project_definition.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Propuesta de trabajo\n",
    "\n",
    "Presentación grupal, puede ser utilizando diapositivas o jupyter lab.\n",
    "\n",
    "1. Presentación de los datos, definición de variables y contexto de la problemática. (10 puntos)\n",
    "2. ¿Cuál es la pregunta que desean resolver? (5 puntos)\n",
    "3. Análisis estadístico de los datos. (15 puntos)\n",
    "4. Visualización de variables. (15 puntos)\n",
    "5. ¿Hay que realizar preprocesamiento? (15 puntos)\n",
    "6. ¿Hay que realizar inputación de datos faltantes? (15 puntos)\n",
    "7. ¿Hay que realizar balanceo de datos? (15 puntos)\n",
    "8. Propuesta de cuatro modelos y sus hiperparámetros asociados. (20 puntos)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Proyecto Final: Entrega 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[MUSHROOM](https://archive.ics.uci.edu/ml/datasets/Mushroom)\n",
    "\n",
    "En nuestro proyecto trabajaremos con una data de hongos en las familias [lepiota](https://en.wikipedia.org/wiki/Lepiota) y [agaricus](https://en.wikipedia.org/wiki/Agaricus), que incluye descripción, como veremos, de 22 variables que hablan de su estructura física.\n",
    "\n",
    "![abalone](../images/Lepiota_clypeolaria.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import altair as alt\n",
    "\n",
    "from pathlib import Path\n",
    "\n",
    "alt.themes.enable('opaque')  # Para quienes utilizan temas oscuros en Jupyter Lab\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 243,
   "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>class</th>\n",
       "      <th>cap-shape</th>\n",
       "      <th>cap-surface</th>\n",
       "      <th>cap-color</th>\n",
       "      <th>bruises</th>\n",
       "      <th>odor</th>\n",
       "      <th>gill-attachment</th>\n",
       "      <th>gill-spacing</th>\n",
       "      <th>gill-size</th>\n",
       "      <th>gill-color</th>\n",
       "      <th>...</th>\n",
       "      <th>stalk-surface-below-ring</th>\n",
       "      <th>stalk-color-above-ring</th>\n",
       "      <th>stalk-color-below-ring</th>\n",
       "      <th>veil-type</th>\n",
       "      <th>veil-color</th>\n",
       "      <th>ring-number</th>\n",
       "      <th>ring-type</th>\n",
       "      <th>spore-print-color</th>\n",
       "      <th>population</th>\n",
       "      <th>habitat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>p</td>\n",
       "      <td>x</td>\n",
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       "      <td>k</td>\n",
       "      <td>...</td>\n",
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       "      <td>w</td>\n",
       "      <td>w</td>\n",
       "      <td>p</td>\n",
       "      <td>w</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>k</td>\n",
       "      <td>s</td>\n",
       "      <td>u</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>e</td>\n",
       "      <td>x</td>\n",
       "      <td>s</td>\n",
       "      <td>y</td>\n",
       "      <td>t</td>\n",
       "      <td>a</td>\n",
       "      <td>f</td>\n",
       "      <td>c</td>\n",
       "      <td>b</td>\n",
       "      <td>k</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>w</td>\n",
       "      <td>w</td>\n",
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       "      <td>w</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>n</td>\n",
       "      <td>n</td>\n",
       "      <td>g</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>e</td>\n",
       "      <td>b</td>\n",
       "      <td>s</td>\n",
       "      <td>w</td>\n",
       "      <td>t</td>\n",
       "      <td>l</td>\n",
       "      <td>f</td>\n",
       "      <td>c</td>\n",
       "      <td>b</td>\n",
       "      <td>n</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>w</td>\n",
       "      <td>w</td>\n",
       "      <td>p</td>\n",
       "      <td>w</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>n</td>\n",
       "      <td>n</td>\n",
       "      <td>m</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>p</td>\n",
       "      <td>x</td>\n",
       "      <td>y</td>\n",
       "      <td>w</td>\n",
       "      <td>t</td>\n",
       "      <td>p</td>\n",
       "      <td>f</td>\n",
       "      <td>c</td>\n",
       "      <td>n</td>\n",
       "      <td>n</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>w</td>\n",
       "      <td>w</td>\n",
       "      <td>p</td>\n",
       "      <td>w</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>k</td>\n",
       "      <td>s</td>\n",
       "      <td>u</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>e</td>\n",
       "      <td>x</td>\n",
       "      <td>s</td>\n",
       "      <td>g</td>\n",
       "      <td>f</td>\n",
       "      <td>n</td>\n",
       "      <td>f</td>\n",
       "      <td>w</td>\n",
       "      <td>b</td>\n",
       "      <td>k</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>w</td>\n",
       "      <td>w</td>\n",
       "      <td>p</td>\n",
       "      <td>w</td>\n",
       "      <td>o</td>\n",
       "      <td>e</td>\n",
       "      <td>n</td>\n",
       "      <td>a</td>\n",
       "      <td>g</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  class cap-shape cap-surface cap-color bruises odor gill-attachment  \\\n",
       "0     p         x           s         n       t    p               f   \n",
       "1     e         x           s         y       t    a               f   \n",
       "2     e         b           s         w       t    l               f   \n",
       "3     p         x           y         w       t    p               f   \n",
       "4     e         x           s         g       f    n               f   \n",
       "\n",
       "  gill-spacing gill-size gill-color  ... stalk-surface-below-ring  \\\n",
       "0            c         n          k  ...                        s   \n",
       "1            c         b          k  ...                        s   \n",
       "2            c         b          n  ...                        s   \n",
       "3            c         n          n  ...                        s   \n",
       "4            w         b          k  ...                        s   \n",
       "\n",
       "  stalk-color-above-ring stalk-color-below-ring veil-type veil-color  \\\n",
       "0                      w                      w         p          w   \n",
       "1                      w                      w         p          w   \n",
       "2                      w                      w         p          w   \n",
       "3                      w                      w         p          w   \n",
       "4                      w                      w         p          w   \n",
       "\n",
       "  ring-number ring-type spore-print-color population habitat  \n",
       "0           o         p                 k          s       u  \n",
       "1           o         p                 n          n       g  \n",
       "2           o         p                 n          n       m  \n",
       "3           o         p                 k          s       u  \n",
       "4           o         e                 n          a       g  \n",
       "\n",
       "[5 rows x 23 columns]"
      ]
     },
     "execution_count": 243,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "datapath = Path().resolve().parent / \"data-mushroom\"\n",
    "\n",
    "mushroom = pd.read_csv(\n",
    "    datapath / \"agaricus-lepiota.data\",\n",
    "    header=None,\n",
    "    names=[\"class\", \"cap-shape\", \"cap-surface\", \"cap-color\", \"bruises\", \"odor\", \"gill-attachment\", \"gill-spacing\", \n",
    "           \"gill-size\", \"gill-color\", \"stalk-shape\", \"stalk-root\", \"stalk-surface-above-ring\", \"stalk-surface-below-ring\",\n",
    "           \"stalk-color-above-ring\", \"stalk-color-below-ring\", \"veil-type\", \"veil-color\", \"ring-number\", \"ring-type\",\n",
    "           \"spore-print-color\",  \"population\" , \"habitat\"]\n",
    ")\n",
    "\n",
    "mushroom.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {},
   "outputs": [
    {
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       "\u001b[1;36m1.\u001b[0m \u001b[0mTitle\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mMushroom\u001b[0m \u001b[0mDatabase\u001b[0m\u001b[1;33m\n",
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       "\u001b[0m    \u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m)\u001b[0m \u001b[0mMushroom\u001b[0m \u001b[0mrecords\u001b[0m \u001b[0mdrawn\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mThe\u001b[0m \u001b[0mAudubon\u001b[0m \u001b[0mSociety\u001b[0m \u001b[0mField\u001b[0m \u001b[0mGuide\u001b[0m \u001b[0mto\u001b[0m \u001b[0mNorth\u001b[0m\u001b[1;33m\n",
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       "\u001b[0m        \u001b[0mcomparison\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mother\u001b[0m \u001b[0mresearchers\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mDuch\u001b[0m \u001b[0mW\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mAdamczak\u001b[0m \u001b[0mR\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mGrabczewski\u001b[0m \u001b[0mK\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;36m1996\u001b[0m\u001b[1;33m)\u001b[0m \u001b[0mExtraction\u001b[0m \u001b[0mof\u001b[0m \u001b[0mlogical\u001b[0m \u001b[0mrules\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[1;32mfrom\u001b[0m \u001b[0mtraining\u001b[0m \u001b[0mdata\u001b[0m \u001b[0musing\u001b[0m \u001b[0mbackpropagation\u001b[0m \u001b[0mnetworks\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;32min\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mProc\u001b[0m\u001b[1;33m.\u001b[0m \u001b[0mof\u001b[0m \u001b[0mthe\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mThe\u001b[0m \u001b[1;36m1\u001b[0m\u001b[0mst\u001b[0m \u001b[0mOnline\u001b[0m \u001b[0mWorkshop\u001b[0m \u001b[0mon\u001b[0m \u001b[0mSoft\u001b[0m \u001b[0mComputing\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m19\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m30.\u001b[0m\u001b[0mAug\u001b[0m\u001b[1;36m.1996\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mpp\u001b[0m\u001b[1;33m.