{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "974d9749",
   "metadata": {},
   "source": [
    "The [ggplot](https://ggplot2.tidyverse.org/) library is a great way to make attractive graphics, but unfortunately it's an R library, so we can't use it with Python.\n",
    "\n",
    "Instead, we'll use [plotnine](https://github.com/has2k1/plotnine), which is an attempt to bring ggplot to Python."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "318c3b6b",
   "metadata": {},
   "outputs": [],
   "source": [
    "from plotnine import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "14b3236e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "1e8c4b6d",
   "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>Year</th>\n",
       "      <th>Type of tree</th>\n",
       "      <th>Trees sold (millions)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2004</td>\n",
       "      <td>Real tree</td>\n",
       "      <td>27.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2005</td>\n",
       "      <td>Real tree</td>\n",
       "      <td>32.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2006</td>\n",
       "      <td>Real tree</td>\n",
       "      <td>28.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2007</td>\n",
       "      <td>Real tree</td>\n",
       "      <td>31.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2008</td>\n",
       "      <td>Real tree</td>\n",
       "      <td>28.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year Type of tree  Trees sold (millions)\n",
       "0  2004    Real tree                   27.1\n",
       "1  2005    Real tree                   32.8\n",
       "2  2006    Real tree                   28.6\n",
       "3  2007    Real tree                   31.3\n",
       "4  2008    Real tree                   28.2"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"christmas tree sales.csv\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "76d3953f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (318247485)>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ggplot(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "748410aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (318484294)>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ggplot(df) + aes(x='Year')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "345c3268",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (318513011)>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(\n",
    "    ggplot(df)\n",
    "    + aes(x='Year')\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "d26d7326",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (318569960)>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(\n",
    "    ggplot(df)\n",
    "    + aes(x='Year')\n",
    "    + aes(y='Trees sold (millions)')\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "86ac9209",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (318323523)>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(\n",
    "    ggplot(df)\n",
    "    + aes(x='Year')\n",
    "    + aes(y='Trees sold (millions)')\n",
