{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "40889aa6",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ddc877ad",
   "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>Team</th>\n",
       "      <th>Round 1</th>\n",
       "      <th>Round 2</th>\n",
       "      <th>Round 3</th>\n",
       "      <th>Round 4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>10</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>B</td>\n",
       "      <td>20</td>\n",
       "      <td>25</td>\n",
       "      <td>15</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>C</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "      <td>19</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>D</td>\n",
       "      <td>10</td>\n",
       "      <td>18</td>\n",
       "      <td>11</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Team  Round 1  Round 2  Round 3  Round 4\n",
       "0    A       10       20       10       26\n",
       "1    B       20       25       15       21\n",
       "2    C       12       15       19        6\n",
       "3    D       10       18       11       19"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame([['A', 10, 20, 10, 26], ['B', 20, 25, 15, 21], ['C', 12, 15, 19, 6],\n",
    "                   ['D', 10, 18, 11, 19]],\n",
    "                  columns=['Team', 'Round 1', 'Round 2', 'Round 3', 'Round 4'])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "8422fd4f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<AxesSubplot:>, <BarContainer object of 4 artists>)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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nVVBQEJ8vLy+XJJWUlOitt97Sli1bNDAwoA0bNqi7u1uLFi3S8ePH5fV63SoZgIMIHwAcl5+fL9u2b7nesiyFw2GFw2FzRQFwDed8AAAAowgfAADAKMIHAAAwivABAACMInwAAACjCB8AAMAowgcAADCK8AEAAIwifAAAAKMIHwAAwCjCBwAAMIrwAQAAjCJ8AAAAo5IePsLhsCzLSpj8fn+ydwMAAFJUmhNv+t3vfld/+tOf4vNTpkxxYjcAACAFORI+0tLSGO0AAAAjcuScjwsXLigrK0s5OTl6/vnn9c9//vOW28ZiMUWj0YQJAABMXEkPH4sWLdL+/ft17Ngx7d69W5FIRHl5ebpy5cqI21dVVSk9PT0+ZWdnJ7skAAAwjiQ9fIRCIa1evVqPPvqonn76aR0+fFiStG/fvhG3r6ioUE9PT3zq6OhIdkkAAGAcceScj5vNmDFDjz76qC5cuDDieo/HI4/H43QZAABgnHD8Ph+xWEznzp1TIBBwelcAACAFJD18vPTSS2psbFRbW5s+/vhjPfvss4pGoyopKUn2rgBMENwfCJhckv61y7/+9S/95Cc/0eeff677779fixcv1kcffaRgMJjsXQGYQLg/EDB5JD18vPPOO8l+SwCTAPcHAiYPnu0CYFwYzf2BJO4RBKQywgcA1432/kAS9wgCUhnhA4DrRnt/IIl7BAGpzPH7fADAaH3d/YEk7hEEpDJGPgCMO9wfCJjYCB8AXMf9gYDJha9dALiO+wMBkwvhA4DruD8QMLnwtQsAADCK8AEAAIwifAAAAKMIHwAAwCjCBwAAMIrwAQAAjCJ8AAAAowgfAADAKMIHAAAwivABAACMInwAAACjCB8AAMAowgcAADCK8AEAAIwifAAAAKMIHwAAwCjCBwAAMIrwAQAAjCJ8AAAAowgfAADAKMfCx5tvvqmcnBx94xvf0IIFC/SXv/zFqV0BmCDoG8Dk4Ej4qKur0+bNm7V161b97W9/05NPPqlQKKRLly45sTsAEwB9A5g8HAkfO3bs0Isvvqhf/OIX+s53vqOdO3cqOztbu3btcmJ3ACYA+gYweSQ9fFy7dk0tLS0qLCxMWF5YWKjm5uZk7w7ABEDfACaXtGS/4eeff67r16/L5/MlLPf5fIpEIsO2j8ViisVi8fmenh5JUjQaTXZprpuAhySJ40o1d3JcQ79/tm07XM2XRts3pLvsHf937LUaN5ofRI7LfZP4uEbTN5IePoZYlpUwb9v2sGWSVFVVpW3btg1bnp2d7VRprklPd7sCZ3BcqWU0x9Xb26t0g/8Rd9o3pEnUO9ZN0B9Ejiu1jOK47qRvJD18zJ49W1OmTBn210pXV9ewv2okqaKiQuXl5fH5Gzdu6IsvvtCsWbNu2XScFI1GlZ2drY6ODs2cOdP4/p3CcaUWt4/Ltm319vYqKyvLyP5G2zckeocpHFdqcfO4RtM3kh4+pk6dqgULFqi+vl4rV66ML6+vr9czzzwzbHuPxyOPx5Ow7Jvf/Gayyxq1mTNnTqgfyCEcV2px87hMjniMtm9I9A7TOK7U4tZx3WnfcORrl/Lycv30pz/V448/rh/84Af67W9/q0uXLumXv/ylE7sDMAHQN4DJw5HwsWbNGl25ckWvvfaaOjs7NW/ePB05ckTBYNCJ3QGYAOgbwOTh2AmnGzZs0IYNG5x6e8d4PB69+uqrw4ZzUx3HlVom6nF9nVTtG9LE/cw4rtSSKsdl2aaupQMAABAPlgMAAIYRPgAAgFGEDwAAYBThAwAAGEX4+Irm5mZNmTJFRUVFbpeSFKWlpbIsKz7NmjVLRUVF+uSTT9wu7a5FIhFt2rRJ3/72t+XxeJSdna3i4mKdOHHC7dLG5ObP6t5775XP59OyZcu0d+9e3bhxw+3ycBv0jdRC73Af4eMr9u7dq02bNumDDz7QpUuX3C4nKYqKitTZ2anOzk6dOHFCaWlpWr58udtl3ZX29nYtWLBAJ0+e1Pbt23XmzBkdPXpUBQUFKisrc7u8MRv6rNrb2/X++++roKBAv/rVr7R8+XINDg66XR5ugb6ROugd44SNuL6+Ptvr9dr/+Mc/7DVr1tjbtm1zu6S7VlJSYj/zzDMJy5qammxJdldXlztFJUEoFLLnzJlj9/X1DVvX3d1tvqAkGOmzsm3bPnHihC3J3r17t/mi8LXoG6mF3jE+MPJxk7q6Oj388MN6+OGH9cILL6impsbYI8VN6evr04EDB/TQQw9p1qxZbpczJl988YWOHj2qsrIyzZgxY9j68fB8j2RaunSp5s+fr3fffdftUjAC+kbqoHeMH4SPm+zZs0cvvPCCpC+HsPr6+lL2O8Cb/fGPf9R9992n++67T16vV4cOHVJdXZ3uuSc1P/6LFy/Ktm098sgjbpdizCOPPKL29na3y8AI6Bupg94xfqTuT1GSnT9/Xn/961/1/PPPS5LS0tK0Zs0a7d271+XK7l5BQYFaW1vV2tqqjz/+WIWFhQqFQvr000/dLm1Mhv6qdOOx6W6xbXtSHW+qoG+kFnrH+OHYs11SzZ49ezQ4OKg5c+bEl9m2rXvvvVfd3d361re+5WJ1d2fGjBl66KGH4vMLFixQenq6du/erddff93FysYmNzdXlmXp3LlzWrFihdvlGHHu3Dnl5OS4XQa+gr6RWugd4wcjH5IGBwe1f/9+vfHGG/Gk39raqr///e8KBoM6cOCA2yUmlWVZuueeezQwMOB2KWOSkZGhH/7wh/rNb36j/v7+YeuvXr1qvigHnTx5UmfOnNHq1avdLgU3oW+kHnrH+MHIh778brO7u1svvvii0tPTE9Y9++yz2rNnjzZu3OhSdXcvFospEolIkrq7u1VdXa2+vj4VFxe7XNnYvfnmm8rLy9P3v/99vfbaa/re976nwcFB1dfXa9euXTp37pzbJY7J0Gd1/fp1ffbZZzp69Kiqqqq0fPly/exnP3O7PNyEvpGa6B3jhFuX2Ywny5cvt3/0ox+NuK6lpcWWZLe0tBiuKjlKSkpsSfHJ6/XaCxcutH//+9+7Xdpdu3z5sl1WVmYHg0F76tSp9pw5c+wf//jH9p///Ge3SxuTmz+rtLQ0+/7777effvppe+/evfb169fdLg9fQd9IXfQO91m2PcGuCQMAAOMa53wAAACjCB8AAMAowgcAADCK8AEAAIwifAAAAKMIHwAAwCjCBwAAMIrwAQAAjCJ8AAAAowgfAADAqHH3YLkbN27o8uXL8nq9sizL7XKAScm2bfX29iorK0v33JMaf6PQOwB3jaZvjLvwcfnyZWVnZ7tdBgBJHR0deuCBB9wu447QO4Dx4U76xrgLH16vV9KXxc+cOdPlaoDJKRqNKjs7O/77mAroHYC7RtM3xl34GBounTlzJg0EcFkqfX1B7wDGhzvpG6nxZS4AAJgwCB8AAMAowgcAADCK8AEAAIwifAAAAKPG3dUumNisbalz9YT9qu12CXBKCl3FI5ufQ0w8jHwAAACjCB8AHFdVVaWFCxfK6/UqMzNTK1as0Pnz5xO2KS0tlWVZCdPixYtdqhiAkwgfABzX2NiosrIyffTRR6qvr9fg4KAKCwvV39+fsF1RUZE6Ozvj05EjR1yqGICTOOcDgOOOHj2aMF9TU6PMzEy1tLToqaeeii/3eDzy+/2mywNgGCMfAIzr6emRJGVkZCQsb2hoUGZmpubOnat169apq6vrlu8Ri8UUjUYTJgCpgfABwCjbtlVeXq4nnnhC8+bNiy8PhUI6cOCATp48qTfeeEOnTp3S0qVLFYvFRnyfqqoqpaenxyeeaAukDsu2x9d1XNFoVOnp6erp6eHhUBMQl9qmBid/D8vKynT48GF98MEHt33sdmdnp4LBoN555x2tWrVq2PpYLJYQTIaeqHlHNXOpLZB0o+kbnPMBwJhNmzbp0KFDampqum3wkKRAIKBgMKgLFy6MuN7j8cjj8ThRJgCHET4AOM62bW3atEnvvfeeGhoalJOT87WvuXLlijo6OhQIBAxUCMAkzvkA4LiysjL97ne/U21trbxeryKRiCKRiAYGBiRJfX19eumll/Thhx+qvb1dDQ0NKi4u1uzZs7Vy5UqXqweQbIx8AHDcrl27JEn5+fkJy2tqalRaWqopU6bozJkz2r9/v65evapAIKCCggLV1dXJ6/W6UDEAJxE+ADju685rnzZtmo4dO2aoGgBu42sXAABgFOEDAAAYRfgAAABGET4AAIBRhA8AAGAU4QMAABhF+AAAAEYRPgAAgFGEDwAAYBThAwAAGEX4AAAARhE+AACAUYQPAABgFOEDAAAYRfgAAABGET4AAIBRhA8AAGDUqMNHU1OTiouLlZWVJcuydPDgwYT1paWlsiwrYVq8eHGy6gUAACkubbQv6O/v1/z58/Xzn/9cq1evHnGboqIi1dTUxOenTp069goBAHfGstyu4M7ZttsVwEWjDh+hUEihUOi223g8Hvn9/jEXBQAAJi5HzvloaGhQZmam5s6dq3Xr1qmrq+uW28ZiMUWj0YQJwMRSVVWlhQsXyuv1KjMzUytWrND58+cTtrFtW+FwWFlZWZo2bZry8/N19uxZlyoG4KRRj3x8nVAopOeee07BYFBtbW165ZVXtHTpUrW0tMjj8QzbvqqqStu2bUt2GSnP2pY6w6f2qwyf4vYaGxtVVlamhQsXanBwUFu3blVhYaH++7//WzNmzJAkbd++XTt27NBbb72luXPn6vXXX9eyZct0/vx5eb1el48AQDJZtj32L94sy9J7772nFStW3HKbzs5OBYNBvfPOO1q1atWw9bFYTLFYLD4fjUaVnZ2tnp4ezZw5c6ylpbyJGj4m6nFNNNFoVOnp6Y79Hv7v//6vMjMz1djYqKeeekq2bSsrK0ubN2/Wv//7v0v6sjf4fD79+te/1vr165Nb80Q9N2KiHhdSwmh+Bx2/1DYQCCgYDOrChQsjrvd4PJo5c2bCBGBi6+npkSRlZGRIktra2hSJRFRYWBjfxuPxaMmSJWpubh7xPfjKFkhdjoePK1euqKOjQ4FAwOldAUgBtm2rvLxcTzzxhObNmydJikQikiSfz5ewrc/ni6/7qqqqKqWnp8en7OxsZwsHkDSjDh99fX1qbW1Va2urpC//YmltbdWlS5fU19enl156SR9++KHa29vV0NCg4uJizZ49WytXrkx27QBS0MaNG/XJJ5/o7bffHrbO+srXBrZtD1s2pKKiQj09PfGpo6PDkXoBJN+oTzg9ffq0CgoK4vPl5eWSpJKSEu3atUtnzpzR/v37dfXqVQUCARUUFKiuro4TxgBo06ZNOnTokJqamvTAAw/Elw9dmh+JRBJGSbu6uoaNhgzxeDwjnsQOYPwbdfjIz8/X7c5RPXbs2F0VBGDisW1bmzZt0nvvvaeGhgbl5OQkrM/JyZHf71d9fb0ee+wxSdK1a9fU2NioX//6126UDMBBSb/UFgC+qqysTLW1tfrDH/4gr9cbP48jPT1d06ZNk2VZ2rx5syorK5Wbm6vc3FxVVlZq+vTpWrt2rcvVA0g2wgcAx+3atUvSlyOnN6upqVFpaakkacuWLRoYGNCGDRvU3d2tRYsW6fjx43xlC0xAhA8AjruT2wlZlqVwOKxwOOx8QcB4MInvy+L4pbYAAAA3I3wAAACjCB8AAMAowgcAADCK8AEAAIwifAAAAKMIHwAAwCjCBwAAMIrwAQAAjCJ8AAAAowgfAADAKMIHAAAwivABAACMInwAAACjCB8AAMAowgcAADCK8AEAAIwifAAAAKMIHwAAwCjCBwAAMIrwAcBxTU1NKi4uVlZWlizL0sGDBxPWl5aWyrKshGnx4sXuFAvAcYQPAI7r7+/X/PnzVV1dfcttioqK1NnZGZ+OHDlisEIAJqW5XQCAiS8UCikUCt12G4/HI7/fb6giAG5i5APAuNDQ0KDMzEzNnTtX69atU1dX1223j8ViikajCROA1MDIB5AE1jbL7RLumP2q7XYJw4RCIT333HMKBoNqa2vTK6+8oqVLl6qlpUUej2fE11RVVWnbtm2GKwWQDIQPAK5bs2ZN/N/z5s3T448/rmAwqMOHD2vVqlUjvqaiokLl5eXx+Wg0quzsbMdrBXD3CB8Axp1AIKBgMKgLFy7cchuPx3PLUREA4xvnfAAYd65cuaKOjg4FAgG3SwHggFGHj6+7Xt+2bYXDYWVlZWnatGnKz8/X2bNnk1UvgBTU19en1tZWtba2SpLa2trU2tqqS5cuqa+vTy+99JI+/PBDtbe3q6GhQcXFxZo9e7ZWrlzpbuEAHDHq8PF11+tv375dO3bsUHV1tU6dOiW/369ly5apt7f3rosFkJpOnz6txx57TI899pgkqby8XI899pj+8z//U1OmTNGZM2f0zDPPaO7cuSopKdHcuXP14Ycfyuv1ulw5ACeM+pyP212vb9u2du7cqa1bt8ZPEtu3b598Pp9qa2u1fv36u6sWQErKz8+Xbd/6Kptjx44ZrAaA25J6zkdbW5sikYgKCwvjyzwej5YsWaLm5uYRX8O1+gAATC5JvdolEolIknw+X8Jyn8+nTz/9dMTX3O21+txfAQCA1OLI1S6WlRgIbNsetmxIRUWFenp64lNHR4cTJQEAgHEiqSMfQ89liEQiCZfIdXV1DRsNGcK1+gAATC5JHfnIycmR3+9XfX19fNm1a9fU2NiovLy8ZO4KAACkqFGPfPT19enixYvx+aHr9TMyMvTggw9q8+bNqqysVG5urnJzc1VZWanp06dr7dq1SS0cAACkplGHj9OnT6ugoCA+P/RshZKSEr311lvasmWLBgYGtGHDBnV3d2vRokU6fvw41+sDAABJYwgfX3e9vmVZCofDCofDd1MXAACYoHi2CwAAMIrwAQAAjCJ8AAAAowgfAADAKMIHAAAwivABAACMInwAAACjCB8AAMAowgcAADCK8AEAAIwifAAAAKMIHwAAwCjCBwDHNTU1qbi4WFlZWbIsSwcPHkxYb9u2wuGwsrKyNG3aNOXn5+vs2bPuFAvAcYQPAI7r7+/X/PnzVV1dPeL67du3a8eOHaqurtapU6fk9/u1bNky9fb2Gq4UgAlpbhcAYOILhUIKhUIjrrNtWzt37tTWrVu1atUqSdK+ffvk8/lUW1ur9evXmywVgAGMfABwVVtbmyKRiAoLC+PLPB6PlixZoubm5lu+LhaLKRqNJkwAUgPhA4CrIpGIJMnn8yUs9/l88XUjqaqqUnp6enzKzs52tE4AyUP4ADAuWJaVMG/b9rBlN6uoqFBPT0986ujocLpEAEnCOR8AXOX3+yV9OQISCATiy7u6uoaNhtzM4/HI4/E4Xh+A5GPkA4CrcnJy5Pf7VV9fH1927do1NTY2Ki8vz8XKADiFkQ8Ajuvr69PFixfj821tbWptbVVGRoYefPBBbd68WZWVlcrNzVVubq4qKys1ffp0rV271sWqATiF8AHAcadPn1ZBQUF8vry8XJJUUlKit956S1u2bNHAwIA2bNig7u5uLVq0SMePH5fX63WrZAAOInwAcFx+fr5s277lesuyFA6HFQ6HzRUFwDWc8wEAAIwifAAAAKMIHwAAwCjCBwAAMIrwAQAAjCJ8AAAAowgfAADAKMIHAAAwKunhIxwOy7KshGnowVEAAACO3OH0u9/9rv70pz/F56dMmeLEbgAAQApyJHykpaUx2gEAAEbkyDkfFy5cUFZWlnJycvT888/rn//85y23jcViikajCRMAAJi4kh4+Fi1apP379+vYsWPavXu3IpGI8vLydOXKlRG3r6qqUnp6enzKzs5OdkkAAGAcSXr4CIVCWr16tR599FE9/fTTOnz4sCRp3759I25fUVGhnp6e+NTR0ZHskgAAwDjiyDkfN5sxY4YeffRRXbhwYcT1Ho9HHo/H6TIAAMA44fh9PmKxmM6dO6dAIOD0rgAAQApIevh46aWX1NjYqLa2Nn388cd69tlnFY1GVVJSkuxdAQCAFJT0r13+9a9/6Sc/+Yk+//xz3X///Vq8eLE++ugjBYPBZO8KADAZWJbbFdw523a7gpSQ9PDxzjvvJPstAQDABMKzXQC4jscyAJOL41e7AMCd4LEMwORB+AAwLvBYBmDy4GsXAOPCaB7LACC1MfIBwHVDj2WYO3euPvvsM73++uvKy8vT2bNnNWvWrBFfE4vFFIvF4vM8FwpIHYx8AHDdaB/LIPFcKCCVET4AjDtf91gGiedCAamMr10AjDtDj2V48sknb7kNz4UCUhcjHwBcx2MZgMmFkQ8AruOxDMDkQvgA4DoeywBMLnztAgAAjCJ8AAAAowgfAADAKMIHAAAwivABAACMInwAAACjCB8AAMAowgcAADCK8AEAAIwifAAAAKMIHwAAwCjCBwAAMIrwAQAAjCJ8AAAAowgfAADAKMIHAAAwivABAACMInwAAACjCB8AAMAowgcAADDKsfDx5ptvKicnR9/4xje0YMEC/eUvf3FqVwAmCPoGMDk4Ej7q6uq0efNmbd26VX/729/05JNPKhQK6dKlS07sDsAEQN8AJg9HwseOHTv04osv6he/+IW+853vaOfOncrOztauXbuc2B2ACYC+AUweacl+w2vXrqmlpUX/8R//kbC8sLBQzc3Nw7aPxWKKxWLx+Z6eHklSNBq9sx3+v7HXatodH5PEcY0Dk/m4hraxbdvpciSNvm9ISegdqWKiHc8Qjiu1JLlvJD18fP7557p+/bp8Pl/Ccp/Pp0gkMmz7qqoqbdu2bdjy7OzsZJfmuvT/k+52CY7guFLLaI6rt7dX6enO/z+Mtm9Ik6h3GPj/dwXHlVpGcVx30jeSHj6GWJaVMG/b9rBlklRRUaHy8vL4/I0bN/TFF19o1qxZI27vtGg0quzsbHV0dGjmzJnG9+8Ujiu1uH1ctm2rt7dXWVlZRvd7p31DoneYwnGlFjePazR9I+nhY/bs2ZoyZcqwv1a6urqG/VUjSR6PRx6PJ2HZN7/5zWSXNWozZ86cUD+QQziu1OLmcZkY8Rgy2r4h0TtM47hSi1vHdad9I+knnE6dOlULFixQfX19wvL6+nrl5eUle3cAJgD6BjC5OPK1S3l5uX7605/q8ccf1w9+8AP99re/1aVLl/TLX/7Sid0BmADoG8Dk4Uj4WLNmja5cuaLXXntNnZ2dmjdvno4cOaJgMOjE7pLK4/Ho1VdfHTacm+o4rtQyUY/rdlK5b0gT9zPjuFJLqhyXZZu6lg4AAEA82wUAABhG+AAAAEYRPgAAgFGEDwAAYBTh4yuam5s1ZcoUFRUVuV1KUpSWlsqyrPg0a9YsFRUV6ZNPPnG7tLsWiUS0adMmffvb35bH41F2draKi4t14sQJt0sbk5s/q3vvvVc+n0/Lli3T3r17dePGDbfLw23QN1ILvcN9hI+v2Lt3rzZt2qQPPvhgwjzKu6ioSJ2dners7NSJEyeUlpam5cuXu13WXWlvb9eCBQt08uRJbd++XWfOnNHRo0dVUFCgsrIyt8sbs6HPqr29Xe+//74KCgr0q1/9SsuXL9fg4KDb5eEW6Bupg94xTtiI6+vrs71er/2Pf/zDXrNmjb1t2za3S7prJSUl9jPPPJOwrKmpyZZkd3V1uVNUEoRCIXvOnDl2X1/fsHXd3d3mC0qCkT4r27btEydO2JLs3bt3my8KX4u+kVroHeMDIx83qaur08MPP6yHH35YL7zwgmpqaow9UtyUvr4+HThwQA899JBmzZrldjlj8sUXX+jo0aMqKyvTjBkzhq0fD8/3SKalS5dq/vz5evfdd90uBSOgb6QOesf4Qfi4yZ49e/TCCy9I+nIIq6+vL2W/A7zZH//4R913332677775PV6dejQIdXV1emee1Lz47948aJs29YjjzzidinGPPLII2pvb3e7DIyAvpE66B3jR+r+FCXZ+fPn9de//lXPP/+8JCktLU1r1qzR3r17Xa7s7hUUFKi1tVWtra36+OOPVVhYqFAopE8//dTt0sZk6K9KNx6b7hb7No+Wh3voG6mF3jF+OPJsl1S0Z88eDQ4Oas6cOfFltm3r3nvvVXd3t771rW+5WN3dmTFjhh566KH4/IIFC5Senq7du3fr9ddfd7GyscnNzZVlWTp37pxWrFjhdjlGnDt3Tjk5OW6Xga+gb6QWesf4wciHpMHBQe3fv19vvPFGPOm3trbq73//u4LBoA4cOOB2iUllWZbuueceDQwMuF3KmGRkZOiHP/yhfvOb36i/v3/Y+qtXr5ovykEnT57UmTNntHr1ardLwU3oG6mH3jF+MPKhL7/b7O7u1osvvqj09PSEdc8++6z27NmjjRs3ulTd3YvFYopEIpKk7u5uVVdXq6+vT8XFxS5XNnZvvvmm8vLy9P3vf1+vvfaavve972lwcFD19fXatWuXzp0753aJYzL0WV2/fl2fffaZjh49qqqqKi1fvlw/+9nP3C4PN6FvpCZ6xzjh1mU248ny5cvtH/3oRyOua2lpsSXZLS0thqtKjpKSEltSfPJ6vfbChQvt3//+926XdtcuX75sl5WV2cFg0J46dao9Z84c+8c//rH95z//2e3SxuTmzyotLc2+//777aefftreu3evff36dbfLw1fQN1IXvcN9lm1PsGvCAADAuMY5HwAAwCjCBwAAMIrwAQAAjCJ8AAAAowgfAADAKMIHAAAwivABAACMInwAAACjCB8AAMAowgcAADCK8AEAAIwifAAAAKP+P9ZMcWoLG/P2AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 640x480 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(2,2,1),plt.bar(df['Team'],df['Round 1'],color='blue')\n",
