{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 192,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "import seaborn as sns\n",
    "\n",
    "import highlight_text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "metadata": {},
   "outputs": [],
   "source": [
    "# the famous import font code to use Andale Mono\n",
    "import matplotlib.font_manager\n",
    "from IPython.core.display import HTML\n",
    "\n",
    "def make_html(fontname):\n",
    "    return \"<p>{font}: <span style='font-family:{font}; font-size: 24px;'>{font}</p>\".format(font=fontname)\n",
    "\n",
    "code = \"\\n\".join([make_html(font) for font in sorted(set([f.name for f in matplotlib.font_manager.fontManager.ttflist]))])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "#import data\n",
    "df = pd.read_csv('beeswarmTutorial.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "metadata": {},
   "outputs": [],
   "source": [
    "#set default colors\n",
    "text_color = 'white'\n",
    "background = '#313332'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "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>Player</th>\n",
       "      <th>Pos</th>\n",
       "      <th>Squad</th>\n",
       "      <th>90s</th>\n",
       "      <th>Prog</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Patrick van Aanholt\\Patrick-van-Aanholt</td>\n",
       "      <td>DF</td>\n",
       "      <td>Crystal Palace</td>\n",
       "      <td>11.7</td>\n",
       "      <td>76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Tammy Abraham\\Tammy-Abraham</td>\n",
       "      <td>FW</td>\n",
       "      <td>Chelsea</td>\n",
       "      <td>10.6</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Che Adams\\Che-Adams</td>\n",
       "      <td>FW</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>19.0</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Tosin Adarabioyo\\Tosin-Adarabioyo</td>\n",
       "      <td>DF</td>\n",
       "      <td>Fulham</td>\n",
       "      <td>18.0</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Adrián\\Adrian</td>\n",
       "      <td>GK</td>\n",
       "      <td>Liverpool</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    Player Pos           Squad   90s  Prog\n",
       "0  Patrick van Aanholt\\Patrick-van-Aanholt  DF  Crystal Palace  11.7    76\n",
       "1              Tammy Abraham\\Tammy-Abraham  FW         Chelsea  10.6    11\n",
       "2                      Che Adams\\Che-Adams  FW     Southampton  19.0    38\n",
       "3        Tosin Adarabioyo\\Tosin-Adarabioyo  DF          Fulham  18.0    36\n",
       "4                            Adrián\\Adrian  GK       Liverpool   2.0     0"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#look at top of dataframe\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "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>Player</th>\n",
       "      <th>Pos</th>\n",
       "      <th>Squad</th>\n",
       "      <th>90s</th>\n",
       "      <th>Prog</th>\n",
       "      <th>per90</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Patrick van Aanholt\\Patrick-van-Aanholt</td>\n",
       "      <td>DF</td>\n",
       "      <td>Crystal Palace</td>\n",
       "      <td>11.7</td>\n",
       "      <td>76</td>\n",
       "      <td>6.495726</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Tammy Abraham\\Tammy-Abraham</td>\n",
       "      <td>FW</td>\n",
       "      <td>Chelsea</td>\n",
       "      <td>10.6</td>\n",
       "      <td>11</td>\n",
       "      <td>1.037736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Che Adams\\Che-Adams</td>\n",
       "      <td>FW</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>19.0</td>\n",
       "      <td>38</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Tosin Adarabioyo\\Tosin-Adarabioyo</td>\n",
       "      <td>DF</td>\n",
       "      <td>Fulham</td>\n",
       "      <td>18.0</td>\n",
       "      <td>36</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Adrián\\Adrian</td>\n",
       "      <td>GK</td>\n",
       "      <td>Liverpool</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</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>492</th>\n",
       "      <td>Andre-Frank Zambo Anguissa\\Andre-Frank-Zambo-A...</td>\n",
       "      <td>MF</td>\n",
       "      <td>Fulham</td>\n",
       "      <td>18.7</td>\n",
       "      <td>74</td>\n",
       "      <td>3.957219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>493</th>\n",
       "      <td>Andi Zeqiri\\Andi-Zeqiri</td>\n",
       "      <td>FWDF</td>\n",
       "      <td>Brighton</td>\n",
       "      <td>0.8</td>\n",
       "      <td>1</td>\n",
       "      <td>1.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>494</th>\n",
       "      <td>Oleksandr Zinchenko\\Oleksandr-Zinchenko</td>\n",
       "      <td>DF</td>\n",
       "      <td>Manchester City</td>\n",
       "      <td>7.1</td>\n",
       "      <td>39</td>\n",
       "      <td>5.492958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>495</th>\n",