    "    + geom_point()\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "d37c7105",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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6//771aFDB33xxRehrh8AgBprFmvXw42S9ae0RE1omKgJDZOUbA/voIzPNDUvr0gvHCrWWwWlev5Qsf5+qEg+pkgAJ1XtEdsffvhBrVu3PuHz6enpGjBggAYMGKCnnnpKr732mrKzs9W9e/egFAoAQCg4DEOtImj6weoStza6PfLpyMVskvRDmUfrSst1XrwjnKUBEa9an8nPPvtsQAe12+267rrralQQAADRLMfj1fFjs4akPR5uIQ2cTFB+31JcXKzNmzfL5NckAADUSordpqpm0zawMccWOJmAg+2MGTM0ZcoU/+PPPvtMzZo10+mnn642bdpoy5YtQS0QAIBockG8Uyl2m+y/PrZLami3qXu8M5xlAfVCwMH2ueeeU/Pmzf2Px48frzPOOEPLly9Xenq6Jk2aFNQCAQCIJvE2QxMaJqqfy6kucbG6yOXUfQ2T5GTEFjipgGfL79y5U6eddpokaffu3Vq/fr0++eQT9ezZUx6PR7fddlvQiwQAIJok2GwaksRtfYFABTxiGx8fr/z8fEnSBx98oMTERP/KBykpKTp8+HBwKwQAAACqIeAR227duunxxx+XzWbT9OnTNWDAANntR2YCbdmyRc2aNQt6kQAAAMDJ1OjisZycHA0ePFiFhYWaNm2a/7nFixezbi0AAADCIuAR2w4dOmjr1q06ePCgGjZsWOG5J598Uk2aNAnoeOXl5Zo3b56++eYbFRQUKD09XcOHD1fv3r0lSWPGjNGhQ4f8t+dt1KiRnnnmmUDLBgAAgMXV+FYrx4daSerUqVPAx/F6vUpLS9MjjzyijIwMbdiwQX/5y1+UkZGhdu3aSZImTpyorl271rRUAAAARIEaBdv3339fr7/+unbt2qXS0tIKzxmGoQ8++KDax4qLi9M111zjf9yhQwe1b99eGzZs8AdbAAAA4GQCDrbTp0/XhAkT1KpVK7Vv314NGjQIakGlpaXavHmzBg8e7N82c+ZMmaaprKwsXXvtterQoUNQ3xMAAAD1X8DB9plnntGdd96pp59+OujF+Hw+zZw5U23atNHZZ58t6cgNIFq3bi3pyPJiU6ZM0ezZs9W4ceMKr83JyVFOTo7/sdPpVNOmTYNa39HVH47+bVWGYVj2HKOhh1bun0QP67to6J9ED4FwMUzTNAN5QXJyst5880317ds3qIWYpqlnnnlGO3bs0JQpUxQfX/XC1BMnTlSvXr00YMCACtsffvjhCrf6nTRpUoUVGwAAAGBtAY/YDh48WKtWrQpqsDVNU/PmzdO2bds0derUE4ZaSbLZbKoqi48dO1ZDhgzxP3Y6ncrLywtajdKRn06Tk5OVn58vr9cb1GNHEpfLpaKionCXERLR0EMr90+ih/VdNPRPooe1kZqaGvRjInoEHGxvuOEG3XbbbSopKdHFF1+slJSUSvt06dIloGPOnz9fGzdu1COPPKKEhAT/9v3792vfvn1q27atJOnDDz/Upk2bdOedd1Y6RmZmpjIzM/2PDxw4ELIvml6v19JfkE3TtPT5SdbuYTT0T6KH9Z2V+yfRQyBcAp6KcHQ9Wf8BDMP/b9M0ZRhGQP/R9+3bpzFjxig2NrbCfJ1hw4bpvPPO05NPPqmcnBzFxMSoRYsWuvbaa6u1rNiBAweqXUN12e12paamKi8vz9KfzElJSSooKAh3GSERDT20cv8kelhdG8vKtbXcq3jD0O/iY5VoC/h+PCERDf2TrP15GOoepqenB/2YiB4Bj9h+9NFHQS2gcePG+uc//3nC52fNmhXU9wMAq3u3oETvFJXJLsmU9K+iUt3XMElp9sgItwAQKgEH26N3BAMARJ59Hq/eLiqTJHl+3VbsM7U0v0Q3p7rCVxgA1IEa33nshx9+0KpVq5Sbm6u0tDT16NFDZ5xxRjBrAwAEaL/XJ5sk3zHbvJJyPNb9tT8AHBVwsC0rK9N1112npUuXyjRNOZ1OlZWVyTAMDRs2TC+//LIcDkcoagUAnESqzVYh1EqSTVJDpiEAiAIBf6WbNGmS3n77bc2bN0+HDh1SSUmJDh06pHnz5untt9/WpEmTQlEnAKAamsba1SPeIZskQ5JdUowhXZF84mUUAcAqAh6xXbRokR577DHdfPPN/m3Jycm6+eabVVxcrCeeeEIzZswIapEAgOobkRyvUxwx2ur2KMFm6IJ4h9JjuEsUAOsLONjm5uaqXbt2VT7Xrl075ebm1rooAEDNGYahc+MdOjeeaWEAokvAUxHatWunl19+ucrnXnnllROGXgAAACCUAh6xffDBB3XVVVcpOztbV155pTIyMrRv3z69/vrrWr16tZYsWRKKOgEAAIDfFHCwveKKK/TGG29oypQpuvfee/13GzvrrLP0xhtvaPDgwaGoEwAAAPhNNVrHdsiQIRoyZIiKiop06NAhpaSkyOVi4W8AAACET41v0CBJLpeLQAsAAICIUK1ge9ddd+lPf/qTsrKydNddd/3mvoZhaNasWUEpDgAAAKiuagXbFStW6KabblJWVpZWrFjxm/sSbAEAABAO1Qq227Ztq/LfAAAAQKTg5uEAAACwhGqN2C5btiygg15xxRU1KgYAAACoqWoF22HDhlX7gIZhyOv11rggAAAAoCYCnmMLAAAARKJqBduWLVuGug4AAACgVqoVbHNzcwM6aFpaWo2KAQAAAGqqWsE2PT1dhmFU+6DMsQUAAEBdq1awfeGFFwIKtgAAAEBdq1awvf7660NcBgAAAFA73KABAABEJcMwTvpnwYIF4S6zWrZt26Z+/fopKSlJhmHo66+/rnK/mTNn6p133qnb4upQtUZszzzzTL322mvq2LGjOnXq9JvTEgzD0DfffBO0AgEAAEJh9erVFR6ff/75+uMf/6hRo0b5t7Vu3bquy6qRBx98UFu3btXrr7+uBg0aqG3btlXuN3PmTP3+97/XwIED67jCulGtYNu1a1e5XC7/v5lvCwAA6rvzzjuv0rasrKwqt0e6n376ST179tQll1wSlOOVlZUpNjZWNlv9+uV+tap98cUXdcopp0iSFixYoBdffPE3/wAAANRnK1askGEY2rRpU4XteXl5io+P19y5cyUduQ6pY8eOevfdd9WxY0fFxcWpa9euWrNmTaVjLliwQGeeeabi4uLUrFkz/fnPf67WSlKffvqpunfvrvj4eKWnp+vGG2/0L8WanZ0twzC0fv16