{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "135e1f28",
   "metadata": {},
   "source": [
    "# Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a02319bb",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "sns.set_theme(palette= \"colorblind\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f085979",
   "metadata": {},
   "source": [
    "## Jupyter FAQ\n",
    "```{admonition} Question from class\n",
    "Why doesn't my jupyter print things out that are on the last line?\n",
    "```\n",
    "\n",
    "Whem we create a variable and then put that on the last line of a cell, jupyter\n",
    "displays it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3edf0c07",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'sarah'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name = 'sarah'\n",
    "name"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f243b19a",
   "metadata": {},
   "source": [
    "How it diplsays it depends on the type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "bd1e7c57",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "str"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(name)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef36be26",
   "metadata": {},
   "source": [
    "For a string, it uses `print`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9bf34b50",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sarah\n"
     ]
    }
   ],
   "source": [
    "print(name)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56943cf4",
   "metadata": {},
   "source": [
    "so this and the one above look the same.  For objects that have a `_repr_html_`\n",
    "method, juypter uses that, and uses html to render the object in a more visually\n",
    "appealing way.\n",
    "\n",
    "\n",
    "## Review of describe\n",
    "we're going to work with the arabica data today, because it's a little bigger\n",
    "and more interesting for plotting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "5db0e861",
   "metadata": {},
   "outputs": [],
   "source": [
    "arabica_data_url = 'https://raw.githubusercontent.com/jldbc/coffee-quality-database/master/data/arabica_data_cleaned.csv'\n",
    "\n",
    "coffee_df = pd.read_csv(arabica_data_url)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e5280407",
   "metadata": {},
   "source": [
    "We can describe it again, to see it has mostly the same variables we saw before,\n",
    "but some different as well."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "5bd85c6f",
   "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>Unnamed: 0</th>\n",
       "      <th>Number.of.Bags</th>\n",
       "      <th>Aroma</th>\n",
       "      <th>Flavor</th>\n",
       "      <th>Aftertaste</th>\n",
       "      <th>Acidity</th>\n",
       "      <th>Body</th>\n",
       "      <th>Balance</th>\n",
       "      <th>Uniformity</th>\n",
       "      <th>Clean.Cup</th>\n",
       "      <th>Sweetness</th>\n",
       "      <th>Cupper.Points</th>\n",
       "      <th>Total.Cup.Points</th>\n",
       "      <th>Moisture</th>\n",
       "      <th>Category.One.Defects</th>\n",
       "      <th>Quakers</th>\n",
       "      <th>Category.Two.Defects</th>\n",
       "      <th>altitude_low_meters</th>\n",
       "      <th>altitude_high_meters</th>\n",
       "      <th>altitude_mean_meters</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1311.000000</td>\n",
       "      <td>1311.000000</td>\n",
       "      <td>1311.000000</td>\n",
       "      <td>1311.000000</td>\n",
       "      <td>1311.000000</td>\n",
       "      <td>1311.000000</td>\n",
       "      <td>1311.000000</td>\n",
       "      <td>1311.000000</td>\n",
       "      <td>1311.000000</td>\n",
       "      <td>1311.00000</td>\n",
       "      <td>1311.000000</td>\n",
       "      <td>1311.000000</td>\n",
       "      <td>1311.000000</td>\n",
       "      <td>1311.000000</td>\n",
       "      <td>1311.000000</td>\n",
       "      <td>1310.000000</td>\n",
       "      <td>1311.000000</td>\n",
       "      <td>1084.000000</td>\n",
       "      <td>1084.000000</td>\n",
       "      <td>1084.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>656.000763</td>\n",
       "      <td>153.887872</td>\n",
       "      <td>7.563806</td>\n",
       "      <td>7.518070</td>\n",
       "      <td>7.397696</td>\n",
       "      <td>7.533112</td>\n",
       "      <td>7.517727</td>\n",
       "      <td>7.517506</td>\n",
       "      <td>9.833394</td>\n",
       "      <td>9.83312</td>\n",
       "      <td>9.903272</td>\n",
       "      <td>7.497864</td>\n",
       "      <td>82.115927</td>\n",
       "      <td>0.088863</td>\n",
       "      <td>0.426392</td>\n",
       "      <td>0.177099</td>\n",
       "      <td>3.591915</td>\n",
       "      <td>1759.548954</td>\n",
       "      <td>1808.843803</td>\n",
       "      <td>1784.196379</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>378.598733</td>\n",
       "      <td>129.733734</td>\n",
       "      <td>0.378666</td>\n",
       "      <td>0.399979</td>\n",
       "      <td>0.405119</td>\n",
       "      <td>0.381599</td>\n",
       "      <td>0.359213</td>\n",
       "      <td>0.406316</td>\n",
       "      <td>0.559343</td>\n",
       "      <td>0.77135</td>\n",
       "      <td>0.530832</td>\n",
       "      <td>0.474610</td>\n",
       "      <td>3.515761</td>\n",
       "      <td>0.047957</td>\n",
       "      <td>1.832415</td>\n",
       "      <td>0.840583</td>\n",
       "      <td>5.350371</td>\n",
       "      <td>8767.847252</td>\n",
       "      <td>8767.187498</td>\n",
       "      <td>8767.016913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>328.500000</td>\n",
       "      <td>14.500000</td>\n",
       "      <td>7.420000</td>\n",
       "      <td>7.330000</td>\n",
       "      <td>7.250000</td>\n",
       "      <td>7.330000</td>\n",
       "      <td>7.330000</td>\n",
       "      <td>7.330000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>10.00000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>7.250000</td>\n",
       "      <td>81.170000</td>\n",
       "      <td>0.090000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1100.000000</td>\n",
       "      <td>1100.000000</td>\n",
       "      <td>1100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>656.000000</td>\n",
       "      <td>175.000000</td>\n",
       "      <td>7.580000</td>\n",
       "      <td>7.580000</td>\n",
       "      <td>7.420000</td>\n",
       "      <td>7.500000</td>\n",
       "      <td>7.500000</td>\n",
       "      <td>7.500000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>10.00000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>7.500000</td>\n",
       "      <td>82.500000</td>\n",
       "      <td>0.110000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1310.640000</td>\n",
       "      <td>1350.000000</td>\n",
       "      <td>1310.640000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>983.500000</td>\n",
       "      <td>275.000000</td>\n",
       "      <td>7.750000</td>\n",
       "      <td>7.750000</td>\n",
       "      <td>7.580000</td>\n",
       "      <td>7.750000</td>\n",
       "      <td>7.670000</td>\n",
       "      <td>7.750000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>10.00000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>7.750000</td>\n",
       "      <td>83.670000</td>\n",
       "      <td>0.120000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1600.000000</td>\n",
       "      <td>1650.000000</td>\n",
       "      <td>1600.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1312.000000</td>\n",
       "      <td>1062.000000</td>\n",
       "      <td>8.750000</td>\n",
       "      <td>8.830000</td>\n",
       "      <td>8.670000</td>\n",
       "      <td>8.750000</td>\n",
       "      <td>8.580000</td>\n",
       "      <td>8.750000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>10.00000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>90.580000</td>\n",
       "      <td>0.280000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>55.000000</td>\n",
       "      <td>190164.000000</td>\n",
       "      <td>190164.000000</td>\n",
       "      <td>190164.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Unnamed: 0  Number.of.Bags        Aroma       Flavor   Aftertaste  \\\n",
       "count  1311.000000     1311.000000  1311.000000  1311.000000  1311.000000   \n",
       "mean    656.000763      153.887872     7.563806     7.518070     7.397696   \n",
       "std     378.598733      129.733734     0.378666     0.399979     0.405119   \n",
       "min       1.000000        0.000000     0.000000     0.000000     0.000000   \n",
       "25%     328.500000       14.500000     7.420000     7.330000     7.250000   \n",
       "50%     656.000000      175.000000     7.580000     7.580000     7.420000   \n",
       "75%     983.500000      275.000000     7.750000     7.750000     7.580000   \n",
       "max    1312.000000     1062.000000     8.750000     8.830000     8.670000   \n",
       "\n",
       "           Acidity         Body      Balance   Uniformity   Clean.Cup  \\\n",
       "count  1311.000000  1311.000000  1311.000000  1311.000000  1311.00000   \n",
       "mean      7.533112     7.517727     7.517506     9.833394     9.83312   \n",
       "std       0.381599     0.359213     0.406316     0.559343     0.77135   \n",
       "min       0.000000     0.000000     0.000000     0.000000     0.00000   \n",
       "25%       7.330000     7.330000     7.330000    10.000000    10.00000   \n",
       "50%       7.500000     7.500000     7.500000    10.000000    10.00000   \n",
       "75%       7.750000     7.670000     7.750000    10.000000    10.00000   \n",
       "max       8.750000     8.580000     8.750000    10.000000    10.00000   \n",
       "\n",
       "         Sweetness  Cupper.Points  Total.Cup.Points     Moisture  \\\n",
       "count  1311.000000    1311.000000       1311.000000  1311.000000   \n",
       "mean      9.903272       7.497864         82.115927     0.088863   \n",
       "std       0.530832       0.474610          3.515761     0.047957   \n",
       "min       0.000000       0.000000          0.000000     0.000000   \n",
       "25%      10.000000       7.250000         81.170000     0.090000   \n",
       "50%      10.000000       7.500000         82.500000     0.110000   \n",
       "75%      10.000000       7.750000         83.670000     0.120000   \n",
       "max      10.000000      10.000000         90.580000     0.280000   \n",
       "\n",
       "       Category.One.Defects      Quakers  Category.Two.Defects  \\\n",
       "count           1311.000000  1310.000000           1311.000000   \n",
       "mean               0.426392     0.177099              3.591915   \n",
       "std                1.832415     0.840583              5.350371   \n",
       "min                0.000000     0.000000              0.000000   \n",
       "25%                0.000000     0.000000              0.000000   \n",
       "50%                0.000000     0.000000              2.000000   \n",
       "75%                0.000000     0.000000              4.000000   \n",
       "max               31.000000    11.000000             55.000000   \n",
       "\n",
       "       altitude_low_meters  altitude_high_meters  altitude_mean_meters  \n",
       "count          1084.000000           1084.000000           1084.000000  \n",
       "mean           1759.548954           1808.843803           1784.196379  \n",
       "std            8767.847252           8767.187498           8767.016913  \n",
       "min               1.000000              1.000000              1.000000  \n",
       "25%            1100.000000           1100.000000           1100.000000  \n",
       "50%            1310.640000           1350.000000           1310.640000  \n",
       "75%            1600.000000           1650.000000           1600.000000  \n",
       "max          190164.000000         190164.000000         190164.000000  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coffee_df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f06abb8",
   "metadata": {},
   "source": [
    "```{admonition} Question from class\n",
    "Why do we need the `()` on the describe but not on just the data\n",
    "```\n",
    "\n",
    "As is often the case, again this comes back to the type."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "449d660a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(coffee_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac9fbfca",
   "metadata": {},
   "source": [
    "is a data frame which has the  `_repr_html_` method\n",
    "\n",
    "````{margin}\n",
    "```{note}\n",
    "notice that this one has the ... in the columns and rows directions.\n",
    "```\n",
    "```{admonition} Try it Yourself\n",
    "what can you check in a dataFrame to predict if it will display with or without\n",
    "the ...?\n",
    "```\n",
    "````"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "bca3366f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Species</th>\n",