\u001b[0m \u001b[1;36m25\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m30\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mavailable\u001b[0m \u001b[0mon\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mline\u001b[0m \u001b[0mat\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mhttp\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m//\u001b[0m\u001b[0mwww\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mbioele\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnuee\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnagoya\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mu\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mac\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mjp\u001b[0m\u001b[1;33m/\u001b[0m\u001b[0mwsc1\u001b[0m\u001b[1;33m/\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mDuch\u001b[0m \u001b[0mW\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mAdamczak\u001b[0m \u001b[0mR\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mGrabczewski\u001b[0m \u001b[0mK\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mIshikawa\u001b[0m \u001b[0mM\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mUeda\u001b[0m \u001b[0mH\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mExtraction\u001b[0m \u001b[0mof\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mcrisp\u001b[0m \u001b[0mlogical\u001b[0m \u001b[0mrules\u001b[0m \u001b[0musing\u001b[0m \u001b[0mconstrained\u001b[0m \u001b[0mbackpropagation\u001b[0m \u001b[0mnetworks\u001b[0m \u001b[1;33m-\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mcomparison\u001b[0m \u001b[0mof\u001b[0m \u001b[0mtwo\u001b[0m \u001b[0mnew\u001b[0m \u001b[0mapproaches\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;32min\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mProc\u001b[0m\u001b[1;33m.\u001b[0m \u001b[0mof\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mEuropean\u001b[0m \u001b[0mSymposium\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mon\u001b[0m \u001b[0mArtificial\u001b[0m \u001b[0mNeural\u001b[0m \u001b[0mNetworks\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mESANN\u001b[0m\u001b[0;31m'\u001b[0m\u001b[1;36m97\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mBruge\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mBelgium\u001b[0m \u001b[1;36m16\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m18.4\u001b[0m\u001b[1;36m.1997\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mpp\u001b[0m\u001b[1;33m.\u001b[0m \u001b[0mxx\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mxx\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mWlodzislaw\u001b[0m \u001b[0mDuch\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mDepartment\u001b[0m \u001b[0mof\u001b[0m \u001b[0mComputer\u001b[0m \u001b[0mMethods\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mNicholas\u001b[0m \u001b[0mCopernicus\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mUniversity\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m87\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m100\u001b[0m \u001b[0mTorun\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mGrudziadzka\u001b[0m \u001b[1;36m5\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mPoland\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0me\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mmail\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mduch\u001b[0m\u001b[1;33m@\u001b[0m\u001b[0mphys\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0muni\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtorun\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpl\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mWWW\u001b[0m     \u001b[0mhttp\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m//\u001b[0m\u001b[0mwww\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mphys\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0muni\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtorun\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpl\u001b[0m\u001b[1;33m/\u001b[0m\u001b[0mkmk\u001b[0m\u001b[1;33m/\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[1;33m\n",
       "\u001b[0m        \u001b[0mDate\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mMon\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m17\u001b[0m \u001b[0mFeb\u001b[0m \u001b[1;36m1997\u001b[0m \u001b[1;36m13\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;36m47\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;36m40\u001b[0m \u001b[1;33m+\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;36m100\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mFrom\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mWlodzislaw\u001b[0m \u001b[0mDuch\u001b[0m \u001b[1;33m<\u001b[0m\u001b[0mduch\u001b[0m\u001b[1;33m@\u001b[0m\u001b[0mphys\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0muni\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtorun\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpl\u001b[0m\u001b[1;33m>\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mOrganization\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mDept\u001b[0m\u001b[1;33m.\u001b[0m \u001b[0mof\u001b[0m \u001b[0mComputer\u001b[0m \u001b[0mMethods\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mUMK\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mI\u001b[0m \u001b[0mhave\u001b[0m \u001b[0mattached\u001b[0m \u001b[0ma\u001b[0m \u001b[0mfile\u001b[0m \u001b[0mcontaining\u001b[0m \u001b[0mlogical\u001b[0m \u001b[0mrules\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mmushrooms\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mIt\u001b[0m \u001b[0mshould\u001b[0m \u001b[0mbe\u001b[0m \u001b[0mhelpful\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mother\u001b[0m \u001b[0mpeople\u001b[0m \u001b[0msince\u001b[0m \u001b[0monly\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mlast\u001b[0m \u001b[0myear\u001b[0m \u001b[0mI\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mhave\u001b[0m \u001b[0mseen\u001b[0m \u001b[0mabout\u001b[0m \u001b[1;36m10\u001b[0m \u001b[0mpapers\u001b[0m \u001b[0manalyzing\u001b[0m \u001b[0mthis\u001b[0m \u001b[0mdataset\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mobtaining\u001b[0m \u001b[0mquite\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mcomplex\u001b[0m \u001b[0mrules\u001b[0m\u001b[1;33m.\u001b[0m \u001b[0mWe\u001b[0m \u001b[0mwill\u001b[0m \u001b[1;32mtry\u001b[0m \u001b[0mto\u001b[0m \u001b[0mcontribute\u001b[0m \u001b[0mother\u001b[0m \u001b[0mresults\u001b[0m \u001b[0mlater\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mWith\u001b[0m \u001b[0mbest\u001b[0m \u001b[0mregards\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mWlodek\u001b[0m \u001b[0mDuch\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0m________________________________________________________________\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mLogical\u001b[0m \u001b[0mrules\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mmushroom\u001b[0m \u001b[0mdata\u001b[0m \u001b[0msets\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mLogical\u001b[0m \u001b[0mrules\u001b[0m \u001b[0mgiven\u001b[0m \u001b[0mbelow\u001b[0m \u001b[0mseem\u001b[0m \u001b[0mto\u001b[0m \u001b[0mbe\u001b[0m \u001b[0mthe\u001b[0m \u001b[0msimplest\u001b[0m \u001b[0mpossible\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mthe\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mmushroom\u001b[0m \u001b[0mdataset\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mtherefore\u001b[0m \u001b[0mshould\u001b[0m \u001b[0mbe\u001b[0m \u001b[0mtreated\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mbenchmark\u001b[0m \u001b[0mresults\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mDisjunctive\u001b[0m \u001b[0mrules\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mpoisonous\u001b[0m \u001b[0mmushrooms\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mmost\u001b[0m \u001b[0mgeneral\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mto\u001b[0m \u001b[0mmost\u001b[0m \u001b[0mspecific\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mP_1\u001b[0m\u001b[1;33m)\u001b[0m \u001b[0modor\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mNOT\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0malmond\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mOR\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0manise\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mOR\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\n",
       "\u001b[0m             \u001b[1;36m120\u001b[0m \u001b[0mpoisonous\u001b[0m \u001b[0mcases\u001b[0m \u001b[0mmissed\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m98.52\u001b[0m\u001b[1;33m%\u001b[0m \u001b[0maccuracy\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mP_2\u001b[0m\u001b[1;33m)\u001b[0m \u001b[0mspore\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mprint\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mcolor\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mgreen\u001b[0m\u001b[1;33m\n",
       "\u001b[0m             \u001b[1;36m48\u001b[0m \u001b[0mcases\u001b[0m \u001b[0mmissed\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m99.41\u001b[0m\u001b[1;33m%\u001b[0m \u001b[0maccuracy\u001b[0m\u001b[1;33m\n",
       "\u001b[0m         \u001b[1;33m\n",
       "\u001b[0m        \u001b[0mP_3\u001b[0m\u001b[1;33m)\u001b[0m \u001b[0modor\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mnone\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mAND\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstalk\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0msurface\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mbelow\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mring\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mscaly\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mAND\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\n",
       "\u001b[0m                  \u001b[1;33m(\u001b[0m\u001b[0mstalk\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mcolor\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mabove\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mring\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mNOT\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mbrown\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m\n",
       "\u001b[0m             \u001b[1;36m8\u001b[0m \u001b[0mcases\u001b[0m \u001b[0mmissed\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m99.90\u001b[0m\u001b[1;33m%\u001b[0m \u001b[0maccuracy\u001b[0m\u001b[1;33m\n",
       "\u001b[0m         \u001b[1;33m\n",
       "\u001b[0m        \u001b[0mP_4\u001b[0m\u001b[1;33m)\u001b[0m \u001b[0mhabitat\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mleaves\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mAND\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcap\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mcolor\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mwhite\u001b[0m\u001b[1;33m\n",