vfzyyzIMQ61ataryOK1atdL27dv1zDPPVJpq0apVK91555164okn1LJlS8XHx/vfozp179q1S9dee63S09MVHx+vXr16af369Sc9t2CrXzEcAACgDgwcOFDNmjXTCy+8UGH7a6+9JkkVpivk5OTo9ttv13333ad//OMfcjqduuSSS7Rv3z7/Pk899ZTGjBmjSy65RCtWrNCECRP09NNP689//vNv1rF+/XpdfPHFSkpK0pIlS/TXv/5VK1as0IABA+T1epWZmanVq1erTZs2GjhwoFavXq033nijymO98cYbatKkiYYNG6bVq1dr9erVGjRokP/5pUuX6q233tKsWbO0fPlyuVyuatWdl5enHj166Ouvv9bs2bO1dOlSuVwu9e3bt8LHoC5UayrC8dasWaMlS5Zo586dKi0trfCcYRhavnx5UIoDAAAIB7vdrhtuuEEvvPCCHnnkEdntdklHlkC94oorlJKS4t83NzdXS5YsUd++fSVJvXv3VosWLfS3v/1Njz32mAoKCvTQQw/p/vvv16OPPipJuvjii+VwODR+/Hjdd999atiwYZV1TJs2TU2aNNFbb72l2NhYSVKLFi10ySWX6J133tHgwYN13nnnKSEhQY0aNfrNaRRnn322nE6nMjIyqtyvvLxc7777rn/6aXXrnjlzpg4dOqR169apcePGkqR+/fqpbdu2mjFjhp544olAPvS1EnCwnTVrlsaNG6fGjRurdevWcjgcoair1hwOh5xOZ1CPeXRuscvlkmmaQT12JImJiVFSUlK4ywiJaOihlfsn0cP6Lhr6J9FDq7jppps0bdo0vffeexo0aJC+/fZbffXVV5o+fXqF/Ro0aOAPtUcfX3TRRVq7dq0k6YsvvlBhYaGuuuoqeTwe/34XXXSRSkpK9P3336t3795V1vDZZ5/p6quv9odaSerfv79SUlK0atUqDR48OGjn26dPH3+oDaTu999/XxdeeKHS0tL8+9ntdvXu3Vtffvll0OqrjoCD7YwZM3TnnXdq5syZET2h2O12y+12B/WYdrtdDodDRUVFlr67WlJSkgoKCsJdRkhEQw+t3D+JHtZ30dA/iR7WRrAHpWqjVatWuvjii/X8889r0KBBeuGFF3TKKafowgsvrLBfo0aNKr02IyNDGzZskCQdOHBAktSlS5cq32fnzp0nrCEvL08ZGRlVHv/oHNhgOf59qlv3gQMHtGbNmgrh+6i6XlUi4GBbVFSkoUOHRnSoBQAACIabb75Zo0aN0u7du/Xqq6/qrrvuqrQ61P79+yu9bu/evcrMzJQkpaWlSZKWLVumFi1aVNr36AX6VUlLS6tynurevXv9xw2W48+runWnpaXp0ksv1dSpUyvtU9c/qAQcbEeMGKF3331X/fr1C0U9AAAAEWPo0KFKTU3VqFGjlJubW+XdWA8fPqwPP/zQPx3h8OHDWrlype644w5JR9bHTUhI0K5du3T55ZcH9P49evTQm2++qSeffFIxMUdi27///W8dOnRIPXr0CPh8HA5HpeujTqS6dV900UV65ZVX1L59+wpTGcIh4GA7c+ZMjRkzRqNGjdJFF11UYfL0UVdccUUwagMAAAir2NhY/eEPf9D06dN1ySWXVDlymZaWpptuuklTpkxRSkqKHn/8cZmmqXvuuUeSlJKSor/85S+6//77tWvXLvXp00d2u11bt27V8uXLtXTpUiUkJFT5/n/+85/VvXt3/f73v9cf//hH7d27Vw888IC6detWo5sstG/fXh9++KH+/e9/KzU1VaeccsoJL1yrbt3jx4/Xq6++qt69e+vuu+9WVlaW9u/fr7Vr16pp06YaN25cwHXWVMDB9qefftLnn3+u7OxsLVq0qNLzhmFYet4UAACILpdffrmmT5+uG2+8scrnMzMz9de//lX33XeftmzZojPOOEP/+te/KsxZvffee9WsWTM99dRTmj17tmJjY9W6dWv9/ve//80L8bt27ar3339fEydO1JVXXimXy6UhQ4boySef9K/UEIhHH31Ut912m6688koVFBToxRdfrHIUOpC6GzZsqDVr1mjy5MmaMGGCDh48qMaNG+u8884LeIS6tgwzwEsau3btqvLycj322GNq27Ztlc1o2bJl0AqsqaMTnoPJbrcrNTVVeXl5lg7vVr/oweo9tHL/JHpY30VD/yR6WBvp6elBP2Zt/c///I/mzp2r3bt3V5ozev311+s///mPvv/++zBVh2MFPGK7YcMGLVu2TJdeemko6gEAAIgIGzdu1MaNGzV79mzdcccdEbViA6oWcLA966yztHfv3lDUAgAAEDHGjh2rNWvW6NJLL9XEiRPDXQ6qIeBgO3fuXF1//fXKzMxU3759/VfoAQAAWMnHH3980n0WLFgQ8jpQfQGn0p49e6q8vFwDBgyQzWZTfHx8hecNw9Dhw4eDViAAAEAohGoetFXvOlcfBBxs77333koL+AIAAADhFnCwffjhh0NQBgAAAFA73BcXAAAAllCtYDtixAh9/fXX1T5oaWmp5syZoxdeeKGmdQEAAAABqVawzcrK0gUXXKCzzz5b06ZN08cff6zc3Fz/8263Wxs3btRrr72m6667ThkZGXrppZfUuXPnkBUOAABgZQ8//LBGjhwZ7jLqlWoF2+nTp2vz5s0aMmSInn/+efXt21eNGjVSbGysEhISFB8frw4dOuj6669Xfn6+Xn31VX355Zfq2rVrqOsHAACIeH369FFcXJwSExP9f9588806ee8FCxbovPPOq5P3CrdqXzyWmZmpKVOmaMqUKdqyZYu+/PJL5eTkqLS0VGlpaTr99NPVrVs3JSQkhLJeAACAemnmzJm69dZbw11GlTwejyXuTVCji8dat26tkSNHaty4cZo4caLGjh2rPn36EGoBAIClmOXlKv70IxUs+4eKP/1IZnl5UI8/fvx4ZWVlKSkpSV26dNEnn3xS5X4+n0933HGHLrzwQuXn5ys/P1+33nqrmjdvriZNmujOO+9UaWlppdd99913uvXWW/Xll1/6R4qLior08MMP64orrtCNN96olJQUTZ8+XW63W5MmTdIpp5yi9PR0jRo1Snl5ef5jffnll+rVq5dSU1PVvn17LVu2LKgfi2BgVQQAAIAqmOXlyp35hAqWLVbxpx+qYNli5c6aHtRw27VrV3311VfKy8vT6NGjddVVV6m4uLjCPm63W1dffbV2796td999V8nJybrhhhtUWlqqH3/8UT/99JM2bdqkqVOnVjp+p06dNG/ePJ1zzjkqLCxUYWGhXC6XJGnFihXq37+/cnNzdc8992jixIn66quvtHbtWu3cuVMOh0N33nmnJCknJ0eXXnqpxo8frwMHDmjBggUaM2aMNmzYELSPRTAQbAEAAKpQsnqVPLt3Sl6v/49n1w6VrF5Vo+ONHz9eKSkpSklJUfPmzSVJ11xzjdLT0xUTE6N77rlH5eXlFcJiYWGhBg0apISEBC1dulRxcXHat2+f/vnPf2r27NlKTk5WSkqKJk+erIULFwZUT9euXTVy5EjZbDbFxcVp3rx5+tvf/qbGjRsrPj5eU6dO1ZIlS+T1evXyyy/roosu0mWXXSa73a5zzz1Xl19+uZYsWVKjj0Wo1P/JFAAAACHgPbC/6u0HD9ToeE899VSlObYzZszQ888/r19++UWGYSg/P18HDvz3+OvWrVNRUZG+++472e12SVJ2dra8Xq9atGjh3880TXm93oDqadmypf/f+/fvV3Fxsc4///wK+9hsNu3Zs0fZ2dlavny5UlJS/M95PB5dd911Ab1nqBFsAQAAqmBPb1T19obpQTn+Z599pscee0wfffSROnbsKJvNptTUVJmm6d+nb9++6t69u/r27auPPvpIp5xyirKyshQTE6N9+/bJ4XCc9H0Mwzjp9vT0dMXHx+vrr79Wq1atKu2blZWlkSNHasGCBQGfZ11iKgIAAEAV4s/voZhmLSS73f8npnmW4s/vEZTjFxQUKCYmRunp6fJ4PJo2bZry8/Mr7XfXXXdp3LhxuvDCC5Wdna0mTZpo0KBBuvvuu5WXlyfTNLVz50699957Vb5PRkaGdu/erbKyshPWYrPZNHbsWI0bN045OTmSpH379mn58uWSpGuvvVbvvvuuVqxYIY/HI7fbrbVr1zLHFgAAoD4wYmOVds/9SrpihBJ691PSFSOUdvd9MmJjg3L8Sy65RIMGDVK7du3UsmVLxcbGVphecKy7775b99xzjz/cvvTSS4qNjdVZZ52lBg0a6JJLLtHPP/9c5Wv79u2rs846S5mZmUpJSVFRUVGV+z3++OPq3LmzevbsqaSkJHXv3l3r1q2TJDVv3lzvvPOOZs6cqYyMDDVt2lQTJ078zbAcDoZ57Hj3CdhsthMOY1cl0DkeoXDs/JRgsdvtSk1NVV5eXkScY6gkJSWpoKAg3GWERDT00Mr9k+hhfRcN/ZPoYW2kpwfn1/zVEaoeJSUlheS4OLlqzbF96qmn/MHW4/Fo5syZcjgcuuyyy5SRkaE9e/bozTffVHl5ucaNGxfSggEAAICqVCvY3nPPPf5/T5gwQWeffbbefPNN2Wz/nckwY8YMDR061D8vAwAAAKhLAc+xXbBggW6//fYKoVY6Ml3h9ttv10svvRS04gAAAIDqCni5r5KSEmVnZ1f5XHZ2dpW3c/st5eXlmjdvnr755hsVFBQoPT1dw4cPV+/evSVJ27dv1+zZs5Wdna2MjAzdcsst6ty5c6BlAwAAwOICHrG97LLLNGHCBL300ks6fPiwJOnw4cNasGCBJk6cqMsuuyyg43m9XqWlpemRRx7RokWLdMcdd+h///d/9dNPP8nj8Wjq1Knq1q2bFi5cqJEjR+qxxx7ToUOHAi0bAAAAFhfwiO0zzzyj4uJi3XjjjbrxxhsVGxur8vJymaapyy+/XHPmzAnoeHFxcbrmmmv8jzt06KD27dtrw4YNKikpUVlZmYYNGyabzaaePXtqxYoV+vzzzzVo0KBASwcAAICFBRxsk5KS9Prrr2vDhg368ssvlZOTo8zMTJ1zzjlq3759rQsqLS3V5s2bNXjwYO3YsUOtWrWqMJ/31FNP1fbt2yu9Licnp8KFa06nU02bNq11Pcc6eiu7o39blWEYlj3HaOihlfsn0cP6Lhr6J9HD+oJluaynxrfUbd++fVCC7LF8Pp9mzpypNm3a6Oyzz9bPP/8sl8tVYR+Xy6V9+/ZVeu38+fM1ZcoU/+NJkyZp2rRpQa3vqOTk5JAcN5JU5xZ99ZnVe2j1/kn0sL6zev8kegiEQ7WC7VdffRXQQbt06RJwIaZpau7cucrNzdWUKVNkGIbi4+Mr3R2jqKhI8fHxlV4/duxYDRkyxP/Y6XQqLy8v4Dp+i91uV3JysvLz8y29sLjL5TrhXUnqu2jooZX7J9HD+i4a+ifRw9pITU0N+jERPaoVbH/3u99V685jpmnKMIyA/6Obpql58+Zp27Ztmjp1qj+4ZmVlaenSpfL5fP7pCNu2bVOvXr0qHSMzM1OZmZn+xwcOHAjZF02v12vpL8imaVr6/CRr9zAa+ifRw/rOyv2T6GF9wZ3HrKdawfajjz4KaRHz58/Xxo0b9cgjjyghIcG/vVOnTnI4HFq2bJmGDh2qtWvXavv27brgggtCWg8AAADqn2oF26NryobCvn379M477yg2NlY33nijf/uwYcM0fPhwTZ48WXPmzNGiRYvUuHFjTZw4USkpKSGrBwAAAPVTjS8e++GHH7Rq1Srl5uYqLS1NPXr00BlnnBHwcRo3bqx//vOfJ3y+VatWmjFjRk3LBAAAQJQIONiWlZXpuuuu09KlS2WappxOp8rKymQYhoYNG6aXX37Z8leCAgAAIPIEfOexSZMm6e2339a8efN06NAhlZSU6NChQ5o3b57efvttTZo0KRR1AgAAoAqtWrXSe++9F+4yIkLAwXbRokV67LHHdPPNN/vXsEtOTtbNN9+sadOmaeHChUEvEgAAoD7r06eP4uLilJiYqIYNG+rSSy/Vzz//HPL3vf766/XAAw+E/H0iRcDBNjc3V+3atavyuXbt2ik3N7fWRQEAAFjNzJkzVVhYqJ07d6pRo0YVLpoPF6stTRdwsG3Xrp1efvnlKp975ZVXThh6AQAA6pty09RHBcX6R26BPiooVrlp1vqYCQkJGjlypP7f//t//m179uzRiBEjlJGRoRYtWujhhx+Wz+eTdGQN/379+qlhw4ZKT0/X1VdfXa2bUM2dO1evvvqqnnrqKSUmJvrvA9CnTx9NmjRJffr0kcvl0rp1637z/aUjGa9jx45KSUlRz5499cMPP9T64xAKAV889uCDD+qqq65Sdna2rrzySmVkZGjfvn16/fXXtXr1ai1ZsiQUdQIAANSpctPUE3tytdPt8W9bXVii+5qkKbYaN646kYKCAr366qs67bTTJEk+n09DhgzRxRdfrJdeekm5ubkaNGiQmjVrpptvvlmmaWrChAnq