       "      <td>Hakim Ziyech\\Hakim-Ziyech</td>\n",
       "      <td>FWMF</td>\n",
       "      <td>Chelsea</td>\n",
       "      <td>7.0</td>\n",
       "      <td>42</td>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>496</th>\n",
       "      <td>Kurt Zouma\\Kurt-Zouma</td>\n",
       "      <td>DF</td>\n",
       "      <td>Chelsea</td>\n",
       "      <td>15.0</td>\n",
       "      <td>46</td>\n",
       "      <td>3.066667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>497 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                Player   Pos            Squad  \\\n",
       "0              Patrick van Aanholt\\Patrick-van-Aanholt    DF   Crystal Palace   \n",
       "1                          Tammy Abraham\\Tammy-Abraham    FW          Chelsea   \n",
       "2                                  Che Adams\\Che-Adams    FW      Southampton   \n",
       "3                    Tosin Adarabioyo\\Tosin-Adarabioyo    DF           Fulham   \n",
       "4                                        Adrián\\Adrian    GK        Liverpool   \n",
       "..                                                 ...   ...              ...   \n",
       "492  Andre-Frank Zambo Anguissa\\Andre-Frank-Zambo-A...    MF           Fulham   \n",
       "493                            Andi Zeqiri\\Andi-Zeqiri  FWDF         Brighton   \n",
       "494            Oleksandr Zinchenko\\Oleksandr-Zinchenko    DF  Manchester City   \n",
       "495                          Hakim Ziyech\\Hakim-Ziyech  FWMF          Chelsea   \n",
       "496                              Kurt Zouma\\Kurt-Zouma    DF          Chelsea   \n",
       "\n",
       "      90s  Prog     per90  \n",
       "0    11.7    76  6.495726  \n",
       "1    10.6    11  1.037736  \n",
       "2    19.0    38  2.000000  \n",
       "3    18.0    36  2.000000  \n",
       "4     2.0     0  0.000000  \n",
       "..    ...   ...       ...  \n",
       "492  18.7    74  3.957219  \n",
       "493   0.8     1  1.250000  \n",
       "494   7.1    39  5.492958  \n",
       "495   7.0    42  6.000000  \n",
       "496  15.0    46  3.066667  \n",
       "\n",
       "[497 rows x 6 columns]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#create a new column for progressive passes per 90\n",
    "df['per90'] = df['Prog']/df['90s']\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "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>index</th>\n",
       "      <th>Player</th>\n",
       "      <th>Pos</th>\n",
       "      <th>Squad</th>\n",
       "      <th>90s</th>\n",
       "      <th>Prog</th>\n",
       "      <th>per90</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Patrick van Aanholt\\Patrick-van-Aanholt</td>\n",
       "      <td>DF</td>\n",
       "      <td>Crystal Palace</td>\n",
       "      <td>11.7</td>\n",
       "      <td>76</td>\n",
       "      <td>6.495726</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Tammy Abraham\\Tammy-Abraham</td>\n",
       "      <td>FW</td>\n",
       "      <td>Chelsea</td>\n",
       "      <td>10.6</td>\n",
       "      <td>11</td>\n",
       "      <td>1.037736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Che Adams\\Che-Adams</td>\n",
       "      <td>FW</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>19.0</td>\n",
       "      <td>38</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Tosin Adarabioyo\\Tosin-Adarabioyo</td>\n",
       "      <td>DF</td>\n",
       "      <td>Fulham</td>\n",
       "      <td>18.0</td>\n",
       "      <td>36</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6</td>\n",
       "      <td>Ola Aina\\Ola-Aina</td>\n",
       "      <td>DF</td>\n",
       "      <td>Fulham</td>\n",
       "      <td>17.7</td>\n",
       "      <td>69</td>\n",
       "      <td>3.898305</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300</th>\n",
       "      <td>491</td>\n",
       "      <td>Wilfried Zaha\\Wilfried-Zaha</td>\n",
       "      <td>FW</td>\n",
       "      <td>Crystal Palace</td>\n",
       "      <td>18.5</td>\n",
       "      <td>39</td>\n",
       "      <td>2.108108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>301</th>\n",
       "      <td>492</td>\n",
       "      <td>Andre-Frank Zambo Anguissa\\Andre-Frank-Zambo-A...</td>\n",
       "      <td>MF</td>\n",
       "      <td>Fulham</td>\n",
       "      <td>18.7</td>\n",
       "      <td>74</td>\n",
       "      <td>3.957219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>302</th>\n",
       "      <td>494</td>\n",
       "      <td>Oleksandr Zinchenko\\Oleksandr-Zinchenko</td>\n",
       "      <td>DF</td>\n",
       "      <td>Manchester City</td>\n",
       "      <td>7.1</td>\n",
       "      <td>39</td>\n",
       "      <td>5.492958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>303</th>\n",
       "      <td>495</td>\n",
       "      <td>Hakim Ziyech\\Hakim-Ziyech</td>\n",
       "      <td>FWMF</td>\n",
       "      <td>Chelsea</td>\n",
