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bill Parcells</td>\n",
       "      <td>Buffalo Bills</td>\n",
       "      <td>19</td>\n",
       "      <td>Jim Kelly</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Marv Levy</td>\n",
       "      <td>39</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          date  super_bowl          venue   city    state  attendance  \\\n",
       "27  1991-01-27          25  Tampa Stadium  Tampa  Florida       73813   \n",
       "\n",
       "        team_winner  winning_pts     qb_winner_1 qb_winner_2   coach_winner  \\\n",
       "27  New York Giants           20  Jeff Hostetler         NaN  Bill Parcells   \n",
       "\n",
       "       team_loser  losing_pts qb_loser_1 qb_loser_2 coach_loser  combined_pts  \\\n",
       "27  Buffalo Bills          19  Jim Kelly        NaN   Marv Levy            39   \n",
       "\n",
       "    difference_pts  \n",
       "27               1  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n"
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    {
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       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>super_bowl</th>\n",
       "      <th>venue</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>attendance</th>\n",
       "      <th>team_winner</th>\n",
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       "      <th>qb_winner_1</th>\n",
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       "      <th>coach_winner</th>\n",
       "      <th>team_loser</th>\n",
       "      <th>losing_pts</th>\n",
       "      <th>qb_loser_1</th>\n",
       "      <th>qb_loser_2</th>\n",
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       "      <th>combined_pts</th>\n",
       "      <th>difference_pts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014-02-02</td>\n",
       "      <td>48</td>\n",
       "      <td>MetLife Stadium</td>\n",
       "      <td>East Rutherford</td>\n",
       "      <td>New Jersey</td>\n",
       "      <td>82529</td>\n",
       "      <td>Seattle Seahawks</td>\n",
       "      <td>43</td>\n",
       "      <td>Russell Wilson</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Pete Carroll</td>\n",
       "      <td>Denver Broncos</td>\n",
       "      <td>8</td>\n",
       "      <td>Peyton Manning</td>\n",
       "      <td>NaN</td>\n",
       "      <td>John Fox</td>\n",
       "      <td>51</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1993-01-31</td>\n",
       "      <td>27</td>\n",
       "      <td>Rose Bowl</td>\n",
       "      <td>Pasadena</td>\n",
       "      <td>California</td>\n",
       "      <td>98374</td>\n",
       "      <td>Dallas Cowboys</td>\n",
       "      <td>52</td>\n",
       "      <td>Troy Aikman</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Jimmy Johnson</td>\n",
       "      <td>Buffalo Bills</td>\n",
       "      <td>17</td>\n",
       "      <td>Jim Kelly</td>\n",
       "      <td>Frank Reich</td>\n",
       "      <td>Marv Levy</td>\n",
       "      <td>69</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1990-01-28</td>\n",
       "      <td>24</td>\n",
       "      <td>Louisiana Superdome</td>\n",
       "      <td>New Orleans</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>72919</td>\n",
       "      <td>San Francisco 49ers</td>\n",
       "      <td>55</td>\n",
       "      <td>Joe Montana</td>\n",
       "      <td>NaN</td>\n",
       "      <td>George Seifert</td>\n",
       "      <td>Denver Broncos</td>\n",
       "      <td>10</td>\n",
       "      <td>John Elway</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Dan Reeves</td>\n",
       "      <td>65</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>1986-01-26</td>\n",
       "      <td>20</td>\n",
       "      <td>Louisiana Superdome</td>\n",
       "      <td>New Orleans</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>73818</td>\n",
       "      <td>Chicago Bears</td>\n",
       "      <td>46</td>\n",
       "      <td>Jim McMahon</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mike Ditka</td>\n",
       "      <td>New England Patriots</td>\n",
       "      <td>10</td>\n",
       "      <td>Tony Eason</td>\n",
       "      <td>Steve Grogan</td>\n",
       "      <td>Raymond Berry</td>\n",
       "      <td>56</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          date  super_bowl                venue             city       state  \\\n",
       "4   2014-02-02          48      MetLife Stadium  East Rutherford  New Jersey   \n",
       "25  1993-01-31          27            Rose Bowl         Pasadena  California   \n",
       "28  1990-01-28          24  Louisiana Superdome      New Orleans   Louisiana   \n",
       "32  1986-01-26          20  Louisiana Superdome      New Orleans   Louisiana   \n",
       "\n",
       "    attendance          team_winner  winning_pts     qb_winner_1 qb_winner_2  \\\n",
       "4        82529     Seattle Seahawks           43  Russell Wilson         NaN   \n",
       "25       98374       Dallas Cowboys           52     Troy Aikman         NaN   \n",
       "28       72919  San Francisco 49ers           55     Joe Montana         NaN   \n",
       "32       73818        Chicago Bears           46     Jim McMahon         NaN   \n",
       "\n",
       "      coach_winner            team_loser  losing_pts      qb_loser_1  \\\n",
       "4     Pete Carroll        Denver Broncos           8  Peyton Manning   \n",
       "25   Jimmy Johnson         Buffalo Bills          17       Jim Kelly   \n",
       "28  George Seifert        Denver Broncos          10      John Elway   \n",
       "32      Mike Ditka  New England Patriots          10      Tony Eason   \n",
       "\n",
       "      qb_loser_2    coach_loser  combined_pts  difference_pts  \n",
       "4            NaN       John Fox            51              35  \n",
       "25   Frank Reich      Marv Levy            69              35  \n",
       "28           NaN     Dan Reeves            65              45  \n",
       "32  Steve Grogan  Raymond Berry            56              36  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot a histogram of point differences\n",
    "plt.hist(super_bowls.difference_pts)\n",
    "plt.xlabel('Point Difference')\n",
    "plt.ylabel('Number of Super Bowls')\n",
    "plt.show()\n",
    "\n",
    "\n",
    "# Display the closest game(s) and biggest blowouts\n",
    "display(super_bowls[super_bowls['difference_pts']==1])\n",
    "\n",
    "print('\\n')\n",
    "\n",
    "display(super_bowls[super_bowls['difference_pts']>=35])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Task 5. Do blowouts translate to lost viewers?\n",
    "\n",
    "### Import seaborn and plot household share vs. point difference.\n",
    "\n",
    "The vast majority of Super Bowls are close games. Makes sense. Both teams are likely to be deserving if they've made it this far. The closest game ever was when the Buffalo Bills lost to the New York Giants by 1 point in 1991, which was best remembered for Scott Norwood's last-second missed field goal attempt that went wide right, kicking off four Bills Super Bowl losses in a row. Poor Scott. The biggest point discrepancy ever was 45 points (!) where Hall of Famer Joe Montana's led the San Francisco 49ers to victory in 1990, one year before the closest game ever.\n",
    "\n",
    "I remember watching the Seahawks crush the Broncos by 35 points (43-8) in 2014, which was a boring experience in my opinion. The game was never really close. I'm pretty sure we changed the channel at the end of the third quarter. Let's combine our game data and TV to see if this is a universal phenomenon. Do large point differences translate to lost viewers? We can plot household share (average percentage of U.S. households with a TV in use that were watching for the entire broadcast) vs. point difference to find out."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>super_bowl</th>\n",
       "      <th>network</th>\n",
       "      <th>avg_us_viewers</th>\n",
       "      <th>total_us_viewers</th>\n",
       "      <th>rating_household</th>\n",
       "      <th>share_household</th>\n",
       "      <th>rating_18_49</th>\n",
       "      <th>share_18_49</th>\n",
       "      <th>ad_cost</th>\n",
       "      <th>date</th>\n",
       "      <th>...</th>\n",
       "      <th>qb_winner_1</th>\n",
       "      <th>qb_winner_2</th>\n",
       "      <th>coach_winner</th>\n",
       "      <th>team_loser</th>\n",
       "      <th>losing_pts</th>\n",
       "      <th>qb_loser_1</th>\n",
       "      <th>qb_loser_2</th>\n",
       "      <th>coach_loser</th>\n",
       "      <th>combined_pts</th>\n",
       "      <th>difference_pts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>52</td>\n",
       "      <td>NBC</td>\n",
       "      <td>103390000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>43.1</td>\n",
       "      <td>68</td>\n",
       "      <td>33.4</td>\n",
       "      <td>78.0</td>\n",
       "      <td>5000000</td>\n",
       "      <td>2018-02-04</td>\n",
       "      <td>...</td>\n",
       "      <td>Nick Foles</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Doug Pederson</td>\n",
       "      <td>New England Patriots</td>\n",
       "      <td>33</td>\n",
       "      <td>Tom Brady</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bill Belichick</td>\n",
       "      <td>74</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>51</td>\n",
       "      <td>Fox</td>\n",
       "      <td>111319000</td>\n",
       "      <td>172000000.0</td>\n",
       "      <td>45.3</td>\n",
       "      <td>73</td>\n",
       "      <td>37.1</td>\n",
       "      <td>79.0</td>\n",
       "      <td>5000000</td>\n",
       "      <td>2017-02-05</td>\n",
       "      <td>...</td>\n",
       "      <td>Tom Brady</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bill Belichick</td>\n",
       "      <td>Atlanta Falcons</td>\n",
       "      <td>28</td>\n",
       "      <td>Matt Ryan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Dan Quinn</td>\n",
       "      <td>62</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>50</td>\n",
       "      <td>CBS</td>\n",
       "      <td>111864000</td>\n",
       "      <td>167000000.0</td>\n",
       "      <td>46.6</td>\n",
       "      <td>72</td>\n",
       "      <td>37.7</td>\n",
       "      <td>79.0</td>\n",
       "      <td>5000000</td>\n",
       "      <td>2016-02-07</td>\n",
       "      <td>...</td>\n",
       "      <td>Peyton Manning</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Gary Kubiak</td>\n",
       "      <td>Carolina Panthers</td>\n",
       "      <td>10</td>\n",
       "      <td>Cam Newton</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ron Rivera</td>\n",
       "      <td>34</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>49</td>\n",
       "      <td>NBC</td>\n",
       "      <td>114442000</td>\n",
       "      <td>168000000.0</td>\n",
       "      <td>47.5</td>\n",
       "      <td>71</td>\n",
       "      <td>39.1</td>\n",
       "      <td>79.0</td>\n",
       "      <td>4500000</td>\n",
       "      <td>2015-02-01</td>\n",
       "      <td>...</td>\n",
       "      <td>Tom Brady</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bill Belichick</td>\n",
       "      <td>Seattle Seahawks</td>\n",
       "      <td>24</td>\n",
       "      <td>Russell Wilson</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Pete Carroll</td>\n",
       "      <td>52</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>48</td>\n",
       "      <td>Fox</td>\n",
       "      <td>112191000</td>\n",
       "      <td>167000000.0</td>\n",
       "      <td>46.7</td>\n",
       "      <td>69</td>\n",
       "      <td>39.3</td>\n",
       "      <td>77.0</td>\n",
       "      <td>4000000</td>\n",
       "      <td>2014-02-02</td>\n",
       "      <td>...</td>\n",
       "      <td>Russell Wilson</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Pete Carroll</td>\n",
       "      <td>Denver Broncos</td>\n",
       "      <td>8</td>\n",
       "      <td>Peyton Manning</td>\n",
       "      <td>NaN</td>\n",
       "      <td>John Fox</td>\n",
       "      <td>51</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   super_bowl network  avg_us_viewers  total_us_viewers  rating_household  \\\n",
       "0          52     NBC       103390000               NaN              43.1   \n",
       "1          51     Fox       111319000       172000000.0              45.3   \n",
       "2          50     CBS       111864000       167000000.0              46.6   \n",
       "3          49     NBC       114442000       168000000.0              47.5   \n",
       "4          48     Fox       112191000       167000000.0              46.7   \n",
       "\n",
       "   share_household  rating_18_49  share_18_49  ad_cost        date  ...  \\\n",
       "0               68          33.4         78.0  5000000  2018-02-04  ...   \n",
       "1               73          37.1         79.0  5000000  2017-02-05  ...   \n",
       "2               72          37.7         79.0  5000000  2016-02-07  ...   \n",
       "3               71          39.1         79.0  4500000  2015-02-01  ...   \n",
       "4               69          39.3         77.0  4000000  2014-02-02  ...   \n",
       "\n",
       "      qb_winner_1 qb_winner_2    coach_winner            team_loser  \\\n",
       "0      Nick Foles         NaN   Doug Pederson  New England Patriots   \n",
       "1       Tom Brady         NaN  Bill Belichick       Atlanta Falcons   \n",
       "2  Peyton Manning         NaN     Gary Kubiak     Carolina Panthers   \n",
       "3       Tom Brady         NaN  Bill Belichick      Seattle Seahawks   \n",
       "4  Russell Wilson         NaN    Pete Carroll        Denver Broncos   \n",
       "\n",
       "  losing_pts      qb_loser_1 qb_loser_2     coach_loser combined_pts  \\\n",
       "0         33       Tom Brady        NaN  Bill Belichick           74   \n",
       "1         28       Matt Ryan        NaN       Dan Quinn           62   \n",
       "2         10      Cam Newton        NaN      Ron Rivera           34   \n",
       "3         24  Russell Wilson        NaN    Pete Carroll           52   \n",
       "4          8  Peyton Manning        NaN        John Fox           51   \n",
       "\n",
       "  difference_pts  \n",
       "0              8  \n",
       "1              6  \n",
       "2             14  \n",
       "3              4  \n",
       "4             35  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
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     "text": [
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1c605710>"
      ]
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     "execution_count": 35,