3bu3CgoKNGzYMD344IOaM2fOb77P7bffrnXr1qlJkyZ6/PHHKzy3YMECvfPOOzrzzDNVXl6unj17nvD9V6xYocmTJ2vFihXq0KGDnnvuOQ0ePFg//fRTxC0YEPCI7RVXXKE33nhDxcXFuvfee3XNNddo/PjxKi4u1htvvKHLL788FHUCAADUqVWFJdrp9sgr+f/scHu0qrCkRscbP368GjRooOTkZK1bt06vvPKKJOk///mPdu7cqUceeURxcXFq2rSpxo8f779u6dRTT1X//v3ldDqVnp6ucePG6ZNPPqnVuY0ePVpnnXWWbDabvvnmm998///93//VhAkT1KlTJ9ntdo0dO1aGYWjNmjW1qiEUarSO7ZAhQzRkyBAVFRXp0KFDSklJkcvlCnZtAAAAYbO/vOq5pwc8NZuT+tRTT+nWW2/V5s2bNXDgQG3atEmdOnVSdna29u/fr9TUVP++Pp9PLVq0kCTt3btXd999tz777DMVFBTI5/PV+ra9LVu29P/7ZO+fnZ2t++67TxMnTvQ/73a7tXv37lrVEAo1vkGDJLlcLrlcLhUXF2vz5s1q3bq1jFoMzQMAAESKRrH2Krenx1S9vbpOO+00zZo1SzfddJMGDBigrKwsNW/eXNnZ2VXuP2nSJPl8Pn377bdq2LChli9frrFjx1brvU6Uy47dfrL3z8rK0v3336/rr7++Wu8ZTgFPRZgxY4amTJnif/zZZ5+pWbNmOv3009WmTRtt2bIlqAUCAACEQ4/EeLVwxMgu+f9kOWLUIzG+1sceMGCAMjIyNH/+fJ1zzjlq1KiRpk6dqqKiIvl8Pm3atMk/3aCgoEAul0sNGjTQL7/8EtAdWTMyMrR169bf3Odk73/bbbfp8ccf1zfffCPTNFVYWKgVK1aooKCg5h+AEAk42D733HNq3ry5//H48eN1xhlnaPny5UpPT+cGDQAAWJRn2xYVvr5Qe1+YL/f334a7nJCLNQzd3yRNI9KS1C85QSPSkmp94dixJkyYoL/+9a9yu91asWKFNm3apDZt2ig1NVXDhw9XTk6OJOmhhx7St99+q5SUFA0cOFCXXXZZtd/jpptu0qZNm5SamqoLL7ywyn3sdvtvvv/QoUP10EMP6Q9/+INSUlLUpk2bE66QFW6GaQa2boXL5dI777yj3r17a/fu3WrRooU++eQT9ezZU2+++aZuu+02/wcinA4cOBD0Y9rtdqWmpiovL89Sa74dLykpKSJ/CguGaOihlfsn0cP6Lhr6J1mzh+7vv1HxS89JMiQdiQ7xQ6+Us0efoL5Penp6UI/3W0LVo9rOf0XNBTxiGx8fr/z8fEnSBx98oMTERHXv3l2SlJKSosOHDwe3QgAAEHYlSxdLpimZvl//NlXyz2Uyy8vDXRrgF/DFY926ddPjjz8um82m6dOna8CAAbLbj0yi3rJli5o1axb0IgEAQPiYpimzsIrRTZ9PZlGhjJTUys8BYVCji8dycnI0ePBgFRYWatq0af7nFi9e7B+9BQAA1mAYhmwN06Xj55Y6HDKSksNTFFCFgEdsO3TooK1bt+rgwYNq2LBhheeefPJJNWnSJGjFAQCAyJBw9R9UOP9pyeeTYRgyvV4ljPqDDHvtlr4CgqnG69geH2olqVOnTrUqBgAARKaYlq2U9Kc/y/vj94p3OuVp2UpGYwazEFlqdYMGAAAQPexpDeXo3TcqVrZA/USwBQAAUYlluawn4IvHAAAAgEhEsAUAAIAlBCXYZmdna+XKlcrNzQ3G4QAAAICABRxs7733Xt1zzz3+x2+88YZOP/109e/fX23atNH69euDWR8AAABQLQEH2zfeeEO/+93v/I8nTZqkgQMH6ttvv1W3bt00efLkoBYIAAAAVEfAwTYnJ0dZWVmSjtxCd+PGjZo8ebI6duyoP/7xj/rPf/4T9CIBAACAkwk42DZo0ED79u2TJP373/9WWlqaunbtKklyOp0qKSkJboUAAABANQS8jm2vXr30P//zP9q7d69mzJihyy67zP/cxo0b/aO5QKTx5h6UJ3ubClNS5GveQnI4w10SAAAIooCD7d/+9jddd911euCBB9SlSxdNmzbN/9zLL7+snj17BrVAIBjKN/ygogV/lwyp0DRluBKVeMc42Rumh7s0AAAQJIZpmmawDpafn6+4uDg5HI5gHbJWtTidwR2RMwxDDodDbrdbQfywRZyYmBh5PJ5wlxE0PneZfrn3jzLdZf/daLPLceqpyrjPehc7Wq1/x4uGz0Mr9zAa+ifRw9oI9vduRJda3VJ3586d2rlzpzp37iyXy6Xk5ORg1VVrbrdbbrc7qMe02+1yOBwqKiqy9P2xk5KSVFBQEO4ygsa7J6diqJUkn1fuHTssdZ5HWa1/x4uGz0Mr9zAa+ifRw9og2KI2anSDhmeffVbNmjVTy5Yt1bNnT23cuFGSdPnll2vWrFlBLRCoLSMxsertLlcdVwIAAEIp4GA7c+ZM/fGPf9To0aP1/vvvV/g1RJ8+fbRkyZKgFgjUli0xSY4evSVbxf/u8b+/LDwFAQCAkAh4KsLs2bP14IMPavLkyZV+BXH66af7R2+BSBI/dJjsjRrL8+P3crhcsp1zvuxtTg93WQAAIIgCDra7d+9W9+7dq3wuNjZWhYWFtS4KCDbDMOS8oLcSevVVamqq8vLyLD2/DwCAaBTwVISWLVtq3bp1VT63du1atW3bttZFAQAAAIEKONjefPPNeuSRR/T8888rPz9fklReXq63335b06dP19ixY4NeJAAAAHAyAU9F+NOf/qQdO3bolltu8YfYCy64QJJ0++236/bbbw9uhQAAAEA11Ggd26efflp33323Vq5cqYMHDyotLU39+vVTmzZtgl0fAAAAUC01vkFD69at1bp162DWAgAAANRYjW7QUF5ernnz5ummm25S//79tWnTJknS4sWLtWHDhqAWCAAAAFRHwCO2W7du1UUXXaQDBw7o7LPP1qpVq/y3Dfz000/13nvv6cUXXwx6oQAAAMBvCXjE9q677lKjRo20detWffDBBxXuPNa7d299+umnQS0QAAAAqI6AR2w//vhjLVy4UOnp6ZUWuG/SpIlycnKCVhwAAABQXQGP2MbExFQYpT3W3r17lZiYWOuiAAAAgEAFHGx79+6tJ598UuXl5f5thmHINE09++yz6tevX1ALBAAAAKoj4KkIjz/+uC644AJ16NBBQ4YMkWEYeuaZZ/T9999r06ZNJ7zdLgAAABBKAY/Ytm/fXuvXr1f37t21cOFC2e12vfXWWzrttNO0bt061rYFAABAWAQ0YltaWqq5c+eqf//+eumll0JVEwAAABCwgEZs4+LiNHnyZB08eDBU9QAAAAA1EvBUhLPOOks//vhjKGoBAAAAaizgi8dmzZqla665Ro0aNdLAgQOVkJAQiroAAACAgFQr2P7f//2fBg0apIYNG6pv375yu90aMWKEJCkhIUGGYfj3NQxDhw8fDk21AAAAwAlUK9jecMMNWr16tRo2bKh77723QpAFAAAAIkG1gu2xdxp7+OGHQ1ULAAAAUGMBXzwGAAAARKJqXzy2cOFCrVq16qT7GYahcePG1aooAAAAIFDVDrazZs2q1n4EWwAAAIRDtYPtmjVr1K1bt6AX8NZbb+nDDz9Udna2zj//fN13333+58aMGaNDhw7JZjsyY6JRo0Z65plngl4DAAAA6r+A17ENtrS0NA0fPlxff/21CgoKKj0/ceJEde3aNQyVAQAAoD4Je7Dt3r27JGnr1q1VBlsAAACgOsIebE9m5syZMk1TWVlZuvbaa9WhQ4dwlwQAAIAIVK1g6/P5Ql1HlcaPH6/WrVtLkj744ANNmTJFs2fPVuPGjSvtm5OTo5ycHP9jp9Oppk2bBrUeu91e4W+rMgzDsucYDT20cv8keljfRUP/JHoIhEtEj9geOzo7cOBAffbZZ1q/fr0GDBhQad/58+drypQp/seTJk3StGnTQlJXcnJySI4bSRwOR7hLCCmr99Dq/ZPoYX1n9f5J9BAIh4gOtsez2WwV7oJ2rLFjx2rIkCH+x06nU3l5eUF9f7vdruTkZOXn58vr9Qb12JHE5XKpqKgo3GWERDT00Mr9k+hhfVa+ZZOK314uFRbI3jxLCZdfJVuSNcORVXsohf5zMDU1NejHRPQIe7D1er3yer3y+Xzy+Xxyu92y2WzKy8vTvn371LZtW0nShx9+qE2bNunOO++s8jiZmZnKzMz0Pz5w4EDIvukdrdmqTNO09PlJ1u5hNPRPoof1jWd7tgrnzpR+ndrmyT2o8p3blTR+ogwLjmxasYfHs/LnIOqvsAfbxYsXa9GiRf7Hn3/+ufr27asrrrhCzz77rHJychQTE6MWLVrowQcfrBBeAQD1Q9mnH0q+Y37j5vXKl3tQ5Rt/lKPTWWGrC4C1hD3Yjho1SqNGjaryuere7QwAENnMkmJJx00ls9lklpSEpR4A1mQLdwEAAOuLOa2tdPxV9F6vYrJahaUeANZEsAUAhJyzdz/Fduh05IFhSDabEoZfI3sTppcBCJ6wT0UAAFifYbcrYfRN0t49cslUsStJSkoKd1kALIZgCwCoE4ZhyN6suRJSU1WWl8cV9QCCjqkIAAAAsASCLQAAACyBYAsAiHqmz3fCO1sCqD+YYwsAiFq+4iIVL3xZno0/SjabHOecr/ihV8qI4dsjUB/xmQsAiEqmaaroxWfl3ZF95Fa/Pp/c676Q7DYlXHZVuMsDUANMRQAARCWzoEDebVukY1dn8Hrl/nJt+IoCUCsEWwBAdPKdYLkx01e3dQAIGoItACAqGckNZMtsKtmO+VZotyv2jDPDVxSAWiHYAgCikmGzKfGm22TPbOrfFtOugxKGXR3GqgDUBhePAQCili0lVYn3TJBZXCTDbpcRFx/ukgDUAsEWABDVDMOQ4UoMdxkAgoCpCAAAALAEgi0AAAAsgWALAAAASyDYAgAAwBIItgAAALAEgi0AAAAsgWALAAAASyDYAgAAwBIItgAAALAEgi0AAAAsgWALAEAEMk1TZlmZTNMMdylAvRET7gIAAEBF7u++UfHiV6TSEhnxCUoYea1izzgz3GUBEY8RWwAAIohnR7aK/+85qbREkmSWFKtowXPy7NoZ5sqAyEewBQAggpR//41kO+7bs804sh3Ab7LsVASHwyGn0xnUYxqGIUlyuVyWnvMUExOjpKSkcJcREtHQQyv3T6KH9V009E+qXQ+9DofKjt9oGHI6nRHx/yJaeoj6ybLB1u12y+12B/WYdrtdDodDRUVF8nq9QT12JElKSlJBQUG4ywiJaOihlfsn0cP6Lhr6J9Wuh2bb9tK/3qm40euTr027iPh/EeoeBntQCtGFqQgAAESQmKxWShh9kxQXJ0ky4uPl+sMYxTRvEebKgMhn2RFbAADqK0ensxTbsbNUViY5nf5f/wP4bQRbAAAikGEY/lFbANXDVAQAAABYAsEWAAAAlsBUBCDMfIcPyXcoT7a0hrIlJYe7HEmS6fXKt3ePTNOUPSNDRkxsuEsCAOCkCLZAGJX8622V/fvdIw8MQ/FDr5SzR5+w1uQ7fEiFz86Rb+8eSZItraFct9wpe3qjsNYFAMDJMBUBCBP3d1+rbOV7/91gmip583V5tmwOX1GSil5+Qb79+/2PfYfyVPTCPBZiBwBEPIItECaeTT9X3hgTI8+WKrbXEdPrlXf7Nsl3zKLrPp98+/bKLCkOW10AAFQHwRYIE8PprHw/eFOSwxGWeiQdqcdur/IpI5Z5tgCAyEawBcLEcc65kmEc+SMdCZWxMXKc1TVsNRmGcWSO77GB225XbLfzZMSGMXADAFANXDwGhIm9cRMl3j5OJW8sli8vV7ZGGUq4cqRsKalhrStu4BDJ4ZB73RrJ9MlxdlfFDRgS1poAAKgOgi0QRjFZLZV09/3hLqMCw2ZTfP+Biu8/MNylAAAQEKYiAAAAwBIItgAAALAEgi0AAAAsgTm2AGBB3j058uzIlhGfoNh27VnVAkBUINgCgMWUrf1CJa8vPLImsc8nW8NGSrxznGyuxHCXBgAhxVQEALAQX17ukVBrmpLHc+TOcbkHVPLPZeEuDQBCjmALABbi3ZNTxUavvDuy67wWAKhrBFsAsBAjKenIaG2FjYaM5AbhKQgA6hDBFgAsxN6shWLO6HRkfq3kv21z/IDB4S0MAOoAF48BgIUYhiHX6DEq+3ilPJt/luFKlLNXX8VktQx3aQAQcgRbALAYw25XXL9LpH6XhLsUAKhTTEUAAACAJRBsAQAAYAkEWwAAAFhCRMyxfeutt/Thhx8qOztb559/vu677z7/c9u3b9fs2bOVnZ2tjIwM3XLLLercuXMYqwUAAEAkiogR27S0NA0fPlz9+/evsN3j8Wjq1Knq1q2bFi5cqJEjR+qxxx7ToUOHwlMoAAAAIlZEBNvu3bvrvPPOU3JycoXt3333ncrKyjRs2DDFxsaqZ8+eysrK0ueffx6mSgEAABCpIiLYnsiOHTvUqlUr2Wz/LfPUU0/V9u3bw1gVAAAAIlFEzLE9kZKSErlcrgrbXC6X9u3bV2nfnJwc5eT89x7pTqdTTZs2DWo99l/v5HP0b6syDMOy5xgNPbRy/yR6WN9FQ/8kegiES0QH2/j4eBUVFVXYVlRUpPj4+Er7zp8/X1OmTPE/njRpkqZNmxaSuo6fMmFFDocj3CWElNV7aPX+SfSwvrN6/yR6CIRDRAfbrKwsLV26VD6fzz8dYdu2berVq1elfceOHashQ4b4HzudTuXl5QW1HrvdruTkZOXn58vr9Qb12JHE5XJV+oHCKqKhh1bun0QP67to6J9ED2sjNTU16MdE9IiIYOv1euX1euXz+eTz+eR2u2Wz2dSpUyc5HA4tW7ZMQ4cO1dq1a7V9+3ZdcMEFlY6RmZmpzMxM/+MDBw6E7Ivm0XqtyjRNS5+fZO0eRkP/JHpY31m5fxI9BMIlIoLt4sWLtWjRIv/jzz//XH379tU999yjyZMna86cOVq0aJEaN26siRMnKiUlJXzFAsAxfMXFKv/hW6msVPZTTlNMs+bhLgkAolZEBNtRo0Zp1KhRVT7XqlUrzZgxo44rAoCT8+XmqmDODJlFRZJhk7wexV81Ss5u54e7NACIShG93BcARLLiZYtkFhZJXq/kKZdMUyWvL5SvID/cpQFAVIqIEVvUjOkpV+nKf8mzdbNsrkQ5+16smBYtw12WvL/sVukH78lXkK+YVqcq7uIBMmKtfXUwopP3l92S77g5hj6ffAf2y5bEFeMAUNcItvWU6fOp6Pl58mzdLHm98hqGyn/4Vol3jldMVquw1eX9ZZcKnp5xZATLNOXdni3P1i1KvO1uGax5CIuxNWggb0G+ZJoVthuEWgAIC6Yi1FPe7dvk2bTxSICUjnxjNU2V/uvtsNZV+u/3/KFW0pHQvX2bPFt+DmtdQCjED75CMowjfyTJZpPj/B6ypzcKb2EAEKUYsa2nfIWFkt3+32ArSaYZ9rl9vipGr2SzyywsDE9BQAjFnHqaEu/6k8q++EwqLVVMm9PlOK/ycoQAgLpBsK0mz/ZsFa/9XKWmKZ16mmJ+d66Mo6M0YWDPbCr5fMdttCsm65TwFHS0hKxW8u7cXjFw+7yyN2UJJFhTTPMsxQy/JtxlAABEsK2W8k0bVfTsHEmS2zSl9evk+GWXEoYOC1tN9vRGir9yhEqWLj4ycuvzyZbRRPGDhoatJkmKv2SQvNu2yLtrp2S3SR6P4oZcIXuTzJO/GAAAoBYIttVQsnxpxV+v+3xyf/ax4vpcJFuDlHCVJed5PRTTqrW8u3fKiI9XTNt2MmJiw1aPJBlOpxLvHC/Pzz/JLCqUvWlz2Zs2C2tNAAAgOhBsq8EsOFzldl/+4bAGW0myN8mMuNFQw25XbPszwl0GAACIMqyKUA22Jk0l23EfKrtdtoZc+QwAABApCLbVkHDVKBkJLslulxEbKxmGEkZcK1tCQrhLAwAAwK+YilAN9vRGSrrvz/Ju+EHxMTEqz2wmI6NJuMsCAADAMQi21WRzJSr23O5KSU1VXl6evF7vyV8EAACAOsNUBAAAAFgCwRYAAACWQLAFAACAJTDHFkC94Dt8SCXL/iFvzm4VpafLMXCobM2zwl0WACCCMGILIOL5SopV8PQMlf/0g3y5B1W66Wflz35S3l92hbs0AEAEIdgCiHjl338rs7BAOroaiWlKPp/KPv8svIUBACIKwRZA5CstlYzjvlyZpszSkvDUAwCISARbABHP3uoUyeupuNFmU8ypp4WnIABARCLYAoh4MS1aKv7y4ZJhSDIkSc7fnSvH+T3CWxgAIKKwKgKAesHZvadiO3SUDh5QSossFcUncAdAAEAFBFsA9YYtJVX2hulypKaqKC8v3OUAACIMUxEAAABgCQRbAAAAWALBFgAAAJZAsAUAAIAlEGwBAABgCYZpmma4iwiF/Px8OZ3OoB7TMAw5HA653W5Z9MMmSYqJiZHH4zn5jvVQNPTQyv2T6GF9Fw39k+hhbQT7ezeii2WX+3K73XK73UE9pt1ul8PhUFFRkaXXz0xKSlJBQUG4ywiJaOihlfsn0cP6Lhr6J9HD2iDYojaYigAAAABLINgCAADAEgi2AAAAsASCLQAAACyBYAsAAABLsOxyX6GQk5Oj+fPna+zYscrMzAx3OagBelj/0cP6jf7Vf/QQkYwR2wDk5ORoypQpysnJCXcpqCF6WP/Rw/qN/tV/9BCRjGALAAAASyDYAgAAwBIItgHIzMzUQw89xJyieowe1n/0sH6jf/UfPUQk4+IxAAAAWAIjtgAAALAEgi0AAAAsISbcBYRLeXm55s2bp2+++UYFBQVKT0/X8OHD1bt3b0nS9u3bNXv2bGVnZysjI0O33HKLOnfu7H/9559/rpdeekm5ublq166d7rrrLjVu3LjS+/z5z3/Wd999p9dff10Oh6POzs/qQtm/hx9+WD/++KN/X4/Ho9jYWC1evLhuT9LiatPD3NxczZ07V5s3b/b/u3nz5hWO/8orr+i9996Tx+PRBRdcoFtvvVWxsbF1fp5WFsoevvfee1q2bJny8/MVGxurrl276pZbblFCQkJYztWKQv05uG3bNj333HPatGmTHA6H+vfvr9GjR9f5eSLKmFGqpKTEfOWVV8ycnBzT5/OZP/zwgzlixAhzw4YNZnl5uXnTTTeZixcvNt1ut/npp5+aI0aMMPPy8kzTNM0dO3aYV111lfnVV1+ZpaWl5t///nfz3nvvrfQeK1euNCdMmGAOHjzYLCsrq+MztLa66N9Rf/3rX82nn366js4setSmh7m5uebbb79tbty40Rw8eLC5c+fOCsf+17/+ZY4ZM8bMyckxDx8+bN5///3miy++WPcnaXGh7GFOTo6Zn59vmqZpFhUVmdOnTzfnzp1b16doaaHsX35+vnnttdeaK1euNMvKyszS0lJz69atYThLRJuonYoQFxena665Rk2aNJFhGOrQoYPat2+vDRs26LvvvlNZWZmGDRum2NhY9ezZU1lZWfr8888lSR9//LG6dOmis88+W06nU6NGjdK2bdu0Y8cO//Hz8/P1j3/8QzfccEO4TtHSQt2/owoKCrR27VpddNFFdX2KllebHqampmrgwIFq27ZtlcdeuXKlhg4dqiZNmig5OVkjR47UBx98UJenFxVC2cMmTZooKSnJ/9gwDG4IEGSh7N/y5ct11llnqV+/fnI4HHI