01_explore_dataset.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "sealed-hours",
   "metadata": {},
   "source": [
    "### Initial exploration of the dataset\n",
    "Looking for ways to present the records in an optimal way"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "described-incident",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "permanent-crash",
   "metadata": {},
   "outputs": [],
   "source": [
    "#read dataset\n",
    "df = pd.read_csv('data/test_export.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "marine-council",
   "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>id</th>\n",
       "      <th>days</th>\n",
       "      <th>level</th>\n",
       "      <th>energy</th>\n",
       "      <th>material</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>15.0</td>\n",
       "      <td>19.315345</td>\n",
       "      <td>6.575597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>16.0</td>\n",
       "      <td>164.275327</td>\n",
       "      <td>46.729636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>23.0</td>\n",
       "      <td>448.717153</td>\n",
       "      <td>153.574486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>25.0</td>\n",
       "      <td>685.119133</td>\n",
       "      <td>240.709294</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id  days  level      energy    material\n",
       "0   0     0    0.0    0.000000    0.000000\n",
       "1   0     1   15.0   19.315345    6.575597\n",
       "2   0     2   16.0  164.275327   46.729636\n",
       "3   0     3   23.0  448.717153  153.574486\n",
       "4   0     4   25.0  685.119133  240.709294"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "incorporate-reform",
   "metadata": {},
   "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": [
    "#Energy production per player_id\n",
    "ax = sns.scatterplot(data=df, x='days', y='energy', hue='id',palette='hls')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ideal-fruit",
   "metadata": {},
   "outputs": [],
   "source": [
    "stat1 = df.groupby(['days']).describe()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "downtown-motel",
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"8\" halign=\"left\">id</th>\n",
       "      <th colspan=\"2\" halign=\"left\">level</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"2\" halign=\"left\">energy</th>\n",
       "      <th colspan=\"8\" halign=\"left\">material</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>...</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>days</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1635.0</td>\n",
       "      <td>1093.931498</td>\n",
       "      <td>637.443778</td>\n",
       "      <td>0.0</td>\n",
       "      <td>543.0</td>\n",
       "      <td>1098.0</td>\n",
       "      <td>1641.5</td>\n",
       "      <td>2197.0</td>\n",
       "      <td>1635.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1635.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>767.0</td>\n",
       "      <td>1093.870926</td>\n",