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    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Join game and TV data, filtering out SB I (super_bowl==1)  because it was split over two networks\n",
    "games_tv = pd.merge(tv[tv['super_bowl'] > 1], super_bowls, on='super_bowl')\n",
    "display(games_tv.head())\n",
    "\n",
    "print('\\n')\n",
    "\n",
    "# Import seaborn\n",
    "import seaborn as sns\n",
    "\n",
    "# Create a scatter plot with a linear regression model fit\n",
    "sns.regplot(x='difference_pts', y='share_household', data=games_tv)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>super_bowl</th>\n",
       "      <th>venue</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>attendance</th>\n",
       "      <th>team_winner</th>\n",
       "      <th>winning_pts</th>\n",
       "      <th>qb_winner_1</th>\n",
       "      <th>qb_winner_2</th>\n",
       "      <th>coach_winner</th>\n",
       "      <th>team_loser</th>\n",
       "      <th>losing_pts</th>\n",
       "      <th>qb_loser_1</th>\n",
       "      <th>qb_loser_2</th>\n",
       "      <th>coach_loser</th>\n",
       "      <th>combined_pts</th>\n",
       "      <th>difference_pts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-02-04</td>\n",
       "      <td>52</td>\n",
       "      <td>U.S. Bank Stadium</td>\n",
       "      <td>Minneapolis</td>\n",
       "      <td>Minnesota</td>\n",
       "      <td>67612</td>\n",
       "      <td>Philadelphia Eagles</td>\n",
       "      <td>41</td>\n",
       "      <td>Nick Foles</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Doug Pederson</td>\n",
       "      <td>New England Patriots</td>\n",
       "      <td>33</td>\n",
       "      <td>Tom Brady</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bill Belichick</td>\n",
       "      <td>74</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017-02-05</td>\n",
       "      <td>51</td>\n",
       "      <td>NRG Stadium</td>\n",
       "      <td>Houston</td>\n",
       "      <td>Texas</td>\n",
       "      <td>70807</td>\n",
       "      <td>New England Patriots</td>\n",
       "      <td>34</td>\n",
       "      <td>Tom Brady</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bill Belichick</td>\n",
       "      <td>Atlanta Falcons</td>\n",
       "      <td>28</td>\n",
       "      <td>Matt Ryan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Dan Quinn</td>\n",
       "      <td>62</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016-02-07</td>\n",
       "      <td>50</td>\n",
       "      <td>Levi's Stadium</td>\n",
       "      <td>Santa Clara</td>\n",
       "      <td>California</td>\n",
       "      <td>71088</td>\n",
       "      <td>Denver Broncos</td>\n",
       "      <td>24</td>\n",
       "      <td>Peyton Manning</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Gary Kubiak</td>\n",
       "      <td>Carolina Panthers</td>\n",
       "      <td>10</td>\n",
       "      <td>Cam Newton</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ron Rivera</td>\n",
       "      <td>34</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015-02-01</td>\n",
       "      <td>49</td>\n",
       "      <td>University of Phoenix Stadium</td>\n",
       "      <td>Glendale</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>70288</td>\n",
       "      <td>New England Patriots</td>\n",
       "      <td>28</td>\n",
       "      <td>Tom Brady</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bill Belichick</td>\n",
       "      <td>Seattle Seahawks</td>\n",
       "      <td>24</td>\n",
       "      <td>Russell Wilson</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Pete Carroll</td>\n",
       "      <td>52</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014-02-02</td>\n",
       "      <td>48</td>\n",
       "      <td>MetLife Stadium</td>\n",
       "      <td>East Rutherford</td>\n",
       "      <td>New Jersey</td>\n",
       "      <td>82529</td>\n",
       "      <td>Seattle Seahawks</td>\n",
       "      <td>43</td>\n",
       "      <td>Russell Wilson</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Pete Carroll</td>\n",
       "      <td>Denver Broncos</td>\n",
       "      <td>8</td>\n",
       "      <td>Peyton Manning</td>\n",
       "      <td>NaN</td>\n",
       "      <td>John Fox</td>\n",
       "      <td>51</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2013-02-03</td>\n",
       "      <td>47</td>\n",
       "      <td>Mercedes-Benz Superdome</td>\n",
       "      <td>New Orleans</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>71024</td>\n",
       "      <td>Baltimore Ravens</td>\n",
       "      <td>34</td>\n",
       "      <td>Joe Flacco</td>\n",
       "      <td>NaN</td>\n",
       "      <td>John Harbaugh</td>\n",
       "      <td>San Francisco 49ers</td>\n",
       "      <td>31</td>\n",
       "      <td>Colin Kaepernick</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Jim Harbaugh</td>\n",
       "      <td>65</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2012-02-05</td>\n",
       "      <td>46</td>\n",
       "      <td>Lucas Oil Stadium</td>\n",
       "      <td>Indianapolis</td>\n",
       "      <td>Indiana</td>\n",
       "      <td>68658</td>\n",
       "      <td>New York Giants</td>\n",
       "      <td>21</td>\n",
       "      <td>Eli Manning</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Tom Coughlin</td>\n",
       "      <td>New England Patriots</td>\n",
       "      <td>17</td>\n",
       "      <td>Tom Brady</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bill Belichick</td>\n",
       "      <td>38</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2011-02-06</td>\n",
       "      <td>45</td>\n",
       "      <td>Cowboys Stadium</td>\n",
       "      <td>Arlington</td>\n",
       "      <td>Texas</td>\n",
       "      <td>103219</td>\n",
       "      <td>Green Bay Packers</td>\n",
       "      <td>31</td>\n",
       "      <td>Aaron Rodgers</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mike McCarthy</td>\n",
       "      <td>Pittsburgh Steelers</td>\n",
       "      <td>25</td>\n",
       "      <td>Ben Roethlisberger</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mike Tomlin</td>\n",
       "      <td>56</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2010-02-07</td>\n",
       "      <td>44</td>\n",
       "      <td>Sun Life Stadium</td>\n",
       "      <td>Miami Gardens</td>\n",
       "      <td>Florida</td>\n",
       "      <td>74059</td>\n",
       "      <td>New Orleans Saints</td>\n",
       "      <td>31</td>\n",
       "      <td>Drew Brees</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sean Payton</td>\n",
       "      <td>Indianapolis Colts</td>\n",
       "      <td>17</td>\n",
       "      <td>Peyton Manning</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Jim Caldwell</td>\n",
       "      <td>48</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2009-02-01</td>\n",
       "      <td>43</td>\n",
       "      <td>Raymond James Stadium</td>\n",
       "      <td>Tampa</td>\n",
       "      <td>Florida</td>\n",
       "      <td>70774</td>\n",
       "      <td>Pittsburgh Steelers</td>\n",
       "      <td>27</td>\n",
       "      <td>Ben Roethlisberger</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mike Tomlin</td>\n",
       "      <td>Arizona Cardinals</td>\n",
       "      <td>23</td>\n",
       "      <td>Kurt Warner</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ken Whisenhunt</td>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2008-02-03</td>\n",
       "      <td>42</td>\n",
       "      <td>University of Phoenix Stadium</td>\n",
       "      <td>Glendale</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>71101</td>\n",
       "      <td>New York Giants</td>\n",
       "      <td>17</td>\n",
       "      <td>Eli Manning</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Tom Coughlin</td>\n",
       "      <td>New England Patriots</td>\n",
       "      <td>14</td>\n",
       "      <td>Tom Brady</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bill Belichick</td>\n",
       "      <td>31</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2007-02-04</td>\n",
       "      <td>41</td>\n",
       "      <td>Dolphin Stadium</td>\n",
       "      <td>Miami Gardens</td>\n",
       "      <td>Florida</td>\n",
       "      <td>74512</td>\n",
       "      <td>Indianapolis Colts</td>\n",
       "      <td>29</td>\n",
       "      <td>Peyton Manning</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Tony Dungy</td>\n",
       "      <td>Chicago Bears</td>\n",
       "      <td>17</td>\n",
       "      <td>Rex Grossman</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lovie Smith</td>\n",
       "      <td>46</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2006-02-05</td>\n",
       "      <td>40</td>\n",
       "      <td>Ford Field</td>\n",
       "      <td>Detroit</td>\n",
       "      <td>Michigan</td>\n",
       "      <td>68206</td>\n",
       "      <td>Pittsburgh Steelers</td>\n",
       "      <td>21</td>\n",
       "      <td>Ben Roethlisberger</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bill Cowher</td>\n",
       "      <td>Seattle Seahawks</td>\n",
       "      <td>10</td>\n",
       "      <td>Matt Hasselbeck</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mike Holmgren</td>\n",
       "      <td>31</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2005-02-06</td>\n",
       "      <td>39</td>\n",
       "      <td>Alltel Stadium</td>\n",
       "      <td>Jacksonville</td>\n",
       "      <td>Florida</td>\n",
       "      <td>78125</td>\n",
       "      <td>New England Patriots</td>\n",
       "      <td>24</td>\n",
       "      <td>Tom Brady</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bill Belichick</td>\n",
       "      <td>Philadelphia Eagles</td>\n",
       "      <td>21</td>\n",
       "      <td>Donovan McNabb</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Andy Reid</td>\n",
       "      <td>45</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2004-02-01</td>\n",
       "      <td>38</td>\n",
       "      <td>Reliant Stadium</td>\n",
       "      <td>Houston</td>\n",
       "      <td>Texas</td>\n",
       "      <td>71525</td>\n",
       "      <td>New England Patriots</td>\n",
       "      <td>32</td>\n",
       "      <td>Tom Brady</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bill Belichick</td>\n",
       "      <td>Carolina Panthers</td>\n",
       "      <td>29</td>\n",
       "      <td>Jake Delhomme</td>\n",
       "      <td>NaN</td>\n",
       "      <td>John Fox</td>\n",
       "      <td>61</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2003-01-26</td>\n",
       "      <td>37</td>\n",
       "      <td>Qualcomm Stadium</td>\n",
       "      <td>San Diego</td>\n",
       "      <td>California</td>\n",
       "      <td>67603</td>\n",
       "      <td>Tampa Bay Buccaneers</td>\n",
       "      <td>48</td>\n",
       "      <td>Brad Johnson</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Jon Gruden</td>\n",
       "      <td>Oakland Raiders</td>\n",
       "      <td>21</td>\n",
       "      <td>Rich Gannon</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bill Callahan</td>\n",
       "      <td>69</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2002-02-03</td>\n",
       "      <td>36</td>\n",
       "      <td>Louisiana Superdome</td>\n",
       "      <td>New Orleans</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>72922</td>\n",
       "      <td>New England Patriots</td>\n",
       "      <td>20</td>\n",
       "      <td>Tom Brady</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bill Belichick</td>\n",
       "      <td>St. Louis Rams</td>\n",
       "      <td>17</td>\n",
       "      <td>Kurt Warner</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mike Martz</td>\n",
       "      <td>37</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2001-01-28</td>\n",
       "      <td>35</td>\n",
       "      <td>Raymond James Stadium</td>\n",
       "      <td>Tampa</td>\n",
       "      <td>Florida</td>\n",
       "      <td>71921</td>\n",
       "      <td>Baltimore Ravens</td>\n",
       "      <td>34</td>\n",
       "      <td>Trent Dilfer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Brian Billick</td>\n",
       "      <td>New York Giants</td>\n",
       "      <td>7</td>\n",
       "      <td>Kerry Collins</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Jim Fassel</td>\n",
       "      <td>41</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2000-01-30</td>\n",
       "      <td>34</td>\n",
       "      <td>Georgia Dome</td>\n",
       "      <td>Atlanta</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>72625</td>\n",
       "      <td>St. Louis Rams</td>\n",
       "      <td>23</td>\n",
       "      <td>Kurt Warner</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Dick Vermeil</td>\n",
       "      <td>Tennessee Titans</td>\n",
       "      <td>16</td>\n",
       "      <td>Steve McNair</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Jeff Fisher</td>\n",
       "      <td>39</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1999-01-31</td>\n",
       "      <td>33</td>\n",
       "      <td>Pro Player Stadium</td>\n",
       "      <td>Miami Gardens</td>\n",
       "      <td>Florida</td>\n",
       "      <td>74803</td>\n",
       "      <td>Denver Broncos</td>\n",
       "      <td>34</td>\n",
       "      <td>John Elway</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mike Shanahan</td>\n",
       "      <td>Atlanta Falcons</td>\n",
       "      <td>19</td>\n",
       "      <td>Chris Chandler</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Dan Reeves</td>\n",
       "      <td>53</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1998-01-25</td>\n",
       "      <td>32</td>\n",
       "      <td>Qualcomm Stadium</td>\n",
       "      <td>San Diego</td>\n",
       "      <td>California</td>\n",
       "      <td>68912</td>\n",
       "      <td>Denver Broncos</td>\n",
       "      <td>31</td>\n",
       "      <td>John Elway</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mike Shanahan</td>\n",
       "      <td>Green Bay Packers</td>\n",
       "      <td>24</td>\n",
       "      <td>Brett Favre</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mike Holmgren</td>\n",
       "      <td>55</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1997-01-26</td>\n",
       "      <td>31</td>\n",
       "      <td>Louisiana Superdome</td>\n",
       "      <td>New Orleans</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>72301</td>\n",
       "      <td>Green Bay Packers</td>\n",
       "      <td>35</td>\n",
