DV.barplot2.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "d3e6a40f-87ca-43f1-8607-dccdbbae9b97",
   "metadata": {},
   "source": [
    "# BARPLOT"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "959e0c46-ef51-429b-9c5c-f64726462828",
   "metadata": {},
   "source": [
    "Veri Seti Hikayesi\n",
    "* price:dolar cinsinden fiyat\n",
    "* carat:ağırlık\n",
    "* color:renk\n",
    "* cut:kalite (fair, good, very good, premium, ideal)\n",
    "* clarity:temizlik,berraklık"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe7dc527-cf12-426e-9c0d-aba0897d6d13",
   "metadata": {},
   "source": [
    "* x:lenght\n",
    "* y:width\n",
    "* z:depth\n",
    "* depth:toplam derinlik yüzdesi\n",
    "* table:elmasın enn geniş noktasına göre genişliği"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "282d0da1-7ac0-4c52-8230-de72bbc9d841",
   "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>carat</th>\n",
       "      <th>cut</th>\n",
       "      <th>color</th>\n",
       "      <th>clarity</th>\n",
       "      <th>depth</th>\n",
       "      <th>table</th>\n",
       "      <th>price</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>z</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.23</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>E</td>\n",
       "      <td>SI2</td>\n",
       "      <td>61.5</td>\n",
       "      <td>55.0</td>\n",
       "      <td>326</td>\n",
       "      <td>3.95</td>\n",
       "      <td>3.98</td>\n",
       "      <td>2.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.21</td>\n",
       "      <td>Premium</td>\n",
       "      <td>E</td>\n",
       "      <td>SI1</td>\n",
       "      <td>59.8</td>\n",
       "      <td>61.0</td>\n",
       "      <td>326</td>\n",
       "      <td>3.89</td>\n",
       "      <td>3.84</td>\n",
       "      <td>2.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.23</td>\n",
       "      <td>Good</td>\n",
       "      <td>E</td>\n",
       "      <td>VS1</td>\n",
       "      <td>56.9</td>\n",
       "      <td>65.0</td>\n",
       "      <td>327</td>\n",
       "      <td>4.05</td>\n",
       "      <td>4.07</td>\n",
       "      <td>2.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.29</td>\n",
       "      <td>Premium</td>\n",
       "      <td>I</td>\n",
       "      <td>VS2</td>\n",
       "      <td>62.4</td>\n",
       "      <td>58.0</td>\n",
       "      <td>334</td>\n",
       "      <td>4.20</td>\n",
