LindsaySprattFinalProject.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "bb9a621f",
   "metadata": {},
   "source": [
    "# Discrepancy of Gender in Head Coaching Positions "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d4ea7ddb",
   "metadata": {},
   "source": [
    "#  Introduction and Prior Work"
   ]
  },
  {
   "cell_type": "raw",
   "id": "01c1b385",
   "metadata": {},
   "source": [
    "     Are women’s resources suitable under Title IX requirements in comparison to the men’s in regards to college athletics? Considering the recent uproar regarding gender equity in the workforce, college athletics has become the new target for focusing on equal opportunities for both sexes. The NCAA has received backlash in the discrepancy between male and female athletics, as multiple studies have shown alarming statistics. As recently as October of 2021, NCAA schools have been investigated regarding the gap between funding. Under Title IX, college athletics are required to enable equal opportunities for all student-athletes regardless of gender. Despite this, the investigation found that “The NCAA has fallen short of upholding its commitment to gender equity, spending more on male athletes on average than female ones” (Associated Press). Although, this issue is not as black and white as it may seem. There have been counter arguments saying that a school’s funding for particular athletic teams is based purely off the revenue it produces, rather than maliciously discriminatory- based. This issue is not unique to the NCAA, as the investigation proved that the sports conglomerate ESPN is significantly underpaying for rights to broadcast women’s tournaments in college athletics. These types of pay cuts largely influence the amount of funding the NCAA can provide to its female athletes. \n",
    "\n",
    "\tFollowing the 2021 investigation, the NCAA received recommendations for reducing the gap between male and female athletics. On March 15, 2022 United States House members criticized the failure of NCAA president Mark Emmert to implement suggestions on creating true equity. The NCAA has formally acknowledged the discrepancies in college athletics, but has not taken any significant steps to fully address the issue. With data provided from the years 2010-2020 surrounding the first ten universities in the United States sorted alphabetically, we will see how the data aligns with Title IX requirements. This data has been retrieved from the EADA (Equity in Athletics Data Analysis), sorted, cleaned and visually represented to get a glimpse of equity in college sports. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "958c3f1f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0a14d604",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Survey Year</th>\n",
       "      <th>UNITID</th>\n",
       "      <th>Institution Name</th>\n",
       "      <th>State CD</th>\n",
       "      <th>Classification Name</th>\n",
       "      <th>Classification Other</th>\n",
       "      <th>Sanction Code</th>\n",
       "      <th>Sanction Name</th>\n",
       "      <th>Male Undergraduates</th>\n",
       "      <th>Female Undergraduates</th>\n",
       "      <th>...</th>\n",
       "      <th>Other Sports Male HD Coach FT Coaching Duties</th>\n",
       "      <th>Other Sports Male HD Coach PT Coaching Duties</th>\n",
       "      <th>Other Sports Female HD Coach FT Coaching Duties</th>\n",
       "      <th>Other Sports Female HD Coach PT Coaching Duties</th>\n",
       "      <th>Other Sports Total</th>\n",
       "      <th>Total Male HD Coach FT Coaching Duties</th>\n",
       "      <th>Total Male HD Coach PT Coaching Duties</th>\n",
       "      <th>Total Female HD Coach FT Coaching Duties</th>\n",
       "      <th>Total Female HD Coach PT Coaching Duties</th>\n",
       "      <th>Total HD Coaches</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010</td>\n",
       "      <td>222178</td>\n",
       "      <td>Abilene Christian University</td>\n",
       "      <td>TX</td>\n",
       "      <td>NCAA Division II (with football)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>1666</td>\n",
       "      <td>1933</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010</td>\n",
       "      <td>138558</td>\n",
       "      <td>Abraham Baldwin Agricultural College</td>\n",
       "      <td>GA</td>\n",
       "      <td>NJCAA Division I</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>NJCAA</td>\n",
       "      <td>1196</td>\n",
       "      <td>1220</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010</td>\n",
       "      <td>108232</td>\n",
       "      <td>ACADEMY OF ART UNIVERSITY</td>\n",
       "      <td>CA</td>\n",
       "      <td>NCAA Division II (without football)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>3141</td>\n",
       "      <td>3645</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010</td>\n",
       "      <td>126182</td>\n",
       "      <td>Adams State College</td>\n",
       "      <td>CO</td>\n",
       "      <td>NCAA Division II (with football)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>948</td>\n",
       "      <td>1079</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010</td>\n",
       "      <td>188429</td>\n",
       "      <td>Adelphi University</td>\n",
       "      <td>NY</td>\n",
       "      <td>NCAA Division II (without football)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>1331</td>\n",
       "      <td>3001</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>11</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>2020</td>\n",
       "      <td>168528</td>\n",
       "      <td>Adrian College</td>\n",
       "      <td>MI</td>\n",
       "      <td>NCAA Division III with football</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>877</td>\n",
       "      <td>861</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>2020</td>\n",
       "      <td>100654</td>\n",
       "      <td>Alabama A &amp; M University</td>\n",
       "      <td>AL</td>\n",
       "      <td>NCAA Division I-FCS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>1849</td>\n",
       "      <td>2814</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>2020</td>\n",
       "      <td>100724</td>\n",
       "      <td>Alabama State University</td>\n",
       "      <td>AL</td>\n",
       "      <td>NCAA Division I-FCS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>1171</td>\n",
       "      <td>2118</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>2020</td>\n",
       "      <td>188526</td>\n",
       "      <td>Albany College of Pharmacy and Health Sciences</td>\n",
       "      <td>NY</td>\n",
       "      <td>USCAA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9</td>\n",
       "      <td>other</td>\n",
       "      <td>270</td>\n",
       "      <td>413</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>2020</td>\n",
       "      <td>138716</td>\n",
       "      <td>Albany State University</td>\n",
       "      <td>GA</td>\n",
       "      <td>NCAA Division II with football</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>1210</td>\n",
       "      <td>2942</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>110 rows × 207 columns</p>\n",
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      ],
      "text/plain": [
       "     Survey Year  UNITID                                Institution Name  \\\n",
       "0           2010  222178                    Abilene Christian University   \n",
       "1           2010  138558            Abraham Baldwin Agricultural College   \n",
       "2           2010  108232                       ACADEMY OF ART UNIVERSITY   \n",
       "3           2010  126182                             Adams State College   \n",
       "4           2010  188429                              Adelphi University   \n",
       "..           ...     ...                                             ...   \n",
       "105         2020  168528                                  Adrian College   \n",
       "106         2020  100654                        Alabama A & M University   \n",
       "107         2020  100724                        Alabama State University   \n",
       "108         2020  188526  Albany College of Pharmacy and Health Sciences   \n",
       "109         2020  138716                         Albany State University   \n",
       "\n",
       "    State CD                  Classification Name Classification Other  \\\n",
       "0         TX     NCAA Division II (with football)                  NaN   \n",
       "1         GA                     NJCAA Division I                  NaN   \n",
       "2         CA  NCAA Division II (without football)                  NaN   \n",
       "3         CO     NCAA Division II (with football)                  NaN   \n",
       "4         NY  NCAA Division II (without football)                  NaN   \n",
       "..       ...                                  ...                  ...   \n",
       "105       MI      NCAA Division III with football                  NaN   \n",
       "106       AL                  NCAA Division I-FCS                  NaN   \n",
       "107       AL                  NCAA Division I-FCS                  NaN   \n",
       "108       NY                                USCAA                  NaN   \n",
       "109       GA       NCAA Division II with football                  NaN   \n",
       "\n",
       "     Sanction Code Sanction Name  Male Undergraduates  Female Undergraduates  \\\n",
       "0                1          NCAA                 1666                   1933   \n",
       "1                3         NJCAA                 1196                   1220   \n",
       "2                1          NCAA                 3141                   3645   \n",
       "3                1          NCAA                  948                   1079   \n",
       "4                1          NCAA                 1331                   3001   \n",
       "..             ...           ...                  ...                    ...   \n",
       "105              1          NCAA                  877                    861   \n",
       "106              1          NCAA                 1849                   2814   \n",
       "107              1          NCAA                 1171                   2118   \n",
       "108              9         other                  270                    413   \n",
       "109              1          NCAA                 1210                   2942   \n",
       "\n",
       "     ...  Other Sports Male HD Coach FT Coaching Duties  \\\n",
       "0    ...                                            NaN   \n",
       "1    ...                                            NaN   \n",
       "2    ...                                            NaN   \n",
       "3    ...                                            NaN   \n",
       "4    ...                                            NaN   \n",
       "..   ...                                            ...   \n",
       "105  ...                                            NaN   \n",
       "106  ...                                            NaN   \n",
       "107  ...                                            NaN   \n",
       "108  ...                                            NaN   \n",
       "109  ...                                            NaN   \n",
       "\n",
       "    Other Sports Male HD Coach PT Coaching Duties  \\\n",
       "0                                             NaN   \n",
       "1                                             NaN   \n",
       "2                                             NaN   \n",
       "3                                             NaN   \n",
       "4                                             NaN   \n",
       "..                                            ...   \n",
       "105                                           NaN   \n",
       "106                                           NaN   \n",
       "107                                           NaN   \n",
       "108                                           NaN   \n",
       "109                                           NaN   \n",
       "\n",
       "     Other Sports Female HD Coach FT Coaching Duties  \\\n",
       "0                                                NaN   \n",
       "1                                                NaN   \n",
       "2                                                NaN   \n",
       "3                                                NaN   \n",
       "4                                                NaN   \n",
       "..                                               ...   \n",
       "105                                              NaN   \n",
       "106                                              NaN   \n",
       "107                                              NaN   \n",
       "108                                              NaN   \n",
       "109                                              NaN   \n",
       "\n",
       "     Other Sports Female HD Coach PT Coaching Duties  Other Sports Total  \\\n",
       "0                                                NaN                 NaN   \n",
       "1                                                NaN                 NaN   \n",
       "2                                                NaN                 NaN   \n",
       "3                                                NaN                 NaN   \n",
       "4                                                NaN                 NaN   \n",
       "..                                               ...                 ...   \n",
       "105                                              1.0                 1.0   \n",
       "106                                              NaN                 NaN   \n",
       "107                                              NaN                 NaN   \n",
       "108                                              NaN                 NaN   \n",
       "109                                              NaN                 NaN   \n",
       "\n",
       "     Total Male HD Coach FT Coaching Duties  \\\n",
       "0                                         2   \n",
       "1                                         0   \n",
       "2                                         2   \n",
       "3                                         3   \n",
       "4                                         0   \n",
       "..                                      ...   \n",
       "105                                       0   \n",
       "106                                       2   \n",
       "107                                       3   \n",
       "108                                       0   \n",
       "109                                       2   \n",
       "\n",
       "     Total Male HD Coach PT Coaching Duties  \\\n",
       "0                                         2   \n",
       "1                                         2   \n",
       "2                                         2   \n",
       "3                                         3   \n",
       "4                                         5   \n",
       "..                                      ...   \n",
       "105                                      11   \n",
       "106                                       1   \n",
       "107                                       3   \n",
       "108                                       2   \n",