       "      <td>7.0</td>\n",
       "      <td>42</td>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>304</th>\n",
       "      <td>496</td>\n",
       "      <td>Kurt Zouma\\Kurt-Zouma</td>\n",
       "      <td>DF</td>\n",
       "      <td>Chelsea</td>\n",
       "      <td>15.0</td>\n",
       "      <td>46</td>\n",
       "      <td>3.066667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>305 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     index                                             Player   Pos  \\\n",
       "0        0            Patrick van Aanholt\\Patrick-van-Aanholt    DF   \n",
       "1        1                        Tammy Abraham\\Tammy-Abraham    FW   \n",
       "2        2                                Che Adams\\Che-Adams    FW   \n",
       "3        3                  Tosin Adarabioyo\\Tosin-Adarabioyo    DF   \n",
       "4        6                                  Ola Aina\\Ola-Aina    DF   \n",
       "..     ...                                                ...   ...   \n",
       "300    491                        Wilfried Zaha\\Wilfried-Zaha    FW   \n",
       "301    492  Andre-Frank Zambo Anguissa\\Andre-Frank-Zambo-A...    MF   \n",
       "302    494            Oleksandr Zinchenko\\Oleksandr-Zinchenko    DF   \n",
       "303    495                          Hakim Ziyech\\Hakim-Ziyech  FWMF   \n",
       "304    496                              Kurt Zouma\\Kurt-Zouma    DF   \n",
       "\n",
       "               Squad   90s  Prog     per90  \n",
       "0     Crystal Palace  11.7    76  6.495726  \n",
       "1            Chelsea  10.6    11  1.037736  \n",
       "2        Southampton  19.0    38  2.000000  \n",
       "3             Fulham  18.0    36  2.000000  \n",
       "4             Fulham  17.7    69  3.898305  \n",
       "..               ...   ...   ...       ...  \n",
       "300   Crystal Palace  18.5    39  2.108108  \n",
       "301           Fulham  18.7    74  3.957219  \n",
       "302  Manchester City   7.1    39  5.492958  \n",
       "303          Chelsea   7.0    42  6.000000  \n",
       "304          Chelsea  15.0    46  3.066667  \n",
       "\n",
       "[305 rows x 7 columns]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#filter the dataframe so it is only players who have played more than 6.5 90's which is about 585 minutes\n",
    "df = df[df['90s']>=6.5].reset_index()\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "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>index</th>\n",
       "      <th>90s</th>\n",
       "      <th>Prog</th>\n",
       "      <th>per90</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>305.000000</td>\n",
       "      <td>305.000000</td>\n",
       "      <td>305.000000</td>\n",
       "      <td>305.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>241.468852</td>\n",
       "      <td>14.688525</td>\n",
       "      <td>43.655738</td>\n",
       "      <td>3.019502</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>146.384632</td>\n",
       "      <td>4.758721</td>\n",
       "      <td>31.651934</td>\n",
       "      <td>1.798697</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.600000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>110.000000</td>\n",
       "      <td>10.900000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>1.932773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>243.000000</td>\n",
       "      <td>14.700000</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>2.857143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>371.000000</td>\n",
       "      <td>18.800000</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>4.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>496.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>171.000000</td>\n",
       "      <td>9.879518</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            index         90s        Prog       per90\n",
       "count  305.000000  305.000000  305.000000  305.000000\n",
       "mean   241.468852   14.688525   43.655738    3.019502\n",
       "std    146.384632    4.758721   31.651934    1.798697\n",
       "min      0.000000    6.600000    0.000000    0.000000\n",
       "25%    110.000000   10.900000   21.000000    1.932773\n",
       "50%    243.000000   14.700000   37.000000    2.857143\n",
       "75%    371.000000   18.800000   60.000000    4.000000\n",
       "max    496.000000   23.000000  171.000000    9.879518"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.sort_values(by='per90',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[df['Pos'] != 'GK']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "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>index</th>\n",
       "      <th>Player</th>\n",
       "      <th>Pos</th>\n",
       "      <th>Squad</th>\n",
       "      <th>90s</th>\n",
       "      <th>Prog</th>\n",
       "      <th>per90</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>11</td>\n",
       "      <td>Thiago Alcántara\\Thiago-Alcantara</td>\n",