       "      <td>Brett Favre</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mike Holmgren</td>\n",
       "      <td>New England Patriots</td>\n",
       "      <td>21</td>\n",
       "      <td>Drew Bledsoe</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bill Parcells</td>\n",
       "      <td>56</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1996-01-28</td>\n",
       "      <td>30</td>\n",
       "      <td>Sun Devil Stadium</td>\n",
       "      <td>Tempe</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>76347</td>\n",
       "      <td>Dallas Cowboys</td>\n",
       "      <td>27</td>\n",
       "      <td>Troy Aikman</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Barry Switzer</td>\n",
       "      <td>Pittsburgh Steelers</td>\n",
       "      <td>17</td>\n",
       "      <td>Neil O'Donnell</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bill Cowher</td>\n",
       "      <td>44</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1995-01-29</td>\n",
       "      <td>29</td>\n",
       "      <td>Joe Robbie Stadium</td>\n",
       "      <td>Miami Gardens</td>\n",
       "      <td>Florida</td>\n",
       "      <td>74107</td>\n",
       "      <td>San Francisco 49ers</td>\n",
       "      <td>49</td>\n",
       "      <td>Steve Young</td>\n",
       "      <td>NaN</td>\n",
       "      <td>George Seifert</td>\n",
       "      <td>San Diego Chargers</td>\n",
       "      <td>26</td>\n",
       "      <td>Stan Humphreys</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bobby Ross</td>\n",
       "      <td>75</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1994-01-30</td>\n",
       "      <td>28</td>\n",
       "      <td>Georgia Dome</td>\n",
       "      <td>Atlanta</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>72817</td>\n",
       "      <td>Dallas Cowboys</td>\n",
       "      <td>30</td>\n",
       "      <td>Troy Aikman</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Jimmy Johnson</td>\n",
       "      <td>Buffalo Bills</td>\n",
       "      <td>13</td>\n",
       "      <td>Jim Kelly</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Marv Levy</td>\n",
       "      <td>43</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1993-01-31</td>\n",
       "      <td>27</td>\n",
       "      <td>Rose Bowl</td>\n",
       "      <td>Pasadena</td>\n",
       "      <td>California</td>\n",
       "      <td>98374</td>\n",
       "      <td>Dallas Cowboys</td>\n",
       "      <td>52</td>\n",
       "      <td>Troy Aikman</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Jimmy Johnson</td>\n",
       "      <td>Buffalo Bills</td>\n",
       "      <td>17</td>\n",
       "      <td>Jim Kelly</td>\n",
       "      <td>Frank Reich</td>\n",
       "      <td>Marv Levy</td>\n",
       "      <td>69</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1992-01-26</td>\n",
       "      <td>26</td>\n",
       "      <td>Metrodome</td>\n",
       "      <td>Minneapolis</td>\n",
       "      <td>Minnesota</td>\n",
       "      <td>63130</td>\n",
       "      <td>Washington Redskins</td>\n",
       "      <td>37</td>\n",
       "      <td>Mark Rypien</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Joe Gibbs</td>\n",
       "      <td>Buffalo Bills</td>\n",
       "      <td>24</td>\n",
       "      <td>Jim Kelly</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Marv Levy</td>\n",
       "      <td>61</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1991-01-27</td>\n",
       "      <td>25</td>\n",
       "      <td>Tampa Stadium</td>\n",
       "      <td>Tampa</td>\n",
       "      <td>Florida</td>\n",
       "      <td>73813</td>\n",
       "      <td>New York Giants</td>\n",
       "      <td>20</td>\n",
       "      <td>Jeff Hostetler</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bill Parcells</td>\n",
       "      <td>Buffalo Bills</td>\n",
       "      <td>19</td>\n",
       "      <td>Jim Kelly</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Marv Levy</td>\n",
       "      <td>39</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1990-01-28</td>\n",
       "      <td>24</td>\n",
       "      <td>Louisiana Superdome</td>\n",
       "      <td>New Orleans</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>72919</td>\n",
       "      <td>San Francisco 49ers</td>\n",
       "      <td>55</td>\n",
       "      <td>Joe Montana</td>\n",
       "      <td>NaN</td>\n",
       "      <td>George Seifert</td>\n",
       "      <td>Denver Broncos</td>\n",
       "      <td>10</td>\n",
       "      <td>John Elway</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Dan Reeves</td>\n",
       "      <td>65</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1989-01-22</td>\n",
       "      <td>23</td>\n",
       "      <td>Joe Robbie Stadium</td>\n",
       "      <td>Miami Gardens</td>\n",
       "      <td>Florida</td>\n",
       "      <td>75129</td>\n",
       "      <td>San Francisco 49ers</td>\n",
       "      <td>20</td>\n",
       "      <td>Joe Montana</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bill Walsh</td>\n",
       "      <td>Cincinnati Bengals</td>\n",
       "      <td>16</td>\n",
       "      <td>Boomer Esiason</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sam Wyche</td>\n",
       "      <td>36</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>1988-01-31</td>\n",
       "      <td>22</td>\n",
       "      <td>Jack Murphy Stadium</td>\n",
       "      <td>San Diego</td>\n",
       "      <td>California</td>\n",
       "      <td>73302</td>\n",
       "      <td>Washington Redskins</td>\n",
       "      <td>42</td>\n",
       "      <td>Doug Williams</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Joe Gibbs</td>\n",
       "      <td>Denver Broncos</td>\n",
       "      <td>10</td>\n",
       "      <td>John Elway</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Dan Reeves</td>\n",
       "      <td>52</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>1987-01-25</td>\n",
       "      <td>21</td>\n",
       "      <td>Rose Bowl</td>\n",
       "      <td>Pasadena</td>\n",
       "      <td>California</td>\n",
       "      <td>101063</td>\n",
       "      <td>New York Giants</td>\n",
       "      <td>39</td>\n",
       "      <td>Phil Simms</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bill Parcells</td>\n",
       "      <td>Denver Broncos</td>\n",
       "      <td>20</td>\n",
       "      <td>John Elway</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Dan Reeves</td>\n",
       "      <td>59</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>1986-01-26</td>\n",
       "      <td>20</td>\n",
       "      <td>Louisiana Superdome</td>\n",
       "      <td>New Orleans</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>73818</td>\n",
       "      <td>Chicago Bears</td>\n",
       "      <td>46</td>\n",
       "      <td>Jim McMahon</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mike Ditka</td>\n",
       "      <td>New England Patriots</td>\n",
       "      <td>10</td>\n",
       "      <td>Tony Eason</td>\n",
       "      <td>Steve Grogan</td>\n",
       "      <td>Raymond Berry</td>\n",
       "      <td>56</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>1985-01-20</td>\n",
       "      <td>19</td>\n",
       "      <td>Stanford Stadium</td>\n",
       "      <td>Palo Alto</td>\n",
       "      <td>California</td>\n",
       "      <td>84059</td>\n",
       "      <td>San Francisco 49ers</td>\n",
       "      <td>38</td>\n",
       "      <td>Joe Montano</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bill Walsh</td>\n",
       "      <td>Miami Dolphins</td>\n",
       "      <td>16</td>\n",
       "      <td>Dan Marino</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Don Shula</td>\n",
       "      <td>54</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>1984-01-22</td>\n",
       "      <td>18</td>\n",
       "      <td>Tampa Stadium</td>\n",
       "      <td>Tampa</td>\n",
       "      <td>Florida</td>\n",
       "      <td>72920</td>\n",
       "      <td>Los Angeles Raiders</td>\n",
       "      <td>38</td>\n",
       "      <td>Jim Plunkett</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Tom Flores</td>\n",
       "      <td>Washington Redskins</td>\n",
       "      <td>9</td>\n",
       "      <td>Joe Theismann</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Joe Gibbs</td>\n",
       "      <td>47</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>1983-01-30</td>\n",
       "      <td>17</td>\n",
       "      <td>Rose Bowl</td>\n",
       "      <td>Pasadena</td>\n",
       "      <td>California</td>\n",
       "      <td>103667</td>\n",
       "      <td>Washington Redskins</td>\n",
       "      <td>27</td>\n",
       "      <td>Joe Theismann</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Joe Gibbs</td>\n",
       "      <td>Miami Dolphins</td>\n",
       "      <td>17</td>\n",
       "      <td>David Woodley</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Don Shula</td>\n",
       "      <td>44</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>1982-01-24</td>\n",
       "      <td>16</td>\n",
       "      <td>Pontiac Silverdome</td>\n",
       "      <td>Pontiac</td>\n",
       "      <td>Michigan</td>\n",
       "      <td>81270</td>\n",
       "      <td>San Francisco 49ers</td>\n",
       "      <td>26</td>\n",
       "      <td>Joe Montana</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bill Walsh</td>\n",
       "      <td>Cincinnati Bengals</td>\n",
       "      <td>21</td>\n",
       "      <td>Ken Anderson</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Forrest Gregg</td>\n",
       "      <td>47</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>1981-01-25</td>\n",
       "      <td>15</td>\n",
       "      <td>Louisiana Superdome</td>\n",
       "      <td>New Orleans</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>76135</td>\n",
       "      <td>Oakland Raiders</td>\n",
       "      <td>27</td>\n",
       "      <td>Jim Plunkett</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Tom Flores</td>\n",
       "      <td>Philadelphia Eagles</td>\n",
       "      <td>10</td>\n",
       "      <td>Ron Jaworski</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Dick Vermeil</td>\n",
       "      <td>37</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>1980-01-20</td>\n",
       "      <td>14</td>\n",
       "      <td>Rose Bowl</td>\n",
       "      <td>Pasadena</td>\n",
       "      <td>California</td>\n",
       "      <td>103985</td>\n",
       "      <td>Pittsburgh Steelers</td>\n",
       "      <td>31</td>\n",
       "      <td>Terry Bradshaw</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Chuck Noll</td>\n",
       "      <td>Los Angeles Rams</td>\n",
       "      <td>19</td>\n",
       "      <td>Vince Ferragamo</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ray Malavasi</td>\n",
       "      <td>50</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>1979-01-21</td>\n",
       "      <td>13</td>\n",
       "      <td>Orange Bowl</td>\n",
       "      <td>Miami</td>\n",
       "      <td>Florida</td>\n",
       "      <td>79484</td>\n",
       "      <td>Pittsburgh Steelers</td>\n",
       "      <td>35</td>\n",
       "      <td>Terry Bradshaw</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Chuck Noll</td>\n",
       "      <td>Dallas Cowboys</td>\n",
       "      <td>31</td>\n",
       "      <td>Roger Staubach</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Tom Landry</td>\n",
       "      <td>66</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>1978-01-15</td>\n",
       "      <td>12</td>\n",
       "      <td>Superdome</td>\n",
       "      <td>New Orleans</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>76400</td>\n",
       "      <td>Dallas Cowboys</td>\n",
       "      <td>27</td>\n",
       "      <td>Roger Staubach</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Tom Landry</td>\n",
       "      <td>Denver Broncos</td>\n",
       "      <td>10</td>\n",
       "      <td>Craig Morton</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Red Miller</td>\n",
       "      <td>37</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>1977-01-09</td>\n",
       "      <td>11</td>\n",
       "      <td>Rose Bowl</td>\n",
       "      <td>Pasadena</td>\n",
       "      <td>California</td>\n",
       "      <td>103438</td>\n",
       "      <td>Oakland Raiders</td>\n",
       "      <td>32</td>\n",
       "      <td>Kenny Stabler</td>\n",
       "      <td>NaN</td>\n",
       "      <td>John Madden</td>\n",
       "      <td>Minnesota Vikings</td>\n",
       "      <td>14</td>\n",
       "      <td>Fran Tarkenton</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bud Grant</td>\n",
       "      <td>46</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>1976-01-18</td>\n",
       "      <td>10</td>\n",
       "      <td>Orange Bowl</td>\n",
       "      <td>Miami</td>\n",
       "      <td>Florida</td>\n",
       "      <td>80187</td>\n",
       "      <td>Pittsburgh Steelers</td>\n",
       "      <td>21</td>\n",
       "      <td>Terry Bradshaw</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Chuck Noll</td>\n",
       "      <td>Dallas Cowboys</td>\n",
       "      <td>17</td>\n",
       "      <td>Roger Staubach</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Tom Landry</td>\n",
       "      <td>38</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>1975-01-12</td>\n",
       "      <td>9</td>\n",
       "      <td>Tulane Stadium</td>\n",
       "      <td>New Orleans</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>80997</td>\n",
       "      <td>Pittsburgh Steelers</td>\n",
       "      <td>16</td>\n",
       "      <td>Terry Bradshaw</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Chuck Noll</td>\n",
       "      <td>Minnesota Vikings</td>\n",
       "      <td>6</td>\n",
       "      <td>Fran Tarkenton</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bud Grant</td>\n",
       "      <td>22</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>1974-01-13</td>\n",
       "      <td>8</td>\n",
       "      <td>Rice Stadium</td>\n",
       "      <td>Houston</td>\n",
       "      <td>Texas</td>\n",
       "      <td>71882</td>\n",
       "      <td>Miami Dolphins</td>\n",
       "      <td>24</td>\n",
       "      <td>Bob Griese</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Don Shula</td>\n",
       "      <td>Minnesota Vikings</td>\n",
       "      <td>7</td>\n",
       "      <td>Fran Tarkenton</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bud Grant</td>\n",
       "      <td>31</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>1973-01-14</td>\n",