       "109                                       2   \n",
       "\n",
       "     Total Female HD Coach FT Coaching Duties  \\\n",
       "0                                           2   \n",
       "1                                           0   \n",
       "2                                           3   \n",
       "3                                           1   \n",
       "4                                           0   \n",
       "..                                        ...   \n",
       "105                                         0   \n",
       "106                                         2   \n",
       "107                                         2   \n",
       "108                                         0   \n",
       "109                                         3   \n",
       "\n",
       "     Total Female HD Coach PT Coaching Duties  Total HD Coaches  \n",
       "0                                           0                 6  \n",
       "1                                           1                 3  \n",
       "2                                           1                 8  \n",
       "3                                           1                 8  \n",
       "4                                           6                11  \n",
       "..                                        ...               ...  \n",
       "105                                         4                15  \n",
       "106                                         2                 7  \n",
       "107                                         0                 8  \n",
       "108                                         0                 2  \n",
       "109                                         0                 7  \n",
       "\n",
       "[110 rows x 207 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "url = open('womens.csv', 'r')  # women's teams \n",
    "df = pd.read_csv(url)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "84e98e5c",
   "metadata": {},
   "source": [
    "# Data Cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "11ec3c07",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>Survey Year</th>\n",
       "      <th>Total Male HD Coach FT Coaching Duties</th>\n",
       "      <th>Total Male HD Coach PT Coaching Duties</th>\n",
       "      <th>Total Female HD Coach FT Coaching Duties</th>\n",
       "      <th>Total Female HD Coach PT Coaching Duties</th>\n",
       "      <th>Total HD Coaches</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>2020</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>2020</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>2020</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>2020</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>2020</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>110 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Survey Year  Total Male HD Coach FT Coaching Duties  \\\n",
       "0           2010                                       2   \n",
       "1           2010                                       0   \n",
       "2           2010                                       2   \n",
       "3           2010                                       3   \n",
       "4           2010                                       0   \n",
       "..           ...                                     ...   \n",
       "105         2020                                       0   \n",
       "106         2020                                       2   \n",
       "107         2020                                       3   \n",
       "108         2020                                       0   \n",
       "109         2020                                       2   \n",
       "\n",
       "     Total Male HD Coach PT Coaching Duties  \\\n",
       "0                                         2   \n",
       "1                                         2   \n",
       "2                                         2   \n",
       "3                                         3   \n",
       "4                                         5   \n",
       "..                                      ...   \n",
       "105                                      11   \n",
       "106                                       1   \n",
       "107                                       3   \n",
       "108                                       2   \n",
       "109                                       2   \n",
       "\n",
       "     Total Female HD Coach FT Coaching Duties  \\\n",
       "0                                           2   \n",
       "1                                           0   \n",
       "2                                           3   \n",
       "3                                           1   \n",
       "4                                           0   \n",
       "..                                        ...   \n",
       "105                                         0   \n",
       "106                                         2   \n",
       "107                                         2   \n",
       "108                                         0   \n",
       "109                                         3   \n",
       "\n",
       "     Total Female HD Coach PT Coaching Duties  Total HD Coaches  \n",
       "0                                           0                 6  \n",
       "1                                           1                 3  \n",
       "2                                           1                 8  \n",
       "3                                           1                 8  \n",
       "4                                           6                11  \n",
       "..                                        ...               ...  \n",
       "105                                         4                15  \n",
       "106                                         2                 7  \n",
       "107                                         0                 8  \n",
       "108                                         0                 2  \n",
       "109                                         0                 7  \n",
       "\n",
       "[110 rows x 6 columns]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.drop(df.iloc[:, 1:202], axis = 1, inplace = True)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "9135bb20",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    54\n",
       "2    25\n",
       "1    19\n",
       "3    11\n",
       "4     1\n",
       "Name: Total Male HD Coach FT Coaching Duties, dtype: int64"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Total Male HD Coach FT Coaching Duties\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "b6027eba",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "165\n"
     ]
    }
   ],
   "source": [
    "female_ft_total = df[\"Total Female HD Coach FT Coaching Duties\"].sum()     \n",
    "print(female_ft_total) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "552fa3ff",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "215\n"
     ]
    }
   ],
   "source": [
    "female_pt_total = df[\"Total Female HD Coach PT Coaching Duties\"].sum()\n",
    "print(female_pt_total)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "c483b325",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "106\n"
     ]
    }
   ],
   "source": [
    "male_ft_total = df[\"Total Male HD Coach FT Coaching Duties\"].sum()\n",
    "print(male_ft_total)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "23ee8dd1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "346\n"
     ]
    }
   ],
   "source": [
    "male_pt_total = df[\"Total Male HD Coach PT Coaching Duties\"].sum()\n",
    "print(male_pt_total)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "0b6a7022",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "832\n"
     ]
    }
   ],
   "source": [
    "sum_head_coaches = female_pt_total + male_ft_total + female_ft_total + male_pt_total\n",
    "print(sum_head_coaches)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "06d2d0a2",
   "metadata": {},
   "source": [
    "# Data Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "7b2c5c49",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.DataFrame({'Positions by Gender': [female_ft_total, female_pt_total, male_ft_total, male_pt_total],\n",
    "                   ' ': [165, 215, 106, 346]},\n",
    "                  index=[\"Female Full Time Coaches\", \"Female Part Time Coaches\", \"Male Full Time Coaches\",\n",
    "                        \"Male Part Time Coaches\"])\n",
    "plot = df.plot.pie(y = \" \", figsize=(5, 5), autopct='%.1f%%')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "7e3c7270",
   "metadata": {
    "scrolled": false
   },
   "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>Survey Year</th>\n",
       "      <th>UNITID</th>\n",
       "      <th>Institution Name</th>\n",
       "      <th>State CD</th>\n",
       "      <th>Classification Name</th>\n",
       "      <th>Classification Other</th>\n",
       "      <th>Sanction Code</th>\n",
       "      <th>Sanction Name</th>\n",
       "      <th>Male Undergraduates</th>\n",
       "      <th>Female Undergraduates</th>\n",
       "      <th>...</th>\n",
       "      <th>Other Sports Male HD Coach FT Coaching Duties</th>\n",
       "      <th>Other Sports Male HD Coach PT Coaching Duties</th>\n",
       "      <th>Other Sports Female HD Coach FT Coaching Duties</th>\n",
       "      <th>Other Sports Female HD Coach PT Coaching Duties</th>\n",
       "      <th>Other Sports Total</th>\n",
       "      <th>Total Male HD Coach FT Coaching Duties</th>\n",
       "      <th>Total Male HD Coach PT Coaching Duties</th>\n",
       "      <th>Total Female HD Coach FT Coaching Duties</th>\n",
       "      <th>Total Female HD Coach PT Coaching Duties</th>\n",
       "      <th>Total HD Coaches</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010</td>\n",
       "      <td>222178</td>\n",
       "      <td>Abilene Christian University</td>\n",
       "      <td>TX</td>\n",
       "      <td>NCAA Division II (with football)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>1666</td>\n",
       "      <td>1933</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010</td>\n",
       "      <td>138558</td>\n",
       "      <td>Abraham Baldwin Agricultural College</td>\n",
       "      <td>GA</td>\n",
       "      <td>NJCAA Division I</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>NJCAA</td>\n",
       "      <td>1196</td>\n",
       "      <td>1220</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010</td>\n",
       "      <td>108232</td>\n",
       "      <td>ACADEMY OF ART UNIVERSITY</td>\n",
       "      <td>CA</td>\n",
       "      <td>NCAA Division II (without football)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>3141</td>\n",
       "      <td>3645</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010</td>\n",
       "      <td>126182</td>\n",
       "      <td>Adams State College</td>\n",
       "      <td>CO</td>\n",
       "      <td>NCAA Division II (with football)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>948</td>\n",
       "      <td>1079</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010</td>\n",
       "      <td>188429</td>\n",
       "      <td>Adelphi University</td>\n",
       "      <td>NY</td>\n",
       "      <td>NCAA Division II (without football)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>1331</td>\n",
       "      <td>3001</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>2020</td>\n",
       "      <td>168528</td>\n",
       "      <td>Adrian College</td>\n",
       "      <td>MI</td>\n",
       "      <td>NCAA Division III with football</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>877</td>\n",
       "      <td>861</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>2020</td>\n",
       "      <td>100654</td>\n",
       "      <td>Alabama A &amp; M University</td>\n",
       "      <td>AL</td>\n",
       "      <td>NCAA Division I-FCS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>1849</td>\n",
       "      <td>2814</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>2020</td>\n",
       "      <td>100724</td>\n",
       "      <td>Alabama State University</td>\n",
       "      <td>AL</td>\n",
       "      <td>NCAA Division I-FCS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>1171</td>\n",
       "      <td>2118</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>2020</td>\n",
       "      <td>188526</td>\n",
       "      <td>Albany College of Pharmacy and Health Sciences</td>\n",
       "      <td>NY</td>\n",
       "      <td>USCAA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9</td>\n",
       "      <td>other</td>\n",
       "      <td>270</td>\n",
       "      <td>413</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>2020</td>\n",
       "      <td>138716</td>\n",
       "      <td>Albany State University</td>\n",
       "      <td>GA</td>\n",
       "      <td>NCAA Division II with football</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>1210</td>\n",
       "      <td>2942</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>110 rows × 207 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Survey Year  UNITID                                Institution Name  \\\n",
       "0           2010  222178                    Abilene Christian University   \n",
       "1           2010  138558            Abraham Baldwin Agricultural College   \n",
       "2           2010  108232                       ACADEMY OF ART UNIVERSITY   \n",
       "3           2010  126182                             Adams State College   \n",
       "4           2010  188429                              Adelphi University   \n",
       "..           ...     ...                                             ...   \n",
       "105         2020  168528                                  Adrian College   \n",
       "106         2020  100654                        Alabama A & M University   \n",
       "107         2020  100724                        Alabama State University   \n",
       "108         2020  188526  Albany College of Pharmacy and Health Sciences   \n",
       "109         2020  138716                         Albany State University   \n",
       "\n",
       "    State CD                  Classification Name Classification Other  \\\n",
       "0         TX     NCAA Division II (with football)                  NaN   \n",
       "1         GA                     NJCAA Division I                  NaN   \n",
       "2         CA  NCAA Division II (without football)                  NaN   \n",
       "3         CO     NCAA Division II (with football)                  NaN   \n",
       "4         NY  NCAA Division II (without football)                  NaN   \n",
       "..       ...                                  ...                  ...   \n",
       "105       MI      NCAA Division III with football                  NaN   \n",
       "106       AL                  NCAA Division I-FCS                  NaN   \n",
       "107       AL                  NCAA Division I-FCS                  NaN   \n",
       "108       NY                                USCAA                  NaN   \n",
       "109       GA       NCAA Division II with football                  NaN   \n",
       "\n",
       "     Sanction Code Sanction Name  Male Undergraduates  Female Undergraduates  \\\n",