    "plt.subplot(2,2,2),plt.bar(df['Team'],df['Round 2'],color='orange')\n",
    "plt.subplot(2,2,3),plt.bar(df['Team'],df['Round 3'],color='green')\n",
    "plt.subplot(2,2,4),plt.bar(df['Team'],df['Round 4'],color='red')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "1634748c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Team'>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot(kind='bar',x='Team',stacked=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "b5703332",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "5e52f35f",
   "metadata": {},
   "outputs": [],
   "source": [
    "width=0.25\n",
    "n=3\n",
    "ind=np.arange(n)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "3fcaab03",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xv=[8,9,11]\n",
    "bar1=plt.bar(ind,xv,width,color='r')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "c8e809a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "yv=[15,7,19]\n",
    "bar2=plt.bar(ind+width,yv,width,color='g')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "75e5fa3f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "zv=[4,9,8]\n",
    "bar3=plt.bar(ind+width*2,zv,width,color='b')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "a98c29e6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x162802032e0>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Vq1fb9hcXFysxMVEPP/xwiTq8vb1t//8fQxUAANcDAchk/Pz81KRJk8u227Jli+Li4tS/f39Jv4WZgwcPKjIy0q7dsGHDNGvWLB07dkydO3dWeHi4bV/Lli114MCBK3o9AACuJwIQStWkSRMtW7ZMW7duVc2aNTVz5kxlZ2eXCED9+vVTQkKCFi5cqJSUFLt9L730knr27Knw8HD17t1bbm5u2rt3rzIyMmzf9irLoUOHdP78eWVnZ+vXX39Venq6JKlZs2aqVq2aQ8cKADAfvgWGUk2cOFEtW7ZUbGysOnTooODgYD344IMl2gUEBCg+Pl7+/v4l9sfGxio1NVXr169X69atFRMTo5kzZ6pBgwaXff1hw4apRYsWWrBggf7v//5PLVq0UIsWLXT8+HEHjRAAYGYWwzCYKv4nVqtVgYGBysnJUUBAgN2+vLw8ZWZmqlGjRnbzWMysS5cuioyM1Jw5c5xaB38bANcD3wJzXeV9fv8Zt8BQYadPn9a6deu0YcMGzZs3z9nlAABwxQhAqLCWLVvqzJkzmj59upo2berscgAAuGIEIFTYzz//7OwSAACoECZBAwAA0yEAAQAA0yEAAQAA0yEAAQAA0yEAAQAA0yEAAQAA0yEAQZKUlpYmi8Wis2fPOrsUAAAqHc8BcqDr/Xj0q33U+eDBg/Xee+9Jkjw8PBQeHq6HH35YiYmJlVFehe3Zs0fTpk3T119/rZMnT6phw4Z68skn9eyzzzq7NADADYIAZDLdunVTcnKyCgoKtGXLFg0bNky5ubnq06ePs0uTJBUUFGjnzp2qU6eOPvjgA4WHh2vr1q0aMWKE3N3d9cwzzzi7RADADYBbYCbj5eWl4OBghYeHq2/fvurXr59WrlxZot2pU6f0+OOPq169evL19VVUVJQWL15s25+SkqLatWsrPz/frl98fLwGDhxoW1+9erWio6Pl7e2tiIgIJSYmqrCw0LbfYrFo/vz5iouLk5+fn6ZMmaKhQ4dqzpw5uu+++xQREaH+/ftryJAhWr58uePfEACAKRGATM7Hx0cFBQUltufl5Sk6Olqpqan6/vvvNWLECA0YMEDbt2+XJPXu3VtFRUVatWqVrc/JkyeVmpqqIUOGSJK++OIL9e/fX6NHj9a+ffu0YMECLVq0SFOnTrV7rUmTJikuLk4ZGRkaOnRoqXXm5OSoVq1ajho2AMDkCEAm9u9//1sfffSROnXqVGJfWFiYEhISdOeddyoiIkKjRo1SbGysli5dKum34NS3b18lJyfb+nz44YeqV6+eOnToIEmaOnWqxo8fr0GDBikiIkJdunTRyy+/rAULFti9Vt++fTV06FBFRESoQYMGJWrZtm2bPvnkE/31r3914OgBAGbGHCCTSU1Nlb+/vwoLC1VQUKC4uDjNnTtX+/bts2tXVFSkadOmacmSJTp27Jjy8/OVn58vPz8/W5vhw4erdevWOnbsmMLCwpScnKzBgwfLYvltMvjOnTv13Xff2V3xKSoqUl5eni5cuCBfX19JUqtWrcqs94cfflBcXJxeeukldenSxZFvBQDAxJx6BWjz5s3q1auXQkNDZbFYSsxFsVgspS6vvvpqmcdctGhRqX3y8vIqeTRVQ8eOHZWenq4DBw4oLy9Py5cvV926dUu0mzFjhmbNmqVx48Zpw4YNSk9PV2xsrC5evGhr06JFCzVv3lwpKSnatWuXMjIyNHjwYNv+4uJiJSYmKj093bZkZGTo4MGD8vb2trX7Y6j6o3379un+++/X8OHD9fe//91xbwIAwPScegUoNzdXzZs315AhQxQfH19if1ZWlt36559/rieeeKLUtn8UEBCgAwcO2G374weumfn5+alJkyaXbbdlyxbFxcWpf//+kn4LMwcPHlRkZKRdu2HDhmnWrFk6duyYOnfurPDwcNu+li1b6sCBA1f0en/2ww8/6P7779egQYNKzBkCAOBaOTUAde/eXd27dy9zf3BwsN36p59+qo4dOyoiIqLc41oslhJ9cXWaNGmiZcuWaevWrapZs6Zmzpyp7OzsEgGoX79+SkhI0MKFC5WSkmK376WXXlLPnj0VHh6u3r17y83NTXv37lVGRoamTJlS5mv/8MMP6tixo7p27aqxY8cqOztbkuTu7q46deo4frAAANOpMpOgf/nlF3322Wd64oknLtv2/PnzatCggerVq6eePXtq9+7d16HCG8vEiRPVsmVLxcbGqkOHDgoODtaDDz5Yol1AQIDi4+Pl7+9fYn9sbKxSU1O1fv16tW7dWjExMZo5c2apE53/aOnSpfrf//6nDz/8UCEhIbaldevWDhwhAMDMLIZhXN3jhCuJxWLRihUrSv2QlaRXXnlF06ZN0/Hjx8u9nfXtt9/q0KFDioqKktVq1euvv641a9Zoz549uvnmm0vtc2mC7yVWq1Xh4eHKyclRQECAXdu8vDxlZmaqUaNG3Fb7/7p06aLIyEjNmTPHqXXwtwFwPVzvp/5XxNX+UsCNwmq1KjAwsNTP7z+rMt8Ce/fdd9WvX7/LfrDFxMQoJibGtt6uXTu1bNlSc+fOLfMDOikpyeV+DqIqOH36tNatW6cNGzZo3rx5zi4HAIArViUC0JYtW3TgwAEtWbLkqvu6ubmpdevWOnjwYJltJkyYoLFjx9rWL10BQvlatmypM2fOaPr06WratKmzywEA4IpViQD0zjvvKDo6Ws2bN7/qvoZhKD09XVFRUWW28fLykpeX17WUaEo///yzs0sAAKBCnBqAzp8/r0OHDtnWMzMzlZ6erlq1aql+/fqSfrsas3TpUs2YMaPUYwwcOFBhYWFKSkqSJCUmJiomJkY333yzrFar5syZo/T0dL3xxhuVPyAAAFAlODUA7dixQx07drStX7oNNWjQIC1atEiS9PHHH8swDD3++OOlHuPIkSNyc/v9y2xnz57ViBEjlJ2drcDAQLVo0UKbN2/WXXfdVXkDAQAAVYrLfAvMlZQ3i5xvGrku/jYArge+Bea6ruZbYFXmOUAAAACOQgACAACmQwACAACmQwCCJCktLU0Wi0Vnz551dikAAFQ6ApADWSzXd7lagwcPlsVikcVikaenpyIiIpSQkKDc3FzHvxnX4NSpU+rWrZtCQ0Pl5eWl8PBwPfPMM7Jarc4uDQBwg6gSD0KE43Tr1k3JyckqKCjQli1bNGzYMOXm5qpPnz7OLk2SVFBQIDc3N8XFxWnKlCmqU6eODh06pJEjR+r06dP66KOPnF0iAOAGwBUgk/Hy8lJwcLDCw8PVt29f9evXTytXrizR7tSpU3r88cdVr149+fr6KioqSosXL7btT0lJUe3ate1+RFaS4uPjNXDgQNv66tWrFR0dLW9vb0VERCgxMVGFhYW2/RaLRfPnz1dcXJz8/Pw0ZcoU1axZU0899ZRatWqlBg0aqFOnTnr66ae1ZcsWx78hAABTIgCZnI+PjwoKCkpsz8vLU3R0tFJTU/X9999rxIgRGjBggLZv3y5J6t27t4qKirRq1Spbn5MnTyo1NVVDhgyRJH3xxRfq37+/Ro8erX379mnBggVatGiRpk6davdakyZNUlxcnDIyMjR06NAStRw/flzLly/Xfffd58ihAwBMjABkYv/+97/10UcfqVOnTiX2hYWFKSEhQXfeeaciIiI0atQoxcbGaunSpZJ+C059+/ZVcnKyrc+HH36oevXqqUOHDpKkqVOnavz48Ro0aJAiIiLUpUsXvfzyy1qwYIHda/Xt21dDhw5VRESEGjRoYNv++OOPy9fXV2FhYQoICNDbb79dCe8CAMCMCEAmk5qaKn9/f3l7e6tNmzZq37695s6dW6JdUVGRpk6dqjvuuEO1a9eWv7+/1q1bpyNHjtjaDB8+XOvWrdOxY8ckScnJybaJ1pK0c+dO/eMf/5C/v79tGT58uLKysnThwgXbcVq1alVqrbNmzdKuXbu0cuVK/fjjj7afSgEA4FoxCdpkOnbsqLfeekuenp4KDQ2Vp6enJGnfvn127WbMmKFZs2Zp9uzZioqKkp+fn8aMGaOLFy/a2rRo0ULNmzdXSkqKYmNjlZGRodWrV9v2FxcXKzExUQ8//HCJOv74UxV+fn6l1hocHKzg4GDdeuutql27tu69915NnDhRISEh1/QeAABAADIZPz8/NWnS5LLttmzZori4OPXv31/Sb2Hm4MGDioyMtGs3bNgwzZo1S8eOHVPnzp0VHh5u29eyZUsdOHDgil7vci79ZN2fJ10DAFARBCCUqkmTJlq2bJm2bt2qmjVraubMmcrOzi4RgPr166eEhAQtXLhQKSkpdvteeukl9ezZU+Hh4erdu7fc3Ny0d+9eZWRkaMqUKWW+9po1a/TLL7+odevW8vf31759+zRu3Di1a9dODRs2rIzhAgBMhjlAKNXEiRPVsmVLxcbGqkOHDgoODtaDDz5Yol1AQIDi4+Pl7+9fYn9sbKxSU1O1fv16tW7dWjExMZo5c6bdROfS+Pj4aOHChbrnnnsUGRmpMWPGqGfPnkpNTXXgCAEAZmYxLt1bgI3ValVgYKBycnIUEBBgty8vL0+ZmZlq1KiR3TwWM+vSpYsiIyM1Z84cp9bB3wbA9WBJrMCj+K8zY5I5P9rL+/z+M26BocJOnz6tdevWacOGDZo3b56zywEA4IoRgFBhLVu21JkzZzR9+nQ1bdrU2eUAAHDFCECosJ9//tnZJQAAUCFMggYAAKZDAKog5o67Hv4mAIArRQC6SpeenPzHn3KAa7j0N7n0NwIAoCzMAbpK7u7uqlGjhk6cOCFJ8vX1tf32FZzDMAxduHBBJ06cUI0aNeTu7u7skgAALo4AVAHBwcGSZAtBcA01atSw/W0AACgPAagCLBaLQkJCVLduXRUUFDi7HOi3215c+QEAXCkC0DVwd3fnQxcAgCqISdAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0nBqANm/erF69eik0NFQWi0UrV6602z948GBZLBa7JSYm5rLHXbZsmZo1ayYvLy81a9ZMK1asqKQRAACAqsipASg3N1fNmzfXvHnzymzTrVs3ZWVl2ZY1a9aUe8xt27apT58+GjBggPbs2aMBAwbo0Ucf1fbt2x1dPgAAqKKc+mvw3bt3V/fu3ctt4+XlpeDg4Cs+5uzZs9WlSxdNmDBBkjRhwgRt2rRJs2fP1uLFi6+pXgAAcGNw+TlAaWlpqlu3rm655RYNHz5cJ06cKLf9tm3b1LVrV7ttsbGx2rp1a5l98vPzZbVa7RYAAHDjcuoVoMvp3r27evfurQYNGigzM1MTJ07U/fffr507d8rLy6vUPtnZ2QoKCrLbFhQUpOzs7DJfJykpSYmJiQ6tvaqzJFqcXcJlGZMMZ5cAAKiiXDoA9enTx/b/33777WrVqpUaNGigzz77TA8//HCZ/SwW+w9vwzBKbPujCRMmaOzYsbZ1q9Wq8PDwa6gcAAC4MpcOQH8WEhKiBg0a6ODBg2W2CQ4OLnG158SJEyWuCv2Rl5dXmVeUAADAjcfl5wD90alTp3T06FGFhISU2aZNmzZav3693bZ169apbdu2lV0eAACoIpx6Bej8+fM6dOiQbT0zM1Pp6emqVauWatWqpcmTJys+Pl4hISH6+eef9cILL+imm27SQw89ZOszcOBAhYWFKSkpSZL07LPPqn379po+fbri4uL06aef6ssvv9TXX3993ccHAABck1MD0I4dO9SxY0fb+qV5OIMGDdJbb72ljIwMpaSk6OzZswoJCVHHjh21ZMkSVa9e3dbnyJEjcnP7/UJW27Zt9fHHH+vvf/+7Jk6cqMaNG2vJkiW6++67r9/AAACAS7MYhsFXaf7EarUqMDBQOTk5CggIcHY5TsG3wACgdPz76Lqu5vO7Ss0BAgAAcAQCEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB2nBqDNmzerV69eCg0NlcVi0cqVK237CgoK9PzzzysqKkp+fn4KDQ3VwIEDdfz48XKPuWjRIlkslhJLXl5eJY8GAABUFU4NQLm5uWrevLnmzZtXYt+FCxe0a9cuTZw4Ubt27dLy5cv1f//3f/rLX/5y2eMGBAQoKyvLbvH29q6MIQAAgCrIw5kv3r17d3Xv3r3UfYGBgVq/fr3dtrlz5+quu+7SkSNHVL9+/TKPa7FYFBwc7NBaAQDAjaNKzQHKycmRxWJRjRo1ym13/vx5NWjQQPXq1VPPnj21e/fuctvn5+fLarXaLQAA4MZVZQJQXl6exo8fr759+yogIKDMdrfeeqsWLVqkVatWafHixfL29la7du108ODBMvskJSUpMDDQtoSHh1fGEAAAgIuoEgGooKBAjz32mIqLi/Xmm2+W2zYmJkb9+/dX8+bNde+99+qTTz7RLbfcorlz55bZZ8KECcrJybEtR48edfQQAACAC3HqHKArUVBQoEcffVSZmZnasGFDuVd/SuPm5qbWrVuXewXIy8tLXl5e11oqAACoIlz6CtCl8HPw4EF9+eWXql279lUfwzAMpaenKyQkpBIqBAAAVZFTrwCdP39ehw4dsq1nZmYqPT1dtWrVUmhoqB555BHt2rVLqampKioqUnZ2tiSpVq1aqlatmiRp4MCBCgsLU1JSkiQpMTFRMTExuvnmm2W1WjVnzhylp6frjTfeuP4DBAAALsmpAWjHjh3q2LGjbX3s2LGSpEGDBmny5MlatWqVJOnOO++067dx40Z16NBBknTkyBG5uf1+Ievs2bMaMWKEsrOzFRgYqBYtWmjz5s266667KncwAACgyrAYhmE4uwhXY7VaFRgYqJycnKuec3SjsCRanF3CZRmTOHUBXH/8++i6rubz26XnAAEAAFQGAhAAADAdAhAAADAdAhAAADAdAhAAADAdAhAAADAdAhAAADAdAhAAADAdAhAAADAdAhAAADAdAhAAADAdAhAAADAdAhAAADAdAhAAADAdAhAAADAdAhAAADAdAhAAADAdAhAAADAdAhAAADAdhwQgq9WqlStXav/+/Y44HAAAQKWqUAB69NFHNW/ePEnSr7/+qlatWunRRx/VHXfcoWXLljm0QAAAAEerUADavHmz7r33XknSihUrZBiGzp49qzlz5mjKlCkOLRAAYCIWi+svuCFUKADl5OSoVq1akqS1a9cqPj5evr6+euCBB3Tw4EGHFggAAOBoFQpA4eHh2rZtm3Jzc7V27Vp17dpVknTmzBl5e3s7tEAAAABH86hIpzFjxqhfv37y9/dX/fr11aFDB0m/3RqLiopyZH0AAAAOV6EA9PTTT+uuu+7S0aNH1aVLF7m5/XYhKSIigjlAAADA5VUoAElSq1atdMcddygzM1ONGzeWh4eHHnjgAUfWBgAAUCkqNAfowoULeuKJJ+Tr66vbbrtNR44ckSSNHj1a06ZNc2iBAAAAjlahADRhwgTt2bNHaWlpdpOeO3furCVLljisOAAAgMpQoVtgK1eu1JIlSxQTEyPLH56J0KxZM/34448OKw4AAKAyVOgK0P/+9z/VrVu3xPbc3Fy7QAQAAOCKKhSAWrdurc8++8y2fin0LFy4UG3atHFMZQAAAJWkQrfAkpKS1K1bN+3bt0+FhYV6/fXX9cMPP2jbtm3atGmTo2sEAABwqApdAWrbtq22bt2qCxcuqHHjxlq3bp2CgoK0bds2RUdHO7pGAAAAh7rqK0AFBQUaMWKEJk6cqPfee68yagIAAKhUV30FyNPTUytWrHDIi2/evFm9evVSaGioLBaLVq5cabffMAxNnjxZoaGh8vHxUYcOHfTDDz9c9rjLli1Ts2bN5OXlpWbNmjmsXgAAcGOo0C2whx56qERYqYjc3Fw1b95c8+bNK3X/K6+8opkzZ2revHn67rvvFBwcrC5duujcuXNlHnPbtm3q06ePBgwYoD179mjAgAF69NFHtX379muuFwAA3BgshmEYV9tp6tSpeu2119SpUydFR0fLz8/Pbv/o0aOvvhCLRStWrNCDDz4o6berP6GhoRozZoyef/55SVJ+fr6CgoI0ffp0/fWvfy31OH369JHVatXnn39u29atWzfVrFlTixcvvqJarFarAgMDlZOTo4CAgKsey43Akuj6jzMwJl31qQvA1VWBR6lYJju7gssz67+PV/P5XaFvgb399tuqUaOGdu7cqZ07d9rts1gsFQpAf5aZmans7Gx17drVts3Ly0v33Xeftm7dWmYA2rZtm5577jm7bbGxsZo9e3aZr5Wfn6/8/HzbutVqvbbiAQCAS6tQAMrMzHR0HSVkZ2dLkoKCguy2BwUF6fDhw+X2K63PpeOVJikpSYmJiddQLQAAqEoqNAfojwzDUAXuol2xPz9Z2jCMyz5t+mr7TJgwQTk5Obbl6NGjFS8YAAC4vAoHoJSUFEVFRcnHx0c+Pj6644479P777zussODgYEkqceXmxIkTJa7w/Lnf1fbx8vJSQECA3QIAAG5cFQpAM2fO1FNPPaUePXrok08+0ZIlS9StWzc9+eSTmjVrlkMKa9SokYKDg7V+/XrbtosXL2rTpk1q27Ztmf3atGlj10eS1q1bV24fAABgLhWaAzR37ly99dZbGjhwoG1bXFycbrvtNk2ePLnEJOSynD9/XocOHbKtZ2ZmKj09XbVq1VL9+vU1ZswY/fOf/9TNN9+sm2++Wf/85z/l6+urvn372voMHDhQYWFhSkpKkiQ9++yzat++vaZPn664uDh9+umn+vLLL/X1119XZKgAAOAGVKEAlJWVVeoVlbZt2yorK+uKj7Njxw517NjRtj527FhJ0qBBg7Ro0SKNGzdOv/76q55++mmdOXNGd999t9atW6fq1avb+hw5ckRubr9fyGrbtq0+/vhj/f3vf9fEiRPVuHFjLVmyRHfffXdFhgoAAG5AFXoO0O23366+ffvqhRdesNs+ZcoULVmyRBkZGQ4r0Bl4DhDPAQLgJDwHyCHM+u9jpT8HKDExUX369NHmzZvVrl07WSwWff311/rqq6/0ySefVKhoAACA66VCk6Dj4+O1fft23XTTTVq5cqWWL1+um266Sf/+97/10EMPObpGAAAAh6rQFSBJio6O1gcffODIWgAAAK6LCl0BWrNmjb744osS27/44gu73+ACAABwRRUKQOPHj1dRUVGJ7YZhaPz48ddcFAAAQGWqUAA6ePCgmjVrVmL7rbfeavdcHwAAAFdUoQAUGBion376qcT2Q4cOyc/P75qLAgAAqEwVCkB/+ctfNGbMGP3444+2bYcOHdLf/vY3/eUvf3FYcQAAAJWhQgHo1VdflZ+fn2699VY1atRIjRo10q233qratWvrtddec3SNAAAADlWhr8EHBgZq69atWr9+vfbs2SMfHx81b95c9957r6PrAwAAcLirugK0fft229fcLRaLunbtqrp16+q1115TfHy8RowYofz8/EopFAAAwFGuKgBNnjxZe/futa1nZGRo+PDh6tKli8aPH6/Vq1fbfpUdAADAVV3VLbD09HS9/PLLtvWPP/5Yd911lxYuXChJCg8P16RJkzR58mSHFgmgElWBH5/U1f9m83XH2whULVd1BejMmTMKCgqyrW/atEndunWzrbdu3VpHjx51XHUAAACV4KoCUFBQkDIzMyVJFy9e1K5du9SmTRvb/nPnzsnT09OxFQIAADjYVQWgbt26afz48dqyZYsmTJggX19fu29+7d27V40bN3Z4kQAAAI50VXOApkyZoocfflj33Xef/P399d5776latWq2/e+++666du3q8CIBAAAc6aoCUJ06dbRlyxbl5OTI399f7u7udvuXLl0qf39/hxYIAADgaBV+EGJpatWqdU3FAAAAXA8V+ikMAACAqowABAAATIcABAAATIcABAAATIcABAAATIcABAAATIcABAAATIcABAAATIcABAAATIcABAAATIcABAAATIcABAAATKdCP4aKa2SxOLuCy5vs7AIAABVVFT5mDMO5r88VIAAAYDoEIAAAYDoEIAAAYDouH4AaNmwoi8VSYhk5cmSp7dPS0kpt/5///Oc6Vw4AAFyVy0+C/u6771RUVGRb//7779WlSxf17t273H4HDhxQQECAbb1OnTqVViMAAKhaXD4A/Tm4TJs2TY0bN9Z9991Xbr+6deuqRo0alVgZAACoqlz+FtgfXbx4UR988IGGDh0qy2W+49eiRQuFhISoU6dO2rhx43WqEAAAVAUufwXoj1auXKmzZ89q8ODBZbYJCQnRv/71L0VHRys/P1/vv/++OnXqpLS0NLVv377UPvn5+crPz7etW61WR5cOAABcSJUKQO+88466d++u0NDQMts0bdpUTZs2ta23adNGR48e1WuvvVZmAEpKSlJiYqLD6wUAAK6pytwCO3z4sL788ksNGzbsqvvGxMTo4MGDZe6fMGGCcnJybMvRo0evpVQAAODiqswVoOTkZNWtW1cPPPDAVffdvXu3QkJCytzv5eUlLy+vaykPAABUIVUiABUXFys5OVmDBg2Sh4d9yRMmTNCxY8eUkpIiSZo9e7YaNmyo2267zTZpetmyZVq2bJkzSgcAAC6oSgSgL7/8UkeOHNHQoUNL7MvKytKRI0ds6xcvXlRCQoKOHTsmHx8f3Xbbbfrss8/Uo0eP61kyAABwYRbDcPbvsboeq9WqwMBA5eTk2D1M0WGqwM/0WiY7u4LLMyZx6jpEFTgfnf6z0VeAt9FBqsAbWRX+fdRk1/9jV8b5eDWf31VmEjQAAICjEIAAAIDpEIAAAIDpVIlJ0ADMzZLo+vNCJNefcwHgd1wBAgAApkMAAgAApkMAAgAApkMAAgAApkMAAgAApkMAAgAApkMAAgAApkMAAgAApkMAAgAApkMAAgAApkMAAgAApkMAAgAApkMAAgAApkMAAgAApkMAAgAApkMAAgAApkMAAgAApkMAAgAApkMAAgAApkMAAgAApkMAAgAApkMAAgAApkMAAgAApkMAAgAApkMAAgAApkMAAgAApkMAAgAApkMAAgAApkMAAgAApkMAAgAApkMAAgAApkMAAgAApuPSAWjy5MmyWCx2S3BwcLl9Nm3apOjoaHl7eysiIkLz58+/TtUCAICqwsPZBVzObbfdpi+//NK27u7uXmbbzMxM9ejRQ8OHD9cHH3ygb775Rk8//bTq1Kmj+Pj461EuAACoAlw+AHl4eFz2qs8l8+fPV/369TV79mxJUmRkpHbs2KHXXnuNAAQAAGxc+haYJB08eFChoaFq1KiRHnvsMf30009ltt22bZu6du1qty02NlY7duxQQUFBmf3y8/NltVrtFgAAcONy6QB09913KyUlRV988YUWLlyo7OxstW3bVqdOnSq1fXZ2toKCguy2BQUFqbCwUCdPnizzdZKSkhQYGGhbwsPDHToOAADgWlw6AHXv3l3x8fGKiopS586d9dlnn0mS3nvvvTL7WCwWu3XDMErd/kcTJkxQTk6ObTl69KgDqgcAAK7K5ecA/ZGfn5+ioqJ08ODBUvcHBwcrOzvbbtuJEyfk4eGh2rVrl3lcLy8veXl5ObRWAADgulz6CtCf5efna//+/QoJCSl1f5s2bbR+/Xq7bevWrVOrVq3k6el5PUoEAABVgEsHoISEBG3atEmZmZnavn27HnnkEVmtVg0aNEjSb7euBg4caGv/5JNP6vDhwxo7dqz279+vd999V++8844SEhKcNQQAAOCCXPoW2H//+189/vjjOnnypOrUqaOYmBh9++23atCggSQpKytLR44csbVv1KiR1qxZo+eee05vvPGGQkNDNWfOHL4CDwAA7Lh0APr444/L3b9o0aIS2+677z7t2rWrkioCAAA3Ape+BQYAAFAZCEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0CEAAAMB0XPrHUIHyWCzOruDyDMPZFQAASsMVIAAAYDoEIAAAYDoEIAAAYDoEIAAAYDoEIAAAYDoEIAAAYDoEIAAAYDoEIAAAYDoEIAAAYDoEIAAAYDoEIAAAYDoEIAAAYDoEIAAAYDoEIAAAYDoEIAAAYDoEIAAAYDoEIAAAYDoEIAAAYDoEIAAAYDoEIAAAYDoEIAAAYDoEIAAAYDouHYCSkpLUunVrVa9eXXXr1tWDDz6oAwcOlNsnLS1NFoulxPKf//znOlUNAABcnUsHoE2bNmnkyJH69ttvtX79ehUWFqpr167Kzc29bN8DBw4oKyvLttx8883XoWIAAFAVeDi7gPKsXbvWbj05OVl169bVzp071b59+3L71q1bVzVq1KjE6gAAQFXl0leA/iwnJ0eSVKtWrcu2bdGihUJCQtSpUydt3Lix3Lb5+fmyWq12CwAAuHFVmQBkGIbGjh2re+65R7fffnuZ7UJCQvSvf/1Ly5Yt0/Lly9W0aVN16tRJmzdvLrNPUlKSAgMDbUt4eHhlDAEAALgIi2EYhrOLuBIjR47UZ599pq+//lr16tW7qr69evWSxWLRqlWrSt2fn5+v/Px827rValV4eLhycnIUEBBwTXWXymJx/DEdzDLZ2RVcgcmuf+pWif+6OB8dg/PRMTgfHcOk56PValVgYOAVfX5XiStAo0aN0qpVq7Rx48arDj+SFBMTo4MHD5a538vLSwEBAXYLAAC4cbn0JGjDMDRq1CitWLFCaWlpatSoUYWOs3v3boWEhDi4OgAAUFW5dAAaOXKkPvroI3366aeqXr26srOzJUmBgYHy8fGRJE2YMEHHjh1TSkqKJGn27Nlq2LChbrvtNl28eFEffPCBli1bpmXLljltHAAAwLW4dAB66623JEkdOnSw256cnKzBgwdLkrKysnTkyBHbvosXLyohIUHHjh2Tj4+PbrvtNn322Wfq0aPH9SobAAC4OJcOQFcyP3vRokV26+PGjdO4ceMqqSIAAHAjqBKToAEAAByJAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEyHAAQAAEynSgSgN998U40aNZK3t7eio6O1ZcuWcttv2rRJ0dHR8vb2VkREhObPn3+dKgUAAFWBywegJUuWaMyYMXrxxRe1e/du3XvvverevbuOHDlSavvMzEz16NFD9957r3bv3q0XXnhBo0eP1rJly65z5QAAwFW5fACaOXOmnnjiCQ0bNkyRkZGaPXu2wsPD9dZbb5Xafv78+apfv75mz56tyMhIDRs2TEOHDtVrr712nSsHAACuyqUD0MWLF7Vz50517drVbnvXrl21devWUvts27atRPvY2Fjt2LFDBQUFlVYrAACoOjycXUB5Tp48qaKiIgUFBdltDwoKUnZ2dql9srOzS21fWFiokydPKiQkpESf/Px85efn29ZzcnIkSVar9VqHUHXlObuAK+H6fx8zn0IOxfnoEJyPDsL56BCVcT5e+tw2DOOybV06AF1isVjs1g3DKLHtcu1L235JUlKSEhMTS2wPDw+/2lJvHNOcXcCVCHR2AZcV6PolVg2cjw7B+eggnI8OUZnn47lz5xR4mRdw6QB00003yd3dvcTVnhMnTpS4ynNJcHBwqe09PDxUu3btUvtMmDBBY8eOta0XFxfr9OnTql27drlBC1fGarUqPDxcR48eVUBAgLPLgclxPsKVcD46lmEYOnfunEJDQy/b1qUDULVq1RQdHa3169froYcesm1fv3694uLiSu3Tpk0brV692m7bunXr1KpVK3l6epbax8vLS15eXnbbatSocW3Fo4SAgAD+A4fL4HyEK+F8dJzLXfm5xKUnQUvS2LFj9fbbb+vdd9/V/v379dxzz+nIkSN68sknJf129WbgwIG29k8++aQOHz6ssWPHav/+/Xr33Xf1zjvvKCEhwVlDAAAALsalrwBJUp8+fXTq1Cn94x//UFZWlm6//XatWbNGDRo0kCRlZWXZPROoUaNGWrNmjZ577jm98cYbCg0N1Zw5cxQfH++sIQAAABdjMa5kqjRwDfLz85WUlKQJEyaUuNUIXG+cj3AlnI/OQwACAACm4/JzgAAAAByNAAQAAEyHAAQAAEyHAASXNXnyZN15553OLgOQxPkI18L5eO0IQDeYpKQktW7dWtWrV1fdunX14IMP6sCBA3ZtDMPQ5MmTFRoaKh8fH3Xo0EE//PCDbf/p06c1atQoNW3aVL6+vqpfv75Gjx5t+420S6ZOnaq2bdvK19e31AdH/vzzz7JYLCWW/v37O3TMy5YtU7NmzeTl5aVmzZppxYoVdvs3b96sXr16KTQ0VBaLRStXrnTo66NsnI8lz8creU9QOTgfS56Pb731lu644w7bgxjbtGmjzz//3KE1uCoC0A1m06ZNGjlypL799lutX79ehYWF6tq1q3Jzc21tXnnlFc2cOVPz5s3Td999p+DgYHXp0kXnzp2TJB0/flzHjx/Xa6+9poyMDC1atEhr167VE088YfdaFy9eVO/evfXUU0+VW9OXX36prKws2/LGG284bLzbtm1Tnz59NGDAAO3Zs0cDBgzQo48+qu3bt9va5Obmqnnz5po3b57DXhdXhvOx5Pl4Je8JKgfnY8nzsV69epo2bZp27NihHTt26P7771dcXJxd6LthGbihnThxwpBkbNq0yTAMwyguLjaCg4ONadOm2drk5eUZgYGBxvz588s8zieffGJUq1bNKCgoKLEvOTnZCAwMLLE9MzPTkGTs3r271GOePXvWGD58uFGnTh2jevXqRseOHY309HTb/kmTJhnNmzc35s+fb9SrV8/w8fExHnnkEePMmTO2No8++qjRrVs3u+PGxsYajz32WKmvKclYsWJFmeNE5eJ8LOnP7wmuH87H0tWsWdN4++23y21zI+AK0A3u0mXZWrVqSZIyMzOVnZ2trl272tp4eXnpvvvu09atW8s9TkBAgDw8HPPwcMMw9MADDyg7O1tr1qzRzp071bJlS3Xq1EmnT5+2tTt06JA++eQTrV69WmvXrlV6erpGjhxp279t2za7sUhSbGxsuWOB83A+lj4W6ff3BNcP56O9oqIiffzxx8rNzVWbNm0cMhaX5uQAhkpUXFxs9OrVy7jnnnts27755htDknHs2DG7tsOHDze6du1a6nFOnjxp1K9f33jxxRdL3X+5/4Xj4+Nj+Pn52ZZdu3YZX331lREQEGDk5eXZ9WncuLGxYMECwzB++1847u7uxtGjR237P//8c8PNzc3IysoyDMMwPD09jQ8//NDuGB9++KFRrVq1UmsVV4CchvPxyt4TXB+cj7/bu3ev4efnZ7i7uxuBgYHGZ599VupYbjQu/1tgqLhnnnlGe/fu1ddff11in8VisVs3DKPENkmyWq164IEH1KxZM02aNKlCdSxZskSRkZG29fDwcM2ZM0fnz59X7dq17dr++uuv+vHHH23r9evXV7169Wzrbdq0UXFxsQ4cOKDg4OCrGguci/OxpPLeE1QuzsffNW3aVOnp6Tp79qyWLVumQYMGadOmTWrWrFmFxlRVEIBuUKNGjdKqVau0efNmu/9ALv1HkZ2drZCQENv2EydOKCgoyO4Y586dU7du3eTv768VK1bI09OzQrWEh4erSZMmdtuKi4sVEhKitLS0Eu1L+8bEJZf+w730f4ODg5WdnW3XprSxwLk4H0uej2W9J6h8nI/2Y6lWrZqthlatWum7777T66+/rgULFlztcKoU5gDdYAzD0DPPPKPly5drw4YNatSokd3+Ro0aKTg4WOvXr7dtu3jxojZt2qS2bdvatlmtVnXt2lXVqlXTqlWr5O3t7dA6W7ZsqezsbHl4eKhJkyZ2y0033WRrd+TIER0/fty2vm3bNrm5uemWW26R9Nv/4vnjWCRp3bp1dmOB83A+ljwfL/eeoPJwPl7Zv4+GYSg/P9+BI3JRTrr1hkry1FNPGYGBgUZaWpqRlZVlWy5cuGBrM23aNCMwMNBYvny5kZGRYTz++ONGSEiIYbVaDcMwDKvVatx9991GVFSUcejQIbvjFBYW2o5z+PBhY/fu3UZiYqLh7+9v7N6929i9e7dx7tw5wzDK/5ZDcXGxcc899xjNmzc31q5da2RmZhrffPON8eKLLxrfffedYRi/3eP28/MzOnfubKSnpxubN282brnlFrtvMHzzzTeGu7u7MW3aNGP//v3GtGnTDA8PD+Pbb7+1tTl37pytNknGzJkzjd27dxuHDx926HuPkjgfS56PV/KeoHJwPpY8HydMmGBs3rzZyMzMNPbu3Wu88MILhpubm7Fu3TqHvveuiAB0g5FU6pKcnGxrU1xcbEyaNMkIDg42vLy8jPbt2xsZGRm2/Rs3bizzOJmZmbZ2gwYNKrXNxo0bDcO4/Nc8rVarMWrUKCM0NNTw9PQ0wsPDjX79+hlHjhwxDOP3r3m++eabRmhoqOHt7W08/PDDxunTp+2Os3TpUqNp06aGp6enceuttxrLli2z21/WeAYNGlTh9xlXhvOx5Pl4Je8JKgfnY8nzcejQoUaDBg2MatWqGXXq1DE6depkivBjGIZhMQzDuKZLSAAAAFUMc4AAAIDpEIAAAIDpEIAAAIDpEIAAAIDpEIAAAIDpEIAAAIDpEIAAAIDpEIAAAIDpEIAAVAmDBw+WxWKRxWKRp6engoKC1KVLF7377rsqLi6+4uMsWrSo3B+UBGAOBCAAVUa3bt2UlZWln3/+WZ9//rk6duyoZ599Vj179lRhYaGzywNQhRCAAFQZXl5eCg4OVlhYmFq2bKkXXnhBn376qT7//HMtWrRIkjRz5kxFRUXJz89P4eHhevrpp3X+/HlJUlpamoYMGaKcnBzb1aTJkydL+u1Xv8eNG6ewsDD5+fnp7rvvVlpamu21Dx8+rF69eqlmzZry8/PTbbfdpjVr1lzndwCAoxCAAFRp999/v5o3b67ly5dLktzc3DRnzhx9//33eu+997RhwwaNGzdOktS2bVvNnj1bAQEBysrKUlZWlhISEiRJQ4YM0TfffKOPP/5Ye/fuVe/evdWtWzcdPHhQkjRy5Ejl5+dr8+bNysjI0PTp0+Xv7++cQQO4Zh7OLgAArtWtt96qvXv3SpLGjBlj296oUSO9/PLLeuqpp/Tmm2+qWrVqCgwMlMViUXBwsK3djz/+qMWLF+u///2vQkNDJUkJCQlau3atkpOT9c9//lNHjhxRfHy8oqKiJEkRERHXb4AAHI4ABKDKMwxDFotFkrRx40b985//1L59+2S1WlVYWKi8vDzl5ubKz8+v1P67du2SYRi65ZZb7Lbn5+erdu3akqTRo0frqaee0rp169S5c2fFx8frjjvuqNyBAag03AIDUOXt379fjRo10uHDh9WjRw/dfvvtWrZsmXbu3Kk33nhDklRQUFBm/+LiYrm7u2vnzp1KT0+3Lfv379frr78uSRo2bJh++uknDRgwQBkZGWrVqpXmzp17XcYHwPEIQACqtA0bNigjI0Px8fHasWOHCgsLNWPGDMXExOiWW27R8ePH7dpXq1ZNRUVFdttatGihoqIinThxQk2aNLFb/nirLDw8XE8++aSWL1+uv/3tb1q4cOF1GSMAx+MWGIAqIz8/X9nZ2SoqKtIvv/yitWvXKikpST179tTAgQOVkZGhwsJCzZ07V7169dI333yj+fPn2x2jYcOGOn/+vL766is1b95cvr6+uuWWW9SvXz8NHDhQM2bMUIsWLXTy5Elt2LBBUVFR6tGjh8aMGaPu3bvrlltu0ZkzZ7RhwwZFRkY66Z0AcM0MAKgCBg0aZEgyJBkeHh5GnTp1jM6dOxvvvvuuUVRUZGs3c+ZMIyQkxPDx8TFiY2ONlJQUQ5Jx5swZW5snn3zSqF27tiHJmDRpkmEYhnHx4kXjpZdeMho2bGh4enoawcHBxkMPPWTs3bvXMAzDeOaZZ4zGjRsbXl5eRp06dYwBAwYYJ0+evJ5vAQAHshiGYTg3ggEAAFxfzAECAACmQwACAACmQwACAACmQwACAACmQwACAACmQwACAACmQwACAACmQwACAACmQwACAACmQwACAACmQwACAACmQwACAACm8/8ApHiAfyYfIEUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xv=[8,9,11]\n",
    "bar1=plt.bar(ind,xv,width,color='r')\n",
    "yv=[15,7,19]\n",
    "bar2=plt.bar(ind+width,yv,width,color='g')\n",
    "zv=[4,9,8]\n",
    "bar3=plt.bar(ind+width*2,zv,width,color='b')\n",
    " \n",
    "plt.xlabel(\"Dates\")\n",
    "plt.ylabel('Scores')\n",
    "plt.title(\"Players Score\")\n",
    "plt.xticks(ind+width,['2021Feb01', '2021Feb02', '2021Feb03'])\n",
    "plt.legend( (bar1, bar2, bar3), ('Player1', 'Player2', 'Player3') )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "4b116a89",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<AxesSubplot:>, <BarContainer object of 4 artists>)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(2,2,1),plt.barh(df['Team'],df['Round 1'],color='blue')\n",
    "plt.subplot(2,2,2),plt.barh(df['Team'],df['Round 2'],color='orange')\n",
    "plt.subplot(2,2,3),plt.barh(df['Team'],df['Round 3'],color='green')\n",
    "plt.subplot(2,2,4),plt.barh(df['Team'],df['Round 4'],color='red')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "74dc7dbf",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}