       "      <td>MF</td>\n",
       "      <td>Liverpool</td>\n",
       "      <td>8.3</td>\n",
       "      <td>82</td>\n",
       "      <td>9.879518</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>14</td>\n",
       "      <td>Trent Alexander-Arnold\\Trent-Alexander-Arnold</td>\n",
       "      <td>DF</td>\n",
       "      <td>Liverpool</td>\n",
       "      <td>19.5</td>\n",
       "      <td>166</td>\n",
       "      <td>8.512821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>234</td>\n",
       "      <td>Mateo Kovačić\\Mateo-Kovacic</td>\n",
       "      <td>MF</td>\n",
       "      <td>Chelsea</td>\n",
       "      <td>13.1</td>\n",
       "      <td>105</td>\n",
       "      <td>8.015267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>299</th>\n",
       "      <td>487</td>\n",
       "      <td>Granit Xhaka\\Granit-Xhaka</td>\n",
       "      <td>MF</td>\n",
       "      <td>Arsenal</td>\n",
       "      <td>17.1</td>\n",
       "      <td>136</td>\n",
       "      <td>7.953216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>187</td>\n",
       "      <td>Jordan Henderson\\Jordan-Henderson</td>\n",
       "      <td>MFDF</td>\n",
       "      <td>Liverpool</td>\n",
       "      <td>17.6</td>\n",
       "      <td>134</td>\n",
       "      <td>7.613636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>111</td>\n",
       "      <td>Kevin De Bruyne\\Kevin-De-Bruyne</td>\n",
       "      <td>MF</td>\n",
       "      <td>Manchester City</td>\n",
       "      <td>15.6</td>\n",
       "      <td>118</td>\n",
       "      <td>7.564103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>301</td>\n",
       "      <td>James Milner\\James-Milner</td>\n",
       "      <td>MFDF</td>\n",
       "      <td>Liverpool</td>\n",
       "      <td>6.8</td>\n",
       "      <td>51</td>\n",
       "      <td>7.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>230</th>\n",
       "      <td>375</td>\n",
       "      <td>Andrew Robertson\\Andrew-Robertson</td>\n",
       "      <td>DF</td>\n",
       "      <td>Liverpool</td>\n",
       "      <td>22.9</td>\n",
       "      <td>171</td>\n",
       "      <td>7.467249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236</th>\n",
       "      <td>384</td>\n",
       "      <td>James Rodríguez\\James-Rodriguez</td>\n",
       "      <td>FWMF</td>\n",
       "      <td>Everton</td>\n",
       "      <td>13.3</td>\n",
       "      <td>99</td>\n",
       "      <td>7.443609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>140</td>\n",
       "      <td>Bruno Fernandes\\Bruno-Fernandes</td>\n",
       "      <td>MF</td>\n",
       "      <td>Manchester Utd</td>\n",
       "      <td>21.4</td>\n",
       "      <td>158</td>\n",
       "      <td>7.383178</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     index                                         Player   Pos  \\\n",
       "8       11              Thiago Alcántara\\Thiago-Alcantara    MF   \n",
       "10      14  Trent Alexander-Arnold\\Trent-Alexander-Arnold    DF   \n",
       "148    234                    Mateo Kovačić\\Mateo-Kovacic    MF   \n",
       "299    487                      Granit Xhaka\\Granit-Xhaka    MF   \n",
       "122    187              Jordan Henderson\\Jordan-Henderson  MFDF   \n",
       "77     111                Kevin De Bruyne\\Kevin-De-Bruyne    MF   \n",
       "190    301                      James Milner\\James-Milner  MFDF   \n",
       "230    375              Andrew Robertson\\Andrew-Robertson    DF   \n",
       "236    384                James Rodríguez\\James-Rodriguez  FWMF   \n",
       "96     140                Bruno Fernandes\\Bruno-Fernandes    MF   \n",
       "\n",
       "               Squad   90s  Prog     per90  \n",
       "8          Liverpool   8.3    82  9.879518  \n",
       "10         Liverpool  19.5   166  8.512821  \n",
       "148          Chelsea  13.1   105  8.015267  \n",
       "299          Arsenal  17.1   136  7.953216  \n",
       "122        Liverpool  17.6   134  7.613636  \n",
       "77   Manchester City  15.6   118  7.564103  \n",
       "190        Liverpool   6.8    51  7.500000  \n",
       "230        Liverpool  22.9   171  7.467249  \n",
       "236          Everton  13.3    99  7.443609  \n",
       "96    Manchester Utd  21.4   158  7.383178  "
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Progressive Passes per 90')"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(10,5))\n",
    "fig.set_facecolor(background)\n",
    "ax.patch.set_facecolor(background)\n",
    "\n",
    "#set up our base layer\n",
    "mpl.rcParams['xtick.color'] = text_color\n",
    "mpl.rcParams['ytick.color'] = text_color\n",
    "\n",
    "ax.grid(ls='dotted',lw=.5,color='lightgrey',axis='y',zorder=1)\n",
    "spines = ['top','bottom','left','right']\n",
    "for x in spines:\n",
    "    if x in spines:\n",
    "        ax.spines[x].set_visible(False)\n",
    "\n",
    "sns.swarmplot(x='per90',data=df,color='white',zorder=1)\n",
