{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# statsmodels Principal Component Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Key ideas:* Principal component analysis, world bank data, fertility\n",
    "\n",
    "In this notebook, we use principal components analysis (PCA) to analyze the time series of fertility rates in 192 countries, using data obtained from the World Bank.  The main goal is to understand how the trends in fertility over time differ from country to country.  This is a slightly atypical illustration of PCA because the data are time series.  Methods such as functional PCA have been developed for this setting, but since the fertility data are very smooth, there is no real disadvantage to using standard PCA in this case."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import statsmodels.api as sm\n",
    "from statsmodels.multivariate.pca import PCA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The data can be obtained from the [World Bank web site](http://data.worldbank.org/indicator/SP.DYN.TFRT.IN), but here we work with a slightly cleaned-up version of the data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country Name</th>\n",
       "      <th>Country Code</th>\n",
       "      <th>Indicator Name</th>\n",
       "      <th>Indicator Code</th>\n",
       "      <th>1960</th>\n",
       "      <th>1961</th>\n",
       "      <th>1962</th>\n",
       "      <th>1963</th>\n",
       "      <th>1964</th>\n",
       "      <th>1965</th>\n",
       "      <th>...</th>\n",
       "      <th>2004</th>\n",
       "      <th>2005</th>\n",
       "      <th>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Aruba</td>\n",
       "      <td>ABW</td>\n",
       "      <td>Fertility rate, total (births per woman)</td>\n",
       "      <td>SP.DYN.TFRT.IN</td>\n",
       "      <td>4.820</td>\n",
       "      <td>4.655</td>\n",
       "      <td>4.471</td>\n",
       "      <td>4.271</td>\n",
       "      <td>4.059</td>\n",
       "      <td>3.842</td>\n",
       "      <td>...</td>\n",
       "      <td>1.786</td>\n",
       "      <td>1.769</td>\n",
       "      <td>1.754</td>\n",
       "      <td>1.739</td>\n",
       "      <td>1.726</td>\n",
       "      <td>1.713</td>\n",
       "      <td>1.701</td>\n",
       "      <td>1.690</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Andorra</td>\n",
       "      <td>AND</td>\n",
       "      <td>Fertility rate, total (births per woman)</td>\n",
       "      <td>SP.DYN.TFRT.IN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.240</td>\n",
       "      <td>1.180</td>\n",
       "      <td>1.250</td>\n",
       "      <td>1.190</td>\n",
       "      <td>1.220</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>Fertility rate, total (births per woman)</td>\n",
       "      <td>SP.DYN.TFRT.IN</td>\n",
       "      <td>7.671</td>\n",
       "      <td>7.671</td>\n",
       "      <td>7.671</td>\n",
       "      <td>7.671</td>\n",
       "      <td>7.671</td>\n",
       "      <td>7.671</td>\n",
       "      <td>...</td>\n",
       "      <td>7.136</td>\n",
       "      <td>6.930</td>\n",
       "      <td>6.702</td>\n",
       "      <td>6.456</td>\n",
       "      <td>6.196</td>\n",
       "      <td>5.928</td>\n",
       "      <td>5.659</td>\n",
       "      <td>5.395</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Angola</td>\n",
       "      <td>AGO</td>\n",
       "      <td>Fertility rate, total (births per woman)</td>\n",
       "      <td>SP.DYN.TFRT.IN</td>\n",
       "      <td>7.316</td>\n",
       "      <td>7.354</td>\n",
       "      <td>7.385</td>\n",
       "      <td>7.410</td>\n",
       "      <td>7.425</td>\n",
       "      <td>7.430</td>\n",
       "      <td>...</td>\n",
       "      <td>6.704</td>\n",
       "      <td>6.657</td>\n",
       "      <td>6.598</td>\n",
       "      <td>6.523</td>\n",
       "      <td>6.434</td>\n",
       "      <td>6.331</td>\n",
       "      <td>6.218</td>\n",
       "      <td>6.099</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Albania</td>\n",
       "      <td>ALB</td>\n",
       "      <td>Fertility rate, total (births per woman)</td>\n",
       "      <td>SP.DYN.TFRT.IN</td>\n",
       "      <td>6.186</td>\n",
       "      <td>6.076</td>\n",
       "      <td>5.956</td>\n",
       "      <td>5.833</td>\n",
       "      <td>5.711</td>\n",
       "      <td>5.594</td>\n",
       "      <td>...</td>\n",
       "      <td>2.004</td>\n",
       "      <td>1.919</td>\n",
       "      <td>1.849</td>\n",
       "      <td>1.796</td>\n",
       "      <td>1.761</td>\n",
       "      <td>1.744</td>\n",
       "      <td>1.741</td>\n",
       "      <td>1.748</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 58 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  Country Name Country Code                            Indicator Name  \\\n",
       "0        Aruba          ABW  Fertility rate, total (births per woman)   \n",
       "1      Andorra          AND  Fertility rate, total (births per woman)   \n",
       "2  Afghanistan          AFG  Fertility rate, total (births per woman)   \n",
       "3       Angola          AGO  Fertility rate, total (births per woman)   \n",
       "4      Albania          ALB  Fertility rate, total (births per woman)   \n",
       "\n",
       "   Indicator Code   1960   1961   1962   1963   1964   1965  ...   2004  \\\n",
       "0  SP.DYN.TFRT.IN  4.820  4.655  4.471  4.271  4.059  3.842  ...  1.786   \n",
       "1  SP.DYN.TFRT.IN    NaN    NaN    NaN    NaN    NaN    NaN  ...    NaN   \n",
       "2  SP.DYN.TFRT.IN  7.671  7.671  7.671  7.671  7.671  7.671  ...  7.136   \n",
       "3  SP.DYN.TFRT.IN  7.316  7.354  7.385  7.410  7.425  7.430  ...  6.704   \n",
       "4  SP.DYN.TFRT.IN  6.186  6.076  5.956  5.833  5.711  5.594  ...  2.004   \n",
       "\n",
       "    2005   2006   2007   2008   2009   2010   2011  2012  2013  \n",
       "0  1.769  1.754  1.739  1.726  1.713  1.701  1.690   NaN   NaN  \n",
       "1    NaN  1.240  1.180  1.250  1.190  1.220    NaN   NaN   NaN  \n",
       "2  6.930  6.702  6.456  6.196  5.928  5.659  5.395   NaN   NaN  \n",
       "3  6.657  6.598  6.523  6.434  6.331  6.218  6.099   NaN   NaN  \n",
       "4  1.919  1.849  1.796  1.761  1.744  1.741  1.748   NaN   NaN  \n",
       "\n",
       "[5 rows x 58 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = sm.datasets.fertility.load_pandas().data\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we construct a DataFrame that contains only the numerical fertility rate data and set the index to the country names.  We also drop all the countries with any missing data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>1960</th>\n",
       "      <th>1961</th>\n",
       "      <th>1962</th>\n",
       "      <th>1963</th>\n",
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       "      <th>...</th>\n",
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       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Aruba</th>\n",
       "      <td>4.820</td>\n",
       "      <td>4.655</td>\n",
       "      <td>4.471</td>\n",
       "      <td>4.271</td>\n",
       "      <td>4.059</td>\n",
       "      <td>3.842</td>\n",
       "      <td>3.625</td>\n",
       "      <td>3.417</td>\n",
       "      <td>3.226</td>\n",
       "      <td>3.054</td>\n",
       "      <td>...</td>\n",
       "      <td>1.825</td>\n",
       "      <td>1.805</td>\n",
       "      <td>1.786</td>\n",
       "      <td>1.769</td>\n",
       "      <td>1.754</td>\n",
       "      <td>1.739</td>\n",
       "      <td>1.726</td>\n",
       "      <td>1.713</td>\n",
       "      <td>1.701</td>\n",
       "      <td>1.690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Afghanistan</th>\n",