       "      <td>647.142044</td>\n",
       "      <td>0.0</td>\n",
       "      <td>539.5</td>\n",
       "      <td>1094.0</td>\n",
       "      <td>1666.5</td>\n",
       "      <td>2197.0</td>\n",
       "      <td>492.0</td>\n",
       "      <td>6.443089</td>\n",
       "      <td>...</td>\n",
       "      <td>18.504522</td>\n",
       "      <td>1348.148867</td>\n",
       "      <td>388.0</td>\n",
       "      <td>8.074607</td>\n",
       "      <td>39.341785</td>\n",
       "      <td>0.004882</td>\n",
       "      <td>0.514000</td>\n",
       "      <td>1.266467</td>\n",
       "      <td>4.095308</td>\n",
       "      <td>555.946310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>601.0</td>\n",
       "      <td>1098.585691</td>\n",
       "      <td>653.410218</td>\n",
       "      <td>0.0</td>\n",
       "      <td>510.0</td>\n",
       "      <td>1104.0</td>\n",
       "      <td>1674.0</td>\n",
       "      <td>2197.0</td>\n",
       "      <td>386.0</td>\n",
       "      <td>8.370466</td>\n",
       "      <td>...</td>\n",
       "      <td>41.989841</td>\n",
       "      <td>4375.739594</td>\n",
       "      <td>351.0</td>\n",
       "      <td>29.093585</td>\n",
       "      <td>166.331749</td>\n",
       "      <td>0.008082</td>\n",
       "      <td>1.003068</td>\n",
       "      <td>3.019200</td>\n",
       "      <td>11.888113</td>\n",
       "      <td>2718.297819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>523.0</td>\n",
       "      <td>1103.950287</td>\n",
       "      <td>653.963701</td>\n",
       "      <td>0.0</td>\n",
       "      <td>522.0</td>\n",
       "      <td>1122.0</td>\n",
       "      <td>1688.0</td>\n",
       "      <td>2197.0</td>\n",
       "      <td>332.0</td>\n",
       "      <td>10.180723</td>\n",
       "      <td>...</td>\n",
       "      <td>65.963724</td>\n",
       "      <td>6844.391985</td>\n",
       "      <td>332.0</td>\n",
       "      <td>53.969348</td>\n",
       "      <td>282.678238</td>\n",
       "      <td>0.008082</td>\n",
       "      <td>1.605126</td>\n",
       "      <td>6.055864</td>\n",
       "      <td>23.446231</td>\n",
       "      <td>4511.022078</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>467.0</td>\n",
       "      <td>1104.486081</td>\n",
       "      <td>647.536223</td>\n",
       "      <td>0.0</td>\n",
       "      <td>522.0</td>\n",
       "      <td>1152.0</td>\n",
       "      <td>1671.0</td>\n",
       "      <td>2197.0</td>\n",
       "      <td>302.0</td>\n",
       "      <td>11.496689</td>\n",
       "      <td>...</td>\n",
       "      <td>95.199466</td>\n",
       "      <td>12112.632236</td>\n",
       "      <td>306.0</td>\n",
       "      <td>93.703066</td>\n",
       "      <td>470.450033</td>\n",
       "      <td>0.008082</td>\n",
       "      <td>2.388732</td>\n",
       "      <td>8.903589</td>\n",
       "      <td>39.297504</td>\n",
       "      <td>7050.446730</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          id                                                               \\\n",