       "      <th>Owner</th>\n",
       "      <th>Country.of.Origin</th>\n",
       "      <th>Farm.Name</th>\n",
       "      <th>Lot.Number</th>\n",
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       "      <th>ICO.Number</th>\n",
       "      <th>Company</th>\n",
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       "      <th>...</th>\n",
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       "      <th>Expiration</th>\n",
       "      <th>Certification.Body</th>\n",
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       "      <th>Certification.Contact</th>\n",
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       "      <th>altitude_high_meters</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Arabica</td>\n",
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       "      <td>metad plc</td>\n",
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       "      <td>metad agricultural developmet plc</td>\n",
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       "      <td>METAD Agricultural Development plc</td>\n",
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       "      <td>m</td>\n",
       "      <td>1950.00</td>\n",
       "      <td>2200.00</td>\n",
       "      <td>2075.00</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Arabica</td>\n",
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       "      <td>Ethiopia</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>metad plc</td>\n",
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       "      <td>Green</td>\n",
       "      <td>1</td>\n",
       "      <td>April 3rd, 2016</td>\n",
       "      <td>METAD Agricultural Development plc</td>\n",
       "      <td>309fcf77415a3661ae83e027f7e5f05dad786e44</td>\n",
       "      <td>19fef5a731de2db57d16da10287413f5f99bc2dd</td>\n",
       "      <td>m</td>\n",
       "      <td>1950.00</td>\n",
       "      <td>2200.00</td>\n",
       "      <td>2075.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Arabica</td>\n",
       "      <td>grounds for health admin</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>san marcos barrancas \"san cristobal cuch</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1600 - 1800 m</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>May 31st, 2011</td>\n",
       "      <td>Specialty Coffee Association</td>\n",
       "      <td>36d0d00a3724338ba7937c52a378d085f2172daa</td>\n",
       "      <td>0878a7d4b9d35ddbf0fe2ce69a2062cceb45a660</td>\n",
       "      <td>m</td>\n",
       "      <td>1600.00</td>\n",
       "      <td>1800.00</td>\n",
       "      <td>1700.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Arabica</td>\n",
       "      <td>yidnekachew dabessa</td>\n",
       "      <td>Ethiopia</td>\n",
       "      <td>yidnekachew dabessa coffee plantation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>wolensu</td>\n",
       "      <td>NaN</td>\n",
       "      <td>yidnekachew debessa coffee plantation</td>\n",
       "      <td>1800-2200</td>\n",
       "      <td>...</td>\n",
       "      <td>Green</td>\n",
       "      <td>2</td>\n",
       "      <td>March 25th, 2016</td>\n",
       "      <td>METAD Agricultural Development plc</td>\n",
       "      <td>309fcf77415a3661ae83e027f7e5f05dad786e44</td>\n",
       "      <td>19fef5a731de2db57d16da10287413f5f99bc2dd</td>\n",
       "      <td>m</td>\n",
       "      <td>1800.00</td>\n",
       "      <td>2200.00</td>\n",
       "      <td>2000.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Arabica</td>\n",
       "      <td>metad plc</td>\n",
       "      <td>Ethiopia</td>\n",
       "      <td>metad plc</td>\n",
       "      <td>NaN</td>\n",
       "      <td>metad plc</td>\n",
       "      <td>2014/2015</td>\n",
       "      <td>metad agricultural developmet plc</td>\n",
       "      <td>1950-2200</td>\n",
       "      <td>...</td>\n",
       "      <td>Green</td>\n",
       "      <td>2</td>\n",
       "      <td>April 3rd, 2016</td>\n",
       "      <td>METAD Agricultural Development plc</td>\n",
       "      <td>309fcf77415a3661ae83e027f7e5f05dad786e44</td>\n",
       "      <td>19fef5a731de2db57d16da10287413f5f99bc2dd</td>\n",
       "      <td>m</td>\n",
       "      <td>1950.00</td>\n",
       "      <td>2200.00</td>\n",
       "      <td>2075.00</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>1306</th>\n",
       "      <td>1307</td>\n",
       "      <td>Arabica</td>\n",
       "      <td>juan carlos garcia lopez</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>el centenario</td>\n",
       "      <td>NaN</td>\n",
       "      <td>la esperanza, municipio juchique de ferrer, ve...</td>\n",
       "      <td>1104328663</td>\n",
       "      <td>terra mia</td>\n",
       "      <td>900</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>20</td>\n",
       "      <td>September 17th, 2013</td>\n",
       "      <td>AMECAFE</td>\n",
       "      <td>59e396ad6e22a1c22b248f958e1da2bd8af85272</td>\n",
       "      <td>0eb4ee5b3f47b20b049548a2fd1e7d4a2b70d0a7</td>\n",
       "      <td>m</td>\n",
       "      <td>900.00</td>\n",
       "      <td>900.00</td>\n",
       "      <td>900.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1307</th>\n",
       "      <td>1308</td>\n",
       "      <td>Arabica</td>\n",
       "      <td>myriam kaplan-pasternak</td>\n",
       "      <td>Haiti</td>\n",
       "      <td>200 farms</td>\n",
       "      <td>NaN</td>\n",
       "      <td>coeb koperativ ekselsyo basen (350 members)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>haiti coffee</td>\n",
       "      <td>~350m</td>\n",
       "      <td>...</td>\n",
       "      <td>Blue-Green</td>\n",
       "      <td>16</td>\n",
       "      <td>May 24th, 2013</td>\n",
       "      <td>Specialty Coffee Association</td>\n",
       "      <td>36d0d00a3724338ba7937c52a378d085f2172daa</td>\n",
       "      <td>0878a7d4b9d35ddbf0fe2ce69a2062cceb45a660</td>\n",
       "      <td>m</td>\n",
       "      <td>350.00</td>\n",
       "      <td>350.00</td>\n",
       "      <td>350.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1308</th>\n",
       "      <td>1309</td>\n",
       "      <td>Arabica</td>\n",
       "      <td>exportadora atlantic, s.a.</td>\n",
       "      <td>Nicaragua</td>\n",
       "      <td>finca las marías</td>\n",
       "      <td>017-053-0211/ 017-053-0212</td>\n",
       "      <td>beneficio atlantic condega</td>\n",
       "      <td>017-053-0211/ 017-053-0212</td>\n",
       "      <td>exportadora atlantic s.a</td>\n",
       "      <td>1100</td>\n",
       "      <td>...</td>\n",
       "      <td>Green</td>\n",
       "      <td>5</td>\n",
       "      <td>June 6th, 2018</td>\n",
       "      <td>Instituto Hondureño del Café</td>\n",
       "      <td>b4660a57e9f8cc613ae5b8f02bfce8634c763ab4</td>\n",
       "      <td>7f521ca403540f81ec99daec7da19c2788393880</td>\n",
       "      <td>m</td>\n",
       "      <td>1100.00</td>\n",
       "      <td>1100.00</td>\n",
       "      <td>1100.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1309</th>\n",
       "      <td>1310</td>\n",
       "      <td>Arabica</td>\n",
       "      <td>juan luis alvarado romero</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>finca el limon</td>\n",
       "      <td>NaN</td>\n",
       "      <td>beneficio serben</td>\n",
       "      <td>11/853/165</td>\n",
       "      <td>unicafe</td>\n",
       "      <td>4650</td>\n",
       "      <td>...</td>\n",
       "      <td>Green</td>\n",
       "      <td>4</td>\n",
       "      <td>May 24th, 2013</td>\n",
       "      <td>Asociacion Nacional Del Café</td>\n",
       "      <td>b1f20fe3a819fd6b2ee0eb8fdc3da256604f1e53</td>\n",
       "      <td>724f04ad10ed31dbb9d260f0dfd221ba48be8a95</td>\n",
       "      <td>ft</td>\n",
       "      <td>1417.32</td>\n",
       "      <td>1417.32</td>\n",
       "      <td>1417.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1310</th>\n",
       "      <td>1312</td>\n",
       "      <td>Arabica</td>\n",
       "      <td>bismarck castro</td>\n",
       "      <td>Honduras</td>\n",
       "      <td>los hicaques</td>\n",
       "      <td>103</td>\n",
       "      <td>cigrah s.a de c.v.</td>\n",
       "      <td>13-111-053</td>\n",
       "      <td>cigrah s.a de c.v</td>\n",
       "      <td>1400</td>\n",
       "      <td>...</td>\n",
       "      <td>Green</td>\n",
       "      <td>2</td>\n",
       "      <td>April 28th, 2018</td>\n",
       "      <td>Instituto Hondureño del Café</td>\n",
       "      <td>b4660a57e9f8cc613ae5b8f02bfce8634c763ab4</td>\n",
       "      <td>7f521ca403540f81ec99daec7da19c2788393880</td>\n",
       "      <td>m</td>\n",
       "      <td>1400.00</td>\n",
       "      <td>1400.00</td>\n",
       "      <td>1400.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1311 rows × 44 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Unnamed: 0  Species                       Owner Country.of.Origin  \\\n",
       "0              1  Arabica                   metad plc          Ethiopia   \n",
       "1              2  Arabica                   metad plc          Ethiopia   \n",
       "2              3  Arabica    grounds for health admin         Guatemala   \n",
       "3              4  Arabica         yidnekachew dabessa          Ethiopia   \n",
       "4              5  Arabica                   metad plc          Ethiopia   \n",
       "...          ...      ...                         ...               ...   \n",
       "1306        1307  Arabica    juan carlos garcia lopez            Mexico   \n",
       "1307        1308  Arabica     myriam kaplan-pasternak             Haiti   \n",
       "1308        1309  Arabica  exportadora atlantic, s.a.         Nicaragua   \n",
       "1309        1310  Arabica   juan luis alvarado romero         Guatemala   \n",
       "1310        1312  Arabica             bismarck castro          Honduras   \n",
       "\n",
       "                                     Farm.Name                  Lot.Number  \\\n",
       "0                                    metad plc                         NaN   \n",
       "1                                    metad plc                         NaN   \n",
       "2     san marcos barrancas \"san cristobal cuch                         NaN   \n",
       "3        yidnekachew dabessa coffee plantation                         NaN   \n",
       "4                                    metad plc                         NaN   \n",
       "...                                        ...                         ...   \n",
       "1306                             el centenario                         NaN   \n",
       "1307                                 200 farms                         NaN   \n",
       "1308                          finca las marías  017-053-0211/ 017-053-0212   \n",
       "1309                            finca el limon                         NaN   \n",
       "1310                              los hicaques                         103   \n",
       "\n",
       "                                                   Mill  \\\n",
       "0                                             metad plc   \n",
       "1                                             metad plc   \n",
       "2                                                   NaN   \n",
       "3                                               wolensu   \n",
       "4                                             metad plc   \n",
       "...                                                 ...   \n",
       "1306  la esperanza, municipio juchique de ferrer, ve...   \n",
       "1307        coeb koperativ ekselsyo basen (350 members)   \n",
       "1308                         beneficio atlantic condega   \n",
       "1309                                   beneficio serben   \n",
       "1310                                 cigrah s.a de c.v.   \n",
       "\n",
       "                      ICO.Number                                Company  \\\n",
       "0                      2014/2015      metad agricultural developmet plc   \n",
       "1                      2014/2015      metad agricultural developmet plc   \n",
       "2                            NaN                                    NaN   \n",
       "3                            NaN  yidnekachew debessa coffee plantation   \n",
       "4                      2014/2015      metad agricultural developmet plc   \n",
       "...                          ...                                    ...   \n",
       "1306                  1104328663                              terra mia   \n",
       "1307                         NaN                           haiti coffee   \n",
       "1308  017-053-0211/ 017-053-0212               exportadora atlantic s.a   \n",
       "1309                  11/853/165                                unicafe   \n",
       "1310                  13-111-053                      cigrah s.a de c.v   \n",
       "\n",
       "           Altitude  ...       Color Category.Two.Defects  \\\n",
       "0         1950-2200  ...       Green                    0   \n",