       "0                1          NCAA                 1666                   1933   \n",
       "1                3         NJCAA                 1196                   1220   \n",
       "2                1          NCAA                 3141                   3645   \n",
       "3                1          NCAA                  948                   1079   \n",
       "4                1          NCAA                 1331                   3001   \n",
       "..             ...           ...                  ...                    ...   \n",
       "105              1          NCAA                  877                    861   \n",
       "106              1          NCAA                 1849                   2814   \n",
       "107              1          NCAA                 1171                   2118   \n",
       "108              9         other                  270                    413   \n",
       "109              1          NCAA                 1210                   2942   \n",
       "\n",
       "     ...  Other Sports Male HD Coach FT Coaching Duties  \\\n",
       "0    ...                                            NaN   \n",
       "1    ...                                            NaN   \n",
       "2    ...                                            NaN   \n",
       "3    ...                                            NaN   \n",
       "4    ...                                            NaN   \n",
       "..   ...                                            ...   \n",
       "105  ...                                            NaN   \n",
       "106  ...                                            NaN   \n",
       "107  ...                                            NaN   \n",
       "108  ...                                            NaN   \n",
       "109  ...                                            NaN   \n",
       "\n",
       "    Other Sports Male HD Coach PT Coaching Duties  \\\n",
       "0                                             NaN   \n",
       "1                                             NaN   \n",
       "2                                             NaN   \n",
       "3                                             NaN   \n",
       "4                                             NaN   \n",
       "..                                            ...   \n",
       "105                                           NaN   \n",
       "106                                           NaN   \n",
       "107                                           NaN   \n",
       "108                                           NaN   \n",
       "109                                           NaN   \n",
       "\n",
       "     Other Sports Female HD Coach FT Coaching Duties  \\\n",
       "0                                                NaN   \n",
       "1                                                NaN   \n",
       "2                                                NaN   \n",
       "3                                                NaN   \n",
       "4                                                NaN   \n",
       "..                                               ...   \n",
       "105                                              NaN   \n",
       "106                                              NaN   \n",
       "107                                              NaN   \n",
       "108                                              NaN   \n",
       "109                                              NaN   \n",
       "\n",
       "     Other Sports Female HD Coach PT Coaching Duties  Other Sports Total  \\\n",
       "0                                                NaN                 NaN   \n",
       "1                                                NaN                 NaN   \n",
       "2                                                NaN                 NaN   \n",
       "3                                                NaN                 NaN   \n",
       "4                                                NaN                 NaN   \n",
       "..                                               ...                 ...   \n",
       "105                                              NaN                 NaN   \n",
       "106                                              NaN                 NaN   \n",
       "107                                              NaN                 NaN   \n",
       "108                                              NaN                 NaN   \n",
       "109                                              NaN                 NaN   \n",
       "\n",
       "     Total Male HD Coach FT Coaching Duties  \\\n",
       "0                                         4   \n",
       "1                                         0   \n",
       "2                                         3   \n",
       "3                                         4   \n",
       "4                                         0   \n",
       "..                                      ...   \n",
       "105                                       0   \n",
       "106                                       3   \n",
       "107                                       3   \n",
       "108                                       0   \n",
       "109                                       3   \n",
       "\n",
       "     Total Male HD Coach PT Coaching Duties  \\\n",
       "0                                         2   \n",
       "1                                         3   \n",
       "2                                         2   \n",
       "3                                         3   \n",
       "4                                         7   \n",
       "..                                      ...   \n",
       "105                                      13   \n",
       "106                                       2   \n",
       "107                                       3   \n",
       "108                                       2   \n",
       "109                                       1   \n",
       "\n",
       "     Total Female HD Coach FT Coaching Duties  \\\n",
       "0                                           0   \n",
       "1                                           0   \n",
       "2                                           0   \n",
       "3                                           0   \n",
       "4                                           0   \n",
       "..                                        ...   \n",
       "105                                         0   \n",
       "106                                         0   \n",
       "107                                         0   \n",
       "108                                         0   \n",
       "109                                         0   \n",
       "\n",
       "     Total Female HD Coach PT Coaching Duties  Total HD Coaches  \n",
       "0                                           0                 6  \n",
       "1                                           0                 3  \n",
       "2                                           1                 6  \n",
       "3                                           1                 8  \n",
       "4                                           2                 9  \n",
       "..                                        ...               ...  \n",
       "105                                         0                13  \n",
       "106                                         2                 7  \n",
       "107                                         0                 6  \n",
       "108                                         0                 2  \n",
       "109                                         0                 4  \n",
       "\n",
       "[110 rows x 207 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "open_m_file = open('mens.csv', 'r')\n",
    "df2 = pd.read_csv(open_m_file)\n",
    "df2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f3e5dec1",
   "metadata": {},
   "source": [
    "# Data Cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "4173b136",
   "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>Survey Year</th>\n",
       "      <th>Total Male HD Coach FT Coaching Duties</th>\n",
       "      <th>Total Male HD Coach PT Coaching Duties</th>\n",
       "      <th>Total Female HD Coach FT Coaching Duties</th>\n",
       "      <th>Total Female HD Coach PT Coaching Duties</th>\n",
       "      <th>Total HD Coaches</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>2020</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>2020</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>2020</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>2020</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>2020</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>110 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Survey Year  Total Male HD Coach FT Coaching Duties  \\\n",
       "0           2010                                       4   \n",
       "1           2010                                       0   \n",
       "2           2010                                       3   \n",
       "3           2010                                       4   \n",
       "4           2010                                       0   \n",
       "..           ...                                     ...   \n",
       "105         2020                                       0   \n",
       "106         2020                                       3   \n",
       "107         2020                                       3   \n",
       "108         2020                                       0   \n",
       "109         2020                                       3   \n",
       "\n",
       "     Total Male HD Coach PT Coaching Duties  \\\n",
       "0                                         2   \n",
       "1                                         3   \n",
       "2                                         2   \n",
       "3                                         3   \n",
       "4                                         7   \n",
       "..                                      ...   \n",
       "105                                      13   \n",
       "106                                       2   \n",
       "107                                       3   \n",
       "108                                       2   \n",
       "109                                       1   \n",
       "\n",
       "     Total Female HD Coach FT Coaching Duties  \\\n",
       "0                                           0   \n",
       "1                                           0   \n",
       "2                                           0   \n",
       "3                                           0   \n",
       "4                                           0   \n",
       "..                                        ...   \n",
       "105                                         0   \n",
       "106                                         0   \n",
       "107                                         0   \n",
       "108                                         0   \n",
       "109                                         0   \n",
       "\n",
       "     Total Female HD Coach PT Coaching Duties  Total HD Coaches  \n",
       "0                                           0                 6  \n",
       "1                                           0                 3  \n",
       "2                                           1                 6  \n",
       "3                                           1                 8  \n",
       "4                                           2                 9  \n",
       "..                                        ...               ...  \n",
       "105                                         0                13  \n",
       "106                                         2                 7  \n",
       "107                                         0                 6  \n",
       "108                                         0                 2  \n",
       "109                                         0                 4  \n",
       "\n",
       "[110 rows x 6 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.drop(df2.iloc[:, 1:202], axis = 1, inplace = True)\n",
    "df2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4a0fa07",
   "metadata": {},
   "source": [
    "# Data Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "3fba82c8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Number of Instances')"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "male_part = df2[\"Total Male HD Coach PT Coaching Duties\"].plot(kind='hist', bins = 20)\n",
    "female_part = df2['Total Female HD Coach PT Coaching Duties'].plot(kind='hist', bins = 20)\n",
    "_ = male_part.set(title =\"Women's Team Coaches\")\n",
    "graph = male_part.legend(['Male', 'Female'], loc= 'upper right')\n",
    "plt.xlabel(\"Number of Coaches\")\n",
    "plt.ylabel(\"Number of Instances\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "id": "522cf470",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "355\n"
     ]
    }
   ],
   "source": [
    "difference_pt = (df2[\"Total Male HD Coach PT Coaching Duties\"].sum() \n",
    "                 - df2[\"Total Female HD Coach PT Coaching Duties\"].sum())\n",
    "print(difference_pt)\n",
    "# 355 person different"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "id": "dddee972",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "male_ft = df2[\"Total Male HD Coach FT Coaching Duties\"].plot(kind = 'hist')\n",
    "female_ft = df2[\"Total Female HD Coach FT Coaching Duties\"].plot(kind = 'hist')\n",
    "_ = male_ft.set(title =\"Full Time Positions\")\n",
    "graph = male_ft.legend(['Male', 'Female'], loc= 'upper right')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "id": "1edb78bf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "232\n"
     ]
    }
   ],
   "source": [
    "difference_ft = (df2[\"Total Male HD Coach FT Coaching Duties\"].sum() \n",
    "                 - df2[\"Total Female HD Coach FT Coaching Duties\"].sum())\n",
    "print(difference_ft)\n",
    "# 232 person difference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6b4c7f4f",
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'pltcolor' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m/var/folders/wx/h6xs183s7klgpmp9jmxtv20w0000gn/T/ipykernel_12007/3129572979.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mseaborn\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0msns\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mcols\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpltcolor\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf2\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"Total Male HD Coach PT Coaching Duties\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdf2\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"Total Female HD Coach PT Coaching Duties\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m _ = sns.lmplot(x=\"Total Male HD Coach PT Coaching Duties\",y=\"Total Female HD Coach PT Coaching Duties\",\n\u001b[1;32m      5\u001b[0m            data=df2, palette = cols, fit_reg=True) \n",
      "\u001b[0;31mNameError\u001b[0m: name 'pltcolor' is not defined"
     ]
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "cols = pltcolor(df2[\"Total Male HD Coach PT Coaching Duties\"], df2[\"Total Female HD Coach PT Coaching Duties\"])\n",
    "\n",
    "_ = sns.lmplot(x=\"Total Male HD Coach PT Coaching Duties\",y=\"Total Female HD Coach PT Coaching Duties\",\n",