       "      <td>7.671</td>\n",
       "      <td>7.671</td>\n",
       "      <td>7.671</td>\n",
       "      <td>7.671</td>\n",
       "      <td>7.671</td>\n",
       "      <td>7.671</td>\n",
       "      <td>7.671</td>\n",
       "      <td>7.671</td>\n",
       "      <td>7.671</td>\n",
       "      <td>7.671</td>\n",
       "      <td>...</td>\n",
       "      <td>7.484</td>\n",
       "      <td>7.321</td>\n",
       "      <td>7.136</td>\n",
       "      <td>6.930</td>\n",
       "      <td>6.702</td>\n",
       "      <td>6.456</td>\n",
       "      <td>6.196</td>\n",
       "      <td>5.928</td>\n",
       "      <td>5.659</td>\n",
       "      <td>5.395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Angola</th>\n",
       "      <td>7.316</td>\n",
       "      <td>7.354</td>\n",
       "      <td>7.385</td>\n",
       "      <td>7.410</td>\n",
       "      <td>7.425</td>\n",
       "      <td>7.430</td>\n",
       "      <td>7.422</td>\n",
       "      <td>7.403</td>\n",
       "      <td>7.375</td>\n",
       "      <td>7.339</td>\n",
       "      <td>...</td>\n",
       "      <td>6.778</td>\n",
       "      <td>6.743</td>\n",
       "      <td>6.704</td>\n",
       "      <td>6.657</td>\n",
       "      <td>6.598</td>\n",
       "      <td>6.523</td>\n",
       "      <td>6.434</td>\n",
       "      <td>6.331</td>\n",
       "      <td>6.218</td>\n",
       "      <td>6.099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Albania</th>\n",
       "      <td>6.186</td>\n",
       "      <td>6.076</td>\n",
       "      <td>5.956</td>\n",
       "      <td>5.833</td>\n",
       "      <td>5.711</td>\n",
       "      <td>5.594</td>\n",
       "      <td>5.483</td>\n",
       "      <td>5.376</td>\n",
       "      <td>5.268</td>\n",
       "      <td>5.160</td>\n",
       "      <td>...</td>\n",
       "      <td>2.195</td>\n",
       "      <td>2.097</td>\n",
       "      <td>2.004</td>\n",
       "      <td>1.919</td>\n",
       "      <td>1.849</td>\n",
       "      <td>1.796</td>\n",
       "      <td>1.761</td>\n",
       "      <td>1.744</td>\n",
       "      <td>1.741</td>\n",
       "      <td>1.748</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>United Arab Emirates</th>\n",
       "      <td>6.928</td>\n",
       "      <td>6.910</td>\n",
       "      <td>6.893</td>\n",
       "      <td>6.877</td>\n",
       "      <td>6.861</td>\n",
       "      <td>6.841</td>\n",
       "      <td>6.816</td>\n",
       "      <td>6.783</td>\n",
       "      <td>6.738</td>\n",
       "      <td>6.679</td>\n",
       "      <td>...</td>\n",
       "      <td>2.428</td>\n",
       "      <td>2.329</td>\n",
       "      <td>2.236</td>\n",
       "      <td>2.149</td>\n",
       "      <td>2.071</td>\n",
       "      <td>2.004</td>\n",
       "      <td>1.948</td>\n",
       "      <td>1.903</td>\n",
       "      <td>1.868</td>\n",
       "      <td>1.841</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 52 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       1960   1961   1962   1963   1964   1965   1966   1967  \\\n",
       "Country Name                                                                   \n",
       "Aruba                 4.820  4.655  4.471  4.271  4.059  3.842  3.625  3.417   \n",
       "Afghanistan           7.671  7.671  7.671  7.671  7.671  7.671  7.671  7.671   \n",
       "Angola                7.316  7.354  7.385  7.410  7.425  7.430  7.422  7.403   \n",
       "Albania               6.186  6.076  5.956  5.833  5.711  5.594  5.483  5.376   \n",
       "United Arab Emirates  6.928  6.910  6.893  6.877  6.861  6.841  6.816  6.783   \n",
       "\n",
       "                       1968   1969  ...   2002   2003   2004   2005   2006  \\\n",
       "Country Name                        ...                                      \n",
       "Aruba                 3.226  3.054  ...  1.825  1.805  1.786  1.769  1.754   \n",
       "Afghanistan           7.671  7.671  ...  7.484  7.321  7.136  6.930  6.702   \n",
       "Angola                7.375  7.339  ...  6.778  6.743  6.704  6.657  6.598   \n",
       "Albania               5.268  5.160  ...  2.195  2.097  2.004  1.919  1.849   \n",
       "United Arab Emirates  6.738  6.679  ...  2.428  2.329  2.236  2.149  2.071   \n",
       "\n",
       "                       2007   2008   2009   2010   2011  \n",
       "Country Name                                             \n",
       "Aruba                 1.739  1.726  1.713  1.701  1.690  \n",
       "Afghanistan           6.456  6.196  5.928  5.659  5.395  \n",
       "Angola                6.523  6.434  6.331  6.218  6.099  \n",
       "Albania               1.796  1.761  1.744  1.741  1.748  \n",
       "United Arab Emirates  2.004  1.948  1.903  1.868  1.841  \n",
       "\n",
       "[5 rows x 52 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "columns = list(map(str, range(1960, 2012)))\n",
    "data.set_index('Country Name', inplace=True)\n",
    "dta = data[columns]\n",
    "dta = dta.dropna()\n",
    "dta.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are two ways to use PCA to analyze a rectangular matrix: we can treat the rows as the \"objects\" and the columns as the \"variables\", or vice-versa.  Here we will treat the fertility measures as \"variables\" used to measure the countries as \"objects\".  Thus the goal will be to reduce the yearly fertility rate values to a small number of fertility rate \"profiles\" or \"basis functions\" that capture most of the variation over time in the different countries."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The mean trend is removed in PCA, but its worthwhile taking a look at it.  It shows that fertility has dropped steadily over the time period covered in this dataset.  Note that the mean is calculated using a country as the unit of analysis, ignoring population size.  This is also true for the PC analysis conducted below.  A more sophisticated analysis might weight the countries, say by population in 1980."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/lib/python3/dist-packages/pandas/plotting/_matplotlib/core.py:1182: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  ax.set_xticklabels(xticklabels)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(0.0, 51.0)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = dta.mean().plot(grid=False)\n",
    "ax.set_xlabel(\"Year\", size=17)\n",
    "ax.set_ylabel(\"Fertility rate\", size=17);\n",
    "ax.set_xlim(0, 51)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next we perform the PCA:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "pca_model = PCA(dta.T, standardize=False, demean=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Based on the eigenvalues, we see that the first PC dominates, with perhaps a small amount of meaningful variation captured in the second and third PC's."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = pca_model.plot_scree(log_scale=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next we will plot the PC factors.  The dominant factor is monotonically increasing.  Countries with a positive score on the first factor will increase faster (or decrease slower) compared to the mean shown above.  Countries with a negative score on the first factor will decrease faster than the mean.  The second factor is U-shaped with a positive peak at around 1985.  Countries with a large positive score on the second factor will have lower than average fertilities at the beginning and end of the data range, but higher than average fertility in the middle of the range."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-7-79858d32f82e>:3: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  ax.set_xticklabels(dta.columns.values[::10])\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8, 4))\n",