       "1         1950-2200  ...       Green                    1   \n",
       "2     1600 - 1800 m  ...         NaN                    0   \n",
       "3         1800-2200  ...       Green                    2   \n",
       "4         1950-2200  ...       Green                    2   \n",
       "...             ...  ...         ...                  ...   \n",
       "1306            900  ...        None                   20   \n",
       "1307          ~350m  ...  Blue-Green                   16   \n",
       "1308           1100  ...       Green                    5   \n",
       "1309           4650  ...       Green                    4   \n",
       "1310           1400  ...       Green                    2   \n",
       "\n",
       "                Expiration                  Certification.Body  \\\n",
       "0          April 3rd, 2016  METAD Agricultural Development plc   \n",
       "1          April 3rd, 2016  METAD Agricultural Development plc   \n",
       "2           May 31st, 2011        Specialty Coffee Association   \n",
       "3         March 25th, 2016  METAD Agricultural Development plc   \n",
       "4          April 3rd, 2016  METAD Agricultural Development plc   \n",
       "...                    ...                                 ...   \n",
       "1306  September 17th, 2013                             AMECAFE   \n",
       "1307        May 24th, 2013        Specialty Coffee Association   \n",
       "1308        June 6th, 2018        Instituto Hondureño del Café   \n",
       "1309        May 24th, 2013        Asociacion Nacional Del Café   \n",
       "1310      April 28th, 2018        Instituto Hondureño del Café   \n",
       "\n",
       "                         Certification.Address  \\\n",
       "0     309fcf77415a3661ae83e027f7e5f05dad786e44   \n",
       "1     309fcf77415a3661ae83e027f7e5f05dad786e44   \n",
       "2     36d0d00a3724338ba7937c52a378d085f2172daa   \n",
       "3     309fcf77415a3661ae83e027f7e5f05dad786e44   \n",
       "4     309fcf77415a3661ae83e027f7e5f05dad786e44   \n",
       "...                                        ...   \n",
       "1306  59e396ad6e22a1c22b248f958e1da2bd8af85272   \n",
       "1307  36d0d00a3724338ba7937c52a378d085f2172daa   \n",
       "1308  b4660a57e9f8cc613ae5b8f02bfce8634c763ab4   \n",
       "1309  b1f20fe3a819fd6b2ee0eb8fdc3da256604f1e53   \n",
       "1310  b4660a57e9f8cc613ae5b8f02bfce8634c763ab4   \n",
       "\n",
       "                         Certification.Contact unit_of_measurement  \\\n",
       "0     19fef5a731de2db57d16da10287413f5f99bc2dd                   m   \n",
       "1     19fef5a731de2db57d16da10287413f5f99bc2dd                   m   \n",
       "2     0878a7d4b9d35ddbf0fe2ce69a2062cceb45a660                   m   \n",
       "3     19fef5a731de2db57d16da10287413f5f99bc2dd                   m   \n",
       "4     19fef5a731de2db57d16da10287413f5f99bc2dd                   m   \n",
       "...                                        ...                 ...   \n",
       "1306  0eb4ee5b3f47b20b049548a2fd1e7d4a2b70d0a7                   m   \n",
       "1307  0878a7d4b9d35ddbf0fe2ce69a2062cceb45a660                   m   \n",
       "1308  7f521ca403540f81ec99daec7da19c2788393880                   m   \n",
       "1309  724f04ad10ed31dbb9d260f0dfd221ba48be8a95                  ft   \n",
       "1310  7f521ca403540f81ec99daec7da19c2788393880                   m   \n",
       "\n",
       "     altitude_low_meters altitude_high_meters altitude_mean_meters  \n",
       "0                1950.00              2200.00              2075.00  \n",
       "1                1950.00              2200.00              2075.00  \n",
       "2                1600.00              1800.00              1700.00  \n",
       "3                1800.00              2200.00              2000.00  \n",
       "4                1950.00              2200.00              2075.00  \n",
       "...                  ...                  ...                  ...  \n",
       "1306              900.00               900.00               900.00  \n",
       "1307              350.00               350.00               350.00  \n",
       "1308             1100.00              1100.00              1100.00  \n",
       "1309             1417.32              1417.32              1417.32  \n",
       "1310             1400.00              1400.00              1400.00  \n",
       "\n",
       "[1311 rows x 44 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coffee_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "01f64495",
   "metadata": {},
   "source": [
    "so it prints nicely as tdid the `coffee_df.describe()`\n",
    "\n",
    "If we leave the `()` off we don't get nice formatting\n",
    "\n",
    "````{margin}\n",
    "```{hint}\n",
    "when objects do not have the `_repr_html_` method their output includes the type\n",
    "```\n",
    "````"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8a4a53ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method NDFrame.describe of       Unnamed: 0  Species                       Owner Country.of.Origin  \\\n",
       "0              1  Arabica                   metad plc          Ethiopia   \n",
       "1              2  Arabica                   metad plc          Ethiopia   \n",
       "2              3  Arabica    grounds for health admin         Guatemala   \n",
       "3              4  Arabica         yidnekachew dabessa          Ethiopia   \n",
       "4              5  Arabica                   metad plc          Ethiopia   \n",
       "...          ...      ...                         ...               ...   \n",
       "1306        1307  Arabica    juan carlos garcia lopez            Mexico   \n",
       "1307        1308  Arabica     myriam kaplan-pasternak             Haiti   \n",
       "1308        1309  Arabica  exportadora atlantic, s.a.         Nicaragua   \n",
       "1309        1310  Arabica   juan luis alvarado romero         Guatemala   \n",
       "1310        1312  Arabica             bismarck castro          Honduras   \n",
       "\n",
       "                                     Farm.Name                  Lot.Number  \\\n",
       "0                                    metad plc                         NaN   \n",
       "1                                    metad plc                         NaN   \n",
       "2     san marcos barrancas \"san cristobal cuch                         NaN   \n",
       "3        yidnekachew dabessa coffee plantation                         NaN   \n",
       "4                                    metad plc                         NaN   \n",
       "...                                        ...                         ...   \n",
       "1306                             el centenario                         NaN   \n",
       "1307                                 200 farms                         NaN   \n",
       "1308                          finca las marías  017-053-0211/ 017-053-0212   \n",
       "1309                            finca el limon                         NaN   \n",
       "1310                              los hicaques                         103   \n",
       "\n",
       "                                                   Mill  \\\n",
       "0                                             metad plc   \n",
       "1                                             metad plc   \n",
       "2                                                   NaN   \n",
       "3                                               wolensu   \n",
       "4                                             metad plc   \n",
       "...                                                 ...   \n",
       "1306  la esperanza, municipio juchique de ferrer, ve...   \n",
       "1307        coeb koperativ ekselsyo basen (350 members)   \n",
       "1308                         beneficio atlantic condega   \n",
       "1309                                   beneficio serben   \n",
       "1310                                 cigrah s.a de c.v.   \n",
       "\n",
       "                      ICO.Number                                Company  \\\n",
       "0                      2014/2015      metad agricultural developmet plc   \n",
       "1                      2014/2015      metad agricultural developmet plc   \n",
       "2                            NaN                                    NaN   \n",
       "3                            NaN  yidnekachew debessa coffee plantation   \n",
       "4                      2014/2015      metad agricultural developmet plc   \n",
       "...                          ...                                    ...   \n",
       "1306                  1104328663                              terra mia   \n",
       "1307                         NaN                           haiti coffee   \n",
       "1308  017-053-0211/ 017-053-0212               exportadora atlantic s.a   \n",
       "1309                  11/853/165                                unicafe   \n",
       "1310                  13-111-053                      cigrah s.a de c.v   \n",
       "\n",
       "           Altitude  ...       Color Category.Two.Defects  \\\n",
       "0         1950-2200  ...       Green                    0   \n",
       "1         1950-2200  ...       Green                    1   \n",
       "2     1600 - 1800 m  ...         NaN                    0   \n",
       "3         1800-2200  ...       Green                    2   \n",
       "4         1950-2200  ...       Green                    2   \n",
       "...             ...  ...         ...                  ...   \n",
       "1306            900  ...        None                   20   \n",
       "1307          ~350m  ...  Blue-Green                   16   \n",
       "1308           1100  ...       Green                    5   \n",
       "1309           4650  ...       Green                    4   \n",
       "1310           1400  ...       Green                    2   \n",
       "\n",
       "                Expiration                  Certification.Body  \\\n",
       "0          April 3rd, 2016  METAD Agricultural Development plc   \n",
       "1          April 3rd, 2016  METAD Agricultural Development plc   \n",
       "2           May 31st, 2011        Specialty Coffee Association   \n",
       "3         March 25th, 2016  METAD Agricultural Development plc   \n",
       "4          April 3rd, 2016  METAD Agricultural Development plc   \n",
       "...                    ...                                 ...   \n",
       "1306  September 17th, 2013                             AMECAFE   \n",
       "1307        May 24th, 2013        Specialty Coffee Association   \n",
       "1308        June 6th, 2018        Instituto Hondureño del Café   \n",
       "1309        May 24th, 2013        Asociacion Nacional Del Café   \n",
       "1310      April 28th, 2018        Instituto Hondureño del Café   \n",
       "\n",
       "                         Certification.Address  \\\n",
       "0     309fcf77415a3661ae83e027f7e5f05dad786e44   \n",
       "1     309fcf77415a3661ae83e027f7e5f05dad786e44   \n",
       "2     36d0d00a3724338ba7937c52a378d085f2172daa   \n",
       "3     309fcf77415a3661ae83e027f7e5f05dad786e44   \n",
       "4     309fcf77415a3661ae83e027f7e5f05dad786e44   \n",
       "...                                        ...   \n",
       "1306  59e396ad6e22a1c22b248f958e1da2bd8af85272   \n",
       "1307  36d0d00a3724338ba7937c52a378d085f2172daa   \n",
       "1308  b4660a57e9f8cc613ae5b8f02bfce8634c763ab4   \n",
       "1309  b1f20fe3a819fd6b2ee0eb8fdc3da256604f1e53   \n",
       "1310  b4660a57e9f8cc613ae5b8f02bfce8634c763ab4   \n",
       "\n",
       "                         Certification.Contact unit_of_measurement  \\\n",
       "0     19fef5a731de2db57d16da10287413f5f99bc2dd                   m   \n",
       "1     19fef5a731de2db57d16da10287413f5f99bc2dd                   m   \n",
       "2     0878a7d4b9d35ddbf0fe2ce69a2062cceb45a660                   m   \n",
       "3     19fef5a731de2db57d16da10287413f5f99bc2dd                   m   \n",
       "4     19fef5a731de2db57d16da10287413f5f99bc2dd                   m   \n",
       "...                                        ...                 ...   \n",
       "1306  0eb4ee5b3f47b20b049548a2fd1e7d4a2b70d0a7                   m   \n",
       "1307  0878a7d4b9d35ddbf0fe2ce69a2062cceb45a660                   m   \n",
       "1308  7f521ca403540f81ec99daec7da19c2788393880                   m   \n",
       "1309  724f04ad10ed31dbb9d260f0dfd221ba48be8a95                  ft   \n",
       "1310  7f521ca403540f81ec99daec7da19c2788393880                   m   \n",
       "\n",
       "     altitude_low_meters altitude_high_meters altitude_mean_meters  \n",
       "0                1950.00              2200.00              2075.00  \n",
       "1                1950.00              2200.00              2075.00  \n",
       "2                1600.00              1800.00              1700.00  \n",
       "3                1800.00              2200.00              2000.00  \n",
       "4                1950.00              2200.00              2075.00  \n",
