{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a071108f-193a-4072-ac2b-44b73098994a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8b8717f9-3f86-4285-be08-c05e084fa9e8",
   "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>month</th>\n",
       "      <th>temperature</th>\n",
       "      <th>ice_cream_sales</th>\n",
       "      <th>beach_visitors</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Янв</td>\n",
       "      <td>-5</td>\n",
       "      <td>120</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Фев</td>\n",
       "      <td>-2</td>\n",
       "      <td>130</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Мар</td>\n",
       "      <td>4</td>\n",
       "      <td>180</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Апр</td>\n",
       "      <td>11</td>\n",
       "      <td>280</td>\n",
       "      <td>110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Май</td>\n",
       "      <td>17</td>\n",
       "      <td>430</td>\n",
       "      <td>340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Июн</td>\n",
       "      <td>22</td>\n",
       "      <td>680</td>\n",
       "      <td>760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Июл</td>\n",
       "      <td>26</td>\n",
       "      <td>920</td>\n",
       "      <td>1250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Авг</td>\n",
       "      <td>24</td>\n",
       "      <td>870</td>\n",
       "      <td>1180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Сен</td>\n",
       "      <td>17</td>\n",
       "      <td>490</td>\n",
       "      <td>410</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Окт</td>\n",
       "      <td>9</td>\n",
       "      <td>260</td>\n",
       "      <td>130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Ноя</td>\n",
       "      <td>3</td>\n",
       "      <td>160</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Дек</td>\n",
       "      <td>-2</td>\n",
       "      <td>125</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   month  temperature  ice_cream_sales  beach_visitors\n",
       "0    Янв           -5              120              20\n",
       "1    Фев           -2              130              25\n",
       "2    Мар            4              180              40\n",
       "3    Апр           11              280             110\n",
       "4    Май           17              430             340\n",
       "5    Июн           22              680             760\n",
       "6    Июл           26              920            1250\n",
       "7    Авг           24              870            1180\n",
       "8    Сен           17              490             410\n",
       "9    Окт            9              260             130\n",
       "10   Ноя            3              160              45\n",
       "11   Дек           -2              125              20"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.DataFrame({\n",
    "    'month': [\n",
    "        'Янв', 'Фев', 'Мар', 'Апр',\n",
    "        'Май', 'Июн', 'Июл', 'Авг',\n",
    "        'Сен', 'Окт', 'Ноя', 'Дек'\n",
    "    ],\n",
    "    'temperature': [-5, -2, 4, 11, 17, 22, 26, 24, 17, 9, 3, -2],\n",
    "    'ice_cream_sales': [120, 130, 180, 280, 430, 680, 920, 870, 490, 260, 160, 125],\n",
    "    'beach_visitors': [20, 25, 40, 110, 340, 760, 1250, 1180, 410, 130, 45, 20]\n",
    "})\n",
    "\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "259d32a0-fba3-43c8-8439-f60e101b6ce4",
   "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>ice_cream_sales</th>\n",
       "      <th>beach_visitors</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ice_cream_sales</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.987935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beach_visitors</th>\n",
       "      <td>0.987935</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 ice_cream_sales  beach_visitors\n",
       "ice_cream_sales         1.000000        0.987935\n",
       "beach_visitors          0.987935        1.000000"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "correlation = data[\n",
    "    ['ice_cream_sales', 'beach_visitors']\n",
    "].corr()\n",
    "\n",
    "correlation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "24d50fe8-c94c-4fb3-a709-92afc8ac59b6",
   "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>temperature</th>\n",
       "      <th>ice_cream_sales</th>\n",
       "      <th>beach_visitors</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>temperature</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.942339</td>\n",
       "      <td>0.883225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ice_cream_sales</th>\n",
       "      <td>0.942339</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.987935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beach_visitors</th>\n",
       "      <td>0.883225</td>\n",
       "      <td>0.987935</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 temperature  ice_cream_sales  beach_visitors\n",
       "temperature         1.000000         0.942339        0.883225\n",
       "ice_cream_sales     0.942339         1.000000        0.987935\n",
       "beach_visitors      0.883225         0.987935        1.000000"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "correlations = data[\n",
    "    ['temperature', 'ice_cream_sales', 'beach_visitors']\n",
    "].corr()\n",
    "\n",
    "correlations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f252b0a2-40e4-40e0-81c4-30134c932f68",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(9, 5))\n",
    "\n",
    "sns.set_theme(style='whitegrid')\n",
    "\n",
    "sns.regplot(\n",
    "    data=data,\n",
    "    x='ice_cream_sales',\n",
    "    y='beach_visitors',\n",
    "    scatter_kws={'s': 70, 'color': '#4C78A8'},\n",
    "    line_kws={'color': '#E45756'}\n",
    ")\n",
    "\n",
    "plt.title('Продажи мороженого и посещаемость пляжа')\n",
    "plt.xlabel('Продажи мороженого')\n",
    "plt.ylabel('Посетители пляжа')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:base] *",
   "language": "python",
   "name": "conda-base-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}