       "      <td>7</td>\n",
       "      <td>Memorial Coliseum</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "      <td>90182</td>\n",
       "      <td>Miami Dolphins</td>\n",
       "      <td>14</td>\n",
       "      <td>Bob Griese</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Don Shula</td>\n",
       "      <td>Washington Redskins</td>\n",
       "      <td>7</td>\n",
       "      <td>Bill Kilmer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>George Allen</td>\n",
       "      <td>21</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>1972-01-16</td>\n",
       "      <td>6</td>\n",
       "      <td>Tulane Stadium</td>\n",
       "      <td>New Orleans</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>81023</td>\n",
       "      <td>Dallas Cowboys</td>\n",
       "      <td>24</td>\n",
       "      <td>Roger Staubach</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Tom Landry</td>\n",
       "      <td>Miami Dolphins</td>\n",
       "      <td>3</td>\n",
       "      <td>Bob Griese</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Don Shula</td>\n",
       "      <td>27</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>1971-01-17</td>\n",
       "      <td>5</td>\n",
       "      <td>Orange Bowl</td>\n",
       "      <td>Miami</td>\n",
       "      <td>Florida</td>\n",
       "      <td>79204</td>\n",
       "      <td>Baltimore Colts</td>\n",
       "      <td>16</td>\n",
       "      <td>Earl Morrall</td>\n",
       "      <td>Johnny Unitas</td>\n",
       "      <td>Don McCafferty</td>\n",
       "      <td>Dallas Cowboys</td>\n",
       "      <td>13</td>\n",
       "      <td>Craig Morton</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Tom Landry</td>\n",
       "      <td>29</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>1970-01-11</td>\n",
       "      <td>4</td>\n",
       "      <td>Tulane Stadium</td>\n",
       "      <td>New Orleans</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>80562</td>\n",
       "      <td>Kansas City Chiefs</td>\n",
       "      <td>23</td>\n",
       "      <td>Len Dawson</td>\n",
       "      <td>Mike Livingston</td>\n",
       "      <td>Hank Stram</td>\n",
       "      <td>Minnesota Vikings</td>\n",
       "      <td>7</td>\n",
       "      <td>Joe Kapp</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bud Grant</td>\n",
       "      <td>30</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>1969-01-12</td>\n",
       "      <td>3</td>\n",
       "      <td>Orange Bowl</td>\n",
       "      <td>Miami</td>\n",
       "      <td>Florida</td>\n",
       "      <td>75389</td>\n",
       "      <td>New York Jets</td>\n",
       "      <td>16</td>\n",
       "      <td>Joe Namath</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Weeb Ewbank</td>\n",
       "      <td>Baltimore Colts</td>\n",
       "      <td>7</td>\n",
       "      <td>Earl Morrall</td>\n",
       "      <td>Johnny Unitas</td>\n",
       "      <td>Don Shula</td>\n",
       "      <td>23</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>1968-01-14</td>\n",
       "      <td>2</td>\n",
       "      <td>Orange Bowl</td>\n",
       "      <td>Miami</td>\n",
       "      <td>Florida</td>\n",
       "      <td>75546</td>\n",
       "      <td>Green Bay Packers</td>\n",
       "      <td>33</td>\n",
       "      <td>Bart Starr</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vince Lombardi</td>\n",
       "      <td>Oakland Raiders</td>\n",
       "      <td>14</td>\n",
       "      <td>Daryle Lamonica</td>\n",
       "      <td>NaN</td>\n",
       "      <td>John Rauch</td>\n",
       "      <td>47</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>1967-01-15</td>\n",
       "      <td>1</td>\n",
       "      <td>Memorial Coliseum</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "      <td>61946</td>\n",
       "      <td>Green Bay Packers</td>\n",
       "      <td>35</td>\n",
       "      <td>Bart Starr</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vince Lombardi</td>\n",
       "      <td>Kansas City Chiefs</td>\n",
       "      <td>10</td>\n",
       "      <td>Len Dawson</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Hank Stram</td>\n",
       "      <td>45</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          date  super_bowl                          venue             city  \\\n",
       "0   2018-02-04          52              U.S. Bank Stadium      Minneapolis   \n",
       "1   2017-02-05          51                    NRG Stadium          Houston   \n",
       "2   2016-02-07          50                 Levi's Stadium      Santa Clara   \n",
       "3   2015-02-01          49  University of Phoenix Stadium         Glendale   \n",
       "4   2014-02-02          48                MetLife Stadium  East Rutherford   \n",
       "5   2013-02-03          47        Mercedes-Benz Superdome      New Orleans   \n",
       "6   2012-02-05          46              Lucas Oil Stadium     Indianapolis   \n",
       "7   2011-02-06          45                Cowboys Stadium        Arlington   \n",
       "8   2010-02-07          44               Sun Life Stadium    Miami Gardens   \n",
       "9   2009-02-01          43          Raymond James Stadium            Tampa   \n",
       "10  2008-02-03          42  University of Phoenix Stadium         Glendale   \n",
       "11  2007-02-04          41                Dolphin Stadium    Miami Gardens   \n",
       "12  2006-02-05          40                     Ford Field          Detroit   \n",
       "13  2005-02-06          39                 Alltel Stadium     Jacksonville   \n",
       "14  2004-02-01          38                Reliant Stadium          Houston   \n",
       "15  2003-01-26          37               Qualcomm Stadium        San Diego   \n",
       "16  2002-02-03          36            Louisiana Superdome      New Orleans   \n",
       "17  2001-01-28          35          Raymond James Stadium            Tampa   \n",
       "18  2000-01-30          34                   Georgia Dome          Atlanta   \n",
       "19  1999-01-31          33             Pro Player Stadium    Miami Gardens   \n",
       "20  1998-01-25          32               Qualcomm Stadium        San Diego   \n",
       "21  1997-01-26          31            Louisiana Superdome      New Orleans   \n",
       "22  1996-01-28          30              Sun Devil Stadium            Tempe   \n",
       "23  1995-01-29          29             Joe Robbie Stadium    Miami Gardens   \n",
       "24  1994-01-30          28                   Georgia Dome          Atlanta   \n",
       "25  1993-01-31          27                      Rose Bowl         Pasadena   \n",
       "26  1992-01-26          26                      Metrodome      Minneapolis   \n",
       "27  1991-01-27          25                  Tampa Stadium            Tampa   \n",
       "28  1990-01-28          24            Louisiana Superdome      New Orleans   \n",
       "29  1989-01-22          23             Joe Robbie Stadium    Miami Gardens   \n",
       "30  1988-01-31          22            Jack Murphy Stadium        San Diego   \n",
       "31  1987-01-25          21                      Rose Bowl         Pasadena   \n",
       "32  1986-01-26          20            Louisiana Superdome      New Orleans   \n",
       "33  1985-01-20          19               Stanford Stadium        Palo Alto   \n",
       "34  1984-01-22          18                  Tampa Stadium            Tampa   \n",
       "35  1983-01-30          17                      Rose Bowl         Pasadena   \n",
       "36  1982-01-24          16             Pontiac Silverdome          Pontiac   \n",
       "37  1981-01-25          15            Louisiana Superdome      New Orleans   \n",
       "38  1980-01-20          14                      Rose Bowl         Pasadena   \n",
       "39  1979-01-21          13                    Orange Bowl            Miami   \n",
       "40  1978-01-15          12                      Superdome      New Orleans   \n",
       "41  1977-01-09          11                      Rose Bowl         Pasadena   \n",
       "42  1976-01-18          10                    Orange Bowl            Miami   \n",
       "43  1975-01-12           9                 Tulane Stadium      New Orleans   \n",
       "44  1974-01-13           8                   Rice Stadium          Houston   \n",
       "45  1973-01-14           7              Memorial Coliseum      Los Angeles   \n",
       "46  1972-01-16           6                 Tulane Stadium      New Orleans   \n",
       "47  1971-01-17           5                    Orange Bowl            Miami   \n",
       "48  1970-01-11           4                 Tulane Stadium      New Orleans   \n",
       "49  1969-01-12           3                    Orange Bowl            Miami   \n",
       "50  1968-01-14           2                    Orange Bowl            Miami   \n",
       "51  1967-01-15           1              Memorial Coliseum      Los Angeles   \n",
       "\n",
       "         state  attendance           team_winner  winning_pts  \\\n",
       "0    Minnesota       67612   Philadelphia Eagles           41   \n",
       "1        Texas       70807  New England Patriots           34   \n",
       "2   California       71088        Denver Broncos           24   \n",
       "3      Arizona       70288  New England Patriots           28   \n",
       "4   New Jersey       82529      Seattle Seahawks           43   \n",
       "5    Louisiana       71024      Baltimore Ravens           34   \n",
       "6      Indiana       68658       New York Giants           21   \n",
       "7        Texas      103219     Green Bay Packers           31   \n",
       "8      Florida       74059    New Orleans Saints           31   \n",
       "9      Florida       70774   Pittsburgh Steelers           27   \n",
       "10     Arizona       71101       New York Giants           17   \n",
       "11     Florida       74512    Indianapolis Colts           29   \n",
       "12    Michigan       68206   Pittsburgh Steelers           21   \n",
       "13     Florida       78125  New England Patriots           24   \n",
       "14       Texas       71525  New England Patriots           32   \n",
       "15  California       67603  Tampa Bay Buccaneers           48   \n",
       "16   Louisiana       72922  New England Patriots           20   \n",
       "17     Florida       71921      Baltimore Ravens           34   \n",
       "18     Georgia       72625        St. Louis Rams           23   \n",
       "19     Florida       74803        Denver Broncos           34   \n",
       "20  California       68912        Denver Broncos           31   \n",
       "21   Louisiana       72301     Green Bay Packers           35   \n",
       "22     Arizona       76347        Dallas Cowboys           27   \n",
       "23     Florida       74107   San Francisco 49ers           49   \n",
       "24     Georgia       72817        Dallas Cowboys           30   \n",
       "25  California       98374        Dallas Cowboys           52   \n",
       "26   Minnesota       63130   Washington Redskins           37   \n",
       "27     Florida       73813       New York Giants           20   \n",
       "28   Louisiana       72919   San Francisco 49ers           55   \n",
       "29     Florida       75129   San Francisco 49ers           20   \n",
       "30  California       73302   Washington Redskins           42   \n",
       "31  California      101063       New York Giants           39   \n",
       "32   Louisiana       73818         Chicago Bears           46   \n",
       "33  California       84059   San Francisco 49ers           38   \n",
       "34     Florida       72920   Los Angeles Raiders           38   \n",
       "35  California      103667   Washington Redskins           27   \n",
       "36    Michigan       81270   San Francisco 49ers           26   \n",
       "37   Louisiana       76135       Oakland Raiders           27   \n",
       "38  California      103985   Pittsburgh Steelers           31   \n",
       "39     Florida       79484   Pittsburgh Steelers           35   \n",
       "40   Louisiana       76400        Dallas Cowboys           27   \n",
       "41  California      103438       Oakland Raiders           32   \n",
       "42     Florida       80187   Pittsburgh Steelers           21   \n",
       "43   Louisiana       80997   Pittsburgh Steelers           16   \n",
       "44       Texas       71882        Miami Dolphins           24   \n",
       "45  California       90182        Miami Dolphins           14   \n",
       "46   Louisiana       81023        Dallas Cowboys           24   \n",
       "47     Florida       79204       Baltimore Colts           16   \n",
       "48   Louisiana       80562    Kansas City Chiefs           23   \n",
       "49     Florida       75389         New York Jets           16   \n",
       "50     Florida       75546     Green Bay Packers           33   \n",
       "51  California       61946     Green Bay Packers           35   \n",
       "\n",
       "           qb_winner_1      qb_winner_2    coach_winner            team_loser  \\\n",
       "0           Nick Foles              NaN   Doug Pederson  New England Patriots   \n",
       "1            Tom Brady              NaN  Bill Belichick       Atlanta Falcons   \n",
       "2       Peyton Manning              NaN     Gary Kubiak     Carolina Panthers   \n",
       "3            Tom Brady              NaN  Bill Belichick      Seattle Seahawks   \n",
       "4       Russell Wilson              NaN    Pete Carroll        Denver Broncos   \n",
       "5           Joe Flacco              NaN   John Harbaugh   San Francisco 49ers   \n",
       "6          Eli Manning              NaN    Tom Coughlin  New England Patriots   \n",
       "7        Aaron Rodgers              NaN   Mike McCarthy   Pittsburgh Steelers   \n",
       "8           Drew Brees              NaN     Sean Payton    Indianapolis Colts   \n",
       "9   Ben Roethlisberger              NaN     Mike Tomlin     Arizona Cardinals   \n",
       "10         Eli Manning              NaN    Tom Coughlin  New England Patriots   \n",
       "11      Peyton Manning              NaN      Tony Dungy         Chicago Bears   \n",
       "12  Ben Roethlisberger              NaN     Bill Cowher      Seattle Seahawks   \n",
       "13           Tom Brady              NaN  Bill Belichick   Philadelphia Eagles   \n",
       "14           Tom Brady              NaN  Bill Belichick     Carolina Panthers   \n",
       "15        Brad Johnson              NaN      Jon Gruden       Oakland Raiders   \n",
       "16           Tom Brady              NaN  Bill Belichick        St. Louis Rams   \n",
       "17        Trent Dilfer              NaN   Brian Billick       New York Giants   \n",