       "      <td>4.23</td>\n",
       "      <td>2.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.31</td>\n",
       "      <td>Good</td>\n",
       "      <td>J</td>\n",
       "      <td>SI2</td>\n",
       "      <td>63.3</td>\n",
       "      <td>58.0</td>\n",
       "      <td>335</td>\n",
       "      <td>4.34</td>\n",
       "      <td>4.35</td>\n",
       "      <td>2.75</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   carat      cut color clarity  depth  table  price     x     y     z\n",
       "0   0.23    Ideal     E     SI2   61.5   55.0    326  3.95  3.98  2.43\n",
       "1   0.21  Premium     E     SI1   59.8   61.0    326  3.89  3.84  2.31\n",
       "2   0.23     Good     E     VS1   56.9   65.0    327  4.05  4.07  2.31\n",
       "3   0.29  Premium     I     VS2   62.4   58.0    334  4.20  4.23  2.63\n",
       "4   0.31     Good     J     SI2   63.3   58.0    335  4.34  4.35  2.75"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "diamonds = sns.load_dataset('diamonds')\n",
    "df = diamonds.copy()\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "31cbf6c1-9eec-464e-a91f-1023f82a1c71",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['cut'].value_counts().plot.barh()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "62ee6c4a-148c-48bd-ac6a-237b1c9adf56",
   "metadata": {},
   "source": [
    "* ; koyduğun zaman"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "30bdc9e9-172b-4cf7-ad9f-5e7bcd96ec7e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['cut'].value_counts().plot.barh();"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e231696c-a208-4896-90cb-3c21a6f02eb3",
   "metadata": {},
   "source": [
    "* Başlık eklemek"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "b21ce004-bc5f-4024-8edf-3fa3f462d2ae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['cut'].value_counts().plot.barh().set_title(\"Cut Değişkeninin Sınıf Frekansları\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9b362da6-2403-4e29-8b2f-1a339730ae0b",
   "metadata": {},
   "source": [
    "* Seaborn ile grafik oluşturma"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "4b3c2352-7939-4386-8202-a93f3495cade",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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kZCUkJJg12dnZiomJ0YMPPqisrCwNGzZMAwYM0IoVK8yaefPmKT4+XmPHjtXWrVvVrFkzRUdH68SJEzfmxQAAAC6tkjOffPny5Q7zycnJCgwMVGZmpu6//37l5ubq448/VkpKih566CFJUlJSkho3bqyNGzfqvvvu08qVK7V792599dVXCgoKUvPmzfX6669r1