    "           data=df2, palette = cols, fit_reg=True) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "3b499e56",
   "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>Survey Year</th>\n",
       "      <th>UNITID</th>\n",
       "      <th>Institution Name</th>\n",
       "      <th>State CD</th>\n",
       "      <th>Classification Name</th>\n",
       "      <th>Classification Other</th>\n",
       "      <th>Sanction Code</th>\n",
       "      <th>Sanction Name</th>\n",
       "      <th>Male Undergraduates</th>\n",
       "      <th>Female Undergraduates</th>\n",
       "      <th>...</th>\n",
       "      <th>Wrestling Total Revenue</th>\n",
       "      <th>Other Sports Men's Team Revenue</th>\n",
       "      <th>Other Sports Women's Team Revenue</th>\n",
       "      <th>Other Sports Coed Team Revenue</th>\n",
       "      <th>Other Sports Total Revenue</th>\n",
       "      <th>Total Men's Team Revenue</th>\n",
       "      <th>Total Women's Team Revenue</th>\n",
       "      <th>Total Coed Team Revenue</th>\n",
       "      <th>Not Allocated by Gender/Sport Revenue</th>\n",
       "      <th>Grand Total Revenue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010</td>\n",
       "      <td>222178</td>\n",
       "      <td>Abilene Christian University</td>\n",
       "      <td>TX</td>\n",
       "      <td>NCAA Division II (with football)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>1666</td>\n",
       "      <td>1933</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4177358</td>\n",
       "      <td>2516288</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1657756</td>\n",
       "      <td>8351402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010</td>\n",
       "      <td>138558</td>\n",
       "      <td>Abraham Baldwin Agricultural College</td>\n",
       "      <td>GA</td>\n",
       "      <td>NJCAA Division I</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>NJCAA</td>\n",
       "      <td>1196</td>\n",
       "      <td>1220</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>240901</td>\n",
       "      <td>263222</td>\n",
       "      <td>NaN</td>\n",
       "      <td>143966</td>\n",
       "      <td>648089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010</td>\n",
       "      <td>108232</td>\n",
       "      <td>ACADEMY OF ART UNIVERSITY</td>\n",
       "      <td>CA</td>\n",
       "      <td>NCAA Division II (without football)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>3141</td>\n",
       "      <td>3645</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1944029</td>\n",
       "      <td>2878866</td>\n",
       "      <td>NaN</td>\n",
       "      <td>827374</td>\n",
       "      <td>5650269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010</td>\n",
       "      <td>126182</td>\n",
       "      <td>Adams State College</td>\n",
       "      <td>CO</td>\n",
       "      <td>NCAA Division II (with football)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>948</td>\n",
       "      <td>1079</td>\n",
       "      <td>...</td>\n",
       "      <td>241554.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2379968</td>\n",
       "      <td>1951906</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1455979</td>\n",
       "      <td>5787853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010</td>\n",
       "      <td>188429</td>\n",
       "      <td>Adelphi University</td>\n",
       "      <td>NY</td>\n",
       "      <td>NCAA Division II (without football)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>1331</td>\n",
       "      <td>3001</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2452503</td>\n",
       "      <td>2821229</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2047445</td>\n",
       "      <td>7321177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>2020</td>\n",
       "      <td>168528</td>\n",
       "      <td>Adrian College</td>\n",
       "      <td>MI</td>\n",
       "      <td>NCAA Division III with football</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>877</td>\n",
       "      <td>861</td>\n",
       "      <td>...</td>\n",
       "      <td>211274.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>94085.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>94085.0</td>\n",
       "      <td>1405675</td>\n",
       "      <td>1091642</td>\n",
       "      <td>NaN</td>\n",
       "      <td>718716</td>\n",
       "      <td>3216033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>2020</td>\n",
       "      <td>100654</td>\n",
       "      <td>Alabama A &amp; M University</td>\n",
       "      <td>AL</td>\n",
       "      <td>NCAA Division I-FCS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>1849</td>\n",
       "      <td>2814</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5770773</td>\n",
       "      <td>2470361</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1813910</td>\n",
       "      <td>10055044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>2020</td>\n",
       "      <td>100724</td>\n",
       "      <td>Alabama State University</td>\n",
       "      <td>AL</td>\n",
       "      <td>NCAA Division I-FCS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>1171</td>\n",
       "      <td>2118</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5520136</td>\n",
       "      <td>3116013</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2796995</td>\n",
       "      <td>11433144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>2020</td>\n",
       "      <td>188526</td>\n",
       "      <td>Albany College of Pharmacy and Health Sciences</td>\n",
       "      <td>NY</td>\n",
       "      <td>USCAA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9</td>\n",
       "      <td>other</td>\n",
       "      <td>270</td>\n",
       "      <td>413</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26710</td>\n",
       "      <td>26660</td>\n",
       "      <td>NaN</td>\n",
       "      <td>91073</td>\n",
       "      <td>144443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>2020</td>\n",
       "      <td>138716</td>\n",
       "      <td>Albany State University</td>\n",
       "      <td>GA</td>\n",
       "      <td>NCAA Division II with football</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>1210</td>\n",
       "      <td>2942</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1392895</td>\n",
       "      <td>640448</td>\n",
       "      <td>NaN</td>\n",
       "      <td>490064</td>\n",
       "      <td>2523407</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>110 rows × 168 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Survey Year  UNITID                                Institution Name  \\\n",
       "0           2010  222178                    Abilene Christian University   \n",
       "1           2010  138558            Abraham Baldwin Agricultural College   \n",
       "2           2010  108232                       ACADEMY OF ART UNIVERSITY   \n",
       "3           2010  126182                             Adams State College   \n",
       "4           2010  188429                              Adelphi University   \n",
       "..           ...     ...                                             ...   \n",
       "105         2020  168528                                  Adrian College   \n",
       "106         2020  100654                        Alabama A & M University   \n",
       "107         2020  100724                        Alabama State University   \n",
       "108         2020  188526  Albany College of Pharmacy and Health Sciences   \n",
       "109         2020  138716                         Albany State University   \n",
       "\n",
       "    State CD                  Classification Name Classification Other  \\\n",
       "0         TX     NCAA Division II (with football)                  NaN   \n",
       "1         GA                     NJCAA Division I                  NaN   \n",
       "2         CA  NCAA Division II (without football)                  NaN   \n",
       "3         CO     NCAA Division II (with football)                  NaN   \n",
       "4         NY  NCAA Division II (without football)                  NaN   \n",
       "..       ...                                  ...                  ...   \n",
       "105       MI      NCAA Division III with football                  NaN   \n",
       "106       AL                  NCAA Division I-FCS                  NaN   \n",
       "107       AL                  NCAA Division I-FCS                  NaN   \n",
       "108       NY                                USCAA                  NaN   \n",
       "109       GA       NCAA Division II with football                  NaN   \n",
       "\n",
       "     Sanction Code Sanction Name  Male Undergraduates  Female Undergraduates  \\\n",
       "0                1          NCAA                 1666                   1933   \n",
       "1                3         NJCAA                 1196                   1220   \n",
       "2                1          NCAA                 3141                   3645   \n",
       "3                1          NCAA                  948                   1079   \n",
       "4                1          NCAA                 1331                   3001   \n",
       "..             ...           ...                  ...                    ...   \n",
       "105              1          NCAA                  877                    861   \n",
       "106              1          NCAA                 1849                   2814   \n",
       "107              1          NCAA                 1171                   2118   \n",
       "108              9         other                  270                    413   \n",
       "109              1          NCAA                 1210                   2942   \n",
       "\n",
       "     ...  Wrestling Total Revenue  Other Sports Men's Team Revenue  \\\n",
       "0    ...                      NaN                              NaN   \n",
       "1    ...                      NaN                              NaN   \n",
       "2    ...                      NaN                              NaN   \n",
       "3    ...                 241554.0                              NaN   \n",
       "4    ...                      NaN                              NaN   \n",
       "..   ...                      ...                              ...   \n",
       "105  ...                 211274.0                              NaN   \n",
       "106  ...                      NaN                              NaN   \n",
       "107  ...                      NaN                              NaN   \n",
       "108  ...                      NaN                              NaN   \n",
       "109  ...                      NaN                              NaN   \n",
       "\n",
       "     Other Sports Women's Team Revenue  Other Sports Coed Team Revenue  \\\n",
       "0                                  NaN                             NaN   \n",
       "1                                  NaN                             NaN   \n",
       "2                                  NaN                             NaN   \n",
       "3                                  NaN                             NaN   \n",
       "4                                  NaN                             NaN   \n",
       "..                                 ...                             ...   \n",
       "105                            94085.0                             NaN   \n",
       "106                                NaN                             NaN   \n",
       "107                                NaN                             NaN   \n",
       "108                                NaN                             NaN   \n",
       "109                                NaN                             NaN   \n",
       "\n",
       "     Other Sports Total Revenue  Total Men's Team Revenue  \\\n",
       "0                           NaN                   4177358   \n",
       "1                           NaN                    240901   \n",
       "2                           NaN                   1944029   \n",
       "3                           NaN                   2379968   \n",
       "4                           NaN                   2452503   \n",
       "..                          ...                       ...   \n",
       "105                     94085.0                   1405675   \n",
       "106                         NaN                   5770773   \n",
       "107                         NaN                   5520136   \n",
       "108                         NaN                     26710   \n",
       "109                         NaN                   1392895   \n",
       "\n",
       "     Total Women's Team Revenue  Total Coed Team Revenue  \\\n",
       "0                       2516288                      NaN   \n",
       "1                        263222                      NaN   \n",
       "2                       2878866                      NaN   \n",
       "3                       1951906                      NaN   \n",
       "4                       2821229                      NaN   \n",
       "..                          ...                      ...   \n",
       "105                     1091642                      NaN   \n",
       "106                     2470361                      NaN   \n",
       "107                     3116013                      NaN   \n",
       "108                       26660                      NaN   \n",
       "109                      640448                      NaN   \n",
       "\n",
       "     Not Allocated by Gender/Sport Revenue  Grand Total Revenue  \n",
       "0                                  1657756              8351402  \n",
       "1                                   143966               648089  \n",
       "2                                   827374              5650269  \n",
       "3                                  1455979              5787853  \n",
       "4                                  2047445              7321177  \n",
       "..                                     ...                  ...  \n",
       "105                                 718716              3216033  \n",
       "106                                1813910             10055044  \n",
       "107                                2796995             11433144  \n",
       "108                                  91073               144443  \n",
       "109                                 490064              2523407  \n",
       "\n",
       "[110 rows x 168 columns]"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "revenue = open('revenues.csv', 'r')\n",
    "df3 = pd.read_csv(revenue)\n",
    "df3"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f6007e40",
   "metadata": {},
   "source": [
    "# Data Cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "a97819a7",
   "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>Survey Year</th>\n",
       "      <th>Total Men's Team Revenue</th>\n",
       "      <th>Total Women's Team Revenue</th>\n",
       "      <th>Total Coed Team Revenue</th>\n",
       "      <th>Not Allocated by Gender/Sport Revenue</th>\n",
       "      <th>Grand Total Revenue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010</td>\n",
       "      <td>4177358</td>\n",