       "18         Kurt Warner              NaN    Dick Vermeil      Tennessee Titans   \n",
       "19          John Elway              NaN   Mike Shanahan       Atlanta Falcons   \n",
       "20          John Elway              NaN   Mike Shanahan     Green Bay Packers   \n",
       "21         Brett Favre              NaN   Mike Holmgren  New England Patriots   \n",
       "22         Troy Aikman              NaN   Barry Switzer   Pittsburgh Steelers   \n",
       "23         Steve Young              NaN  George Seifert    San Diego Chargers   \n",
       "24         Troy Aikman              NaN   Jimmy Johnson         Buffalo Bills   \n",
       "25         Troy Aikman              NaN   Jimmy Johnson         Buffalo Bills   \n",
       "26         Mark Rypien              NaN       Joe Gibbs         Buffalo Bills   \n",
       "27      Jeff Hostetler              NaN   Bill Parcells         Buffalo Bills   \n",
       "28         Joe Montana              NaN  George Seifert        Denver Broncos   \n",
       "29         Joe Montana              NaN      Bill Walsh    Cincinnati Bengals   \n",
       "30       Doug Williams              NaN       Joe Gibbs        Denver Broncos   \n",
       "31          Phil Simms              NaN   Bill Parcells        Denver Broncos   \n",
       "32         Jim McMahon              NaN      Mike Ditka  New England Patriots   \n",
       "33         Joe Montano              NaN      Bill Walsh        Miami Dolphins   \n",
       "34        Jim Plunkett              NaN      Tom Flores   Washington Redskins   \n",
       "35       Joe Theismann              NaN       Joe Gibbs        Miami Dolphins   \n",
       "36         Joe Montana              NaN      Bill Walsh    Cincinnati Bengals   \n",
       "37        Jim Plunkett              NaN      Tom Flores   Philadelphia Eagles   \n",
       "38      Terry Bradshaw              NaN      Chuck Noll      Los Angeles Rams   \n",
       "39      Terry Bradshaw              NaN      Chuck Noll        Dallas Cowboys   \n",
       "40      Roger Staubach              NaN      Tom Landry        Denver Broncos   \n",
       "41       Kenny Stabler              NaN     John Madden     Minnesota Vikings   \n",
       "42      Terry Bradshaw              NaN      Chuck Noll        Dallas Cowboys   \n",
       "43      Terry Bradshaw              NaN      Chuck Noll     Minnesota Vikings   \n",
       "44          Bob Griese              NaN       Don Shula     Minnesota Vikings   \n",
       "45          Bob Griese              NaN       Don Shula   Washington Redskins   \n",
       "46      Roger Staubach              NaN      Tom Landry        Miami Dolphins   \n",
       "47        Earl Morrall    Johnny Unitas  Don McCafferty        Dallas Cowboys   \n",
       "48          Len Dawson  Mike Livingston      Hank Stram     Minnesota Vikings   \n",
       "49          Joe Namath              NaN     Weeb Ewbank       Baltimore Colts   \n",
       "50          Bart Starr              NaN  Vince Lombardi       Oakland Raiders   \n",
       "51          Bart Starr              NaN  Vince Lombardi    Kansas City Chiefs   \n",
       "\n",
       "    losing_pts          qb_loser_1     qb_loser_2     coach_loser  \\\n",
       "0           33           Tom Brady            NaN  Bill Belichick   \n",
       "1           28           Matt Ryan            NaN       Dan Quinn   \n",
       "2           10          Cam Newton            NaN      Ron Rivera   \n",
       "3           24      Russell Wilson            NaN    Pete Carroll   \n",
       "4            8      Peyton Manning            NaN        John Fox   \n",
       "5           31    Colin Kaepernick            NaN    Jim Harbaugh   \n",
       "6           17           Tom Brady            NaN  Bill Belichick   \n",
       "7           25  Ben Roethlisberger            NaN     Mike Tomlin   \n",
       "8           17      Peyton Manning            NaN    Jim Caldwell   \n",
       "9           23         Kurt Warner            NaN  Ken Whisenhunt   \n",
       "10          14           Tom Brady            NaN  Bill Belichick   \n",
       "11          17        Rex Grossman            NaN     Lovie Smith   \n",
       "12          10     Matt Hasselbeck            NaN   Mike Holmgren   \n",
       "13          21      Donovan McNabb            NaN       Andy Reid   \n",
       "14          29       Jake Delhomme            NaN        John Fox   \n",
       "15          21         Rich Gannon            NaN   Bill Callahan   \n",
       "16          17         Kurt Warner            NaN      Mike Martz   \n",
       "17           7       Kerry Collins            NaN      Jim Fassel   \n",
       "18          16        Steve McNair            NaN     Jeff Fisher   \n",
       "19          19      Chris Chandler            NaN      Dan Reeves   \n",
       "20          24         Brett Favre            NaN   Mike Holmgren   \n",
       "21          21        Drew Bledsoe            NaN   Bill Parcells   \n",
       "22          17      Neil O'Donnell            NaN     Bill Cowher   \n",
       "23          26      Stan Humphreys            NaN      Bobby Ross   \n",
       "24          13           Jim Kelly            NaN       Marv Levy   \n",
       "25          17           Jim Kelly    Frank Reich       Marv Levy   \n",
       "26          24           Jim Kelly            NaN       Marv Levy   \n",
       "27          19           Jim Kelly            NaN       Marv Levy   \n",
       "28          10          John Elway            NaN      Dan Reeves   \n",
       "29          16      Boomer Esiason            NaN       Sam Wyche   \n",
       "30          10          John Elway            NaN      Dan Reeves   \n",
       "31          20          John Elway            NaN      Dan Reeves   \n",
       "32          10          Tony Eason   Steve Grogan   Raymond Berry   \n",
       "33          16          Dan Marino            NaN       Don Shula   \n",
       "34           9       Joe Theismann            NaN       Joe Gibbs   \n",
       "35          17       David Woodley            NaN       Don Shula   \n",
       "36          21        Ken Anderson            NaN   Forrest Gregg   \n",
       "37          10        Ron Jaworski            NaN    Dick Vermeil   \n",
       "38          19     Vince Ferragamo            NaN    Ray Malavasi   \n",
       "39          31      Roger Staubach            NaN      Tom Landry   \n",
       "40          10        Craig Morton            NaN      Red Miller   \n",
       "41          14      Fran Tarkenton            NaN       Bud Grant   \n",
       "42          17      Roger Staubach            NaN      Tom Landry   \n",
       "43           6      Fran Tarkenton            NaN       Bud Grant   \n",
       "44           7      Fran Tarkenton            NaN       Bud Grant   \n",
       "45           7         Bill Kilmer            NaN    George Allen   \n",
       "46           3          Bob Griese            NaN       Don Shula   \n",
       "47          13        Craig Morton            NaN      Tom Landry   \n",
       "48           7            Joe Kapp            NaN       Bud Grant   \n",
       "49           7        Earl Morrall  Johnny Unitas       Don Shula   \n",
       "50          14     Daryle Lamonica            NaN      John Rauch   \n",
       "51          10          Len Dawson            NaN      Hank Stram   \n",
       "\n",
       "    combined_pts  difference_pts  \n",
       "0             74               8  \n",
       "1             62               6  \n",
       "2             34              14  \n",
       "3             52               4  \n",
       "4             51              35  \n",
       "5             65               3  \n",
       "6             38               4  \n",
       "7             56               6  \n",
       "8             48              14  \n",
       "9             50               4  \n",
       "10            31               3  \n",
       "11            46              12  \n",
       "12            31              11  \n",
       "13            45               3  \n",
       "14            61               3  \n",
       "15            69              27  \n",
       "16            37               3  \n",
       "17            41              27  \n",
       "18            39               7  \n",
       "19            53              15  \n",
       "20            55               7  \n",
       "21            56              14  \n",
       "22            44              10  \n",
       "23            75              23  \n",
       "24            43              17  \n",
       "25            69              35  \n",
       "26            61              13  \n",
       "27            39               1  \n",
       "28            65              45  \n",
       "29            36               4  \n",
       "30            52              32  \n",
       "31            59              19  \n",
       "32            56              36  \n",
       "33            54              22  \n",
       "34            47              29  \n",
       "35            44              10  \n",
       "36            47               5  \n",
       "37            37              17  \n",
       "38            50              12  \n",
       "39            66               4  \n",
       "40            37              17  \n",
       "41            46              18  \n",
       "42            38               4  \n",
       "43            22              10  \n",
       "44            31              17  \n",
       "45            21               7  \n",
       "46            27              21  \n",
       "47            29               3  \n",
       "48            30              16  \n",
       "49            23               9  \n",
       "50            47              19  \n",
       "51            45              25  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(super_bowls)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>super_bowl</th>\n",
       "      <th>network</th>\n",
       "      <th>avg_us_viewers</th>\n",
       "      <th>total_us_viewers</th>\n",
       "      <th>rating_household</th>\n",
       "      <th>share_household</th>\n",
       "      <th>rating_18_49</th>\n",
       "      <th>share_18_49</th>\n",
       "      <th>ad_cost</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>52</td>\n",
       "      <td>NBC</td>\n",
       "      <td>103390000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>43.1</td>\n",
       "      <td>68</td>\n",
       "      <td>33.4</td>\n",
       "      <td>78.0</td>\n",
       "      <td>5000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>51</td>\n",
       "      <td>Fox</td>\n",
       "      <td>111319000</td>\n",
       "      <td>172000000.0</td>\n",
       "      <td>45.3</td>\n",
       "      <td>73</td>\n",
       "      <td>37.1</td>\n",
       "      <td>79.0</td>\n",
       "      <td>5000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>50</td>\n",
       "      <td>CBS</td>\n",
       "      <td>111864000</td>\n",
       "      <td>167000000.0</td>\n",
       "      <td>46.6</td>\n",
       "      <td>72</td>\n",
       "      <td>37.7</td>\n",
       "      <td>79.0</td>\n",
       "      <td>5000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>49</td>\n",
       "      <td>NBC</td>\n",
       "      <td>114442000</td>\n",
       "      <td>168000000.0</td>\n",
       "      <td>47.5</td>\n",
       "      <td>71</td>\n",
       "      <td>39.1</td>\n",
       "      <td>79.0</td>\n",
       "      <td>4500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>48</td>\n",
       "      <td>Fox</td>\n",
       "      <td>112191000</td>\n",
       "      <td>167000000.0</td>\n",
       "      <td>46.7</td>\n",
       "      <td>69</td>\n",
       "      <td>39.3</td>\n",
       "      <td>77.0</td>\n",
       "      <td>4000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>47</td>\n",
       "      <td>CBS</td>\n",
       "      <td>108693000</td>\n",
       "      <td>164100000.0</td>\n",
       "      <td>46.3</td>\n",
       "      <td>69</td>\n",
       "      <td>39.7</td>\n",
       "      <td>77.0</td>\n",
       "      <td>4000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>46</td>\n",
       "      <td>NBC</td>\n",
       "      <td>111346000</td>\n",
       "      <td>163500000.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>71</td>\n",
       "      <td>40.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>45</td>\n",
       "      <td>Fox</td>\n",
       "      <td>111041000</td>\n",
       "      <td>162900000.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>69</td>\n",
       "      <td>39.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>44</td>\n",
       "      <td>CBS</td>\n",
       "      <td>106476000</td>\n",
       "      <td>153400000.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>68</td>\n",
       "      <td>38.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>43</td>\n",
       "      <td>NBC</td>\n",
       "      <td>98732000</td>\n",
       "      <td>151600000.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>64</td>\n",
       "      <td>36.7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>42</td>\n",
       "      <td>Fox</td>\n",
       "      <td>97448000</td>\n",
       "      <td>148300000.0</td>\n",
       "      <td>43.1</td>\n",
       "      <td>65</td>\n",
       "      <td>37.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2699963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>41</td>\n",
       "      <td>CBS</td>\n",
       "      <td>93184000</td>\n",
       "      <td>139800000.0</td>\n",
       "      <td>42.6</td>\n",
       "      <td>64</td>\n",
       "      <td>35.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2385365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>40</td>\n",
       "      <td>ABC</td>\n",
       "      <td>90745000</td>\n",
       "      <td>141400000.0</td>\n",
       "      <td>41.6</td>\n",
       "      <td>62</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>39</td>\n",
       "      <td>Fox</td>\n",
       "      <td>86072000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>41.1</td>\n",
       "      <td>62</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>38</td>\n",
       "      <td>CBS</td>\n",
       "      <td>89795000</td>\n",
       "      <td>144400000.0</td>\n",
       "      <td>41.4</td>\n",
       "      <td>63</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2302200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>37</td>\n",
       "      <td>ABC</td>\n",
       "      <td>88637000</td>\n",
       "      <td>138500000.0</td>\n",
       "      <td>40.7</td>\n",