    "lines = ax.plot(pca_model.factors.iloc[:,:3], lw=4, alpha=.6)\n",
    "ax.set_xticklabels(dta.columns.values[::10])\n",
    "ax.set_xlim(0, 51)\n",
    "ax.set_xlabel(\"Year\", size=17)\n",
    "fig.subplots_adjust(.1, .1, .85, .9)\n",
    "legend = fig.legend(lines, ['PC 1', 'PC 2', 'PC 3'], loc='center right')\n",
    "legend.draw_frame(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To better understand what is going on, we will plot the fertility trajectories for sets of countries with similar PC scores.  The following convenience function produces such a plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "idx = pca_model.loadings.iloc[:,0].argsort()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First we plot the five countries with the greatest scores on PC 1.  These countries have a higher rate of fertility increase than the global mean (which is decreasing)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def make_plot(labels):\n",
    "    fig, ax = plt.subplots(figsize=(9,5))\n",
    "    ax = dta.loc[labels].T.plot(legend=False, grid=False, ax=ax)\n",
    "    dta.mean().plot(ax=ax, grid=False, label='Mean')\n",
    "    ax.set_xlim(0, 51);\n",
    "    fig.subplots_adjust(.1, .1, .75, .9)\n",
    "    ax.set_xlabel(\"Year\", size=17)\n",
    "    ax.set_ylabel(\"Fertility\", size=17);\n",
    "    legend = ax.legend(*ax.get_legend_handles_labels(), loc='center left', bbox_to_anchor=(1, .5))\n",
    "    legend.draw_frame(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/lib/python3/dist-packages/pandas/plotting/_matplotlib/core.py:1182: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  ax.set_xticklabels(xticklabels)\n"
     ]
    },
    {
     "data": {
      "image/png": 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1AkiZbkytIIQHaa3ZUdLIe9vLWJRbTkO7jchAH64am8B1OYkMjz39aT60zYb10CE69+zFWniIriIjVHWVlJwQYkzBwfgkJ+MdF4s5Jhbv2BhjGxeLOTYWc3Q0Jp/zN75La42zubk7cDlqa7HX1mGvqaarpBTbkSN0lZTgbGk54XXm6Gh8MzPxy8oybiOz8E5I8Ei4qWzq5JUNxby+6QhNHTbGJIZw+4xULh8dh3cPtjr2ZRKyhDsSsvqrtlojUBWuNFqrmo4Yj4ckQdoFkHohpM40FlwVog8oqW/nvR1lvLejjKLaNnzNRnfgNeMTmJkR5fYXs7OzE+uBA3Tu3Uvnnr107t2L9cABtCtMKR8ffIYk45OSik9KinFLTcUnNQWv0P43rYPWGkdjI7aSErqOlGArOUJX8WE68/OxFhSA3ZhCxRQcjN+IEd3By3/sGLwTE8/b523vsvPO9jJeWltEUW0bcSF+3DothRsnJfeP5XvOgYQs4Y6ErP6iqx2OrD8WrCrzjMf9QoyWqrQLIW02hKfJdAqiz6hv62Lp7kre31HG5uJ6AKakhXPNuETmjY496eBp7XBgLSigY9cuOnJz6czNw3roEDiMyW5NISH4ZR0LFn4jsvAZkozy8jpvn82TnFYr1gMHjcDpulnz89FdXQCY4+MImDQZy+TJBEyehHd8fO/X5NR8nl/Ni2uK2FBYh8XHi+tzkrhjRuqAHbclIUu4IyGrr3I6jFnUj3YBlmwCR5exsnzS5GOhKn4smAbHLxbRP7R02vhkTxUf5Zaz9mAtdqcmPSqAa8YnsnBsPIlhX/6Fa6uqomPXLjpzc+nYlUvHnj3o9nbACFT+o0fjN2qkK1SNxDshvt+1TPU2bbNhLSykfetW2jdtpn3zZhyNjQB4JyVhmTSRgMmTsUyZgnd0dK/WsrusiX+uLeKjXeU4tWbeqFi+PTON8ckDa7iChCzhjoSsvkJrqDsERSvh0OdQvMZYbR6MaRXSLjRuyVNlnT/R53R0OVixv5qPdpWzIr+aLruThFB/rhgTzxVj4siKC+4ORVpruoqKad+2lY6tW2nfshVbeblxIm9v/IYPxz87G/8x2fhnZ+M9ZIgEqrOgnU6sBw/SvmkTbZs2075lC87mZgD8Ro0iaO4cAufMwXfYsF77+lY2dfLy+mJe33SY5k47E4aE8Z2ZqVycFYvXAJhvS0KWcEdClic1lUHRqmNXAba4ftGEJBmBKn22MWA9INKjZQrxVTptDlYdqGFxXgWf7q2irctBVJAv80fHccWY+O7lbbTDgTU/n/at24xWlm3bcNTVAeAVEYFlwgQsORPwHzMG3+HDMfn6eviTDUza4aBz/37a1q6jdcUKOnbtAsA7IYHAOXMImjMbS04Oyrvnx1G1We38d2sJL60roqS+gyERFu6alc61ExLwNffflngJWcKdQRuynE6NzenE7tDYHcf2bQ4ndqfG7nBic2jsTtfW4cThdP+1MpkUPmYTPl6mE7beXiZ8uxrwL9+A9+HVRrCqKzBeZIlwXQHougpQxlWJPqrT5mBlfjWL8yr5bJ8RrEIt3swbGcuVY+KZnBaByemgc98+2jdvoX3LFtq3beu+Ss47Ph7LxBz8c3KwTMjBJzXlvLdSaa3pbLXR2mil7bhbZ6uNU32HK8A3wBtLsA/+QT5YQnywBPlgCfbB28+r37W22WtqaFm5ktYVn9O2fj3aasUUFETgrFkEz59P4MwZPR64HE7Nsj2VPLfqELtKm4gO8uU7M9O4aXIyAb79byUJCVnCnX4VsqJSs/TCR1/B4dQ4NDicRvBxOsHu2j8ajE4MTsc95gpRpxOYzlUkTUwy7WOyaR9TTPvINJUC0Kr92GHKItd7LPmW8dQHpBPo50uQn5kQf2+ig32JCfYjNtjP2Ib44efdf//aE/1bR5cRrD7Oq2DF/mrauxyEWbyZNyqWy0fHMTkpGEf+fto2G11SHdu2d0/e6ZOSgmXiRCyTJmKZMOG8DMDurru1i9rSVupct8bqDiNQNVtx2r/8/e9rMaNO0YWltaar3c5X/cg0e5vwD/YhONKP8PhAwuMCCI8PIDwuAL+Avn+FnbOjg7YNG2hZsYLWz1bgaGjAKzyc4MsvJ2ThlfiNGtWjIVJrzbqCOv6+soD1h+oI8ffmtmkp3DYt5aznRvMECVnCnX4VskKShuvp97+Al0kduyl1wn1vL4XZZMLbbMLbpDB7KcxeR/dNmL0U3ibX1suE2fW4t5fr9a7nTvaaU/2Y8W6vJqByI4GVmwip2kRgSyEANi9/qkPHUR46nsOB4zjknUljlzFAuKXTftzWTmNHF50255fOHexnJjbECF0pEQGkRgaQGhVAWmQAiWGWATG+QfQdda1WVuyv5tN9Vaw+UEuHzUF4gA+XjoxlflYUYzursG7dQtumzXRs24bTNUjdJz0dy8QcAiZNwj8np9cHWIPxC7upuoPqI83UlbZ2B6u2pq7uYyzBPoTFWggI9e2+BR63bwnxwes05nZyOo1WsPbmLtqbrXQ0d9HebKO92Up7cxdNNR3Ul7dhszq6XxMQ4uMKXIFEJgUSNzSU4Ei/PtvypW02WtespenDD2ldsQLd1YVPaiohC68k5Ior8E5I6NH323Gkgb+vPMTyvVVYfLy4aVIy356ZRmyI5ydedUdClnCnX4WsPjUmS2toKILDG+DwemN6hXojVOETBEOmHluuJm4MeJ3eX7Naa1qsdqqaOqlqtlLZ3EmV61bZ1EllcydFtW20dNq7X+PjZSI5wkJqpBG60qMDGR4bREZ0EP4+0gImTk9BdSuf7qvi071VbDvSgNYQF+LHRZmRzLe0kl6WT+eWLbRv3do9Y7rP0HQCJk3CMmkSlokTMUdEnJdaW+o7KctvoHR/A6X5DbQ1WgEweSnC4gKITAgkIjGwe2sJPo8TjTo1LQ2d1Je3GbcKY9tQ0Ybd9QdUQKgv8RmhxA8NIS4jlPDYgFO2onmKo7mZ5mXLaP7gQ9pdP3stOTmE3nA9QZde2qMTuOZXtvDsqkN8uKscL6W4cVIS98weSnRw3w1bErKEOxKyTpfTCTX7jEB1eL2xVE1LhfGcfxgkT4MhrltsNnj13vgCrTX1bV0U1rZRVNNmbGtbKaxp43BdO10O4we5ScGQiAAyY4LIjA1ieKyxHRIRIC1fgk6bg22HG1h1oIZP91ZRWGt08Y2KDeTqoDamtBwm+EAe7du242wyrnT1SUnpnnvJMmkS5sjzc1FGR2sXZfmNlOY3ULq/nqbqDgD8Ar1JzAwjcXgYMakhhMVa8DL3zdnGnU5NQ0Ub5QcbKS9opOJgY3drm2+AmfihocRnhJIyOpLQmL43r1RXaRnNH31I0/sf0HX4MF4REYRe/zXCbrgB79iem/S4pL6dv68s4H9bS/EyKb45dQh3X5BORGDfuyBCQpZwR0LWyVhboHQrlGw25qgq3QpW15QKQfGuQOVqrYrMhD6yqKvDqTlc10Z+ZQv7K1vIr2whv6qF4rq27rEk/t5ejIwPZnRiCNmJIYxOCCE1MlCC1wDndGr2VjSztqCWtQdr2VJcj9XuxFc5WRjQykVdZaSW5ePctbO7pcp7SDKWia75lSZNwjsm5rzV29rQyaEdNRTuqKG8oBE0ePt5kZARSkJmGInDw4mI75stQKdDa01zbQflB5u6Q1dTjREeQ2MspI6JJDU7kpi0EEx96DNqp5O29Rto+M9/aF25Ekwmgi6+mPBv3IR/Tk6PdYMermvj6c8O8v6OMvy8vfjW9BTunJlOiKXvjHGTkCXckZAFrq6/YijdYgSqkk1QtQe0E1AQnQVJk4zbkGkQOqTfXf3X0eXgYLURvPaWN5NX1sSe8qbu8V8BPl6MjA/pDl5jEkMZEmHps+NGhHtaaw7XtbOhsI61B2tZf6iWhnYb3g4bc1Utc7rKyagqwD//2MSfPqmp3V1/lokT8Y7p/TFVx2uq6eDQjmoKd9RQVWTM6RQeH0DauCiGjIwgakjQaY2d6q9a6jsp2lVLcW4NZfmNOJ0a/yBvhow2AlfSiHC8ffvOEICu0lIa3niDxrffwdnUhO+wYYR94xuEXLEAk6VnWuMKqlt56tMDLMqtIMjPzLdnpHH7jBSCTrJawPkkIUu4MzhDVlcblO8wWqlKtxi3thrjOZ9ASMwxZlVPmgSJE42lawYgu8PJoZo2cksb2V3WRG5ZE3vLm7HajeAVZvFmTFIoY4+7hVr6z5U/g43TqTlQ3cLmovruW3WLFX9bJ9M6y5lrKyez+hCWwnxwLb/im5GBf84EY1xVTg7mqKjzXndTTTsHt1RzaEc1tSVGC1pUchBp46JIHxdFWOzgnHzX2mHnyJ46inbVcmRPHdZ2O17eJoaMimDYxBiGjI7A3EeuOnZ2dNC8eDH1r/0H6759eIWGEvbNWwj/xjfwCumZn5/7K5v58/IDLNtTRajFm3suHMotU4d49MprCVnCnYEfspxOY0B62VZXS9VmVyuV6+qf8PRjYSpxIsSMHNTL1NgdTg5UtbKzpJGdJQ3sLGnkYHVrd1djamQAY5NCGZMYQnZSKFlxwTK9hId02hzsrWhma7ERqLYUN9DU3kVURyNTO8qY0VlOWnUhASWFxveBlxd+I0cak39OzMF/3DjMYZ5Z5qSzzUbBtmoObKqk4pDRDR+TGkz6uGjSx0cRHOnvkbr6KofDScXBRgp31VKwrZqO5i58/LxIGxfFsImxJGSG4lRODjUewqmdJAQlEOwTfN7r1FrTsX07dS/+k9bPP8dksRB649cJv/XWHrvSNLe0kT98coDVB2pICPXn/kuHsXBMgke6VCVkCXcGXshqq3MFqq3GtmzbseVpfAIhYcKJocoS3vuF93MtnTbySpvYUdLoCl+N1LQYV3OZTYrM2CCyE0MZmxRCdmIoGdGBmAdwl44nOJyag9Ut5JY0sbO0kdzSRvZXtKDtdtKbyphhrSCntYTEsgK8G2oBUBaLsTzNuLFYcnKwjB2LKcBzrUIOu5PDu+vI31RJcV4tTrsmLC6AzMkxDJsUS1B4372KrC9xOpyU5jeQu+EwJbkNOK2KLt8OCiK2sz98E9WBh0FBsE8wCYEJJAYlGtvARBKCEhgaOpTYgJ4bqH4ynfkHqHvhBZoXL0aZzYRcczURd9yBT1JSj5x/XUEtjy/Zx+6yZkbGB/PQZSOYkXF+V8eQkCXc6d8hq7MZKnONrr/ynUaoaig2nlMmYyxVwgSj+y8hB6IyB3UrVU/RWlPZ3MmukiZySxvJLW1iV2lj97QS/t5ejIgLYmR8CFnxwWTFBZMZGyQtXqep0+agoLqV/ZUt7K9oJre0ibyyJjq67ES3NzC2tYypXZVk1B8mrKwQk6vrzxwfh2XsOPzHj8d/3Fj8MjNRZs/Ooq21pqq4mfyNlRzcWoW1zY5/kDfDJsaSOSWWyKRAGfd3mjrsHbx94G22Vm4lrzaPmo4avJxmUptGM7bpAiKqh6AcJrzDNWpEI9VJBymxF1PWUkZ5azldzmPzho2PHs/8tPlcMuQSQv1Ce7XuriNHqHvxnzS99x7a6ST48suJvPM7+GZknPO5nU7NR7nlPLk0n7LGDmZmRPLQZSPIij8/rXgSsoQ7/StkZQ/XW5/7/rFQVXfw2JPBiZAwzghTiTkQNxZ8Az1V6qDjdGqK69q6A9eesmb2VjTTajWCl5dJkR4VQFZcMCPjQxgeF8TQ6EBig/vupIy9zeHUHKlvJ7+y+cQrQWvbcGqw2DoY2VzGDHslIxtLiSk/hLmpAQDl64tfVhb+2aPxHzsW/3HjevQy+nPV1mQlf2Ml+zdU0FDZjpe3ibQxkWROiSNpRBgmaek8IytLVvLE5icoay0jOSiZ0VGjGR05muzIbDLDM/Hx8sHaYadwRw371pVTcagJL7OJ9PFRjJyZQEx6ELUdtZS1lrGtahuLChdR2FSI2WRmRsIMFqQt4ILEC/Az915roq2qmvqXX6bhrbfQHR0EX7GAqHvvxScx8ZzPbbU7eHXDYf6yooDmThtXj0vgx5dkkhDau93OErKEOx4LWUqpTOCt4x5KA36htX7qZK/JiffSW+8MNKZQiB8H8WONbdxYCDz/A3bFqTmdmpKGdvaWG4FrT3kze8ubqWzu7D7G4uNFWlQA6VGBx27RAaREBAyIli+tNXVtXRTWuOYyO25usyPHzWnmpR1MpZEp1goyG44QXXoIn/IjHB0M55Oain92Nn5jsvHPHoNf5rBeWcj3XDhsTopya9m/oYIje+qMyUzTQxg+NY6hE6Lx8e9/a9N5WmlLKU9sfoJVpasYGjqUn07+KRNjJ7p9XV1ZK3vWlJO/qZKuDjthcQGMnBFP5pRY/AK80Vqzv34/Hxd+zOKixdR01BDgHcDFQy5mQdoCJsVO6rU/fuwNDdS/9BL1/34V7XQSdsMNRN59V4/MudbUbuPvqwr417piTAruuXAo35mV1ms/SyRkCXf6REuWUsoLKAMma60Pn+y4nFHD9NYNayDo/M3VI3peXauV/MoWDtW2cai6lUM1xkSqZY0dJxwXGehLXIhf9y02xJ/4UGNNx7gQf8IDfQjw8ezCvJ02B5VNnVQ0dVLR1EFFU6frvrF/pL79S7PzDwn3J9unk+zWMlKri4koOYhXQT660wifXmFhJwQq/9GjeuwKrZ6mtaa2pJV96ys4sKUSa5udgFBfhk+JZfjUuD45qWZ/YHVY+dfuf/Fi3ouYlIn/N+b/8Y2sb+BtOrNgbbM6KNhWxe7V5VQXN+PlbSIjJ5rs2UlEJQcB4HA62FK1hUWHFvHpkU9ps7WRGZbJ7aNu55KUSzCbeicc26qqqP3b32l85x2Ury8Rt91G+O3fwivw3HsgShva+e3ifSzOqyQ53MLPF2Rx0YjoHv9ZISFLuNNXQtYlwCNa6+mnOq5PLasjelx7l52i2jYO1bRRWNPaHV4qmzopb+o4Iawc5e2lCPH3IdTiTai/N6GWY/sBvmb8vL3wNZu6t77eJvzMXvh6mzCbTF9aONzmMO7bnU66HJrmDptx67TR1GHcmjvs3ftNHbYv1RRq8XYFQT8SwyxkBCqG1rtapw7upTMvD0eta3C6j4/R7TcmG7/sbPzHjME7IaHPd6F2ttrI31zJvvUV1JW24mU2kTY2kuFT40gcEd6nJs/sb9aWreXxTY9zpOUIl6Zcyv059/fIQPWakpbu1i271UF8RijZcxJJHRPV/e/Vae9kafFS/rX7XxQ2FZIQmMC3Rn6LhUMX9lpXorWoiJqnn6Fl6VK8wsKIvPsuQm+8sUeW7FlXUMsjH+6hoLqVCzOjeOSKkaRG9tzFHxKyhDt9JWS9BGzXWv/1VMdJyBrcWq12Y/1GV0tRQ3sXDe02GtttNHV00dBmo7HDRpPr8Q6bw/1JT4Ov2USIvzfB/t6EuG7BfmZC/L2JDvbrDlSxIX7EWsyowgI68nLpzNtNR14uXYcKj3X7paQcC1RHu/16cP233uR0akr31bN3XQVFuTU47ZroIUGMmBbH0JwY/AL6Vvdlf9PQ2cBjGx7j0yOfkhKcwk8n/5Sp8VN7/H2s7Tb2ra8g9/NSWuo6CYrwY/SFiWRNj8PXNZu6UztZWbKSf+b9k9zaXML9wrl5xM3cMPyGXpsaoiNvNzV//hNt6zdgjo8j5v77CbrssnP+g8PmcPLK+mKe+vQgXXYnd8xM5XuzhxLge+4tdBKyhDseD1lKKR+gHBipta76iufvBO4ESE5OnnD48El7E4U4gdOpsdqdWO0OrHYnnTZja7U56bQ7sDmceHuZ8PYyYTYpY+ul8Da5tl4mgvzMJx3PoR0OuoqK6MjbTWdeLh15u7Hu34+2Ga1bXuHh+I0eZUyjkD0G/+zRfbbb71SaajrYv6GC/RsqaG2w4hfgzbDJMYyYFkdkYpCnyxsQGjob+PYn36a4qZjvjv0u38z6Jj5evRu+nU5N8a5adq0oofxgI2ZfL0ZMiSV7TlJ3N6/Wmq1VW/nn7n+yrmwdAd4BXD/seu4acxcB3r0zHUjb+vVU/f4PWPftw5KTQ8zDP8Nv+PBzPm91SydPLNnPu9vLiA3246fzR3BFdtw5hTgJWcKdvhCyFgL3aK0vcXestGQJT7JVV9OZm0vHrlw6cnPp3L0bZ5uxqLLJYsFv1CgjVI0ejf/o0Zjj4/t8t9/JdHW6rlRbX0H5wUaUgqSsCEZMiyM1OxIvb7k6sKccDViHmw/zlzl/6ZXWK3dqjrSQu6KEA1urcDo0aWOjmDBvCNFDjrVa7a/fz0t5L7Hs8DKuzbiWX0z9Ra/Vox0OGv/3NjVPPYWjuZmwr99A5Pe/3yOT5247XM8jH+5hd1kzMzMi+fVVoxgScXaBUUKWcKcvhKw3gWVa63+5O1ZCljhfnB0ddO7Z0x2oOnJzsVdUGE+azfhlZhrdfqOz8R89Cp/UVJRX/74aUmtNRUEj+zZUUrCtGrvVQUiUP8OnxjF8aiyBYTJZaE/rCwHreO3NXeStLCVvZSnWdjtJI8IYPy+FhGGh3X8wPLbhMd4veJ/F1yzu9UlNHY2N1Pz1bzS88QZegYFE/fAHhF5//Tl/rzmcmtc2Hub3y/KxOZzcOzeD78xMw8d8Zn88SMgS7ng0ZCmlLEAJkKa1bnJ3vIQs0Ru000lXYeEJgcp64AA4jDFd3gkJJ46jyhqByW/gBI6W+k7yN1awb0MlzTUdePt6MTQnmhFT44hND+m3rXF9XUNnA9/55DsUNxf3iYB1vK4OO7vXlLHz0xI6mruISQ1mwrwhpIyOpLy9nAXvLuCG4Tfw4KQHz0s9nfkHqPrtb2nftAnf4cOJ/dlPsUx0P5WFO5VNnfzyoz0s2V3JsJhAfnv1aHJSTn8VEAlZwh2Pt2SdCQlZoifYGxro2LmTjh07jW6/vLxj3X6Bgfhnj+4OVP7Zo3tk/p6+xtph59D2ag5srqTsQCNoSMgMY8TUWNLGRePt279b5fq64wPWM3OeYVr8NE+X9JXsNgf711ew/ZMjtNR1Eh4fwPhLh/Ba199ZcngxS69dSqT/+fn+0FrT8slyqn73BPbyCoKvuIKYB3+COSLinM/96d4qHvlwD2WNHdw4KYkH540gxOL+Qg4JWcIdCVliQNNOpzE4fccO2rfvoGPHDrqKiownzWb8hg07Nh/VmGx8UlJQpoE53shhc3J4Tx0HNldSnFuHw+4kJNqfzMmxZE6OlUWZz5PGzkZjkHsfD1jHczqcHNxazfZlh6kvbyMg0puPwl5i+szR3DfpvvNbS0cHdS+8QO0LL+JlsRD9f/9HyDVXn3OLa5vVztOfHeSfa4sIs3jz8wVZXDnm1OMqJWQJdyRkiQHF2dVFZ14e7Vu30bF9Ox07d+JoMnqivUJD8R83Dv9x47CMG4vfqFGY/Ad2sNBOTcWhJvI3V3JoWzXWdmPtwIycGIZNjiV6SJB0B55H/TFgHU87NUW7atm8qIi6slYa/au5/GuTGDslFXWe50azFhRQ8cijdGzbhmXyZGIffQTf1NRzPu+e8iZ++t5udpU0cmFmFL+5evRJl+eRkCXckZAl+jVnWxvtO3fSvnUrHVu30bFrF9q1YLJPWhr+48dhGTce/3Hj8ElNGRSB4ugs7Ae3VHFwWxWt9VbMPibSxkUxbFIsScNl7UBPOCFgzX6GaQn9K2AdTzs169bm8fl7eYR3xBEeH8DE+amkj4s6r2FLO500vv021b//A9pqJfK7dxNxxx3nPPecw6n594Zifr8sHwU8eNlwvjF5yJcm2ZWQJdyRkCX6FWdbG+1bt9K2cRPtW7fSuXevMUDdZMIvKwtLTg6WnAn4T5jQI5d79yf15W0c3FrFwa1VNFV3YDIpkkeGMzQnhtQxkfj4ydqBnmJ32rlj2R3sqdvT7wPW8e77/D7Kd7Uyv+E2mqs6iUgIZNIVqaSOiTyvf9DYa2qoevxxmhcvwWdoOnGPPYZl/PhzPm9JfTs/fS+PNQdrmZQSzhPXjiYt6tiyPxKyhDsSskSf5uzqomPnTto3bqRtw0Y68vLAbkd5e+M3JtsVqibiP3YsXoG9MzliX9ZU00HBtioObqmmrqwVpYwB7Bk5MaSNi5JZ2PuIZ7Y/wwt5L/DbGb/livQrPF1Oj9lfv5+vffQ17sn+HrO7FrLl4yKaqjuISg5iysI0krLCz2vYal21ispfPoatvJzQr99A9P0PnPPPBa01b28r5VeL9mK1O/nRxcP49oxUzF4mCVnCLQlZok/RWmPdv5/WtWtp37CR9u3bjYWTTSb8Ro0iYMoUAqZMxn/8+AE1jcKZaK7r4NC2Ggq2VVF9uAWA2LQQMibGkD4+ioAQXw9XKI63rmwdd396N9dmXMuj0x71dDk97nuffY+dNTtZdu0y/E3+HNhcxeZFRbTUdRKfEcrUq9OJTTt/Kx0429upefoZ6v/9b7zj4oj77W8ImDLlnM9b3dzJzz/YzbI9VYxKCObJa8cwMiFEQpY4JQlZwuMczc20rV9P6+o1tK1Zg72mBgDfjAwsU6cQMGUKlokT8QoavEu4tDZ0cmh7DQe3VlFV1AxA9JAghk6IIX1CFMERA3sAf39V1VbF1z76GpGWSF6//PVeW2TZk/Jq8rhp8U38aMKPuH3U7YBxJeueteVsXVJMR3MXKdmRTL4yjcjEQDdn6znt27dT8dBP6Tp8mLCbbiT6xz/GFHDurd1L8ir4+Qd7aGzv4tDj8yVkiVOSkCXOu+7WqtVraF2zmo4dO8HhwBQcTMD0aQTOnEXgzBmYo6I8XapHtTVZObTdaLGqKDCukIxMCmTohGiGTogmJMri4QrFqRwdh7Wvfh9vLniTtJA0T5fUa+5afhf76/ez9Nql+JuPBX6b1cGuFSXs+OQIXZ12MnJimHxl6nn7v+vs6KDmqaeNVq2EBKNVa9Kkcz5vY3sXjy3ay59vGCchS5yShCxxXmibjfatW2n59DNaVqzoXqLGN2uEEaoumIV/djbKPLgHZ3e22SjcYbRYleU3oDVEJAS4glVM98K9ou87Og7r8ZmPsyBtgafL6VXbqrZx29Lb+MnEn3Bz1s1fer6zzcaOT46Qu6IEp0OTNSOeiQtSsQT37iLYR7Vv20b5T3+K7fARwm6+mej7foTJcu7fSzImS7gjIUv0GmdbG61r1tLy2We0rlqFs7kZ5edHwPTpBM2ZQ8DMGXhHR3u6TI/r6rRTtKuWgq1VHNlbj9OhCYn2JyMnhoycGMLjB9+A/v7u6DisazKu4ZfTfunpcs6Lby39Fkeaj7Dk2iX4eH11eGprsrJ1cTF715Tj5WNi/KVDGDs3CbNP768w4OzooPrPf6bh36/inZxM/G9/gyXn3PKRhCzhjoQs0aMcjY20fPYZLZ8sp23DBnRXF16hoQTOnk3QRXMJmDZtwE8AejrsXQ4O76nj4JYqivPqcNicBIb5GsFqYgyRSYGDYk6vgejoOKwI/when//6Cd1nA9mG8g3cufxOfj7l51yfef0pj22obGP9u4cozq0lMMyXKVelM2xizHmZY6tt82YqfvYwttJSwm+7jagf/gCT79ldLCIhS7gjIUucM0dzMy2fraB5yWLa1m8Aux3vhASCLrqIwLlzsIwfP+i7AQEcDicle+sp2FpN4a4abJ0O/IO8GTohhoycaGLTQs77rNmiZw2mcVhfpLXm5iU3U9tey6JrFuFtcj99SFl+A+veKaDmSAvRQ4KYfl0G8RmhvV6rs72dqt//nsY33sQ3Yyjxv/sdfllZZ3weCVnCHQlZ4qw4Wltp/fxzmhcvoW3tWrTNhnd8PMGXX0bQvMvwG5klLTGA06kpP9jIwS1VHNpRjbXNjq/FTNq4KDJyYkgYFiqzrw8gA3U+rNO1unQ193x2D49Ne4yrM64+rddop+bA5ko2flBIa4OVtLFRTL06/byMP2xds4aKn/4Me2MjUffcQ8S37zijPwglZAl3JGSJ0+bs7KR15SqaP15E66rV6K4uzLGxBM+bR/Bl8/DLzpZghRGsKg81UbC9mkPbqmlv7sLs60VqdiTDJsaQlBWOl1mC1UAzGMdhfZHWmhsW3UCbrY0PrvoAs+n0A4uty8GuT0vYtuwwTruTMXOTyLk8pddXKnA0NlL52GM0L16C/5gxxP/uCXxSUk7rtRKyhDsSssQpabudtg0baV60iJZPP8XZ1oZXVCTB8y4j+LLL8B87BmWSwOB0aioKGjm0rZpDO2pob+7Cy2xiyKgIMibGMGR0BN7nYXCv8IwmaxNXvn8l4X7hg2oc1lf57PBn/HDlD3li5hPMT5t/xq9va7Ky8YNC9q+vICDUl+nXDWXohOhe/wOu6eOPqfzlY2ibjZj/e4DQr3/d7XtKyBLuSMgSX6K1pmPnTpoXfUzz0qU46uowBQURdMnFhCxYgGXSJJSXBAanU1NxsJGC7dUUHg1W3kawGjo+miGjI2S9wEHikfWP8EHBB7wx/w1GRIzwdDke5dROrv3wWrTWvLvwXUzq7P4IqyxsYtUb+dSWtJKQGcasrw8jPK53r7S1VVVR8dOf0bZuHQEzZhD3m9/gHXPyK6AlZAl3JGSJbtaDB2la9DHNixZhKytD+foSOHs2IQvmEzBrFqZzXNl+IHA4nJTnN3JoRzWFO2voaLFh9jYxZHQE6eOjGTJKgtVgs6VyC7cvu51vjfwW9+Xc5+ly+oTFhYv5yZqf8OcL/8xFQy466/M4nZq9a8rY+EEhtk4H2XOTmDi/d7sQtdY0vvkmVb97EpOfH3G//Q1Bc+Z85bESsoQ7ErIGOVtZGU2LF9O86GOs+fng5UXAlCkEX7GAoIsuwivw/C2D0Vc5bE5K9tdzaHs1Rbm1WNvsmH29SBl1LFh5+0rL3mBkdVi57sPrsDltvHvlu1i8ZbJYAIfTwcIPFmIxW3hrwVvn3NXX0dLFhvcPsW9dBQEhPky7bigZOTG92oVoLSyk7P77se7dR+jXbyDmJz/50vQzErKEOxKyBiF7fT3NS5fS/PFiOrZtA8B/7FiCFywgeN6lmCMjPVyh59m6HJTsqadgezWH82rp6nTg428mJTuC9HHRJGeFn5cJFEXf9tcdf+W53Od47qLnmJYwzdPl9CnvF7zPz9f9nL/N/RuzEmf1yDkri5pY/cYBao60kJAZxoU3ZfbqVYjOri5jWZ6XXsInPZ2EP/4Bv+HDu5+XkCXckZA1SNgbGmj97DOaly6jbcMGcDjwzRhK8IIrCJ5/OT6JiZ4u0eM6WroozqulcGctJfvqcdic+AV4kzomkvTx0SQOD5OrAkW3goYCvrboa8xLmcfjMx/3dDl9js1pY8G7C4j0j+S1y1/rsVano12IG94vxGFzMuGyIYy/ZAhe3r33vdm6bh0VDz6Eo7GRqB/fR/g3v4kymSRkCbckZA1g9oYGWpYvp2XpMto2bQKHA++kJGPKhQUL8Msc5ukSPa6ppoOiXTUU7aqloqARrSEwzJfUsVGkjokkIUPmsRJf5tRObl1yK0XNRXx41YeE+4V7uqQ+6b/5/+VXG3/FC5e8wJS4KT167rYmK2v/d5CCrdWExli48BuZJAwL69H3OJ69oYGKnz1M64oVBEyfTtzjv8UnJkZCljglCVkDjL2uzliEedlS2jZtNoJVcjLBl15K0LxL8csa3JOEOh1OKouaObK7juK8OurKWgFjEebUMVGkjY2SJW2EW0fDw6+n/5qFQxd6upw+y+qwcvk7lzMkZAgvXfpSr7zH4d11rHojn5a6ToZPi2P6NUPxC3Q/2/zZ0FrT+NZbVD3xO0z+/mRu3CAhS5yShKx+TjuddO7dR+uqlbSuWk1nXh5ojc+QIQTNm0fwvEvxHT58UIeGtiYrR/bUc2RPHSX76rG221EmRVx6CKljIkkdE0lIlAxYFqenur2ahe8vZGTESF645IVB/b11Ol7d+ypPbnmSV+a9wviY8b3yHrYuB1s/LmLn8hJ8LGamXzeUzMmxvfZvYz10iLIf30/6B+9LyBKnJCGrH3K0ttG2fh2tq1bRuno1jppaUAq/0aMJvGAWQXPn4puZOWh/+DvsTqqKmjmyt44je+qpOdICgCXEh+SREQwZGUHSiDB8Lb3z164Y2O5beR+rS1fz7pXvkhyc7Oly+rwOewfz3pnHiPARPHvxs736XnVlraz8z34qC5tJyAxj9s2ZvfYHlO7qwuTrKyFLnJJM6NMPaJuNjrzdtG/eTNvGjbRv2wY2G6agIAJmTCfwggsInDkTc0SEp0v1CKdTU1vSQml+A2X7GygvaMTe5USZFLFpwUy5Ko3kkRFEJko3oDg3K46sYPnh5fxg/A8kYJ0mf7M/38z6Jk9tf4rdtbsZFTmq194rIiGQa+6fwJ615ax/t4A3H9vM5IVpZM9JwtTDi68rmTdQnAZpyeqDtN1O5969tG3aRPumzbRv345ubwfANzOzO1hZxo1DeQ++1hitNQ2V7ZTlN1C6v4GyAw1Y2+0AhMVaSBweTmJmGAmZodJaJXpMa1crCz9YSLBPMP+94r94m+T/1ulq7Wrl0ncuZULMBJ6Z88z5ec+GTla+ns/hvDpiUoOZfctwIuJ7dt4/ubpQuCMtWX2Ava6Ozj176Ni9m85dubRv3YqzrQ0An6HphF51FZbJk7FMmog5rPeunumrnE5NXWkr5QcbKS9opKKgkY4WGwBB4X6kjY0iITOMxOFhBIT4erhaMVD9ZcdfqGmv4U8X/kkC1hkK9Ank5hE38/ddfye/Pp/M8Mzef88wP+b/v2wObqlizVsH+e9vtpBzeQrjLx0iU7GI86ZftWQljEjQd7x4B3an3bhpOzanrfu+RmPChEmZUEqhUCfse5u8CfAOOOkt2CeY+MB4ovyj8DL1zkST9vp6OvfsORaq9uzFXlFhPKkUPqmpWCZOJGDyJCyTJg3KiUHtXQ6qj7RQUdBI+cFGKg41Yet0ABAc6Ufc0FDih4aSkBlKcKS/dAGKXrenbg83LrqRGzJv4GdTfubpcvqlJmsTl75zKTMSZvCHC/5wXt+7o6WLNW8d4ODWaiISAph9ywhiUoLP+bzSkiXc6VchKyg9SE96YhLeJm/MJjNmZTa2rptCodForXFqJ06caK3RGPe7HF2029pps7fRbmtH89Wf3WwykxCY0H1LDErs3g4NHYqvl/vWEnt9PdaCAroKC7EWHKKr8BDWgkPYq6u7j/FJScFv5Ej8Ro3Cb2QWfllZg24ZG+3UNFa3U1XUbNyKm6krbcXpNP5twuICiM8IJX5oCHFDQwkK9/NwxWKwcWontyy5hbKWMj66+iOCfII8XVK/9dS2p3hp90u8f9X7pIWknff3L9pVw6rX82lv7mLMRclMviL1nFZukJAl3OlXIasnx2Q5tZMOewdttjbabEboarQ2UtZaRmlrKWUtZd37Tdam7teZTWYywzIZHT6ScV4pZHaGEdHkxF5ejq2sjK6iYqyHDuFoaOh+jcliwSc9Hd/0dHwzMoxgNTILr6DB98O6rclK9eEWqoubqSpqoqq4ha4OYzyVt68X0SlBxKSEEJMaTNzQEPwDZXCp8Kyjy8P8ZsZvuDL9Sk+X06/Vd9Zz6duXcknKJfxmxm88UoO1w876dwrYu7ac0BgLc28dQWxayFmdS0KWcGfQhqxT0VrjbGnBVlGJvaqS1tLDNJQU0FZaTGdZKV5VdQQ2WDE7T3xdV4g/pqREwkdk45c+FN/0ofgOTccc23vztfRl1g47NYeN1qmjwaq1wQqAUhCeEEhMajAxKcHEpAYTFhvQ41cACXEumruaueK9K0gOSuaVy17BpGQsz7l6csuTvL7vdT666iOSgpM8VkfJ3npWvLqPtkYrYy9OZtIVqZi9z6xVS0KWcGfQDXzXdjv2ujrsVVXYq6uxVVVhr6rGXl2NvboKW0Ultqqq7qv5uilFSGQkkQkJeE8ei1d8HE3hvhRb2tjtXc0WXcS+9kKcuoggn1pmxHcxKyGSmeEWQgZBwLJ22KktaaHmSAs1JS1UF7fQWHXsaxgc5U9cegjRKcFEpwQTlRSEt68ssCz6tn/s/AcNnQ08e9GzErB6yG0jb+Ot/W/xz93/5NFpj3qsjqSscG78xWTWvVPAjk+OUJxby9xbs4hJPfexWkIcNaBasnRXF7bqGuyVFdgqq7BXVXa3Rtkqq7BXVmKvqwPnF5qgvLwwR0VhjonGOzYO79gYzDGxeMfFGtvYGMxRUW6nS2iztbGxYiOrSlaxunQ1dZ11mJSJsVFjuTDpQi5IvIDUkNR+36rV0dpFzZEWaktajVB1pIWmmo7u5wNCfYlKDiImJYjoIcFEDwnutWUuhOgtBxoOcP1H13PdsOt4eMrDni5nQPn1xl/zzsF3WHz1YuIC4zxdDkf21PH5a/tpa7Qy7pIhTFqQeloLTktLlnCnX4WsCWPH6rWv/QdbRTn2igps5RXYKo7eyo2Zz7/AFBiIOTYG75hY1zYGc3Q05mhj6x0TjVd4OMqrZ1tVnNrJnto9rCxdyerS1eyv3w9Aakgq12ZcyxXpV/T5RWW1U9Nc10FtSSu1pa1GS1VJK22N1u5jgiP9iEoKIjI5iKjkIKKSgrAEyzgq0b9prbl92e0UNBaw6OpFhPie3Zgd8dXKW8uZ/+58rht2XZ+5WtPaYWfd2wfZt66CsLgA5t7q/gpECVnCnX4Vskb5+ev/paR031f+/njHxeEdF4c5LtbYj409rhUqps9crVfZVsmqklV8XPQxO6p3YDaZuSj5Iq4ddi2TYid5vCvC3uWgrryNurJjgaqutJUu19QJyqQIi7UQmRRIZEIQUcmBRCYF4RcgLVRi4FlStIT/W/1//GLqL/jasK95upwB6ZH1j7Do0CKWXruUKEuUp8vpdni30arV3tzF+EuTmTg/9aTzaknIEu70q5A1NjVNr3nxBVeoisMrNLRfdr0VNBTwzsF3+PDQhzR3NZMUlMQ1Gddw1dCriPTv3XmxtNa0Nli7w1RdaSt1Za00VrVz9L+C2deLyIRAI1AlBhKVHER4XMA5XeosRH/RbmvniveuINISyeuXv95rc+YNdkeaj3DF+1dw84ibeWDiA54u5wTWdhtr/3uQ/RsriUwK5KLbsohI+PIf7BKyhDv9KmQNtGV1rA4ryw8v5+0Db7OtahtmZWZ28mxuH3V7j6zvZe2wU1/W2t1CVVfWSn15W/cSNGB090UkBBKRGEikaxsS6Y+Sq/zEIPXnbX/mpd0v8Z/L/0N2VLanyxnQHlrzEJ8d+Yyl1y7tk8MnCnfWsPI/+7F22Jl8RRpjL04+4QpoCVnCHQlZfURhUyHvHniXdwvepaWrhenx07lrzF2Mix7n9rX2LgcNle3Ul7dSX9FGXZkRqo5OlwDg4+dFeHwgEQkB3aEqIiEQX/9Bd4GpECdV1FTENR9ewxVpV/DY9Mc8Xc6AV9hYyFUfXMUdo+/gB+N/4OlyvlJHSxerXs/n0I4aYtNCmHvbCEKjLYCELOGehKw+prWrlTfz3+Tfe/5Ng7WBSbGTuCv7LibGTsRp1zRUtVNf0Up9WRv1FW3Ul7fRXNvR3dVn8jLGTp0QqBICCQzz7Zddq0KcL1pr7v70bvJq8vjo6o+I8I/wdEmDwo9X/ph15etYdu2yPnuBgdaaA5urWPPWARx2J9OuGcqoWQmYvEwSssQpSTNGHxPoE8i3sm7nspCrWLJ9BTt27OXNVWtZ3VWGf1sIR1cCUiZFaLQ/kUmBDJsUQ3h8IOHxAYRE++PlJfP5CHGmVpSsYH35eh6c9KAErPPozuw7+eTwJ7y+73W+O/a7ni7nKymlyJwcS8KwMD5/dR+r3zxA4c4aT5cl+gEJWR7U1Wmnsaqdhsp217ate9/p0EAkI9UsVIidUv9D7A3ZSEC0N9dNWcCMrEmnNY+LEMK9TnsnT25+koywDG7IvMHT5QwqmeGZXJh0Ia/ue5Vbsm4h0KdvXBH+VQLDfFnw/THsWVPOuncKPF2O6AckZPUyp8NJc10nTTUdNFW301jVQUNlG41V7SeMmVLKmBU9LDaAlNGRhMcHEB4XQFisBbOPFzaHjQ8OfcDzuc/zvZ0fML95Pvfn3N/rVyMKMRi8kPcC5W3lvDTjJcwm+bF4vt2VfRc3fnwjb+a/ybdHf9vT5ZySUopRsxJIGhHO3c94uhrR18mYrB7wxSDVVN1BY7Wx31LXidN57Gvs7edFWIyFsNgAQmMthMVaCIsJICTK/7RapjrsHbyY9yL/2v0vfL18uWfsPXx9+NflF4MQZ+noYPd5KfN4fObjni5n0Lp7+d3srdvL0muXYvG2eLqc09JXB74rpX4G3AQ4ACdwl9Z6Uy+9V6vWOlApFQ88o7W+rjfep7+SkHWaHHYnLfVfEaRq2mmp/UKQ8vUiJNqfkCgLodH+xn60hZAofyzBPj0yAP1w82F+u+m3rC9fT2ZYJg9PeZix0WPP+bxCDCZaa77zyXfYW7+XD6/6UFqGPWhH9Q6+ueSbPJDzAN8c+U1Pl3Na+mLIUkpNBf4EXKi1tiqlIgEfrXV5L71fq9a67/bxepg0f7jYuxy0Nlhpruugpa6TlrpOmus6aa03tm1N1u5B52BM2Bka7U9kYhDp46ONMBVlISS654LUqQwJHsKzFz3Lp0c+5Xebf8ctS27hqqFX8aMJP+qT880I0RctKVrCpspNPDz5YQlYHjYuehyTYifx8p6XuWH4Dfh6+Xq6pP4qDqjVWlsBtNa1AEqpucAfMH7vbwG+6wphxcDrwGzAG7gTeBwYCvxea/2sUioQ+AAIcx3zsNb6g+PfVCmVAizSWo9y7b8KBLie/p7Wen2vfeI+zKMtWUqpUOBFYBRGhLlda73hZMefbUuW0+GkvdlGW6OVlvpOWhs6jW39sfsdLbYTazMpAsN8CY7wIyjCj6BwY3s+g9Tpare181zuc/x7z7/x9/bnwUkPcmX6lZ4uS4g+raWrhSvfv5JYSyyvXf6azOzeB2yq2MS3P/k2P5v8M74+/OueLsctdy1ZKQ9+/BQwtoffdmfxE/N/eIqaAoG1gAX4FHgL2AQcBOZqrQ8opf4NbNdaP+UKWb/TWv9DKfVnYC4wHfAD9mito5VSZsCitW52tYxtBDK01vq47sIUjoUsC+DUWncqpTKAN/pai9/54umWrKeBpVrr65RSPhj/KU6L1hpbp4P25i7aW7pob+oy9pustB3dNhnbjlbbCa1QYHTpBYb7ERTuS9SQIILCjP2gCH+CIvwICPHB1E+mQrB4W/jRhB+xMH0hj218jJ+t/Rm5Nbn8ZOJP8PaStQWF+Cp/2fEX6jvr+dvcv0nA6iMmxU5ibNRY/rn7n1ybca38/DoLWutWpdQEYCZG69RbGC1TRVrrA67DXgHuAZ5y3f/Qtc0DArXWLUCLUqrT1RjSBvxWKTULY4xXAhADVJ6kDG/gr0qpsRjjwob12AfsZzwWspRSwcAs4DYArXUX0HWq1zTVdPD277YaYaq5C4fN+eXzmhSWIG8sIb4EhfkSkxKMJcSHgBBfAkJ9CQr3JTDMD1+Luc+0RPWUtNA0XrzkRZ7Z/gz/2vMvDjQc4I8X/LFPLb4qRF+wp24Pb+W/xdczv05WRJanyxEuSinuzL6T//fZ/+PDQx9y7bBrPV3SOTlVi1Nv0lo7gJXASqVUHnCrm5ccvdTdedz+0ftm4BtAFDBBa21ztX75neJ8PwKqgDGACeg8w48wYHiyJSsNqAH+pZQaA2wDfqC1bjv+IKXUnRh9xCRFD8Xb14u49BAswT74B/tgCfbBEmTsB4T44hfofcLaUoON2WTmvpz7yIrI4hfrf8ENi27gTxf+SQbFC+HicDr41YZfEe4XzvfGfc/T5YgvmJEwg5ERI3kx70UWDl0oV06fIaVUJkZX3UHXQ2NxBR6l1FCtdQFwC7DqDE4bAlS7AtZsYMhpHF+qtXYqpW4FBm1TsSf7w8zAeOAfWutxGM2RD37xIK3181rrHK11TnRSCAt/OI6Lbx/J9OsyGH/JEIZPiSN5ZARRSUFYgn0GdcA63rzUebx2+Wv4mf341rJv8db+t+hPV5IK0Vv+d+B/7KnbwwM5DxDkE+TpcsQXHG3NKm0tZUnREk+X0x8FAq8opfYqpXKBLIzfrd8C/udq2XICz57BOf8D5CiltmK0au13c/zfgVuVUhsxugrb3Bw/YHls4LtSKhbYqLVOcd2fCTyotZ5/stf01Xmy+rImaxMPrXmINWVruGroVTw85WG5akcMWrUdtVz53pVkRWbxwsUvDLghAwOFUzu57qPrsDvtvHfle312zFxfnMJB9C0ea8nSWlcCJa6mTTCuaNjrqXoGqhDfEP4696/clX0X7xe8z61LbqWitcLTZQnhEX/Y+gc6HZ08PPlhCVh9mEmZuDP7Toqailh+ZLmnyxHirHn68rnvA/9xNWmOBX7r2XIGJpMy8b1x3+Pp2U9T3FzMTYtvoqS5xNNlCXFeba7YzMeFH3P7qNtJCUnxdDnCjYuTLyYlOIXnc5/Hqb98kZMQ/YFHQ5bWeqdrvFW21voqrXWDJ+sZ6OYkz+HVy17F5rTxneXfobq92tMlCXFe2Bw2fr3p1yQGJvb5tfGEwcvkxZ3Zd3Kw4SArS1Z6uhwhzoqnW7LEeZYRlsE/5v6D+s567lp+F03WJk+XJESve2n3SxQ1FfHTyT/Fz3yqK89FX3JZ6mUkBibyXO5zcuGO6JfOOGS5ZpMV/djoqNE8M+cZDjcf5p7P7qHd1u7pkoToNfvr9/Ns7rNcmnIpMxNneroccQbMJjPfHv1t9tbtZV35Ok+XI8QZO5uWrCql1KtKqYuVjBztt6bETeHJWU+SV5vHj1b+CJvD5v5FQvQzVoeVh9Y8RJhvGA9PftjT5YizcGX6lcQFxPHcLmnNEv3P2YSsfwOXAUsxrg58Qik1smfLEufDRUMu4tGpj7K+fD0PrX0Ih9Ph6ZKE6FF/3fFXChoL+OW0XxLqF+rpcsRZ8Pby5vZRt7OzZidbKrd4upx+QSmllVJ/PO7+/UqpR137dyulvumx4gaZMw5ZWuvvYqzy/TWMlbx/COQqpbYppe5VSskaLv3I1RlX8+MJP2ZZ8TJ+s+k38peiGDC2Vm7llT2v8LVhX5Nuwn7u6oyrifKP4rnc5zxdSn9hBa5xLeZ8Aq31s1rrf5/rGyil+ubkZX3MWQ1811rbtNbvaq2vxghc38f4R30KKFVKfaCUulYpJat79gO3jbqNO0bdwf8O/I+/7PiLp8sR4py1drXy8LqHSQxK5P6c+z1djjhHvl6+3DbyNjZXbmZH9Q5Pl9Mf2IHnMdYQPIFS6lGl1P2u/YlKqVyl1Aal1O+VUrtdj3u57m9xPX+X6/ELlVKfK6Vex1hMWrhxzotCuaZd+LtSajnwGHADcIXrVq+U+gvwhNbaeorTCA/7wfgf0NTVxAt5LxDiG8KtI92tJypE3/X7rb+noq2CV+a9gsXb4ulyRA+4bth1/HP3P3ku9zmevehMVoTxoEdDnsKYA7In7eTRph+exnF/w+hlevIUx/wLuFNrvV4p9cRxj98BNGmtJyqlfIF1SqlPXM9NAkZprYvOpvjB5pymcFBKhSulvquU2oCxltFC4A3gUmAO8CnwC+DFcy1U9C6lFA9PfphLhlzCH7b+QealEf3W50c+592D73L7qNtlYfQBxOJt4ZasW1hXto49tXs8XU6fp7VuxhhDfe9XPa+UCgWCtNbrXQ+9ftzTlwDfVErtBDYBEUCG67nNErBO3xm3ZLm6ABcA38QYAO8DbAS+C7zp+oc9aqVSKp+vaLIUfY+XyYvHZz5OSUsJP1/3c/53xf+IDYj1dFlCnLb6znoe3fAomWGZ/L8x/8/T5YgeduPwG/nX7n/xXO5zPDPnGU+X497ptTj1pqeA7RgtVl90qtkBFPB9rfWyEx5U6kIG8WLPZ+NsugsrgVCgHPgz8C+t9YFTHL8PY1Vw0Q/4ePnw5KwnuX7R9Ty05iFevOTFPrs4qxDH01rz2IbHaOlq4YVLXsDbS4aEDjQB3gHcnHUzf9/5d57PfR6L+ey7gmMCYrgo+aIBvYal1rpeKfVfjO6/l77wXINSqkUpNUVrvRH4+nFPLwO+q5RaobW2KaWGAWXnr/KB42xC1ifAy8An+jQuRdNavwm8eRbvIzwkJSSFh6c8zM/W/ozn857nu2O+6+mShHDrw0Mf8tmRz7hvwn0MCxvm6XJEL7lp+E28uf/NHrlIZ17KPH457ZcDfdzeH4HvneS5O4AXlFJtwErg6BIgLwIpwHbXfJg1wFW9WuUApc70kn2l1Cxgn9a65iTPRwJZWuvVPVDfCXJycvTWrVt7+rTiJB5a8xCLixbzz0v+SU5sjqfLEeKkylvLufbDaxkWNoyXLn1JWl8HuC5HFx32jnM6x9sH3uaZHc+QHprO0xc+TVJw0hmfQym1TWvdb384KqUCtdatrv0HgTit9Q88XNaAcjYhywHcorV+/STP3wC8rrXu8Z9yErLOrzZbG9d/dD1Wh5W3r3hbJnMUfZLNaePOT+5kb91e3rnyHRKDEj1dkugn1pet5//W/B9O7eR3M393xvOpDYCQdQPwEEav1mHgtpM1oIizczZXF7rrwPYFZOrwASDAO4AnL3iSus46fr7+5zJRqehztNb8dtNv2Vq1lYenPCwBS5yRaQnTeHP+myQEJnDPZ/fw3K7ncGqnp8s6b7TWb2mtx2qtR2mt50vA6nmnFbKUUolKqWlKqWmuhzKO3v/C7XLgO0BJr1UszquRESO5b8J9rCxZyRv73/B0OUKc4NW9r/L2gbf59uhvc0X6FZ4uR/RDiUGJ/PuyfzM/bT5/3flXfvj5D2ntavV0WWKAOK3uQqXUI8AjgLuDleuY72ut/37u5Z1Iugs9Q2vN91Z8jw3lG3h9/usMDx/u6ZKEYGXJSu5dcS9zk+fyxwv/iEmd07R/YpDTWvP6/tf5/ZbfkxSUxNOznyYtNO2Ur+nv3YWi951uyBqDMWutwrgM9HlgwxcO0xjzZ2zvrYnKJGR5Tn1nPV/78GtYvC28teCtgX41jujj8uvzuWXJLaSGpPLyvJfxN/t7uiQxQGyp3ML9q+6n097J4zMfZ07ynJMeKyFLuHM2A98fAd7RWu/unZJOTkKWZ22u2My3P/k2C4cu5FfTf+XpcsQgVdNew02Lb8Kpnbwx/w2iLdGeLkkMMJVtlfzo8x+xu24394y9hzuz7/zKllIJWcKdM25f11r/0hMBC8DW2Ul1cSH15aU011bT3txEV0c7ToeMsz8fJsVN4s7sO3m/4H2WFi/1dDliEOq0d3Lvintpsjbx1zl/lYAlekVsQCwvX/YyV6Rdwd92/o37V91Pu63d02WdFqVUhFJqp+tWqZQqc+23KqV6fBjPV7z/y0qp687xHD/tqXo8zW1LllLqm67dV7XW+rj7p6S1/ve5FvdFSeGh+ocXz/jK50xeXvgFBhEQEoolNOzY1nWzhIQSGB5BcGQU3r5+PV3aoGF32rll8S2Ut5Xz4VUfEuIb4umSxCDh1E4eWPUAyw8v56nZT52yG0eInqC15tW9r/LHbX8kPTSdZ2Y/c8IVrH29JUsp9SjQqrX+Qy++h5fW2nHc/ZeBRVrrt8/hnK1a6wGxUszphCwnxngrf611l+u+O7o35skanZWl3335RexdXdhtXca2qwt7lxV7VxedLS20NTXS3thAW1MDbY0NOGy2L53HEhJKcGQUwZHRBEfHGPtRMYTGxBIWl4DJSyYyPJX8+nxuWHQDC4cu5JfTfunpcsQg8Zcdf+H53Of58YQfc9uo2zxdjhhE1pev54FVD2BSJv5wwR+YHDcZ6F8hy7Xu4P1a6wWux1OBOGAYcB8wBWM94jLgCtdyOnOBP2DMo7UF+K7W2qqUKsYYn30J8FfXyi5H3/NlvhCylFJewBPAhRjTPP1Na/2cUioOeAsIdr3Hd4H5wANAHrBHa/0NpdTNGAtd+2AsWP3/jg92fdnpLKuTCqC17jr+vif4WixkTJrm/kAXrTXW9jbaGhtob2qkpa6W5ppqmmuraa6ppuZIMYe2bz4hiJm9fYhMHkJ0ajrRKelEp6YRmZyCt49vb3ykfikzPJNbR97KS7tfYkHaAibGTvR0SWKA++jQRzyf+zzXZFzDrSNv9XQ5YpCZFj+NN+a/wfdXfJ+7lt/FAxMf4KbhN7l93ehXRj+FcdFYT9qZd2veD3vgPOnAbCAL40K2a7XW/6eUeg+Yr5RairGE3lyt9QGl1L8xQtBTrtd3aq2/umvpy+4AmrTWE5VSvsA6pdQnwDXAMq31b1xBzKK1XqOU+p7WeiyAUmoEcAMw3RX8/g58A+jx3rLe4DZkaa0Pn+p+X6aUwi8gEL+AQCISvnrJBO100t7cRFN1FY2V5VQXF1JdXEj++jXkfmqMO1ImExEJSUSnppMydgJp4ybiaxncV9fdPeZuPin+hMc2PMbbV76Nr5eEUNE7lhQt4ZH1jzApdhIPT354QC/oK/qu5OBk/nP5f3ho7UM8sfkJDjQc8HRJ52qJK7TkAV7A0YG2eRjrFmYCRVrrox/0FeAejoWst87gvS4Bso8bqxUCZGC0jr2klPIG3tda7/yK184FJgBbXN/7/kD1Gby3R53NAtEDijKZusdtxQ8bTtYsY5yH1prmmiqqiwqpLj5EVdEhinZuY+/qFXiZzQzJHkfGpGmk50zGPyjYw5/i/PM3+/PzqT/nruV38ULuC3xv3MnWHxXi7Di1k3/s+gfP7nqW8dHj+dOFf8Lby9vTZYlBLNAnkKdnP83fd/6d53Kfc3t8D7U49RYrgNbaqZSy6WNjh5wY2cDdXzNtAEqpfwHjgHKt9eUnOVZhzJ+57EtPGOshzwdeVUr9/ivGcyvgFa31Q6fzofoatyFLKfXSWZxXa63vOIvX9RlKKUKiYwmJjiVjstFFqZ1Oyg/s5+DmdRzcvIHC7VtQJhNJI7PJmDSNjElTCQgN83Dl58+0+GlckXYF/9z9T+alzGNo2FBPlyQGiA57Bz9f93OWFS/jqqFX8fMpP8fHy8fTZQmBSZn43rjvMSJ8BBdxkafL6U37gRSl1FCtdQFwC7Dqiwdprb91GudaBnxXKbXC1Xo2DGPsVyRQprV+QSkVAIzH6Aa0KaW8tdY24DPgA6XUn7XW1UqpcCCov/SqnU5L1hzcz/T+RQNykTtlMpEwPIuE4VlccMu3qS46xIFN6zi4aT2f/fPvfPbSP0gcPpLh02eRMXk6luCBf+Xd/RPvZ03ZGn654Ze8ctkrMuu2OGc17TXcu+Je9tTt4b4J93HbyNuki1D0OXOHzPV0Cb1Ka92plPoW8D+l1NGB78+e5sufU0o95dovAaZjdEFuV8Y3cw1wFcZA+AeUUjagFTg6e8HzQK5Sartr4PvDwCdKKRNgw+i27Bch64wnI/WkvjoZqdaautIjHNi4jvwNa6gvK0GZTAzJHsfwabMYOnHqgB7D9eGhD/nZ2p/x8yk/5/rM6z1djujH9tXt43srvkdLVwu/m/k7ZifP9nRJQpxUX7+6UHiehKweprWm5nAR+9evJn/9apprqvHy9iZt3ESGT59F6viJA+5KRa0131n+HfbU7uGDqz6QCSLFWfns8Gc8tPYhQnxD+Oucv5IZnunpkoQ4JQlZwh0JWb1Ia03Fwf3sX7ea/A1raG9qxOztQ8KIkSSPGsOQ0WOJTklDmfp/F9uR5iNc8+E1zEqcxZ8u/JOnyxH9iNaaf+7+J09vf5rsyGyenvM0kf6Rni5LCLckZAl3Tmcy0iKMqw2GuwasFeF+zJXWWqf3UI3d+lvIOp7T4aBkTx6F2zdzOG8ndaVHAPALCnYFLiN0hUTHerjSs/di3os8vf1pnp79tMzGfZ4UNhZyuPkwjdZGGqwNNHZ+YWttxNfLl2FhwxgWNozMsEyGhQ/rEyGmy9HFkqIlvLbvNfbX7+ey1Mt4bNpj+JllRQbRP0jIEu6cTsh6GSNUfVtr7Tju/imd5hUHZ6Q/h6wvaq2v48juXRzO28mRvJ20NtQDEBoTR8aU6WROnWm0cvWjAb82p40bFt1Ak7WJDxZ+QKDPgFgVoc9xaierSlbx773/ZmvVid8PPiYfwvzCCPMLI8Q3hDDfMNpsbRxoOEBVe1X3ceF+4d2hKzM8kwkxE4gPjD8v9dd21PLf/P/yVv5b1HfWkx6Szq0jb+WqoVf1q//vQkjIEu5Id2EfoLWmvqyUw3k7KdqxhcN5O9FOJ2Fx8WROnUnm1JlEJqd4uszTkluTy82Lb+amETfx4KQHPV3OgNJua+f9gvf5z77/cKTlCHEBcdw0/CYmxk0kzDeMUN9Q/M3+Jw0qjZ2NHGg4wIGGA+Q35HOg4QAFDQV0OY3FHGIDYpkQM4Hx0ePJickhNSS1R0PP3rq9/Gfff1hctBi7086sxFncPOJmpsRNkXAl+iUJWcKdMw5ZrgWiV2uti0/y/BDggt5YIHqghqwvam9uomDzBvI3rKZkz260dhKRmGwErmkzCY9PdH8SD/r1xl/z9oG3+e8V/2VY2DBPl9PvVbZV8vq+13n74Nu0dLWQHZXNLVm3cFHyRZhN5zafsN1p51DjIbZVbWNb1Ta2V2+ntqMWgDDfMMbHjGdc9DgSAxOJtEQS5R9FpH/kKeessjlt1LbXUtVeRWV7JVVtVaw4soLt1dvxN/tz9dCruWnETQwJHnJOtQvhaRKyhDtnE7IcwC1a69dP8vwNwOu9sUD0YAlZx2trbODApnXkr19DWf5e0JqoIakMmzKDYVNmEB6f4OkSv6TJ2sSC9xYwNHQoL136krRSnKXajlqe3PIknxR/AsBFQy7ilqxbGBM1ptfeU2vNkZYj3aFrW9U2ylrLvnRciG9Id+CK9I+k095JVXsVVW1V1HTUoL8woiAhMIEbh9/I1RlXE+wz+FZIEANTXw1ZSqlYjOVvJmLM7F4MvA9cqbVecJbnTMFY+HlUjxQ5SJxNyHICN58iZN0O/ENr3ePzFAzGkHW8lvpaDmxYx4GNayk/sA+gzwau/+b/l19t/BW/n/V75qXO83Q5/c7eur3cu+JemqxN3JB5AzeNuOm8jZn6orqOOqraq6jtqKWmvYaajpru/dqOWmo7avEz+xEbEEuMJYaYgBhiLbHEBMQQY4khNiCWQO9ACdtiwOmLIcs12ed6jKVonnU9Nha4ApgsIev8Oq2QpZQaBWS77r4G/B3jH/GLQoH/5zrvyB6qsdtgD1nHa66t4eCm9eRvXEPFgf3AscCVOXUGYXGeDVwOp4MbP76R+s56PrzqQyzeA3cy1p62tGgpP1/3c0L9Qnlm9jOMiBjh6ZKEEF+hj4asOcCjWutZX3j8QuBRoBYYBWzDaDDRSqlfYIQwf4zf7Xe5Hp8AvAS0A2uByyRknZnTDVmPAI+47mpOvXBkB/BNrfU7517eiSRkfbWvClzRKelkTptJ5tQZHpsWYkf1Dr655Jt8Z/R3uHf8vR6poT9xaid/3fFXXsh7gXHR4/jThX/qE1MtCCG+mruQtW/4iKeAsT38tjtH7N/3w1PUdC+QqrX+0RcevxD4ABgJlAPrgAe01muVUuFa63rXca8C/9Vaf6SUysVY2HmVUur3SMg6Y6c7avZlYCVGuFoB/BZY/oVjNMaq3Pu01u09VJ84DcGRUUyYv5AJ8xe6ApcxhmvN6y+z5vWXiU3PIHPqTIZNnUFw5PmbjX1c9DgWpC3g5T0vc9XQq0gOTj5v793ftNnaeHDNg6wsWck1Gdfw8OSH8fby9nRZQoiBZbPWuhRAKbUTYz3BtcBspdT/ARYgHNijlFoNhGqtjy4K/Spw2XmvuJ87ozFZrr7ee4FlWuv9vVbVSUhL1plpqq7iwMa15G9YQ1VhAQBxw4aTOWUGaeMnnpcuxZr2Gha8t4CJsRP569y/9vr79UclzSXc+/m9FDUV8cDEB7hp+E0yfkmIfqCPdhfOBR45SXfh/UfHZCml/gpsBd7EWGw5R2tdopR61PWSp4BdWushruOzMS5qk5asM3Cm13/7An8E/IDzHrLEmQmJjmHildcy8cpraags58AGI3Ct/PeLrPz3i4TFxZM2fiKp4yaSOGIkXuaebzmJskRx95i7+dO2P7G6dDWzEme5f9EgsqliEz9e9WO01jx78bNMiZvi6ZKEEP3bCuC3SqnvaK1fAFBKTQQuOMnxR5dYqFVKBQLXAW9rrRuVUk1KqRla67XAN3q98gHojEKW1rpTKVWFMQhO9CNhsfFMvvp6Jl99PU3VlRRu30Lhjq3sXPYx2z7+AB9/f4ZkjyNt/CRSx04gIDSsx9775hE38+7Bd3lyy5NMiZtyyjmWBpNFhYt4eO3DpASn8Jc5fyEpOMnTJQkh+jnXgPWrgaeUUg8CnRybwuGrjm9USr0A5LmO23Lc098CXlJKtQPLerHsAetspnD4EzAZmKW1dvRKVSch3YU9z9bZyeHduyjcvpmi7VtobahHKROp4yYwes6lpI2fiMnr3Kc8W1e2jrs/vZsfjv8hd4y+owcq79/Wl6/nnk/vYVzMOJ6Z/YwsQSREP9QXuwtF33I2IWsuRl9tB/ACUOjaP4HW+qumeDgnErJ6l9aa6uJCDm5ax+6Vn9LWUE9AWDijLryY0XMuPuerFO9dcS8bKzby0VUfERMQ00NV9z/76/dz29LbiA+M55V5rxDkE+TpkoQQZ0FClnDnbCcjPd4XT6AwWixlxvd+zOlwULh9C3krllG0YxtaOxmSPY7Rcy5l6MTJZzV+q6SlhKvev4qLhlzE72b9rheq7vsqWiv4xuJvYFImXrv8NWIDPDO9hhDi3EnIEu6czcJn3+qpN1dKFQMtgAOwy3/WvsPk5cXQiVMYOnEKzbU17P58Obs/X86ip57APziEUbMvZsxFlxESffotUklBSdw26jaez32e6zOvZ0LMhF78BH1Pk7WJuz+9m057J69c9ooELCGEGODOuCWrR9/cCFk5Wuva0zleWrI8y+l0cHjXDnZ9upTCbZvRaNLGT2TcJfMZkj0OZTK5PUeHvYMr37+SYJ9g3lrw1jkvcNxfWB1W7lp+F7k1uTx38XNMjJ3o6ZKEEOdIWrKEO+f0G04plQFEA7u11k09U5Loq0wmL1LH5ZA6Lofm2mpyP11G3oplvLNtM6GxcYy9ZD4jL7gIv8CTD+L2N/vzk4k/4Ucrf8Rre1/jtlG3nb8P4CFO7eRna3/GtqptPDnrSQlYQggxSJxVS5ZS6gbgSSDR9dDFWusVSqlIYAPwU631/07jPEVAA8a4rue01s+f6nhpyep77DYbBzetY+eyjyk/sA+zjy/Dp1/AmIvmEZOe8ZWTamqt+cHnP2BD+QbeW/geiUGJX3HmgeMPW/7AK3tf4ccTfjwoQqUQg4W0ZAl3zmbg+0LgPYx1j5YAvwYu0lqvcD3/IYDW+srTOFe81rpcKRWNsUzP97XWq79wzJ3AnQDJyckTDh8+fEb1ivOnuriQnZ98zL61K7FbrYTFJ5I1czZZM2cTHHXicj6VbZUsfH8h46LH8Y+L/jFgZzh