       "      <td>2516288</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1657756</td>\n",
       "      <td>8351402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010</td>\n",
       "      <td>240901</td>\n",
       "      <td>263222</td>\n",
       "      <td>NaN</td>\n",
       "      <td>143966</td>\n",
       "      <td>648089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010</td>\n",
       "      <td>1944029</td>\n",
       "      <td>2878866</td>\n",
       "      <td>NaN</td>\n",
       "      <td>827374</td>\n",
       "      <td>5650269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010</td>\n",
       "      <td>2379968</td>\n",
       "      <td>1951906</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1455979</td>\n",
       "      <td>5787853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010</td>\n",
       "      <td>2452503</td>\n",
       "      <td>2821229</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2047445</td>\n",
       "      <td>7321177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>2020</td>\n",
       "      <td>1405675</td>\n",
       "      <td>1091642</td>\n",
       "      <td>NaN</td>\n",
       "      <td>718716</td>\n",
       "      <td>3216033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>2020</td>\n",
       "      <td>5770773</td>\n",
       "      <td>2470361</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1813910</td>\n",
       "      <td>10055044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>2020</td>\n",
       "      <td>5520136</td>\n",
       "      <td>3116013</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2796995</td>\n",
       "      <td>11433144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>2020</td>\n",
       "      <td>26710</td>\n",
       "      <td>26660</td>\n",
       "      <td>NaN</td>\n",
       "      <td>91073</td>\n",
       "      <td>144443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>2020</td>\n",
       "      <td>1392895</td>\n",
       "      <td>640448</td>\n",
       "      <td>NaN</td>\n",
       "      <td>490064</td>\n",
       "      <td>2523407</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>110 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Survey Year  Total Men's Team Revenue  Total Women's Team Revenue  \\\n",
       "0           2010                   4177358                     2516288   \n",
       "1           2010                    240901                      263222   \n",
       "2           2010                   1944029                     2878866   \n",
       "3           2010                   2379968                     1951906   \n",
       "4           2010                   2452503                     2821229   \n",
       "..           ...                       ...                         ...   \n",
       "105         2020                   1405675                     1091642   \n",
       "106         2020                   5770773                     2470361   \n",
       "107         2020                   5520136                     3116013   \n",
       "108         2020                     26710                       26660   \n",
       "109         2020                   1392895                      640448   \n",
       "\n",
       "     Total Coed Team Revenue  Not Allocated by Gender/Sport Revenue  \\\n",
       "0                        NaN                                1657756   \n",
       "1                        NaN                                 143966   \n",
       "2                        NaN                                 827374   \n",
       "3                        NaN                                1455979   \n",
       "4                        NaN                                2047445   \n",
       "..                       ...                                    ...   \n",
       "105                      NaN                                 718716   \n",
       "106                      NaN                                1813910   \n",
       "107                      NaN                                2796995   \n",
       "108                      NaN                                  91073   \n",
       "109                      NaN                                 490064   \n",
       "\n",
       "     Grand Total Revenue  \n",
       "0                8351402  \n",
       "1                 648089  \n",
       "2                5650269  \n",
       "3                5787853  \n",
       "4                7321177  \n",
       "..                   ...  \n",
       "105              3216033  \n",
       "106             10055044  \n",
       "107             11433144  \n",
       "108               144443  \n",
       "109              2523407  \n",
       "\n",
       "[110 rows x 6 columns]"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3.drop(df3.iloc[:, 1:163], axis = 1, inplace = True)\n",
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "0093f298",
   "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>Survey Year</th>\n",
       "      <th>Total Men's Team Revenue</th>\n",
       "      <th>Total Women's Team Revenue</th>\n",
       "      <th>Not Allocated by Gender/Sport Revenue</th>\n",
       "      <th>Grand Total Revenue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010</td>\n",
       "      <td>4177358</td>\n",
       "      <td>2516288</td>\n",
       "      <td>1657756</td>\n",
       "      <td>8351402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010</td>\n",
       "      <td>240901</td>\n",
       "      <td>263222</td>\n",
       "      <td>143966</td>\n",
       "      <td>648089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010</td>\n",
       "      <td>1944029</td>\n",
       "      <td>2878866</td>\n",
       "      <td>827374</td>\n",
       "      <td>5650269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010</td>\n",
       "      <td>2379968</td>\n",
       "      <td>1951906</td>\n",
       "      <td>1455979</td>\n",
       "      <td>5787853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010</td>\n",
       "      <td>2452503</td>\n",
       "      <td>2821229</td>\n",
       "      <td>2047445</td>\n",
       "      <td>7321177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>2020</td>\n",
       "      <td>1405675</td>\n",
       "      <td>1091642</td>\n",
       "      <td>718716</td>\n",
       "      <td>3216033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>2020</td>\n",
       "      <td>5770773</td>\n",
       "      <td>2470361</td>\n",
       "      <td>1813910</td>\n",
       "      <td>10055044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>2020</td>\n",
       "      <td>5520136</td>\n",
       "      <td>3116013</td>\n",
       "      <td>2796995</td>\n",
       "      <td>11433144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>2020</td>\n",
       "      <td>26710</td>\n",
       "      <td>26660</td>\n",
       "      <td>91073</td>\n",
       "      <td>144443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>2020</td>\n",
       "      <td>1392895</td>\n",
       "      <td>640448</td>\n",
       "      <td>490064</td>\n",
       "      <td>2523407</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>110 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Survey Year  Total Men's Team Revenue  Total Women's Team Revenue  \\\n",
       "0           2010                   4177358                     2516288   \n",
       "1           2010                    240901                      263222   \n",
       "2           2010                   1944029                     2878866   \n",
       "3           2010                   2379968                     1951906   \n",
       "4           2010                   2452503                     2821229   \n",
       "..           ...                       ...                         ...   \n",
       "105         2020                   1405675                     1091642   \n",
       "106         2020                   5770773                     2470361   \n",
       "107         2020                   5520136                     3116013   \n",
       "108         2020                     26710                       26660   \n",
       "109         2020                   1392895                      640448   \n",
       "\n",
       "     Not Allocated by Gender/Sport Revenue  Grand Total Revenue  \n",
       "0                                  1657756              8351402  \n",
       "1                                   143966               648089  \n",
       "2                                   827374              5650269  \n",
       "3                                  1455979              5787853  \n",
       "4                                  2047445              7321177  \n",
       "..                                     ...                  ...  \n",
       "105                                 718716              3216033  \n",
       "106                                1813910             10055044  \n",
       "107                                2796995             11433144  \n",
       "108                                  91073               144443  \n",
       "109                                 490064              2523407  \n",
       "\n",
       "[110 rows x 5 columns]"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3.drop(['Total Coed Team Revenue'], axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "713bebf1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "151400514\n",
      "320281147\n",
      "228590342\n"
     ]
    }
   ],
   "source": [
    "print(df3[\"Not Allocated by Gender/Sport Revenue\"].sum())\n",
    "print(df3[\"Total Men's Team Revenue\"].sum())\n",
    "print(df3[\"Total Women's Team Revenue\"].sum())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1fc1c888",
   "metadata": {},
   "source": [
    "# Data Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "c01e7910",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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OZHdOSqcsn6sv+i1PTX4XrrkYAcRbFYPbN4ztex9M5fk3p+D2uNm2Yzcrly9JGpzZiQibIbKqOJ3CzTUTmFi7lzZVe7qceMwQeeP5ST3dlWXRfTI67X8Nz5gxI/Hbb79NzM7OzgbYt2+fbcWKFTE9evSo7NSpU8Wxxx5bBjB48OB9eXl5BwxenpKS4omOjvaOHTu226hRowqrx2892NSpU5N79eqVkJeXF/PYY4/lxcXFmbqm0OrYsaO7S5cuFbNmzWqTk5NTvm7dupjTTz+9ZOLEiWl1TbkVGRlpxo4dWwgwdOjQ0pkzZybW92Op65zPOuusegfZV+pIaOFUqj67VvbBXR6L8dY5I0dNbeJiG14JWL9xC48+9xpzp79BclIiV9x6L+Xl9Y4LLyJg91a2uez807jgqjtinH+6Fvas7msTYOfyvjFUyu233Fh0/a137oiNtJdXT+e1cuXKqKioqP2DUtvtdlNWVnZAb1NkZCQLFy5c/vHHHye+/fbbyc8880z6nDlzVh0covoa58yZM9v87ne/633BBRcU1jeF1oUXXljw1ltvJWdlZZWfddZZBTabrd4ptyIiIozNZqv+mJrTd3k8vrHdvV4vVVVV1dN3ceutt2678847w2K8YhUatKtWqfpU7YsPtGgClJdXkrdpG2vWbwTg9f99wonH+O5XSohvQ3HJPgCKiktpExuLIzGeHbv28OlXPwQc6YSjh/CXm37PJeef8etCd3nc2ScPj33zrXdSFq/fnrN0a9Gg7xeu6L1o1fqOZVXeQ+7QPVhhYaEtPz/ffvHFFxc+++yzm5YvX17vNqeddlrp6NGj9zz88MPt6ptC69JLLy2YMWNG8nvvvZcybty4fDi8Kbe6detWOX/+/DiAN998M6m6oJ511llFr7/+emphYaENYP369ZHV+1WquegvmFJNKCYmilcev5cx196F2+PhqIHZXHfZhQD8Yfxozrr0Jjqkp/LV+88zuF8WOSdfSI+unTnuqIEBH0NEuOO6yw9ZPvLEEXy3ao/nsvNG2gB7XJv4xAf/81yizW7H2CLYsKe0myM2cq8x5pCZpffu3Ws/++yze1VPxPzAAw9saijHvffeu33YsGHZDzzwwLbqKbS8Xi+RkZFm0qRJGzMzMyvT0tI8vXv3Llu9enXsySefvA8OnHLr4PXrOtZNN9206+yzz+7Vv3//vr/5zW+KYmNjvQCjR48uWrp0acxRRx2VBRAXF+d9880313fq1Mkd6PdTqcbSacVUSAt4WjFjoKK4DWUFKVQUJeN1h93ciAbxLvFmiIFDCmNNNhFvXJS9KDE2cq8jNrIw0m7TImMhnVYs9GiLU4U3X7FMprwwGa+73u7AUOe1x1QYLw1eZPUaYyupcCeVVLiTtu4tIzbSXuKIi8xv2yZ6j90mh/2MqVKthRZOFX6qyqMo3ZVGeWEK3qqwLpY1VUiM53C2K6vyxJcVeuJ3FlV0ToyJyE+Jj94VHx2xr6nzKRUutHCq8FFeFE/pznZUFCdZHcUKJUTX20XbEK8xtr1lVal7y6pSYyLs+5LbRO1KaROVr61QpQ6khVOFOqF0Vwqlu9vhLm/w7tFwVuiJbrLWdbnbE7etsKzbjqLyLomxkXvatona1SY6oqyp9q9UKNPCqUKT05ECXBt55v86URj44yLhyojdXeaxNfkNT15jbHv3Vabt3VeZFh8dsbddYsxWLaCqtdPCqUKL09EJ+CtwBRAn5rAu64Udtz22Ak/zvp5LKtxJJbtKkuKjI/a2d8RsjYvSAqpaJx0AQYUGpyMZp+NhYDVwAxAU3bK33fso/37hzf2fnzHuBq6+4/79n//pvsd5/Lk3mj1HmcQccB3ynttuYO7s7wPa9qN3/8tJA3tx0RkncN5Jw3n9hafrXb+kwp20ZmdJ9vrdpT32VbpjDj+1UqFJW5wquDkdMcAtwAQgqaHV+39x6MAAR8J1+mv1fv3YYQN5b9pMbr1mPF6vl935eykqLt3/9R/nLeLf993RpJlqU+yNPqLX8shzLuCvDzzC3oJ8zjvxKE4fdS7tO9Y7QQrF5VXJxeVVyQkxkQXtE6O3xkZFlB9JBqVChbY4VfByOi4CVgATCaBoWuG4owbx47xFACxduZZ+fXqREN+Ggr1FVFRUsnzNegb3y2LWdz8xeOQl9D/1Iq683UlFhW+QnIyjR/HXh55gxDm5DDtrPL+4lnPGuBvoeey5PPva+/uP88gzkznqt5cy4LSLuPfRZwDI27SVvieO5uo7/86JJ/wm9tpxoykv8/WexicmEhnpu+T574ecXHDKMVx4+nE89vd76j2fpOQUumT0YNcO35Si06a8w7izT+WiM07g/gm34vF4ePe1l/jXP/62f5s3XpucfNW1N+Rsyt/X5cmnn26r04WpcKeFUwUfp2MITse3wDtAN6vj1Kdj+zQiIuxs3LKNH+ctYsTQARw9uB+z5y9m3uJlDOjbG6/XyxW3OXnnmYm4Zr2L2+3hmdfe27+PLh3bM3vqZE4YPpgrbruX959/hDlTJ/M3f4H8/JvZrF6/kZ+nv87Cz99m/uLlfDvHN7/26vWbuP6KcZVTvpxDosPBzE8/BuCu+yYyaNjRFBYU8OWM6UyZNZv3v/iBa26uv/W7bcsmKivKyeybw7rVK/ls6gdM/mAG7372HXabnU8+eI/TRp3HrE+n7d/ms6lTGHnOBcxf5Ep/f8rH3b74dvZ2nS5MhTPtqlXBw+mIB/4JXEsIvanztToX8+O8xdz+h0vZsn0nP85bhCMxnmOHDWTl2g1079qRzJ6+9wC5Y87mqcnvcus14wE4d+SJAPTv24uSfWUkxLchIb4NMdHR7C0s5vNv5vD5N3MYPPISAEr27WP1+k107dSB7l06kjNwSOWqSqL69h/I1k0HDjHbJiGB6OhonHfezAmnjuTEU8+gNp9P/YC5s79nw9rV/O3h/xAdE8NPP3zD8sWLGH/2KQCUl5eTkppGSttUOnXNYPEvc+navSd569Yw+KhjeHvyCyxzLZKTjh/RA2O85WWlbp0uTIUjLZwqODgdvwFeAXpYHaWxjh02gB/nLcK1Yg39snrSpWM7HnvudRIT4rny4nNpaDzo6Ghfl6pNbERH/fpEic0muD1ujDH85cbfc61/sPhqeZu2Eh0dxT58U2vabXYqPAdeZoyIiODNqbP46YdvmPHxFN5+9QVefOfjQzJUX+NcNP9nbsy9mONPPg1j4JwxY7llwr2HrH/GuRfw2dQP6d6rN6eccTYicvD6NhGJTG0TZbzGiE4XpsJJyLyrV2HK6YjB6Xgc+IoQLJoAxw0bxLSZ35GSlIjdbicl2cHeomJmz1/MiGEDyOqVUedUY4E446QRvPzOx5SU+kbB27JtJzt35+//epEnus7nN/eVllBcXMQJp4zkz/c+xMqlrnqPNXDocM7+3cW8+fKzHH3cb5g5/WP27N4FQGFBAVs3+87htDPP4avPp/PpR//jjHMuADhk/b35+bJoxeqOq7YXZ4PUOqqRThemQpH+IirrOB3DgclAltVRjkT/vr3Ynb+Xceef+euyrN6UlJaRmuK776WuqcYCMfLEESxfvZ4R514BQHxcLG888QB2ux0MFHsiouvatrSkhFuuGk9lRTnGGO6898EGj/f7629h7G9P4uobb+ePd/4f148fjdfrJSIykr8+8AgdO3clMSmJHr37sG71SvoP9r0J6JmZVdf6MYiwpaCsU8ekmAMmr9bpwlQo0mnFVMtzOqKAe4G7gCMa9Wf5Ge/St1t6k8QKRW57XNmyqnYNzogSLGIj7aVd28ati46w1zn3Zmuj04qFHu2qVS3L6egP/Ixv9J9WP1TekaqwxYRUC6ysytNmzY6S7IJ9lUlWZ1HqcGnhVC3H6bgQmA0MtDpKuCgx0SH3GvYYY9+Uv6/npvx9XbzGHNGMLkpZQa9xqubndAjgBO4B9A9lEyp0R9V5fTPYFeyrTC+r9MR3bRu3LibSXmF1HqUCFXLvVlWIcTraAP8D/kazFE3T4OMe4crYIqrKvbaQfvNb7vbErdlZkr13X6XD6ixW8Hq9Auh8pyFGC6dqPk5HBvAjcEFzHSKmcB17St2tsnhW2WLD4gYbrzG2Tfn7eu0qrki1OktL8nq9smvXLgewxOosqnH0rlrVPJyOE4H3gWb9Y1gVlcTmIXdR7uhBa+sF3meLr8j3xIZsV21t4iKlMD7KttfqHC3ECyxxu91XDx06dKfVYVTgtHCqpud0XAdMApp8YmX1q99X3rnoK+/gcLzR6g3gyryJo6qsDqJUbbSrVjUtp8MJPIMWzWZlDO453uzeVudoJpcCMzImTG+V1z1V8NPCqZqO0/F3fAMbqGZWRvTaMqKDYjLvZnIK8H3GhOn1TwraCCKSISJLDlrmFJHmnzC17kwdReT9Gp+/JSKLReQ2EblfRE5rxL4OOT//cpuITBKRJSLiEpG5ItK9ifKfLyLZjVj/JBEpFJEFIrJCRB5tihwtTQunahpOx0TgbqtjtBYrTJcdVmdoAf2AORkTpodryxpjzFZjzIUAItIeONYYM8AY8y9jzN+MMTOb4DAXAx2BAcaY/vhu1tt7pDsVkQjgfCDgwun3nTFmMDAYOFtEjjvSLC1NC6c6ck7HY/iGz1Mt5GvPoNby2u0EzMqYML3Z52UVka9F5GER+VlEVonICf7lOf5lC/2twd7+1t0KEZnsX/a+iMT51x8qIt+IyHwR+UxEOviX9xKRmSKySER+EZGeB7USPwfS/cc5QUReFZELG9jnUP/+ZgN/rOPUOgDbjDFeAGPMZmNMgX/7EhF5zJ9nloik+ZcPEpE5/nP7QESSa3yPHhSRb/C95s8FHvFn7ikiN4vIMv92b9f3/TbGlAEL8f2MEZGRIjLbn+U9EYkXkbNE5N0aP6OTRGRqXev7l+eJyH3+5S4RyfIvP6B3wd8Cz/B/fGmNn/FzIlLvqGat5cWnmovT8R/gdqtjtDZfeId2sDpDC+qCr3h2bIFjRRhjhgO38utlh+uA/xhjBgHDgM3+5X2A540xA4Ai4AYRiQSeAC40xgwFXgb+4V//TeApY8xA4Fhg20HHPhdYa4wZZIz5rnphA/t8BbjZGDOinnN6FzjHXxQeE5HBNb7WBvjFGDME+KbGOb8G3OU/NxcHXoJJMsacaIz5B/AxcKc/81pgAjDYv9119WTCX4x7A9+KSCq+HqvT/Fnm4fu78gVwjIi08W92MfBOPetX2+1f/gxQb1e8iPT17/c4/8/YA4yvbxstnOrwOB2C0/E0cLPVUVobYyhcbrqG5BRsR6AnvuJ5JCP61/UIQc3lU/z/zwcy/B/PBv4qIncB3fwtJYBNxpgf/B+/ARyPr5j2A74QkYX4/rh3FpEEoJMx5gMAY0y5MWZfgLnr2qcDXxH7xr/e67WenDGb/fv4C75HYGaJyKn+L3