       "       count         mean         std  min    25%     50%     75%     max   \n",
       "days                                                                        \n",
       "0     1635.0  1093.931498  637.443778  0.0  543.0  1098.0  1641.5  2197.0   \n",
       "1      767.0  1093.870926  647.142044  0.0  539.5  1094.0  1666.5  2197.0   \n",
       "2      601.0  1098.585691  653.410218  0.0  510.0  1104.0  1674.0  2197.0   \n",
       "3      523.0  1103.950287  653.963701  0.0  522.0  1122.0  1688.0  2197.0   \n",
       "4      467.0  1104.486081  647.536223  0.0  522.0  1152.0  1671.0  2197.0   \n",
       "\n",
       "       level             ...     energy               material             \\\n",
       "       count       mean  ...        75%           max    count       mean   \n",
       "days                     ...                                                \n",
       "0     1635.0   0.000000  ...   0.000000      0.000000   1635.0   0.000000   \n",
       "1      492.0   6.443089  ...  18.504522   1348.148867    388.0   8.074607   \n",
       "2      386.0   8.370466  ...  41.989841   4375.739594    351.0  29.093585   \n",
       "3      332.0  10.180723  ...  65.963724   6844.391985    332.0  53.969348   \n",
       "4      302.0  11.496689  ...  95.199466  12112.632236    306.0  93.703066   \n",
       "\n",
       "                                                                        \n",
       "             std       min       25%       50%        75%          max  \n",
       "days                                                                    \n",
       "0       0.000000  0.000000  0.000000  0.000000   0.000000     0.000000  \n",
       "1      39.341785  0.004882  0.514000  1.266467   4.095308   555.946310  \n",
       "2     166.331749  0.008082  1.003068  3.019200  11.888113  2718.297819  \n",
       "3     282.678238  0.008082  1.605126  6.055864  23.446231  4511.022078  \n",
       "4     470.450033  0.008082  2.388732  8.903589  39.297504  7050.446730  \n",
       "\n",
       "[5 rows x 32 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stat1.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "conceptual-population",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>days</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1635.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>492.0</td>\n",
       "      <td>6.443089</td>\n",
       "      <td>4.351980</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>30.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>386.0</td>\n",
       "      <td>8.370466</td>\n",
       "      <td>5.695298</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>33.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>332.0</td>\n",
       "      <td>10.180723</td>\n",
       "      <td>6.777686</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>302.0</td>\n",
       "      <td>11.496689</td>\n",