       "      <td>61</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>36</td>\n",
       "      <td>Fox</td>\n",
       "      <td>86801000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.4</td>\n",
       "      <td>61</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>35</td>\n",
       "      <td>CBS</td>\n",
       "      <td>84335000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.4</td>\n",
       "      <td>61</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>34</td>\n",
       "      <td>ABC</td>\n",
       "      <td>88465000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>43.3</td>\n",
       "      <td>63</td>\n",
       "      <td>37.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>33</td>\n",
       "      <td>Fox</td>\n",
       "      <td>83720000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.2</td>\n",
       "      <td>61</td>\n",
       "      <td>36.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>32</td>\n",
       "      <td>NBC</td>\n",
       "      <td>90000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>44.5</td>\n",
       "      <td>67</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1291100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>31</td>\n",
       "      <td>Fox</td>\n",
       "      <td>87870000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>43.3</td>\n",
       "      <td>65</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>30</td>\n",
       "      <td>NBC</td>\n",
       "      <td>94080000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>46.0</td>\n",
       "      <td>68</td>\n",
       "      <td>41.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1085000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>29</td>\n",
       "      <td>ABC</td>\n",
       "      <td>83420000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>41.3</td>\n",
       "      <td>62</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1150000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>28</td>\n",
       "      <td>NBC</td>\n",
       "      <td>90000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45.5</td>\n",
       "      <td>66</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>900000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>27</td>\n",
       "      <td>NBC</td>\n",
       "      <td>90990000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45.1</td>\n",
       "      <td>66</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>850000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>26</td>\n",
       "      <td>CBS</td>\n",
       "      <td>79590000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.3</td>\n",
       "      <td>61</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>850000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>25</td>\n",
       "      <td>ABC</td>\n",
       "      <td>79510000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>41.9</td>\n",
       "      <td>63</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>24</td>\n",
       "      <td>CBS</td>\n",
       "      <td>73852000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39.0</td>\n",
       "      <td>67</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>700400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>23</td>\n",
       "      <td>NBC</td>\n",
       "      <td>81590000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>43.5</td>\n",
       "      <td>68</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>675000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>22</td>\n",
       "      <td>ABC</td>\n",
       "      <td>80140000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>41.9</td>\n",
       "      <td>62</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>645000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>21</td>\n",
       "      <td>CBS</td>\n",
       "      <td>87190000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45.8</td>\n",
       "      <td>66</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>20</td>\n",
       "      <td>NBC</td>\n",
       "      <td>92570000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>48.3</td>\n",
       "      <td>70</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>550000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>19</td>\n",
       "      <td>ABC</td>\n",
       "      <td>85530000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>46.4</td>\n",
       "      <td>63</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>525000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>18</td>\n",
       "      <td>CBS</td>\n",
       "      <td>77620000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>46.4</td>\n",
       "      <td>71</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>368200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>17</td>\n",
       "      <td>NBC</td>\n",
       "      <td>81770000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>48.6</td>\n",
       "      <td>69</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>16</td>\n",
       "      <td>CBS</td>\n",
       "      <td>85240000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>49.1</td>\n",
       "      <td>73</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>324300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>15</td>\n",
       "      <td>NBC</td>\n",
       "      <td>68290000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>44.4</td>\n",
       "      <td>63</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>275000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>14</td>\n",
       "      <td>CBS</td>\n",
       "      <td>76240000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>46.3</td>\n",
       "      <td>67</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>222000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>13</td>\n",
       "      <td>NBC</td>\n",
       "      <td>74740000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>47.1</td>\n",
       "      <td>74</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>185000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>12</td>\n",
       "      <td>CBS</td>\n",
       "      <td>78940000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>47.2</td>\n",
       "      <td>67</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>162300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>11</td>\n",
       "      <td>NBC</td>\n",
       "      <td>62050000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>44.4</td>\n",
       "      <td>73</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>125000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>10</td>\n",
       "      <td>CBS</td>\n",
       "      <td>57710000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>42.3</td>\n",
       "      <td>78</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>110000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>9</td>\n",
       "      <td>NBC</td>\n",
       "      <td>56050000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>42.4</td>\n",
       "      <td>72</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>107000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>8</td>\n",
       "      <td>CBS</td>\n",
       "      <td>51700000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>41.6</td>\n",
       "      <td>73</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>103500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>7</td>\n",
       "      <td>NBC</td>\n",
       "      <td>53320000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>42.7</td>\n",
       "      <td>72</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>88100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>6</td>\n",
       "      <td>CBS</td>\n",
       "      <td>56640000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>44.2</td>\n",
       "      <td>74</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>86100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>5</td>\n",
       "      <td>NBC</td>\n",
       "      <td>46040000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39.9</td>\n",
       "      <td>75</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>72500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>4</td>\n",
       "      <td>CBS</td>\n",
       "      <td>44270000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39.4</td>\n",
       "      <td>69</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>78200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>3</td>\n",
       "      <td>NBC</td>\n",
       "      <td>41660000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.0</td>\n",
       "      <td>70</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>55000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>2</td>\n",
       "      <td>CBS</td>\n",
       "      <td>39120000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.8</td>\n",
       "      <td>68</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>54500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>1</td>\n",
       "      <td>CBS</td>\n",
       "      <td>26750000</td>\n",
       "      <td>51180000.0</td>\n",
       "      <td>22.6</td>\n",
       "      <td>43</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>42500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>1</td>\n",
       "      <td>NBC</td>\n",
       "      <td>24430000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.5</td>\n",
       "      <td>36</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    super_bowl network  avg_us_viewers  total_us_viewers  rating_household  \\\n",
       "0           52     NBC       103390000               NaN              43.1   \n",
       "1           51     Fox       111319000       172000000.0              45.3   \n",
       "2           50     CBS       111864000       167000000.0              46.6   \n",
       "3           49     NBC       114442000       168000000.0              47.5   \n",
       "4           48     Fox       112191000       167000000.0              46.7   \n",
       "5           47     CBS       108693000       164100000.0              46.3   \n",
       "6           46     NBC       111346000       163500000.0              47.0   \n",
       "7           45     Fox       111041000       162900000.0              46.0   \n",
       "8           44     CBS       106476000       153400000.0              45.0   \n",
       "9           43     NBC        98732000       151600000.0              42.0   \n",
       "10          42     Fox        97448000       148300000.0              43.1   \n",
       "11          41     CBS        93184000       139800000.0              42.6   \n",
       "12          40     ABC        90745000       141400000.0              41.6   \n",
       "13          39     Fox        86072000               NaN              41.1   \n",
       "14          38     CBS        89795000       144400000.0              41.4   \n",
       "15          37     ABC        88637000       138500000.0              40.7   \n",
       "16          36     Fox        86801000               NaN              40.4   \n",
       "17          35     CBS        84335000               NaN              40.4   \n",
       "18          34     ABC        88465000               NaN              43.3   \n",
       "19          33     Fox        83720000               NaN              40.2   \n",
       "20          32     NBC        90000000               NaN              44.5   \n",
       "21          31     Fox        87870000               NaN              43.3   \n",
       "22          30     NBC        94080000               NaN              46.0   \n",
       "23          29     ABC        83420000               NaN              41.3   \n",
       "24          28     NBC        90000000               NaN              45.5   \n",
       "25          27     NBC        90990000               NaN              45.1   \n",
       "26          26     CBS        79590000               NaN              40.3   \n",
       "27          25     ABC        79510000               NaN              41.9   \n",
       "28          24     CBS        73852000               NaN              39.0   \n",
       "29          23     NBC        81590000               NaN              43.5   \n",
       "30          22     ABC        80140000               NaN              41.9   \n",
       "31          21     CBS        87190000               NaN              45.8   \n",
       "32          20     NBC        92570000               NaN              48.3   \n",
       "33          19     ABC        85530000               NaN              46.4   \n",
       "34          18     CBS        77620000               NaN              46.4   \n",
       "35          17     NBC        81770000               NaN              48.6   \n",
       "36          16     CBS        85240000               NaN              49.1   \n",
       "37          15     NBC        68290000               NaN              44.4   \n",
       "38          14     CBS        76240000               NaN              46.3   \n",
       "39          13     NBC        74740000               NaN              47.1   \n",
       "40          12     CBS        78940000               NaN              47.2   \n",
       "41          11     NBC        62050000               NaN              44.4   \n",
       "42          10     CBS        57710000               NaN              42.3   \n",
       "43           9     NBC        56050000               NaN              42.4   \n",
       "44           8     CBS        51700000               NaN              41.6   \n",
       "45           7     NBC        53320000               NaN              42.7   \n",
       "46           6     CBS        56640000               NaN              44.2   \n",
       "47           5     NBC        46040000               NaN              39.9   \n",
       "48           4     CBS        44270000               NaN              39.4   \n",
       "49           3     NBC        41660000               NaN              36.0   \n",
       "50           2     CBS        39120000               NaN              36.8   \n",
       "51           1     CBS        26750000        51180000.0              22.6   \n",
       "52           1     NBC        24430000               NaN              18.5   \n",
       "\n",
       "    share_household  rating_18_49  share_18_49  ad_cost  \n",
       "0                68          33.4         78.0  5000000  \n",
       "1                73          37.1         79.0  5000000  \n",
       "2                72          37.7         79.0  5000000  \n",
       "3                71          39.1         79.0  4500000  \n",
       "4                69          39.3         77.0  4000000  \n",