       "\u001b[0m                 \u001b[1;36m100\u001b[0m\u001b[1;33m%\u001b[0m \u001b[0maccuracy\u001b[0m     \u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mRule\u001b[0m \u001b[0mP_4\u001b[0m\u001b[1;33m)\u001b[0m \u001b[0mmay\u001b[0m \u001b[0malso\u001b[0m \u001b[0mbe\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mP_4\u001b[0m\u001b[0;31m'\u001b[0m\u001b[1;33m)\u001b[0m \u001b[0mpopulation\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mclustered\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mAND\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcap_color\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mwhite\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mThese\u001b[0m \u001b[0mrule\u001b[0m \u001b[0minvolve\u001b[0m \u001b[1;36m6\u001b[0m \u001b[0mattributes\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mout\u001b[0m \u001b[0mof\u001b[0m \u001b[1;36m22\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m \u001b[0mRules\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0medible\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mmushrooms\u001b[0m \u001b[0mare\u001b[0m \u001b[0mobtained\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mnegation\u001b[0m \u001b[0mof\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mrules\u001b[0m \u001b[0mgiven\u001b[0m \u001b[0mabove\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;32mfor\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mexample\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mrule\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0modor\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0malmond\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mOR\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0manise\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mOR\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mAND\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mspore\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mprint\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mcolor\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mNOT\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mgreen\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mgives\u001b[0m \u001b[1;36m48\u001b[0m \u001b[0merrors\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;32mor\u001b[0m \u001b[1;36m99.41\u001b[0m\u001b[1;33m%\u001b[0m \u001b[0maccuracy\u001b[0m \u001b[0mon\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mwhole\u001b[0m \u001b[0mdataset\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mSeveral\u001b[0m \u001b[0mslightly\u001b[0m \u001b[0mmore\u001b[0m \u001b[0mcomplex\u001b[0m \u001b[0mvariations\u001b[0m \u001b[0mon\u001b[0m \u001b[0mthese\u001b[0m \u001b[0mrules\u001b[0m \u001b[0mexist\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0minvolving\u001b[0m \u001b[0mother\u001b[0m \u001b[0mattributes\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msuch\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mgill_size\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mgill_spacing\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mstalk_surface_above_ring\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mbut\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mrules\u001b[0m \u001b[0mgiven\u001b[0m \u001b[0mabove\u001b[0m \u001b[0mare\u001b[0m \u001b[0mthe\u001b[0m \u001b[0msimplest\u001b[0m\u001b[1;33m\n",
       "\u001b[0m        \u001b[0mwe\u001b[0m \u001b[0mhave\u001b[0m \u001b[0mfound\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;36m4.\u001b[0m \u001b[0mRelevant\u001b[0m \u001b[0mInformation\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mThis\u001b[0m \u001b[0mdata\u001b[0m \u001b[0mset\u001b[0m \u001b[0mincludes\u001b[0m \u001b[0mdescriptions\u001b[0m \u001b[0mof\u001b[0m \u001b[0mhypothetical\u001b[0m \u001b[0msamples\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mcorresponding\u001b[0m \u001b[0mto\u001b[0m \u001b[1;36m23\u001b[0m \u001b[0mspecies\u001b[0m \u001b[0mof\u001b[0m \u001b[0mgilled\u001b[0m \u001b[0mmushrooms\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mAgaricus\u001b[0m \u001b[1;32mand\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mLepiota\u001b[0m \u001b[0mFamily\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mpp\u001b[0m\u001b[1;33m.\u001b[0m \u001b[1;36m500\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m525\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m  \u001b[0mEach\u001b[0m \u001b[0mspecies\u001b[0m \u001b[1;32mis\u001b[0m \u001b[0midentified\u001b[0m \u001b[1;32mas\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mdefinitely\u001b[0m \u001b[0medible\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdefinitely\u001b[0m \u001b[0mpoisonous\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0mof\u001b[0m \u001b[0munknown\u001b[0m \u001b[0medibility\u001b[0m \u001b[1;32mand\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[1;32mnot\u001b[0m \u001b[0mrecommended\u001b[0m\u001b[1;33m.\u001b[0m  \u001b[0mThis\u001b[0m \u001b[0mlatter\u001b[0m \u001b[1;32mclass\u001b[0m \u001b[0mwas\u001b[0m \u001b[0mcombined\u001b[0m \u001b[1;32mwith\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mpoisonous\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mone\u001b[0m\u001b[1;33m.\u001b[0m  \u001b[0mThe\u001b[0m \u001b[0mGuide\u001b[0m \u001b[0mclearly\u001b[0m \u001b[0mstates\u001b[0m \u001b[0mthat\u001b[0m \u001b[0mthere\u001b[0m \u001b[1;32mis\u001b[0m \u001b[0mno\u001b[0m \u001b[0msimple\u001b[0m \u001b[0mrule\u001b[0m \u001b[1;32mfor\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mdetermining\u001b[0m \u001b[0mthe\u001b[0m \u001b[0medibility\u001b[0m \u001b[0mof\u001b[0m \u001b[0ma\u001b[0m \u001b[0mmushroom\u001b[0m\u001b[1;33m;\u001b[0m \u001b[0mno\u001b[0m \u001b[0mrule\u001b[0m \u001b[0mlike\u001b[0m\u001b[0;31m \u001b[0m\u001b[0;31m`\u001b[0m\u001b[0;31m`\u001b[0m\u001b[0mleaflets\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mthree\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlet\u001b[0m \u001b[0mit\u001b[0m \u001b[0mbe\u001b[0m\u001b[1;34m''\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mPoisonous\u001b[0m \u001b[0mOak\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mIvy\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;36m5.\u001b[0m \u001b[0mNumber\u001b[0m \u001b[0mof\u001b[0m \u001b[0mInstances\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;36m8124\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;36m6.\u001b[0m \u001b[0mNumber\u001b[0m \u001b[0mof\u001b[0m \u001b[0mAttributes\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;36m22\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mall\u001b[0m \u001b[0mnominally\u001b[0m \u001b[0mvalued\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;36m7.\u001b[0m \u001b[0mAttribute\u001b[0m \u001b[0mInformation\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mclasses\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0medible\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0me\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mpoisonous\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mp\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\n",
       "\u001b[0m     \u001b[1;36m1.\u001b[0m \u001b[0mcap\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mshape\u001b[0m\u001b[1;33m:\u001b[0m                \u001b[0mbell\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mb\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mconical\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mc\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mconvex\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mflat\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m                                  \u001b[0mknobbed\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0msunken\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0ms\u001b[0m\u001b[1;33m\n",
       "\u001b[0m     \u001b[1;36m2.\u001b[0m \u001b[0mcap\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0msurface\u001b[0m\u001b[1;33m:\u001b[0m              \u001b[0mfibrous\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mgrooves\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mg\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mscaly\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0msmooth\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0ms\u001b[0m\u001b[1;33m\n",
       "\u001b[0m     \u001b[1;36m3.\u001b[0m \u001b[0mcap\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mcolor\u001b[0m\u001b[1;33m:\u001b[0m                \u001b[0mbrown\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mbuff\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mb\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mcinnamon\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mc\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mgray\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mg\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mgreen\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mr\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m                                  \u001b[0mpink\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mp\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mpurple\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mu\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mred\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0me\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mwhite\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mw\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0myellow\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m\n",
       "\u001b[0m     \u001b[1;36m4.\u001b[0m \u001b[0mbruises\u001b[0m\u001b[0;31m?\u001b[0m\u001b[1;33m:\u001b[0m                 \u001b[0mbruises\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mt\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mno\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m\n",
       "\u001b[0m     \u001b[1;36m5.\u001b[0m \u001b[0modor\u001b[0m\u001b[1;33m:\u001b[0m                     \u001b[0malmond\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0manise\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0ml\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mcreosote\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mc\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mfishy\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mfoul\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m                                  \u001b[0mmusty\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mm\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mnone\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mpungent\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mp\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mspicy\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0ms\u001b[0m\u001b[1;33m\n",
       "\u001b[0m     \u001b[1;36m6.\u001b[0m \u001b[0mgill\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mattachment\u001b[0m\u001b[1;33m:\u001b[0m          \u001b[0mattached\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mdescending\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0md\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mfree\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mnotched\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m\n",
       "\u001b[0m     \u001b[1;36m7.\u001b[0m \u001b[0mgill\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mspacing\u001b[0m\u001b[1;33m:\u001b[0m             \u001b[0mclose\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mc\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mcrowded\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mw\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mdistant\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0md\u001b[0m\u001b[1;33m\n",
       "\u001b[0m     \u001b[1;36m8.\u001b[0m \u001b[0mgill\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0msize\u001b[0m\u001b[1;33m:\u001b[0m                \u001b[0mbroad\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mb\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mnarrow\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m\n",
       "\u001b[0m     \u001b[1;36m9.\u001b[0m \u001b[0mgill\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mcolor\u001b[0m\u001b[1;33m:\u001b[0m               \u001b[0mblack\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mbrown\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mbuff\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mb\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mchocolate\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mh\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mgray\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mg\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m                                  \u001b[0mgreen\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mr\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0morange\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mo\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mpink\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mp\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mpurple\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mu\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mred\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0me\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m                                  \u001b[0mwhite\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mw\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0myellow\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[1;36m10.\u001b[0m \u001b[0mstalk\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mshape\u001b[0m\u001b[1;33m:\u001b[0m              \u001b[0menlarging\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0me\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mtapering\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mt\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[1;36m11.\u001b[0m \u001b[0mstalk\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mroot\u001b[0m\u001b[1;33m:\u001b[0m               \u001b[0mbulbous\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mb\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mclub\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mc\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mcup\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mu\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mequal\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0me\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m                                  \u001b[0mrhizomorphs\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mz\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mrooted\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mr\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mmissing\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0;31m?\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[1;36m12.\u001b[0m \u001b[0mstalk\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0msurface\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mabove\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mring\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mfibrous\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mscaly\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0msilky\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0msmooth\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0ms\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[1;36m13.\u001b[0m \u001b[0mstalk\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0msurface\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mbelow\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mring\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mfibrous\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mscaly\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0msilky\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0msmooth\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0ms\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[1;36m14.\u001b[0m \u001b[0mstalk\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mcolor\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mabove\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mring\u001b[0m\u001b[1;33m:\u001b[0m   \u001b[0mbrown\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mbuff\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mb\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mcinnamon\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mc\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mgray\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mg\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0morange\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mo\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m                                  \u001b[0mpink\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mp\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mred\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0me\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mwhite\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mw\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0myellow\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[1;36m15.\u001b[0m \u001b[0mstalk\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mcolor\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mbelow\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mring\u001b[0m\u001b[1;33m:\u001b[0m   \u001b[0mbrown\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mbuff\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mb\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mcinnamon\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mc\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mgray\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mg\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0morange\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mo\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m                                  \u001b[0mpink\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mp\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mred\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0me\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mwhite\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mw\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0myellow\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[1;36m16.\u001b[0m \u001b[0mveil\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mtype\u001b[0m\u001b[1;33m:\u001b[0m                \u001b[0mpartial\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mp\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0muniversal\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mu\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[1;36m17.\u001b[0m \u001b[0mveil\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mcolor\u001b[0m\u001b[1;33m:\u001b[0m               \u001b[0mbrown\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0morange\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mo\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mwhite\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mw\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0myellow\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[1;36m18.\u001b[0m \u001b[0mring\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mnumber\u001b[0m\u001b[1;33m:\u001b[0m              \u001b[0mnone\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mone\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mo\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mtwo\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mt\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[1;36m19.\u001b[0m \u001b[0mring\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mtype\u001b[0m\u001b[1;33m:\u001b[0m                \u001b[0mcobwebby\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mc\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mevanescent\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0me\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mflaring\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mlarge\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0ml\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m                                  \u001b[0mnone\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mpendant\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mp\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0msheathing\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0ms\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mzone\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mz\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[1;36m20.\u001b[0m \u001b[0mspore\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mprint\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mcolor\u001b[0m\u001b[1;33m:\u001b[0m        \u001b[0mblack\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mbrown\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mbuff\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mb\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mchocolate\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mh\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mgreen\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mr\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m                                  \u001b[0morange\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mo\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mpurple\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mu\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mwhite\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mw\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0myellow\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[1;36m21.\u001b[0m \u001b[0mpopulation\u001b[0m\u001b[1;33m:\u001b[0m               \u001b[0mabundant\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mclustered\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mc\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mnumerous\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m                                  \u001b[0mscattered\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0ms\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mseveral\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mv\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0msolitary\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[1;36m22.\u001b[0m \u001b[0mhabitat\u001b[0m\u001b[1;33m:\u001b[0m                  \u001b[0mgrasses\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mg\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mleaves\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0ml\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mmeadows\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mm\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mpaths\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mp\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m                                  \u001b[0murban\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mu\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mwaste\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mw\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mwoods\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0md\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;36m8.\u001b[0m \u001b[0mMissing\u001b[0m \u001b[0mAttribute\u001b[0m \u001b[0mValues\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;36m2480\u001b[0m \u001b[0mof\u001b[0m \u001b[0mthem\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mdenoted\u001b[0m \u001b[0mby\u001b[0m \u001b[1;34m\"?\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mall\u001b[0m \u001b[0mfor2\u001b[0m\u001b[1;33m\n",