uBd2qeQy37nQz8psYu36Fui4E3ReRSoK5xlE8QkcXAdmCaMWY7cAy+Lt8f/OeYi+977QZm4Cv8EcAo4KO61q9xjNp+jnU5FRgKzPXv61QamOIwpEcdUZZ6FviD1SFao9041oIMsTqHBbKALzImTD8pb+KogsPYfg+QfNCyFGB9jc+rh/7z4P/7aIz5r4j8hO+P9mcicjWwjkMLscH3MPHSg1uAIpJ4GHn3b17HPpNqyVArY0wF8CnwqYjswHdtclZtqwawu9J6vjYKX5E9F7hHRHL8xa+m74wxZ4tIJvC9iHyA7xy/MMZcUss+38HXDZ0PzDXGFItIfetDLT9HfIW8ZmMxxv+/AJONMX+p57wOoC1O1XhOx31o0bTML97eRVZnsNAA4LOMCdMbXYiMMSXAturWloikAGcC39e3nYj0ANYZYybh65oc4P9SVxGpLmaX+PezEkirXi4ikf7iUQRsFpHz/cujq6+JBqCufe4FCkXkeP96tXYvisgQEeno/9jmz7/B/2UbUD057Djge2NMIVAg/mu8wGX4unFrUwwk1Nh3F2PMV8CfgSQgvq6TMsasAh7Cd610DnCciPTy7yvOX1gBvgaGANfwa2u3vvXrkuffDyIyBKi+s3gWcKGIpPu/liIi9V5T18KpGsfpGI9v3FllkS+8Q8P5MZRAHAVMz5gw/XC+D5cDd/u75L4E7vNfm6vPxcAS/zZZ+K7/ASwHcv3djinAM8aYSnyF6GERWYTv5pdj/etfBtzsX/9HoH0ggRvY5++Bp/w3B5XVvgfSganiuwlpMb6W15P+r5UCOSIyH98jQPf7l+fiu+lnMTCoxvKDvQ3cKSIL8F2vfENEXMAC4F/+4l6fZ/G1UOOBK4C3/Mecg3+Ce2OMB5gGnOX/H2PMrrrWr8f/gBT/z/F6YJV/X8vwdX9/7t/XF/huqKqTjhykAud0HA/MBMJqmLdQM7T8md17cLSqcV3rMBU4P2/iqBYfJN1/N+Y0Y0y/lj52UxKREmNMna1CVTttcarAOB09gQ/RommpKmPfpEVzv3OAB60OoVofLZyqYU5HMjAdaGt1lNZug0nfZHWGIHNXxoTpl7f0QY0xeaHe2gTQ1ubh0cKp6ud0ROK7NtDH6igKfvD214HPD/V8xoTpx1gdQrUeWjhVQ54FTrY6hPL53DtMW/2Higb+lzFhejurg6jWQQunqpvTcQNwpdUxlI8xVM719gnbcVuPUEfgnYwJ0/XZdNXstHCq2jkdfYGQnLkgXJUSs6aSSL05q24nAg9bHUKFPy2c6lBORxTwXyDW6ijqV8tMt91WZwgBt2dMmH6e1SFUeNPCqWrzD3wPPasgMsszpN4ZG9R+z2VMmK7XglWz0cKpDuR0nAL8yeoY6lAzvUOabFLnMNcOeNrqECp8aeFUv/I9rzkZ36DHKoh4jeSvNZ2afU7KMHJRxoTpF1kdQoUnLZyqpucAbdUEoZ0krbM6Qwh6Wh9RUc1BC6fycTquAMZYHUPVbp63T31TOanatcX3HLJSTUoLpwKnIx34t9UxVN0+8wxrY3WGEHV+xoTpl1odQoUXLZwKfANlO6wOoWpnDOZb74BeVucIYU9kTJje0eoQKnxo4WztnI6h+Ob0U0Gqioi8QuKTrM4RwpKAR6wOocKHFk41Cf09CGrrTfutVmcIA5dkTJh+lNUhVHjQP5itmdMxnl9nkldB6lvvAI/VGcKAAI9ZHUKFBy2crZXT0QYd1zMkfO4ZlmZ1hjBxQsaE6RdYHUKFPi2crddfgU5Wh1D1M4byBaaX3hjUdB7OmDA90uoQKrRp4WyNnI7uwO1Wx1ANKyJutZsI/UPfdHoDN1gdQoU2LZyt08NAjNUhVMOWeLvnW50hDP0tY8L0ZKtDqNClhbO1cTqygAutjqECM8s7JMrqDGEoBbjb6hAqdGnhbH3+jA7iHjJmeod0sTpDmLohY8L0dKtDqNCkhbM1cTo6AeOtjqEC4zGya6Npp4PuN48Y4I9Wh1ChSQtn63I7oF1/IWI7KeutzhDmbsiYMD3W6hAq9ERYHUC1EN9cm3+wOoYK3E/evvta4jjuol3snv44npICRGzEDzqDxGHnUbriewq//y9VezbR/vLHie7Qu9btveUl7Pl0EpW7NwKQ+ttbiO7Ul4KvX6Fs3Xyi0ruTerZvbvSSJV/iLS8mcdh5LXFqDUkFctEZVFQj1dviFJG2IrLQ/2+7iGyp8XnUQeveKiJxDR1QRL4WkWF1LN8oIlJj2YciUtKYEzpon6+KyEkBrnuFiOzyn9sKEbntcI8bpP4IxFsdQgXuc8+wlhl432Yn+eSr6HTNs7S/7FGKf5lO5e6NRKV2I+2CvxLdJafezfNnPU9Mj6F0uuZZOl75BJFtu+CtKKViy3I6Xvkkxnip3JWHt6qC0iUzSRg8qkVOK0C3ZUyYrj1vqlHq/YUxxuwxxgwyxgzC967sX9WfG2MqD1r9VqDBwtmAvcBxACKSBHQ4wv011jv+cz0O+D8RCY8bM5yOWOBmq2OowBmD9ztv/xYZ+CAiPoXo9r5D2aLjiGzbBU/xHiJTuxDZtv5LrN6KfZRvWkr8gJEAiD0SW0w8IBiPG2MMxl2J2OwU/TyFhKHnIvag6ujKBM6xOoQKLY1+pyUip4rIAhFxicjLIhItIjcDHYGvROQr/3rPiMg8EVkqIvcFuPu3gbH+j0cDUw469p0iMldEFlfvU0QyRGS5iLzgP9bnIlJ93aIQqPSvN1FElvm3fbS+EMaYPcAa/IVbRC4VkZ/9rdHnRMQuIteLyD9rZLtCRJ6oa33/8hIR+YeILBKROSLSzr/8VRG5sMa+Smp8fMg5H4YrAR22LYRUELmulNiElj6uu3AHlTvWEd2xT2Dr792OPS6RPZ/8m62v3MyeTyfhrSzHFh1HXJ9j2fbqzUQ42iHRbajctoq43sc08xkcljusDqBCS2MLZwzwKnCxMaY/vmuk1xtjJgFbgZONMSf71/0/Y8wwYABwoogMCGD/s4Df+AvNWOCd6i+IyEh8o34MBwYBQ0XkN/4v9waeMsbk4Gu1/g7AGHOLMeZHEUkBLgByjDEDgAfqCyEiXf3nulhE+gIXA8f5W6MefHemvo+vuFe7GHinnvUB2gBzjDEDgW+BaxrIUd85B8bpECDcup3D3hrTaVtLH9NbWcauDx4k5dRrsEUH1nlkvB4qt68lYfBv6fj7SUhkNEVz3gPAcfSFdPz9E6SccjWF371B0gmXUrzoM3Z9OJG9P77dnKfSWMdnTJg+3OoQKnQ0tnDagfXGmFX+zycDdf0hv0hEfgEWADlAdgD79wDf4ys8scaYvBpfG+n/twD4BcjCV1TwZ1ro/3g+kHHQfouAcuBFERkN1HXTxcUishRYB/zHGFMOnAoMBeaKyEL/5z2MMbuAdSJyjIi0BfoAP9S1vn//lcC0enIerL5zDtSJQM9GbqMs9o03kPeZTcd43Oz64EHaZJ9EXJ/AJ8yJSEjFnpC6v4Ua1+c4KnesPWCd6s8jkjtRuuRL0s6fQNWuDVTlb2m6Ezhyt1gdQIWOxl5sKA1kJRHpjq/74yhjTIGIvErgQ7y9DXwAOA/eLfCQMea5g46VAVTUWOQBDrjF3BjjFpHh+IrYWOBG4JRajv2OMeZGERkBTBeRT/3HnWyM+Utt6wMXASuAD4wxxn9zU13rVxljTI2c1d9/N/43Mf7tq2+8qvWcG0knqQ5BX3iGtdjD+cYY9nz6HyLbdiFxeOMmD7HHJxORmErVns1Etu1M+YZFRKZ2PWCdvd+9QcoZN4LXDcbrWyg2jLuilj1a5vyMCdPj8yaOOuybEVXrcThdtRkiUn3TwmXAN/6Pi4HqazKJ+Ipsof863lmNOMZ3wEPAWwct/wy4UkTiAUSkk4gE9MfFv43DGPMJvpuYBtW3vjFmNvA6vnehs4ALq48lIiki0s2/6hTgfOASfu1Wrm/9uuTha6UCnAdUD+p92OcMgNORgA6vF3KMoXSx6dFiM6JUbFlG6dKvKN+4mK2v3MTWV26ibO1c9q36kc1P5VKxdQU737+PHe/cA4C7eA873rt3//Ypp13H7mmPsvXlG6ncuZ7EERft/9q+VbOJat+biIS22GLiie6YxdaX/ggCUek9DslioTh8r2WlGtTYFmc5vhbMeyISAczl12egngc+FZFtxpiTRWQBUN3t+UOgB/C3yA65eccY87n/+uFs/xMrJcCl+FpuDUkAPhKRGHytuECu+T2Mr3v0QXzjWn4uIjagCt+jHRv8rellQLYx5md/zmUiUuv69RzrBX++n/EV3tIGznlnAPnB1xo+0judVQvbS/xqL7ZBLXW8mM45dLtrWq1fi8s8tNs2IqEt7cb8ep9aVLsedMj9dx3bjyAuc8T+z5NPuYpkrjqywM1nHPCG1SFU8JNfew5V2HE6vgJOsjqGapyvPAO//n3VXSdZnaMVcgMd8yaO2mV1EBXc9MHfcOV0dKDuG7dUEJvlHaJTvlkjAl8vjVL10sIZvi5Cf74h6UvP4Iauiavmo5MgqAbpH9bwNbbhVVSw8Rjb9q2ktvSIWepXIzImTO9udQgV3LRwhiOnoysQlEO0qPptNql5VmdQjLM6gApuWjjD0xlWB1CHZ7Y3u9zqDIqgmLpFBS8tnOHpVKsDqMPzuXdYstUZFEMzJkxPsjqECl5aOMONb2za2kZFUkHOGDxzvNktNvCBqpMNfYxL1UMLZ/jpj86EEpLKiFq7j5g2VudQgL75VPXQwhl+tJs2RK00XbZbnUHtp68jVSctnOHHshe8x2sY/FwJZ//XN/mM8+tyOj1ezKBnSxj0bAmfrK46ZJuVuz37vz7o2RISHyri33N8g3/f9UU5A54p4fIPyvav//qiSv4zJ6gGB28yX3sG6esxeGRnTJiujwWpWgXVVOzqCDkdEVg4WtB/fqqkb6qNohp17bZjorjj2Og6t+mTamfhdfGAr/B2eryEC7IiKSw3/LjZw+Lr4xk/ZR+uHR56pdh4dVEVM8aH5/C7X3iH6h/q4HIK8KbVIVTw0Xe44WU4v85Q06I2F3mZvtrN1UOiGl65DrPWe+iZYqNbkg2bQKXHYIyhrAoi7fDIj5XcPDyKSLs0YfLgYAxFy01XffA+uOh1TlUrLZzhxbJu2ltnlPPP02KwHVTTnvy5kgHPlHDlR2UUlNU/ocDbS6q4pJ9vRrWEaOF3fSMZ/Fwp3ZNsOKKFuVs9nJcVWe8+QtUeEtcabPp6DC56nVPVSl+o4eXQOaBawLRVVaS3EYZ2tB+w/PphUay9OZ6F17WhQ7zwp8/rfra/0mP4eKWbMdm/Xj3483HRLLwunsfOiOGeryq4/6RoXvylkove28cD34bXdc5fvL0Lrc6gDtEtY8L0FptQXIUOLZzhJceKg/6w0cPHK91k/LuYse+X8eV6N5dOKaNdvA27TbCJcM3QKH7eUvfUqZ+udjOkg4128Yf+Si7Y5tsus62N1xZV8e6YOJbs9LB6TyBTsYaGL7xDw/PCbejrZ3UAFXz05qBw4XQkAl2sOPRDp8Xw0Gm+mbC+znPz6I+VvDE6lm3FXjok+ArhB8ur6Jde9/u0t2p00x7snq8qeP6cGKq84PH39toE9h16k27I+sozSK9vBqd+wJdWh1DBRQtn+Mi2OsDB/jyzgoXbPQiQkWTjubN9xXVrsZerPy7nE//dsfuqDF+s8/Dc2bGH7OPDFVUc1dFOR38BHtHZTv9nShjQzsbA9vZD1g9FVca+eTdJna3OoWqlLU51CDGm/hs2lI+ItAMeBDoaY84SkWxghDHmJYuj+TgdVwEvWh1DNd5ab4fZp1Y+NsLqHKpWc/ImjtKfjTqAXuMM3KvAZ0BH/+ergFutClMLS65vqiP3g7dfpdUZVJ30daUOoYUzcKnGmHcBL4Axxg0E090p+gIPUZ97h6VYnUHVKSFjwvRuVodQwUULZ+BKRaQtYABE5BggmB4h0MIZgoyhaq63T2+rc6h66XVOdQAtnIG7HfgY6CkiPwCvATdZG8nP6XAAnayOoRqvlJjVFUTFWJ1D1UsLpzqA3lUbIGPMLyJyItAHEGClMSZYHojoa3UAdXiWm267rc6gGqSPCqkDaOEMkIhcftCiISKCMeY1SwIdSFubIWqWZ3B4PFMT3nT0IHUALZyBO6rGxzH4xrH8BV+XrdVSrQ6gDs8s7xB90xP8tHCqA2jhDJAx5oDrmSLiAF63KM7B2lodQDWe11Cw2nTOsDqHapAWTnUAvTno8O0DguVuSG1xhqBdJK21OoMKiBZOdQAtnAESkaki8rH/3zRgJfCR1bn8tMUZguZ5+5RanUEFxJExYfrhTzSrwo521Qbu0Rofu4ENxpjNVoU5iLY4Q9DnnmFtrM6gApYOBMvrXVlMC2eAjDHfWJ2hHlo4Q9A33gE9rc6gAqaFU+2nXbUBEpHRIrJaRApFpEhEikWkyOpcftpVG2IqTUTeXhKSrc6hAqbXOdV+WjgD90/gXGOMwxiTaIxJMMYkWh3KT1ucIWa9ab/F6gyqUfRNjtpPC2fgdhhjllsdog7BUsBVgL7z9g+mCQJUw/SyltpPfxkCN09E3gE+BCqqFxpjpliWSIWszz3DtJcgtOjfSrWf/jIELhHfs5sjaywzQDAUTg/6swwZxlD+i+kdLM8Aq8Do0IhqP/1jGyBjzO+tzlAPLZwhZI/ErPJElLQTq4OoRrAZqxOo4KF/bAMkIpnAM0A7Y0w/ERmA72ahByyOBsE1obZqwHUdk4rioycOsDqHapQIuMTqDCpI6M1BgXsB+AtQBWCMWQyMtTTRr7RwhoiVkZHrVkZFjrA6h2o0r9UBVPDQwhm4OGPMzwctc1uS5FDBkkM14PZ2qTsQ0etloUffnKr9tHAGbreI9MR3QxAiciGwzdpI++mLOgQsio5auTEi4hirc6jDEiyT1qsgoNc4A/dH4HkgS0S2AOuB8dZG2k8LZwi4PT21CBG9Jyg07bU6gAoeWjgDt8EYc5qItAFsxphiqwPVoF21Qe6H2BjXzoiIoxpeUwWpvVYHUMFDu2oDt15EngeOAUqsDnOQYMujDjIhra32CoS2AqsDqOChhTNwfYCZ+Lps14vIkyJyvMWZqgXLtVZVi8/axP2y124fZHUOdUT2Wh1ABQ8tnAEyxpQZY941xowGBuMbSShYphrbanUAVbd7U1NirM6gjpi2ONV+WjgbQUROFJGngV+AGOAiiyNV08IZpN5PaPNzqc2WbXUOdUSqXLmuUqtDqOChNwcFSETWAwuBd4E7jTHB9ELSKaqCkBe8E1OSdTqq0LfH6gAquGjhDNxAY0ywTFx9MG1xBqHJjoTZFTbbcVbnUEcsz+oAKrhoV23g2ovILBFZAiAiA0TkbqtD+WnhDDJucE9KTupsdQ7VJNZbHUAFFy2cgQvmsWq1cAaZp5Mds90i3azOoZqEFk51AC2cgQvmsWq1cAaRSqh42ZHY0+ocqslo4VQH0MIZuOAdq9ZZWI7ewBA0Hmmb/JNHpKPVOVST0cKpDqA3BwUumMeqBVgOBMuADK3WPpHSdxLi+1qdQzUpLZzqANriDJAxZp0x5jQgDcgCTiK4CtUvVgdQ8PfUlLlGJM3qHKrJVAAbrQ6hgosWzgaISKKI/MU/xN7pwD4gF1hD8AyAALDA6gCtXaFNCqe1iRtsdQ7VpFyuXFew3MuggoR21TbsdXzDbc0GrgH+DEQB5xtjFlqY62Da4rTY3altFyByktU5VJPS15U6hBbOhvUwxvQHEJEXgd1A1yCbVgxgGVCObyhA1cJ22227vo6L1WnDwo8WTnUI7apt2P6Z340xHmB9EBZNcBa6AZfVMVqrP6elLsc3V6sKL1o41SG0xdmwgSJSPdSeALH+zwUwxphE66IdYgGgrZ4WtiXCvnVuTPTRVudQTc4NLLY6hAo+WjgbYIyxW52hEfTdsQX+lJ66Fn1uMxwtc+W6KqwOoYKPdtWGFy2cLWxdZMSGpVFRI6zOoZrFbKsDqOCkhTO8LMZ3g5BqIbelp21GRHtuwtMsqwOo4KSFM5w4CyuAr62O0VosjYpavS4yQlub4ckAX1kdQgUnLZzh5xOrA7QWt6enFiCir6HwtMiV69ptdQgVnPRFH360cLaAn2Oil26NjBhudQ7VbLSbVtVJC2e4cRauBVZZHSPc/TktVa8lhzctnKpOWjjDk7Y6m9GXcbEL90TYh1qdQzWbKuBbq0Oo4KWFMzxp4WxGd6e2DaVne1XjzXTlukqtDqGClxbO8PQNoC/8ZvBxfNzcYrutv9U5VLN63+oAKrhp4QxHzsJK9BpNkzNgHmibkmB1DtWs3MCHVodQwU0LZ/iabnWAcPPfxPg5ZTZbltU5VLOa5cp15VsdQgU3LZzh639ApdUhwoUHPI+nJLezOodqdu9ZHUAFPy2c4cpZuAdtdTaZF5ISZ1eK9LA6h2pW2k2rAqKFM7xNtjpAOKiEymeTHBlW51DNbqYr17XH6hAq+GnhDG+fALusDhHq/pOSNMcj0tnqHKrZPW91ABUatHCGM2dhFfCG1TFCWblI2RuJCX2szqGa3RZgqtUhVGjQwhn+nrM6QCh7qG3yT14RvSko/L3kynW5rQ6hQoMWznDnLFyJTo90WIpFij6IbzPA6hyq2XmAF60OoUKHFs7W4VmrA4Sie9Pa/mJEUqzOoZrdJ65c1yarQ6jQoYWzdfgA2GF1iFBSYLPlfxEXqwO5tw76xlI1ihbO1sB3k9Akq2OEkglpbV2I6PB64W8p8KnVIVRo0cLZejwB6DNqAdhht+/4MTZGJ6luHR5y5bqM1SFUaNHC2Vo4C4uBx62OEQruSE9diUis1TlUs1sLvG11CBV6tHC2Lk8AOoB1PTZERGxaGB01wuocqkU87Mp1eawOoUKPFs7WRFudDbo9PXUDIpFW51DNbjM6JKU6TFo4W59JaKuzVisjI9etiorU1mbr8Kgr16WzB6nDooWztdFWZ51ua5e6ExG71TlUs9uCjkurjkCE1QGUJSYBtwP6cL/fwuioFZsiIo62OkdjeSu9rH9oPcZtMB5D4lGJtLugHdvf3k7RwiIkQohKj6LzVZ2xtzn0PYGn1MOWV7ZQvrkcEaHTVZ2I6xXH9ne3U7y4mNiusXT+g298+4IfCvCUekgdmdrSp9nU7nHlusqsDqFClxijd2K3Sk7HX4F/WB0jWJzapePcnRERR1mdo7GMMXgrvNhj7Bi3Yd2D6+gwrgOecg/xfeMRu7D93e0AtL+o/SHbb35hM3GZcaScmILX7cVUGBDY8O8N9PhrDzY9u4m0UWlEtYtiw782kPGnDCRCWvo0m5ILGOTKdXmtDqJCl3bVtl6P47sdv9X7PjZmcSgWTQARwR7ja0kaj6/ViUBCvwTE7itwcT3jqMqvOmRbT5mH0pWlJP8mGQBbhM3XKhV8LVhjMFUGsQu7P91N29PbhnrRBLhDi6Y6Ulo4WytnYTnwR6tjBIMJaW1D+g+p8RrW3LOGFTevID4nnriecQd8veDbAhIGHDoIUuXOSiISItjy4hbW/G0NW17e4mu9xtpJHJbI2r+tJTI1ElucjbJ1ZSQOSWypU2ouU125rs+tDqFCnxbO1sxZ+BnwntUxrDSjTdz8Qrt9kNU5joTYhF5/70Wfx/tQtq6M8s3l+7+28+OdYAfHCMehG3qhbEMZKaek0Ov+Xtiibeya5pv3PO23afT6ey86XNKBnVN2kj46nfxv8tn41EbfPkNPJfAnq0Oo8KCFU90KFFsdwirO1JSwGSHI3sZOm6w2lLhKACj4voDiRcV0ubYLIod2sUYkRxCZHLm/hZo4LJGyDQfeM1P9eXT7aPb+sJeuf+xKxeYKKrZXNPPZNLnHXLmu1VaHUOFBC2dr5yzcCtxjdQwrvJfQ5qdSmy3b6hxHwl3kxlPqG/zGW+mlZFkJUR2iKF5czO5PdtPtlm7Yomt/mUcmRRLZNpKKbb4iWLKshJiOMQess3PKTtIvSMe4DVR3aNt8xwohK4H7rQ6hwoc+jqIAngQuB4ZYHaSleMH7cEpyyD+O4y50s/mFzRivAQOO4Q4SByWy6s+r8Lq95D2SB0Bsz1g6XdGJqoIqtryyhYzbMwDoML4Dm57bhHEbotKi6Hx15/37LppfRGz3WCKTfQMpxfaKZfXdq4npHENs15BpqHuBq1y5rvIG11QqQPo4ivJxOo4C5tBKeiFediT8+K+U5GOtzqGa3ZOuXNdNVodQ4aVV/JFUAXAWzqWVTOjrBvcTyUmdrM6hmt0G4C9Wh1DhRwunqmkCEPY3UDyd7JjtFulmdQ7V7K5x5frvlFKqCWnhVL/yjWN7ERByt0wGqhIqXnIk9rI6h2p2T7tyXV9YHUKFJy2c6kDOwoX4xrENS4+0TZ7jFelgdQ7VrBYQxr/Dynp6c5CqndPxLjDG6hhNqVSkZES3zmVGJM3qLKrZFANDXLmuNVYHUeFLW5yqLlcTZmPZ/j01ZZ4WzbD3By2aqrlp4VS1cxYWEUbXOwttUji9Tdxgq3OoZvW8K9f1ttUhVPjTwqnq5iz8BbjD6hhN4f/S2i5EpJYBW1WYWATcYnUI1TroNU7VMKfjPeBCq2Mcrl12265TunSKQ6SN1VlUs9gOHO3KdW20OohqHbTFqQJxBfCz1SEO111pqcu0aIatMuBcLZqqJWnhVA1zFpYCowjBwRG2RNi3zo2JPsbqHKpZGOAyV65rrtVBVOuihVMFxlm4GzgDX7dYyLg9PXUtItFW51DN4q+uXNf/rA6hWh8tnCpwzsL1wFmEyPyd6yIjNiyLihphdQ7VLF525bomWh1CtU5aOFXj+EYWGg1UWpykQbemp21BRKfOCz8fAtdaHUK1Xlo4VeM5C2fiu2EoaG/JXhIVtXp9ZIS2NsPPp8DFrlyX2+ogqvXSwqkOj7PwLeBPVseoy+3pqfmIiNU5VJOaBYx25bqCvrdDhTctnOrwOQv/BfzV6hgH+zkmeum2yIijrc6hmtR3+B47Kbc6iFJaONWRcRY+BFwPeK2OUu3O9NSwGCZQ7fcTMMqV69pndRClQAunagrOwmeB8UCV1VG+jItdmG+3D7E6h2oyXwEjXbmukLiTW7UOWjhV03AWvg2cj28kF8vcndrWbuXxVZN6HzjLlesqsjqIUjVp4VRNx1n4Cb5BEgqtOPxH8W3mFttt/a04tmpyz+C7e1a73VXQ0UHeVdNzOgYDM4D0ljqkATO8W+dV5TZbn5Y6pmo2Tleu6z6rQyhVF21xqqbnLFwAnADktdQh30yMn6NFM+S5geu1aKpgp4VTNQ9n4SpgKL6WZ7PygOfxlOT2zX0c1ax2Aae7cl3PWh1EqYZo4VTNx1mYj29WFSfN+LjKC0mJs6tEujfX/lWzmw8MdeW6vrY4h1IB0WucqmU4HWcBbwApTbnbSqgcntFlp0ekc1PuV7WY14BrdWADFUq0cKqW43RkAP8Dmuw5y0dSkr59zZH4m6ban2oxbuB2V67rCauDKNVY2lWrWo6zMA84FnipKXZXLlL2RmKC3hAUelYDx2vRVKFKC6dqWc7CCpyFVwNXAaVHsqsH2yb/7BVp1zTBVAt5DhjsynX9ZHUQpQ6XdtUq6/i6bp/FN2hCoxSLFB3XrbPHiCQ3eS7VHHYAV7tyXdOsDqLUkdIWp7KOszAPZ+GZwOXAnsZsem9a2wVaNEPGR0B/LZoqXGiLUwUHpyMN+A9wSUOr5ttse07s2ikKkYTmD6aOwHbgNleu622rgyjVlLRwquDidPwW3zilXeta5dp2ad/8GBd7YsuFUo3kBZ4HJrhyXZaMW6xUc9LCqYKP0xEPPATcwEGXE7bb7dtP79LRgUisJdlUQ+YAN7pyXfOtDqJUc9HCqYKX0zEQeJgaNw9d2qHdt4tiovW5zeCzFbgbeNWV69I/KiqsaeFUwc/pOAX454aIiPSzO3doj0ik1ZHUfnuAicBTrlyXpXOxKtVStHCq0OB0yI3t0s75Ji52ItDX6jiKIuBx4HFXrqvY6jBKtSQtnCqk9J/c3waMBf4G6KhBLW8f8BTwsCvX1ahHiABE5F/ABmPMv/2ffwZsMsZc7f/8MWCLMebxposcUK5XgVeNMV8HsO4VwCPAFiAGeM4Y86/mzKeCiz7HqUKKK9fldeW6/gtkA+cBX1ubqNXYCvwV6OLKdf35cIqm34/4hl1ERGxAKpBT4+vHAj8cSdAW8o4xZhBwHPB/ItLF4jyqBWnhVCHJX0A/duW6TsY3aPxrQKXFscLRL8BlQIYr1/WQK9eVf4T7+wF/4cRXMJcAxSKSLCLR+LrhF4jIqSKyQERcIvKy/2uISJ6IPCgis0VknogMEZHPRGStiFxXfRARuVNE5orIYhG5z78sQ0SWi8gLIrJURD6XX+/OLsT/+yMiE0VkmX/bR+s7GWPMHmAN0MG/7aUi8rOILBSR50TELiLXi8g/a2S7QkSeqGt9//ISEfmHiCwSkTniH1pSRF4VkQtr7KukvnNWzUMLpwp5rlzXAleuKxfIAP6B78F7dfiqgA+Ak1y5rqGuXNcbrlxXVVPs2BizFXCLSFd8BXQ28BMwAhgGLMb3d+lV4GJjTH8gAri+xm42GWNGAN/517sQOAa4H0BERgK9geHAIGCoiFTfid0beMoYkwPsBX7nz3WLMeZHEUkBLgByjDEDgAfqOx//ecQAi0WkL3AxcJy/NeoBxgPvA6NrbHYx8E496wO0AeYYYwYC3wLXNJCjvnNWTSzC6gBKNRVXrmsbcHf/yf3vBUbiG8rvPECf+QzMPHwt97dcua7dzXic6lbnsfhuMOrk/7gQX1duH2C9MWaVf/3JwB+Bf/s//9j/vwuIN8YU42u1lotIEr6f/UhggX+9eHxFZaN/vwv9y+fje7NVUxFQDrwoItOBuoYJvFhETvZnvcYYUy4ipwJDgbkiAr7fu53GmF0isk5EjsE3M0wf//fgj7Wt799/ZY1jzwdOryNHtbrO+dsGtlOHQQunCjuuXJcH+BT4tP/k/onAGHxF9ARArMwWhDYDbwKvuXJdy1romNXXOfvj66rdBPwJX9F6mYZ/RhX+/701Pq7+PMK//UPGmOdqbiQiGQet7+GgN1XGGLeIDAdOxXcT2o3AKbVkeMcYc6OIjACmi8in/uNONsb8pbb1gYuAFcAHxhgjvmpZ1/pV5tc7Nz38+rfajb+n0L99VPXp1XbOqnloV60Ka65cV5Er1/WSK9d1Ir7WxY34imq5pcGstRTfwBInAN1cua4JLVg0wdfaOhvIN8Z4jDH5QBK+7trZ+IpLhoj08q9/GfBNI/b/GXCliMQDiEgnEUkPZEP/Ng5jzCfArfi6PetkjJkNvA7cAswCLqw+loikiEg3/6pTgPPxjcX8jn9ZfevXJQ9fKxV8vSnVzzQf9jmrxtMWp2o1XLmujfgepXiq/+T+ccBp+P6AjwI6WpmtmVXgu/t4GjDNlevKszSNr4s1FfjvQcvijTG7AUTk98B7IhIBzMU3/VxAjDGf+68fzvZ3gZYAl+JruTUkAfhIRGLwteJuC2Cbh/HdRPUgvtGTPvffMVyFrzt2gzGmQESWAdnGmJ/9OZeJSK3r13OsF/z5fsZXeEsbOOedde1IHT59jlMpoP/k/v349brbcUCv+rcIanvxjRn7g//fT65c1z5LEykVRrRwKlWL/pP7p/FrIR2M7zGJzpaGql0xvq7NJfiK5Y/AUh0vVqnmo4VTqQD5bzTKwldEs/3/d8X3DF8qzXfPQBGwzf9vFbAcWAYsd+W6NjXTMZVSddDCqVQT6D+5fwSQjq+Itvf/n4DvGb/a/nnxPXJQhe9GpVL/vxJgF78Wym3azapUcNHCqZRSSjWCPo6ilFJKNYIWTqWUUqoRtHAqpZRSjaCFUymllGoELZxKKaVUI2jhVEoppRpBC6dSSinVCFo4lVJKqUbQwqmUUko1ghZOpZRSqhG0cCqllFKNoIVTKaWUagQtnEoppVQjaOFUSimlGkELp1JKKdUIWjiVUkqpRtDCqZRSSjWCFk6llFKqEbRwKqWUUo2ghVMppZRqBC2cSimlVCNo4VRKKaUaQQunUkop1QhaOJVSSqlG0MKplFJKNYIWTqWUUqoRtHAqpZRSjaCFUymllGoELZxKKaVUI2jhVEoppRpBC6dSSinVCFo4lVJKqUbQwqmUUko1wv8DPK5/jSH0vuYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "total_na = df3[\"Not Allocated by Gender/Sport Revenue\"].sum()\n",
    "sum_m = df3[\"Total Men's Team Revenue\"].sum()\n",
    "sum_w = df3[\"Total Women's Team Revenue\"].sum()\n",
    "x = np.array([\"$151,400,514\", \"$320281147\", \"$228590342\"])\n",
    "df = pd.DataFrame({'Revenue': [total_na, sum_m, sum_w],\n",
    "                   'total': [151400514, 320281147, 228590342]},\n",
    "                  index=[\"Unspecified Sports Revenue\", \"Total Men's Revenue\", \"Women's Revenue\"])\n",
    "plot = df.plot.pie(y='Revenue', figsize=(5, 5), autopct='%.1f%%')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "id": "8dc8cbd1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "men_total = df3[\"Total Men's Team Revenue\"].sum()\n",
    "women_total = df3[\"Total Women's Team Revenue\"].sum()\n",
    "grand_total = df3[\"Grand Total Revenue\"].sum()\n",
    "x = np.array([\"$320,281,147\", \"$228,590,342\"])\n",
    "df = pd.DataFrame({'Revenue': [men_total, women_total],\n",
    "                   'total': [320281147, 228590342]},\n",
    "                  index=[\"Men's Total\", \"Women's Total\"])\n",
    "plot = df.plot.pie(y='Revenue', figsize=(5, 5), autopct='%.1f%%')\n",
    "# deficit of $91,690,805"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "id": "1ca23de7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "320281147\n",