       "      <td>7.914723</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>50.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>0.0</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>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>0.0</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>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>0.0</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>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>0.0</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>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>0.0</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>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>184 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       count       mean       std  min  25%   50%   75%   max\n",
       "days                                                         \n",
       "0     1635.0   0.000000  0.000000  0.0  0.0   0.0   0.0   0.0\n",
       "1      492.0   6.443089  4.351980  1.0  3.0   5.0   9.0  30.0\n",
       "2      386.0   8.370466  5.695298  1.0  4.0   7.0  12.0  33.0\n",
       "3      332.0  10.180723  6.777686  1.0  4.0   9.0  14.0  36.0\n",
       "4      302.0  11.496689  7.914723  1.0  5.0  10.0  16.0  50.0\n",
       "...      ...        ...       ...  ...  ...   ...   ...   ...\n",
       "179      0.0        NaN       NaN  NaN  NaN   NaN   NaN   NaN\n",
       "180      0.0        NaN       NaN  NaN  NaN   NaN   NaN   NaN\n",
       "181      0.0        NaN       NaN  NaN  NaN   NaN   NaN   NaN\n",
       "182      0.0        NaN       NaN  NaN  NaN   NaN   NaN   NaN\n",
       "183      0.0        NaN       NaN  NaN  NaN   NaN   NaN   NaN\n",
       "\n",
       "[184 rows x 8 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stat1['level']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "completed-fraud",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:label='028df830-d420-4470-857f-4b6cc065376d', xlabel='days', ylabel='energy'>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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RQy6uP33VKYkB0bYTrsVisWxFlNKMVkLSbRoMcewxBxFNZ+cMcUoA2d4pnVacLBbLlqUWJSit27amXhAK6TmKuyaJIG57V7VYa6w4WSyWLUu5Hq1N+YJVIolhrtzgJAZx2nnka48VJ4vFsmUZrravS0+puRNwAVQiVpw2egAWi8WyVlSDhNQmqgwxQRKDuFacLBaLZUsStnMPp2T+iqmJspaTFSeLxbIl0Vq3fYNB0XOPTSWCY8XJYrFYth6x0ug2nt+VmpV7O7XPuvWsOFkslq1JonRbd781ZYvmFiClrOVkxclisWxJokS1dRi5WqD/oUrEWk4bPQCLxWJZC9rdckqUzOt2VIngtGcE/LphxclisWxJYqXb23JaIJRcKaxbb6MHYLFYLGtBFCukjW0nlbCw5eRZcbJYLJYtRxC3bxg5mFYZ8w1PKcG1a04Wi8Wy9Wh3cYpCkHlmYJ3IvPu2C9v841sslq1KPUpw51vUaaJShgvnZbI1+nphir7ObR1pJbjWrWexWCxbjyhReO7C4jQ8JNz7XY9HD7kE9XUaWIM4ljkrkoOxnFwbrWexWCxbj3qkcBaxnMpFSKU0nqcnW6OvF3G0gFvPrjlZcbJYLFsPpTSxWnzNqVQSUimTD5Wo9V2fipO5ezlBo0KEFSeLxWLZWsSqtYm9WhE834R0b4TlNK922jUnK04Wi2XroJRmpBK2VB0ijk3EnOcZCyaK1mWIkyTJ3GtO//SFABU5+P76jqfd8DZ6ABaLxbJaXCrWefhcket2dSxaHSIMQWsBNK6rCYP1GOEUcQyp1NTzx0/GvPc9DkOP95PurfHyH1/f8bQbLVlOIvILItKz1oOxWCyW5RIliqNDZfJpj5PD5UWPDwMjTACuC0G4zmtO0dSa06MnYn7vlzsZPlHgaS8d5s/fW+eGaza37bBS3WjVrbcbuFtEPiEiLxJpIXnAYrFY1pFzozUSpSmkPVzHwV+kPXtQn4qWcxzW1XJSyqxzTcykDz6UoGOXN/23MX7151KkUltixWVFutHSFdBa/w5wLfC3wBuAx0Xkf4jI1fO9RkQ+ICKXROThefY/V0TGReSBxs/vLWXgFovFMkGcKE6PVunKGD9ZZ8anM7Pwok25BH4j6MBxIQpWfs99/qwwPLT4eZSC5kWxWs383rtz4+77V3vOXo5uNNOyPGutNXCh8RMDPcA/icifzvOSDwIvWuS039Ba39r4eVerY7FYLJZmJoIgFgodTxKmVYEol2Uy6MB1IVxhQESSwMljDvXa4seqZJo2UWskAOfzG+qU+iCrPGcvQzcmaXXN6ZdE5F7gT4FvAbdorX8OeDLwinkG9XVgpJXzWywWy0o4PVIln1p4jWZ0WHjskDNZCbxWmRInxzFrQMtp6x6F5nUjQ0KxKC25BxPFtB7t9YY4dWygOK32nL0c3Wim1RW3fuDlWutTzRu11kpEXrrEMTfzDBE5CJwDfkNrfWiug0TkLcBbAFLN4S0Wi2XbU6pHlOoR/YXMgscFAQyccejdoUmnIQqnEl0nVkOSxISWt0qtBgfvdcnlNFEkFAqaKJ4KtJgPrUDL1DH1mhlAR2FNaxZ5InJP0/M7tdZ3LvEcLc3ZDVakG61+De8BEJHepm0lrXWktX6kxXPM5D7gcq11WUReAnwW45+cReMC3gmQz+e3d2aaxWKZRrke485XaqGJoA4dHZrHDzsgQmenmrZfYxJxWxWnKIJHH3JwHROGHkaQzbYWkp7McOuFAeAoFjH+Vkqstb5jBa9vec5u8B5Yvm60uuZ0HzAIHAEebzw+ISL3iciTWzzHNLTWRa11ufH4i4AvIv3LOZfFYtm+lIMYr4XWGGEgpNKanj5N/w5FKj3zCCFJWnvP8VHh4L0u9bqQL0AuD93dGseFuIWQdK2muxCDQHB8Nf8L2oBlzNkr0o1WxelfgZdorfu11n3Ai4FPAP8V+KsWzzENEdk9EVooIk9tjGV4OeeyWCzbl1IQLxo2Dsat57nMW+1b0Iu2zajX4LHDDgfvd3EcTVf3dEeO4ywcWBFFcPG8zKrjFwaC47WojBvEMubsFelGq0bkHVrrt0480Vp/SUT+h9b610Rk1v1HY/AfA54L9IvIAPDfAb/x+vcDrwR+TkRioAa8uhHZYbFYLC1TCeJFw8bBWCeZzPxTjNam4OrM9aIkMdUkhi4Jp044eB709Snmytpx3YXLIA0PCYcPulxxtZrm14sCwU1trOW0BnP2knWjmVbFaUREfhP4eOP5TwKjIuICc15RrfVrFjqh1vp9wPtafH+LxWKZRRgr4kQv2hpDayMa+fzC55tZ/HVkWHjkYQeUgGi6uvSCfZZEGkVkk9kWmtZw7rRDoUNx8fxMy8nB3WC33hrM2UvWjWZadeu9FtiPWQD7LHCgsc0FXrWEwVosFsuqEcTJnBbMTJJkekWGuXAEoiZxGh0RDh10KBQ0PX2Knt6FhakZNYeHrlKGSkUodJjKFM1WXBwK3gZbTmvAinRjUcupoXLv0Vr/1DyHHG1xoBaLxbKqBHFrE3ocgSyyaOC4JmouqMPxow6Dlxw6O9WSq4OLFuKk4Q9r4tIFwffNIDo7pw8mDh0yhQQWraW+OVgN3VjUctJaJ8AOEbEJRhaLpa2oBjFuC6ZTkkzLeZ0Tx9GEgXD0iMPosNDXp1hOWqUWPaflNHjJIV+YWyGTyMFPbZ0l99XQjVbXnE4C3xKRu4BK0wDevdw3tlgslpVSDluL1IsjWSwvFteF4hhUykLfjuULhTB77SoKzZrXfG7BJHLw04ot1mLvJCvQjVbF6VzjxwE6ljhAi8WyyQjiBN9xcFrIH9pIyrWYlNeCOLXgMXNdGBl26O5d+dpPnEyP+qvXF357FTmk01vHcmqwIt1oSZy01u8EEJG81rqy2PEWi2Vzc3ywwp6uDN259vXmJ0pTixQ9/uJRClG0+GqOn4KubkVm4SpILTHTrRfUZcG6fSp250gK3tysVDdaLfz6DBE5DDzSeP4kEVlW8q3FYmlvEqUZLgckqr3v5M+OVtFoWmkTFAbzu9QmEIFsbuXjEmbnOpWKTAZDzCSKgcQhvUAO1mZkpbrRqoPzPcAP0cgG1lofBJ69tKFaLJbNQCWMKQcxSRvnxJfqEccGK3RnW7PsgkBw3fX5PM4cibjj4zJvcEW5YsysTLZ9r/cyeQ8r0I2Wywxqrc/MuENp71obFotlWRRrEWGsiFoM014PEqV5+Nw4XRkfjeb0SJVcyl2wf1MzQR3cdep6PhH1N7HmpDVUyzKr1NEEpYbDazXcie3GSnSj1a/rjIg8E9CN0MBfomGqWSyWrcVgKSCX8oiS9rmTD2PFSDmgWItAQ1cm1bIwgaldt16Wk+ua6LwJ6nVTFknmSbQqV8xNQHbridOKdKNVt95bgZ8H9gEDwK2N5xaLZQsRJ4piPSKXcomS9rGcwkThiNCdTdGdW5owQWPNaZ2itGcWfw3qgl4gjr1SNb+z2TUe2PqzIt1oNVpvCHjdMgZnsVg2EZUgQWtwHSFS7SNOUaIWS1OaF6VMEq6zpn38pjAt36fEc/iS4C3w3uWK+WS5bHuH7S+VlepGS+IkIjuANwNXNL9Ga/2m5b6xxWJpP0aqAa4IjghR3EZuvUjhLLO0TxQumn+7qjguxA1raHxUOHvWoa9vfqGftJxy7XO9V4OV6kara06fA74BfAUbCGGxbFkuFQPyac9U8W4jt141ipfsypugVlu8OsRq4jgQx6b306OHHToKc7fXmBqfGVwht6WqQ8AKdaNVccpprX9zqSe3WCybh1qYUAsTcgWPOFHU2yharxYpPHd54lQcXzzHadURePigi9aQXiTQoVYzv/OrkGPVZqxIN1qV6s83esZbLJYtSqk+VUbBcaStLKdai91u52J0ZOEmg2uBVqASPav6+FzU6uZ3obC11pxYoW60+m3/MvDPIlITkaKIlESkuNw3tVgs7celUkC2UQrIEUFpUG1SJaIeJ3jLcOslCZSKsu6lgfr6NYUWq8nVa+ZzdeS3nDitSDdaFacu4A3AH2mtO4GbgBcueagWi6UtUUozUgnJzKhT1w5VIqJEoTQtlSmaSbWR4CoCdz8Y0UYBiJPUG5ZTR2G9fY9rzop0o1Vx+kvg6cBEG98StsW6xbJpqIUJl4r1efcHsULr6e3OBWmL+npRopbdgq9aMa+858GIP39bLx/5ZDD93DG8