       "...                  ...                  ...                  ...  \n",
       "1306              900.00               900.00               900.00  \n",
       "1307              350.00               350.00               350.00  \n",
       "1308             1100.00              1100.00              1100.00  \n",
       "1309             1417.32              1417.32              1417.32  \n",
       "1310             1400.00              1400.00              1400.00  \n",
       "\n",
       "[1311 rows x 44 columns]>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coffee_df.describe"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a531cc38",
   "metadata": {},
   "source": [
    "so lets check the type of that."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "f85a1704",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "method"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(coffee_df.describe)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16a30df9",
   "metadata": {},
   "source": [
    "it's a `bound method` or a function that *will* be applied to the DataFrame, but\n",
    "we didn't actually run the method.  To see that it hasn't run, we can use an\n",
    "ipython[^ipy] [magic `%%timeit`](https://ipython.readthedocs.io/en/stable/interactive/magics.html#magic-timeit)\n",
    "\n",
    "[^ipy]: the kernel of python we're using\n",
    "\n",
    "````{margin}\n",
    "```{admonition} Further reading\n",
    "The [magic functions](https://ipython.readthedocs.io/en/stable/interactive/magics.html#)\n",
    "can be defined for a cell or a line.\n",
    "[Timeit](https://docs.python.org/3/library/timeit.html)\n",
    "is actually a standard python library that you can call on the command line or in a python\n",
    "script as well, but juypter, by way of ipython gives us easy access to it with\n",
    "nice defaults.\n",
    "```\n",
    "````"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "05dc46f7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "74.8 ns ± 0.0775 ns per loop (mean ± std. dev. of 7 runs, 10,000,000 loops each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit\n",
    "coffee_df.describe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "28f89be7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "28.3 ms ± 288 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit\n",
    "coffee_df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eb648d45",
   "metadata": {},
   "source": [
    "Note that without the `()` it runs much much faster, signaling that it did less\n",
    "finding the method, is less calcuation than computing statistics on the data\n",
    "\n",
    "## Basic plots in pandas\n",
    "\n",
    "\n",
    "Pandas gives us basic plots."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "cb38f97d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "filenames": {
       "image/png": "/home/runner/work/BrownFall21/BrownFall21/_build/jupyter_execute/notes/2021-09-22_24_1.png"
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "coffee_df['Flavor'].plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0339cbe2",
   "metadata": {},
   "source": [
    "Since we chose a series, it plotted that data as line vs the index."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "915e8057",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RangeIndex(start=0, stop=1311, step=1)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coffee_df.index"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1736a0c9",
   "metadata": {},
   "source": [
    "We can change the kind, for example to a [Kernel Density Estimate](https://en.wikipedia.org/wiki/Kernel_density_estimation).\n",
    "This approximates the distribution of the data, you can think of it rougly like\n",
    "a smoothed out histogram."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "acb283ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Density'>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "filenames": {
       "image/png": "/home/runner/work/BrownFall21/BrownFall21/_build/jupyter_execute/notes/2021-09-22_28_1.png"
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "coffee_df['Flavor'].plot(kind='kde')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "957ef36a",
   "metadata": {},
   "source": [
    "We can also plot two variables as a scatter plot, by specifying the `x`, `y` and\n",
    "`kind`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "9f601ae6",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Flavor', ylabel='Balance'>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "filenames": {
       "image/png": "/home/runner/work/BrownFall21/BrownFall21/_build/jupyter_execute/notes/2021-09-22_30_2.png"
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "coffee_df.plot(x='Flavor',y='Balance', kind='scatter')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "108e6653",
   "metadata": {},
   "source": [
    "Let's Make a histogram plot of the Balance variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "88e8d12e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Frequency'>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "filenames": {
       "image/png": "/home/runner/work/BrownFall21/BrownFall21/_build/jupyter_execute/notes/2021-09-22_32_1.png"
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "coffee_df['Balance'].plot(kind='hist')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "432245d6",
   "metadata": {},
   "source": [
    "```{admonition} Question from class\n",
    "Can we plot two histograms with `coffee_df['Balance']['Flavor'].plot(kind='hist')`\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "a3557f79",
   "metadata": {},
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "invalid syntax (3818478052.py, line 1)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;36m  Input \u001b[0;32mIn [18]\u001b[0;36m\u001b[0m\n\u001b[0;31m    :tags: [\"raises-exception\"]\u001b[0m\n\u001b[0m    ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
     ]
    }
   ],
   "source": [
    ":tags: [\"raises-exception\"]\n",
    "\n",
    "coffee_df['Balance']['Flavor'].plot(kind='hist')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4da241d",
   "metadata": {},
   "source": [
    "Let's break down why that errors.  When we append things to the left, python\n",
    "interprets them by passing the output of one step to the input of the next one.  \n",
    "So `coffee_df['Balance'].plot(kind='hist')` first made a series, then plotted it.\n",
    "In the above, we again got the series, which works\n",
    "\n",
    "````{margin}\n",
    "```{note}\n",
    "Since I know these will be DataFrames, I'm appending the `head()` method to\n",
    "reduce the output for presenation.\n",
    "```\n",
    "````"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "9339c03e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    8.42\n",
       "1    8.42\n",
       "Name: Balance, dtype: float64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coffee_df['Balance'].head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7d91278",
   "metadata": {},
   "source": [
    "But then, we tried to index it with 'Flavor', but we don't have that any more"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "d4f05ca7",
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "'Flavor'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "Input \u001b[0;32mIn [20]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mcoffee_df\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mBalance\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mFlavor\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\n",
      "File \u001b[0;32m/opt/hostedtoolcache/Python/3.8.13/x64/lib/python3.8/site-packages/pandas/core/series.py:958\u001b[0m, in \u001b[0;36mSeries.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m    955\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_values[key]\n\u001b[1;32m    957\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m key_is_scalar:\n\u001b[0;32m--> 958\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_value\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    960\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_hashable(key):\n\u001b[1;32m    961\u001b[0m     \u001b[38;5;66;03m# Otherwise index.get_value will raise InvalidIndexError\u001b[39;00m\n\u001b[1;32m    962\u001b[0m     \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m    963\u001b[0m         \u001b[38;5;66;03m# For labels that don't resolve as scalars like tuples and frozensets\u001b[39;00m\n",
      "File \u001b[0;32m/opt/hostedtoolcache/Python/3.8.13/x64/lib/python3.8/site-packages/pandas/core/series.py:1069\u001b[0m, in \u001b[0;36mSeries._get_value\u001b[0;34m(self, label, takeable)\u001b[0m\n\u001b[1;32m   1066\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_values[label]\n\u001b[1;32m   1068\u001b[0m \u001b[38;5;66;03m# Similar to Index.get_value, but we do not fall back to positional\u001b[39;00m\n\u001b[0;32m-> 1069\u001b[0m loc \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mindex\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlabel\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1070\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mindex\u001b[38;5;241m.\u001b[39m_get_values_for_loc(\u001b[38;5;28mself\u001b[39m, loc, label)\n",
      "File \u001b[0;32m/opt/hostedtoolcache/Python/3.8.13/x64/lib/python3.8/site-packages/pandas/core/indexes/range.py:389\u001b[0m, in \u001b[0;36mRangeIndex.get_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m    387\u001b[0m             \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(key) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01merr\u001b[39;00m\n\u001b[1;32m    388\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_check_indexing_error(key)\n\u001b[0;32m--> 389\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(key)\n\u001b[1;32m    390\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28msuper\u001b[39m()\u001b[38;5;241m.\u001b[39mget_loc(key, method\u001b[38;5;241m=\u001b[39mmethod, tolerance\u001b[38;5;241m=\u001b[39mtolerance)\n",
      "\u001b[0;31mKeyError\u001b[0m: 'Flavor'"
     ]
    }
   ],
   "source": [
    "coffee_df['Balance']['Flavor']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dadca868",
   "metadata": {},
   "source": [
    "So  we get a key error and we know this is the part of the line we have to change.\n",
    "\n",
    "\n",
    "We need to index into the DataFrame and pick two columns at once. When we index,\n",
    "we can use the name of a variable as a string or a list.  We can buil this list\n",
    "on the fly and python exectues fromt he inside out.  \n",
    "The outer `[ ]` index and the inner `[ ]` make alist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "371dbb07",
   "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>Balance</th>\n",
       "      <th>Flavor</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8.42</td>\n",
       "      <td>8.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8.42</td>\n",
       "      <td>8.67</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Balance  Flavor\n",
       "0     8.42    8.83\n",
       "1     8.42    8.67"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coffee_df[['Balance','Flavor']].head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04f1905f",
   "metadata": {},
   "source": [
    "we could also build the list first, then index for readability"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "d480a387",
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'list' object has no attribute 'head'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "Input \u001b[0;32mIn [22]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0m hist_vars \u001b[38;5;241m=\u001b[39m \u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mBalance\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mFlavor\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mhead\u001b[49m(\u001b[38;5;241m2\u001b[39m)\n\u001b[1;32m      2\u001b[0m coffee_df[hist_vars]\n",
      "\u001b[0;31mAttributeError\u001b[0m: 'list' object has no attribute 'head'"
     ]
    }
   ],
   "source": [
    "hist_vars = ['Balance','Flavor'].head(2)\n",
    "coffee_df[hist_vars]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e1bc8509",
   "metadata": {},
   "source": [
    "This gives us a data frame, which we can plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "03f4d800",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Frequency'>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "filenames": {
       "image/png": "/home/runner/work/BrownFall21/BrownFall21/_build/jupyter_execute/notes/2021-09-22_44_1.png"
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "coffee_df[['Balance','Flavor']].plot(kind='hist')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "03a06fb0",
   "metadata": {},
   "source": [
    "We'll see ways to improve this on Friday.\n",
    "\n",
    "## Plotting in Python\n",
    "\n",
    "- [matplotlib](https://matplotlib.org/): low level plotting tools\n",
