IS445_Olson_Miller_Individual.ipynb

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   "source": [
    "**<h2>NFL Statistics: Individual</h2>**"
   ]
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>name</th>\n",
       "      <th>position</th>\n",
       "      <th>team</th>\n",
       "      <th>season</th>\n",
       "      <th>season_type</th>\n",
       "      <th>completions</th>\n",
       "      <th>attempts</th>\n",
       "      <th>passing_yards</th>\n",
       "      <th>passing_tds</th>\n",
       "      <th>...</th>\n",
       "      <th>ypg</th>\n",
       "      <th>pr</th>\n",
       "      <th>rookie_season</th>\n",
       "      <th>round</th>\n",
       "      <th>overall</th>\n",
       "      <th>ht</th>\n",
       "      <th>wt</th>\n",
       "      <th>forty</th>\n",
       "      <th>vertical</th>\n",
       "      <th>years_played</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>A.J. Brown</td>\n",
       "      <td>WR</td>\n",
       "      <td>PHI</td>\n",
       "      <td>2022</td>\n",
       "      <td>REG</td>\n",
       "      <td>0</td>\n",
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       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>A.J. Brown</td>\n",
       "      <td>WR</td>\n",
       "      <td>TEN</td>\n",
       "      <td>2019</td>\n",
       "      <td>REG</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>33.87</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>Jun-00</td>\n",
       "      <td>226.0</td>\n",
       "      <td>4.49</td>\n",
       "      <td>36.5</td>\n",
       "      <td>1.0</td>\n",
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       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>A.J. Brown</td>\n",
       "      <td>WR</td>\n",
       "      <td>TEN</td>\n",
       "      <td>2020</td>\n",
       "      <td>REG</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>33.87</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>Jun-00</td>\n",
       "      <td>226.0</td>\n",
       "      <td>4.49</td>\n",
       "      <td>36.5</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>A.J. Brown</td>\n",
       "      <td>WR</td>\n",
       "      <td>TEN</td>\n",
       "      <td>2021</td>\n",
       "      <td>REG</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>33.87</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>Jun-00</td>\n",
       "      <td>226.0</td>\n",
       "      <td>4.49</td>\n",
       "      <td>36.5</td>\n",
       "      <td>3.0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>A.J. Derby</td>\n",
       "      <td>TE</td>\n",
       "      <td>DEN</td>\n",
       "      <td>2016</td>\n",
       "      <td>REG</td>\n",
       "      <td>0</td>\n",
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       "      <th>6176</th>\n",
       "      <td>1767</td>\n",
       "      <td>Zay Jones</td>\n",
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       "      <td>2020</td>\n",
       "      <td>REG</td>\n",
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       "      <td>Zonovan Knight</td>\n",
       "      <td>RB</td>\n",
       "      <td>NYJ</td>\n",
       "      <td>2022</td>\n",
       "      <td>REG</td>\n",
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      "text/plain": [
       "        id            name position team  season season_type  completions  \\\n",
       "0        1      A.J. Brown       WR  PHI    2022         REG            0   \n",
       "1        1      A.J. Brown       WR  TEN    2019         REG            0   \n",
       "2        1      A.J. Brown       WR  TEN    2020         REG            0   \n",
       "3        1      A.J. Brown       WR  TEN    2021         REG            0   \n",
       "4        2      A.J. Derby       TE  DEN    2016         REG            0   \n",
       "...    ...             ...      ...  ...     ...         ...          ...   \n",
       "6176  1767       Zay Jones       WR   LV    2020         REG            1   \n",
       "6177  1767       Zay Jones       WR   LV    2021         REG            0   \n",
       "6178  1768  Zonovan Knight       RB  NYJ    2022         REG            0   \n",
       "6179  1769   Zurlon Tipton       RB  IND    2014         REG            0   \n",
       "6180  1769   Zurlon Tipton       RB  IND    2015         REG            0   \n",
       "\n",
       "      attempts  passing_yards  passing_tds  ...       ypg      pr  \\\n",
       "0            0              0            0  ...  0.000000   33.87   \n",
       "1            0              0            0  ...  0.000000   33.87   \n",
       "2            0              0            0  ...  0.000000   33.87   \n",
       "3            2              0            0  ...  0.000000   33.87   \n",
       "4            0              0            0  ...  0.000000   33.87   \n",
       "...        ...            ...          ...  ...       ...     ...   \n",
       "6176         1             29            0  ...  2.636364  113.04   \n",
       "6177         0              0            0  ...  0.000000   33.87   \n",
       "6178         0              0            0  ...  0.000000   33.87   \n",
       "6179         0              0            0  ...  0.000000   33.87   \n",
       "6180         0              0            0  ...  0.000000   33.87   \n",
       "\n",
       "      rookie_season  round  overall      ht     wt  forty  vertical  \\\n",
       "0               NaN    NaN      NaN     NaN    NaN    NaN       NaN   \n",
       "1            2019.0    2.0     51.0  Jun-00  226.0   4.49      36.5   \n",
       "2            2019.0    2.0     51.0  Jun-00  226.0   4.49      36.5   \n",
       "3            2019.0    2.0     51.0  Jun-00  226.0   4.49      36.5   \n",
       "4               NaN    NaN      NaN     NaN    NaN    NaN       NaN   \n",
       "...             ...    ...      ...     ...    ...    ...       ...   \n",
       "6176            NaN    NaN      NaN     NaN    NaN    NaN       NaN   \n",
       "6177            NaN    NaN      NaN     NaN    NaN    NaN       NaN   \n",
       "6178            NaN    NaN      NaN     NaN    NaN    NaN       NaN   \n",
       "6179            NaN    NaN      NaN     NaN    NaN    NaN       NaN   \n",
       "6180            NaN    NaN      NaN     NaN    NaN    NaN       NaN   \n",
       "\n",
       "      years_played  \n",
       "0              NaN  \n",
       "1              1.0  \n",
       "2              2.0  \n",
       "3              3.0  \n",
       "4              NaN  \n",
       "...            ...  \n",
       "6176           NaN  \n",
       "6177           NaN  \n",
       "6178           NaN  \n",
       "6179           NaN  \n",
       "6180           NaN  \n",
       "\n",
       "[6181 rows x 71 columns]"
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   "source": [
    "import pandas as pd \n",
    "import matplotlib.pyplot as plt\n",
    "data = pd.read_csv(\"/Users/millerolson/Desktop/yearly_data_updated_08_23.csv\")\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4682989f-ab99-440d-bfd2-30996e765110",
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   "source": [
    "Name of dataset: NFL Stats 2012-2022\n",
    "\n",
    "Source of data: https://www.kaggle.com/datasets/philiphyde1/nfl-stats-1999-2022\n",
    "\n",
    "I obtained this dataset from Kaggle and the liscense infiramtion can be ound at this link: https://creativecommons.org/publicdomain/zero/1.0/"
   ]
  },
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   "cell_type": "markdown",
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   "source": [
    "Data Overview: This data is an overall representation of yearly NFL statistics on many offesive players from 2012-2022. The initial purpose of this data was to accurately understand player statistics in order to in turn make accurate predictions for things like Fantasy football, sports betting, and future NFL drafts. There are many different rows that represent different things. Name, position, team and season, all of which are fairly self-explanatory are rows that are describing the player in order to differentiate between them, espeically since there are player stattistics listed for the same player over multiple seasons. Other rows showcase stattostics like passing yards, passing first downs, passing 2 point conversions, rushing yards, rushing fumbles, and a lot of other data that are representative of areas players are measured on in order to evaluate their preformance in that season and then predict their preformance for future seasons. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc3302e7-59eb-46a1-acb3-9c424d357299",
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   "source": [
    "I chose this dataset because sports, especially the NFL really interest me. Furthermore, I have played Fantasy football for multiple years, so understanding the data and being able to visualize it through creating graphs is really benefivcial in being able to determine who to draft based on how well they preformed in previous seasons. Overall, using data visualizations in order to get a better understadning of player statistics is a good way to see all options for things like Fantas drafting, but the draft in real life. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7ad5e63-26ed-40bc-ab5a-b6c1c867caed",