       "\u001b[0m   \u001b[0mattribute\u001b[0m \u001b[1;31m#11.\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;36m9.\u001b[0m \u001b[0mClass\u001b[0m \u001b[0mDistribution\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;33m\n",
       "\u001b[0m    \u001b[1;33m-\u001b[0m\u001b[1;33m-\u001b[0m    \u001b[0medible\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;36m4208\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;36m51.8\u001b[0m\u001b[1;33m%\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[1;33m-\u001b[0m\u001b[1;33m-\u001b[0m \u001b[0mpoisonous\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;36m3916\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;36m48.2\u001b[0m\u001b[1;33m%\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[1;33m-\u001b[0m\u001b[1;33m-\u001b[0m     \u001b[0mtotal\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;36m8124\u001b[0m \u001b[0minstances\u001b[0m\u001b[0;31m\n",
       "\n",
       "*** ERROR: EOF in multi-line statement\u001b[0m\n",
       "\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%pycat ../data-mushroom/agaricus-lepiota.names"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "De la descripción dada se nos presenta el problema de cómo determinar si un especimen es venenoso o comestible, de ahí que nos preguntamos, \n",
    "\n",
    "¿cómo, a traves de las variables dadas, podemos determinar si una especia lo es o no?  y en el caso de ser muy complejo y no determinante, ¿podemos hacer alguna afirmación como acercamiento al menos?\n",
    "\n",
    "Por otro lado, investigando un poco los datos nos damos cuenta de que estan todos conformados de forma categórica en todas sus variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "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>count</th>\n",
       "      <th>unique</th>\n",
       "      <th>top</th>\n",
       "      <th>freq</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>class</th>\n",
       "      <td>8124</td>\n",
       "      <td>2</td>\n",
       "      <td>e</td>\n",
       "      <td>4208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cap-shape</th>\n",
       "      <td>8124</td>\n",
       "      <td>6</td>\n",
       "      <td>x</td>\n",
       "      <td>3656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cap-surface</th>\n",
       "      <td>8124</td>\n",
       "      <td>4</td>\n",
       "      <td>y</td>\n",
       "      <td>3244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cap-color</th>\n",
       "      <td>8124</td>\n",
       "      <td>10</td>\n",
       "      <td>n</td>\n",
       "      <td>2284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bruises</th>\n",
       "      <td>8124</td>\n",
       "      <td>2</td>\n",
       "      <td>f</td>\n",
       "      <td>4748</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>odor</th>\n",
       "      <td>8124</td>\n",
       "      <td>9</td>\n",
       "      <td>n</td>\n",
       "      <td>3528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gill-attachment</th>\n",
       "      <td>8124</td>\n",
       "      <td>2</td>\n",
       "      <td>f</td>\n",
       "      <td>7914</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gill-spacing</th>\n",
       "      <td>8124</td>\n",
       "      <td>2</td>\n",
       "      <td>c</td>\n",
       "      <td>6812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gill-size</th>\n",
       "      <td>8124</td>\n",
       "      <td>2</td>\n",
       "      <td>b</td>\n",
       "      <td>5612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gill-color</th>\n",
       "      <td>8124</td>\n",
       "      <td>12</td>\n",
       "      <td>b</td>\n",
       "      <td>1728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-shape</th>\n",
       "      <td>8124</td>\n",
       "      <td>2</td>\n",
       "      <td>t</td>\n",
       "      <td>4608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-root</th>\n",
       "      <td>8124</td>\n",
       "      <td>5</td>\n",
       "      <td>b</td>\n",
       "      <td>3776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-surface-above-ring</th>\n",
       "      <td>8124</td>\n",
       "      <td>4</td>\n",
       "      <td>s</td>\n",
       "      <td>5176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-surface-below-ring</th>\n",
       "      <td>8124</td>\n",
       "      <td>4</td>\n",
       "      <td>s</td>\n",
       "      <td>4936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-color-above-ring</th>\n",
       "      <td>8124</td>\n",
       "      <td>9</td>\n",
       "      <td>w</td>\n",
       "      <td>4464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-color-below-ring</th>\n",
       "      <td>8124</td>\n",
       "      <td>9</td>\n",
       "      <td>w</td>\n",
       "      <td>4384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>veil-type</th>\n",
       "      <td>8124</td>\n",
       "      <td>1</td>\n",
       "      <td>p</td>\n",
       "      <td>8124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>veil-color</th>\n",
       "      <td>8124</td>\n",
       "      <td>4</td>\n",
       "      <td>w</td>\n",
       "      <td>7924</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ring-number</th>\n",
       "      <td>8124</td>\n",
       "      <td>3</td>\n",
       "      <td>o</td>\n",
       "      <td>7488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ring-type</th>\n",
       "      <td>8124</td>\n",
       "      <td>5</td>\n",
       "      <td>p</td>\n",
       "      <td>3968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>spore-print-color</th>\n",
       "      <td>8124</td>\n",
       "      <td>9</td>\n",
       "      <td>w</td>\n",
       "      <td>2388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>population</th>\n",
       "      <td>8124</td>\n",
       "      <td>6</td>\n",
       "      <td>v</td>\n",
       "      <td>4040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>habitat</th>\n",
       "      <td>8124</td>\n",
       "      <td>7</td>\n",
       "      <td>d</td>\n",
       "      <td>3148</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         count unique top  freq\n",
       "class                     8124      2   e  4208\n",
       "cap-shape                 8124      6   x  3656\n",
       "cap-surface               8124      4   y  3244\n",
       "cap-color                 8124     10   n  2284\n",
       "bruises                   8124      2   f  4748\n",
       "odor                      8124      9   n  3528\n",
       "gill-attachment           8124      2   f  7914\n",
       "gill-spacing              8124      2   c  6812\n",
       "gill-size                 8124      2   b  5612\n",
       "gill-color                8124     12   b  1728\n",
       "stalk-shape               8124      2   t  4608\n",
       "stalk-root                8124      5   b  3776\n",
       "stalk-surface-above-ring  8124      4   s  5176\n",
       "stalk-surface-below-ring  8124      4   s  4936\n",
       "stalk-color-above-ring    8124      9   w  4464\n",
       "stalk-color-below-ring    8124      9   w  4384\n",
       "veil-type                 8124      1   p  8124\n",
       "veil-color                8124      4   w  7924\n",
       "ring-number               8124      3   o  7488\n",
       "ring-type                 8124      5   p  3968\n",
       "spore-print-color         8124      9   w  2388\n",
       "population                8124      6   v  4040\n",
       "habitat                   8124      7   d  3148"
      ]
     },
     "execution_count": 207,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mushroom.describe().T"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "además tenemos, en concreto, sus respectivos calisificarores asociados a cada letra en las columnas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "| Feature       | Description     |\n",
    "| :------------- | :----------: |\n",
    "| cap-shape | bell=b, conical=c, convex=x,flat=f, knobbed=k, sunken=s|\n",
    "| cap-surface|            fibrous=f,grooves=g,scaly=y,smooth=s|\n",
    "| cap-color|                brown=n,buff=b,cinnamon=c,gray=g,green=r,pink=p,purple=u,red=e,white=w,yellow=y|\n",
    "| bruises?|                 bruises=t,no=f|\n",
    "| odor|                     almond=a,anise=l,creosote=c,fishy=y,foul=f,musty=m,none=n,pungent=p,spicy=s|\n",
    "| gill-attachment|          attached=a,descending=d,free=f,notched=n|\n",
    "| gill-spacing|             close=c,crowded=w,distant=d|\n",
    "| gill-size: |               broad=b,narrow=n|\n",
    "| gill-color|               black=k,brown=n,buff=b,chocolate=h,gray=g,green=r,orange=o,pink=p,purple=u,red=e,white=w,yellow=y|\n",
    "| stalk-shape|              enlarging=e,tapering=t|\n",
    "| stalk-root:|               bulbous=b,club=c,cup=u,equal=e, rhizomorphs=z,rooted=r,missing=?|\n",
    "| stalk-surface-above-ring: |fibrous=f,scaly=y,silky=k,smooth=s|\n",
    "|stalk-surface-below-ring: |fibrous=f,scaly=y,silky=k,smooth=s|\n",
    "| stalk-color-above-ring: |  brown=n,buff=b,cinnamon=c,gray=g,orange=o, pink=p,red=e,white=w,yellow=y|\n",
    "| stalk-color-below-ring:  | brown=n,buff=b,cinnamon=c,gray=g,orange=o,pink=p,red=e,white=w,yellow=y|\n",
    "| veil-type:    |            partial=p,universal=u|\n",
    "| veil-color:   |            brown=n,orange=o,white=w,yellow=y|\n",
    "| ring-number:   |           none=n,one=o,two=t|\n",
    "| ring-type:     |           cobwebby=c,evanescent=e,flaring=f,large=l, none=n,pendant=p,sheathing=s,zone=z|\n",
    "|spore-print-color: |       black=k,brown=n,buff=b,chocolate=h,green=r,orange=o,purple=u,white=w,yellow=y|\n",
    "| population:   |            abundant=a,clustered=c,numerous=n,scattered=s,several=v,solitary=y|\n",