    "- [seaborn](https://seaborn.pydata.org/index.html): high level plotting with opinionated defaults\n",
    "- [ggplot](https://yhat.github.io/ggpy/): plotting based on the ggplot library in R.\n",
    "\n",
    "\n",
    "Pandas and seaborn use matplotlib under the hood.\n",
    "\n",
    "````{margin}\n",
    "```{admonition}  Think Ahead\n",
    "Learning ggplot is a way to earn level 3 for visualize\n",
    "```\n",
    "````\n",
    "Seaborn and ggplot both assume the data is set up as a DataFrame.\n",
    "Getting started with seaborn is the simplest, so we'll use that.\n",
    "\n",
    "\n",
    "\n",
    "We can get that basic plot back."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "f773af65",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Flavor', ylabel='Balance'>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "filenames": {
       "image/png": "/home/runner/work/BrownFall21/BrownFall21/_build/jupyter_execute/notes/2021-09-22_46_1.png"
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(data=coffee_df,x='Flavor',y='Balance')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c7e2b88",
   "metadata": {},
   "source": [
    "But now we have more power to investigate more relationships in the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "bc3a8aff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Flavor', ylabel='Balance'>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "filenames": {
       "image/png": "/home/runner/work/BrownFall21/BrownFall21/_build/jupyter_execute/notes/2021-09-22_48_1.png"
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(data=coffee_df,x='Flavor',y='Balance',hue='Color')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d8cbf391",
   "metadata": {},
   "source": [
    " From this we can see that the color doesn't appear to be related to the flavor\n",
    " or balance scores, but that the flavor and balacne are related.\n",
    "\n",
    "We can also break this apart. `lmplot` is a higher level plotting function so\n",
    "it allows us to create grids of plots and by default also includes a regression\n",
    "line. We'll turn that off for now, with `,fit_reg=False`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "368dc11f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7ff7d31776a0>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 4 Axes>"
      ]
     },
     "metadata": {
      "filenames": {
       "image/png": "/home/runner/work/BrownFall21/BrownFall21/_build/jupyter_execute/notes/2021-09-22_50_1.png"
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lmplot(data=coffee_df,x='Flavor',y='Balance',hue='Color',\n",
    "               col='Color',fit_reg=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "09b0f1c6",
   "metadata": {},
   "source": [
    "`col` stands for column.  We can also use `row`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "3ad8190b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7ff7d2d51fa0>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x1440 with 4 Axes>"
      ]
     },
     "metadata": {
      "filenames": {
       "image/png": "/home/runner/work/BrownFall21/BrownFall21/_build/jupyter_execute/notes/2021-09-22_52_1.png"
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lmplot(data=coffee_df,x='Flavor',y='Balance',hue='Color',\n",
    "               row='Color')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ebf6ad48",
   "metadata": {},
   "source": [
    "We can also use both together:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "f59e14eb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7ff7d27eefa0>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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uBy4F3+Xp0Tn+08ETzMYZ9ThVjENE5BoxBmajDGstH37yLAC7tvXRV/JXuWciIneeJeuAWA5NNnh2oo5r6Mx/K76z7HpiJXA79/aVfM2XRURuEOVkiIjcHBbG49RahrtDDDBSa1EJPH7lrdvZXC2SXawgqIiIiIiIiIjIKlmIaWQ2Z2tvgclmrBiziIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiI3Da81e4AwDPPPPMB4AOr3Q8Rkaux7+AIgWco+S7GMTBfUCkHXMcwVA5opjl/e2Kmc0/oGgbKPtWCj+vAQBCyZ8dGuoObYngWEbkl7Ds4QjnwSC3EWU7gOpQDj1qUXdFzanG7oHTBc+gueNSaKbVWekG7wAFjDPufm+Jn37CtfViL62AX1dHbta1fB4SLiMw7cHiCfQdHOF5rsalaYM+O4QvGyIu1+eg3z/AbnzvG0akmC8Pshu6Qf/iKDbz1rn5cxwDwuuEe3rC5ly29xSXjsYiIiIjIannfYydxDHiOA0DgQpxZzjZSTCPlaqetjoG+UkB3wWOykXBqJul8VvAcugOHiUZCkuW884OPs2fHMHt2DLN3/yEgo+i1D9eKU8ueHcNX2RsRkTvDcvGLPTuG+Yn/+SRzSU5uobvgMVAOCFzDN0fnqLVSskWDvmPgVC3Gdw2//Ja7V+9lRERERESuk30HR0hyy/hs0snhKHiG/+evn+eRzx/HsZYfevlauiab/M6jR2llOZuqRX70gXXKsxARWWTfwRHiLGOimROlOaHn0BU47Ds4whNn55bEnz1jSPOcD33jLD/2io2cmG7yyOePsf+59oEqXaHLQ9+6mbdtH2BLTwljVvPNRERuLStZX1u8j+S52Sbu/EA73ky5q68IZOw7ONKZ7y43Z66G3pI2IiJybSxey7urvwy094OUAo9mmnCiFjMbpcRZvrANsMM1UPAdAsfhl992D68arACwrivkkc8dBTKs9Whmyr0QEbkWzs/J+OnXbeLsXMyvfeYIFvAcw/qukCS3RLnV/FlE5CIutrd538ERZloxM3FOZtvzXQM4jqGe5JeMUSyOj6zvCjkzF/PseKOTC+0aCFyH07NxJ46tMVpE5IWLspwkzfjq6Vmen2wC8P0vXbPKvRIRuTOdP48GcICxRgLWUk/yTtvQgXsHy4xMN5mOcizt/SODRY/uYkDJdzl/3VBERK69xTkcgMZfEbnjraT22/WwXB70lu4CW3qLbK0WyFUkTkRkVa3W7wcRERERkZvdfzw4wsZqSK2VMRO1KHoOqfKWRUREROSOZ2nvQBERkRvh/LW8n9wxzFsUlxARERERERERERERERERERGRa8Rb7Q6IiNwujtda9BbaBe/i9FxBpa7Qo7vgcWam1SlkClD2HX75LXfxsW+OYl3DQMHn3S9fyxs29d3orouI3NKeHa8z3UpwjGkf5p3ljNWjK36OY6Ba8GkmGaNz8bJtSoHLUMmn6DtMNVP6Cj4AqqMnIrK8A4cn2Lv/EIFn6C24jNYj9u4/xMO76RTtWK7Nz//Fs2zsCTl4YqZzoKxroBK4/PRrN/H6zb1LvseY9oFbIiIiIiI3i7k4xV80R7WLggdXEkYwy7TvLngMlAPmopSjk43OnHlBPclJc+gv+QyUvEXz8O08vHs7+w6OMFJrMawi1CIiK3axGMerN3Qxl+R4jsNAuR1fPjLRuGDs9hyDtZb13SH1OMcojCEiIiIit6mFHA4DDJUDCr5LamGymZBmGVFm+ZW/eR5jDGXfYUN3yHjjwjVEEZE73TPjdWaiFEM7XyLJciaaOcl4/YL4szGwoTvEYth/aJxf/cxhxuoJADs2VvnFN25lsBxgFJAQEbliu7b18/BuLrm+tmQfSZbjmXY8OEpzAIqew0it1Wl/sbznJMtv7MuJiNwBHj89w1ySY2nnXjw3XgfAcOF6HrTn3m/e2seJWotaK2G4WuRHvmUdb7tvDbO1Jr7r8Na7B6gWfD785Bnm4pyBgstD37pFMQ0Rkatwfk7GVCtm7/5DHJ5qYgHfMbx4qEw5cJlupZR8d8kcW0RELu/rZ2aYjc/FHjo1LzKLIb9kjGLXtn5+bTf80TfO8IXj04w3kiWfB56Da8ySOLaIiLxw9SQnt/DhJ88C8NKhCi8arKxyr0RE7kznz6MBcqAeZxe0jXL4+tn2XNg17Tl3buFsI6UURHQXvAvWDUVE5NpbnMOxQOOviNypVlL77Xo5Pw+64Dm4jsPnj02T72y3sdZy8ESNzxyb5p+4Lvd1Bde1TyIi0raavx9ERERERG52UZZzotbi9PwZJS8ZKivGLCIiIiJ3LGOgFqUUPJfAWe3eiIjcGRbW8nwXekKHqWbMf3rsBKHvsHO49/IPEBERERERERERERERERERERG5DG+1OyAicrvYVC3w1NgctVZKDriOYbAcUI8zTi7alOgYMBZKvsvuewb5gZevZ+OabsbGZlev8yIit4hHHj3C+x47yVycUgk8Hnz1BuLMkuWQdI4lvHJl3yGzMNVMLvjMAD1Fn2rRw1poxhmnZlsUPU2lRUQu5sDhCfYdHOFLJ2s4xrC24mN8lzTLGa0n/P2PPcGaSsB4PaGR5jgGBks+YTmg1koZaySMzEZAe/48VAnoDlyiLOePv3GGN2zpxTGG0HMo+i4FzyF0HewL+zUgIiIiInLNVQKPuTjFYrH2hUUsDEvvC13Dmu4CeW45Md0iPu+A2cXtN/WElPz2IS3tnxn7Do7wsXc9oILTIiJXYCEmXYvSdvyi6FHqLnTG1j99aozegkdq4dRMtORezzGUfYcks2yohvQVfXpLPlONhMlmwr6DIxqTRUREROS2E2eWNG/HKE7Oxks+G28sbTvdgvFmyqs2dBF4RnNkEZFFksxircV12hWgDRBnOVPNlNxCK7MELgSuw9qugLkoZbwR80/+9zNA+9DuV6zv4vFTs7zjjx6n5Lv8/Veu55+/8a5VfCsRkVvTrm39l5ynbqoWGK1HlHyXwHVI59fwQs9hppVwZi4ht5Z3fvBx9uwYJs7aK3qOMZ2fubWd6yIicu2877GTOIAxhpGpc4GJxSOuAVwD1kJ/MeDXv2M7Jd8j9BwM7Tn3mr4yU/P5HwDfc+8gf+e+wfazNHyLiFy1fQdHCDxDyXdxgLkk5/BUE4CS77CuK2BtV8h0q73vr5FkDFcLq9hjEZFbw8L+vuO1FrNxO15xfm4yQGYtjjEXxCgW7j9bj+krenzjzBzNtP0c36GzJmiMIbPtGEea5ySKcYiIXAVLPUo5PRvx2WNTAHz/S9escp9ERO4Mi+fPm6oF9uwYppG057bLzaMvZWFKHLgOg2Uf13HwHMNMpJiGiMj1tjiHY0EzzTX+isgdafEaHCytOXG99m0szKsnGu2qoIFrqBY8+koBx6YauMYht5bPHpvmD756iqfH6wB8+ugkLx6ssGfHsPaUiIhcZ6vx+0FERERE5EZbbu3v/Pnu4vNOego+D75mA89PNpmcP6dkoOQTuobZWGt8IiIiInLnscBYPaYeZ6zrcmhn0YmIyPW27+AIxliOTEV0hR6vGa4y2Yz5/a+cYudw72p3T0RERERk1a1kHVBERERERERERERERC7NW+0OiIjcLtZVfB49ngJQCV0qgcfoXER+XvXSgmcYLIf0FX3WlgMddCUiskKPPHqERx49hmPAdwyNJOWRR49hLeQv8Jm+Y3AcQz258AkFz6Gn6FMOXGajlNMzEXnebpdbePDVG67ibUREbl8HDk+wd/8hAs+QzU92T87GNOKMqSjDAElmOV6LOvfkFqajjPFGncVnXDkGPAO9RZ/egkfBM0SZYX13gdB1cIwOjhURERGRm9Nb7+rlI98cu+C6Y7ggZnwxC80cA0OVkKLvMlaPmIuyy95b9JwL/n+k1lrZF4uICLA0Jg3t8ftsIwVaDJQD4izHGMNEM132/m29IQXPw3Md+osecZYz1UhopbnGZRERERG5beU2v6LDvhdojiwislTgGhoJ5NbiGEOaWzILrrEMlnxGGwmlwGOo7DM2FzHVOhc3fvmaCvcNlvjIE6PtvAsHWmnG/3jiLH1Fn/e8ZtMqvpmIyO1nz45h9u4/BGQMlnxOzLTntVXPMDLTzpHb2F1gtB6xd/8hctuOLVssnjEkucUYg++q6L+IyLU2F6d4BqJlEjVc0z5uxXcNfUWfroKH7zgMdxcvbOuYC/KVlb8sInLtHK+16C24YC2jzZST8/Po0DW8d9fdfPSbo5yaaWGAZpqTWcOeHcOr22kRkZvc4v19vQWXkVr7+nLT2DQHa3M8x3RiFAv39xZd0izniydmOu0dls6HA9fB0o5nt/9fMQ4RkRcqyiDOcj72zbPkFgZKPm/eokMKRUSut/PnzwvretkLDAQ7BvpKPpmFU/Nxjrv6CiQZimmIiFxni3M4ip5DM82JU6vxV0TuSJ01uEWu576NxfNqx0BmoRx4VAsex6YaxKml4Ft+5KNPcGSq2bmv7Du8aLDSmYc/vBsdRCsich3d6N8PIiIiIiI32sXW/hbHHBbXlqsELl0Fl1/7zNFOjdDu0OX+tWVOzcaKMYuIiIjIHSe1lrF6+3wpo+0hIiI31PFai6LnkFmYbqU8PTpHX9Hj9Gx0+ZtFRERERG5zK1kHFBERERERERERERGRy/NWuwMiIreLv3x+Ct8x9JV8ZqOMM+cl+xlgoBKwphyQpCkl39VhVyIiV+B9j52cP5DbAcAzhjTPSV7AWOqY9iGESWZh0WGGBuguePQUfQLXMNWIOVlLGCz5uAZSC5XA48FXb+ChnVuv0ZuJiNxe9h0cIfAMJd8l9NqHXBlgvJniOe0dijntMdcYKHguUZoRpXnnGQvFP/pLPqHnkOY5jjGM1hOqoU/Bbf8u0HxaRERERG5Wp+cS+goe01G6OPRwxbpDj4FKwHQzuSDmfD5j2ofKgqGZ5pT8cwWnm2nOcLXwwjsiInIHWhyTzmxObsFzDFNRxmijseQwcAO4DpQDh1LgU/ZdXjRU4UfuX8dv/e1xjk43NS6LiIiIyB3BMQ6uac+f+8sBcZqTWUvRc7hvsITrOhybajLTSukpeAyWAxxjNEcWETnPPQNljkw1qUUpSZaTW4troOi7bKiGrOsOmWgkPDfR6MSgfcfw46/ayLtetpa3//ev4Bgo+A49BZ+u0CPOcn7niyd4z2s2re7LiYjcZIyBqVaKMeA7Do5pj6meY1aUn7ZrWz8P727nzY3UWtzTX8Zay+GpFp7jsK4rpDt024d6+xYI6C26WOPQTDJOzUR0BQ7b+srX/V1FRO40lcCjHqf4jqFa8Ki1EvIcLDBY9in4LoHr0Eoy5qKUzT2l1e6yiMgdaVO1wNm5FtOtjPFGArTzL161ocr3v2wd67tCfnt+vj1cLfCLb72HVw1ozBYRuZTF+/sAXAPZJeIcmYWi63RiFPsOjtBb8jg61WK6lXbaLeTJQXvv32ApIAXG52I816EaemztLV6/FxMRuc01kpRmkvFnz4wB8I4XDeEvDLwiInLdnD9/bv/McI0BLJaV17XoKXg4jmGinnT2nDgGBkoh//h1m3SYlojIdXZ+DsdwtcCeHcMaf0XkjrSpWmC0Ht2wvc2L59VF36UrdPE9l+cnm7iOAQP1JOfIVBOA7tCl6Dts7C5QDl3qcXsevu/giMZtEZHr6Eb/fhARERERudEutva3OOawUFuuWvAp+S7Hplqdtb0fetkanh1v0ExhsBzyE2/eqFiFiIiIiNwxoswyWm8RpzoISkRkNSys5fUWPKZaKadmYwq+w72qgyEiIiIisqJ1QBERERERERERERERuTxvtTsgInIzO3B4gn0HRzhea7FpURG7xde7AhdrLRioFn1G52LOT7/uLfr0lnxmo5Qky2ilsGfHcOc5J2cjNnSFKpInIreVi42hL7T9XJziGIiyvFMY+oVsd/EcQ5pb8kWntQSuQ2/RoxJ6zMUZ43MR67tDyr7Hb33Xdo3NIiJX4HitRW+hndg3VA44OdMCa9uHZGXteXMlcHEdQz3OaCRZ517HwNpyQHfRw3cMJ2Yi6lHaPmXcQpxafvGN21bpzUREREREVubA4Qm+dHKGNM8xgAPk85/llwhmtI/EanMMrK8WsBaOTzVJL3XjPNe0n/+OFw3w2MlZIKPoOTTTnDi17NkxfFXvJSJyp5mLU3ynPToHrkOc5UvGYwNsqoaMNxL6Sj6VwKWR5MxEKf/otZt58FvWAxBnOXv3H0LjsoiIiIjcCQLX4Jh2bkbFdyiWfKZaKXGa0UwyZuZirLUM9xToDj0KnsNUM9EcWUTuOJfLlduzY5i9+w+xviug6Dk8OVbHNYbN1ZChSsipmYjRetyJOXuO4e6+Inf1FXEdg+catnQV8V2HWivh5EyLOM1JVhBrFhG5E81FKVHaXtEzBhxjcB0IXBfPMQSeg2fac10LuPN/d43BGPj2u/qXjOPGwK7f/xJ9RQ/PNXiOQyPOODUbUU9yalFClsNgOSDLLWmO5sMiItfBg6/ewCOPHsMxlsGyz3QzwQLf99IhTs7ExFlGkuVY6yg2ISKyin70gXX80//9LPX5vSXV0GVrb5Gf3DFM6Bjesq2ftyyabw8OdjE2Nrta3RURuSlcLsZ8vNbCxfL8bEyU5jjGkNlLx4fXdQXz8+KN/Iu/ep5j000WtmE7gOe0twZ2hR79RZ8os4w3YhpJxuaeIo5B82oRkas0F6V88rkJZqMM3zF874uGVrtLIiJ3hOO1FlGS8fxk85J7/y6l4DkUfZdaK7ngGeu7C4Sec/UdFRGRFdm1rV/14kREOJeLfC32Ni9Xf3kuyZf8fXQuolrwODMXUy34WCwnpttz7IWanwZ489ZefvSB9ez9y0NUQ3fJ9xQ9h5Fa6xq8vYiIXMy1/P0gIiIiInIzWlwbf8FCzGEhxlGLUqoFD8e02y8wwD9+7WZKgctgKcBzzA3uvYiIiIjI6qknGWP1mGw+Ae4LI9N85MmzJNYSOo7OVhURuQEW1vIGyj61KCXNLcemWgSOwzs/+LjGYhERERG5o11qHVBERERERERERERERFbOW+0OiIjcrA4cnmDv/kMEnqG34DJaj9i7/xA/+LIZPvSNswSewTVwvNakp+jTTDJqrXTJM8qBw2AlJE4tI9NN8txyT19Pp6jHwvP7Sn7n+Q/vRsmBInLLu9gYerExbiXtQ8+hkeQY2ofHXinXtA9XSRdVii4HLgPlAIDpZkKt1S6U5xjDUDlUwraIyAuwqVpgtB5R8l26Qxe6C5yZi+jyDSXfxQBjjaSzcRHaB2D1lQLKgUcrTknSjDD06Sn4NJP2weIal0VERETkVrAQ47DYzqGvK7E43lH0HNZ2h0w0EmbOizmfz3NMJ9ZR8j0efPUGHtq5tVNgb6TWYniZg21FROTSaq2ErtCjkWTEqeX8qHTRc9hYDfnlXds5NFHndx87yaGJBuX5sfhf7L6XsbFZoB3jfng3GpdFRERE5I5wz0CZI1NNalHK6bkI33UIHEOWw1g97cyHq91F/t1fP8dslNFT8Pmn37pFc2QRuWOsJFfu/HhCXyFguBrQXfT5+ulZTs/Fned1hy5ryz6NNOM/Hhyhr+Szrivk5EyLZFGgOrOWSqDtIyIil2Nte8zMcojTc2t1pvMfMBiMAceA5zgABK6DxZJbSHJLf8lnrB5hMIzXI8YaKQspc53R2cRYwOgsLBGR6+KhnVsB+M9fOkmaQyXw+IkdG/nHr93Mp49M8tsHRzg7l2j9TkRkFR2davLwZ45QTzIAegser9/Sy499yzresKlvlXsnInJzWkmMueI7HJps4Jp2PQwLOEC+6DkO4LmGOLMY2nv3/sEr1vOHXzvD4akm0N6X7ToGay2h57C2u8BAKeDpsTkacc5dfUWstTRzy1rt/RMRuSqtNCfOcj7y5FkAvv2uPvqK/ir3SkTkDmEto43kBd3qGiiHHvUopZXmF3zuGCh4DmOqLSciIiIiN9i12tu8OCbtGnh2og5AX8Hn9Gz7wNiNXSEWmIky1ncFjDcSZqJsyXNeub6Lh751C1t6iwCs7wqZaMZUFrVppjnD1cILfmcREbk81b4QERERkdvd4tr4C5ppTiVwz50NVfRIcstovb130NDOp+svBfSVfHoLytcQERERkTuJZaqVMtVMsPOFML4wMs0jnztKpeAyXC1wfLql/DcRkRtgYS3vd790gulWylg9Ic4sXeHlz4AVEREREbndXWwdULnHIiIiIiIiIiIiIiJXRicYiohcxL6DIwSe6SxKtn9mvO+xkwxVfMq+y2SaELoOJ2rRkns9B9Z0FXAdw9nZmOb84Sslz+Fj73oAgHd+8PHO840xnefvOziixEARueVdbAy92Bi3kvZ9BY9GEp879HWFHAO5hYWzvA3QU/TpK/nMxRlnZ6NOEent/UXi1PIfv+/lvGqg9ALeXERE9uwYZu/+Q3hOTl/RpxK6rKsEnJ6LOD7d6ozHC3qLPoNln4l6wivXlnns5CzO/MFYngNryoHGZRERERG5ZSzEOBxjgPaBsJeKZSzELRbaDJR9Qs9tz53zy0dBDBbXwL986z38xLes71zfta1fcWYRkSuUW8vnj0/zga+f5s+fGSfKlh4+aIBqwWNbb5H+csBkI+J3Dh7nwz/0AD/xquFLPlvjsoiIiIjcKRbWCtd3BRQ9h2aaE6eWh3dvXzInHhzs0vqfiNyxVppbtxBPyKzlwJEJ/uVfPscTo3XiRYkXPaHL2q6Q0HPYWPJJcssHvnaG77l3gEcePYZjwDWGzFpyCw++esONfl0RkduG7fwHLO0FvgxoxAmnZyNOzkacqLU4ORtxcibi0ESD0Xp8yWcmmeXegRKNRPtIRESul4d2buWhnVuZiVOMMXT5DmB4y7Z+3qJxV0RkVX3tzCw//OGvM95ICFzDe99yN3/nxUP0FTzaWRoiIrKclcSYjTk3jhrT3qfnONBf8JlsJktix66Bh3Zu5v613fz0J55mvJEAUHANA2Ufz0CKIXQdQscwXo/oDjz2ffe59b/BwS7GxmZv7D+EiMhtpp5kfPnULM9PNgH4/pesXeUeiYjcOSaa7Tnw5fYBLm5jgHLo0kxyZlrpBe1Cz6Gn6FMJXEq+gwECz2pNUERERERuqGuxt3lxTPq52SbufPx5vJngO+2/T7ZSBko+jSTn8FRryf1dgcvvveMlbOheerjsu+9fxyOfO0orzbAWGklGnFr27Lj0fm0REbl6qn0hIiIiIrezhXoXkC2pd+H5lsAzDJV9Ts9EzCXn6ss5QF8p4CdfN0xvwV+1vouIiIiI3Gg5lrFGwtyiHLiZKOW3vnCc6ShltJHQSnJ6iz46W1VE5MZYWMv70Y89wV89N05m4eh0i6FygMZiEREREbmTXWwdULnHIiIiIiIiIiIiIiJXxlvtDoiI3KyO11pEScbzk01