    "\n",
    "#plot thiago\n",
    "plt.scatter(x=9.87,y=0,c='red',edgecolor='white',s=200,zorder=2)\n",
    "plt.text(s='Thiago',x=9.87,y=-.04,c=text_color)\n",
    "\n",
    "#plot de bruyne\n",
    "plt.scatter(x=7.564,y=0,c='blue',edgecolor='white',s=200,zorder=2)\n",
    "\n",
    "plt.title('Progressive Passes in the Premier League 2020/21',c=text_color,fontsize=14)\n",
    "\n",
    "plt.xlabel('Progressive Passes per 90',c=text_color)\n",
    "\n",
    "\n",
    "\n",
    "#plt.savefig('swarm.png',dpi=500,bbox_inches = 'tight',facecolor=background)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {},
   "outputs": [],
   "source": [
    "#import our next dataframe\n",
    "df2 = pd.read_csv('beeswarm2.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "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>Player</th>\n",
       "      <th>Nation</th>\n",
       "      <th>Pos</th>\n",
       "      <th>Squad</th>\n",
       "      <th>90s</th>\n",
       "      <th>Cmp</th>\n",
       "      <th>Att</th>\n",
       "      <th>Cmp%</th>\n",
       "      <th>TotDist</th>\n",
       "      <th>PrgDist</th>\n",
       "      <th>Ast</th>\n",
       "      <th>xA</th>\n",
       "      <th>A-xA</th>\n",
       "      <th>KP</th>\n",
       "      <th>1/3</th>\n",
       "      <th>PPA</th>\n",
       "      <th>CrsPA</th>\n",
       "      <th>Prog</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Patrick van Aanholt\\Patrick-van-Aanholt</td>\n",
       "      <td>nl NED</td>\n",
       "      <td>DF</td>\n",
       "      <td>Crystal Palace</td>\n",
       "      <td>11.7</td>\n",
       "      <td>573</td>\n",
       "      <td>705</td>\n",
       "      <td>81.3</td>\n",
       "      <td>9485</td>\n",
       "      <td>4365</td>\n",
       "      <td>1</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.2</td>\n",
       "      <td>11</td>\n",
       "      <td>43</td>\n",
       "      <td>21</td>\n",
       "      <td>4</td>\n",
       "      <td>76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Tammy Abraham\\Tammy-Abraham</td>\n",
       "      <td>eng ENG</td>\n",
       "      <td>FW</td>\n",
       "      <td>Chelsea</td>\n",
       "      <td>10.6</td>\n",
       "      <td>138</td>\n",
       "      <td>201</td>\n",
       "      <td>68.7</td>\n",
       "      <td>1925</td>\n",
       "      <td>327</td>\n",
       "      <td>1</td>\n",
       "      <td>0.9</td>\n",
       "      <td>0.1</td>\n",
       "      <td>8</td>\n",
       "      <td>12</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Che Adams\\Che-Adams</td>\n",
       "      <td>eng ENG</td>\n",
       "      <td>FW</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>19.0</td>\n",
       "      <td>288</td>\n",
       "      <td>413</td>\n",
       "      <td>69.7</td>\n",
       "      <td>4739</td>\n",
       "      <td>1079</td>\n",
       "      <td>4</td>\n",
       "      <td>4.3</td>\n",
       "      <td>-0.3</td>\n",
       "      <td>22</td>\n",
       "      <td>20</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Tosin Adarabioyo\\Tosin-Adarabioyo</td>\n",
       "      <td>eng ENG</td>\n",
       "      <td>DF</td>\n",
       "      <td>Fulham</td>\n",
       "      <td>18.0</td>\n",
       "      <td>779</td>\n",
       "      <td>905</td>\n",
       "      <td>86.1</td>\n",
       "      <td>18458</td>\n",
       "      <td>6406</td>\n",
       "      <td>0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>3</td>\n",
       "      <td>39</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Adrián\\Adrian</td>\n",
       "      <td>es ESP</td>\n",
       "      <td>GK</td>\n",
       "      <td>Liverpool</td>\n",
       "      <td>2.0</td>\n",
       "      <td>43</td>\n",
       "      <td>62</td>\n",
       "      <td>69.4</td>\n",
       "      <td>1147</td>\n",
       "      <td>723</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Sergio Agüero\\Sergio-Aguero</td>\n",
       "      <td>ar ARG</td>\n",
       "      <td>FW</td>\n",
       "      <td>Manchester City</td>\n",
       "      <td>1.6</td>\n",
       "      <td>33</td>\n",
       "      <td>42</td>\n",
       "      <td>78.6</td>\n",
       "      <td>386</td>\n",
       "      <td>58</td>\n",
       "      <td>0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>-0.6</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Ola Aina\\Ola-Aina</td>\n",
       "      <td>ng NGA</td>\n",
       "      <td>DF</td>\n",
       "      <td>Fulham</td>\n",
       "      <td>17.7</td>\n",
       "      <td>782</td>\n",
       "      <td>1013</td>\n",
       "      <td>77.2</td>\n",
       "      <td>15293</td>\n",
       "      <td>6132</td>\n",
       "      <td>0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>-0.3</td>\n",
       "      <td>8</td>\n",
       "      <td>66</td>\n",
       "      <td>11</td>\n",
       "      <td>6</td>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Rayan Aït Nouri\\Rayan-Ait-Nouri</td>\n",
       "      <td>fr FRA</td>\n",