       "5                69          39.7         77.0  4000000  \n",
       "6                71          40.5          NaN  3500000  \n",
       "7                69          39.9          NaN  3100000  \n",
       "8                68          38.6          NaN  2800000  \n",
       "9                64          36.7          NaN  3000000  \n",
       "10               65          37.5          NaN  2699963  \n",
       "11               64          35.2          NaN  2385365  \n",
       "12               62           NaN          NaN  2500000  \n",
       "13               62           NaN          NaN  2400000  \n",
       "14               63           NaN          NaN  2302200  \n",
       "15               61           NaN          NaN  2200000  \n",
       "16               61           NaN          NaN  2200000  \n",
       "17               61           NaN          NaN  2200000  \n",
       "18               63          37.9          NaN  2100000  \n",
       "19               61          36.4          NaN  1600000  \n",
       "20               67           NaN          NaN  1291100  \n",
       "21               65           NaN          NaN  1200000  \n",
       "22               68          41.2          NaN  1085000  \n",
       "23               62           NaN          NaN  1150000  \n",
       "24               66           NaN          NaN   900000  \n",
       "25               66           NaN          NaN   850000  \n",
       "26               61           NaN          NaN   850000  \n",
       "27               63           NaN          NaN   800000  \n",
       "28               67           NaN          NaN   700400  \n",
       "29               68           NaN          NaN   675000  \n",
       "30               62           NaN          NaN   645000  \n",
       "31               66           NaN          NaN   600000  \n",
       "32               70           NaN          NaN   550000  \n",
       "33               63           NaN          NaN   525000  \n",
       "34               71           NaN          NaN   368200  \n",
       "35               69           NaN          NaN   400000  \n",
       "36               73           NaN          NaN   324300  \n",
       "37               63           NaN          NaN   275000  \n",
       "38               67           NaN          NaN   222000  \n",
       "39               74           NaN          NaN   185000  \n",
       "40               67           NaN          NaN   162300  \n",
       "41               73           NaN          NaN   125000  \n",
       "42               78           NaN          NaN   110000  \n",
       "43               72           NaN          NaN   107000  \n",
       "44               73           NaN          NaN   103500  \n",
       "45               72           NaN          NaN    88100  \n",
       "46               74           NaN          NaN    86100  \n",
       "47               75           NaN          NaN    72500  \n",
       "48               69           NaN          NaN    78200  \n",
       "49               70           NaN          NaN    55000  \n",
       "50               68           NaN          NaN    54500  \n",
       "51               43           NaN          NaN    42500  \n",
       "52               36           NaN          NaN    37500  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(tv)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 6. Viewership and the ad industry over time\n",
    "\n",
    "### Create three line plots using the tv DataFrame to compare viewers, rating, and ad cost.\n",
    "\n",
    "The downward sloping regression line and the 95% confidence interval for that regression suggest that bailing on the game if it is a blowout is common. Though it matches our intuition, we must take it with a grain of salt because the linear relationship in the data is weak due to our small sample size of 52 games.\n",
    "\n",
    "Regardless of the score though, I bet most people stick it out for the halftime show, which is good news for the TV networks and advertisers. A 30-second spot costs a pretty $5 million now, but has it always been that way? And how have number of viewers and household ratings trended alongside ad cost? We can find out using line plots that share a \"Super Bowl\" x-axis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x396 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a figure with 3x1 subplot and activate the top subplot\n",
    "plt.subplot(3, 1, 1)\n",
    "plt.plot(tv.super_bowl, tv.avg_us_viewers, color='#648FFF')\n",
    "plt.title('Average Number of US Viewers')\n",
    "\n",
    "# Activate the middle subplot\n",
    "plt.subplot(3, 1, 2)\n",
    "plt.plot(tv.super_bowl,tv.rating_household, color ='#DC267F')\n",
    "plt.title('Household Rating')\n",
    "\n",
    "# Activate the bottom subplot\n",
    "plt.subplot(3, 1, 3)\n",
    "plt.plot(tv.super_bowl, tv.ad_cost, color = '#FFB000')\n",
    "plt.title('Ad Cost')\n",
    "plt.xlabel('SUPER BOWL')\n",
    "\n",
    "# Improve the spacing between subplots\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Task 7. Halftime shows weren't always this great\n",
    "\n",
    "## Filter and display the musicians for halftime shows up to and including Super Bowl XXVII.\n",
    "Using halftime_musicians, select the musicians that performed in halftime shows up to and including Super Bowl XXVII (27) (i.e. Michael Jackson's performance).\n",
    "\n",
    "\n",
    "We can see viewers increased before ad costs did. Maybe the **networks weren't very data savvy and were slow to react?** Makes sense since DataCamp didn't exist back then.\n",
    "\n",
    "Another hypothesis: maybe halftime shows weren't that good in the earlier years? The modern spectacle of the Super Bowl has a lot to do with the cultural prestige of big halftime acts. I went down a YouTube rabbit hole and it turns out the old ones weren't up to today's standards. Some offenders:\n",
    "\n",
    "Super Bowl XXVI in 1992: A Frosty The Snowman rap performed by children.\n",
    "Super Bowl XXIII in 1989: An Elvis impersonator that did magic tricks and didn't even sing one Elvis song.\n",
    "Super Bowl XXI in 1987: Tap dancing ponies. (Okay, that's pretty awesome actually.)\n",
    "It turns out Michael Jackson's Super Bowl XXVII performance, one of the most watched events in American TV history, was when the NFL realized the value of Super Bowl airtime and decided they needed to sign big name acts from then on out. The halftime shows before MJ indeed weren't that impressive, which we can see by filtering our halftime_musician data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>super_bowl</th>\n",
       "      <th>musician</th>\n",
       "      <th>num_songs</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>27</td>\n",
       "      <td>Michael Jackson</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>26</td>\n",
       "      <td>Gloria Estefan</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>26</td>\n",
       "      <td>University of Minnesota Marching Band</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>25</td>\n",
       "      <td>New Kids on the Block</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>24</td>\n",
       "      <td>Pete Fountain</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>24</td>\n",
       "      <td>Doug Kershaw</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>24</td>\n",
       "      <td>Irma Thomas</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>24</td>\n",
       "      <td>Pride of Nicholls Marching Band</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>24</td>\n",
       "      <td>The Human Jukebox</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>24</td>\n",
       "      <td>Pride of Acadiana</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>23</td>\n",
       "      <td>Elvis Presto</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>22</td>\n",
       "      <td>Chubby Checker</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>22</td>\n",
       "      <td>San Diego State University Marching Aztecs</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>22</td>\n",
       "      <td>Spirit of Troy</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>21</td>\n",
       "      <td>Grambling State University Tiger Marching Band</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>21</td>\n",
       "      <td>Spirit of Troy</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>20</td>\n",
       "      <td>Up with People</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>19</td>\n",
       "      <td>Tops In Blue</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>18</td>\n",
       "      <td>The University of Florida Fightin' Gator March...</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>18</td>\n",
       "      <td>The Florida State University Marching Chiefs</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>17</td>\n",
       "      <td>Los Angeles Unified School District All City H...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>16</td>\n",
       "      <td>Up with People</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>15</td>\n",
       "      <td>The Human Jukebox</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>15</td>\n",
       "      <td>Helen O'Connell</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>14</td>\n",
       "      <td>Up with People</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>14</td>\n",
       "      <td>Grambling State University Tiger Marching Band</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>13</td>\n",
       "      <td>Ken Hamilton</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>13</td>\n",
       "      <td>Gramacks</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>12</td>\n",
       "      <td>Tyler Junior College Apache Band</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>12</td>\n",
       "      <td>Pete Fountain</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>12</td>\n",
       "      <td>Al Hirt</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>11</td>\n",
       "      <td>Los Angeles Unified School District All City H...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>10</td>\n",
       "      <td>Up with People</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>9</td>\n",
       "      <td>Mercer Ellington</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>9</td>\n",
       "      <td>Grambling State University Tiger Marching Band</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>8</td>\n",
       "      <td>University of Texas Longhorn Band</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>8</td>\n",
       "      <td>Judy Mallett</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>7</td>\n",
       "      <td>University of Michigan Marching Band</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>7</td>\n",
       "      <td>Woody Herman</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>7</td>\n",
       "      <td>Andy Williams</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>6</td>\n",
       "      <td>Ella Fitzgerald</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>6</td>\n",
       "      <td>Carol Channing</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>6</td>\n",
       "      <td>Al Hirt</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>6</td>\n",
       "      <td>United States Air Force Academy Cadet Chorale</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>5</td>\n",
       "      <td>Southeast Missouri State Marching Band</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>4</td>\n",
       "      <td>Marguerite Piazza</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>4</td>\n",
       "      <td>Doc Severinsen</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>4</td>\n",
       "      <td>Al Hirt</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>4</td>\n",
       "      <td>The Human Jukebox</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>3</td>\n",
       "      <td>Florida A&amp;M University Marching 100 Band</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>2</td>\n",
       "      <td>Grambling State University Tiger Marching Band</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>1</td>\n",
       "      <td>University of Arizona Symphonic Marching Band</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>1</td>\n",
       "      <td>Grambling State University Tiger Marching Band</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>1</td>\n",
       "      <td>Al Hirt</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     super_bowl                                           musician  num_songs\n",
       "80           27                                    Michael Jackson        5.0\n",
       "81           26                                     Gloria Estefan        2.0\n",
       "82           26              University of Minnesota Marching Band        NaN\n",
       "83           25                              New Kids on the Block        2.0\n",
       "84           24                                      Pete Fountain        1.0\n",
       "85           24                                       Doug Kershaw        1.0\n",
       "86           24                                        Irma Thomas        1.0\n",
       "87           24                    Pride of Nicholls Marching Band        NaN\n",
       "88           24                                  The Human Jukebox        NaN\n",
       "89           24                                  Pride of Acadiana        NaN\n",
       "90           23                                       Elvis Presto        7.0\n",
       "91           22                                     Chubby Checker        2.0\n",
       "92           22         San Diego State University Marching Aztecs        NaN\n",
       "93           22                                     Spirit of Troy        NaN\n",
       "94           21     Grambling State University Tiger Marching Band        8.0\n",
       "95           21                                     Spirit of Troy        8.0\n",
       "96           20                                     Up with People        NaN\n",
       "97           19                                       Tops In Blue        NaN\n",
       "98           18  The University of Florida Fightin' Gator March...        7.0\n",
       "99           18       The Florida State University Marching Chiefs        7.0\n",
       "100          17  Los Angeles Unified School District All City H...        NaN\n",
       "101          16                                     Up with People        NaN\n",
       "102          15                                  The Human Jukebox        NaN\n",