    "| habitat:     |             grasses=g,leaves=l,meadows=m,paths=p, urban=u,waste=w,woods=d|"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "respecto a las visualizaciones, solo nos interesa contar en cada columna cuanto se repiten los elementos de esta, por lo mismo haremos histogramas para cada columna, diferenciando entre comestible o venenoso, que es información entregada en la primera columan del dataframe `mushroom`\n",
    "\n",
    "* notar que en `stalk-root` tenemos muchos datos perdidos (2480), marcados con un ?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 244,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\aaihs\\Miniconda3\\envs\\mat281-v2\\lib\\site-packages\\pandas\\plotting\\_matplotlib\\core.py:328: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n",
      "  fig = self.plt.figure(figsize=self.figsize)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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AAQccsMXO6c0EkiRJVViwYAFnnXUWn/vc53jhhRe44oorOO644xgxYsQWO2dVQS0iGoBzgDOAEcAzwHdTSjeX1YwHpgIfBd4Ark4pzaw4zn7AZcB+wDLgBuCSlNKasprdgMuBg4FW4GfARSml5V17i5IkqQjWta6u+5MB1rWupk+/pi7tO2HCBLbZZhvOOeccBg0axKmnnsqZZ55Z4xZuqNoetYuBycAlwG+Aw4GbIqI1pTQnIj4O3AXcCvxv4CBgRkQ0pJQuA4iIUcD9wGPACcCeZMFuCHBWXjMMeAB4HZgI7AxMJwuHn97sdytJkuqmqwGpKG1oampiypQpTJkypYYt2rQOg1pENAIXAN9PKU3NV9+f9459BZhDFuJ+l1I6Jd9+T77f1yPiqpRSCzAJWAoclVJaDdwdESuBqyJiWkppAXAmMAzYJ6W0OD//a3nt/imlx2v1xiVJkoqumpsJ1gKfBKZVrF8NbBMR2wCfACr7Mm8DtgM+ni+PB+7MQ1p5Td98W6nm4VJIy90LLAeOqKKtkiRJW40Oe9RSSuuAJ2H9WLXhwBeAQ4EvAyOBRiBV7Ppc/hoR8TjZ5csNalJKCyNiGRD5qj2A2RU1ayPixbIaSZKkbvXAAw/U5bydvevzGLJeMIC5ZKFqn3y5cra30uD/IcDQjdSU6obk3w+toqYq8+fP70y5aqC5ubneTVAPMXbs2Ho3oVfyd1TV2pzPSr9+/VixYkUNW9PzrV69uss/084Gtd+RXQb9W2AKWVj7X/m2to3ssw5o2ERNQ15T+r6jmqqMHj2a/v37d2YXbYbm5mb/8ZUKzt9RVWNz/54/9dRTGzxmSdlNCGPGjGl3W0tLyyY7lzoV1FJKLwIvAo/klyx/zLshrLLHq7S8lHd7ydrrFRuU15Rq26sZDLzUmbZKkqT6aGtro6GhoePCXqCtbWP9WNXp8GaCiNg+Ik6JiPdXbPpd/ror2Q0Hoyq2l5ZTSultYEFlTUQMJwtmpbFrqZ2avvk5KsfASZKkgmlqamLVqlX1bkZhrFq1isbGxi7vX81dn33Ies6+XLG+dKfmb4FHgGPymw1KjiXrISs9Uv5eYEJENFXUrAUeKqs5JCLKH5o1nqzX7b4q2ipJkupoxx135LXXXuOtt95izZo1m92j1FO1tbWxcuVKFixY8J6HuXdGNXd9LoqIa4BJ+bxnT5BNaHsx8IOUUoqIb5MFqVsi4gayKTkuBCallFbmh5oOnEQ2J9oVwO7ApcD1KaVX8ppryOZmuz8iJgM75Pv9MqX0WJffpSRJ6hZDhw6lf//+LFy4kMWLF2/wbMzeprGxkZ133pkhQzp1P+QGqh2jdh7wCnAa8C3gNbKnFMwASCk9EBHH5tvuILvMeWH5I6RSSk/nj5maQXbn6CKyR0VdUlazKCIOAa4AbiK723MOWeiTJEk9wDbbbLNFn3/Zm1QV1PJncU7PvzZW83Pg5x0cZx6wyUfMp5Tmk83RJkmS1KtVM0ZNkiRJdWBQkyRJKiiDmiRJUkEZ1CRJkgrKoCZJklRQBjVJkqSCMqhJkiQVlEFNkiSpoAxqkiRJBWVQkyRJKiiDmiRJUkEZ1CRJkgrKoCZJklRQBjVJkqSCMqhJkiQVlEFNkiSpoAxqkiRJBWVQkyRJKiiDmiRJUkEZ1CRJkgrKoCZJklRQBjVJkqSCMqhJkiQVlEFNkiSpoAxqkiRJBWVQkyRJKiiDmiRJUkH1q6YoIvoAXwLOAEYCbwC/AC5JKS3Pa54DPtLO7jullBblNfsBlwH7AcuAG/JjrCk7127A5cDBQCvwM+Ci0nkkSZJ6i6qCGnAR8G1gBnA/sDswBdgLOCwiBpEFuEnAwxX7LgGIiFH5vo8BJwB7AlOBIcBZec0w4AHgdWAisDMwHRgBfLoL70+SJKnH6jCoRUQDWVC7LqV0cb76vohYDNwSEfsAA4EG4Bcppac3cqhJwFLgqJTSauDuiFgJXBUR01JKC4AzgWHAPimlxfn5X8tr908pPd7ldypJktTDVDNGbTAwG7i5Yn0pkH0E2Ad4B3h2E8cZD9yZh7SS24C++bZSzcOlkJa7F1gOHFFFWyVJkrYaHfaopZSWAWe3s+kz+esfyQLWYuCnETE+P+5dwLkppb9ExECyy5ep4tgLI2IZEPmqPchCYXnN2oh4saxGkiSpV+jSXZ8RsT/Zpcw78kudY4BdyELbBOA84JPAgxExABia77qsncMtJxunRl7XUY0kSVKvUO3NBOtFxD+Q9Za9CJyerz4baCgbQzYvIv4E/Br4R2Buvr6tnUM2AOvKvu+opirz58/vTLlqoLm5ud5NUA8xduzYejehV/J3VNXys1IcnQpqEXEi2ZQazwCHlcaSpZT+vbI2pfRoRCwl6237ab66vV6xQWQ3GZC/tlczGHipM20dPXo0/fv378wu2gzNzc3+4ysVnL+jqoZ/z7tXS0vLJjuXqr70GRHnkwWufwM+kVJ6PV+/bUR8ISLGVNQ3AE3AopTS28ACYFRFzXCyYFYau5baqekL7ErF+DZJkqStXVVBLSJOA2YCc8h60paWbX4n33ZJxW5HAQOAh/Lle4EJEdFUVnMssLai5pCI2L6sZjxZr9t91bRVkiRpa1HNPGrDgSuBl4Grgb+L2OAGzOfIJsOdGRFXAv8CjAa+RTav2kN53XTgJLI50a4gmzT3UuD6lNIrec01wFeA+yNiMrBDvt8vU0qPdf1tSpIk9TzV9KgdRjah7YeAeWSXPsu/DkspXU52Y8GnyILaBcC1ZMEMgPzu0FLv2G3A+WSPijqnrGYRcAjZVB83kT25YA5wYtffoiRJUs9UzTxqNwI3VlH3Q+CHHdTMAw7ooGY+cGhH55MkSdradWkeNUmSJG15BjVJkqSCMqhJkiQVlEFNkiSpoAxqkiRJBWVQkyRJKiiDmiRJUkEZ1CRJkgrKoCZJklRQBjVJkqSCMqhJkiQVlEFNkiSpoAxqkiRJBWVQkyRJKiiDmiRJUkEZ1CRJkgrKoCZJklRQBjVJkqSCMqhJkiQVlEFNkiSpoAxqkiRJBWVQkyRJKiiDmiRJUkEZ1CRJkgrKoCZJklRQBjVJkqSCMqhJkiQVlEFNkiSpoPpVUxQRfYAvAWcAI4E3gF8Al6SUluc144GpwEfz7VenlGZWHGc/4DJgP2AZcEN+jDVlNbsBlwMHA63Az4CLSueRJEnqLartUbsIuBqYC3wGmAl8nixEEREfB+4CngaOAW4CZkTEBaUDRMQo4H5gFXBCfozzgVllNcOAB4CdgYnAxcBngZ928f1JkiT1WB32qEVEA1lQuy6ldHG++r6IWAzcEhH7AJOB36WUTsm33xMRjcDXI+KqlFILMAlYChyVUloN3B0RK4GrImJaSmkBcCYwDNgnpbQ4P/9ree3+KaXHa/XGJUmSiq6aHrXBwGzg5or1T+evHwU+Adxesf02YDvg4/nyeODOPKSV1/TNt5VqHi6FtNy9wHLgiCraKkmStNXoMKillJallM5OKT1asekz+evvgUYgVWx/Ln+NiBgIjKisSSktJBurFvmqPdqpWQu8WFYjSZLUK3Tprs+I2J/sUuYdwNB89bKKstLg/yGbqCnVDcm/H1pFjSRJUq9Q1V2f5SLiH8huHHgROJ13e7raNrLLOqBhEzUNeU3p+45qqjJ//vzOlKsGmpub690E9RBjx46tdxN6JX9HVS0/K8XRqaAWESeSTanxDHBYSmlxRCzNN1f2eJWWl/JuL1l7vWKD8ppSbXs1g4GXOtPW0aNH079//87sos3Q3NzsP75Swfk7qmr497x7tbS0bLJzqepLnxFxPtk0Gf8GfCKl9Hq+6XlgLTCqYpfSckopvQ0sqKyJiOFkwaw0Li21U9MX2JX3joGTJEnaqlUV1CLiNLJ5z+aQ9aSVesBIKb0DPAIck0/lUXIsWQ/ZE/nyvcCEiGiqqFkLPFRWc0hEbF9WM56s1+2+Kt+TJEnSVqGaedSGA1cCL5NNevt3ERvcgPkc8G2yIHVLRNxANiXHhcCklNLKvG46cBLZnGhXALsDlwLXp5ReyWuuAb4C3B8Rk4Ed8v1+mVJ6rOtvU5IkqeeppkftMGAg8CFgHtmlz/Kvw1JKD5D1ju1JdifoycCFKaXppYOklJ7m3d6x28ieSnA5cE5ZzSLgEGAx2dMNppL14p24Ge9RkiSpR+qwRy2ldCNwYxV1Pwd+3kHNPOCADmrmA4d2dD5JkqStXZfmUZMkSdKWZ1CTJEkqKIOaJElSQRnUJEmSCsqgJkmSVFAGNUmSpIIyqEmSJBWUQU2SJKmgDGqSJEkFZVCTJEkqKIOaJElSQRnUJEmSCsqgJkmSVFAGNUmSpIIyqEmSJBWUQU2SJKmgDGqSJEkFZVCTJEkqKIOaJElSQRnUJEmSCsqgJkmSVFAGNUmSpIIyqEmSJBWUQU2SJKmgDGqSJEkFZVCTJEkqKIOaJElSQRnUJEmSCqpfZ3eIiH2A3wK7ppReK1v/HPCRdnbZKaW0KK/ZD7gM2A9YBtwAXJJSWlN2nN2Ay4GDgVbgZ8BFKaXlnW2rJElST9apoBYRAdxVuV9EDAJGApOAhyt2W5LXjALuBx4DTgD2BKYCQ4Cz8pphwAPA68BEYGdgOjAC+HRn2ipJktTTVRXUIqIf8CXgO8Cadkr+FmgAfpFSenojh5kELAWOSimtBu6OiJXAVRExLaW0ADgTGAbsk1JanJ/7tbx2/5TS4514b5IkST1atWPUDiLr2ZoJfK2d7fsA7wDPbuIY44E785BWchvQN99Wqnm4FNJy9wLLgSOqbKskSdJWodqg9hQwMqX0LbJxY5XGAIuBn0bEkoh4OyJuiYhdACJiINnly1S+U0ppIdlYtchX7dFOzVrgxbIaSZKkXqGqS58ppTc6KBkD7AL8EbiKLHBNBh6MiL8DhuZ1y9rZdznZODXyuo5qJEmSeoVO3/W5EWcDDWVjyOZFxJ+AXwP/CMzN17e1s28DsK7s+45qqjJ//vzOlKsGmpub690E9RBjx46tdxN6JX9HVS0/K8VRk6CWUvr3dtY9GhFLyXrbfpqvbq9XbBDZTQbkr+3VDAZe6kybRo8eTf/+/TuzizZDc3Oz//hKBefvqKrh3/Pu1dLSssnOpc2e8DYito2IL0TEmIr1DUATsCil9DawABhVUTOcLJiVxqWldmr6ArtSMXZNkiRpa1eLJxO8Q3Y36CUV648CBgAP5cv3AhMioqms5lhgbUXNIRGxfVnNeLJet/tq0FZJkqQeY7MvfaaU1kbEt4GZEXEl8C/AaOBbZPOqPZSXTgdOIpsT7Qpgd+BS4PqU0it5zTXAV4D7I2IysEO+3y9TSo9tblslSZJ6kpo86zOldDlwOvApsqB2AXAtWTAr1TzNu71jtwHnkz0q6pyymkXAIWRTfdxE9uSCOcCJtWinJElST9LpHrWU0g1kz+isXP9D4Icd7DsPOKCDmvnAoZ1tlyRJ0tamJj1qkiRJqj2DmiRJUkEZ1CRJkgrKoCZJklRQBjVJkqSCMqhJkiQVlEFNkiSpoAxqkiRJBWVQkyRJKiiDmiRJUkEZ1CRJkgrKoCZJklRQBjVJkqSCMqhJkiQVlEFNkiSpoAxqkiRJBWVQkyRJKiiDmiRJUkEZ1CRJkgrKoCZJklRQBjVJkqSCMqhJkiQVlEFNkiSpoAxqkiRJBWVQkyRJKiiDmiRJUkEZ1CRJkgrKoCZJklRQ/Tq7Q0TsA/wW2DWl9FrZ+vHAVOCjwBvA1SmlmRX77gdcBuwHLANuAC5JKa0pq9kNuBw4GGgFfgZclFJa3tm2SpIk9WSd6lGLiADuoiLgRcTH8/VPA8cANwEzIuKCsppRwP3AKuAEYCZwPjCrrGYY8ACwMzARuBj4LPDTTr4vSZKkHq+qHrWI6Ad8CfgOsKadksnA71JKp+TL90REI/D1iLgqpdQCTAKWAkellFYDd0fESuCqiJiWUloAnAkMA/ZJKS3Oz/1aXrt/Sunxrr9VSZKknqXaHrWDgOlkvWBfK98QEdsAnwBur9jnNmA74OP58njgzjykldf0zbeVah4uhbTcvcBy4Igq2ypJkrRVqDaoPQWMTCl9i2zcWLmRQCOQKtY/l79GRAwERlTWpJQWko1Vi3zVHu3UrAVeLKuRJEnqFaq69JlSemMTm4fmr8sq1pcG/w/ZRE2pbkjZsTqqqcr8+fM7U64aaG5urncT1EOMHTu23k3olfwdVbX8rBRHp+/6bEdD/tq2ke3rOqhpyGtK33dUU5XRo0fTv3//zuyizdDc3Ow/vlLB+Tuqavj3vHu1tLRssnOpFvOoLc1fK3u8hpRtX7aRGoBBZcdYupGawWU1kiRJvUItgtrzwFpgVMX60nJKKb0NLKisiYjhZMGsNC4ttVPTF9iV946BkyRJ2qptdlBLKb0DPAIcExENZZuOJesFeyJfvheYEBFNFTVrgYfKag6JiO3LasaT9brdt7ltlSRJ6klqMUYN4NtkQeqWiLiBbEqOC4FJKaWVec104CSyOdGuAHYHLgWuTym9ktdcA3wFuD8iJgM75Pv9MqX0WI3aKkmS1CPU5FmfKaUHyHrH9gTuAE4GLkwpTS+reZp3e8duI3sqweXAOWU1i4BDgMVkTzeYCswBTqxFOyVJknqSTveopZRuIHtGZ+X6nwM/72DfecABHdTMBw7tbLskSZK2NjXpUZMkSVLtGdQkSZIKyqAmSZJUUAY1SZKkgjKoSZIkFZRBTZIkqaAMapIkSQVlUJMkSSoog5okSVJBGdQkSZIKyqAmSZJUUAY1SZKkgjKoSZIkFZRBTZIkqaAMapIkSQVlUJMkSSoog5okSVJBGdQkSZIKyqAmSZJUUAY1SZKkgjKoSZIkFZRBTZIkqaAMapIkSQVlUJMkSSoog5okSVJBGdQkSZIKyqAmSZJUUAY1SZKkgupXqwNFRD9gObBNxaYVKaVBec14YCrwUeAN4OqU0syK4+wHXAbsBywDbgAuSSmtqVVbJUmSeoKaBTUgyELa54FnytavBYiIjwN3AbcC/xs4CJgREQ0ppcvymlHA/cBjwAnAnmTBbghwVg3bKkmSVHi1DGpjgHXAbSmlle1snwz8LqV0Sr58T0Q0Al+PiKtSSi3AJGApcFRKaTVwd0SsBK6KiGkppQU1bK8kSVKh1XKM2j7A8+2FtIjYBvgEcHvFptuA7YCP58vjgTvzkFZe0zffJklSj7B6zdp6N6FL9tjzo/VugsrUuketJSLuIbusuQaYA1wAjAAagVSxz3P5a0TE43ndBjUppYURsYzs0qokST1CU2NfJnz1F/VuRqfdOfOoejdBZWod1IYA/xe4lOxmgG+SBayL85plFfssz1+HAEM3UlOqG9KZxsyfP78z5aqB5ubmejdBPcTYsWPr3YReyd/R7tWTP+d+VoqjlkHtROCtlNKT+fIjEfEGMJt3L1u2bWTfdUDDJmoa8pqqjR49mv79+3dmF22G5ubmHv1HSeoN/B1VtfysdJ+WlpZNdi7VLKillB5uZ/XciuXKXrHS8lLe7Ulrr+dsUF4jSZLUa9TkZoKIGB4Rp0fEyIpNA/LXN8im6RhVsb20nFJKbwMLKmsiYjhZeKsc3yZJkrRVq9Vdn+uA63jvXGcnkgW0+4BHgGMioqFs+7FkPWVP5Mv3AhMioqmiZi3wUI3aKkmS1CPU5NJnSmlRRHwPODu/Q3Me8A/A18mePvBcRHybLLDdEhE3kE3JcSEwqWxKj+nASWTzp10B7E52Y8L1KaVXatFWSZKknqKW86h9FfifwGfJxqZ9HrgEOB8gpfQAWe/YnsAdwMnAhSml6aUDpJSeJrvxYBDZ/GnnA5cD59SwnZIkST1CLW8mWEPWIzZ9EzU/B37ewXHmAQfUql2SJEk9VS171CRJklRDBjVJkqSCMqhJkiQVlEFNkiSpoAxqkiRJBWVQkyRJKiiDmiRJUkEZ1CRJkgrKoCZJklRQBjVJkqSCMqhJkiQVlEFNkiSpoAxqkiRJBWVQkyRJKiiDmiRJUkEZ1CRJkgrKoCZJklRQBjVJkqSCMqhJkiQVlEFNkiSpoAxqkiRJBWVQkyRJKiiDmiRJUkEZ1CRJkgrKoCZJklRQBjVJkqSCMqhJkiQVVL96N6A9EXES8L+AkcBLwLSU0o11bZQkSb3AutbV9OnXVO9mdElPbvvGFC6oRcTxwE3A/wHuAT4D/DgiVqaUbqtn2yRJ2tr16dfEC1OPrXczumTk12+vdxNqrnBBDZgGzEkpnZcv/yoitgemAAY1SZLUaxRqjFpEjAQ+AlRG4tuAPSJi1+5vlaqx91571LsJXbaudXW9myBJUruK1qNW+tc+Vax/Ln8N4MXua46q1TRgW7vKJUmqsaIFtaH567KK9cvz1yFVHKMvwOrV9pJ0t7UDhnZcVEAtLS31bkKvtN22fevdhE5raWnxc65O8XPevXri57wsr7T7YWloa2vrvtZ0ICI+R3YjwYdTSi+Xrd8NeAY4vqMbCpqbmw8C5m3RhkqSJNXWwWPHjv115cqi9agtzV8re84GV2zflN8CBwOvA2tr1C5JkqQtoS/wPrL88h5FC2qlsWmjgCfL1o+q2L5RY8eObQHek0glSZIK6vmNbSjUXZ8ppefIbhY4rmLTscCzKaVXur9VkiRJ9VG0HjWAycCPIuKvwF3AfwNOAD5b11ZJkiR1s0LdTFASEV8GLgBGAC+QPULqJ/VtlSRJUvcqZFCTJElSwcaoSZIk6V0GNUmSpIIyqEmSJBWUQU2SpF4qIj4REYM2sm27iDi+u9ukDRVxeg5JKoyI2Av4JNmziBcBv04pPV3fVkk18yBwAO3Pir8vcCPws25tkTbgXZ/aLBExGNiWdnpnU0p/7v4WSbUREX2A64BTgYayTW1k/3idmlLyD6h6nIj4Mdn0VwCfAn4HLGundHdgTUpp125qmtrhpU91SUR8JCIeBpYAC4BX2/mSerJJwMT89YNAI/A3wMXAScCF9WuatFnmkD0Lu/Q87LXtfK0mexzjifVooN7lpU911dXAXsA3gdeAdXVtjVR7pwFTU0ozyta9BkyPiG3y7dPr0jJpM6SU5gJzASLiQeB/eDm/uAxq6qpPAKenlH5a74ZIW8j7gEc3su0xsp41qUdLKR1S7zZo07z0qa5aDrxV70ZIW9ALwIEb2XYg8Ho3tkVSL2WPmrpqNnBmRNzrgGptpX4ATIuIFcAtwBvAzmTj0/4ncGkd2yaplzCoqauWAgcDz0TE48DKiu1tKaUvd3+zpJq5imx6gpnAZWXrG8j+ozK1Ho2S1Ls4PYe6JCJe7KCkLaU0slsaI21B+TxqnwC2B/4KPJxS+lN9WyWptzCoSZIkFZQ3E0iSJBWUQU2SJKmgDGqS6i4iHoqIl+rdjnqKiBsiwrEokjbgXZ+SimAq2TNjJUllDGqS6i6l9K/1boMkFZGXPiVJkgrKHjVJ3Sofi/avZP9RPBlYRDaB8rYppQ/nNQ8B7wBXAN8GRgNvAv8MTE4prSs73v7ANOBjwDLg/wLrgG+llBo6aMs3gUnA3sAs4JNAK/AvwPkppcVldZcAu6aUXqrYf/36fPkC4O+B/wN8HFiSfz8D+CrwFWAY2fNC/3v58fJjHghcmbfpVeB7KaUrKmo+SPZkhMOBwcBTwGUppZvKam4ADsiPVZqc96SU0j2b+plIKhZ71CTVw0nAPsA5ZMFqYTs1ewNzgIeAs8mevXkJ8N9LBRExFngQ+DAwOT/WOflXtfrmx1hOFrJuByYC3+/EMco1AQ8Az5EFswXAd4FfAqeTBcIrgf8C/Kid/f8VeDrf9yVgVh4AAYiI9wOPA4fmx7mALOzOjogLK471N2Q/s28C1+f7SepB7FGTVA8DgBNSSs8DRMQh7dS8H/hvKaU785obgT+T9cJdk9dMB1qA/VNKC/O6XwBPdKIt/YBbU0pfzZevi4gPAEdHxMCUUuXj0TrSCMxOKV2Qt+cR4I9kvWsfKWvnh4HPRUT/lFJL2f7XpJQuymu+TxbcJkXEVXkP36XANsDolFLpwfBXR8RNwJSI+HFK6c18/QDgjJTSDZ18D5IKwh41SfXwXCmkbcJKYG5pIaX0DpCAXQAiYhjwKeAnpfCT1/0euLeT7ZlTsfwHsgC3QyePU/Lzsu+fyV8fLW8n8CLZc0N3rth3eumb/BLv1UB/4L9GRB/gM8AjwJqI2LH0Bfy/Ul3F8X7VxfcgqQDsUZNUD292XMLi8rFouRayS5UAI8n+s/lsO/s+DRwGEBF9gZ0qtq9OKb1Vtlx56bXUw9WXrnmj9E1KqTUi4L3veW3+Wv4f5sUppUUVdaVA+2FgR2AoWVj7zEbO/TcVy9X8rCUVlEFNUj2s7biEypBWqTF/bWln2ztl348g670q9zBZb1y159qYjQW51nbWVTOZbXs1pSC3tux8twHXbeQYL5QvpJSq+VlLKiiDmqSeqhRIdm9n225