KhRGjdunOx2uxITE1W/fn1NmjRJktS4cWOtW7dOU6ZMUXR0tCRp8uTJGjhwoPr16ydJSkxM1NKlSzVr1iy98sorN/BVAQAArsilzmnKzc2VJAUEBEiSMjMzVVxcrKioKLOmUaNGqlOnjjIyMiRJGRkZCg8PV1BQkFkTHR2tvLw87dq1y6y5cB1lNWXrKCoqUmZmpkONm5uboqKizJpfKywsVF5ensMEAABuXS4TmkpLSzVs2DC1bdtWd999tyQpJydHdrtd/v7+DrVBQUHKyckxay4MTGXjZWOXq8nLy9PZs2f1n//8RyUlJeXWlK3j1yZMmCA/Pz9zCg0NvboNBwAANwWXCU1xcXHauXOnPvvsM2e3Ysno0aOVm5trTocPH3Z2SwAA4Hfk1HOaygwdOlRLlizRmjVrVLt2bXN5cHCwioqKdPr0aYe9TcePH1dwcLBZ8+ur3Mqurruw5tdX3B0/fly+vr7y8vKSu7u73N3dy60pW8eveXh4yMPD4+o2GAAA3HScuqfJMAwNHTpUCxcu1KpVq1S/fn2H8YiICFWuXFlpaWnmsn379unQoUOKjIyUJEVGRmrHjh0OV7mlpqbK19dXTZo0MWsuXEdZTdk67Ha7IiIiHGpKS0uVlpZm1gAAgIrNqXua4uLilJKSosWLF6tq1arm+UN+fn7y8vKSn5+fYmNjFR8fr4CAAPn6+ur5559XZGSk7rvvPklSp06d1KRJEz399NOaOHGicnJyNGbMGMXFxZl7ggYPHqzp06dr5MiR6t+/v1atWqX58+dr6dKlZi/x8fHq27evWrZsqVatWmnq1KkqKCgwr6YDAAAVm1ND08yZMyVJHTp0cFielJSkZ555RpI0ZcoUubm5qUePHiosLFR0dLQ++OADs9bd3V1LlizRkCFDFBkZKW9vb/Xt21fjx483a+rXr6+lS5dq+PDhmjZtmmrXrq2PPvrIvN2AJPXs2VM//vijEhISlJOTo+bNm2v58uUXnRwOAAAqJqeGJsMwrljj6empGTNmaMaMGZesqVu3rpYtW3bZ9XTo0EHbtm27bM3QoUM1dOjQK/YEAAAqHpe5eg4AAMCVEZoAAAAsIDQBAABYQGgCAACwgNAEAABgAaEJAADAAkITAACABYQmAAAACwhNAAAAFhCaAAAALCA0AQAAWEBoAgAAsIDQBAAAYAGhCQAAwAJCEwAAgAWEJgAAAAsITQAAABYQmgAAACwgNAEAAFhAaAIAALCA0AQAAGABoQkAAMACQhMAAIAFhCYAAAALCE0AAAAWEJoAAAAsIDQBAABYQGgCAACwgNAEAABgAaEJAADAAkITAACABYQmAAAACwhNAAAAFhCaAAAALCA0AQAAWHDVoen8+fP66quv9Ne//lVnzpyRJB09elT5+fnXrTkAAABXUelqHvTvf/9bnTt31qFDh1RYWKg//OEPqlq1qt5++20VFhYqMTHxevcJAADgVFe1p+nFF19Uy5YtderUKXl5eZnLH330UaWlpV235gAAAFzFVe1pWrt2rTZs2CC73e6wvF69evrhhx+uS2MAAACu5Kr2NJWWlqqkpOSi5UeOHFHVqlWvuSkAAABXc1WhqVOnTpo6dao5b7PZlJ+fr7Fjx6pr167XqzcAAACXcVWH5yZNmqTo6Gg1adJE586d01NPPaX9+/erRo0amjt37vXuEQAAwOmuKjTVrl1b3377rT777DNt375d+fn5io2NVe/evR1ODAcAALhVXFVokqRKlSrpT3/60/XsBQAAwGVddWjav3+/vv76a504cUKlpaUOYwkJCdfcGAAAgCu5qtD0t7/9TUOGDFGNGjUUHBwsm81mjtlsNkITAAC45VxVaHrjjTf05ptvatSoUde7HwAAAJd0VbccOHXqlB5//PHr3QsAAIDLuqrQ9Pjjj2vlypXXuxcAAACXdVWH58LCwvTqq69q48aNCg8PV+XKlR3GX3jhhevSHAAAgKu4qj1NH374oXx8fLR69WpNnz5dU6ZMMacL7xR+JWvWrNEjjzyikJAQ2Ww2LVq0yGH8mWeekc1mc5g6d+7sUPPTTz+pd+/e8vX1lb+/v2JjY5Wfn+9Qs337drVv316enp4KDQ3VxIkTL+plwYIFatSokTw9PRUeHq5ly5ZZ3g4AAHDru6o9TdnZ2dflyQsKCtSsWTP1799fjz32WLk1nTt3VlJSkjnv4eHhMN67d28dO3ZMqampKi4uVr9+/TRo0CClpKRIkvLy8tSpUydFRUUpMTFRO3bsUP/+/eXv769BgwZJkjZs2KBevXppwoQJevjhh5WSkqLu3btr69atuvvuu6/LtgIAgJvbVd+nqYxhGJLkcNsBq7p06aIuXbpctsbDw0PBwcHlju3Zs0fLly/Xli1b1LJlS0nS+++/r65du+rdd99VSEiI5syZo6KiIs2aNUt2u1133XWXsrKyNHnyZDM0TZs2TZ07d9aIESMkSa+//rpSU1M1ffp0JSYmlvvchYWFKiwsNOfz8vJ+8/YDAICbx1UdnpOkTz75ROHh4fLy8pKXl5eaNm2qTz/99Hr2JklKT09XYGCgGjZsqCFDhujkyZPmWEZGhvz9/c3AJElRUVFyc3PTpk2bzJr7779fdrvdrImOjta+fft06tQpsyYqKsrheaOjo5WRkXHJviZMmCA/Pz9zCg0NvS7bCwAAXNNVhabJkydryJAh6tq1q+bPn6/58+erc+fOGjx4sKZMmXLdmuvcubM++eQTpaWl6e2339bq1avVpUsXlZSUSJJycnIUGBjo8JhKlSopICBAOTk5Zk1QUJBDTdn8lWrKxsszevRo5ebmmtPhw4evbWMBAIBLu6rDc++//75mzpypPn36mMv++Mc/6q677tK4ceM0fPjw69Lck08+af47PDxcTZs2VYMGDZSenq6OHTtel+e4Wh4eHhedXwUAAG5dV7Wn6dixY2rTps1Fy9u0aaNjx45dc1OXcvvtt6tGjRo6cOCAJCk4OFgnTpxwqDl//rx++ukn8zyo4OBgHT9+3KGmbP5KNZc6lwoAAFQ8VxWawsLCNH/+/IuWz5s3T3fcccc1N3UpR44c0cmTJ1WrVi1JUmRkpE6fPq3MzEyzZtWqVSotLVXr1q3NmjVr1qi4uNisSU1NVcOGDVWtWjWzJi0tzeG5UlNTFRkZ+bttCwAAuLlc1eG51157TT179tSaNWvUtm1bSdL69euVlpZWbpi6lPz8fHOvkfTLrQyysrIUEBCggIAAvfbaa+rRo4eCg4N18OBBjRw5UmFhYYqOjpYkNW7cWJ07d9bAgQOVmJio4uJiDR06VE8++aRCQkIkSU899ZRee+01xcbGatSoUdq5c6emTZvmcO7Viy++qAceeECTJk1STEyMPvvsM33zzTf68MMPr+blAQAAt6Cr2tPUo0cPbdq0SdWrV9eiRYu0aNEi1ahRQ5s3b9ajjz5qeT3ffPON7rnnHt1zzz2SpPj4eN1zzz1KSEiQu7u7tm/frj/+8Y+68847FRsbq4iICK1du9bhXKI5c+aoUaNG6tixo7p27ap27do5hB0/Pz+tXLlS2dnZioiI0EsvvaSEhATzdgPSL4cVU1JS9OGHH6pZs2b6n//5Hy1atIh7NAEAANNV36cpIiJCc+bMuaYn79Chg3mfp/KsWLHiiusICAgwb2R5KU2bNtXatWsvW/P444/zI8QAAOCSflNocnNzu+JNLG02m86fP39NTQEAALia3xSaFi5ceMmxjIwMvffeeyotLb3mpgAAAFzNbwpN3bp1u2jZvn379Morr+iLL75Q7969NX78+OvWHAAAgKu46p9ROXr0qAYOHKjw8HCdP39eWVlZmj17turWrXs9+wMAAHAJvzk05ebmatSoUQoLC9OuXbuUlpamL774givNAADALe03HZ6bOHGi3n77bQUHB2vu3LnlHq4DAAC4Ff2m0PTKK6/Iy8tLYWFhmj17tmbPnl1u3eeff35dmgMAAHAVvyk09enT54q3HAAAALgV/abQlJyc/Du1AQAA4Nqu+uo5AACAioTQBAAAYAGhCQAAwAJCEwAAgAWEJgAAAAsITQAAABYQmgAAACwgNAEAAFhAaAIAALCA0AQAAGABoQkAAMACQhMAAIAFhCYAAAALCE0AAAAWEJoAAAAsIDQBAABYQGgCAACwgNAEAABgAaEJAADAAkITAACABYQmAAAACwhNAAAAFhCaAAAALCA0AQAAWEBoAgAAsIDQBAAAYAGhCQAAwAJCEwAAgAWEJgAAAAsITQAAABYQmgAAACwgNAEAAFhAaAIAALCA0AQAAGABoQkAAMACQhMAAIAFhCYAAAALCE0AAAAWEJoAAAAsIDQBAABY4NTQtGbNGj3yyCMKCQmRzWbTokWLHMYNw1BCQoJq1aolLy8vRUVFaf/+/Q41P/30k3r37i1fX1/5+/srNjZW+fn5DjXbt29X+/bt5enpqdDQUE2cOPGiXhYsWKBGjRrJ09NT4eHhWrZs2XXfXgAAcPNyamgqKChQs2bNNGPGjHLHJ06cqPfee0+JiYnatGmTvL29FR0drXPnzpk1vXv31q5du5SamqolS5ZozZo1GjRokDmel5enTp06qW7dusrMzNQ777yjcePG6cMPPzRrNmzYoF69eik2Nlbbtm1T9+7d1b17d+3cufP323gAAHBTqeTMJ+/SpYu6dOlS7phhGJo6darGjBmjbt26SZI++eQTBQUFadGiRXryySe1Z88eLV++XFu2bFHLli0lSe+//766du2qd999VyEhIZozZ46Kioo0a9Ys2e123XXXXcrKytLkyZPNcDVt2jR17txZI0aMkCS9/vrrSk1N1fTp05WYmFhuf4WFhSosLDTn8/LyrtvrAgAAXI/LntOUnZ2tnJwcRUVFmcv8/PzUunVrZWRkSJIyMjLk7+9vBiZJioqKkpubmzZt2mTW3H///bLb7WZNdHS09u3bp1OnTpk1