{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "1f46f36b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# data ussing a linear model\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "m = 500\n",
    "theta0 = 2.5\n",
    "theta1 = 5\n",
    "disp = 4\n",
    "x = np.linspace(0, 5, m)\n",
    "y = theta0+theta1*x+disp*np.random.randn(m)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d309848",
   "metadata": {},
   "source": [
    "$(x_m,y_m)$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "0419e9fb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(x,y,color='black', alpha=0.3, marker='o')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "089205c7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(0.8681163370978059)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Pearson coefficient\n",
    "xMean = x.mean()\n",
    "yMean = y.mean()\n",
    "\n",
    "#Sxx \n",
    "xSum = 0 \n",
    "for i in range(len(x)):\n",
    "    xSum = xSum+(x[i]-xMean)**2\n",
    "    pass\n",
    "Sxx = xSum\n",
    "\n",
    "Syy = np.sum((y-yMean)**2)\n",
    "\n",
    "Sxy = np.sum((x-xMean)*(y-yMean))\n",
    "r = Sxy/np.sqrt(Sxx*Syy)\n",
    "r"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "f798a04a",
   "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>Country</th>\n",
       "      <th>GDP per capita</th>\n",
       "      <th>Life satisfaction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Russia</td>\n",
       "      <td>9054.914</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Turkey</td>\n",
       "      <td>9437.372</td>\n",
       "      <td>5.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Hungary</td>\n",
       "      <td>12239.894</td>\n",
       "      <td>4.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Poland</td>\n",
       "      <td>12495.334</td>\n",
       "      <td>5.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Slovak Republic</td>\n",
       "      <td>15991.736</td>\n",
       "      <td>6.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Estonia</td>\n",
       "      <td>17288.083</td>\n",
       "      <td>5.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Greece</td>\n",
       "      <td>18064.288</td>\n",
       "      <td>4.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Portugal</td>\n",
       "      <td>19121.592</td>\n",
       "      <td>5.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Slovenia</td>\n",
       "      <td>20732.482</td>\n",
       "      <td>5.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Spain</td>\n",
       "      <td>25864.721</td>\n",
       "      <td>6.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Korea</td>\n",
       "      <td>27195.197</td>\n",
       "      <td>5.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Italy</td>\n",
       "      <td>29866.581</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Japan</td>\n",
       "      <td>32485.545</td>\n",
       "      <td>5.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Israel</td>\n",
       "      <td>35343.336</td>\n",
       "      <td>7.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>New Zealand</td>\n",
       "      <td>37044.891</td>\n",
       "      <td>7.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>France</td>\n",
       "      <td>37675.006</td>\n",
       "      <td>6.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>40106.632</td>\n",
       "      <td>6.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Germany</td>\n",
       "      <td>40996.511</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Finland</td>\n",
       "      <td>41973.988</td>\n",
       "      <td>7.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Canada</td>\n",
       "      <td>43331.961</td>\n",
       "      <td>7.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Netherlands</td>\n",
       "      <td>43603.115</td>\n",
       "      <td>7.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Austria</td>\n",
       "      <td>43724.031</td>\n",
       "      <td>6.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>43770.688</td>\n",
       "      <td>6.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Sweden</td>\n",
       "      <td>49866.266</td>\n",
       "      <td>7.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Iceland</td>\n",
       "      <td>50854.583</td>\n",
       "      <td>7.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Australia</td>\n",
       "      <td>50961.865</td>\n",
       "      <td>7.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Ireland</td>\n",
       "      <td>51350.744</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Denmark</td>\n",
       "      <td>52114.165</td>\n",
       "      <td>7.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>United States</td>\n",
       "      <td>55805.204</td>\n",
       "      <td>7.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Country  GDP per capita  Life satisfaction\n",
       "0            Russia        9054.914                6.0\n",
       "1            Turkey        9437.372                5.6\n",
       "2           Hungary       12239.894                4.9\n",
       "3            Poland       12495.334                5.8\n",
       "4   Slovak Republic       15991.736                6.1\n",
       "5           Estonia       17288.083                5.6\n",
       "6            Greece       18064.288                4.8\n",
       "7          Portugal       19121.592                5.1\n",
       "8          Slovenia       20732.482                5.7\n",
       "9             Spain       25864.721                6.5\n",
       "10            Korea       27195.197                5.8\n",
       "11            Italy       29866.581                6.0\n",
       "12            Japan       32485.545                5.9\n",
       "13           Israel       35343.336                7.4\n",
       "14      New Zealand       37044.891                7.3\n",
       "15           France       37675.006                6.5\n",
       "16          Belgium       40106.632                6.9\n",
       "17          Germany       40996.511                7.0\n",
       "18          Finland       41973.988                7.4\n",
       "19           Canada       43331.961                7.3\n",
       "20      Netherlands       43603.115                7.3\n",
       "21          Austria       43724.031                6.9\n",
       "22   United Kingdom       43770.688                6.8\n",
       "23           Sweden       49866.266                7.2\n",
       "24          Iceland       50854.583                7.5\n",
       "25        Australia       50961.865                7.3\n",
       "26          Ireland       51350.744                7.0\n",
       "27          Denmark       52114.165                7.5\n",
       "28    United States       55805.204                7.2"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#GDP vs life satisfaction:\n",
    "import pandas as pd\n",
    "data = pd.read_csv('gdp-satisfaction.csv')\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "08b9f450",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0              Russia\n",
       "1              Turkey\n",
       "2             Hungary\n",
       "3              Poland\n",
       "4     Slovak Republic\n",
       "5             Estonia\n",
       "6              Greece\n",
       "7            Portugal\n",
       "8            Slovenia\n",
       "9               Spain\n",
       "10              Korea\n",
       "11              Italy\n",
       "12              Japan\n",
       "13             Israel\n",
       "14        New Zealand\n",
       "15             France\n",
       "16            Belgium\n",
       "17            Germany\n",
       "18            Finland\n",
       "19             Canada\n",
       "20        Netherlands\n",
       "21            Austria\n",
       "22     United Kingdom\n",
       "23             Sweden\n",
       "24            Iceland\n",
       "25          Australia\n",
       "26            Ireland\n",
       "27            Denmark\n",
       "28      United States\n",
       "Name: Country, dtype: str"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = data[\"GDP per capita\"]\n",
    "y = data[\"Life satisfaction\"]\n",
    "labels = data[\"Country\"]\n",
    "labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "deaf6ab9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "plt.scatter(x,y, color=\"black\", alpha=0.4, marker=\"v\")\n",
    "# for i, row in data.iterrows():\n",
    "#     plt.annotate(data[\"Country\"], (data[\"Life satisfaction\"], data[\"GDP per capita\"]))\n",
    "#     pass\n",
    "# #plt.ylim([0,20])\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv (3.14.3)",
   "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": "3.14.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}