       "      <td>DF</td>\n",
       "      <td>Wolves</td>\n",
       "      <td>7.7</td>\n",
       "      <td>299</td>\n",
       "      <td>357</td>\n",
       "      <td>83.8</td>\n",
       "      <td>4712</td>\n",
       "      <td>1364</td>\n",
       "      <td>1</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.3</td>\n",
       "      <td>6</td>\n",
       "      <td>13</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Semi Ajayi\\Semi-Ajayi</td>\n",
       "      <td>ng NGA</td>\n",
       "      <td>DF</td>\n",
       "      <td>West Brom</td>\n",
       "      <td>22.0</td>\n",
       "      <td>553</td>\n",
       "      <td>763</td>\n",
       "      <td>72.5</td>\n",
       "      <td>12087</td>\n",
       "      <td>5164</td>\n",
       "      <td>0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>2</td>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Nathan Aké\\Nathan-Ake</td>\n",
       "      <td>nl NED</td>\n",
       "      <td>DF</td>\n",
       "      <td>Manchester City</td>\n",
       "      <td>5.2</td>\n",
       "      <td>429</td>\n",
       "      <td>461</td>\n",
       "      <td>93.1</td>\n",
       "      <td>7845</td>\n",
       "      <td>2158</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    Player   Nation Pos            Squad  \\\n",
       "0  Patrick van Aanholt\\Patrick-van-Aanholt   nl NED  DF   Crystal Palace   \n",
       "1              Tammy Abraham\\Tammy-Abraham  eng ENG  FW          Chelsea   \n",
       "2                      Che Adams\\Che-Adams  eng ENG  FW      Southampton   \n",
       "3        Tosin Adarabioyo\\Tosin-Adarabioyo  eng ENG  DF           Fulham   \n",
       "4                            Adrián\\Adrian   es ESP  GK        Liverpool   \n",
       "5              Sergio Agüero\\Sergio-Aguero   ar ARG  FW  Manchester City   \n",
       "6                        Ola Aina\\Ola-Aina   ng NGA  DF           Fulham   \n",
       "7          Rayan Aït Nouri\\Rayan-Ait-Nouri   fr FRA  DF           Wolves   \n",
       "8                    Semi Ajayi\\Semi-Ajayi   ng NGA  DF        West Brom   \n",
       "9                    Nathan Aké\\Nathan-Ake   nl NED  DF  Manchester City   \n",
       "\n",
       "    90s  Cmp   Att  Cmp%  TotDist  PrgDist  Ast   xA  A-xA  KP  1/3  PPA  \\\n",
       "0  11.7  573   705  81.3     9485     4365    1  0.8   0.2  11   43   21   \n",
       "1  10.6  138   201  68.7     1925      327    1  0.9   0.1   8   12    2   \n",
       "2  19.0  288   413  69.7     4739     1079    4  4.3  -0.3  22   20   12   \n",
       "3  18.0  779   905  86.1    18458     6406    0  0.1  -0.1   3   39    2   \n",
       "4   2.0   43    62  69.4     1147      723    0  0.0   0.0   0    0    0   \n",
       "5   1.6   33    42  78.6      386       58    0  0.6  -0.6   3    2    1   \n",
       "6  17.7  782  1013  77.2    15293     6132    0  0.3  -0.3   8   66   11   \n",
       "7   7.7  299   357  83.8     4712     1364    1  0.7   0.3   6   13    6   \n",
       "8  22.0  553   763  72.5    12087     5164    0  0.1  -0.1   2   50    3   \n",
       "9   5.2  429   461  93.1     7845     2158    0  0.0   0.0   1   36    0   \n",
       "\n",
       "   CrsPA  Prog  \n",
       "0      4    76  \n",
       "1      0    11  \n",
       "2      0    38  \n",
       "3      0    36  \n",
       "4      0     0  \n",
       "5      0     1  \n",
       "6      6    69  \n",
       "7      3    18  \n",
       "8      0    46  \n",
       "9      0    23  "
      ]
     },
     "execution_count": 185,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {},
   "outputs": [],
   "source": [
    "#do some data preprocessing and cleaning\n",
    "\n",
    "#split the player names\n",
    "df2['Player'] = df2['Player'].str.split('\\\\',expand=True)[0]\n",
    "\n",
    "df2 = df2[df2['Pos'] != 'GK']\n",
    "\n",
    "df2 = df2[df2['90s'] > 6.5].reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {},
   "outputs": [],
   "source": [
    "#make the per 90 stats\n",
    "#metrics = ['Prog90','1/390','xA90','Cmp%','KP90','PPA90']\n",
    "df2['Prog'] = df2['Prog'] / df2['90s']\n",
    "df2['1/3'] = df2['1/3'] / df2['90s']\n",
    "df2['xA'] = df2['xA'] / df2['90s']\n",
    "df2['KP'] = df2['KP'] / df2['90s']\n",
    "df2['PPA'] = df2['PPA'] / df2['90s']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   index               Player   Nation Pos           Squad   90s  Cmp   Att  \\\n",
      "0      0  Patrick van Aanholt   nl NED  DF  Crystal Palace  11.7  573   705   \n",
      "1      1        Tammy Abraham  eng ENG  FW         Chelsea  10.6  138   201   \n",
      "2      2            Che Adams  eng ENG  FW     Southampton  19.0  288   413   \n",
      "3      3     Tosin Adarabioyo  eng ENG  DF          Fulham  18.0  779   905   \n",
      "4      6             Ola Aina   ng NGA  DF          Fulham  17.7  782  1013   \n",
      "\n",
      "   Cmp%  TotDist  PrgDist  Ast        xA  A-xA        KP       1/3       PPA  \\\n",