       "103          15                                    Helen O'Connell        NaN\n",
       "104          14                                     Up with People        NaN\n",
       "105          14     Grambling State University Tiger Marching Band        NaN\n",
       "106          13                                       Ken Hamilton        NaN\n",
       "107          13                                           Gramacks        NaN\n",
       "108          12                   Tyler Junior College Apache Band        NaN\n",
       "109          12                                      Pete Fountain        NaN\n",
       "110          12                                            Al Hirt        NaN\n",
       "111          11  Los Angeles Unified School District All City H...        NaN\n",
       "112          10                                     Up with People        NaN\n",
       "113           9                                   Mercer Ellington        NaN\n",
       "114           9     Grambling State University Tiger Marching Band        NaN\n",
       "115           8                  University of Texas Longhorn Band        NaN\n",
       "116           8                                       Judy Mallett        NaN\n",
       "117           7               University of Michigan Marching Band        NaN\n",
       "118           7                                       Woody Herman        NaN\n",
       "119           7                                      Andy Williams        NaN\n",
       "120           6                                    Ella Fitzgerald        NaN\n",
       "121           6                                     Carol Channing        NaN\n",
       "122           6                                            Al Hirt        NaN\n",
       "123           6      United States Air Force Academy Cadet Chorale        NaN\n",
       "124           5             Southeast Missouri State Marching Band        NaN\n",
       "125           4                                  Marguerite Piazza        NaN\n",
       "126           4                                     Doc Severinsen        NaN\n",
       "127           4                                            Al Hirt        NaN\n",
       "128           4                                  The Human Jukebox        NaN\n",
       "129           3           Florida A&M University Marching 100 Band        NaN\n",
       "130           2     Grambling State University Tiger Marching Band        NaN\n",
       "131           1      University of Arizona Symphonic Marching Band        NaN\n",
       "132           1     Grambling State University Tiger Marching Band        NaN\n",
       "133           1                                            Al Hirt        NaN"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Display all halftime musicians for Super Bowls up to and including Super Bowl XXVII\n",
    "halftime_musicians[halftime_musicians.super_bowl <= 27]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 8. Who has the most halftime show appearances?\n",
    "## Select and display the musicians with more than one halftime show appearance.\n",
    "\n",
    "Lots of marching bands. American jazz clarinetist Pete Fountain. Miss Texas 1973 playing a violin. Nothing against those performers, they're just simply not Beyoncé. To be fair, no one is.\n",
    "\n",
    "Let's see all of the musicians that have done more than one halftime show, including their performance counts.\n",
    "\n",
    "\n",
    "**I still have problem with this task!!!**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>musician</th>\n",
       "      <th>super_bowl</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Grambling State University Tiger Marching Band</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>Up with People</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Al Hirt</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>The Human Jukebox</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>Spirit of Troy</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Florida A&amp;M University Marching 100 Band</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Gloria Estefan</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>University of Minnesota Marching Band</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Bruno Mars</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>Pete Fountain</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Beyoncé</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Justin Timberlake</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>Nelly</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>Los Angeles Unified School District All City H...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              musician  super_bowl\n",
       "28      Grambling State University Tiger Marching Band           6\n",
       "104                                     Up with People           4\n",
       "1                                              Al Hirt           4\n",
       "83                                   The Human Jukebox           3\n",
       "76                                      Spirit of Troy           2\n",
       "25            Florida A&M University Marching 100 Band           2\n",
       "26                                      Gloria Estefan           2\n",
       "102              University of Minnesota Marching Band           2\n",
       "10                                          Bruno Mars           2\n",
       "64                                       Pete Fountain           2\n",
       "5                                              Beyoncé           2\n",
       "36                                   Justin Timberlake           2\n",
       "57                                               Nelly           2\n",
       "44   Los Angeles Unified School District All City H...           2"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Count halftime show appearances for each musician and sort them from most to least\n",
    "halftime_appearances = halftime_musicians.groupby('musician').count()['super_bowl'].reset_index()\n",
    "halftime_appearances = halftime_appearances.sort_values('super_bowl', ascending=False)\n",
    "\n",
    "# Display musicians with more than one halftime show appearance\n",
    "halftime_appearances[halftime_appearances['super_bowl']>1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>super_bowl</th>\n",
       "      <th>musician</th>\n",
       "      <th>num_songs</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>52</td>\n",
       "      <td>Justin Timberlake</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>52</td>\n",
       "      <td>University of Minnesota Marching Band</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>51</td>\n",
       "      <td>Lady Gaga</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>50</td>\n",
       "      <td>Coldplay</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>50</td>\n",
       "      <td>Beyoncé</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>3</td>\n",
       "      <td>Florida A&amp;M University Marching 100 Band</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>2</td>\n",
       "      <td>Grambling State University Tiger Marching Band</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>1</td>\n",
       "      <td>University of Arizona Symphonic Marching Band</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>1</td>\n",
       "      <td>Grambling State University Tiger Marching Band</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>1</td>\n",
       "      <td>Al Hirt</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>134 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     super_bowl                                        musician  num_songs\n",
       "0            52                               Justin Timberlake       11.0\n",
       "1            52           University of Minnesota Marching Band        1.0\n",
       "2            51                                       Lady Gaga        7.0\n",
       "3            50                                        Coldplay        6.0\n",
       "4            50                                         Beyoncé        3.0\n",
       "..          ...                                             ...        ...\n",
       "129           3        Florida A&M University Marching 100 Band        NaN\n",
       "130           2  Grambling State University Tiger Marching Band        NaN\n",
       "131           1   University of Arizona Symphonic Marching Band        NaN\n",
       "132           1  Grambling State University Tiger Marching Band        NaN\n",
       "133           1                                         Al Hirt        NaN\n",
       "\n",
       "[134 rows x 3 columns]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "halftime_musicians"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Task 9. Who performed the most songs in a halftime show?\n",
    "\n",
    "Modify the histogram of number of songs performed for non-band musicians.\n",
    "\n",
    "The world famous Grambling State University Tiger Marching Band takes the crown with six appearances. Beyoncé, Justin Timberlake, Nelly, and Bruno Mars are the only post-Y2K musicians with multiple appearances (two each).\n",
    "\n",
    "From our previous inspections, the num_songs column has lots of missing values:\n",
    "\n",
    "A lot of the marching bands don't have num_songs entries.\n",
    "For non-marching bands, missing data starts occurring at Super Bowl XX.\n",
    "Let's filter out marching bands by filtering out musicians with the word \"Marching\" in them and the word \"Spirit\" (a common naming convention for marching bands is \"Spirit of [something]\"). Then we'll filter for Super Bowls after Super Bowl XX to address the missing data issue, then let's see who has the most number of songs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>super_bowl</th>\n",
       "      <th>musician</th>\n",
       "      <th>num_songs</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>52</td>\n",
       "      <td>Justin Timberlake</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>30</td>\n",
       "      <td>Diana Ross</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>49</td>\n",
       "      <td>Katy Perry</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>51</td>\n",
       "      <td>Lady Gaga</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>23</td>\n",
       "      <td>Elvis Presto</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>41</td>\n",
       "      <td>Prince</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>47</td>\n",
       "      <td>Beyoncé</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>48</td>\n",
       "      <td>Bruno Mars</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>50</td>\n",
       "      <td>Coldplay</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>45</td>\n",
       "      <td>The Black Eyed Peas</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>46</td>\n",
       "      <td>Madonna</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>44</td>\n",
       "      <td>The Who</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>27</td>\n",
       "      <td>Michael Jackson</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>32</td>\n",
       "      <td>The Temptations</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>39</td>\n",
       "      <td>Paul McCartney</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    super_bowl             musician  num_songs\n",
       "0           52    Justin Timberlake       11.0\n",
       "70          30           Diana Ross       10.0\n",
       "10          49           Katy Perry        8.0\n",
       "2           51            Lady Gaga        7.0\n",
       "90          23         Elvis Presto        7.0\n",
       "33          41               Prince        7.0\n",
       "16          47              Beyoncé        7.0\n",
       "14          48           Bruno Mars        6.0\n",
       "3           50             Coldplay        6.0\n",
       "25          45  The Black Eyed Peas        6.0\n",
       "20          46              Madonna        5.0\n",
       "30          44              The Who        5.0\n",
       "80          27      Michael Jackson        5.0\n",
       "64          32      The Temptations        4.0\n",
       "36          39       Paul McCartney        4.0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Filter out most marching bands\n",
    "no_bands = halftime_musicians[~halftime_musicians.musician.str.contains('Marching')]\n",
    "no_bands = no_bands[~no_bands.musician.str.contains('Spirit')]\n",
    "\n",
    "# Plot a histogram of number of songs per performance\n",
    "most_songs = int(max(no_bands['num_songs'].values))\n",
    "plt.hist(no_bands.num_songs.dropna(), bins=most_songs)\n",
    "# ... YOUR CODE FOR TASK 9 ...\n",
    "plt.xlabel('Numner of Songs Per Halftime Show Performance')\n",
    "plt.ylabel('Number of Musicians')\n",
    "plt.show()\n",
    "\n",
    "# Sort the non-band musicians by number of songs per appearance...\n",
    "no_bands = no_bands.sort_values('num_songs', ascending=False)\n",
    "# ...and display the top 15\n",
    "display(no_bands.head(15))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Task 10. Conclusion\n",
    "So most non-band musicians do 1-3 songs per halftime show. It's important to note that the duration of the halftime show is fixed (roughly 12 minutes) so songs per performance is more a measure of how many hit songs you have. JT went off in 2018, wow. 11 songs! Diana Ross comes in second with 10 in her medley in 1996.\n",
    "\n",
    "In this notebook, we loaded, cleaned, then explored Super Bowl game, television, and halftime show data. We visualized the distributions of combined points, point differences, and halftime show performances using histograms. We used line plots to see how ad cost increases lagged behind viewership increases. And we discovered that blowouts do appear to lead to a drop in viewers.\n",
    "\n",
    "This year's Big Game will be here before you know it. Who do you think will win Super Bowl LIII?\n",
    "\n",
    "UPDATE: Spoiler alert."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The winner of Super Bowl LIII will be the Los Angeles Rams\n"
     ]
    }
   ],
   "source": [
    "# 2018-2019 conference champions\n",
    "patriots = 'New England Patriots'\n",
    "rams = 'Los Angeles Rams'\n",
    "\n",
    "# Who will win Super Bowl LIII?\n",
    "super_bowl_LIII_winner = rams\n",
    "print('The winner of Super Bowl LIII will be the', super_bowl_LIII_winner)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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