l3/+F914O/Gsnz1UKO/0r1u/SyeN0ZPuIGJxSWl62rvRenifr+VsJNKaU7ivfMSL+Bvg7YEWN2ySpjhyjJqlHygfMPwaclI9XAyAidiWbtqJU905K6b6Kr+ZOnu4v+es+ZecZDBzR5TfQvj7AaWXn6AecC7wN3J9SagXuBo6MiDEV+15ONjZuxxq3SVId2aMmqSe7gGz6jt9GxLVkPV5nkw3Sr6U7yKbCuDoiPkR2ufVLZAGqllYCk/PeseeAz5LdLXpGSmlpXjMJGAc8EhHfA14GPp1/XZdS+mON2ySpjuxRk9RjpZT+jeymgYVkE+OeQRao/h/tj13r6nkWkvXSPU82X9uFwK3AN2p1jtxfgaPJ5kibRXbX6T+mlNbP6ZbfLbs/2R2xXySbFHgkcD5wZo3bI6nOGtraqhnfKknFExG7pJT+0s76O4ExKaXKOyAlqUexR01ST/Z4RGzwSKSI2Bk4BPj3+jRJkmrHMWqSerKfAF+PiJvJHgO1HdnYsT7At+rYLkmqCYOapJ7sG2STy34ROApYBTwKHJdSerKeDZOkWnCMmiRJUkE5Rk2SJKmgDGqSJEkFZVCTJEkqKIOaJElSQRnUJEmSCsqgJkmSVFD/H6NV0PvKcyVvAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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4MjACeA24G7g0pbQsr3kO2KWdzbdPKS3Ma/YFrgD2BZYCN+b7WF1yrF2BK4GDgBbgp8CFbcfRxs2ZM4eWlhb69ctO7QMPPEBdXR37779/lVsmSZK6qrM3E1wIXAZcDjwE7AZMBPYEDo2IQWQBbjzwWNm2iwEiYmS+7ePA8cAewCRgMHBGXjMUeBh4FTgF2AGYAgwHPr4Jn6/XmT9/PmeccQaf/vSnef7557nqqqs49thjGT58eLWbJkmSuqjDoBYRdWRB7fsppYvyxQ9GxCLg9ojYGxgI1AF3p5Se3sCuxgNLgCNTSs3AfRGxArgmIianlOYDXwGGAnunlBblx38lr90vpfTEJn/STlrb0lz1JwOsbWmmT7+GTdp23LhxbLHFFpx11lkMGjSI0047ja985SsVbqEkSeoOnelR2wqYDvykbHlbINuFrOfrLeDZjexnLDArD2ltZgDX5et+lL8+1hbScrOBZcDhwLse1DY1IBWlDQ0NDUycOJGJEydWsEWSJKkaOgxqKaWlwJntrPpk/vrfZAFrEXBbRIzN93sPcHZK6X8iYiDZ5ctUtu8FEbEUiHzR7mShsLRmTUS8UFIjSZLUK2zSXZ8RsR/Zpcy78kudo4EdyULbOOAc4KPAIxExABiSb9reHBHLyMapkdd1VCNJktQrdPnJBBHxj2S9ZS8An8sXnwnUlYwhmxMRfwJ+CfwzcG++vLWdXdYBa0t+7qimU+bOnbvBdf369WP58uVd2V3htNf+WbNmbXBdR5qbm2lqatrsdqlz/K5rl+eutnn+KqexsbFbj9dbz12XglpEnEA2pcYzwKFtY8lSSr8pr00p/SoilpD1tt2WL26vV2wQ2U0G5K/t1WwFvNiVto4aNYr+/fu3u27evHlvm72/1ixfvrzi7W9oaGD06NEV3afa19TU1O1/wakyPHe1zfNX23rquVu1atVGO5c6fekzIs4lC1z/CXwkpfRqvnzLiPhsRIwuq68DGoCFKaU3gfnAyLKaYWTBrG3sWmqnpi+wM2Xj2yRJknq6TgW1iDgdmArcQdaTtqRk9Vv5ukvLNjsSGAA8mr+fDYyLiNJbGo8B1pTVHBwRpdPojyXrdXuwM23trNbW9q6w9k5+F5IkFVNn5lEbBlwNvARcC/x9xNtuwHyObDLcqRFxNfAfwCjgm2Tzqj2a100BTiSbE+0qsklzvwXckFL6S15zHfBV4KGImABsm2/3s5TS45v+Md+uoaGBlStXMnDgwErtsqatXLmS+vr6ajdDkiSV6UyP2qFkE9q+H5hDdumz9NehKaUryW4s+BhZUDsfuJ4smAGQ3x3a1js2AziX7FFRZ5XULAQOJpvq4xayJxfcAZyw6R/xnbbbbjteeeUV3njjDVavXt1re5RaW1tZsWIF8+fPf8fD3CVJUvV1Zh61m4GbO1H3b8C/dVAzB9joQydTSnOBQzo63uYYMmQI/fv3Z8GCBSxatIiWlpZ383AV19zcTENDZSbmra+vZ4cddmDwYGc/kSSpaLo8PUdPscUWW9Ts8y+bmpq8Q1OSpF5gkya8lSRJ0rvPoCZJklRQBjVJkqSCMqhJkiQVlEFNkiSpoAxqkiRJBWVQkyRJKiiDmiRJUkEZ1CRJkgrKoCZJklRQBjVJkqSCMqhJkiQVlEFNkiSpoAxqkiRJBWVQkyRJKiiDmiRJUkEZ1CRJkgrKoCZJklRQBjVJkqSCMqhJkiQVlEFNkiSpoAxqkiRJBWVQkyRJKiiDmiRJUkEZ1CRJkgrKoCZJklRQBjVJkqSCMqhJkiQVlEFNkiSpoAxqkiRJBWVQkyRJKiiDmiRJUkEZ1CRJkgrKoCZJklRQBjVJkqSC6teZoojoA3wB+DIwAngNuBu4NKW0LK8ZC0wCPpivvzalNLVsP/sCVwD7AkuBG/N9rC6p2RW4EjgIaAF+ClzYdhxJkqTeorM9ahcC1wL3Ap8EpgKnkoUoIuLDwD3A08DRwC3A5RFxftsOImIk8BCwEjg+38e5wLSSmqHAw8AOwCnARcCngNs28fNJkiTVrA571CKijiyofT+ldFG++MGIWATcHhF7AxOA36WUTs7X3x8R9cDFEXFNSmkVMB5YAhyZUmoG7ouIFcA1ETE5pTQf+AowFNg7pbQoP/4ree1+KaUnKvXBJUmSiq4zPWpbAdOBW8uWP52/fhD4CDCzbP0MYGvgw/n7scCsPKSV1vTN17XVPNYW0nKzgWXA4Z1oqyRJUo/RYVBLKS1NKZ2ZUvpV2apP5q+/B+qBVLb+ufw1ImIgMLy8JqW0gGysWuSLdm+nZg3wQkmNJElSr7BJd31GxH5klzLvAobki5eWlbUN/h+8kZq2usH5z0M6USNJktQrdOquz1IR8Y9kNw68AHyO9T1drRvYZC1Qt5Gaurym7eeOajpl7ty5XSmvOU1NTdVugjaD5692ee5qm+evchobG7v1eL313HUpqEXECWRTajwDHJpSWhQRS/LV5T1ebe+XsL6XrL1esUF5TVttezVbAS92pa2jRo2if//+XdmkZjQ1NXX7HxBVjuevdnnuapvnr7b11HO3atWqjXYudfrSZ0ScSzZNxn8CH0kpvZqv+jOwBhhZtknb+5RSehOYX14TEcPIglnbuLTUTk1fYGfeOQZOkiSpR+tUUIuI08nmPbuDrCetrQeMlNJbwC+Ao/OpPNocQ9ZD9mT+fjYwLiIaymrWAI+W1BwcEduU1Iwl63V7sJOfSZIkqUfozDxqw4CrgZfIJr39+4i33YD5HHAZWZC6PSJuJJuS4wJgfEppRV43BTiRbE60q4DdgG8BN6SU/pLXXAd8FXgoIiYA2+bb/Syl9Pimf0xJkqTa05ketUOBgcD7gTlklz5Lfx2aUnqYrHdsD7I7QU8CLkgpTWnbSUrpadb3js0geyrBlcBZJTULgYOBRWRPN5hE1ot3wmZ8RkmSpJrUYY9aSulm4OZO1N0J3NlBzRxg/w5q5gKHdHQ8SZKknm6T5lGTJEnSu8+gJkmSVFAGNUmSpIIyqEmSJBWUQU2SJKmgDGqSJEkFZVCTJEkqKIOaJElSQRnUJEmSCsqgJkmSVFAGNUmSpIIyqEmSJBWUQU2SJKmgDGqSJEkFZVCTJEkqKIOaJElSQRnUatBee+7ercdb29LcrceTJEmZftVugLquYcCWPD/pmG473oiLZ3bbsSRJ0nr2qEmSJBWUQU2SJKmgDGqSJEkFZVCTJEkqKIOaJElSQRnUJEmSCsqgJkmSVFAGNUmSpIIyqEmSJBWUQU2SJKmgDGqSJEkFZVCTJEkqKIOaJElSQRnUJEmSCsqgJkmSVFAGNUmSpIIyqEmSJBWUQU2SJKmgDGqSJEkF1a+rG0TE3sBvgZ1TSq+ULH8O2KWdTbZPKS3Ma/YFrgD2BZYCNwKXppRWl+xnV+BK4CCgBfgpcGFKaVlX2ypJklTLuhTUIiKAe8q3i4hBwAhgPPBY2WaL85qRwEPA48DxwB7AJGAwcEZeMxR4GHgVOAXYAZgCDAc+3pW2SpIk1bpOBbWI6Ad8Afg2sLqdkr8D6oC7U0pPb2A344ElwJEppWbgvohYAVwTEZNTSvOBrwBDgb1TSovyY7+S1+6XUnqiC59NkiSppnV2jNqBZD1bU4GvtbN+b+At4NmN7GMsMCsPaW1mAH3zdW01j7WFtNxsYBlweCfbKkmS1CN0NqjNA0aklL5JNm6s3GhgEXBbRCyOiDcj4vaI2BEgIgaSXb5MpRullBaQjVWLfNHu7dSsAV4oqZEkSeoVOnXpM6X0Wgclo4Edgf8GriELXBOARyLi74Ehed3SdrZdRjZOjbyuo5pOmTt3blfKa0pjY2O3H7Opqanbj9mT+X3WLs9dbfP8VU53/1vUW89dl+/63IAzgbqSMWRzIuJPwC+BfwbuzZe3trNtHbC25OeOajpl1KhR9O/fvyubaCOqEQ57qqamJr/PGuW5q22ev9rWU8/dqlWrNtq5VJF51FJKvykf6J9S+hXZzQOjWd9L1l6v2KC8jvy1vZqtSmokSZJ6hc0OahGxZUR8NiJGly2vAxqAhSmlN4H5wMiymmFkwaxtXFpqp6YvsDNlY9ckSZJ6ukr0qL1FdjfopWXLjwQGAI/m72cD4yKioaTmGGBNWc3BEbFNSc1Ysl63ByvQVkmSpJqx2WPUUkprIuIyYGpEXA38BzAK+CbZvGqP5qVTgBPJ5kS7CtgN+BZwQ0rpL3nNdcBXgYciYgKwbb7dz1JKj29uWyVJkmpJpcaoXQl8DvgYWVA7H7ieLJi11TzN+t6xGcC5ZI+KOqukZiFwMNlUH7eQPbngDuCESrRTkiSplnS5Ry2ldCPZMzrLl/8b8G8dbDsH2L+DmrnAIV1tlyRJUk9TkR41SZIkVZ5BTZIkqaAMapIkSQVlUJMkSSoog5okSVJBGdQkSZIKyqAmSZJUUAY1SZKkgjKoSZIkFZRBTZIkqaAMapIkSQVlUJMkSSoog5okddJee+7ercdb29LcrceTVDz9qt0ASaoVDQO25PlJx3Tb8UZcPLPbjiWpmOxRkyRJKiiDmiRJUkEZ1CRJkgrKoCZJklRQBjVJkqSCMqhJkiQVlEFNkiSpoAxqkiRJBWVQkyRJKiiDmiRJUkEZ1CRJkgrKoCZJklRQBjVJkqSCMqhJkiQVlEFNkiSpoAxqkiRJBWVQkyRJKiiDmiRJUkEZ1CRJkgrKoCZJklRQBjVJkqSCMqhJkiQVVL+ubhARewO/BXZOKb1SsnwsMAn4IPAacG1KaWrZtvsCVwD7AkuBG4FLU0qrS2p2Ba4EDgJagJ8CF6aUlnW1rZIkSbWsSz1qERHAPZQFvIj4cL78aeBo4Bbg8og4v6RmJPAQsBI4HpgKnAtMK6kZCjwM7ACcAlwEfAq4rYufS5IkqeZ1qkctIvoBXwC+Daxup2QC8LuU0sn5+/sjoh64OCKuSSmtAsYDS4AjU0rNwH0RsQK4JiImp5TmA18BhgJ7p5QW5cd+Ja/dL6X0xKZ/VEmSpNrS2R61A4EpZL1gXytdERFbAB8BZpZtMwPYGvhw/n4sMCsPaaU1ffN1bTWPtYW03GxgGXB4J9sqSZLUI3Q2qM0DRqSUvkk2bqzUCKAeSGXLn8tfIyIGAsPLa1JKC8jGqkW+aPd2atYAL5TUSJIk9QqduvSZUnptI6uH5K9Ly5a3Df4fvJGatrrBJfvqqKZwmlevoaG+b7WbIUmSepgu3/XZjrr8tXUD69d2UFOX17T93FFNp8ydO7cr5ZulsbGRcefd3W3HmzX1yG47VpumpqZuP2ZP5vdZmxobG7v9mP5eqSy/z8rp7j8PvfXcVSKoLclfy3u8BpesX7qBGoBBJftYsoGarYAXu9KoUaNG0b9//65soo2oxj9QPVVTU5PfpzrN3yuV45+92tZTz92qVas22rlUiQlv/wysAUaWLW97n1JKbwLzy2siYhhZMGsbl5baqekL7Mw7x8BJkiT1aJsd1FJKbwG/AI6OiLqSVceQ9ZA9mb+fDYyLiIaymjXAoyU1B0fENiU1Y8l63R7c3LZKkiTVkkpc+gS4jCxI3R4RN5JNyXEBMD6ltCKvmQKcSDYn2lXAbsC3gBtSSn/Ja64Dvgo8FBETgG3z7X6WUnq8Qm2VJEmqCRV51mdK6WGy3rE9gLuAk4ALUkpTSmqeZn3v2AyypxJcCZxVUrMQOBhYRPZ0g0nAHcAJlWinJElSLelyj1pK6UayZ3SWL78TuLODbecA+3dQMxc4pKvtkiRJ6mkq0qMmSZKkyjOoSZIkFZRBTZIkqaAMapIkSQVlUJMkSSoog5okSVJBGdQkSZIKyqAmSZJUUAY1SZKkgjKoSZIkFZRBTZIkqaAMapIkqdDWtjT36ONtTJcfyi5JktSd+vRr4PlJx3Tb8UZcPLPbjtURe9QkSZIKyqAmSZJUUAY1SZKkgjKoSZIkFZRBTZIkqaAMapIkSQVlUJMkSSoog5okSVJBGdQkSZIKyqAmSZJUUAY1SZKkgjKoSZIkFZRBTZIkqaAMapIkSQVlUJMkSSoog5okSVJBGdQkSZIKyqAmSZJUUAY1SZKkgjKoSZIkFZRBTZIkqaAMapIkSQVlUJMkSSqofpXaUUT0A5YBW5StWp5SGpTXjAUmAR8EXgOuTSlNLdvPvsAVwL7AUuBG4NKU0upKtVWSJKkWVCyoAUEW0k4FnilZvgYgIj4M3AP8BPhX4EDg8oioSyldkdeMBB4CHgeOB/YgC3aDgTMq2FZJkqTCq2RQGw2sBWaklFa0s34C8LuU0sn5+/sjoh64OCKuSSmtAsYDS4AjU0rNwH0RsQK4JiImp5TmV7C9kiRJhVbJMWp7A39uL6RFxBbAR4CZZatmAFsDH87fjwVm5SGttKZvvk6SJKnXqHSP2qqIuJ/ssuZq4A7gfGA4UA+ksm2ey18jIp7I695Wk1JaEBFLyS6tSpIk9RqV7FEbDewC3AccDkwETgRmAUPymqVl2yzLXwdvpKatbnAF2ypJklR4lexROwF4I6X0VP7+FxHxGjCd9ZctWzew7VqgbiM1dXlNp82dO7cr5ZulsbGx245VLU1NTdVuQo/i91mbqvFn3d8rleX3WTk9/d++ovxeqVhQSyk91s7ie8vel/eKtb1fwvqetPZ6zgblNZ02atQo+vfv35VNtBE9/Q9kd2pqavL7VKf5e6Vy/LOnruiu3yurVq3aaOdSRS59RsSwiPhcRIwoWzUgf32NbJqOkWXr296nlNKbwPzymogYRhbeyse3SZIk9WiVGqO2Fvg+75zr7ASygPYg8Avg6IioK1l/DFlP2ZP5+9nAuIhoKKtZAzxaobZKkiTVhIpc+kwpLYyI7wJn5ndozgH+EbiY7OkDz0XEZWSB7faIuJFsSo4LgPElU3pMIbsB4b6IuArYDfgWcENK6S+VaKskSVKtqORdn+cB/wJ8imxs2qnApcC5ACmlh8l6x/YA7gJOAi5IKU1p20FK6WmyGw8Gkc2fdi5wJXBWBdspSZJUEyp5M8Fqsh6xKRupuRO4s4P9zAH2r1S7JEmSalUle9QkSZJUQQY1SZKkgjKoSZIkFZRBTZIkqaAMapIkSQVlUJMkSSoog5okSVJBGdQkSZIKyqAmSZJUUAY1SZKkgjKoSZIkFZRBTZIkqaAMapIkSQVlUJMkSSoog5okSVJBGdQkSZIKyqAmSZJUUAY1SZKkgjKoSZIkFZRBTZIkqaAMapIkSQVlUJMkSSoog5okSVJBGdQkSZIKyqAmSZJUUAY1SZKkgjKoSZIkFZRBTZIkqaAMapIkSQVlUJMkSSoog5okSVJBGdQkSZIKyqAmSZJUUAY1SZKkgjKoSZIkFZRBTZIkqaD6VbsB7YmIE4FLgBHAi8DklNLNVW2UJElSNytcj1pEHAfcAswGPgk8CtwUEcdWsVnqwZpXr+nW4+2+xwe79XiSpNpVxB61ycAdKaVz8vcPRMQ2wERgRvWapZ6qob4v4867u9uON2vqkd12LElSbStUj1pEjAB2AWaWrZoB7B4RO3d/qyRJPcFee+7ercdb29LcrcdTz1S0HrW2P0WpbPlz+WsAL3RfcyRJPUXDgC15ftIx3Xa8EReX9zlIXVe0oDYkf11atnxZ/jq4E/voC9Dc3L3/k9l6y77ddqxVq1axZsCQjgsreLyerrvPn2qXf/Zqm+evsrrr786e/O9eSV5p98usa21t7bbGdCQiPk12I8EHUkovlSzfFXgGOC6ltNFxak1NTQcCc97VhkqSJFXWQY2Njb8sX1i0HrUl+Wt5z9lWZes35rfAQcCrQPfezidJktQ1fYH3kOWXdyhaUGsbmzYSeKpk+ciy9RvU2Ni4CnhHIpUkSSqoP29oRaHu+kwpPUd2s0D5nGnHAM+mlP7S/a2SJEmqjqL1qAFMAH4UEX8D7gE+ARwPfKqqrZIkSepmhbqZoE1EfBE4HxgOPE/2CKkfV7dVkiRJ3auQQU2SJEkFG6MmSZKk9QxqkiRJBWVQkyooIhqq3QZJUs9hUJMq66WI2B8gIr4eETtVu0GSpNpVxOk51I6IeB8wBtgJuJFsFuP/Til170NN1ZGtgffmP18K/Az4a9VaI0mqad71WQMi4nLgLLJg3Qp8CJhMFgjGpJRer2LzVCIiHgUOIAtn7yd7lNmGnu7bmlLapZuapk6KiH/pQnlrSmnyu9YYbbaI2ArYknauIKWU/E9UwUXEHmSPhRwKvA48klJ6saqN6mb2qBVcRHwNOJNsXrl7gOfyVd8AZgCTgM9XpXFqz4lk52tb4HSyZ7ctqGqL1FWXdaG2lew/TSqYiNgF+CFw4EbK+nZTc9RFETEA+DFwFFBXsmptRPwA+FJKqVf0NBnUiu+LwDdSSldHxLq/VFJK/xkRlwATq9c0lUspvQpcBBAR/we4NKX0x+q2Sl2RUnLsbs9wLbAn2X9qXwHWVrU16qorgEPJ/uM7k+w/vMOA44BvkV21mFC11nUjg1rx7UTWK9OeF8l6blRAKaWdq90GqRf7CPC5lNJt1W6INslxwEUppe+WLHsVaOu0OJdeEtT8n2Px/Rn4pw2sO4jsEVuSpLdbBrxR7UZokzWw4X/f/gQM6ca2VJVBrfiuAs6NiKuAj5GNiRkREWcCFwLXVa1lklRc04GvRERdh5UqopuBr+Vj1daJiD7Al4Bbq9KqKvCuzxoQERcBFwMDWD+oshmYmlK6uGoNk6SCioh/Jbs8thB4AlhRVtKaUvpitzdMnRIR3yAbn7Ya+A+yMWnbko1b+wBwC+vvqO/R59KgViMiYjDZtA/bAkuAX6eUFlW3VZJUTBHxQgclrSmlEd3SGHVZJ85fqR59Lg1qkiRJBeUYNUmSpIIyqEmSJBWUQU1STYqIRyPixSodu09EfKAax5bUuxjUJNWqScDZ3X3Q/MaeXwOf6e5jS+p9fDKBpJqUUvp5lQ69DfAh4L4qHV9SL2KPmiRJUkE5PYekwsvHov2c7D+XJ5FNYroE2DKl9IG85lHgLbKneVwGjAJeB34ITEgprS3Z337AZLKesaXA/yN7aPc3U0obnMk+Ij4GPFK2eG+yS6GzUkrHl9V/iezpIR8E/gH4Uf56CXBI/hluBy5OKa0s2W6LvOYk4L1kDxWfDlyWUmreyFclqYexR01SrTiRLBSdRRasFrRTsxdwB/Ao2azmzwOXAv+3rSAiGsnC1gfIHur8//J9ntWJNswDzsl/vhM4GXiO7DLoERExsKz+U8B/pZT+VLJsBjAMGA/8LN/fXSXt6wvcA5xHNiP7mcDDZE8nmekjkaTexTFqkmrFAOD4lNKfASLi4HZqdgI+kVKaldfcTPbomZNY/1zcKWSPntkvpbQgr7sbeLKjBqSUXouIu4BpZAFser79LcDRwMfJgiIRsRNwIPAvZbt5DfhoW89YRLwKXBwR/5RSeoAs/P1v4ND8PXndb4DvA58A7u6orZJ6BnvUJNWK59pC2kasAO5te5NSegtIwI4AETEU+Bjw47aQltf9Hpi9GW27l+wyZumlzxPIns17e1nt1LLLl1fmr5/IX48h6y1siojt2n6R9dqtIQuDknoJe9Qk1YrXO1GzqHQsWm4V0Df/eQTZf1CfbWfbp8ke+Nx2+XH7svXNKaU32jtoSmlVRPw78KmI2DKltJzssufjKaWXysr/VLbtGxHxBtmlWIBd8mO3d2kX4H9tYLmkHsigJqlWrOlETXlIK1efv65qZ91bJT8PB8ofCv0YWW/chtwCfBb4eEQ8QXbTwBnt1LV3M0Bf1n++vmRB8ssbOM7fNtIGST2MQU1Sb/J8/rpbO+t2Lfn5f4D/U7a+o4D0CPAq2SXMHYEW8vFqZXYhuxwLQERsDwxhfS/fi8C+wMNld6rWk42De7mDdkjqQRyjJqnXSCm9DjwOnJiPVwMgInYGDiupeyul9GDZr6Z8dVvP19v+/sxD1e3AP5GNI3uodBxciTPK7tw8P3/99/z1P8gm1f1S2Xb/N9//IZ37tJJ6AnvUJPU255NN3/HbiLge6E82BUZnp71YRHaJ9RMR8RLw7ymltt62W8mm2zgEOHUD2x8M3BcRs4D9ye7yvDml9Kt8/Q/yba+JiL8HfkM27cgXgd+RzcUmqZewR01Sr5JS+k+ymwYWkE2M+2XgarIerfbGrpVvv4JsTrPhwDXA6JJ1TwLPkI13u2sDuziNLBROJZu+4yKysW1t+1hFNj3H1Pz1arIeuu8BY/PjS+olfDKBpF4lInZMKf1PO8tnAaNTSpt1V2VEzCObY+2EsuWfIesNOzil9OjmHENS72GPmqTe5omIuL90QUTsQHZJ8jebs+OI+CiwO16elFQhjlGT1Nv8mOxJALeS3am5NfAFsv+4fnNTdhgRp5BdnhwL/BF4YONbSFLnGNQk9TZfJ3uM0+eBI4GVwK+AY1NKT23iPlvI7hp9Bvh0SskxJZIqwjFqkiRJBeUYNUmSpIIyqEmSJBWUQU2SJKmgDGqSJEkFZVCTJEkqKIOaJElSQf1/AqEj3CMT7hAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "mushroom[\"count_p_e\"] = 1\n",