      "0  81.3     9485     4365    1  0.068376   0.2  0.940171  3.675214  1.794872   \n",
      "1  68.7     1925      327    1  0.084906   0.1  0.754717  1.132075  0.188679   \n",
      "2  69.7     4739     1079    4  0.226316  -0.3  1.157895  1.052632  0.631579   \n",
      "3  86.1    18458     6406    0  0.005556  -0.1  0.166667  2.166667  0.111111   \n",
      "4  77.2    15293     6132    0  0.016949  -0.3  0.451977  3.728814  0.621469   \n",
      "\n",
      "   CrsPA      Prog  \n",
      "0      4  6.495726  \n",
      "1      0  1.037736  \n",
      "2      0  2.000000  \n",
      "3      0  2.000000  \n",
      "4      6  3.898305  \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array(['Patrick van Aanholt', 'Tammy Abraham', 'Che Adams',\n",
       "       'Tosin Adarabioyo', 'Ola Aina', 'Rayan Aït Nouri', 'Semi Ajayi',\n",
       "       'Marc Albrighton', 'Thiago Alcántara', 'Toby Alderweireld',\n",
       "       'Trent Alexander-Arnold', 'Ezgjan Alioski', 'Allan',\n",
       "       'Miguel Almirón', 'Steven Alzate', 'Ethan Ampadu',\n",
       "       'Joachim Andersen', 'Michail Antonio', 'Stuart Armstrong',\n",
       "       'Pierre-Emerick Aubameyang', 'Serge Aurier', 'Jordan Ayew',\n",
       "       'Luke Ayling', 'César Azpilicueta', 'Fabián Balbuena',\n",
       "       'George Baldock', 'Patrick Bamford', 'Ross Barkley',\n",
       "       'Ashley Barnes', 'Harvey Barnes', 'Kyle Bartley', 'Chris Basham',\n",
       "       'Michy Batshuayi', 'Jan Bednarek', 'Héctor Bellerín',\n",
       "       'Saïd Benrahma', 'Christian Benteke', 'Jóhann Berg Guðmundsson',\n",
       "       'Sander Berge', 'Steven Bergwijn', 'Ryan Bertrand',\n",
       "       'Yves Bissouma', 'Jayden Bogle', 'Willy Boly', 'Jarrod Bowen',\n",
       "       'Robbie Brady', 'Rhian Brewster', 'Josh Brownhill', 'Oliver Burke',\n",
       "       'Dan Burn', 'Gary Cahill', 'Tom Cairney', 'Dominic Calvert-Lewin',\n",
       "       'João Cancelo', 'Matty Cash', 'Timothy Castagne', 'Ivan Cavaleiro',\n",
       "       'Edinson Cavani', 'Dani Ceballos', 'Ben Chilwell', 'Ciaran Clark',\n",
       "       'Nathaniel Clyne', 'Conor Coady', 'Séamus Coleman',\n",
       "       'Aaron Connolly', 'Liam Cooper', 'Hélder Costa', 'Vladimír Coufal',\n",
       "       'Aaron Cresswell', 'Stuart Dallas', 'Scott Dann', 'Ben Davies',\n",
       "       'Tom Davies', 'Craig Dawson', 'Kevin De Bruyne',\n",
       "       'Leander Dendoncker', 'Grady Diangana', 'Raphael Dias Belloli',\n",
       "       'Rúben Dias', 'Eric Dier', 'Lucas Digne', 'Moussa Djenepo',\n",
       "       'Matt Doherty', 'Gabriel Dos Santos', 'Abdoulaye Doucouré',\n",
       "       'Lewis Dunk', 'John Egan', 'Mohamed Elneny', 'Jonny Evans',\n",
       "       'Eberechi Eze', 'Fabinho', 'Bruno Fernandes', 'Federico Fernández',\n",
       "       'Roberto Firmino', 'John Fleck', 'Phil Foden', 'Wesley Fofana',\n",
       "       'Pablo Fornals', 'Fred', 'Christian Fuchs', 'Darnell Furlong',\n",
       "       'Conor Gallagher', 'Kieran Gibbs', 'Ben Godfrey', 'André Gomes',\n",
       "       'Joe Gomez', 'Karlan Grant', 'Jack Grealish', 'Mason Greenwood',\n",
       "       'Pascal Groß', 'İlkay Gündoğan', 'Sébastien Haller',\n",
       "       'Jack Harrison', 'Kai Havertz', 'Isaac Hayden', 'Jordan Henderson',\n",
       "       'Jeff Hendrick', 'Son Heung-min', 'Rob Holding', 'Mason Holgate',\n",
       "       'Callum Hudson-Odoi', 'Pierre Højbjerg', 'Danny Ings',\n",
       "       'Branislav Ivanović', 'Alex Iwobi', 'Reece James', 'Gabriel Jesus',\n",
       "       'Raúl Jiménez', 'Joelinton', 'Curtis Jones', 'Jorginho',\n",
       "       'James Justin', 'Harry Kane', \"N'Golo Kanté\", 'Michael Keane',\n",
       "       'Max Kilman', 'Mateusz Klich', 'Robin Koch', 'Ezri Konsa',\n",
       "       'Cheikhou Kouyaté', 'Mateo Kovačić', 'Alexandre Lacazette',\n",
       "       'Adam Lallana', 'Tariq Lamptey', 'Jamaal Lascelles',\n",
       "       'Mario Lemina', 'Jamal Lewis', 'Victor Lindelöf', 'Jake Livermore',\n",
       "       'Ruben Loftus-Cheek', 'Sean Longstaff', 'Ademola Lookman',\n",
       "       'Matthew Lowton', 'David Luiz', 'Douglas Luiz', 'John Lundstram',\n",
       "       'James Maddison', 'Harry Maguire', 'Riyad Mahrez', 'Sadio Mané',\n",
       "       'Javier Manquillo', 'Solly March', 'Anthony Martial',\n",
       "       'Arthur Masuaku', 'Nemanja Matić', 'Joël Matip', 'Neal Maupay',\n",
       "       'James McArthur', 'Oliver McBurnie', 'John McGinn',\n",
       "       'David McGoldrick', 'Dwight McNeil', 'Scott McTominay', 'Ben Mee',\n",
       "       'Nampalys Mendy', 'Luka Milivojević', 'James Milner', 'Yerry Mina',\n",
       "       'Tyrone Mings', 'Tyrick Mitchell', 'Aleksandar Mitrović',\n",
       "       'Mason Mount', 'Lucas Moura', 'João Moutinho', 'Jacob Murphy',\n",
       "       'Wilfred Ndidi', 'Tanguy Ndombele', 'Pedro Neto', 'Rúben Neves',\n",
       "       'Oliver Norwood', \"Dara O'Shea\", 'Angelo Ogbonna', 'Ben Osborn',\n",
       "       'Thomas Partey', 'Nicolas Pépé', 'Matheus Pereira', 'Ayoze Pérez',\n",