6nTrllFPq8vQQpaI22B6vtLRUmzdvVsuWLbVjxw61atVKNtt/Pzynnnqqtm/fLunIr2eO/QRNSEhQkyZN/M9L0osvvqghQ4YoJSWlzs4hmgW7f0d98sknaty4sdq3bx/6k4hygfTwZHbs2KFTTz21wmsPHz6svLy8oNeN/wpmDyXpyy+/1MiRIzVy5EitWbNGQ4cODUXZ+FUw+/fTTz8pOTlZEyZM0DXXXKMHH3xQO3fuDFXpgB/BVpLP59PMmTPVpk0bnX322SopKZHL5aqwj8vlUklJiaQjn/y/9fz333+v7du3a8CAAXVzAlEu2P071sqVKxmtrQOB9vBkju/x0X9X9/UIXLB7KEnnnHOOFi1apOeff15DhgxRkyZNgl02fhXs/h04cEArV67UDTfcoAULFqh9+/aaNm2avF5vKMoH/KI+2Jqmqblz5yo3N1f33XefDMNQfHy8ioqKKuxXVFSk+Ph4SUd+fVNcXFzh+eLiYsXHx8vj8WjevHm69dZbK/yki9AIdv+OtW3bNmVnZ+vCCy8M7UlEuZr08GTi4uIqvP5ov6v7egQmFD08VqNGjdSlSxdNnz49WCXjGKHon9Pp1Lnnnqt27dopNjZWI0aM0P79+7V79+5QnALgF9XJyzRNzZs3T9u2bdPDDz/s/4TNysrS9u3b5fP5/Ptu27ZNLVu2lCS1bNlSW7du9T9XUlKiPXv2qGXLljp48KB27dqlRx55RKNHj9a9994rSRozZozWr19fh2dnfaHo37FWrlypLl26KC0trQ7OJjrVtIcnk5WVpW3btvkfb926VQ0aNFBqampwTwAh6+HxvF6v9uzZE5Sa8V+h6l+rVq1kGEZIagZ+S1QH2/nz52vjxo2aMmVKhSVkOnXqJIfDoWXLlqm8vFyrVq3S9u3bdcEFF0iS+vTpo6+++kpff/213G63XnvtNbVq1UpZWVlKT0/Xiy++qFmzZmnWrFl66KGHJEkzZszQmWeeGZbztKpQ9O+o8vJyffzxx0xDCLGa9lCS3G633G63pCP9crvdMn+9kWK/fv20fPly7dmzRwUFBVq0aJH69etXtycXJULVw3//+9/Kzc2VJO3Zs0evvPJKhSX7EByh6t/FF1+stWvXatOmTfJ6vVqyZIkaN26sZs2a1e0JIupE7S119+3bpzFjxig2NlZ2u92/fdiwYRo+fLiys7M1Z84cZWdnq3Hjxho7dmyFL6qrVq3SSy+9pLy8PJ1++um6++67q1zHdu/evbr55ptZxzbIQt2/L774QnPnztWCBQsUExO1yz2HVG17OGTIkErH/Pvf/66MjAyZpqlXX31V7777rrxer7p3767bbruNdWyDLJQ9nDt3rtauXavi4mIlJSXpd7/7nUaPHq3ExMQ6ObdoEMr+SdL777+vRYsWqbi4WKeddppuvfXWSmvdAsEWtcEWAAAA1hLVUxEAAABgHQRbAAAAWALBFgAAAJZAsAUAAIAlEGwBAABgCQRbAAAAWALBFgAAAJZAsAUAAIAlEGwBAABgCQRbAEF34YUXqn379v77yB/rqquuUosWLVRYWBiGygAAVkawBRB08+bN07Zt2/TEE09U2P7ee+/p9ddf1+zZs5WYmBim6gAAVmWYpmmGuwgA1jNlyhQ9/vjj+uGHH3TqqaeqtLRUHTt2VMeOHfXmm2+G7H1LSkoUHx8fsuMDACIXI7YAQmLixIlq2bKl7rjjDknSo48+qr1792rOnDnatWuXrr32WqWnpys+Pl69evXS+vXrK7z+//7v/9SjRw+lpaUpNTVVffr00bp16yrs8/DDDysxMVHr1q3T+eefr7i4OD3zzDN1do4AgMgSE+4CAFiTw+HQ/Pnz1adPHz3yyCN64okn9Pjjj8vlcunss89WYmKiZs+erQYNGmj27Nnq27evNm3apMaNG0uSsrOzNXr0aLVu3Vput1sLFy5Ur1699O2336pt27b+93G73Ro1apTGjRunRx99VA0bNgzXKQMAwoypCABC6sYbb9SLL76oLl26aN26dfrLX/6iWbNm6eeff/aH2LKyMrVt21YjRoyoNC9Xknw+n3w+nzp27KgrrrhCjz76qKQjI7ZTpkzRokWLNGLEiDo9LwBA5GEqAoCQeuCBByRJ9957r+x2u95//31deOGFSktLk8fjkcfjkd1uV+/evfXll1/6X7dhwwZdfvnlysjIkN1uV2xsrDZu3Kiff/650nsMGjSozs4HABC5mIoAIKQcDkeFvw8cOKA1a9YoNja20r6tW7eWJBUUFKh///5q1KiRnnrqKbVs2VJxcXEaM2aMSktLK7wmISGBFRYAAJIItgDqWFpami699FJNnTq10nNOp1OStHr1au3atUtvvfWWOnfu7H/+8OHDat68eYXXGIYR2oIBAPUGwRZAnbrooov0yiuvqH379nK5XFXuU1JSIum/o7yS9MUXXyg7O1tnnHFGndQJAKh/CLYA6tT48eP16quvqnfv3rr77ruVlZWl/fv3a+3atWratKnGjRun8847T4mJibrjjjv0wAMPaPfu3XrooYfUrFmzcJcPAIhgXDwGoE41bNhQa9as0VlnnaUJEyaof//+GjdunLKzs3XuuedKkjIyMrRkyRLt27dPQ4cO1cyZMzV//nyddtppYa4eABDJWO4LAAAAlsCILQAAACyBYAsAAABLINgCAADAEgi2AAAAsASCLQAAACyBYAsAAABLINgCAADAEgi2AAAAsASCLQAAACyBYAsAAABLINgCAADAEv4/nsT5D371MdsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (318157629)>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(\n",
    "    ggplot(df)\n",
    "    + aes(x='Year')\n",
    "    + aes(y='Trees sold (millions)')\n",
    "    + geom_point()\n",
    "    + aes(color='Type of tree')\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "be62a1ab",
   "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": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}