yC45pbz5MLXiOpRV4nJqJyM6rWtpX8ukp+kw2Eqbni5s6BlwgyvIlz+8tuEvuLXoOI7WlBZtERG5FVzrGraS9cRxKLjSylfXBMZDb9p+F/+8vBVRCj+lmwpHJRuezBSdnIvqLPns+9g02dIXs2TGsZG0RkStgDHzbtj7+7dvu4Y++cYYjE3XSvL1J8cRMtKRtyXdZ0xXSSDLG5mJ+/FUbeGjnVg4cnmDfwRFGai2GqwX27Bjm7S9ao0OwREREROSWsBDjyKzFAfJLtPUcQzofnHAMbKwWmI0yTl5BjLjkezz46g380u57NWcWEXmBTsy0+PXPHuF/PTNGI1k6chvAd6Cr0F7/Cx1wHBidi7DWcrSudT0RERERkcV2bevn4d1csN6n3AsRkXNWlCtnoJVa5uKUWivhqydnOTETkczHlAdLPkmWs64roLfk0xV6zEYpc1HKdKvFB77vZQC877GTzMUplaAdS35o59Yb96IiIreAA4cn+IOvnuLwVJPTMxG+a9jaW+Td96/jdcM9nXaNJOPUTMRfH5ngL5+bZLKZ4DkG3zVMt9IL8pEvJnQNcWZxDPiOYW0lALSPRETkelrIS64nGd2hx0+8eqPiFCIiq2hhXD482WC0npBZS3fo8hvfcQ9v3NpHf9HHrnB+LSJyp7pUjHlhnH1mvI7vOlhryazFdx3WlXxyC+/Y0sOfPDVOkrdjFAMlj//21dOM1o8B7ZzmSuBS9g3Wgud7RHFKbHOSzGr9T0TkOrBAPUr5yJNnASj7Dr/4V4co+y4WSyPJWd8V8qMPrOcdLy6sbmdFRG4jez7+JH/y1DjZfDBiJSEJCxR9lzjLmYuWFkBygO0DRSyGOLfMNFMaWHqKRdI005qgiIiIiNySFsek4yzHAElmMQZc16HkOSS55fRsvGRO7TkwUPCIcnj4M0c4NRuxvivs5Oa9briHh16/hT99apSpVsJQWXU/RUREREREROTqXazexS/sP8T6roAvn5qjlZ6rM+ca2Fgt8ta7ennwVcOr2HMRERERkRsryXNG6wmtJOPsXMRnj03z2WNTfOXUbCenDqCR5PQWVRNDRORGG28kDJV9Ts8lZPOFjTQWi4iIiMidTHXvRURERERERERERESuDW+1OyAictOyltFG0vnf3IIzf8jgbJQyUYuWNA9dw9ruAklmOTbV7CT7tT9zSPOcin9u2N1ULTBajyj55w4YaKY5w1UVmxaRW9+VjnEraW/znEa23N1LOaY9Zi8Mw55jGCj7+K7LVDNmrB4vfx/twnqn5yI29xQZrUfs3X+Ih3ejhBQRkctIcstcktFKMqI0Z1N3gd3b+vjPk02+OTa7pG3Bgw1dBTCGM3MtNnUX+NR7Xtf5fNe2fo27IiIiInLLWohxWGvJL9LGNWCMIZ0PXgSuYV13gbOz0ZKCeCvx7M+8/ip7LCJyZ2qlGR9/eow/+sYZvnB8etmDCn2gvxJQCT2KLiQ5+K5DkrVba11PRERERGR5Wu8TEbm0i+XKbekpYOf/PtNKaSQpZ2Yj/s2nj/ClUzMArCkH/PM3beVVG6r83CefxXENDpbRuYjcLo1XPLRzKw/t3Loarygicks4cHiCvfsPUfANc1FKM8loJvDcZIP/56+f596BMnGWc3ImYqKZXP6B5yn5DuXAAWuoBC45lqLncqzWIs1yXMdQmP9doHiziMj1sTDWB56h6Dmcnm1pj4iIyCpaGJczm3NmLsbSzqV7z45h3rStn76Ch10ugUNERJa4WIy5Erid+W/oOSRZjjGGDV0B3QWfRpLhOw6PnZxlW1+7JsZ4M2aqmZHkaedZPaFLfynAGkMjybBZ+9lxanl493bNpUVEroNmmjNSa/GZo1MAFH0H18DR6SYAa8s+E82Y3/z8UdZ1h7x5S99qdldE5Law5+NP8pFvjl3RPYFryCw0k6XFjzwHeksBd/cW+ei7HsA1hnd+8HF8g2rLiYiIiMgt7+6+IuONmK7QY20lwGLwXYc8zxlvJIw3Lsytu7uviOcYJpsJUZZRT1LWdwVkWN7/tVP0FH12bKzyXfcO8r0vXsOWtVUmJuZW4e1ERERERERE5Ha0XL2LDd0jHDwx3Tm7xDXQFbqs7y5Q8Ax/+dwkb9k2ofw4EREREbkjNJOMzx+f5m+OTPLZY1M8Pd5Y8rkBugseG7tDfMd06iEp/01E5MZZ3xXgmJy7B8rMtlKNxSIiIiIiqO69iIiIiIiIiIiIiMi14K12B0REbgYHDk+w7+AIx2stNlUL7NkxvOSQQsdAb9HHcQxnZyPOP0NlqBJQDjzG6hFzUcb50jwnt/Dgqzd0ru3ZMcze/YeAjC7XoZFkxKllz47h6/SWIiI3zuIxrug5NNP8kmPcStpPttJl713gGMgtnc3jnmMYqgRYYKqR0ErjS96fA74xAIzWY7b1FoGMfQdHlKAiInIZzTTjz58e5QNfO82x6SZxZpmNz82LK4FLM87oKQX0FT1mWgnTrZTMWsz82CsiIiIicitZLqa8a1s/e3YM8zOfeJo0X/6+cuC2D4OdD2BUCx6VwGVkutmJaaxUNXQv30hE5DZ0sTH4cqy1fOnUDH/09TN8/JlRZhet6RlYsv7XW/TpK/nEScaJWhPHGAZLAZm1K4p5i4iIiIiIiIhczPm5cpmFrsDjJ3YMc2KmSZJacmv57YMjfOiJM53Y8avWd/Orb72bSuDx9bOzhL7DF45PYy2sKfv4nqN4hYjIFdh3cASwHJmKSDLbiRHPzMeOv3Rq5oJ7DBC47QO8A7ed9zbVTHEA14EkPxdrbiU53QWP2SijmbUXD6uBZVN3yOm5mMBziTPLsakmlcDll99y93V9XxGRO9G+gyMEnqHkt/Mr2j+1R0RE5EZYLrfjt//2OHGec3q2vccvdA3D1ZBnxhv0hh72CvPnRETuVBfbj+35tjP/XVMJOTLVBCxHpiMgoujClt4S4/UW9RRKvkMjOZfw7DkGB0sp9IktjM1GxFlGwXO5q0/7rUVErtbFt1Ib6nHKR795Fgu4BvqLPsdnIpz5ezIMGyshGZY//sZZ3ryl7wb1WkTk9rA4ToG1TDSTJXPhy3GNAQNxtjR4UQoceosBoedQa6Y8MTrHp45Msu/gCM+M15mNMvpLPmu7VVtORERERG5uC3GL3EJmLWne/pPklh97xQb+wxeO00ozWmlOrZUuybdbzDFQCT0GSn472c4YNvU4VAs+dv65M1HKH33tNN99z+C5+xzVoBMRERERERGR6+Nvjkzwrz99hCfOzgHt+IXvQF8xoBK6ZLklyw2BZ5QfJyIiIiK3lfP39/2j12ykO/T406dG+eShCU7ORkvad4cuOzf18MbNvfSUfP7Ll04wG6W4RjWYRURWw7sfWMdvfPoIZ5qR6uGLiIiIiIiIiIiIiIiIiIiIyDXjrXYHRERW24HDE+zdf4jAM/QWXEbrEXv3H+oUKe0ueFQLHmdnowuKkBY8h3XdBepxytGpxpIDVgznDi8s+R4PvnoDD+3c2vl817Z+Ht7dPkzr5FzEhkrInh3D2tQoIreFxWPcSK3F8PxBVRcb41bS/mLFox3TLpi3cNC35xiGKgGZhbF6TJKt/PQrxxistURp+7uKnsNIrbXi+0VE7lRfOjXDr336MHNpTnPReD1Y9skzS3/FJ80hznKOTDWx1lLwXdaVfObibBV7LiIiIiJy5S4WU354d/vz5Q7iLgcOnuNQa6Wda2u7QjJrOTkTXXjDZZQ8Q7Xgv9BXEBG5ZV1qDF4u/myBkzMR/+OJM3zsm2c5NNHofOYaw85NPRw8MUU0H54oBS5DlYAozTk21cR3DFiIspyHd29fccxbRERERERERORidm3r59e/A37/K6eoRSmD5YC3be9nS7VInFommwl7//IQ35g/TMU10Ff0ODXT4htn5+gKPX7vyyepRQlD5YAzczEjMxH39Jf45d13K14hIrJCx2ststxesEcEoOAZwPBDL1vLxu6Qjd0FfunAc/QWXBzH6bSz1jLZTHEdKPguRWMo+C4Fz8F3HdI8x3UcstziGMgsxLmlWvCwFmZbCZZzB4iLiMi1dbzWorfgLrmmPSIiItffcrkdv/DJZ5mJM6bn8+dKvsM9AyXWlAOeODO3yj0WEbm1XGw/9s/vP9SZ/07WL8xNbmbw1HiD0HMIXHvBnu2+ok+l4DHZSJhuJp1aGa2knVynubSIyAtnDJyai4mT5fdTz8Upf/b0GAC9BQ9jDEmW4xqDa6Cn6BN6DtZanh7T/FlE5EosjlNEScZoI1nxvcaAA2TWniskB3SHHv3lgCTLmW4lNOIMd34tcOG71ncFjDkxE42EzFru7itpD4qIiIiIrCpjIM8htTlZDqm1JLklyyxxnpPl7evt6a/t1My4p6/ED798Lf/lSycYqy8/n/Yc6C+HlAOXRpwxl+QMlQMOTzYJnIDxetxpa61dstdbREREREREROR6OfD8OD/9iWcZa7RjE55j8AwMdhXwjCXLoRS29woqP05EREREbicLeXO+C66xfOPsLP/nR58kPa9w/tpKwBu39PLGzb28fG0XgWvoKQX0hi7V0FMNZhGRVfRtm/vIX281FouIiIiIiIiIiIiIiIiIiIjINeWtdgdERFbbvoMjBJ6h5LcL+rd/ZhQ8h8FKQK2VMjJ94WbDoUpAOfAYnYuox+eKTBvAMfDSNRUaScZQOeRj73pg2e/eta2fXdv6GRzsYmxs9jq8nYjI6lkY465He8eAMYYst+Tze2M8xzBYCQAYq8ckyxxIu5yFQ1gA8vmNNqHX3nDeTHOGq4UVv4OIyJ3o6FSTn/uLZxlrpp1roWvoLrg044x7BssMlgMePz3LdDPBNeB7Lnf1FTvzZRERERGRW8nFYsr7Do4A0FP0GJs/DCv0HPpLAZONmHrcnjM7Bjb2FJlqJMxG6bLfcSn3r61oLi0id6xLjcG7tvVjDMRZzlySc+C5CT7y5Bk+e2yaND8XL97aU+S77x3gO7YP0Ff0ef3vfhHXMQxVAgLXYXQupjG/9uc7hsxaKoF3xTFvEREREREREZHzGQOt1PLA+iq/2l8mznIW14b+9NEpfv2zR5hutWPHlcBlbSXAcwxxlvM3R6YAy1QroeS7FDyoFjwaSUZfKVDsQkTkCmyqFjgz16Kn4GGwzMUZ1oLvOQyVffqLAf/3qzZ22g9XC0w0Y4rtFGMM4HkO67tCKqGLtTAbZzSTjOlGQpTlnRxlx0DoOqR5Tm4N2/oKnTg3QCM5F+cWEZFrZ1O1wGg9WjLmao+IiMj1d35uR9l3mWwmnXhHV+Byz0CJgXLAyHSTofn9gCIisnLL5bJtqo505r+1OF/ymZn/WQld5qKMxbuvy4HDUKVAK8k4NtXEWotj6MSuF9pqLi0icnWyPF+Sz7zYXxyaYDbOMEDBbwehfdchzXIC18FaS62Vah+JiMgLsDhO8fxkE1haZ+hiHAO5hYWqcgaoFn36Sj71OONkrUWctefdRa+9DmgwS2IiQ5WQSpixsafEH3/fy67L+4mIiIiIrESS54zO1+a01mLt5efEC54eq/Pxp8d4arxxwWeugcFKSClwmWokjM1FGAxfe8/rAHjnBx9X3oaIiIiIiIiIrIrResSeP3+aqfma+d2hy9beAj3FgMMTDTzfUcxCRERERG5bC3lzs1HGmbl4yWfb+0q8YUsPb9zSy/a+Esa0d5y0z/0LKc2f2acazCIiq09jsYiIiIiIiIiIiIiIiIiIiIhca95qd0BEZLUdr7WIkoznJ5vkFnzXcE9fib6Sz8lai/PrR5cClzWVkHqccnSqseTgWThXyGmsnjDRSJhqprzzg4+zZ8ewkgBF5KZx4PAE+w6OcLzWYlO1cMVj1NXefyXPWWgDELiG3NIu7j8/AC8Uv3Mdw3g9JkrzC77nYhxgoXU1cKjP3ztUDmgkGXFq2bNj+IrfS0TkTtFMMr7z/V9hopkA7XF6oOTTFbgUfYfZ2NIduozOtYuQTjUTsJYozTXOioiIiMgt63itRW/BXXKt6DmM1FpY2rGK0HPoKfp4xnBqptWJGxc8hzVdAadnos4hV1dKc2kRuZOdPwYXPIfu0CXOLVNRylNnZ/nTp8b482fHGG8knXZl3+Wtd/Xx3fcO8qLBcqfAErQPIewt+Uw3E07PREu+L81zcgsPvnrD9X85EREREREREbmNWWpRxmyUEmf5BbnHc3HKb37+OJ84NA6AAXpCl1aWc3SqSSX0eNFgmaNTDWpRhmvgudkmcZYTuA6DJZ+RWuvGv5aIyC1sz45h9u4/xJqKz2yUMRtlAHQFLklqeff965a0f/f96/hXf30IYxy6Qp+S75AkGbu29fKhJ85i508FTxaN8Qt/dc3CT0OSW4rzRf8XLKw1iojItbUw1kNG0XNoprnyLUREboDjtRYuludnY6y1WKCRtHPlyr7D5t6Q/pLPyHSTepzzL96scVlEZCUW78fGWiaaCVGaUwk8Hnz1hiXz3/OVQ5c0s534B7TjFWu6Cviu4fRMi9b8/mrPgDHnYhzWwuhcxGQzY1p1M0RErjlrLR958iwAr1zfzamZFs00o6/gcWYuxhhDd+AyHaWKa4iILGPxPNnmOZOtlCjNCT2H/qLPqdmI0HNYUwk7deTsJZ7nGMgtnbaOgd6iT7XoMxulHJtqki0qSOcaiLOczLaffHy6hTGGzNpOPseRqcb1en0RERERkRWL0/yC2sqX8kdfP81/f/wUM9GFMWdoz5N7Sz5TjYSzc1EnN/r7XjzQaaO8DRERERERERFZDV87M8uPfvQbTDVTAAZKPlt7CvSVAybqMa00xzEGxSxERERE5Ha1ULu5leZ4jqEcuISOwQJ/8HdfekH7gu8yVPHxjXPhw0RERERERERERERERERERERERETktqFMQRERaxltJFigvxSwobvA81NNTs1EFxRoWtMVMlQJODMbMToXX3AA7aJHMtFI6Cu6rO8KGK1H7N1/iAOHJ67764iIXM7/fuose/cfYrQe0Vtwr3iMOnB44qruv5LnHDg8wS/uf5aTs0181xBnlnR+cHYMDFUCNvQUqbVSTtZaRPMHrFyKAQIHQtdgDJR8h41dAdViwD39Zbb3lciAoXLIw7u36xAWEZFL8F3Dpp4CXYFLf9Fja0+BnoLHYCWkWvSpxykn5+fV3aHLhu4CjuPgGKNxVkRERERuWZuqBZrnxSCaac5wtT03noszNvcUaMQpJ2danUOxeos+/eWAkekWcXb5GMZyDIpZiMidbWEM9hzDxmqBcuAy3UoZn4v5wQ8+zjs++DX+4PFTjDcSAF6xrot/9W3b+Pjfe4Cfe8NWXjxUwRgDtA/p7ip4rCkHnKo1mW4mGNpj7YKS7/HQzs08tHPrjX9ZEREREREREbltWGuYaiZEaX5B7vGXTtb4kY88wScOjQPw6g3dDFdDZuKMNLf0Fj3WVgKeGp8jyy1dgcuJmRZpluMZQ5rlnJhpUQncVXgzEZFb165t/Ty8eztbekqUA4+C59IVemzsLvDQ67fwuuGeTlvHGE7PtVjbVaQr9JmNUp6fbHB4qsW6rpCfed0mSr5HDpQ8h03VsBNv9h3wnPb2vcxaXGMuutYoIiLX1sJYP1QOmW5lyrcQEblBKr7DidmI0DUkuaWRtOe/fUWPX9t9D9v7u3huoklvMdC4LCKyQov3Y0dJxshMRCPJcQw0kpRHHj3G46dnOvPfBQXPob/sU48yWoviEV2hy+a+Es0k49hUc8lnbYaC5+A77b3ck82M/pLPOtXNEBG55r58apbDU00A9uwY5qHXb6G/GJBb2NJTZGtvkdRqH4mIyHKWzpNTTszGnThEI8kZmYlwDCRZzsmZ1pK9Iudz5j9cqDfnGBgsB2zuLZFZODrZYGwuJptvsFC3yM7f01fwKHgOUWZppTkGOvkc3aF33f4NRERERESuJWstXzxR4+995Bv89sERZqIMAN8x9IbtPGXPMQz3FCkFLsenmkw1E6wF1xi+78WD7Puel3Sep7wNEREREREREbnR/uSpUb73A1/lzFzcXvMredw3WKa3HDBej6lFKfcMlBWzEBEREZHb2kLt5r6iz85NVe4bKFEMnAtqWhjadZnXdQX4Rkdai4iIiIiIiIiIiIiIiIiIiIiIiNzuVBVPRO4oBw5PsO/gCMdrLTZVC+zZMcxEM6G74NFfCphsxBydii+4rxS4rKmE1OOUY1PNJYfPek672JJjDLm1ZNYSuA4bukNKfrtIU/tnxr6DI9q4KCKr7t996nkCz7zgMWrfwZGrun8lzwH4z4+N8PWzdebilDhbeup3X8mnWvAZr8eMzl04bi/n/rUVGkl7I/nH3vXAJdsODnYxNja74ncREblTffroFCXf5b6hMo+fmqUrdNneU2Y6ShidTvjRB9bxoW+cBTKKnoPnwJqyDikUERERkVvL+XHlnZuqS+a5zTQnTi0//bpN/M5jI0y2Ep6baHQOvAJY1x2SZJaTtdYVf78DuE77MKyHdm7moZ1br9m7iYjcavbsGGbv/kNEbsapmRbPTjRoxDmLI8hrygHfde8A37l9kPXd4bLPCTxDfymk7Dv8nfsGeOTRY7gGXMeQWasxV0RERERERESuu1aa8R8PjvCRb44CELoOP7ljmHe8eIgf++gTAKypBBR9j5FaiyjLMRWDXZTEfLG/i4jIyuza1s+339XfHmfTfMlnxkDgOjw9UedD3zjDp49MMROlWNsu5G8MYOF9j53k2Z95fSeevLC2WGul1KKMLAfX2E7s+R0vGuCxk7Ocv9a4Z8fwDX9/EZE7wa5t/cpZFhG5QRbmws9PNekp+kw1Eha2BBpgfVfId983xA+8dO2q9lNE5Fa0eD/285NNoD22ZhYc0855+7efO0Y19Hjw1Rs4eKJGX8mnHmdM1JPOcxwDa7sKeK5hZLpJsmjvduAa4sySAy8dLHViFuXAJclz1c0QEblOPvLkWQBevqbCvQNlAF433NP53HMMW3qLaClQRORCi+fJh+fnyQCLSxQl+fzaHpbzh1LDufn0wj5A18BAOaQYOEw2EsYmGxd870DJ48mfej0A7/zg4xyerDMb57QWrTcu1ElyAA3iIiIiInKzy63lc8em+YPHT/HUWL1zveA59Bc9KoFLK8sJPIdywWeiHlNrpZ12O4e7+dgPv2LZZytvQ0RERERERERuBGtzfu1zx/jNzx8DYG0l4O/dv45PH50mt5azMy0ai/bxKWYhIiIiIrezhdrNkFENXZppRpJa3n3/uk4bx0BvKaAndGln04mIiIiIiIiIiIiIiIiIiIiIiIjI7c5b7Q6IiNwoBw5PsHf/IQLP0FtwGa1HvPdvDjNYCUmznGOTDfJl7huqBJQClzOzEc0k61yfP6+Qjd0FxhoJSZbjuw7rSj4jtRZFz1nynKLnMFJrXdd3FBFZiSOTDbqDFz5GHa+16C24L/j+yz3n1EyLXzrwHKdmIprnHSZbLXj0lwNqzZSjU40rrvGssVhE5NpZPL++u7/EfUMVWknGN8fqbOkp8vDuLeza1s8D67rZd3CEkVqL4WqhU+BDRERERORWsFxc+UPfOMsPvmwNjx6vMVJrcVdfkffsGOa+wQqPn64x2TwXz3ANbOwpMtGImYuyS3zThULXYK0ls1Dy2wfSPrRz67V+RRGRW8qubf383BsSfn7/Iebic+Nq4BreuKWX775nkFeu78Z1li+e5BioFn16Ch4OBmvpjK3ve+wkc3FKJdCYKyIiIiIiIiLX1xNn5/jXnz7M8flctpcMlfmXb76L4WoBgHqS8ZKhCs0s5/h0E89x2NhdYC7O2rnLXSHjzZQozQk9h3VFj3qyXBa0iIhcCQN4rqESepR9j4MjU/zS/udwXZYc2G2hk8M8E527vnhtcXNPgRMzEVPNlCizdIfnYs8HDk8op05EREREbiuL58J9RZ+zczEL2/4C17Clp0B3wad03r5rERFZmcX7sfNF+6pzC/mijdatNOW/ffU0A+WAs7MRi7dgFzyH9dUC082EyZnkgu9wjcF3LEkO062sE7P4+f2HrsmechERudCpmYjPHZ8C4PtfsmbZNhfLiRYRkaXz5OwS9YdcB7JFKRWOAccY0tySzc+nXQMDlZDQc5hsxJydW34fYDV0KPnnSnc+M15nJkovevx3DhybalzJa4mIiIiI3DBZbvnrI5P898dP8fxks3Pddwxryj7lwMWY9mx3TTkgtfDceJ2Z+NwEO3Rgz2s33/C+i4iIiIiIiIgsqCcp7/n40/zFoXEA7l9T4Vd3b+eu/jI7Nlb5zS8cZ2pRTpz28YmIiIjI7W7Xtn4e3g37Do5Qi1L6igE/9sAGXjfcA4DnGAYrofb6iYiIiIiIiIiIiIiIiIiIiIiIiNxhvMs3ERFZXQuH+x2vtdh0FZsC9x0cIckt47Ptgvz9RZ/EZJyajUiWqWAauA7rukNaac6xqSaLav9T9BzSPCe3Bt813N1X7HzWSDIqgUczzSn554r5N9O8czCtiMhq2tpX4sR04wWPUZuqBUbr0VWPcZuqBY5MNanNH/zaE7pkFsYaCVm+dFwu+g5ruwo0koxjU80LPl+JZ8Yb5NZiMLzzg49rk7mIyFXad3CEwDOUfBfXMfQWXE4nKVt6inzsXQ902u3a1q/xVkRERERuWYvnvcD8z4wPfv0MjSQn9BzGGwl/9PgpvjnWYLJ5rlh/0XcYqgScnomIF5+SdQkLseeS7/Hsz7z+erySiMgtb20lZC5uHyZ470CJ7753kLfe1U93eOn0h4LvMlAKCN0LjxZ8aOdWHtq59br0V0RERERERETuXAs50HNxhmNguhkzWk+oJ+2YsecY/q9XbuCHX74OzzkXs3jJUIUoz3FaKfcNlIF2fvJQOQRgtB5x13m5ywufiYjIlXMdh0roUAlcSr7Lwoj8m184juuyJGd6gQEs4Jhz4/f5a4vD1QL9pfYYrZw6EREREbmdLcyF48xydi5m8c6/7tCjp+gTLJOvISIiK7N4X7dj4Pwt1p5j6C359BU8RmotGsnSvOW+ok+16HN6JqKZZBf9ntyCa8yScfxa7SkXEZELfeyps+QWBss+b9rau2wbz9HBsiIi51vIxRidizgza3GdS8cc0vnpsT/fLskt+XwxOcfAYCUk9Bwm6jFnZy8+X75/beWC/Iwks1hrcR0HWDpRX1hPrCdXXiNJREREROR6SvOcvzg0wfsfP8XITNS5/rrhKj/6wHp+90snGKk1mZxJidOc4d4imbUcnYpY0xWydVG8uJFk7Ds4onw4EREREREREbkhFp9dtbW3yA+/fB2/9YVjfHOsDsB33TPArm19/NevnOQbZ+YYKgc6j0RERERE7kiLa1ocnT531l/Bdxkq+/jKURYRERERERERERERERERERERERG54yh7UERuagcOT7B3/yFG6xG9BZfResTe/Yc4cHjiip/17HidqWZMb8FjqBIy0Uw4Ot0iyS4sEFoteGzsKTDZSDg7G2HPa5LmObmFd7xogDi1NJIMa9s/49Ty4Ks3LHt9z47hF/pPISJyzfzsm++6qjFqz47hazLG7dxUpZ6kDBQ9Kr7L6bmYM3NxZ8MLgOfAhmqBwUrI6ZkWZ2ejJZ9fiVaaE2eWauhc1e8TERFpO15rUfTaYYWR6Ra1VkrRcxiptVa5ZyIiIiIi187iee+C2VZKM7P0l32yPOfJs3P8ydPjPDPR6LTpK/n0lQJGplvEWX7+Yy9q4fAsHfYtInJxr9/cy0d+6H4++kP38/vveCl/98Vr6A69i7Z3HcNAJWB9V0io8VVEREREREREbpDFOdCugcNTTY5MR9STdszYcww//dpN/OgD6/GcczGLgu/yE6/ZyImpFvVlcvSuVf6eiIi0WQtDZZ+1lYCy77I4irx4rfBi4eVK4CzbfoFy6kRERETkTnC81qLgGk7UWize+Re4Dn0lnyfPzvGaDd2r1j8RkVvd4rjwQNEHwAKOgaFKwKbeIkmS8+x4g0ZyLm/ZMbCxWqDguxybatBMsot+R5zlZBa6A7OkrsfOTVXFpEVEroNmkvHxp8cAeMeL1uBd5BBZ1+GCmkciIneyxbkY1dAjyaGVXnqgLPgOoeuQ5JZkvmaRMTBYDhjuKTIXpRyfalKPLz5fBpadCy/sAcwvMVhf6jMRERERkRspSnM++s2zfP+Hvs6vfuYIIzMRAG/e0svv/R8v4ZG33cv9a7t4xfouJhopSZYz3FMgzXIePz1HkmXKjxMRERERERGRVbN4rXBDV8BcnPKT/+spvjlWxzHwj1+7ibff089HvjnK06NzFD2j80hEREREROYZoLvgsb4rxL9I3rKIiIiIiIiIiIiIiIiIiIiIiIiI3N6UQSgiN7V9B0cIPEPJdzGm/TPwDPsOjlzxs7oLHsM9RepxxpHJxrIFRx0D67sLdBd8RqabzEbpss8q+R4P7dzMvu95CQ/v3s5QOWS6lTFUDnl493Ye2rl12eu7tvVfcb9FRK61t79ozVWNUbu29V/1GGeBZyebdAUeJ2YiztZj8vPqNfeVfDb1lqjHGcenmrTSfNlnrZQBPAON1F7V7xMREWnbVC3QPG9sbqY5w9XCKvVIREREROTaO3/eWwlcygUfx8CJWoupZsL5EYv11RDHGE7WWhfEOy7GzP/xXIfBcsg9A+Vr9QoiIrelN2zuvexYaYBS4LKhGlINPMyN6ZqIiIiIiIiICHAuB7roORyealJrnctJ7it6rO/y+Zsjk0vuCT2HNZWAN27u41cvkqN3LfL3RERkKdcY7DLreovXCgu+i7so0OyY9nj+0jVdy7ZfoJw6EREREbkTbKoWaGWW/pJPT9HDM+A5hg3VArVWSrXg8+jx2mp3U0TklrU4LlzwXbZUCwxXQ7b0lchyy5GJBtNRykJ4wwDdvsOWvvYe7VMzK8lpNvSGDpt6S0vqejx6vKaYtIjIdfDJ5yaYjTMC1/C99w1etJ3nKANaRGSxxfXoGmmO57DsXhFjoBy4hJ5DK8mJsvYanqFdz2hLb4koyzk21Vy2Dt0Fz4Nl58L3DJQZLId47oXlPI0B10B36L3AtxURERERuTbqccYHvnaa7/vjr/HIo8c4OxfjGNh9dz9/+Hdfyq++dTv3DZ7bs/2VU7MMVXy29peJs5zJZsqaSohjHOXHiYiIiIiIiMiqWVgrXN8dMpdkfPXULGlucQz8xnfcw499ywb+6vAUk40