       "       'Kalvin Phillips', 'Matt Phillips', 'Erik Pieters',\n",
       "       'Daniel Podence', 'Paul Pogba', 'Dennis Praet',\n",
       "       'Christian Pulisic', 'Marcus Rashford', 'Nathan Redmond',\n",
       "       'Harrison Reed', 'Sergio Reguilón', 'Bobby Reid', 'Declan Rice',\n",
       "       'Richarlison', 'Jaïro Riedewald', 'Andrew Robertson',\n",
       "       'Antonee Robinson', 'Callum Robinson', 'Jack Robinson', 'Rodri',\n",
       "       'Rodrigo', 'James Rodríguez', 'Jay Rodriguez', 'Oriol Romeu',\n",
       "       'Antonio Rüdiger', 'Allan Saint-Maximin', 'Romain Saïss',\n",
       "       'Bukayo Saka', 'Mohamed Salah', 'Davinson Sánchez',\n",
       "       'Romaine Sawyers', 'Fabian Schär', 'Jeffrey Schlupp',\n",
       "       'Nélson Semedo', 'Luke Shaw', 'Jonjo Shelvey', 'Gylfi Sigurðsson',\n",
       "       'Bernardo Silva', 'Fábio Silva', 'Thiago Silva', 'Moussa Sissoko',\n",
       "       'Emile Smith-Rowe', 'Tomáš Souček', 'Çağlar Söyüncü',\n",
       "       'Jack Stephens', 'Raheem Sterling', 'Enda Stevens', 'John Stones',\n",
       "       'Pascal Struijk', 'Matt Targett', 'James Tarkowski',\n",
       "       'Charlie Taylor', 'Kenny Tete', 'Youri Tielemans',\n",
       "       'Kieran Tierney', 'Ferrán Torres', 'Andros Townsend',\n",
       "       'Conor Townsend', 'Adama Traoré', 'Bertrand Traoré', 'Trézéguet',\n",
       "       'Leandro Trossard', 'Jamie Vardy', 'Joël Veltman',\n",
       "       'Jannik Vestergaard', 'Theo Walcott', 'Kyle Walker',\n",
       "       'Kyle Walker-Peters', 'Aaron Wan-Bissaka', 'Joel Ward',\n",
       "       'James Ward-Prowse', 'Ollie Watkins', 'Adam Webster',\n",
       "       'Danny Welbeck', 'Timo Werner', 'Ashley Westwood', 'Ben White',\n",
       "       'Georginio Wijnaldum', 'Willian', 'Callum Wilson', 'Chris Wood',\n",
       "       'Granit Xhaka', 'Wilfried Zaha', 'Andre-Frank Zambo Anguissa',\n",
       "       'Oleksandr Zinchenko', 'Hakim Ziyech', 'Kurt Zouma'], dtype=object)"
      ]
     },
     "execution_count": 188,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(df2.head())\n",
    "\n",
    "df2.Player.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [],
   "source": [
    "#create a list of 6 metrics to compare\n",
    "metrics = ['Prog','1/3','xA','Cmp%','KP','PPA']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x720 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,axes = plt.subplots(3,2,figsize=(14,10))\n",
    "fig.set_facecolor(background)\n",
    "ax.patch.set_facecolor(background)\n",
    "\n",
    "#set up our base layer\n",
    "mpl.rcParams['xtick.color'] = text_color\n",
    "mpl.rcParams['ytick.color'] = text_color\n",
    "\n",
    "#create a list of comparisons\n",
    "counter=0\n",
    "counter2=0\n",
    "met_counter = 0\n",
    "\n",
    "for i,ax in zip(df2['Player'],axes.flatten()):\n",
    "    ax.set_facecolor(background)\n",
    "    ax.grid(ls='dotted',lw=.5,color='lightgrey',axis='y',zorder=1)\n",
    "    \n",
    "    spines = ['top','bottom','left','right']\n",
    "    for x in spines:\n",
    "        if x in spines:\n",
    "            ax.spines[x].set_visible(False)\n",
    "            \n",
    "    sns.swarmplot(x=metrics[met_counter],data=df2,ax=axes[counter,counter2],zorder=1,color='#64645e')\n",
    "    ax.set_xlabel(f'{metrics[met_counter]}',c='white')\n",
    "    \n",
    "    for x in range(len(df2['Player'])):\n",
    "        #if df2['Player'][x] == 'Thiago Alcántara':\n",
    "            #ax.scatter(x=df2[metrics[met_counter]][x],y=0,s=200,c='red',zorder=2)\n",
    "        if df2['Player'][x] == 'İlkay Gündoğan':\n",
    "            ax.scatter(x=df2[metrics[met_counter]][x],y=0,s=200,c='#6CABDD',zorder=2)\n",
    "                        \n",
    "    met_counter+=1\n",
    "    if counter2 == 0:\n",
    "        counter2 = 1\n",
    "        continue\n",
    "    if counter2 == 1:\n",
    "        counter2 = 0\n",
    "        counter+=1\n",
    "        \n",
    "\n",
    "        \n",
    "s='<Ilkay Gündogan> Premier League Passing Stats'\n",
    "highlight_text.fig_text(s=s,\n",
    "                x=.25, y=.88,\n",
    "                #highlight_weights = ['bold'],\n",
    "                fontsize=22,\n",
    "                fontfamily = 'Andale Mono',\n",
    "                color = text_color,\n",
    "                highlight_colors = ['#6CABDD'],\n",
    "                va='center'\n",
    "               )\n",
    "\n",
    "fig.text(.12,.05,\"all stats per 90 / Goal Keepers and those with less than 6.5 90's played excluded\",fontsize=11, fontfamily='Andale Mono',color=text_color)\n",
    "fig.text(.12,.03,\"@mckayjohns / data via fbref.com + Statsbomb\", fontstyle='italic',fontsize=11, fontfamily='Andale Mono',color=text_color)\n",
    "\n",
    "plt.savefig('test.png',dpi=500,bbox_inches = 'tight',facecolor=background)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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