Fz5PWU3Z85RnwoQJ8vPzM6fQ0NBr32gAAOCyXDY05eTkSJKCgoIclgcFBZljOTk5CgwMdBivVKmSAgICHGrKW8eFz3GpmrLx8owePVq5ubnmdPjw4d+6iQAA4Cbi1MNzNzMPDw95eHg4uw0AAHCDuOyepuDgYEnS8ePHHZYfP37cHAsODtaJEyccxs+fP6+ffvrJoaa8dVz4HJeqKRsHAABw2dBUv359BQcHKy0tzVyWl5enTZs2KTIyUpIUGRmp06dPKzMz06xZtWqVSktL1bp1a7NmzZo1Ki4uNmtSU1PVsGFDVatWzay58HnKasqeBwAAwKmhKT8/X1lZWcrKypL0y8nfWVlZOnTokGw2m4YNG6Y33nhD//znP7Vjxw716dNHISEh6t69uySpcePG6ty5swYOHKjNmzdr/fr1Gjp0qJ588kmFhIRIkp566inZ7XbFxsZq165dmjdvnqZNm6b4+HizjxdffFHLly/XpEmTtHfvXo0bN07ffPONhg4deqNfEgAA4KKcek7TN998owcffNCcLwsyffv2VXJyskaOHKmCggINGjRIp0+fVrt27bR8+XJ5enqaj5kzZ46GDh2qjh07ys3NTT169NB7771njvv5+WnlypWKi4tTRESEatSooYSEBId7ObVp00YpKSkaM2aM/vznP+uOO+7QokWLdPfdd9+AVwEAANwMnBqaOnToIMMwLjlus9k0fvx4jR8//pI1AQEBSklJuezzNG3aVGvXrr1szeOPP67HH3/88g0DAIAKy2XPaQIAAHAlhCYAAAALCE0AAAAWEJoAAAAsIDQBAABYQGgCAACwgNAEAABgAaEJAADAAkITAACABYQmAAAACwhNAAAAFhCaAAAALCA0AQAAWEBoAgAAsIDQBAAAYAGhCQAAwAJCEwAAgAWEJgAAAAsITQAAABYQmgAAACwgNAEAAFhAaAIAALCA0AQAAGABoQkAAMACQhMAAIAFhCYAAAALCE0AAAAWEJoAAAAsIDQBAABYQGgCAACwgNAEAABgAaEJAADAAkITAACABYQmAAAACwhNAAAAFhCaAAAALCA0AQAAWEBoAgAAsIDQBAAAYAGhCQAAwAJCEwAAgAWEJgAAAAsITQAAABYQmgAAACwgNAEAAFhAaAIAALCA0AQAAGABoQkAAMACQhMAAIAFLh2axo0bJ5vN5jA1atTIHD937pzi4uJUvXp1+fj4qEePHjp+/LjDOg4dOqSYmBhVqVJFgYGBGjFihM6fP+9Qk56erhYtWsjDw0NhYWFKTk6+EZsHAABuIi4dmiTprrvu0rFjx8xp3bp15tjw4cP1xRdfaMGCBVq9erWOHj2qxx57zBwvKSlRTEyMioqKtGHDBs2ePVvJyclKSEgwa7KzsxUTE6MHH3xQWVlZGjZsmAYMGKAVK1bc0O0EAACurZKzG7iSSpUqKTg4+KLlubm5+vjjj5WSkqKHHnpIkpSUlKTGjRtr48aNuu+++7Ry5Urt3r1bX331lYKCgtS8eXO9/vrrGjVqlMaNGye73a7ExETVr19fkyZNkiQ1btxY69at05QpUxQdHX1DtxUAALgul9/TtH//foWEhOj2229X7969dejQIUlSZmamiouLFRUVZdY2atRIderUUUZGhiQpIyND4eHhCgoKMmuio6OVl5enXbt2mTUXrqOspmwdl1JYWKi8vDyHCQAA3LpcOjS1bt1aycnJWr58uWbOnKns7Gy1b99eZ86cUU5Ojux2u/z9/R0eExQUpJycHElSTk6OQ2AqGy8bu1xNXl6ezp49e8neJkyYID8/P3MKDQ291s0FAAAuzKUPz3Xp0sX8d9OmTdW6dWvVrVtX8+fPl5eXlxM7k0aPHq34+HhzPi8vj+AEAMAtzKX3NP2av7+/7rzzTh04cEDBwcEqKirS6dOnHWqOHz9ungMVHBx80dV0ZfNXqvH19b1sMPPw8JCvr6/DBAAAbl03VWjKz8/XwYMHVatWLUVERKhy5cpKS0szx/ft26dDhw4pMjJSkhQZGakdO3boxIkTZk1qaqp8fX3VpEkTs+bCdZTVlK0DAABAcvHQ9PLLL2v16tX6/vvvtWHDBj366KNyd3dXr1695Ofnp9jYWMXHx+vrr79WZmam+vXrp8jISN13332SpE6dOqlJkyZ6+umn9e2332rFihUaM2aM4uLi5OHhIUkaPHiwvvvuO40cOVJ79+7VBx98oPnz52v48OHO3HQAAOBiXPqcpiNHjqhXr146efKkatasqXbt2mnjxo2qWbOmJGnKlClyc3NTjx49VFhYqOjoaH3wwQfm493d3bVkyRINGTJEkZGR8vb2Vt++fTV+/Hizpn79+lq6dKmGDx+uadOmqXbt2vroo4+43QAAAHDg0qHps88+u+y4p6enZsyYoRkzZlyypm7dulq2bNll19OhQwdt27btqnoEAAAVg0sfngMAAHAVhCYAAAALCE0AAAAWEJoAAAAsIDQBAABYQGgCAACwgNAEAABgAaEJAADAAkITAACABYQmAAAACwhNAAAAFhCaAAAALCA0AQAAWEBoAgAAsIDQBAAAYAGhCQAAwAJCEwAAgAWEJgAAAAsITQAAABYQmgAAACwgNAEAAFhAaAIAALCA0AQAAGABoQkAAMACQhMAAIAFhCYAAAALCE0AAAAWEJoAAAAsIDQBAABYQGgCAACwgNAEAABgAaEJAADAAkITAACABYQmAAAACwhNAAAAFhCaAAAALCA0AQAAWEBoAgAAsIDQBAAAYAGhCQAAwAJCEwAAgAWEJgAAAAsITQAAABYQmgAAACwgNAEAAFhAaAIAALCA0AQAAGABoQkAAMACQhMAAIAFhKZfmTFjhurVqydPT0+1bt1amzdvdnZLAADABRCaLjBv3jzFx8dr7Nix2rp1q5o1a6bo6GidOHHC2a0BAAAnIzRdYPLkyRo4cKD69eunJk2aKDExUVWqVNGsWbOc3RoAAHCySs5uwFUUFRUpMzNTo0ePNpe5ubkpKipKGRkZF9UXFhaqsLDQnM/NzZUk5eXlXfG5SgrPXoeOKyYrr+9vwXtxba7n+8F7cW34bLgO3gvXYeW9KKsxDOPKKzRgGIZh/PDDD4YkY8OGDQ7LR4wYYbRq1eqi+rFjxxqSmJiYmJiYmG6B6fDhw1fMCuxpukqjR49WfHy8OV9aWqqffvpJ1atXl81mc2Jn1yYvL0+hoaE6fPiwfH19nd1OhcZ74Tp4L1wH74VruRXeD8MwdObMGYWEhFyxltD0f2rUqCF3d3cdP37cYfnx48cVHBx8Ub2Hh4c8PDwclvn7+/+eLd5Qvr6+N+0H4FbDe+E6eC9cB++Fa7nZ3w8/Pz9LdZwI/n/sdrsiIiKUlpZmListLVVaWpoiIyOd2BkAAHAF7Gm6QHx8vPr27auWLVuqVatWmjp1qgoKCtSvXz9ntwYAAJyM0HSBnj176scff1RCQoJycnLUvHlzLV++XEFBQc5u7Ybx8PDQ2LFjLzr0iBuP98J18F64Dt4L11LR3g+bYVi5xg4AAKBi45wmAAAACwhNAAAAFhCaAAAALCA0VUAdOnTQsGHDXH6duNj3338vm82mrKwsZ7cCJ+Bzdn3YbDYtWrTI2W3ccpKTk2+p+xWWh9B0C3rmmWfUvXt3Z7dxS3nmmWdks9lks9lkt9sVFham8ePH6/z58ze0j9DQUB07dkx33333DX1eZ3jkkUfUuXPncsfWrl0rm82m7du339CeioqK9M4776hFixby9vaWn5+fmjVrpjFjxujo0aM3tJebXU5Ojl588UWFhYXJ09NTQUFBatu2rWbOnKmff/7Z2e1VaBd+3104HThw4LKP69mzp/71r3/doC6dg1sOABZ17txZSUlJKiws1LJlyxQXF6fKlSs7/Miz9MsfVrvd/rv04O7uXu4d6m9FsbGx6tGjh44cOaLatWs7jCUlJally5Zq2rTpb17v1b4/hYWF6tSpk7Zv367XXntNbdu2Vc2aNZWdna25c+fq/fff14QJE37zeiui7777Tm3btpW/v7/eeusthYeHy8PDQzt27NCHH36o2267TX/84x+d3WaFVvZ9d6GaNWte9jFeXl7y8vK65Pjv+d14o7Cn6RZXUFCgPn36yMfHR7Vq1dKkSZMuqiksLNTLL7+s2267Td7e3mrdurXS09PN8ZMnT6pXr1667bbbVKVKFYWHh2vu3Lk3cCtcg4eHh4KDg1W3bl0NGTJEUVFR+uc//2nu2XvzzTcVEhKihg0bSpIOHz6sJ554Qv7+/goICFC3bt30/fffm+sre9xbb72loKAg+fv7m3uvRowYoYCAANWuXdvhi+vXh+fK2x2+aNEih98/HDdunJo3b65Zs2apTp068vHx0XPPPaeSkhJNnDhRwcHBCgwM1Jtvvvm7vXZX4+GHH1bNmjWVnJzssDw/P18LFixQbGysJGndunVq3769vLy8FBoaqhdeeEEFBQVmfb169fT666+rT58+8vX11aBBg/TQQw9p6NChDuv98ccfZbfbHX4V4EJTpkzRunXrtGrVKr3wwguKiIhQnTp19MADDygxMVFvvfWWWVtYWKgXXnhBgYGB8vT0VLt27bRlyxaH9a1evVqtWrWSh4eHatWqpVdeecVhz6WVz+7N6rnnnlOlSpX0zTff6IknnlDjxo11++23q1u3blq6dKkeeeQRSdKhQ4fUrVs3+fj4yNfXV0888cRFP3U1c+ZMNWjQQHa7XQ0bNtSnn37qML5//37df//98vT0VJMmTZSamnrDtvNmVvZ9d+E0bdo0hYeHy9vbW6GhoXruueeUn59vPubX30dl3z0fffSR6tevL09PTydsyfVFaLrFjRgxQqtXr9bixYu1cuVKpaena+vWrQ41Q4cOVUZGhj777DNt375djz/+uDp37qz9+/dLks6dO6eIiAgtXbpUO3fu1KBBg/T0009r8+bNztgkl+Hl5aWioiJJUlpamvbt26fU1FQtWbJExcXFio6OVtWqVbV27VqtX79ePj4+6ty5s/kYSVq1apWOHj2qNWvWaPLkyRo7dqwefvhhVatWTZs2bdLgwYP17LPP6siRI9fU68GDB/Xll19q+fLlmjt3rj7++GPFxMToyJEjWr16td5++22NGTNGmzZtuqbnuZ4qVaqkPn36KDk5WRfeTm7BggUqKSlRr169dPDgQXXu3Fk9evTQ9u3bNW/ePK1bt+6iQPTuu++qWbNm2rZtm1599VUNGDBAKSkpKiwsNGv+/ve/67bbbtNDDz1Ubj9z587VH/7wB91zzz3ljl8YVEeOHKl//OMfmj17trZu3aqwsDBFR0frp59+kiT98MMP6tq1q+699159++23mjlzpj7++GO98cYb5jqsfHZvRidPntTKlSsVFxcnb2/vcmtsNptKS0vVrVs3/fTTT1q9erVSU1P13XffqWfPnmbdwoUL9eKLL+qll17Szp079eyzz6pfv376+uuvJf3yU1iPPfaY7Ha7Nm3apMTERI0aNeqGbOetyM3NTe+995527dql2bNna9WqVRo5cuRlH3PgwAH94x//0Oeff35rnItp4JbTt29fo1u3bsaZM2cMu91uzJ8/3xw7efKk4eXlZbz44ouGYRjGv//9b8Pd3d344YcfHNbRsWNHY/To0Zd8jpiYGOOll14y5x944AFznbeistfUMAyjtLTUSE1NNTw8PIyXX37Z6Nu3rxEUFGQUFhaa9Z9++qnRsGFDo7S01FxWWFhoeHl5GStWrDDXWbduXaOkpMSsadiwodG+fXtz/vz584a3t7cxd+5cwzAMIzs725BkbNu2zTAMw0hKSjL8/Pwcel24cKFx4Ud77NixRpUqVYy8vDxzWXR0tFGvXr2LnnvChAlX+Qr9Pvbs2WNIMr7++mtzWfv27Y0//elPhmEYRmxsrDFo0CCHx6xdu9Zwc3Mzzp49axiGYdStW9fo3r27Q83Zs2eNatWqGfPmzTOXNW3a1Bg3btwle/H09DReeOEFh2Xdu3c3vL29DW9vbyMyMtIwDMPIz883KleubMyZM8esKyoqMkJCQoyJEycahmEYf/7zny/672PGjBmGj4+PUVJSYumze7PauHGjIcn4/PPPHZZXr17dfC1HjhxprFy50nB3dzcOHTpk1uzatcuQZGzevNkwDMNo06aNMXDgQIf1PP7440bXrl0NwzCMFStWGJUqVXL4fvvyyy8NScbChQt/py28+fXt29dwd3c33w9vb2/jv/7rvy6qW7BggVG9enVz/tffR2PHjjUqV65snDhx4ka0fUNwTtMt7ODBgyoqKlLr1q3NZQEBAebhI0nasWOHSkpKdOeddzo8trCwUNWrV5cklZSU6K233tL8+fP1ww8/qKioSIWFhapSpcqN2RAXsWTJEvn4+Ki4uFilpaV66qmnNG7cOMXFxSk8PNzhWP23336rAwcOqGrVqg7rOHfunA4ePGjO33XXXXJz+/8dvkFBQQ4nebu7u6t69eo6ceLENfVer149h16CgoLk7u5+0XNf6/Ncb40aNVKbNm00a9YsdejQQQcOHNDatWs1fvx4Sb+8ztu3b9ecOXPMxxiGodLSUmVnZ6tx48aSpJYtWzqs19PTU08//bRmzZqlJ554Qlu3btXOnTv1z3/+8zf198EHH6igoEDvvfee1qxZI+mXz11xcbHatm1r1lWuXFmtWrXSnj17JEl79uxRZGSkw96ptm3bKj8/X0eOHNGpU6eu+Nm91WzevFmlpaXq3bu3CgsLtWfPHoWGhio0NNSsadKkifz9/bVnzx7de++92rNnjwYNGuSwnrZt22ratGmSZK4jJCTEHOcH2K158MEHNXPmTHPe29tbX331lSZMmKC9e/cqLy9P58+f17lz5/Tzzz9f8u9B3bp1r3gu1M2E0FTB5efny93dXZmZmXJ3d3cY8/HxkSS98847mjZtmqZOnWoezx42bJjDYaaKoOxLxG63KyQkRJUq/f/H59eHGfLz8xUREeHwx7zMhV8glStXdhiz2WzlListLS23Jzc3N4dDV5JUXFx8Ud21Po8zxcbG6vnnn9eMGTOUlJSkBg0a6IEHHpD0y+v87LPP6oUXXrjocXXq1DH/Xd5hoAEDBqh58+Y6cuSIkpKS9NBDD6lu3bqX7OOOO+7Qvn37HJbVqlVL0i+BBtaEhYXJZrNd9FrefvvtknTZE4lx43h7eyssLMyc//777/Xwww9ryJAhevPNNxUQEKB169YpNjZWRUVFlwxNlzoEe7PinKZbWIMGDVS5cmWH81ROnTrlcEnoPffco5KSEp04cUJhYWEOU9lVWuvXr1e3bt30pz/9Sc2aNdPtt99+y19WWp6yL5E6deo4BKbytGjRQvv371dgYOBFr6ufn99166lmzZo6c+aMw4nPt8R5Axd44okn5ObmppSUFH3yySfq37+/uYemRYsW2r1790WvcVhY2BWv0gkPD1fLli31t7/9TSkpKerfv/9l63v16qXU1FRt27btsnVlJyWvX7/eXFZcXKwtW7aoSZMmkqTGjRsrIyPDIfCuX79eVatWVe3atS19dm9W1atX1x/+8AdNnz7d4b/bX2vcuLEOHz6sw4cPm8t2796t06dPO7yOF77O0i+v44Xjhw8f1rFjx8zxjRs3Xs/NqTAyMzNVWlqqSZMm6b777tOdd95ZIW+zQWi6hfn4+Cg2NlYjRozQqlWrtHPnTj3zzDMOh2TuvPNO9e7dW3369NHnn3+u7Oxsbd68WRMmTNDSpUsl/fJ/2KmpqdqwYYP27NmjZ5999qIrWOCod+/eqlGjhrp166a1a9cqOztb6enpeuGFF675pO4LtW7dWlWqVNGf//xnHTx4UCkpKRddbXaz8/HxUc+ePTV69GgdO3ZMzzzzjDk2atQobdiwQUOHDlVWVpb279+vxYsXX3Qi+KUMGDBAf/nLX2QYhh599NHL1g4fPlyRkZHq2LGjpk2bpq1btyo7O1srVqzQl19+ae6p9fb21pAhQzRixAgtX75cu3fv1sCBA/Xzzz+bV/w999xzOnz4sJ5//nnt3btXixcv1tixYxUfHy83NzdLn92b2QcffKDz58+rZcuWmjdvnvbs2aN9+/bp73//u/bu3St3d3dFRUUpPDxcvXv31tatW7V582b16dNHDzzwgHm4dcSIEUpOTtbMmTO1f/9+TZ48WZ9//rlefvllSVJUVJTuvPNO9e3bV99++63Wrl2r//7v/3bmpt+0wsLCVFxcrPfff1/fffedPv30UyUmJjq7rRvu1vgE4pLeeecdtW/fXo888oiioqLUrl07RUREONQkJSWpT58+eumll9SwYUN1795dW7ZsMQ9vjBkzRi1atFB0dLQ6dOig4OBgbp55BVWqVNGaNWtUp04dPfbYY2rcuLFiY2N17tw5+fr6XrfnCQgI0N///nctW7bMvBXEuHHjrtv6XUVsbKxOnTql6Ohoh/NTmjZtqtWrV+tf//qX2rdvr3vuuUcJCQkONZfTq1cvVapUSb169bri5dCenp5KS0vTqFGjlJSUpHbt2qlx48YaNmyY2rZt63CH6b/85S/q0aOHnn76abVo0UIHDhzQihUrVK1aNUnSbbfdpmXLlmnz5s1q1qyZBg8erNjYWI0ZM8Zch5XP7s2qQYMG2rZtm6KiojR69Gg1a9ZMLVu21Pvvv6+XX35Zr7/+umw2mxYvXqxq1arp/vvvV1RUlG6//XbNmzfPXE/37t01bdo0vfvuu7rrrrv017/+VUlJSerQoYOkXw5fL1y4UGfPnlWrVq00YMAAl7u1xs2iWbNmmjx5st5++23dfffdmjNnToW8L5nN+PUJEQBQQXz//fdq0KCBtmzZohYtWji7HQAujtAEoMIpLi7WyZMn9fLLLys7O/ui82IAoDwcngNQ4axfv161atXSli1bKuR5GQCuDnuaAAAALGBPEwAAgAWEJgAAAAsITQAAABYQmgAAACwgNAEAAFhAaAIAALCA0AQA1yA5OVn+/v7ObgPADUBoAgAAsIDQBKDCKy0t1cSJExUWFiYPDw/VqVNHb775ptLT02Wz2XT69GmzNisrSzabTd9//73S09PVr18/5ebmymazyWaz3ZI/mAzgF5Wc3QAAONvo0aP1t7/9TVOmTFG7du107Ngx7d2794qPa9OmjaZOnaqEhATt27dPkuTj4/N7twvASQhNACq0M2fOaNq0aZo+fbr69u0rSWrQoIHatWun9PT0yz7WbrfLz89PNptNwcHBN6BbAM7E4TkAFdqePXtUWFiojh07OrsVAC6O0ASgQvPy8rrkmJvbL1+RF/6ueXFx8e/eEwDXRGgCUKHdcccd8vLyUlpa2kVjNWvWlCQdO3bMXJaVleVQY7fbVVJS8rv2CMA1cE4TgArN09NTo0aN0siRI2W329W2bVv9+OOP2rVrl/r06aPQ0FCNGzdOb775pv71r39p0qRJDo+vV6+e8vPzlZaWpmbNmqlKlSqqUqWKk7YGwO+JPU0AKrxXX31VL730khISEtS4cWP17NlTJ06cUOXKlTV37lzt3btXTZs21dtvv6033njD4bFt2rTR4MGD1bNnT9WsWVMTJ0500lYA+L3ZjAsP1gMAAKBc7GkCAACwgNAEAABgAaEJAADAAkITAACABYQmAAAACwhNAAAAFhCaAAAALCA0AQAAWEBoAgAAsIDQBAAAYAGhCQAAwIL/BTlhOkl2Ok4gAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x = \"cut\", y = df.cut.index, data = df);"
   ]
  }
 ],
 "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": "3.12.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}