    "\n",
    "for j in mushroom.columns.drop([\"class\",\"count_p_e\"]):\n",
    "    df = mushroom[[\"class\",j,\"count_p_e\"]].groupby([j,\"class\"])[\"count_p_e\"].apply(sum).unstack(\"class\").replace(np.nan,0)\n",
    "    df = df.reset_index()\n",
    "    df.plot(x = j,kind='bar',figsize=(10,6));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Respecto al **preprocesamiento** podemos ver de forma exhaustiva con ayuda de `.describe` que las columnas solo tienen los elementos que deberían tener. A parte de esto no tenemos elementos nulos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "class                       0\n",
       "cap-shape                   0\n",
       "cap-surface                 0\n",
       "cap-color                   0\n",
       "bruises                     0\n",
       "odor                        0\n",
       "gill-attachment             0\n",
       "gill-spacing                0\n",
       "gill-size                   0\n",
       "gill-color                  0\n",
       "stalk-shape                 0\n",
       "stalk-root                  0\n",
       "stalk-surface-above-ring    0\n",
       "stalk-surface-below-ring    0\n",
       "stalk-color-above-ring      0\n",
       "stalk-color-below-ring      0\n",
       "veil-type                   0\n",
       "veil-color                  0\n",
       "ring-number                 0\n",
       "ring-type                   0\n",
       "spore-print-color           0\n",
       "population                  0\n",
       "habitat                     0\n",
       "count_p_e                   0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 220,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mushroom.isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "pero más relevante nos conviene trabajar con datos numéricos ya que las implementaciones que hemos visto funcionan con esta condición, además de que veremos una visualización más clara con esto hecho "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "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>class</th>\n",
       "      <th>cap-shape</th>\n",
       "      <th>cap-surface</th>\n",
       "      <th>cap-color</th>\n",
       "      <th>bruises</th>\n",
       "      <th>odor</th>\n",
       "      <th>gill-attachment</th>\n",
       "      <th>gill-spacing</th>\n",
       "      <th>gill-size</th>\n",
       "      <th>gill-color</th>\n",
       "      <th>...</th>\n",
       "      <th>stalk-surface-below-ring</th>\n",
       "      <th>stalk-color-above-ring</th>\n",
       "      <th>stalk-color-below-ring</th>\n",
       "      <th>veil-type</th>\n",
       "      <th>veil-color</th>\n",
       "      <th>ring-number</th>\n",
       "      <th>ring-type</th>\n",
       "      <th>spore-print-color</th>\n",
       "      <th>population</th>\n",
       "      <th>habitat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8119</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8120</th>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8121</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8122</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8123</th>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8124 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      class  cap-shape  cap-surface  cap-color  bruises  odor  \\\n",
       "0         1          5            2          4        1     6   \n",
       "1         0          5            2          9        1     0   \n",
       "2         0          0            2          8        1     3   \n",
       "3         1          5            3          8        1     6   \n",
       "4         0          5            2          3        0     5   \n",
       "...     ...        ...          ...        ...      ...   ...   \n",
       "8119      0          3            2          4        0     5   \n",
       "8120      0          5            2          4        0     5   \n",
       "8121      0          2            2          4        0     5   \n",
       "8122      1          3            3          4        0     8   \n",
       "8123      0          5            2          4        0     5   \n",
       "\n",
       "      gill-attachment  gill-spacing  gill-size  gill-color  ...  \\\n",
       "0                   1             0          1           4  ...   \n",
       "1                   1             0          0           4  ...   \n",
       "2                   1             0          0           5  ...   \n",
       "3                   1             0          1           5  ...   \n",
       "4                   1             1          0           4  ...   \n",
       "...               ...           ...        ...         ...  ...   \n",
       "8119                0             0          0          11  ...   \n",
       "8120                0             0          0          11  ...   \n",
       "8121                0             0          0           5  ...   \n",
       "8122                1             0          1           0  ...   \n",
       "8123                0             0          0          11  ...   \n",
       "\n",
       "      stalk-surface-below-ring  stalk-color-above-ring  \\\n",
       "0                            2                       7   \n",
       "1                            2                       7   \n",
       "2                            2                       7   \n",
       "3                            2                       7   \n",
       "4                            2                       7   \n",
       "...                        ...                     ...   \n",
       "8119                         2                       5   \n",
       "8120                         2                       5   \n",
       "8121                         2                       5   \n",
       "8122                         1                       7   \n",
       "8123                         2                       5   \n",
       "\n",
       "      stalk-color-below-ring  veil-type  veil-color  ring-number  ring-type  \\\n",
       "0                          7          0           2            1          4   \n",
       "1                          7          0           2            1          4   \n",
       "2                          7          0           2            1          4   \n",
       "3                          7          0           2            1          4   \n",
       "4                          7          0           2            1          0   \n",
       "...                      ...        ...         ...          ...        ...   \n",
       "8119                       5          0           1            1          4   \n",
       "8120                       5          0           0            1          4   \n",
       "8121                       5          0           1            1          4   \n",
       "8122                       7          0           2            1          0   \n",
       "8123                       5          0           1            1          4   \n",
       "\n",
       "      spore-print-color  population  habitat  \n",
       "0                     2           3        5  \n",
       "1                     3           2        1  \n",
       "2                     3           2        3  \n",
       "3                     2           3        5  \n",
       "4                     3           0        1  \n",
       "...                 ...         ...      ...  \n",
       "8119                  0           1        2  \n",
       "8120                  0           4        2  \n",
       "8121                  0           1        2  \n",
       "8122                  7           4        2  \n",
       "8123                  4           1        2  \n",
       "\n",
       "[8124 rows x 23 columns]"
      ]
     },
     "execution_count": 226,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn import preprocessing\n",
    "le = preprocessing.LabelEncoder()\n",
    "for col in mushroom.columns:\n",
    "    mushroom[col] = le.fit_transform(mushroom[col])\n",
    "mushroom"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "con esto hecho podemos visualizar cómo se vería una interpretación numérica un poco más amigable que lo anterior"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 2160x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np; np.random.seed(42)\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "sns.set(rc={'figure.figsize':(30,8)}, font_scale=1.5, style='whitegrid')\n",
    "\n",
    "sns.boxplot(x=\"variable\", y=\"value\", data=pd.melt(mushroom), width=0.5)\n",
    "plt.xticks(rotation=90)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Respecto a la **inputación**, tenemos que hacer algo con las filas que contienen un dato perdido en al columna 11, `stalk-root` ya que representan 1/4 de los datos y además por los histogramas antes visto vemos que estos están cargados a los venenosos (p), en concreto, más del doble de elemento con ? en la columna 11 para \"p\" es el doble que el de \"e\".\n",
    "\n",
    "* rellenar con algún valor fijo (como la moda) no es una buena opción ya que estariamos cargando 1/4 de los datos a una opción, recordemos que son 2480 registros con valor perdido.\n",
    "* eliminar las 2480 filas no parece una buena opción ya que esto corresponde a solo una columan de 22 y hay mucha información relevante en esas 21 variables faltantes y quizá más importante, hay más elementos venenosos que comestibles.\n",
    "\n",
    "* opción 1: podriamos considerarlo como una categoría más. En el caso de ser concluyente en el análisis cambiariamos de criterio.\n",
    "\n",
    "* opción 2: (un poco más complejo) realizar una \"regresión\" con la columna 11 como target. Tenemos 3/4 de los datos para entrenar, entra dentro de un rango efectivo. También hay otros métodos más rebuscados, EM,etc pero están conceptualmente fuera de lo trabajado [Techniques of dealing with missing data](https://en.wikipedia.org/wiki/Missing_data#Techniques_of_dealing_with_missing_data).\n"
   ]
  },
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   "source": [
    "Por la siguiente casilla, notemos que hay una diferencia de un 3.6% respecto al total de datos, lo que no es tan significante, por lo que no consideramos necesario hacer un **balanceo** de los datos."
   ]
  },
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   "source": [
    "**MODELOS:**\n",
    "\n",
    "* Logistico:\n",
    "\n",
    "$$\\min_{w,c} \\frac{1}{2}w^Tw + C \\sum_{i=1}^n log(exp(-y_i(X_i^T w+c)+1))$$\n",
    "\n",
    "* K-Nearest Neighbours (KNN): número de vecinos\n",
    "* Ridge:\n",
    "\n",
    "$$ \\min_{\\omega} ||X\\omega - y||_{2}^{2} + \\alpha||\\omega||_{2}^{2}$$\n",
    "\n",
    "* Lasso:\n",
    "\n",
    "$$\\min_{\\beta}\\dfrac{1}{n_{sample}} ||y-X\\beta||_2^2 + \\alpha||\\beta||_1^2$$\n",
    "\n",
    "similitud Lasso-Ridge"
   ]
  }
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