      "228590342\n",
      "91690805\n"
     ]
    }
   ],
   "source": [
    "print(men_total)\n",
    "print(women_total)\n",
    "print(men_total - women_total)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "id": "cd614194",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Survey Year</th>\n",
       "      <th>UNITID</th>\n",
       "      <th>Institution Name</th>\n",
       "      <th>State CD</th>\n",
       "      <th>Classification Name</th>\n",
       "      <th>Classification Other</th>\n",
       "      <th>Sanction Code</th>\n",
       "      <th>Sanction Name</th>\n",
       "      <th>Male Undergraduates</th>\n",
       "      <th>Female Undergraduates</th>\n",
       "      <th>...</th>\n",
       "      <th>Wrestling Coed Team Operating Expenses</th>\n",
       "      <th>Wrestling Total Operating Expenses</th>\n",
       "      <th>Other Sports Men's Team Operating Expenses</th>\n",
       "      <th>Other Sports Women's Team Operating Expenses</th>\n",
       "      <th>Other Sports Coed Team Operating Expenses</th>\n",
       "      <th>Other Sports Total Operating Expenses</th>\n",
       "      <th>Total Men's Team Operating Expenses</th>\n",
       "      <th>Total Women's Team Operating Expenses</th>\n",
       "      <th>Total Coed Team Operating Expenses</th>\n",
       "      <th>Grand Total Operating Expenses</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010</td>\n",
       "      <td>222178</td>\n",
       "      <td>Abilene Christian University</td>\n",
       "      <td>TX</td>\n",
       "      <td>NCAA Division II (with football)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>1666</td>\n",
       "      <td>1933</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>647030</td>\n",
       "      <td>433128</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1080158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010</td>\n",
       "      <td>138558</td>\n",
       "      <td>Abraham Baldwin Agricultural College</td>\n",
       "      <td>GA</td>\n",
       "      <td>NJCAA Division I</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>NJCAA</td>\n",
       "      <td>1196</td>\n",
       "      <td>1220</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>92647</td>\n",
       "      <td>61172</td>\n",
       "      <td>NaN</td>\n",
       "      <td>153819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010</td>\n",
       "      <td>108232</td>\n",
       "      <td>ACADEMY OF ART UNIVERSITY</td>\n",
       "      <td>CA</td>\n",
       "      <td>NCAA Division II (without football)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>3141</td>\n",
       "      <td>3645</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>450142</td>\n",
       "      <td>571362</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1021504</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010</td>\n",
       "      <td>126182</td>\n",
       "      <td>Adams State College</td>\n",
       "      <td>CO</td>\n",
       "      <td>NCAA Division II (with football)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>948</td>\n",
       "      <td>1079</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>61259.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>547230</td>\n",
       "      <td>533702</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1080932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010</td>\n",
       "      <td>188429</td>\n",
       "      <td>Adelphi University</td>\n",
       "      <td>NY</td>\n",
       "      <td>NCAA Division II (without football)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>1331</td>\n",
       "      <td>3001</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>590802</td>\n",
       "      <td>685016</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1275818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>2020</td>\n",
       "      <td>168528</td>\n",
       "      <td>Adrian College</td>\n",
       "      <td>MI</td>\n",
       "      <td>NCAA Division III with football</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>877</td>\n",
       "      <td>861</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>65232.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>27175.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27175.0</td>\n",
       "      <td>433620</td>\n",
       "      <td>364071</td>\n",
       "      <td>NaN</td>\n",
       "      <td>919277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>2020</td>\n",
       "      <td>100654</td>\n",
       "      <td>Alabama A &amp; M University</td>\n",
       "      <td>AL</td>\n",
       "      <td>NCAA Division I-FCS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>1849</td>\n",
       "      <td>2814</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>192008</td>\n",
       "      <td>212086</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2320605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>2020</td>\n",
       "      <td>100724</td>\n",
       "      <td>Alabama State University</td>\n",
       "      <td>AL</td>\n",
       "      <td>NCAA Division I-FCS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>1171</td>\n",
       "      <td>2118</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>113876</td>\n",
       "      <td>146084</td>\n",
       "      <td>NaN</td>\n",
       "      <td>651021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>2020</td>\n",
       "      <td>188526</td>\n",
       "      <td>Albany College of Pharmacy and Health Sciences</td>\n",
       "      <td>NY</td>\n",
       "      <td>USCAA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9</td>\n",
       "      <td>other</td>\n",
       "      <td>270</td>\n",
       "      <td>413</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16507</td>\n",
       "      <td>14825</td>\n",
       "      <td>NaN</td>\n",
       "      <td>31332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>2020</td>\n",
       "      <td>138716</td>\n",
       "      <td>Albany State University</td>\n",
       "      <td>GA</td>\n",
       "      <td>NCAA Division II with football</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NCAA</td>\n",
       "      <td>1210</td>\n",
       "      <td>2942</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>38733</td>\n",
       "      <td>40347</td>\n",
       "      <td>NaN</td>\n",
       "      <td>175468</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>110 rows × 167 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Survey Year  UNITID                                Institution Name  \\\n",
       "0           2010  222178                    Abilene Christian University   \n",
       "1           2010  138558            Abraham Baldwin Agricultural College   \n",
       "2           2010  108232                       ACADEMY OF ART UNIVERSITY   \n",
       "3           2010  126182                             Adams State College   \n",
       "4           2010  188429                              Adelphi University   \n",
       "..           ...     ...                                             ...   \n",
       "105         2020  168528                                  Adrian College   \n",
       "106         2020  100654                        Alabama A & M University   \n",
       "107         2020  100724                        Alabama State University   \n",
       "108         2020  188526  Albany College of Pharmacy and Health Sciences   \n",
       "109         2020  138716                         Albany State University   \n",
       "\n",
       "    State CD                  Classification Name Classification Other  \\\n",
       "0         TX     NCAA Division II (with football)                  NaN   \n",
       "1         GA                     NJCAA Division I                  NaN   \n",
       "2         CA  NCAA Division II (without football)                  NaN   \n",
       "3         CO     NCAA Division II (with football)                  NaN   \n",
       "4         NY  NCAA Division II (without football)                  NaN   \n",
       "..       ...                                  ...                  ...   \n",
       "105       MI      NCAA Division III with football                  NaN   \n",
       "106       AL                  NCAA Division I-FCS                  NaN   \n",
       "107       AL                  NCAA Division I-FCS                  NaN   \n",
       "108       NY                                USCAA                  NaN   \n",
       "109       GA       NCAA Division II with football                  NaN   \n",
       "\n",
       "     Sanction Code Sanction Name  Male Undergraduates  Female Undergraduates  \\\n",
       "0                1          NCAA                 1666                   1933   \n",
       "1                3         NJCAA                 1196                   1220   \n",
       "2                1          NCAA                 3141                   3645   \n",
       "3                1          NCAA                  948                   1079   \n",
       "4                1          NCAA                 1331                   3001   \n",
       "..             ...           ...                  ...                    ...   \n",
       "105              1          NCAA                  877                    861   \n",
       "106              1          NCAA                 1849                   2814   \n",
       "107              1          NCAA                 1171                   2118   \n",
       "108              9         other                  270                    413   \n",
       "109              1          NCAA                 1210                   2942   \n",
       "\n",
       "     ...  Wrestling Coed Team Operating Expenses  \\\n",
       "0    ...                                     NaN   \n",
       "1    ...                                     NaN   \n",
       "2    ...                                     NaN   \n",
       "3    ...                                     NaN   \n",
       "4    ...                                     NaN   \n",
       "..   ...                                     ...   \n",
       "105  ...                                     NaN   \n",
       "106  ...                                     NaN   \n",
       "107  ...                                     NaN   \n",
       "108  ...                                     NaN   \n",
       "109  ...                                     NaN   \n",
       "\n",
       "     Wrestling Total Operating Expenses  \\\n",
       "0                                   NaN   \n",
       "1                                   NaN   \n",
       "2                                   NaN   \n",
       "3                               61259.0   \n",
       "4                                   NaN   \n",
       "..                                  ...   \n",
       "105                             65232.0   \n",
       "106                                 NaN   \n",
       "107                                 NaN   \n",
       "108                                 NaN   \n",
       "109                                 NaN   \n",
       "\n",
       "     Other Sports Men's Team Operating Expenses  \\\n",
       "0                                           NaN   \n",
       "1                                           NaN   \n",
       "2                                           NaN   \n",
       "3                                           NaN   \n",
       "4                                           NaN   \n",
       "..                                          ...   \n",
       "105                                         0.0   \n",
       "106                                         NaN   \n",
       "107                                         NaN   \n",
       "108                                         NaN   \n",
       "109                                         NaN   \n",
       "\n",
       "     Other Sports Women's Team Operating Expenses  \\\n",
       "0                                             NaN   \n",
       "1                                             NaN   \n",
       "2                                             NaN   \n",
       "3                                             NaN   \n",
       "4                                             NaN   \n",
       "..                                            ...   \n",
       "105                                       27175.0   \n",
       "106                                           NaN   \n",
       "107                                           NaN   \n",
       "108                                           NaN   \n",
       "109                                           NaN   \n",
       "\n",
       "     Other Sports Coed Team Operating Expenses  \\\n",
       "0                                          NaN   \n",
       "1                                          NaN   \n",
       "2                                          NaN   \n",
       "3                                          NaN   \n",
       "4                                          NaN   \n",
       "..                                         ...   \n",
       "105                                        NaN   \n",
       "106                                        NaN   \n",
       "107                                        NaN   \n",
       "108                                        NaN   \n",
       "109                                        NaN   \n",
       "\n",
       "     Other Sports Total Operating Expenses  \\\n",
       "0                                      NaN   \n",
       "1                                      NaN   \n",
       "2                                      NaN   \n",
       "3                                      NaN   \n",
       "4                                      NaN   \n",
       "..                                     ...   \n",
       "105                                27175.0   \n",
       "106                                    NaN   \n",
       "107                                    NaN   \n",
       "108                                    NaN   \n",
       "109                                    NaN   \n",
       "\n",
       "     Total Men's Team Operating Expenses  \\\n",
       "0                                 647030   \n",
       "1                                  92647   \n",
       "2                                 450142   \n",
       "3                                 547230   \n",
       "4                                 590802   \n",
       "..                                   ...   \n",
       "105                               433620   \n",
       "106                               192008   \n",
       "107                               113876   \n",
       "108                                16507   \n",
       "109                                38733   \n",
       "\n",
       "     Total Women's Team Operating Expenses  \\\n",
       "0                                   433128   \n",
       "1                                    61172   \n",
       "2                                   571362   \n",
       "3                                   533702   \n",
       "4                                   685016   \n",
       "..                                     ...   \n",
       "105                                 364071   \n",
       "106                                 212086   \n",