Y33Wu+nwrEREREZHbhesY+isBgyVftZlFRERERERERERERERERERERERE7mCqiiciN7XjtRa9BXfJtaLnMFJrrfgZ1sJs0j409shkgyRfvl3Rd1nbFTLTSploxMu2McBAyeeJn9rZubZwmOz5LnZ9sQOHJ9h3cISTsxEbukL27BhWsX8RuSFWMkZdy/sPHJ7g9796iulWwrqukGro8fGnR8mWGZOLvstQJSCeLxSdXf5UlYsy0DmwpeA5WGuJ5gvnXenvExERWWrPjmH27j8EZBS9dmHSOLXs2TG82l0TEREREblmFua9lRCGSgFTrZTj003SzHJ+xMJzDBurBcYbMXPRxQ++8g0k8zcbYOF8q43dBXzXaF4tInINeI6hrxzQ5Tssf5yhiIiIiIiIiMj1tZADPVpPmG6lnesuMFQOsNZyejbqXA88w1AlwDPtWMalcvSuNv9PRERWZnGO3GDJ58RMhmdgY1eI7zkXrOspp05ERERE7lQLc+FqwcMYQyvJ2NBdoOxDd9COg2gfn4jI1VmIC+dY5uKMWivhNz57hA89MXpB23XdAWXf48xsi1Z6LuPZAc7f1m2Af/b6zXzwG2cvWtdDMWkRkWvLWsuHnzwLwLff1U9v0b9oW8dRHrSIyGKL69FFaY5nDL5nSHKLY8Az4LkuSZ5Tj5fu7+sp+vQWPaaaKUenGtgVlDPyHcgtPLRzMw+s62bfwRF+fv8hugIXay3jjYSZKKOv6FL2HUbrSfs+A5j2vf/kjduu9T+DiIiIiMiK/fkzY/zTv3imk8vsOYa3bx/gRx5Yx8buwrL3jDVitvaWODHTYnQuIfQcAgeS+VoYyo8TERERERERkdVwcibirr6QZyeajNTa+7N9x9Bb8Nh1Vz9D5YCvnJyh5yrPtxIRERERud0MlgMKC0XwRUREREREREREREREREREREREROSOpWxCEbmpbaoWaKZLy+g305zh6vKFks43l2ScmG3y7FidqWZCcl5F/oVBsL8UsLYr5OxsxEQjvujzLFDwrs3QeeDwBHv3H2K0HtFX8hmtR+zdf4gDhyeuyfNFRG4Wnz0+yb4vjjDdijkzE/Hnz4zx/sdPk82PyQsl913HsLYrZE1XwFg95vRMRJavoFr0ZXgOOAZya7FAOD+OX8nvExERudCubf08vHs7Q+WQ6VbGUDnk4d3bdZiViIiIiNxWdm3r5zfefi9rKwWeGW+QZhbydoxhsVLgsr475ORMi7koW/ZZHcYQuoZg/s/2vhL39JfJLZpXi4hcJWOgu+CxoVqgy3c5F4EWEREREREREbmxFnKgXcdgaOcfewZCv52/1spy1nWFABR8l3VdBQJH2ztERG4mi3Pkcgv39JfZ3lcixyy7rqecOhERERG5Uy2eC7uOYWO1QG/BxRjt4xMRuVYsUItTTky3GJ2N+KOvneFPnxpf0sYx8KLBMsPdBY5NN5mNc7Lc4tCuq+Esk07XHbo8sK77qut6iIjIyn351CxHppoAfP9L1lyyrWuUCy0istjieWvoOVja9YR6iz7b+0sY4zATpTQXFZrrCj229hVxjeHoVJPpZoK9RDmjxSNvyfd4aOdmHljX3akV5xp4dqLOockGZd+hv+Qz2czILWyqhpQ8h3zRvb+0+97r8m8hIiIiIrIS//UrJ5lupYSu4ftfsoYP/+DL2fvGrWzsXj72awxs7y/z9Hid0bkY10CS5ZyYjRgo+cqPExEREREREZFV87K1Fb50cpaRWgRAyXfY0B2wY1MPayshrjEMKw9OREREROQCBVf1jEREREREREREREREREREREREREQEvNXugIjIpezZMcze/YeAjKLn0Exz4tSyZ8fwJe6yNFLLZDMhilM+cWic3/rb48xEGQC+Y8hzizHgu4aBSoEstxybapBfojDpgolmck3ebd/BEQLPUPJdjGn/hIx9B0dUwElEbnnGtA/orscZv/WF4zwzNsd0KyNdZqB1gErBo78cUGumnJ1rXrJQ9Eq4hvkC0e0xe6DoM9lq/31d0aORZCv4fSIiIpeza1u/5q4iIiIicttK8pzpVsqnDk/w2SNTzCUZx6ZbnB+26C/5hJ7LSK112ZiGB7xosNSJdaugv4jItRN4hv5SSNl3rjrGLCIiIiIiIiJytRZyoEu+wwNrKxyfiZhu5vSGLs00I0kt775/HUXfZU0lwDVmtbssIiLLuNIcOeXUiYiIiMidamEu/JljU/y7zx1hsplcwb5wERG5GAvMJRnTzZg4tYzVY/7Npw/zxZMzAKypBPzSm7bxga+fxvccbJ7zldNzWAtm/v7Qc4jTnBwIXdN57obuAp7Trnvxwup6iIjIC/HhJ88A8PI1Fe4dKF+0nQGtIYqIzDtweIJ9B0d4drzOdCsFLNZCpeBT9B2mmwlj9XjJPUXPYU1XSCvNOT7dIrtEcbnN1QKBZ5bMhRfv+3vnBx/v1Ip7brbZGZ/Hmyl39RUpBw5D5ZCPveuB6/VPICIiIiJyxQ4cnqCRZGzqKTBU8nntcJU1lZAvjEzzga+d5tRsxPqukHffv47XDffgGMNQJaDWSpiNUlxjMMZg5zdtG2OUHyciIiIiIiIiN8TC+uDxWosXDZb5znsH+MqpGWrzZ071hC4DZZ+hcoEfuX8tC9kVyoMTERERERERERERERERERERERERERERERERWZ632h0QEbmUXdv6eXh3u2j+SK3FcLXAnh3DyxY8MgaaSc5kM6GVZhyfbvFvP3eUL59qF++vBC5v297P8xMNjk63CF2H9dUCJ2pNojTrPMcxMFD0GW0ky/apmeTX5N2O11r0Ftwl14qew0itdU2eLyKyGjJraaQ5s62U2Sjh40+P87lj0yyuAW0AF0iBsu/QXwnJcsvIdJMku3ix6EsxgOuAWXTFWrinv4y1lnqSc0856Px9qBxe9PeJiIiIiIiIiNzZciy1VkqtlfK7Xxrh9758ioWIxeLIhQHWV0NaieXUzOXjuhu7fDb3li8b6xYRkStjDHQXfPqKHs58bFhEREREREREZLUtzoGuxxmbqgWqoUszyekvBrz7/nW8ZVs/a7sCnEWZbyIiIiIiIiIit7I3beklyfIV7QsXEZGLs8BcklFrJkRpu77FXz0/wW88epTZ+UO83769n3/yrZvpKfh84BtnaMUpUWaJ0pwst+fyn63FcSDNIbeWwHMZKgd0hy7WWkZqrSuq6yEiIi/cqZmIzx2bBuAHXrr20o1NO09aROROd+DwBHv3HyLwDOXAZS7O6Cr4BK7DWD1munmuTpxroOQ79JYCLIbTs1FnPn0pD+/efsm58OJacXGW4xmDtbbzbNWNExEREZGbzeJ59N19RU7NRjzyuaN8570DfOKZcXzPUA1dJpoxj3zuKHvftI3vvm+IkucwWk/Y2F1grJGQZDm+67Cu5DMXZ5f/YhERERERERGRq7Q4rrGtt8Dp2Yh/+olnyG37LKkNXSGea3jZ2m7e9bK1vGlLX+de5cGJiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiILM9b7Q6IiFzOrm39l90QGGWWqWZCI0mJ05w//Npp/uDxU8SZnX9GHz/zuk30lwIAQs9hsBwSuoZ3fvBxRusRW3y387xGkjHaSJb9Lrvs1Su3qVpgtB5RWvS9zTRnuFq4Rt8gInJjGAOtNGcmSqnHGc0k4+PPjPH+x08zWo877aqhSyvLyXOLMTBUDOgteIzXYyaaaftZXDjOFj2HNM9JcvAd8Byn81ma5+TWsK2vsGQ8bSQZQ+WQj73rgev45iIiIiIiIiJyu5lLMqYacSe2/MdfP4tjID0vYOE57YJ4M1HGRCNe5klt96+tKE4hInK9GAg8w0AppOg5l28vIiIiIiIiInKDLeRAWwvHak2y/Fywuei7rO0KcDCr2EMRERERERERkWvL2pXtCxcRkeVZoJ5kTDVj4vkE5pko5ZFHj/KXz08CUA09fu4NW/i2rX0UfZehcoBvYLyVUvJdrD0Xi3YMOMaQW4trDFt6Cxetb6HxW0Tk+vvoN89igcGyzxu39FyyrcHgGq0liojsOzhC4BkGywFjjYQ1lYDTsxFRdm7ea4CN3SFruwImmilTzZhWYonSfEXfcbm58OJacYHrkGbt54bze1lUN05EREREbjYL8+iS72JMu55n0zP88dfP0l/2KHrtOHHRc+kuGP76yBQ/8NK1wLn57919xc7zFmpmiIiIiIiIiIhcb/sOjlD0HYZ7ChydanJoogmAa+Dfv/0+XrOxylAloLwoD24x5cGJiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIXMhb7Q6IiFyNNLdMtRLmopTcwtfPzPLrnzvKkan2JsQ1lYCf3bmFnZt6gHah0krB42NPnuHff/44s1FK6Dn4DgxVQoqew1g9ZrKZXfe+79kxzN79h4CMLtehkWTEqWXPjuHr/t0iItdCZi2NNGemlRKlGa0k5+PPjPH+r51irJ4A7c3gr1zfzdGpJsXA4UQtolrwGCgHeAaem2wSLyoobZf5ntxajDHtTy1EWY61YAy48/0ozheEXlD0HEZqrev38iIiIiIiIiJy2zAGGknOZDMhSrIl8YlGkuGcd15gOXAZKPucmll6UNbFKE4hInJ9FH2XgZKPgw52FREREREREZFbS8F3WVMJFNcQEREREREREREREaC9v7qeZEw3E+I07+QzP3ayxr/+9OHOvu3QNWyqhpQDl56iz5Ojs/zk/3qKZ8frzEQZfUW38zxo7/PObfv/KoFDnFogo+g5NNNc9S1ERG6gZpLxv54ZA+CdL1qD5ziXbG8MuJduIiJyR5iLM4YqIcemm5yejcnypfv5DDBY8llTCXh+ssVkM7nmfVhcK26w5HNipr1XcF3RU904EREREbkpHa+16C24S64V5useb3CDzrXeok9X6PL4qZnOtcXzX8WSRURERERERORGG2vEbKmGfP3MHGfmYgAC11ANPV47XO2cKyUiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiK+etdgdERF6I1FpmopSZVkqWW2ajlP/0xRH+9Ol2oWfHwA+8dC3/1ys3UPLd+WuGvrLP+796gl/99FEcA75jSLKcVgrdSc5UM2U2yugv+ZyZjcjP+14DdIfXZujcta2fh3fDvoMjnJyL2FAJ2bNjmF3b+q/J80VErg9LK7XMxin1OCPLLVGa82dPj/L+r51mvNEuAu0aw3feM8CPPbCe9d0hXxiZ5sNPnMVzHIwBYy3NDM6rKb0s33XoChzOzCUki9pbCzntsbmZ5p3xnvn/H64Wru2ri4iIiIiIiMhtJ85zplop9SjFnhenyK3FcwzxogDGQDkg9BxOTrfwXAfHGFwD2fk3045Tg+IUIiLXS5fvXr6RiIiIiIiIiMhNJvQc1lQCXGNWuysiIiIiIiIiIiIisspyLLNxxkwrIU7P5SNHac5//OIIH37yLNDeS91b9BgoelgDH37yLOP1mPc/fprAM6zrCvDdlIlGgqF94LcBLOC5DtXQY2tvkT07htl3cISRWovhakH1LUREbqC/ODTBbJwRuIbvfdHgZdsbwDUOdpn9KiIitztjIMry+dpGOV84PrtsjaLu0GWgEjIXpXz1zBzZSgoZvQCLa8WN1Frc01/GWks9yRkqq26ciIiIiNx8NlULjNajJfU5W1m7Xmcryyl6LgPlgKLvcGy6yfrusNPu/PmvYskiIiIiIiIicqNY4O7+Ep86PEkjaZ8WVfYd+koed/eVWdtVIHS1P1tERERERERERERERERERERERERERERERETkSnmr3QERkSuRWctMlFJrpWS5xVrL3xyZ4t9//hgTzQSAewdK/MIbtnLvQLlzX+AZhsohoevwW184gWPAcxwAPGPI0pxTszGeYzCmfbjsYCXg7FwMgAO4DuQWHnz1hmv2Pru29bNrWz+Dg12Mjc1es+eKiFyJA4cn2HdwhOO1FpsWFZhbuD5aj7lvsMwPvXwt9/WXibMca9uHp/zpU6N84OunGW+0x2DPMXzXPQP86APrWdd1rpDdqdkW9SRjrJ4wG6X0Fj1aaY7BEriGPLekF6khneWWNIeBks/Y/MErCyzt6+1DXTKKnkMzzYlTy54dw9ft30xEREREREREbm2ptdRaKTOtlHyZwwDrccZ7P3WYeP7QKwNs6CnQjHNO1lr0FT26Ao+Hd2/n8dMzPPLoMZz5oMV8rTwAnh1vUAlcfvktd9+AtxIRERERERERERGRm1ngGdZ0BXz6yOSyOXsiIiIiIiIiIiIicmdIrWU2aucyp/nSXOanxub4lU8d5th0C2gf4B26hijLaaQWx4WR6Qb/4W/nGKr4lHwXgMGyTzlw8B2HepwReOaCfdcL9S1EROTGOHB4gv/21VOcmm3x3EQTgLfe1U9Pwb/sva5jaFfUEBG5MyzUOapFKdt6S9y/tsyXTs7wxGj9grZF32GoEpLmlhPTLeIsX+aJK7NzuPuyfVJ+h4iIiIjcavbsGGbv/kNAhrU+zTQnSS0/9PI1fOKZcdZUPELXcGyqSbRM3U7FkkVERERERETkRlhYjzsx0+L+dV3s2FjlyydmaMwX9DRAkuUUPY/3vHYToWsu/UARERERERERERERERERERERERERERERERERWZa32h0QEVmp1FpOzbRIsnZx5jNzEY88eoxHj08DUPAcfvyVG/j+l67Fc9obDw1QLngMFH1c0742F6f4zrmNiWmekwNYi2PBWMvJmRYbugusqQSMzcXkQJfv8eCrN/DQzq037qVFRK6zA4cn2Lv/EIFn6C24jNYj9u4/xLtePsOfPzNOX9lnuBpyZKrBz/3vZ/inO7fwLeu6+NOnxvjDr51mspkA4DmG77l3kB95YB1rK2Hn+Z5j+MShMd7/+BmmWzEOBgNMNlMMUPIdhso+J2ZjfGvJcji/pLQFjAFrYajsM9FIyCy4BvpLPgXP5eHd29l3cISRWothFYwWERERERERkYvIsdSijJlmcsFhsQuOTjX5hb88xPFa+9DYFw+WcRzDsekmjTinGrq8aLBywSGw73vsJDNRO+bhmPafhbiGiIiIiIiIiIiIiNzZQs9hoOzz2SNTy+bsPbwb5byJiIiIiIiIiIiI3OaSPGcmypiNUrLzcpnT3PL+x0/xe185RWYtrjH8w1du4H984zRRZtnQHdJMMo5MNrBAklk294RLnlH0HKZbGb+mfdciIqtuoZZHX9kjz6GVtitp3DtQWtH9nuNcz+6JiNxUFtc/6it4fPbYJH/29Gjnc9eA6xiy3LKmq0DgGUbnYhpxdtlne6Zdyyifr1WULZqG7xzu5mM//IrL9kn5HSIiIiJyq9m1rZ+Hd8O+gyPMRBl9BZ8ff+V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      "text/plain": [
       "<Figure size 10440x1440 with 116 Axes>"
      ]
     },
     "metadata": {
      "filenames": {
       "image/png": "/home/runner/work/BrownFall21/BrownFall21/_build/jupyter_execute/notes/2021-09-22_54_1.png"
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lmplot(data=coffee_df,x='Flavor',y='Balance',hue='Color',\n",
    "               row='Color',col='Variety')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9721ecc8",
   "metadata": {},
   "source": [
    "How could we choose which countries to select to make this not show the ones\n",
    "with very few points?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "bcd3dd71",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Mexico                          236\n",
       "Colombia                        183\n",
       "Guatemala                       181\n",
       "Brazil                          132\n",
       "Taiwan                           75\n",
       "United States (Hawaii)           73\n",
       "Honduras                         53\n",
       "Costa Rica                       51\n",
       "Ethiopia                         44\n",
       "Tanzania, United Republic Of     40\n",
       "Thailand                         32\n",
       "Uganda                           26\n",
       "Nicaragua                        26\n",
       "Kenya                            25\n",
       "El Salvador                      21\n",
       "Indonesia                        20\n",
       "China                            16\n",
       "Malawi                           11\n",
       "Peru                             10\n",
       "United States                     8\n",
       "Myanmar                           8\n",
       "Vietnam                           7\n",
       "Haiti                             6\n",
       "Philippines                       5\n",
       "Panama                            4\n",
       "United States (Puerto Rico)       4\n",
       "Laos                              3\n",
       "Burundi                           2\n",
       "Ecuador                           1\n",
       "Rwanda                            1\n",
       "Japan                             1\n",
       "Zambia                            1\n",
       "Papua New Guinea                  1\n",
       "Mauritius                         1\n",
       "Cote d?Ivoire                     1\n",
       "India                             1\n",
       "Name: Country.of.Origin, dtype: int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coffee_df['Country.of.Origin'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "215beaeb",
   "metadata": {},
   "source": [
    " Or we can focus on the countried, but wrap them."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "544a709e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7ff7cc6b22e0>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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zkOS3k/zwzEN/m+5dV5NlWf54kp+uqupJh2x/z91iM3c37U+yKcl3JPlGkh+tquqGsiw/me7opgPpjmz6qSR3pzuy6a3p3vXz4SSPSHJlVVX/PHP8viR3JnlaVVVfOuS8P5Dk9UnOTvfOuBdVVXVdWZYfS/LkJNNJmkkeWVXV9TP7FEluTnJVVVVvPORYtST/meQfqqp61cx1/o8k/5HkBUnelu7ogHuuvSzLp8+0+4x0P+R/aJK/qKrqj4/sp5k+elGSlyZZN7P9L5zKO5oOjhxI8k9J3p/k1w6O7pq5vpfPXNPKJB9N8nNVVe0sy3JTundZ/XiS30z3zq/frarqdWVZnpHkxiQbq6raMXOsRyb5UJKz0n0z+/+SPDzdn+mHklxRVdXuU3Vd0OvU1cVbVw+5lj/LESOzyrJ8Srr9/LtJfjVJK8krDo4gK8vye5P87yQXJtmT5B1VVb1m5rlN6dbdvqqqmoeOyC3L8sLcT12duUP3/6bbh+ele2f0C6uqmph5/mXp3jneSfLKJO+IEbkscOrs4q2zZVl+OslXqqq64n62+R/p1tnVST6d7nvYOw5p48Gf44qZa/vudH9e/y/Jb1VV1T6ib34iyc4k/z3Jxem+/x1I8rKqqt45c9w/S3f0yYVJHpfki0leUFXVLbOc9z7rPSwGavCirsF/lsNn9freJH9TVdVoWZa/n+Q5SVYk2Zzkf1ZV9amZ7V6T5CHp1sn/muTWdN+Pfn7m+V+b6Yv1SbYk+fWqqt4789yh/XQs9ViNZU6peWpeZq9535bu3/zfM/P8T1RV9ZVD2n7P39yHnmcm+P6LJJclaST5TLrvZWcd2Tzz9/7b0/0M94KqqnaXR4zILcvywen266OSbEvyv6qq+tuyLM9P8qUkq2fe//6/JM+qqmr9zH5/keQLVVX93hHnXJHkjnTf6/79/fTfx3PITGL38TN8wN/z+7uGQ34u6j5LjhG5HOnxSQaTvPd+tvn1dD+wuDTdD5Ifm+6HwcfqR5K8NsmqdF/EX5ckVVV9x8zzD6+6I5r+Zub7M9L9YOa8JD+T5M/TfSN/0PckufOINyMXJ3l3kv+Z7gv8+5P8c1mW/VVVfVeST6X7gj968M3IwV3TDR8PezNWVVU7yd8nedohD1+Wboi54eA1HHL+tUnek+TKdEcOVOlOB3d/vi/JY5L8l3Tf7D1jto3KsvzRsix338+/c+/nHI9N90P9l1SHT9H54iTPTveN2llJdiW56oh9n5Ru/1ye5FVlWV5SVdVdST6ee9+cJsmPJfnrqqqmkxTpvik8K8klSTamOzUeLCXq6uKuq/fnjHT/0Ds73T+yryrvvUN5f7p/0K5M8r1JXlSW5bOP4ZjHUld/OMkzk5yf7rX/+Mx1PjPJr6Tb5xcleeqJXBT0IHV2EdbZsiyH0/3Zvue+Tl6W5XelWxN/OMmZSW5Jd2r72bw13Zp8QbrveV+Qbkhw0GXpfgC5Jt1RJn89c20PSvdn93/Lshw9ZPvnpxsqrE33w8933cd5T7Tew0KhBi/CGjzLMUbTrXsH++xz6f48V6dbM/+uLMvBQ3b5gXTr6Mp0byb/v4c8d0O6YdSKdH+uf1mW5ZmHPH889ViNZa6peWrebDXvWen2ycHn/3EmQH8gtSR/mu7P7twk4zm8Xs7m8+l+Fvsrs7R7JN0w/6/SvVnmR5L8QVmWD6mq6qYke9MN+pNugDpWluUlM98/Od1ZcI70+HRvonnfMVzP8Zj19/z+rmFmP3WfJWmhTGvA3FmTZHtVVc372eb56a4RsDVJyrJ8bZI/TPK/jvEc762q6j9m9n1Xkv/zANu3k7y6qqrJmX3+Msn/KstyeVVVe9MNDv/iiH3+W5J/rarqwzP7vCndaSeekO6L3X1ZO/P/nbM8d+chzyfJHVVVvXXm62ZZlodu+z1Jvl5V1T/MnP8tmeUF9ghvqLojqnaXZflv6b5B+OCRG1VV9VfpvpidiMcl2ZHkA0c8/nPpvkG7baa9r0lya1mWP3bINq+tqmo8yVfKsvxKum9Gr0t3PYRfTPK2sizrSZ6X7h9tmbnb7OAor21lWf6fJK8+wbbDQqWudi3Wunp/ppP8xszP/v1lWY6l+4fvNVVVffyQ7f6zLMt3p/uH0z/e3wGPsa6+pbp3NNo/p3vdSfeP3T+tquprM8+9Jt2aDQudOtu12OrsqnQ/3Jrtug56fpI/qarqizNtvjLJrrIsN1VVdfPBjWbeo/5IkkurqtqXZF9Zlm9O9+fwjpnNbqrunTXhb9L9EPY3Zn6GV5dlOZVuiPDlme3/taqqT85s/+tJ9pRlubGqqi1HXPvHD/n2mOs9LCBqcNdiq8EH/UpZlr+Q7uja/8jMDYJVVf3lIdu8uSzLV6b7PvcrM499uqqq989cy1+kGxYdbM+hAdDfzNTux+bekOCY67EayzxQ87rUvMNr3heqqnrPzLX8n3RHDj8u3UD8PlXd2Q3vGeValuXr0l0K74G8Kslnyu5I4UN9X5KbD9bQJF8qy/Lvk/xQuqHpJ5I8uSzL22eef8/M9xNJlh9yPYdamyN+58uy/Pd0Z14YSPKMg++Jj9N9/Z7f7zWo+yxVglyOtCPJ2rIsG/fzpuSsdO92P+iWmceO1V2HfH0gyeh9bThjWzUzJWSSVFV1R1mWn0ny3LIs35vu9GhHrg1wWBur7pQRW9IdFXV/ts/8f2a601oe6sxDnk+6UwDdl7MOfb6qqk5ZlrNOi3GI4+2XE3FVun/wfLgsy++qqmrXzOPnJXlvWZbtQ7ZtpXvX3AO1731J3l52p+gok+w55IV4Q7prKHx7kmXpfhi3K7C0qKtdi7Wu3p8dR/zM72lDWZaXJXlDulMw9af7B9CsU3Md6hjr6pHXffB36awkXzjkuUN/52AhU2e7Flud3ZXuB5NnJvnmfWxzVrrTGidJqqoaK8tyR7p9dvMh261N0pejfwcO7du7D/l6fOZ4Rz526PUd2ldjZVnuzBF9mJx4vYcFRA3uWmw1+KA3VYcsH3JQWZa/ku6MM2elO8Xr8hwe4BzZtsGDvyNlWb4g3aU+Ns08P3rEvsdcj9VY5oGa16XmHV63Dr2W9sy1PODPvOzOQPO76c6odXD2rmVlWdarqmrd135VVX2tLMt/SfJr6Q6yOei8JJeVZbn7kMcauTfI/0S6g29uS/LJdEP7H0s3uP7UzMjqIx31O19V1RNm2n9bTnzG1/v6ed7vNaj7LFWCXI702XQXqH927nsaszty+KL35848lnSnNxg+uGHZXUP1ZM223sE7k/x0ur/Dn62q6vYjnr8jycMOaUeR7vSTR253pCrdF7MfSnLkWg/PzeF399zfOgx3JjnniPOfc9+bH7uyLJ+f7p189+UhVVXdeh/PtZL8aLo/2w+VZfnUmbvztiT5yaqqPjPL+TbdX3uqqpooy/Jv05225cE5/C6/30q3nx5WddfbfXYeeIoQWGzU1cVdV0/UX6VbD797po7+Xg7/Q/C+nExdvTPdn9lBJzplNPQadXYR1tmqqg6UZfnZdK/hvkYmHPy5HjzPSLojZY7ss+3pzpJwXrprcCXd34EH6tv7c089LbvT763Ovb9ThzrReg8LhRq8CGvwAxzv29Ndn/HydEfUtcuy3JXuEiAPtO956a5Rfnm6P4dWWZZfPpZ974May1xT89S82Wreoe8La+ley8Gf+YEc8jNPdyrsg6H1S9MdFHNZVVV3lWV5abrTOR9LTXx1ujc0vvmQx7Yk+URVVU+bfZd8IsnvzJz/E0k+ne6auxOZfVrl5N7f+WflkNHDszjsdzvd6zwRD3QN6j5LkiCXw1RVtacsy1elu45fM8nV6X7o8dQk31lV1cvTXUPhlWVZfi7dF+VXJTk4xcRXkjx05oXnmzn+9VDvTnfdqm89wHb/mOQP0h0x+sZZnv/bJL9WluXl6d5h9Evpvuj8+/0ddOYOsF9J8v9m7ir6h3Tn3P+tdO+2+t1jvI5/TXfdlmcn+Zd0py4+FW/OUlXVu3Lfa3Ady/7TZVn+ULp9+P6yLJ+R7ov268qyfGFVVbeUZbkuyROqqjrW9Q/+fObf+iSvOOTxZekuPL+nLMuzk7zsRNsNC5W6uvjr6glalmTnzB8ej033Jpurj3G/E62rf5vkT8uy/PN0R6qZ6p5FQZ1d1HX25elOo3lLulMo7yjL8uFJrqyq6kfS/bm+uyzLv0p3NMJvJbm2OmRa5Znzt2ZuPHzdzEiw1emOBnvTCV9U8j1lWT4p3Wn3fjPdafNnG3lyovUeFgQ1eFHX4PuyLEkzybYkjbIsfy3daz0WI+n+DmxLkrIsfyLdUVUn0xY1ljmj5ql591HzHlWW5XPSXRP8F9Pty2tmnvtykh8ty/Lr6a4h/OR017k9eOzxdKeLXp3j+Bu9qqpvld3p538xyVdnHv6XJG8ou0vl/fXMY5cmGauq6rqqqjaXZTme7mCc11dVtbcsy7vTDeH/4D7Os7vsTg/+BzOB+4fSDW3/S7o1/aAvJ3lOWZZ/nO5o5J/K4TMsHKv7vYao+yxRJzr0nUWsqqo3p/vBxivTfZHakuQXcu9dVf873Rec/0z3heKLM4+lqqrrk/xGko8k2ZzunT3H4zVJ3ll2F5//4ftp43i6dwGdn+6bhpRl+YGyLF8x83yV7ovSW9O9A//7k3x/VVVTRx6rLMvnz7yYHjz236Q7rcRL0p0+4htJhpI8cWbtggdUVdX23Ht32o501w34fLov5PNuph+ek+4dV/+c5I/SfbNxdVmW+9J9s3HZcRzvM+lOfffFqqoOnT7mtUkemW7o8K+Z+VnBUqOuLv66egJ+PslvzNTcV6X7h/SxOOG6WlXVB5L8XpKPpfuH/8eOo73Q09TZxVlnq6r69yTfNfPvxrI7ffEfJXn/zPMfSXe9ub9Pd2THhemuhTubF6f7odON6f6M/yrJn5xE8/4q3Q/bdiZ5VLo/u9mcaL2HBUMNXpw1+H58KN11Ka9Pd2rWidz/FKr3qKrqG+mOHvtsuh/wPyzJUTODHQc1ljmn5ql5ObrmvS/ddYd3pds3z6mqanrmuV9Kt393p7t+8j8est/vpdt329P9LPaoNX8fwG/kkDC1qqp9SZ6e7vvhO9Kdvvi3051++KBPpLsM1JZDvi9yyHIlR6qq6o3p/s6/PN3afXe6o55/NfeG/7+bZGrmuXfmBMP0Y7gGdZ8lqeh07m+WA+hdM3fAXVxV1X19aNIzZqbVuC3J86uqOpZF6xecsiw/luSvqqr64/luC3Bi1FWA00udBZg/ajCwlKh5c6Msy9ckedBC6Gdg4TK1MgvSzHQTP5XuXU49aWbK4mvTnSLjZene3XTN/e60QJVl+Zh0R4g9a77bApwYdRXg9FJnAeaPGgwsJWoewOJiamUWnLIs/0e6U1h8oKqqT853e+7H45PckHunKHn2zNQmi0pZlu9Md0qY/zkz/QWwwKirAKeXOgswf9RgYClR8wAWH1MrAwAAAAAAAPSYhTAit5FkU0wDDTAX1FyAuaPmAswN9RZg7qi5AHAKLYQX1HOS3LRjx1ja7eMfPbxq1XB27Tpw6lu1wOmXo+mT2emX2S20flm3bllxjJuquaeBfjmaPpmdfpndQusXNXd+6Zej6ZPZ6ZejLcQ+Ocaae1L1NlmYfXO66ZPZ6ZfZ6ZejLcQ+UXPnjz6ZnX6ZnX452kLsk+P4bIFFbiGMyD0pjUZ9vpvQk/TL0fTJ7PTL7PTL7PTL7PTL0fTJ7PTL7PTL7PTL7PTL0fTJ7PTL0fTJfdM3R9Mns9Mvs9MvR9Mn903fHE2fzE6/zE6/HE2fsJAt+iAXAAAAAAAAYKER5AIAAAAAAAD0GEEuAAAAAAAAQI8R5AIAAAAAAAD0GEEuAAAAAAAAQI8R5AIAAAAAAAD0GEEuAAAAAAAAQI8R5AIAAAAAAAD0GEEuAAAAAAAAQI8R5AIAAAAAAAD0mMZ8NwAAAAC4fx+9cUeuunZLbt0zkXNXDOaKyzbm8gvWHPb4aF8tRVFk31TrsG0AAABYmAS5AAAA0MM+euOOXHn15vQ3iqwarGfr/slcefXm/LeH7c3ffPXu9DeK1NPJ5p0HkiTnLB+8Z5vXPz3CXAAAgAVKkAswY/r2j6R53VvTHrs1tdFz07jkxek7+6nz3SwAAJa4q67dkv5GkeG+epLM/N/KH37u9gz3Fdkx3s7+qVaSpFErsu3AdB60eihJK1ddu+WeYxw5mhcAAIDeZo1cgHRD3KnPvzzt8buT/pVpj9+dqc+/PNO3f2S+mwYAwBJ3656JDDUO//N9qFHLvqlmdow3M91qp5Okk6TZ7mSy2b5nm+u378+VV2/O1v2Th43m/eiNO+b+QgAAADguglyAJM3r3prU+lM0hlMURYrGcFLr7z4OAADz6NwVgxmfCWcPGm+2U6RIp9NJrShSK+59rtPp3LPNVKtzz2jeouj+398o7hmpCwAAQO8S5AIkaY/dmtSHDn+wPtR9HAAA5tEVl23MVLOTA9OtdDrd/6eanYz0ddPbdqeT+kyQ25nZ5+A2ffVi1tG8W/ZMzOEVAAAAcCIEuQBJ+s54fIqiOPzB1nhqo+fOT4MAAGDG5ResyeufflHWjwxk90Qr60cG8vqnX5SHnbE860YG0qjXUhRFBupF+utFGrXinm3KtSOzjubduGJwnq4GAACAY9WY7wYA9ILGph9Ke/z309q/NakNJK3xpD2VxiUvvt/9akUrndTT6dzvZgAAcEp0kuwan85v/tsN2X5gOnsnW1k9VM+6ke70y1PNTl7/9Ity+QVr7tnnyqs3J2llqFG7Z5srLts4b9cAAADAsTEiFyBJff1j07jghakvvzCZ2p3a0Ib0P/qN6Tv7qfe5T9GZTGd82xy2EgCApeijN+7IlVdvztb9k6kXyfU79mfzzgMZ6atlzXBfdo63cse+qXtG4R4a4t7XaN5DtwEAAKA3GZELMKO++uHp2/jMdGpDD7htuzmR9v47U9QaKR5wawAAOHFXXbsl/Y0iw331fGvfeOozS4JsH2/mwtVDGemvZf3IQP7heZfOuv/lF6w5puC2Pbk/RVGkY7oZAACAniDIBZjR6bST6b0pBgfT6dxfPNtJ68C2dNrNFDVlFACA0+vWPRNZNVhPkky12mnMhK2TM2vfDjVq2bJn4qTP09y/K8mKkz4OAAAsdNO3fyTN696a9titqY2em8YlL77f2RvhdDG1MsAhWpNjyeSO+92m1hzrrqELAABz4NwV3fVvk6S/Xku700knyUCj+yf9eLOdjSsGT+ocxeSepDV9sk0FAIAFb/r2j2Tq8y9Pe/zupH9l2uN3Z+rzL8/07R+Z76axBAlyAQ7TSWtid4qp2cPcIs20Ju4/6AXg9PnojTvynHd/OY9++zV5zru/nI/eeGhN7mSqbTpQYPG54rKNmWp2cmC6lXXDfWl1Oml1Olk71MjWscncunsy12/fP0tdvH8Ha+r3/sXn89J/uCb/fpP3uQAA0LzurUmtP0VjOEVRpGgMJ7X+7uMwxwS5ALNoTe5Orbk7SVJkOkk3GOhM7kyn3Zy/hgEsYR+9cUeuvHpztu6fzKrBerbun8yVV2/OR2/ckU6SrQemM9FszXczAU65yy9Yk9c//aKsHxlIu5NcvGYkF60ezth0OzvHW1kz3Jczl/UfVhcfyMGaumdyOhcOjmfLrrG8+eM35BM375qDKwIAgN7VHrs1qQ8d/mB9qPs4zDGLOwLMptNJc3xHGkNJe2osRWMwRWM4zal9890ygCXrqmu3pL9RZLivu07kcF89taKVv/na3blk3WjGp1sZHO2f51YCnB6XX7Aml1+w5rDHnvPuL2fr/snD6mLSylXXbjlq2yMdrKnnjdYzNbYnA41aGvUif/yF2/Md5606XZcBAAA9rzZ6bnda5cbwvQ+2xlMbPXf+GsWSJcgFuC+dTpoHtne/bk6kqO1NOp0URS0H7rgmE198W9KZTm34zNQf9JMWuwc4zW7dM5FVg/V7vm/UimxaNZTNO/ZnfNpIXGDpObIu7p1s5e6xydy4czzPefeXc8VlG3P5BWvy0Rt35Kprt+TWPRM5d8VgrrhsY27dM5FzlvdnWWtPdk1118YdaNRyw96J+bocAADoCY1LXpypz788nWa6I3Nb40l7Ko1LXjzfTWMJMrUywDHqtNtJUUvzzs9m35ffnvbE9qQxmvb4VovdA8yBc1cMZrzZTtING9aODuS2PRMZrHtLCyxNh9bFvZOt3L53ItOtdgYbtXumWX7zZ26adVr6ZX21rKhPZ//+e2ecmWy2c/bywfm6HAAA6Al9Zz81/Y9+Y2pDG5Kp3akNbUj/o99oIA/zYs5G5JZl+X1JfjNJMfPvtVVV/cNcnR/gZBVFkc6BnZm+/t2pDSRFYyhFkaQxlM50d7F7L+YAp88Vl23MlVdvzkCjk1VDfbll14HsHW/mpU86Z76bBnBaFekkRZFO5/DHD9bFpDsSt9PppCiKrB/pu2ea5T/83O1ZP9p31PTLq4YaqR3Ymr0T0xmoF5lsddJodfLTjzp7ri8PAAB6Tt/ZT/VZLz1hToYvlGVZJPmLJD9WVdWlSX4syTvLsjR8AlgQiiTtsR1pHdiT9vhdKWoDh29gsXuA0+7yC9bkjc+8OBetGcn12/dnuFHPS5+0KY/fuHK+mwZwenVaKab3HPXw5ResyeufflHWjwxkstlOvShSJLlt71S+uW1/tuyeyJ7JZm7fO5m9k90p6PdOtrJt/3Qm9+/MnrGx3D02lWV3fj4v2vKG/ObW38ilH3tRJq/78BxfIMDSMX37RzL+kWdly59cnPGPPMvsXgDA/ZrLNXLbSVbMfL0yyZ1VVbXn8PwAJ6RI0t63Le2pA90HBtamPbkrnYltaU/uSDF6rsXuAeZEJ5eeuTznrhg8alTaTbvG88dfuC3LBhr5wx94SGpFMT9NBDgtOmlP7UlRH06n6DvsmcsvWJPLL1iTp7zjP7J554HUiyLpdDI589d2kWS61c7teydyYKgvu8anc8Hyelpju3LnxFQeOfn1/Pz4X6dVa2R788wUO+/M9HtfmuTNGbjkaXN+pQCL2fTtH8nU51+e1PrTGFiV1vjd3e9juk4AYHZzEuRWVdUpy/KHk7yvLMv9SZYl+Z65ODfAkT56445cde2W3LpnIueuGMwVl23MUzcNZvJbn8nEv78z7d13pLbyrAw+8ScydMFl+dK3bsw/fuWmLJvcnO/quyYP6r8hqTeTJJ0kqfVnvFXLW/d+T/717dfcc8zLL1gzr9cJsNhsH29m7/h0Ds1wx6aaeccXbs/fff3utDtJrUie/Vdfzi89/lx1GFhUOq1mMrE9xfCZ+cgNR7+fLQ65gaV16H5Jmu2kVnSybWwqq4YaGZnele0HplIkec7E1Zns1JPaYBpFkTsna+nb38ndf/UbedtD1nlfC3AKNa97a1LrT9EYTlEUKRrD6TRjqSYA4D4VnSOHM5wGZVk2knwwyaurqvpMWZZPTPLuJA+pqmrsAXbflOSm09xEYIn4wHV358Xv/Vr6G0WG++o5MN3KVLOTv3j4lqz56KtSNPpS9A0mnXZqQ8uy56zzctOOG/Pgvs0ZKiYOO1ZnKmntS6bXflve1Hxebh99YpqtTu4cm8xUs5O3/tdvy3dfsmGervQoxzo0bVPUXKDHTDXb2To2mQPT90YT7U4n//T1u/Omj9+Q7funkiSNWpFHnb08eyab812H1VzglOq0ptLce0uS5LN39+Wn/uGG9B3xfnZscjrLBhvZOjaVfTPTKB8sRo1aN8wtiuRhK5OJXXdmotkdsvuO3b+efcVIBvsaaYyszL5mkfrkvizv7MuLLnrXfNfTY3EsNXdT1FugB2z5k4tTDKw67OabTqeTzuSubPzJ6+exZcdMzQWYO6YaI8ncTa18aZKzqqr6TJLMhLn7k1yS5HPHcoAdO8bSbh9/6Lxu3bJs27bvuPdb7PTL0fTJ7BZbv/zWh69PvehkoFZLq9XOQK1Iq2hn19Vvyap6PUWjlvrw/tQGDyS1G7Jy35fziP5795/YX8v4+PJMtDdkTbuZTE/l5pvq+camx6Z/qpVakXuO+Vsfvj6PXjs8fxd7iHXrlh3X9mruqaVfjqZPZqdfjjbebKfZ38jW7ffe+1dt35//8++35Kt3dx+rFcnygXrWj/Rn9XBfJqZb81qH1dz5pV+Opk9mt5D6pehMpz12IJ1OO3/2qVuzfmR5DkznsPezk81OViS5YNVQvnb3WFozZaUokkatlqSdZQON9E9tz0S6tbPTSe6ur82q9p4k9Uy3O2nUahkuprJn8Kws769nV2u6p97XHul4au6J1tuD51kovy9zRZ/MTr/MTr90dYbOSWv87hSN4TQa9TSbrXSaB1IbOmdB9I+aO3/0yez0y+z0y9EWYp8c72cLLF5zFeTeluScsizLqqqqsiwvSbIhyQ1zdH6AJMmteyayarB+2GPnNHbkrJEbUl/RSmNgKp12J52ppDPZSXuik6nJevZMjGb5gT2pdaYzmG1pDjfSWb4y7fpA6nvuyl37JjPQqGX9SDf1HWrUsmXPxGxNAFg0pm//SJrXvTXtsVtTGz03jUtefMxTwh3LvvumW9k+NpmVq0aSJHsmpvNHn789/3jd1numV778gtX5z7v2ZfVQ47CRDeowsBhMXvfhjH/899PaeXPqKzZk4AkvyOaty7Jx3UBuag9lqtVO2bwmz679Xc5atTW3N9fnHXuenVbnEXni5Bfyk+P/kLNbd+f2+oa8c+QHs2fFw7Nzx3ia7fY953jPwNPz8wf+Oq3p8dSHV6bRnkxak7l6w/OSqKcAp1Ljkhdn6vMvT6eZdOqj6TQPJO2pNC558Xw3DQDoUXO1Ru5dZVm+KMl7yrI8+BfjT1ZVtXMuzg9w0LkrBrN1/2SG++4Nc19T/9WsWD+eTruTyc2ttMcOv2O0lnZWZddhj11XbMw/tJ6Zb3bOzA0rzkh7z2SSZKLZzuqhvow329m4YvD0XxDAPJm+/SOZ+vzLk1p/0r8y7fG7u9/njQ8Y5j7wvp3smmxl14GpdDpJq93JP163NW//3JbsnZku9PxVQ/nlJ5yXR521PL/wL9dlx/hUhhr31nZ1GFjoJq/7cMbe+9IUjYEUwyvT3rc9B97/hjxpzY/mP8fqOXP0nAzuvCYvavxBpjqN7GmPZm19V1654v/l4v3fkWeNfSxTRSN7imVZ296V19bflz/eOZZPty+45xz1WpEbVjw87x2p5Xt2/mPWTNyVzX2b8paR52ey/5EZinoKcCp13+u+Mc3r3prO+G2pDZ1zXDdDAgBLz1yNyE1VVe9K8q65Oh/AbK64bGN+7n1fz9h0OwONepJOrlnx8HxnfzN923alMXbgnsUHOknGi4Fsq6/OrX1n5eu1C/PVepmb62fllsbZ3Y0OWamgr1Zk5UDjnnXKrrhs4xxfHcDcaV731qTWn6IxnBS1pBhOp9l9/IE+iGpe99bsbzZy90SRqdaB9Ndr2TDYSO26t6Z21uXZPj6dsYlmkuSrd+/L7//TN/KNmWmUR/rq+elHnZ3nPnT9zFShyfMffmbe/Ombk7TS6XTUYWBRGP/473dD3P7hpFZLBpelM7E3z9n/4Xy4XWZw6s68ZOjqTE01Mt7pBq3F3maW79ienz/w7kx0+rO1vjb1wZHUR9en2dqZ7xl/Vz59/g9l5e6VedT4rjyk+a1s2nt9Lpi+Of1pJs3kY7XvzucHHprcvT8Xrh5MsxX1FFjSPnrjjlx17Zbcumci564YzBWXbczlF6w54eP1nf3U9J391AU5zScAMPfmLMgF6AVfvnNvxqbbaXeSc1YMZqLZzlXNX8gHhjoZ6Hwhm5Z9M61af67Jg/ONvgvTLuqzHueczrZsbN6RxujK3Dp0cfZMNHP+qqG02sn6kYGT/sMOoNe1x25N+lcmSeojZybppDW+q/v4A9i/+6bcNj6SoeUb0l/Usn/P7bltf3Je5+bs2DeZyWY7Ow5M5W3/cVvev3n7Pft9z0Vr8/OP3ZjVw32HHe/xG1fmpU/alHd95c7sm2yrw8Ci0Np5SzpDK1PrdFIfXpVarZbO6JoM792eFUP92T0xnk1rp3Nnc0WKTjsjB8azbvd4MrAqfQP1pDGc85Jsa7UzOb4lzfGxrGk38n+v/+ucP3X3rOe8vn5ePtt/aZKkUSuyfmQgL37cueopsGR99MYdufLqzelvFFk1WM/W/ZO58urNef3TozYCAHNCkAssKX/4udtTL7qjZ3cemMrOA9PpJLl1d5J8WzL4bYdtX++0ckF7Sy5p3ZgHd27M2ev2pRzYmtbI6rx5/09lxfBIxpvddXFXDPblb3744XN9SQDzojZ6btrjdyeN4XTa0+lM7UtRK9JY/6gUnal0iv4URdI5fLb6FEVyW/3irFo5kWZzPO36UBq1WgYzkRum1mbFVDPv+frW/PEXbsuB6e6KHA/ZMJpfumxjHrZh2X225/EbV+aJ567M2tGBLOub/SYcgIWkvua8TO66M82+ofS1mmnv3ZFM7M3WYlUetWw8A2sHcyBrcta6Ndk3tiert9+Wom8wndZkdu0fz/Z2d4aZ1e07s75zyIiv7gz1mU4932hcmC/1PSRfajw4X288KO2BZdlfH81ZA/U8/Izl+bPnfNusbQNYKq66dkv6G0V2HJjO/qlWLlw9lDS6jwtyAYC5IMgFlpSxqWYaRTLZ6mTywPRhz/VnKuc37silrTtSHvhSHty3PQ+p35HGge6IhXYr2Tdwbtp9wxmu78rZywczPNif6dZAhvpqmWx1ZjslwKLUuOTFmfr8y9OenEqnNZnO+NZkek9afcvSvPr707jwv6f/7MszdcO70rr5vUnrQFIfSu3cZ+WD+x+THy7+PK1OI+3RTWm0x5NM5w17fjR3/P3Xc9Pu8STJioFGfvYx5+SFj9+UPbsP3Gdb6rUiI/31LB/oy2CjOCo8BliIhp/yS5l8zy8n6SSdVSkm96YzdkeWrduRp+z4nbz/wOPyt8WKfP+q63Lb7v7csGM4y9rJua1dWd45kOXZfdjx9hdD+UqjzJcGLs5XBzfm+mWr09lzVvo7U2mknYFMZ2XfeHb1r0yz3ckPP+yMeblugF5y656JrBioZed4d9mPZruToUYtW/ZMzHPLAIClQpALLCmj/Y3sn2qmXiRr+/bn2xvXZFPjjjx81Xge0fpEGmmmtePcdJq70jeyIqmvTHN6f6bHx9PuH0iz3U69PZm7Wmdlx+RUmkV/DrRb2TfZyobRwfm+PIA5010H942Z/PRPprN//71PTO1Oe/vnM7X985kqakmnPfNEd1Hx1ld/J5e3y3x++qJcOnhzRjp78u8TG/Obu38y29qrkoynViTPvmR9fuZR52T5YCP1WnHk6ZN0p/1cPtSXZf31NIruNkJcYLEYuORpaX7P61P7zFUpDmxPJ/tz11mb8rnWpkzvKnL+5M05c2Jb1t1+Y87J9FH7b6utSlU/P9trK9JJsra1M99ctSIfOmt9OhnPaGtravvWptXuLjtSSzLcqGXl6uH8wIPX5TFnLZ/zawboNeeuGMzte8fv+X64r579061sXOHvfwBgbghygSXlZx9zdt78mVtSK5K3r31zhlvbM94ZzENGGmntSzqppW/9SKYnmxnfdls6gyPpH1qV7N+fAxvOTqN2IH1FJx+dfnIOTLcy0mpn1+R0dh1o5uVPOnO+Lw9gTvWd/dTkEa/N5JdfmzQPJJ3W4RvcE+Im3Qk+uy6pV7mkXiVJto6N52U7X5HJdKepf9iG0fzyE85LuXZk1nMWRdLfqGfFYCMjfbXUMnvIC7DQbdkzkatzabac/6t5yPW/n6nxldm0+7Z8b+sjqeXou1Zur2/IHbW1mUx/VnT2ZVPztjyx/cU0U0+rKFLrtHLp9r7889kPTVF0Mjq2MSOj/WnUivQVyabVw5lo1zM12p/h/nqK+7iJBmAp+cXHnZtXfGRzkqS/XmSq3c5Us5MrLts4zy0DAJYKQS6wpLz0iecn6a6Vuz53ZXcxmjNG+zNQTGeyVkunsSyN0Vpu2dbMirFkYP+ubBm8OLWzBjI60sx048xMn/W0/MBF35tbPnlj9k21sm54IC974vnWxwGWpL6LfyLNm/827eZ4Oq2pJO3uXPTtZnLg1iT17mDcopG0p5N00ul0sq8znOlOI+878IRMpj+ra3uyaXBP3vr9z01RHB0e3Dt9ciODjZqRt8Ci9k/f3Jqfed830kny4cn/kTP33n3Y863Uckff+uwbHEltuMjKobEMTU7nUVu/maJ1+E01nSTpFGmnlqH2VFrTfcmuM7LnwEj25PCpQc9aNZq79k3mD67dkrXDffmO81af3gsF6HGP27gyZy8fyA07xzPYqGf9yEB+5snn+PsfAJgzglxgyXnpE8/PS594fvZ/+KKcMXF3ao3+pJP0DaxMrTGcfbtuTHPlhhxYdWbu6KzO6+u/lTOyNwPT+/K737khaY5nzbmrUn7fJak1BlOMnCNQAJa02siZae/8RoqinqSe1OvpdFrpTtRZpDZydmr1kUzvuyE3T63N/971wnx88lFJknpaee7IJ/PC0X9Juz6aovjBe45bFEl/vZY1Q30ZbQ+mr2b6ZGBpaM/UuaFGLd9qXJozxq9OfTCpjRSpjRapDRd5UG1HWq2d2dcaylhrJKNbx9KqFUm9kcZUM+kbTFHvS31yLO1OLbV0Mp6h5PYH33OeIvfOl9BXLzLd6T440Wzl9/79VkEusOS10snYZPcGmec+dH3e8LSL57lFAMBSI8gFlpyP3rgjV127JWeMPS2/Mvz2jA62s3zVOal12mnuvTlpbEj/9EQaaea97R/MzsnpNIaG87JHLE+t1kg74w94DoCl4GA9vbT2hPx45wsZqhcZGhxOJncl07uSoj+tib5M374/45123jb9X/Onfc/OdPqSJI8Y2Jz/eda/Z93EN9LpJJsGtmcsSa0oMjwz+naoUcua0YFsG5+a34sFmEPPvmR9nvag1dl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      "text/plain": [
       "<Figure size 1910.97x2880 with 36 Axes>"
      ]
     },
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   ],
   "source": [
    "sns.lmplot(data=coffee_df,x='Flavor',y='Balance',hue='Color',\n",
    "               col='Country.of.Origin',col_wrap=5)"
   ]
  },
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   "source": [
    "## Questions after class\n",
    "\n",
    "```{admonition} Ram Token Opportunity\n",
    "add a question with a pull request; earn 1-2 ram tokens for submitting a question with the answer (with sources)\n",
    "```\n",
    "\n",
    "## More practice\n",
    "\n",
    "1. Plot the kde for the `Aftertaste`\n",
    "1. How does `Total.Cup.Points` vary by `Certification.Body`\n",
    "1. Are  moisture and sweetness related? Does that relationship vary by Color?"
   ]
  }
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