/be9r/G7L77hp+E08OOnBAfs5hRiM+mrIUkrFYswCMBGwYsx/9UOt9QEP1pQC7MOYyNwPYzz237TWr/Ty+16IsWZjIcYC2Iu01vf35nue8P5nEbK2AG1a6wuVUhFADSeGrJ8Bdx6div8Mzvso0Kq1/sPJjpGWrP6hs62VAxvXsW/N55Tu2w1A4ohRjJg5m2FTpuMXYHQnvr7vdR7f/DhPzHyC+WnzPVlyr1h+eDk/Xvlj5iTP4Y8X/BEvU49fcCuE8KC+GLJcy9+tB17RWj/remwsEKS1XuPBulIwAs4o1/004F3gaa31v3rxfS/EtZyQUsof2AHcobVe11vveTz3I5W/bCTw31M8Xwm4veRMKRWglAo6ug9cAuw+i3pEH+MXEEj23Eu54dEn+PZf/sn0G26hramR5c//hWfvuoWP/vwEhdu38LWM68iOzObJLU/S2Nno6bJ71L66ffx0zU/JjsrmiZlPSMASQpwvswHb0YAFoLXeqbVeowy/V0rtVkrluYb+oJS6UCm1Uin1tlJqv1LqP66whlLqctdja5VSzyilFrkeD1dKva+UylVKbXStbXjatNaFwH0Y6yEfzQQvKaW2KKV2uHrNUErd5nqfj5RSRUqp7yml7nMds1EpFX4G79kB7AQSXOe+RCm1QSm1XSn1P9eyQiilipVSv1NKbXbdhp7JZzve2Qx87+TYWkdfJQVoPI3zxADvuf4dzRgLTy49i3pEHxYSHcOUa25g8tXXU3XoIHtWryB//WoObFxLSHQM35gxk1+2PM8ft/2RX03/lafL7RF1HXXc+/m9hPqF8tTsp/Azn+rbRQgxUP3t7hVPAWN7+LQ773l2zg9P8fwoYNtJnrvGVc8YIBLYopQ6OkRnHEYjSjnGcKDpSqmtwHMYK7wUKaXeOO5cvwR2aK2vUkrNAf7NmX/W7cBw1/7PgBVa69uVUqHAZqXUp8d9pnEY2aMA+InWepxS6s/ANzG6Rt1SSoUBGcBq1xjyhzF64tqUUj/BCH2PuQ5v1lpPUkodPf+CM/xswNmFrLXAjcCfvviEUioEuB1jgcpTcqXYMWfx/qIfUkoRO3QYsUOHceE3v03Blo3sXLaIfe8u4npzIgf2r+Yz3w+Ym7PQ06WeE5vDxn0r76Ohs4F/X/ZvIv0jPV2SEEIcNQN4w7UkXpVSahXGuK1mYLPWuhRAKbUTo8GkFSjUWhe5Xv8GrjHSrnNdC+C68C1CKRVyhjMNHD9I9RLgSqXU0fFSfkCya/9zrXUL0KKUagI+cj2eB5xOC9pMpVQukAk8obWuVEotALKAda7GHh+MC/eOeuO47Z/P4DOd4GxC1qPAWqXU58DrrsdylFJZwI+BYGBgNEmIXuFlNpM5dQaZU2dQXVzItqUf4li9nJ2/f4GqzDWMn3clGZOm4WXuf3NoPbH5CbZXb+d3M39HVkSWp8sRQniQmxan3rIHuO4kz53qyhvrcfsOjHxwquO/6rkzna5gHMZg+KPnu1ZrnX/Cmyg1+Qu1OY+77+T0cswa15isYRj55T3X+y3XWt94ktfok+yfkTMek6W13g5cCsRiNCMCPAE8A3QBl2qt953k5UKcIDoljcvu/iHTfnU/W4bXU1F5mI+ffpIXvnc76//3H1rqT2ue2j7hv/n/5b8H/svto27n8rTLPV2OEGJwWgH4KqW+c/QBpdREpdQFwGrgBqWUl1IqCpgFbD7FufYDaa5B6wA3HPfcauAbrvNfCNRqrZuVUpOUUv92V6TrnH8A/uJ6aBnw/ePGgo1zd44z5bq68nHgJ8BGjC7Roa73s7hC2FE3HLfdwFk6raYCpdS7wJ+PuzJhHXA1EIYxV5YJo590u/bkFPKi35qRPpslF8/mP4cW80zqI1St28GGd95k47tvkT5hMmMuuZwho8ac1qzynrC1ciuPb3qcmQkzuXfcvZ4uRwgxSGmttVLqauAppdSDGOOoi4EfYgSjqcAujNaZ/3N1nQ0/ybk6lFL/D1iqlKrlxED2KPAvVzdcO3Cr6/FkoOMk5aUrpXZwbAqHvxx3ZeGvMMY+5bqCVjFnMA5KKXW3q+Zn3Rz6LHA/EAjcBryhlPJ1PfcwcHSaC1+l1CaMfHOj6z2uxFil5henXdfpZCJlLAp9s9b6ddf9CKAa1ySkp/tm50qmcBjYGjobWPj+QpKCk3j1sldprq4m99Ml7P58OR0tzYTFxZN90WWMvPAi/AODPF1ut/LWcr6+6OuE+Ibw+vzXCfLpO7UJIXpPX5zCoacppQK11q2u4PM34KDW+qRjlJRSvwde1Vrnnrcie5g6wyX/TuVcmgVkVkXRo8L8wnhg4gPk1uTy3/z/EhoTy6xvfIs7//4yl33vx/gHhbDq1X/y/N23svTvf6b8wH483XDabmvnB5//ALvTzjNznpGAJYQYaL7jGgi/Bwjh2DChr6S1fqA/B6yedi4tWSdMQno+SEvWwKe1NhZSrs3l7Sve/tKSOzWHi9i1fDF716zE1tlBZHIK2XMvZcTM2d2TnJ7PWh9Y/QCfFH/C3+b+jZmJM8/r+wshPGswtGSJc9M3B7iIQUspxS+m/gIv5cX3V3yf1q7WE56PGpLKRd++h7uffYWL7/weXmZvVvzrOZ5ztW6V5e87b61bL+a9yLLiZfxwwg8lYAkhhPiSM2nJ+iXG+oJgNBl+DPyAk0x6prVe30M1dpOWrMFjU8Um7l5+N1Pip/CXOX/BbDr5NRpVhQXkrVjGvrUr6eroICIx2WjdmjWn18ZuvXfwPX6x/hdclnoZv5v5O1mTUIhBSFqyhDtnErK+eODR3ypf9bjWWvf4OiISsgaX/x34H49teIxvjPgGD0560O3xXZ0d5K9fQ+5nS6ksOICX2Uz6hMlkXTCXlDHje2zeraVFS/nJmp8wJc4IgD5ePj1yXiFE/yIhS7hzur91vtWrVQjxFb427GsUNRXx6t5XSQtJ4/rM6095vI+fP6PnXMLoOZdQXVzInlWfsW/tSg5sWoclJJQRMy4ga9ZcolPSzrqmlSUreWjNQ4yNGstTs5+SgCWEEOKkTqslq6+QlqzBx+F0cO/n97KubB3/uOgfTI2femavt9sp2rmNvas+49C2zTgddqKGpDLygrkMn34BAaFhp32uDeUbuOeze8gMy+SFS14g0Of8DrQXQvQtfbUlSymlgde01re47puBCmCT1vqs1uATZ0dClujzWrtauWXJLVS1VfHa/NdICzm7lqiOlmb2r1/N3lWfUXnoIEqZiM8cwdCJUxiaM4XQ2LiTvnZ71Xbu/vRukoKSeOnSlwjxDTnbjyOEGCD6cMhqBQ4C01wTil6GMdN5qYSs80tClugXylrLuOnjmwjwDuD1y18n1C/0nM5XV3qE/A1rKNiykZrDxtqnkUlDGDpxCuk5U4hJG9o9mH1P7R7u+OQOovyj+Ne8f8miz0IIoM+HrGcwVmF527XMzR5gpmsNvwCM5WxGYwwbelRr/YFrqZtXgQDXqb6ntV7vWjbnUaAWGIVxwdvNssKLexKyRL+xs3onty+7nTFRY3j+4ufx9vLukfM2VVdyaOsmCrZspHTfHrR2EhgRydCcyfhnJfN/RY8T6BPIy/NeJjYgtkfeUwjR/7kLWX+8YcFTwNgeftudP35r0Q9PdYArZE0DfgHcjLFO3w+B+10h67fAXq31a0qpUIzlcsZhXMjm1Fp3KqUygDe01jmukPUBMBIox1ha7wGt9doe/mwDTs9cbiXEeTA2eiyPTX+Mh9Y8xK83/ZpHpz7aI1MnhETHMv7yhYy/fCEdLc0Ubt9CwZaN5K34BMcyG5f7hpA15QK6iqpwjojC5NXjF84KIUSP0lrnulqmbgQWf+HpS4ArlVL3u+77Yaw5WA78VSk1FnAAxy+YvFlrXQrgmgE+BZCQ5YaELNGvLEhbQFFTEc/nPo/Wmh/n/LhHx0f5BwUz8oK52EZE8PeEzwmr0FzlmMbhjZs4tGo1/sEhZEyayrDJM0gaOVoClxDipNy1OJ0HHwJ/AC4EIo57XAHXaq3zjz9YKfUoUAWMwZisvPO4p63H7TuQ/HBa5Isk+p17xt6Dw+ng5T0vs7p0NQ9OepBLUy7tkVat+s56ntr2FO8VvEeMJYZf3vZ3MsMzsVk7Kdq5jQMb1rJvzUpyP12Kf1AwGZOnMXzaLBJGjMRkksAlhOhTXgKatNZ5ri6/o5YB31dKfV9rrZVS47TWOzAmGi/VWjuVUrcC8kPtHMmYLNFv7avbx6MbHmVv3V5mJMzg4SkPkxCYcFbncjgdvHPwHZ7e/jTttnZuGXkLd2ffjcXb8qVjbdZOinduJ3/jWg5t24TdaiUgLJzMKTPInDaLuIxMmQFeiEGgLw9811oHfuGxCzk2JssfeApj3JYCil2PZwDvAO3A58D3tdaBx7/Wda6/Alu11i+flw/Uj0nIEv2aw+ngjf1v8MyOZwCjlesbI75xymV4vmhP7R5+tfFX7Knbw8TYifxs8s9ID00/rdfaOjsp3LGF/etWU7RzKw6bjeCoaDKnzSJz6kyiU9IkcAkxQPXVkCX6DglZYkCoaK3gN5t+w6rSVYwIH8Ej0x5hZMTIU76mydrEM9uf4X8H/kekfyT359zPZamXnXUosra3UbBlI/nrV3M4bydOh4PQmDjSJ05haM5k4jNHSJeiEAOIhCzhjoQsMWBorVl+eDmPb36c+s56xkaNxWwyo5TChAml1An7eTV5NHc1c+PwG7ln7D09OoN7R0szBzet5+CWDZTs3oXDbsc/KJi08ZNInziZlOxxePv69dj7CSHOPwlZwh0JWWLAae5q5h87/8G++n1ordFonNqJRqP1sf0o/yi+P+77ZIZn9mo91vZ2indto2DLRop2bMXa3obZ24fk7LFkTJxKxuTp+Fq+PPZLCNG3ScgS7kjIEuI8ctjtlO7bTcGWjRzauomWuhrM3j6kT5xC1qzZpGSPl2khhOgnJGQJdyRkCeEhWmsqDuazd83n5K9fTWdrC5aQUIZPv4CsmbOJTk2XQfNC9GESsoQ7ErKE6AMcdhuFO7ayb/XnFG7fjMNuJyIxmREzZzNixoUER0Z5ukQhxBdIyBLuSMgSoo/paG3hwIY17F39OeUH9oFSJGWNZsTMCxk2eTq+lgD3JxFC9DoJWcIdCVlC9GGNlRXsW7uSfWs/p6GiHLO3D2k5k8maeSEpY8bjZe6ZRbKFEGdOQpZwR0KWEP2A1prKQwfYu9oYv9XR0oxfUDDDp81k5Ky5xKRnyPgtIc4zCVnCHQlZQvQzDrudw7k72Lvmcw5t2Yjd1kXUkFRGz72UETMuxC+g5+b7EkKcnIQs4Y6ELCH6MWt7G/vWriLvs2VUFx/C7OPLsCnTGT33UhIys6R1S4heJCFLuCMhS4gBoqqwgNzPlrJ/3Sq6OjoIT0hi9JxLyJo1B0twiKfLE2LAkZAl3JGQJcQA09XZQf6GNeR9toyKg/mYvMwMzZnMqNkXM2TMOFk/UYgeIiFLuCMhS4gBrPZIMbtXLmfv6s/paGkmMDyCkRdcxKgLLyI0Ns7T5QnRr0nIEu5IyBJiEHDYbRzatpndKz6heNcOtHaSlDWaUbMvJmPyNFmsWoizICFLuCMhS4hBpqWulr2rV7D78+U0VlXg428ha9Ycxlx8GZFJQzxdnhD9hoQs4Y6ELCEGKe10Urp/D7mfLuXgpnU47HYSR4wi++LLyJg0DbO3THQqxKlIyBLuSMgSQtDe3MSelZ+y69MlNFVV4h8cwqjZFzPmonmERMd6ujwh+iQJWcIdCVlCiG7a6eRw7g52fbqEQ1s3o9GkjBnPmIsuI238RExecmWiEEdJyBLuSMgSQnyllrpa8lYsI++zZbQ21BMYHsHoOZcyeu4lBIVHero8ITxOQpZwR0KWEOKUnA4Hh7ZvJnf5Eop3bUeZTKSNn8SYiy8jJXscymTydIlCeISELOGO2dMFCCH6NpOXFxkTp5IxcSqNlRXkrljG7s+Xc2jrRkKiYxg9dx6j51wis8oLIcQXSEuWEOKM2W02CrZsIHf5Ekr25mH29SV77jxyrrhauhLFoCEtWcIdCVlCiHNSW3KYLR++w761KzGZTIy84CImLryO0Bi5KlEMbBKyhDsSsoQQPaKpupItH77D7s+X43Q6GT79AiZf9TUiEpM9XZoQvUJClnBHQpYQoke11texddF77Pp0CfauLjImTmXSVV8jNj3D06UJ0aMkZAl3PB6ylFJewFagTGu94FTHSsgSov9ob25ix5IP2bF0Edb2NhKzRpGz4GrSxk2UKxLFgCAhS7jTF0LWfUAOECwhS4iBx9reTt6KZWxf8iEttTWExScy4fKFZF0wB28fX0+XJ8RZk5Al3PFoyFJKJQKvAL8B7pOQJcTA5bDbObhpHVsXvU9V4UH8g4IZc8l8xl06H0tIqKfLE+KMScgS7ng6ZL0NPA4EAfdLyBJi4NNaU7ZvD1s/fo9D2zbjZTaTNWsOkxZ+Ta5IFP2KhCzhjscmI1VKLQCqtdbblFIXnuK4O4E7AZKT5SolIfo7pRSJWaNIzBpFfXkZ2xe/z+6Vn7L78+VkzZrDlKtvIDQ2ztNlCiHEOfNYS5ZS6nHgFsAO+AHBwLta65tP9hppyRJiYGqtr2PLh++Q++lSHA47WTPnMPma6wmLjfd0aUKclLRkCXc8PvAdwNWSJd2FQgxyrQ31RthavsQVtmYz+ZobJGyJPklClnBH1i4UQvQZgWHhzL71O0xaeB1bPnybXcuXsnf154yYcQGTr/k64fEJni5RCCFOW59oyTpd0pIlxODS1tjAlg/fYdfyJThsNjKnzWTKNTfILPKiT5CWLOGOhCwhRJ/X3tTI1kXvsXPZx9i6rAybPJ0p19xA1JBUT5cmBjEJWcIdCVlCiH6jvbmJ7Ys/YMfSj+jq6GDoxClMuebrxKQN9XRpYhCSkCXckZAlhOh3Olpb2LHkQ7Yv/hBrextp4ycy9bqbZH1EcV5JyBLuSMgSQvRb1vY2diz5iG0fv09nWysZk6cx/YZbiEhI8nRpYhCQkCXckZAlhOj3rO3tbF30Hts+fh+71crIC+cy9bobCY6M9nRpYgCTkCXckZAlhBgw2psa2fTef9m1fDEoxdhLLmfSVddjCQ7xdGliAJKQJdyRkCWEGHCaa6pZ//br7F21ArOvLzkLriZnwVX4+Fs8XZoYQCRkCXckZAkhBqy60hLWvfUqBzevxy8omJz5VzH20gX4WiRsiXMnIUu4IyFLCDHgVRYcYMM7b1C4fQu+AQFMuPwqxl12BX4BgZ4uTfRjErKEOxKyhBCDRlVhARveeZNDWzfi429h/OVXMv7yhfgHBnm6NNEPScgS7kjIEkIMOtXFhWx8900OblqPt58/4+YtYML8q2SAvDgjErKEOxKyhBCDVu2RYja++xb5G9di9vEhe+48chZcTVBEpKdLE/2AhCzhjoQsIcSgV1dawub3/8u+datQykTWrDlMWngtYXEJni5N9GESsoQ7ErKEEMKlqbqKrYveJW/FJzjsdoZNmcGkhdcRk5ru6dJEHyQhS7gjIUsIIb6grbGB7Ys/YOcnH9PV0UHK2AlMXvg1EkaMRCnl6fJEHyEhS7gjIUsIIU6is62VXZ8sZtviD+hobiJ26DAmXL6QjMnT8TKbPV2e8DAJWcIdCVlCCOGGzdrJ7pWfsmPJhzRUlBMYEcm4SxeQPXcefoEy19ZgJSFLuCMhSwghTpN2OincsYXtiz/gyO5czL6+jLzgIsZfdiXh8TJIfrCRkCXckZAlhBBnobq4kO2LP2T/upU47HbSxk9k/GULSR49RsZtDRISsoQ7ErKEEOIctDU2sGv5YnZ+spiO5iYiEpMZN+8KsmbOxtvPz9PliV4kIUu4IyFLCCF6gL2ri/wNa9i++EOqiw/hGxDA6DmXMvaS+YREx3i6PNELJGQJdyRkCSFED9JaU56/j+1LP+LgpnWgIT1nEuPmXUnSyNHSlTiASMgS7sg1yEII0YOUUiQMzyJheBYtdbXsWr6YXZ8upWDLRiISkxl76QKyZl6Ij7/F06UKIXqZtGQJIUQvs3VZ2b9uFTuXfkx18SF8/P3JmjWXsZfMJyIxydPlibMkLVnCHQlZQghxnmitqTi4n53LPubAxrU47HaSR2Uz9pIFpOdMxuTl5ekSxRmQkCXckZAlhBAe0N7USN6KT9j16RJaamsIDI8g+6J5jLxgLsGR0Z4uT5wGCVnCHQlZQgjhQU6Hg8LtW9j5yccczt0BQFLWaLJmzSFj8nR8LTJ2q6+SkCXckZAlhBB9RFN1JXvXfM7e1StorKzA7O1D+sQpjJw1hyHZ46Q7sY+RkCXckZAlhBB9jDF2K5+9q1eQv341nW2tWEJCGT79AoZPm0Xs0GEyFUQfICFLuCMhSwgh+jC7zUbRji3sXf05hdu34HTYCYyIJGPSVIZNnk585ghMJmnh8gQJWcIdCVlCCNFPdLa2cmjbJg5uXk/xru04bDYsIaFkTJpKxqTpJI0cLV2K55GELOGOhCwhhOiHujraKdy+hYOb1lO4cyt2qxW/wCAyp85g9Nx5xKSme7rEAU9ClnBHQpYQQvRzNmsnxbu2c2DjOgo2b8Bu6yImLYPsi+YxfPosfPz8PV3igCQhS7gjIUsIIQaQztZW9q75nLzPllJbchhvP39GzLiA7LnziEkb6unyBhQJWcIdCVlCCDEAHZ1dPvfTZeRvWIO9y0pM2lBGXXgx6RMnExQe6ekS+z0JWcIdCVlCCDHAdba1sm/N5+R+arRuAUSnppM+YTLpEyYRnZouU0KcBQlZwh0JWUIIMUhorakvK6Fg6yYKt22m/OB+0JrA8AjSJ0wibcIkkkeOwezj4+lS+wUJWcIdCVlCCDFItTc1UrhjK4XbNlO8azs2aydmX1+SskaTkj2OIdnjCU9IlFauk5CQJdyRkCWEEAJ7Vxcle/Mo3L6Fw7k7aKgoAyAwItIIXKPHkjx6LJbgEA9X2ndIyBLuSMgSQgjxJU3VVRzO28HhXTs4vHsn1rY2UIqY1HQSs0aTOHwk8ZkjBnXokpAl3JGQJYQQ4pScTgdVhQUc3rWD4twdVBbk47DbAQiPTyRhxEgSMrNIGD6SkOiYQdO9KCFLuCMhSwghxBmxd3VRVVhA6f49lOfvpSx/r9HSBQSGhZMwYhTJo7JJHjmGkJjYARu6JGQJd8yeLkAIIUT/YvbxIWF4FgnDswDQTie1pUco27+Xsv17KNmbR/761QAERUaRPDKbpJHZJI8aQ1CEzM8lBg9pyRJCCNGjtNbUl5dSsjuXkj25HNmbR2dLMwBhcfEkDB9FTGo6USlpRA1J6bfL/khLlnBHQpYQQohepZ1Oao4UG4Fr9y7KD+yns7XFeFIpwmLjiUpJI3pIKtGp6UQNSSUgNKzPdzNKyBLueCxkKaX8gNWAL0a35dta60dO9RoJWUII0f9prWmpq6W6uJCa4kJje7iQpuqq7mP8g0OISk4hakgKkcmpRCWnEJ6YhLePrwcrP5GELOGOJ8dkWfn/7d15jFXlHcbx73OBIgwQwBGYQWCggEgFq6JSY4pRq6k12s29qY22xsa02hi3tkkT29S6pDGNbdWkbrGpVWtTW7eAdV8rRnBhGRwWkQFBpQiWZZhf/zjvjNdx7jAzzvHOnXk+ycmc+57lvvfJXPjNe99zDxwdEVslDQKelvRQRDxfxj6ZmVnOJDGieh9GVO/D1DmHt7Zv37aVjatXsnFVAxvXrGLTmlUsmv8wTTt3pOMKjKqppXrSZEbX7suocTWMHFfLyHE1DBk+otePfFn/U7YiK7IhtK3p4aC0VM5nl2Zm1qP2qhrGhJmzmDBzVmtbc/NuNq9fz6Y1K1sLrw0N9dQ//wwRza37Da6qYuTYWkbVZEVX9YRJ1EybwfC9q118WdmUdU6WpAHAQmAq8PuIuKydfc4DzgOYOHHiIatXr/5sO2lmZr1O065dbNm4gfcb17F5fSPvr1/H5rRs2bixtQAbNmo0NdNnUDttBjXTZjB2ytQeuzejPy60PekVE98ljQT+DvwoIl4rtZ/nZJmZ2Z407drFpjWrWLd8KY312dIy36swYCBj6ia3FlzjPj+NUbXjKRQGdPl5XGTZnvSKIgtA0i+AbRFxXal9XGSZmVl3bNv8Po31y1hXv5TG5UtZ31BP045srtegwXsxZvIUxk6ZxtgpUxk7ZSqja8ajQqHDc7rIsj0p25wsSfsAuyJis6QhwLHA1eXqj5mZ9V1VI0cx9dC5TD10LpDN9Xrv7bVsaFjBhoYVrG+oZ/GCjybZf27IEMZN3Y/a6fszfr/9qZk2g8FDh5bzJVgFKufVhTXA7WleVgG4OyL+Vcb+mJlZP1EoDKB6wiSqJ0ziC/OOAaB5927effutrOhasZx1y5fwwn1/JaIZqUD1xEmtRVftfjPL/AqsEpTz6sLFwEHlen4zM7NihQEDsu/mmljHAUcdC8CODz+kccWydI/GJbzx1GMsmv9gmXtqlcL3LjQzMyth8NCh1M0+iLrZ2ZhAc/NuNq1ZzdvL3oC7Hyhz76y3c5FlZmbWSYXCAMbUTWFM3ZRyd8UqQMeXTpiZmZlZt7jIMjMzM8uBiywzMzOzHLjIMjMzM8uBiywzMzOzHLjIMjMzM8uBiywzMzOzHLjIMjMzM8uBiywzMzOzHLjIMjMzM8uBiywzMzOzHCgiyt2HTpP0AbCs3P3oA6qBTeXuRB/hLHuGc+w5zrLn7CnLSRGxz2fVGas8lXaD6GURMafcnah0kl5yjj3DWfYM59hznGXPcZb2afnjQjMzM7McuMgyMzMzy0GlFVk3l7sDfYRz7DnOsmc4x57jLHuOs7RPpaImvpuZmZlVikobyTIzMzOrCGUtsiTdIukdSa8VtR0o6TlJr0r6p6QRRdtmp22vp+17pfZD0uMVkn4nSeV4PeXUlSwlnSXplaKlWdIX07Z+nWUXcxwk6fbUvkTSFUXH9OscoctZfk7Sral9kaSjio7p11lKmiDpsfQ79rqkC1P7aEnzJdWnn6OKjrki5bVM0vFF7c6yC1lK2jvtv1XSDW3O1a+ztE6KiLItwJeBg4HXitr+A8xL6+cAv0zrA4HFwIHp8d7AgLT+IvAlQMBDwFfL+bp6e5ZtjpsFNBQ97tdZdvF38kzgrrQ+FFgF1DnHbmV5AXBrWh8DLAQKzjIAaoCD0/pwYDkwE7gGuDy1Xw5cndZnAouAwcBk4E3/W9ntLKuAI4HzgRvanKtfZ+mlc0tZR7Ii4kngvTbN+wFPpvX5wLfS+nHA4ohYlI59NyJ2S6oBRkTEcxERwB3A13PvfC/TxSyLnQH8BcBZdjnHAKokDQSGADuBLc4x08UsZwKPpuPeATYDc5wlRERjRLyc1j8AlgDjgZOB29Nut/NRLieTFf87ImIlsAI4zFl2PcuI2BYRTwPbi8/jLK2zeuOcrNeAk9L6KcCEtD4dCEmPSHpZ0qWpfTywtuj4tanNSmdZ7DRSkYWzLKVUjvcC24BGYA1wXUS8h3PsSKksFwEnSxooaTJwSNrmLItIqgMOAl4AxkZEI2TFA9kIIGT5vFV0WEtmzrJIJ7MsxVlap/TGIusc4AJJC8mGc3em9oFkw7ZnpZ/fkHQM2VBtW75kMlMqSwAkHQ58GBEtc2acZftK5XgYsBuoJftY5mJJU3COHSmV5S1k/1G9BFwPPAs04SxbSRoG/A24KCK2dLRrO23RQXu/04UsS56inbZ+maV1rNfdVicilpJ9NIik6cDX0qa1wBMRsSlte5BsvsedwL5Fp9gXWPeZdbgX6yDLFqfz0SgWZBk7yzY6yPFM4OGI2AW8I+kZYA7wFM6xXaWyjIgm4Cct+0l6FqgH3sdZImkQWVHw54i4LzVvkFQTEY3p46t3UvtaPj5q3ZKZ3990OctSnKV1Sq8byZI0Jv0sAD8HbkybHgFmSxqa5sDMA95IQ7sfSJqbru74LvCPMnS91+kgy5a2U4C7WtqcZfs6yHENcLQyVcBcYKlzLK1Ulul9XZXWvwI0RYTf30B63X8ClkTEb4s23Q+cndbP5qNc7gdOlzQ4ffQ6DXjRWXYry3Y5S+u0cs66JxtFaQR2kf1lcC5wIdkVH8uB35C+MDXt/x3gdbJ5HdcUtc9JbW8CNxQf01+WbmR5FPB8O+fp11l2JUdgGHBP+p18A7jEOXY7yzpgGdlE5AXAJGfZ+vqPJPsoajHwSlpOILvC+lGyEb9HgdFFx/ws5bWMoqvenGW3slxFdgHH1vR7PNNZeuns4m98NzMzM8tBr/u40MzMzKwvcJFlZmZmlgMXWWZmZmY5cJFlZmZmlgMXWWZmZmY5cJFlZmZmlgMXWWYVRNL9kv4naVqJ7Y9L+q8k30fNzKzMXGSZVZYfkt3v76a2GySdS3YnhMsi4u3PumNmZvZx/jJSswoj6Xzgj8A5EXFrahtD9m3prwPzIuc3tqSqiNiW53OYmVU6j2SZVZ6bgCeB61ruBQhcDwwFvg8Mk3SNpJWSdkpaI+laSUOKTyLpe5LmS2pM+zVIukrS4Db73SapSdIESfdJ2gw8nfurNDOrcAPL3QEz65qICEk/ABYB10u6AzgD+CnZTaufIrsp8M3ACmA2cBFwgKQTika5LiC7t90jZPdlOwK4FJgInNXmaZX2Wwxcjv9AMzPbIxdZZhUoIpZLuhL4NXA8WcF1LXAJMAs4NCJebdlf0mKyEbBjgfmpeV5EfFh02hslLQeulHRZRKwt2lYAFkTEj3N7UWZmfYz/GjWrXNcCrwKjgXMjogk4DXgOaJRU3bIAC9IxR7cc3FJgSSpIGpn2e5Js1Orgdp7vD/m9FDOzvscjWWYVKiKaJL0MzIyIhal5OjAE2FjisJY5XEiaSzYSdgQwuM1+I9s5tuFTddjMrJ9xkWXWtxSAJ4Bfldi+DkDSZODfwJvAxcBqYDswHriNT45y746InTn018ysz3KRZda3rABGRMSCPex3EtmI14kRsbqlUdJxeXbOzKw/8Zwss77lLuAgSd9su0HSXpKGp4fN6WehaHuBbFTLzMx6gEeyzPqW64ATgXsk3Qm8CAwim6t1KvBt4HHgYWAH8ICkm8iKrVP55NwsMzPrJhdZZn1IRGyXdDTZ912dnpatwErgBrLvuSIi6iWdRDbx/SpgC3AvcCPZFYtmZvYp+bY6ZmZmZjnwnCwzMzOzHLjIMjMzM8uBiywzMzOzHLjIMjMzM8uBiywzMzOzHLjIMjMzM8uBiywzMzOzHLjIMjMzM8uBiywzMzOzHLjIMjMzM8vB/wH/yS9zA4aCJAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 648x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels = dta.index[idx[-5:]]\n",
    "make_plot(labels)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here are the five countries with the greatest scores on factor 2.  These are countries that reached peak fertility around 1980, later than much of the rest of the world, followed by a rapid decrease in fertility."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/lib/python3/dist-packages/pandas/plotting/_matplotlib/core.py:1182: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  ax.set_xticklabels(xticklabels)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "idx = pca_model.loadings.iloc[:,1].argsort()\n",
    "make_plot(dta.index[idx[-5:]])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally we have the countries with the most negative scores on PC 2.  These are the countries where the fertility rate declined much faster than the global mean during the 1960's and 1970's, then flattened out."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/lib/python3/dist-packages/pandas/plotting/_matplotlib/core.py:1182: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  ax.set_xticklabels(xticklabels)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "make_plot(dta.index[idx[:5]])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also look at a scatterplot of the first two principal component scores.  We see that the variation among countries is fairly continuous, except perhaps that the two countries with highest scores for PC 2 are somewhat separated from the other points.  These countries, Oman and Yemen, are unique in having a sharp spike in fertility around 1980.  No other country has such a spike.  In contrast, the countries with high scores on PC 1 (that have continuously increasing fertility), are part of a continuum of variation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Oman', 'Yemen, Rep.'], dtype=object)"
      ]
     },
     "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": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "pca_model.loadings.plot.scatter(x='comp_00',y='comp_01', ax=ax)\n",
    "ax.set_xlabel(\"PC 1\", size=17)\n",
    "ax.set_ylabel(\"PC 2\", size=17)\n",
    "dta.index[pca_model.loadings.iloc[:, 1] > .2].values"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