   "metadata": {},
   "source": [
    "To start, I wanted to explore overall team statistics; I decided to create visuals that compare specific teams to other statistics like passing yards. This gives me an inside look at what teams are preforming better than the others, which might give me an idea of what players on those specific teams are alo preforming better than others. \n",
    "\n",
    "Located below, the first graph represents total passing hyards by team, the second graph represents total rushing yards by team, the third represents total interceptions vs. total passing touchdowns, and the last visualization represents total passing vs receiving yards by season. "
   ]
  },
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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "team_passing_yards = data.groupby('team')['passing_yards'].sum().reset_index()\n",
    "team_passing_yards = team_passing_yards.sort_values(by='passing_yards', ascending=False)\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.bar(team_passing_yards['team'], team_passing_yards['passing_yards'], color='skyblue')\n",
    "plt.title('Total Passing Yards by Team')\n",
    "plt.xlabel('Team')\n",
    "plt.ylabel('Total Passing Yards')\n",
    "plt.xticks(rotation=45, ha='right')  \n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "dfd8b580-86fe-4019-9e63-5fd806b201ab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "team_rushing_yards = data.groupby('team')['rushing_yards'].sum().reset_index()\n",
    "team_rushing_yards = team_rushing_yards.sort_values(by='rushing_yards', ascending=False)\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.bar(team_rushing_yards['team'], team_rushing_yards['rushing_yards'], color='green')\n",
    "plt.title('Total Rushing Yards by Team')\n",
    "plt.xlabel('Team')\n",
    "plt.ylabel('Total Rushing Yards')\n",
    "plt.xticks(rotation=45, ha='right') \n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "abe2aaa2-9874-4ceb-9002-234a2819067d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "qb_stats = data[data['position'] == 'QB'][['interceptions', 'passing_tds']]\n",
    "total_interceptions = qb_stats['interceptions'].sum()\n",
    "total_passing_touchdowns = qb_stats['passing_tds'].sum()\n",
    "plt.figure(figsize=(8, 5))\n",
    "plt.barh(['Interceptions', 'Passing Touchdowns'], [total_interceptions, total_passing_touchdowns], color=['red', 'blue'])\n",
    "plt.title('Total Interceptions vs. Total Passing Touchdowns')\n",
    "plt.xlabel('Count')\n",
    "plt.ylabel('Statistic')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "13320ec3-17c4-4e90-909b-8b2e73f999e8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rb_data = data[data['position'] == 'RB']\n",
    "wr_te_data = data[data['position'].isin(['WR', 'TE'])]\n",
    "rb_season_totals = rb_data.groupby('season')['rushing_yards'].sum().reset_index()\n",
    "wr_te_season_totals = wr_te_data.groupby('season')['receiving_yards'].sum().reset_index()\n",
    "merged_data = pd.merge(rb_season_totals, wr_te_season_totals, on='season', suffixes=('_rb', '_wr_te'))\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.plot(merged_data['season'], merged_data['rushing_yards'], marker='o', label='Rushing Yards (RB)', color='green')\n",
    "plt.plot(merged_data['season'], merged_data['receiving_yards'], marker='o', label='Receiving Yards (WR+TE)', color='blue')\n",
    "plt.title('Total Rushing Yards vs. Total Receiving Yards by Season')\n",
    "plt.xlabel('Season')\n",
    "plt.ylabel('Total Yards')\n",
    "plt.legend()\n",
    "plt.grid(True)\n",
    "plt.xticks(rotation=45)\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1114d125-a977-49ca-95a1-c7eb792e070a",
   "metadata": {},
   "source": [
    "Creating visualizations such as bar plots and line graphs helped me to better understand my data by providing clear and intuitive representations of key statistics. Comparing metrics like rushing yards for running backs versus receiving yards for wide receivers and tight ends over different seasons allowed me to quickly identify trends and patterns, which also helps people to draft Fantasy teams as well as predict future real season outcomes. Similarly, visualizing statistics such as interceptions versus passing touchdowns for quarterbacks enabled me to make immediate comparisons and gain insights into player performance. Overall, these visualizations enhanced my understanding of the dataset and facilitated data-driven decision-making."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}