       "107                                 146084   \n",
       "108                                  14825   \n",
       "109                                  40347   \n",
       "\n",
       "     Total Coed Team Operating Expenses  Grand Total Operating Expenses  \n",
       "0                                   NaN                         1080158  \n",
       "1                                   NaN                          153819  \n",
       "2                                   NaN                         1021504  \n",
       "3                                   NaN                         1080932  \n",
       "4                                   NaN                         1275818  \n",
       "..                                  ...                             ...  \n",
       "105                                 NaN                          919277  \n",
       "106                                 NaN                         2320605  \n",
       "107                                 NaN                          651021  \n",
       "108                                 NaN                           31332  \n",
       "109                                 NaN                          175468  \n",
       "\n",
       "[110 rows x 167 columns]"
      ]
     },
     "execution_count": 203,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = open('expenses.csv', 'r')\n",
    "df4 = pd.read_csv(data)\n",
    "df4"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "97e208c7",
   "metadata": {},
   "source": [
    "# Data Cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "id": "86ad0dc2",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Survey Year</th>\n",
       "      <th>Total Men's Team Operating Expenses</th>\n",
       "      <th>Total Women's Team Operating Expenses</th>\n",
       "      <th>Total Coed Team Operating Expenses</th>\n",
       "      <th>Grand Total Operating Expenses</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010</td>\n",
       "      <td>647030</td>\n",
       "      <td>433128</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1080158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010</td>\n",
       "      <td>92647</td>\n",
       "      <td>61172</td>\n",
       "      <td>NaN</td>\n",
       "      <td>153819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010</td>\n",
       "      <td>450142</td>\n",
       "      <td>571362</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1021504</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010</td>\n",
       "      <td>547230</td>\n",
       "      <td>533702</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1080932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010</td>\n",
       "      <td>590802</td>\n",
       "      <td>685016</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1275818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>2020</td>\n",
       "      <td>433620</td>\n",
       "      <td>364071</td>\n",
       "      <td>NaN</td>\n",
       "      <td>919277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>2020</td>\n",
       "      <td>192008</td>\n",
       "      <td>212086</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2320605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>2020</td>\n",
       "      <td>113876</td>\n",
       "      <td>146084</td>\n",
       "      <td>NaN</td>\n",
       "      <td>651021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>2020</td>\n",
       "      <td>16507</td>\n",
       "      <td>14825</td>\n",
       "      <td>NaN</td>\n",
       "      <td>31332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>2020</td>\n",
       "      <td>38733</td>\n",
       "      <td>40347</td>\n",
       "      <td>NaN</td>\n",
       "      <td>175468</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>110 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Survey Year  Total Men's Team Operating Expenses  \\\n",
       "0           2010                               647030   \n",
       "1           2010                                92647   \n",
       "2           2010                               450142   \n",
       "3           2010                               547230   \n",
       "4           2010                               590802   \n",
       "..           ...                                  ...   \n",
       "105         2020                               433620   \n",
       "106         2020                               192008   \n",
       "107         2020                               113876   \n",
       "108         2020                                16507   \n",
       "109         2020                                38733   \n",
       "\n",
       "     Total Women's Team Operating Expenses  \\\n",
       "0                                   433128   \n",
       "1                                    61172   \n",
       "2                                   571362   \n",
       "3                                   533702   \n",
       "4                                   685016   \n",
       "..                                     ...   \n",
       "105                                 364071   \n",
       "106                                 212086   \n",
       "107                                 146084   \n",
       "108                                  14825   \n",
       "109                                  40347   \n",
       "\n",
       "     Total Coed Team Operating Expenses  Grand Total Operating Expenses  \n",
       "0                                   NaN                         1080158  \n",
       "1                                   NaN                          153819  \n",
       "2                                   NaN                         1021504  \n",
       "3                                   NaN                         1080932  \n",
       "4                                   NaN                         1275818  \n",
       "..                                  ...                             ...  \n",
       "105                                 NaN                          919277  \n",
       "106                                 NaN                         2320605  \n",
       "107                                 NaN                          651021  \n",
       "108                                 NaN                           31332  \n",
       "109                                 NaN                          175468  \n",
       "\n",
       "[110 rows x 5 columns]"
      ]
     },
     "execution_count": 204,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df4.drop(df4.iloc[:, 1:163], axis = 1, inplace = True)\n",
    "df4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "id": "427f657d",
   "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>Survey Year</th>\n",
       "      <th>Total Men's Team Operating Expenses</th>\n",
       "      <th>Total Women's Team Operating Expenses</th>\n",
       "      <th>Grand Total Operating Expenses</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010</td>\n",
       "      <td>647030</td>\n",
       "      <td>433128</td>\n",
       "      <td>1080158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010</td>\n",
       "      <td>92647</td>\n",
       "      <td>61172</td>\n",
       "      <td>153819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010</td>\n",
       "      <td>450142</td>\n",
       "      <td>571362</td>\n",
       "      <td>1021504</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010</td>\n",
       "      <td>547230</td>\n",
       "      <td>533702</td>\n",
       "      <td>1080932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010</td>\n",
       "      <td>590802</td>\n",
       "      <td>685016</td>\n",
       "      <td>1275818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>2020</td>\n",
       "      <td>433620</td>\n",
       "      <td>364071</td>\n",
       "      <td>919277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>2020</td>\n",
       "      <td>192008</td>\n",
       "      <td>212086</td>\n",
       "      <td>2320605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>2020</td>\n",
       "      <td>113876</td>\n",
       "      <td>146084</td>\n",
       "      <td>651021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>2020</td>\n",
       "      <td>16507</td>\n",
       "      <td>14825</td>\n",
       "      <td>31332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>2020</td>\n",
       "      <td>38733</td>\n",
       "      <td>40347</td>\n",
       "      <td>175468</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>110 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Survey Year  Total Men's Team Operating Expenses  \\\n",
       "0           2010                               647030   \n",
       "1           2010                                92647   \n",
       "2           2010                               450142   \n",
       "3           2010                               547230   \n",
       "4           2010                               590802   \n",
       "..           ...                                  ...   \n",
       "105         2020                               433620   \n",
       "106         2020                               192008   \n",
       "107         2020                               113876   \n",
       "108         2020                                16507   \n",
       "109         2020                                38733   \n",
       "\n",
       "     Total Women's Team Operating Expenses  Grand Total Operating Expenses  \n",
       "0                                   433128                         1080158  \n",
       "1                                    61172                          153819  \n",
       "2                                   571362                         1021504  \n",
       "3                                   533702                         1080932  \n",
       "4                                   685016                         1275818  \n",
       "..                                     ...                             ...  \n",
       "105                                 364071                          919277  \n",
       "106                                 212086                         2320605  \n",
       "107                                 146084                          651021  \n",
       "108                                  14825                           31332  \n",
       "109                                  40347                          175468  \n",
       "\n",
       "[110 rows x 4 columns]"
      ]
     },
     "execution_count": 208,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "id": "13cd3faa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "38669209\n",
      "37341600\n"
     ]
    }
   ],
   "source": [
    "total_expense_m = df4[\"Total Men's Team Operating Expenses\"].sum()\n",
    "total_expense_f = df4[\"Total Women's Team Operating Expenses\"].sum()\n",
    "print(total_expense_m)\n",
    "print(total_expense_f)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f0b0cc6",
   "metadata": {},
   "source": [
    "# Data Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "id": "bff4982f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.array([\"$320,281,147\", \"$228,590,342\"])\n",
    "df = pd.DataFrame({'Expenses': [total_expense_m, total_expense_f],\n",
    "                   'total': [38669209, 37341600]},\n",
    "                  index=[\"Men's Total\", \"Women's Total\"])\n",
    "plot = df.plot.pie(y='Expenses', figsize=(5, 5), autopct='%.1f%%')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e8ac5edf",
   "metadata": {},
   "source": [
    "# Conclusion and Discussion"
   ]
  },
  {
   "cell_type": "raw",
   "id": "9e2cde2b",
   "metadata": {},
   "source": [
    "     In the introduction we learned that the men’s and women’s program need to receive the same level of resources, this is in regards to the quality of the resources, not the amount. Eg: both men’s and women’s teams to receive Under Armour gear, but it’s perfectly acceptable for the men to receive a larger quantity of the gear. Through the data it is obvious that there is a lack of female represenation within coaching positions, and a slight discrepancy in expenses in comparision to revenue generated. Although there is a clear difference between the funds and resources allocated to the two genders, and the lack of diversity in the staff, it’s important to note that the NCAA is a business, and the data shows it values profit rather than making sure everything is 50/50. The Title IX clause is very lenient in its regulations, making this business decision completely legal. The NCAA is well within it's rights to allocate a larger quantity of resources to male athletics rather than female. As of right now there is more social pressure put on the NCAA to make change than anything with legal standing. Some limitations we faced during this project was the amount of data we had access to. The EADA would only allow us to obtain 10 unviersitiy's data within a ten yesr time span, limiting our ability to get the big picture of how this problem affects colleges at a nationwide level. Although we did see data from across the nation, it would have been benficial to cofnidently display data that represented the entire country. Further research needs to be done to conclude how these discrepancies carry throughout the majority of universities in the United States. \n",
    "\n",
    "https://www.forbes.com/sites/ceceliatownes/2021/03/19/where-is-title-ix-in-the-ncaa-weight-rooms/?sh=3fd23dee7007\n"
   ]
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    "# Works Cited"
   ]
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   "source": [
    "Dellenger, R. (2022, March 15). Lawmakers slam NCAA on gender equity, suggest possible title IX violations. Sports Illustrated. Retrieved April 24, 2022, from https://www.si.com/college/2022/03/15/ncaa-tournament-college-sports-gender-equity-congress-title-ix \n",
    "\n",
    "Diaz, J. (2021, October 27). The NCAA's focus on profits means far more gets spent on men's Championships. NPR. Retrieved April 24, 2022, from https://www.npr.org/2021/10/27/1049530975/ncaa-spends-more-on-mens-sports-report-reveals \n",
    "\n",
    "Feinberg, D. (2022, March 15). Lawmakers Rip Emmert, demand more progress on NCAA equity. AP NEWS. Retrieved April 24, 2022, from https://apnews.com/article/march-madness-business-sports-basketball-college-sports-79b42c3d9e312ff711058b73b181278b \n",
    "\n",
    "FOX Sports. (2021, October 27). Second NCAA Gender Equity Report shows spending disparities. FOX Sports. Retrieved April 24, 2022, from https://www.foxsports.com/articles/other/second-ncaa-gender-equity-report-shows-spending-disparities \n",
    "\n",
    "Title IX frequently asked questions. NCAA.org. (n.d.). Retrieved April 24, 2022, from https://www.ncaa.org/sports/2014/1/27/title-ix-frequently-asked-questions.aspx#:~:text=Title%20IX%20does%20not%20require%20identical%20athletics%20programs%20for%20males,same%20team%20in%20each%20sport. \n",
    "\n",
    "Townes, C. (2021, March 19). Where is title IX in the NCAA weight rooms? Forbes. Retrieved April 24, 2022, from https://www.forbes.com/sites/ceceliatownes/2021/03/19/where-is-title-ix-in-the-ncaa-weight-rooms/?sh=3fd23dee7007 "
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