+69CfvcPorlevi4EgYCjSK1TBYt1ZEW60ao4PU1r/fNAHUBrPQq0b7lii8UyjVIQcWEBcapHcwVT6fYQpxWEtI+OCJm05vSAMZm++ZWp6IQz5xJ+8Zfge1/o4/Fv91KpbcxnDevg+G1o0q2cFelGq+IUNdruapiMX9+SV9Ni2YoUaxGVIJ53fzWMkTnsk7Zw66nlJeBqbfKM0hkYHDLbSucK3PdwxBe+GvJbv5RjfCDHjmvHATg1MP/1WUvCQHC8LZmhsyLdaFWc/gL4DLBTRP4Q+CbwP5Y4UIvFskEU6zH1KJlmCY3XIk4MlgEo1WP8OZr2bVRAhG4SxSBKprkbWyWoT3WfHR2ZCENUvPePs3zk3b342YT/9kfj/MjLjSidGtggyykU3K1pOa1IN1otX/RREbkXeD4m2PTHtNa28KvFsgnQWk9aTWGsyKbMwvtQKeDceI3L+/IUaxHpGeKkYUPcekGc8Mi5Ijft68J3Harh8iL1arWpBn/jYw5OJmL3NRXOPdzN5beP8vbfcujM+zx6zFyb8+c3RpyiwMFNbT1xWqluLKVlxqPAo0sfosVi2UiCWKGUCXaYECetNZdKdYLIFHqtRgl9c6zIb4Q4leox58br9OZT7O7KMlgOSC9UnG6+8xTBa3yk8rhDKh/xtt8UHn50mOc9c2rp44r9xvN08eLGhHJHgeClNt59uhasRDe2XnyIxWKZRhBN3ZWHjcTaWpQQRIqU53B+vDZnNJzDxiTiXirW6cz4nByuUKrHxImmI730BNyxEZnsLlsruWQKCTt6nWnCBJBJC14uYnRoY8oHxZFDJp+weCP57cWWK+ZksVimU4uM28oRoRaax8WaqQaRT3mMVKI5Aw5MlYjVv6OPEzVPdKCx1IbKIR0ZD0G4VArozvpLfg+loFQS0o3k26Dske+cP+gg0xUyPrL8e/WDj0b8zrsi3vB6j2OnlxbckIQO/ha1nFaCtZwsli3KYLGO7zkU6zEp10UEyg1xulisk/VdUp7DeC3Em6M0kCurbzlprTlyscTFYsA1Owvs687iNK0nlesxqpFv1Z1bfrZKvQZamwZ/SkFc9enorgJzuwc7emKGBzJA6/lOUQz//OWAL38+xejJXswqnXDwUIWrL2vdDZlEDn5aYW2F6ayZOInIB4CXApe01jfPsV+A9wIvAarAG7TW963VeCyW7caFUsDF8Tr5lEuqsWZTDRKCOGG0GtHbmPyzKW9WMASY6tqrKU5xojg/XudCMaA3l+LIxRJpz2Fn51Tu0WA5wHOWN0lrDRcvCCePOSQxOI3OsyPjCp24dPfM/1l6+hPOP5oiTqIFey8BDI4o/v4fI+77eoGo2IGXD7j9RcM88+nwvnf0MTba+phPn0tIApd0euMtp3abs9fScvogJhv4w/PsfzFwbePnacBfN35bLJZVoBLEdGZ8ykFk2mBgwscvFU2VhIlyQIX03NOAIzK5RrVSjl4qMzBaRWtNby6N6whdWZ8TQxX6C2kcRzg7WuPUSIW+3NIL4VXKcOyIw9io0N2t8Zo8gWcvGjdbb+/8r9+xU4NyOHcx4bK9c6vT3Q9GfOqTwqmDnejEpXN/mR/+ySF+7CUpMqkUY0VzrcbHW1s7+vAnAr744V7QDldc1RbReh+kjebsNRMnrfXXReSKBQ55GfBhbRIaviMi3SKyR2t9fq3GZLFsF5TSBJGiN5+aDB0XIFFwaqRCZ2bxdRzXEeJVWnMaKQd0ZvxplcXTnstQJWCkGlKqRxwfrNCXT7fctymK4NGHHYJAqFUhk9H075g93ouXzLadO+Y/7+7dZt/JgeniFMbw6c8H/Pu/pCkO9CJuwmVPKvLKV2qe8iQfmBLSzoIDrqLUYmnT730rhV+I+K13VbjpunWuTDsH7TZnb+Sa0z7gTNPzgca2WR9URN4CvAUglbJVkyyWxZjP4hGBKNH4mcVdZ44ItcjU5KtHCX2FNPl5rKyFUEpTixN6/NkWSc53eXhgHARjQS0h2XZ0WBgbFbq6Ndks8zb0Gxw04rR75/znPrDP7Bs4a449fynh7z+RcPDrBeJKB35Hnae9dJjXvsplV988lqYDXiaiXGrNLVkZ8+jaWeem65Ye8LFMPBG5p+n5nVrrO5fw+pbn7NVgI8Vprr+UOW/TGhfwToB8Pr/xzlmLpQ1JlObxiyWu3dVBECvm+nfyXYdUi32RHIFyPeLw+SKOCMcGK9x+eQ9dS4yeCxMFWuasKp5LebiOLCuPaeCUQ6GgJ3OZ5mN4xPzes2v+z33lZWbfwXtd7vtewsDDnaAcui8v8YNvKPEjP5jG9xa/MfazCdVya9c3KKbYe3WddQyEiLXWd6zg9S3P2avBRorTAHCg6fl+4NwGjcVi2fQMlwMGRmvs68kSxnPXo2vFnTeBiLCnKzspKmPVkPFquGRxMnlW889hyxGmcgkqFaGvf/G5cWzUAUexo2f+9+nrdnFSMafu70H8hKufMsZP/ATc+oTprrvFSOcSgspkObl5GR5LUKE3pxuyjVnXOXsjxeku4BdE5OOYRbVxu95ksSwPrTWnh6skypQqCmOFu4x6dDNptnYyvstgOeSyvvySzhEkyarfXl845+D7rZ21OGaSbBcLAnzBq8aoVoXXvMKlr3t5rrZsIWH4XBpYuIjs8dPG7bpr96YSp3Wds9cylPxjwHOBfhEZAP474ANord8PfBETkngUE5b4xrUai8Wy1SnWYkpBTFfWZ6QaAiy7rfl8pD2HkWpInKg586Lmo1yPlx0ePhcjw8LZAYe+vtYi3CrjLun84hXH3/SalQcl5DoUF2sei4nTmbNm7Pv3tU9ViHabs9cyWu81i+zXwM+v1ftbLNuJwXKdlOuQ8V1GyhFpT1ZdnERMU41KmNCVbf3cpXrc8jrXYgR1OHLYoatLLWoJTVAve+S7Y9ajPFChQ6MCjzBmweaB586ZsVy5v32637bbnG1Tki2WLUCpHpPyHFzHdK+thgm+u/qTsSCm9NESqIbxqo1l8JKQKGg1aHesqKiNZOjbvT69mjq7TJWI4ZGFSxgNXhLETdi3u33Eqd2w4mSxbAEqQTxpKWm0KaSzCmtOM8mmXIYrU63O40RN6700kzhRBPHS3IALcfG8w1ICdv/jWzEoh6c9bX3Wdrq7zO+Lwwu7HMeGXPyOsGXrbztiL43FsklQSs9ZMDVKFLHSk8mrvuOsWvLsTNKew3gtmhSkk0MVijVjlZSDmPNjtWnHB7FaNWdatQq1qrRsNQHc8z1BvITnPWt9col6esynHV5EnMqjHvnupVmg2w0rThbLJqFUjzne6FzbTBiraZHLHRmPvvzaJKuLCGgaeVQwVosIYiOY5XrEsaHyZPfckUrI8aHZ410u42OmkGurKAWnH83Rd3mZbHp9Ag/6es37jCxSX69e9Ons3ZKt2VcNK04WyyYhTBSDpWBWA8AgVtPW+kVk1dxoc6Ex1prWmmoYUw6mLKdiLWa8FjFejXjgzBjlekLPCqqLN3PxrJDLtS5Ohx+PiIoZbrpt/SyUnf2NnLCx+Y8pVxVJLUXfDitOC2FbZlgsm4RaGFMJEyphPC2ZNogSZJ0b1YWxIvI0YayphGaSrQQJWd/l7FiVeqjIp1xyC4WsLYGgDuWy0Nu3hPWmb5hjn/fs9Qs62Nln3muh4q/Hz5jrtWvXugxp02LFyWLZJFTDBAHKteniVA5WLxpugjgG1527Xp2DUI8S0r7pEVVpspy6sz6DpRBE05/PzH7xMqlUlv75HnnAJ9Vd44ar12+ay2cF8RNKxenjjRP45vdCvvpV4cTBAgCXX9Y+OU7tiBUni2WTUI0S8mmP4WrI3p7s5PZSU6TeSoljODcgnD3tcOMtiq6e2ZaK5wrVMCGbUriOEETKWFKJwsv45FLuquU1TTA6JKSW0C22XFWMni5wzVPHaeSRrhteJqIyo/jr234v5swDfaaM0tUlnvGcIs9+2sZXIm9nrDhZLJuEahDTkfYYq4QopSc7yFaDmEJ6dSbgU8cczp0VNFCvQ9ccx/iuQyWM6Yi9SWdiOYgnH6+WK28CrWFoSMhmlxZCrhOXp65TCHkzfi6hVpkSpw9/IuDMA/1c/8wRfunnHfq6XZZSr2+7YsXJYtkExI1wcc91SJSm3Fh3mhlGvhJGR4SzZ01ZoErZFFfdtWf2cb7rUAlMIITnOMRKUaqvXdBBrQZxKHgdrQvN975rklyf96ypKS5JjNAtVsV8pWRyCfWKy6EjAf/6ZcU9X+6mY1+Z3/lNH9/OuC1jL5XFsgmIEj1pmWRSLvedGuWy3tyqFHcFM3EfecShs0MhAr5vAhDmqq7tOkKUKEp1406MlKJcX7sKDJWSoOcJIT8xEPMvX0p41Y/79PdMWSunHsnSc1mFQm5qW3FcUIqWKpmvhGxBMXKig9//VVMgt7CnzG++PcJfa1XcYtirZbFsAsJ4Kqkzn/LIeC5nR2toILcKt+PjY0IYQkeHee6noFQUtJ47KGKixl7Od/ES4+ZbzeKuE0QhnDsrZNKzBeWP3h1y8N97QDs8dG+R974Xzl6I+chHFeFYB094XhWYCmOf77OsNk95eky1VOLG20Je/EKXay73sFPt0rFXzGLZBITJ9P5MriN0r1L+EMD5gelrOo5jWrpHIaTmWR6JE4Wf8fFdRTVIltUldyGqFXjkYZcggO7u6eJ05lzCwX/vpf+aIldeG3P3F/t465srVAe7AGHXDeP81E9MDyGfsAjDcKo2n9ZQKUOtJvT0aLxVWLp79Y+lefWPgV1XWhlWnCyWNkQpTT1OJoML6lGypBbmC6G1icjbsVOTSps1nZERobd3ugAIEARzi5Mpb9ool+Q6DEfBqorl8JDw6MMO6bSmu3v2/k9/PgEt/D//JeHWJ6T472MjHLm7i+ueMcZrXyvccOUcU5sWunoUo8NTkX9jY0JPryZX0NSrrIo4WVYHK04WSxsyVos4PljmyZf3ICLTCruulFoNjj3mMHAarrzaTNYis11eGgiDedadRIga9fs8R8j53qoEZWgNA6eFE0dduroV/jxi8cC3suR3VRqdauGdb/eJkyqeO7+6aNH09WsuXZwap1Zw4HLFyJBQLjqsYddxyxKx5YssljZkvBYyWKoz3mhPUY0SvFWY/AHKRcHxwPc1Rx5xGBud7TYD8FxTbHUu8mmPfNq4zUSEvsLKXVhRaHo1nTjq0Ns7vzDdfTCiNpTj9u+bXmR2oW7vE+tNXd16UoS1Mf/I5SGTNTlelvbBWk4WSxsyXA7J+h5nx2pkfJdyfXpViKVQr5nJd4KRIRNgkMlAJjO/peD5mkppbsvJd51Vs+SKY1AqCQOnHZLERNPN5cGMYvjT94Yc+mYX4ia8/Edan76SGDIZE+hRyGuCutne0alxXbN9PYIlLK1jxcliaTPiRFEOYnryKS4VA4q1CM+RZbnNajV46H6Hm29V5HKmUvfwsNDVtbj7KuUb0QgDsxZTq0I2x6r1IEoSOHnU4dxZB9cx6z4LtcP45D8HPPTv/ey4bpzXvj5hz47WxTqOId0Q4r0HjMXourD/chMF6fvWndduWHGyWNqMiUKqjggZ38ERIbfMSLgLZ4XxUYeL5zRXXqOplM06SysC4/lQKsP3/q+LOJBEcMvtip7elU3k1aqpRFEcF6IIevtUS1bL1/41g99Z53/9T2fJVdfjGLoa4tTbr3EciCLo7DT7PR/Qc1uJlo3BrjlZLG1GuR5NRuYV0v6SygFFTYUawgDODTjs2qM4d9YhDGBkWJZk+fT0aHr7NN3dupH71Ppr5+PCWWFkWMjlzblbEaZ7HowoDhS4/dnlBdeW5iOOhUzOPPa8KYsp1+iq63nMm+hr2Ris5WSxbCCPnC/iOcLOjgxdOeOmGqlGpL2l3zeGAdx/j8ve/YqduzQDp8w5PM8s/j/0gEOlLMuyfESMW2x8VOCK5U/iSsGlCw6dXWatp1U+9SlTjui1r1relKUUpJtiNnbu0gSBEVww+U+OrF+irmVxrDhZLBtEJYi5MF4n5TqcHavxlCt6UVozVAroXUYn26FBIQrhxFGHU8fBcU10GkBXlwkC6N+xfGFJpUwJoJVM4KVxmWzH0SpRDKce6mDvjSV29S2/N1Nz9F8mC9deP72Vejpj3H/zRQnOh0rMtbasLlacLJYNYrgc4DlCZ9anGsYcOjdOmCjyKW/JCbdJAmdOOXR2mioHMwXEdU3I9EKcH0z40EcTwgD27NO8+aemh4c7Dmgl1OuQzc5zknlQyoxn6JIsOfjg2/eGqKCDJz8tBpapAmKiDxcindGE9aWJk0pgaMjBcTSZjCYIhHRaU+hY3jAtU1hxslg2AK0158brkyV/cimP8VqI6zhkU0ufgEdHTFTdRG28pVo2//CZgM9/pBsVuOBoDiuHZz1thBuvnT5TazS16tLaVwA8cshhbFiIo6UXXv3W/wVE8wPfv7LpajHRyWY11fLiFy5JTORioQPGi8IVVyd0dBrLNZvRnD5lAytWAxsQYbEsE6U0Si1vEqqECfUomZYr1JVNUVhGVF4YwLEjDoXC8sby8GMRd/1dL7neOr/1Z6P86rvGAHjgYTXrWM8zrTSWQrUCI4MO3T3aRMotUXuPPZyhsKvK7v7l+86ExUsTmUTcKXEqjguJCZxEKXOdwxBGRxzSGVNiSYB9+03lieufoOjs1laXVglrOVksy0BrzaMXilSDhOv2dCw5QXa0Eq5Kuwut4fEjjlnwX0ZX9DiBv3i3j+Mqfu9dMZft9akHGlzFkcdm37um0ksPirhwTvA8E5W3lLUmgAtDCeWLBZ70/BGaK4wvhSQxwrRYlGI6bUQIoFgU/JRmbFTo7dOMDAsdHZowFG58YkJvn+bUcSGTZTKoAsB1W4s+tCyOFSeLZQlEicJzhMFSwIWGW+6B02M8/ao+UkuIsBsqB2T8la2ixzEcf9xhZFCW5Cr7+0+FnDgmPP0Zmi/e5VIc6OYFrx3isr1mjSmTFvL9Nc6fnC24qRSMNyyK+YSmXjMWhuuayf78OYeuzqWbE7VA8+F/iEELz3rmkl8+Sakk7Nk72wqcie8bd2itan7f9ETFY4cdLl4QDlyuufaG6ee48po5ag562HypVcKKk8XSIonS3HdqlFhp4kTRnUvhuw61KKAeJy2LU6I0xVpMT275JbDDwKzjlIvmzr5VLg4nfOEj3ejI5dB/grgJt75wmDe9Znrww67LQk480EGc1KblFTmOCQKolKCze/b5i2Pw0EEXmrxbnre0aLaHH4v4p8/Akbs7UPVOcrsqPOPJy7OalDI/e/Ytfo08XxNGguvCLbclZLJwzfUKz3e48prFxQ3At/lSq8aaipOIvAh4LybE5m+01n88Y/9zgc8BJxqbPq21ftdajsliaaYWJojQkhUzXouoRQldGR/tu5PrRRo9rRkgGAvr1HCVME64cW/XtH3VMEajkWX6f+o1OPSgSxSxaM7SJ+4KiBN47Y8b8fng3yfoyOUN/22YwSHNM57ics3lsyf+q69LOH63x6NHI26+frqI+r5J5u2cUSx2ZFg4dNCho0PP2wNqPspVxWe+GPHNr6QZP9MLoth1fYkXvjjmRc9LLSvxFozVtHevnlZbcD5SKejvV1x9vSn1BJAvGAuqVdxNfrvfTnP2ml1KEXGBvwReCAwAd4vIXVrrwzMO/YbW+qVrNQ6LZSGOXirRk0+xvye36LFnR6tkPHdW6RxPHKpBDI3K3EppDg6MUanHgJAoPa0uXiVYfvnrShkePugi6MnSO/PxibsCPv3/9YHA/r0j3HqTx8H/7KTv6iIveu7ClsgTb3L4MnD/Q4pMJuYDfwdD5z3+13s0uRxcuuhw+VVG2LU2nXQPHTTJtUsJxf7u/RF3/TOcuL8TFXr4nXWe8pIhXvXjHgf2uix3nWmCJIbd+1u0elJwy22tC9FcOI5J5lUtloiaiziBSlWTyazv4lW7zdlrqfNPBY5qrY8DiMjHgZcBMz+oxbIh1MKEi8UA1118EqhHCUPlkL45kmNTnkOpPiU447WIUi2mv5BmuBJQDmK6slMz9kg1JLMEUyBJ4MxJoVwWxkZNuHJ2ES396jcDPvM3PRT2VKiXfP7Pe/Kksgkq8Hn5T46zWJfWW57gIW7Clz9V4AsfSoEyM+337h/mec9MERaF4pgwMCCMDglKC52d87e5aGZoVPHJz0bc/fUs1Uu94Cr2PqHID7444QXfn8JzWze74thYkp5vqo43U69BR5eetILWi1SmkZi7RHEqlhWj4wrHEa7Y73LbE1aveWOLtNWcvZbitA840/R8AHjaHMc9Q0QOAueA39BaH5p5gIi8BXgLQGqhssUWyxK4UKzhCJRri1syw+Wg0ZBvtpD5rkOpyRo6NVwh18hVchCKtYiurM94LSKXchkpRy2HjCcJPHrYYXRIyOU0XfOU/Yli+N13xoyPujzlmSFf/kQ3qY6Q3/+jmIcfC/jbP+5Fq5AX//QQz3/W4pN/JiV07q0yfjbP1XeM8dIfgff+bi8PHNQ875mAaA49ZGZfs+bV2jrLA4cj/uS3O9GRR3ZHle9/xRCv+jGfHb0uS02wDepQrZmOvpcuOGQy062eak24/oqVWULLIeVrknjpXXVHi5rnPSPLk65Pk/LXxGryROSepud3aq3vbHq+anP2arCW4jTX1Z35F3wfcLnWuiwiLwE+C1w760XmAt4JkM/n7WqjZcXEieLsaI2eXIrxejTL9TaTC8WA/DwFWH3Xodg4Ry1KGK1G9DdcfNmUy6VSQHfO575To3iu6SDbSvuLJIEjjziMDi8c9KAU/M47Y07d14OTivnSRztJddZ5x5/U2bPDY88OlwPvHePAXpd8tnWr5F1/mBDHRfbtMrPsX3fWOXHEPO7q0kTRbGtlIcIY/uJ/phFH8wvvHOZZd6RYzIJbiHJZeMItiv4dmmoZ6vWp8ejG5eruWf/pIpWGcriMF2pNb5ezVsIEEGut71hg/6rN2avBWibhDgAHmp7vxyjtJFrrota63Hj8RcAXkf41HJPFAsBgKSBKNJ7rIEAQJ5P76pFJkJ0giBOK9WjBoImJc5wfq01LrE17DqV6xGMXS2R9l0LKozOz+D3hhDANDwq9CwQ9KAW/+wcRp+7r4ebnjfBXH6rw/NcM8c4/q3Hl/qn3ueFqj3x2aZPerj6XfbumPvOOK2oMD2RRyoSJL0WYBi4kvOuPIqoX87z09eMNYVo+9RoUCnoyhH7/5ZpqxXy+iTWwvj49LQdpvUilNCpZ/LiZiGMiGzeQtpqz1/JS3A1cKyJXAmeBVwOvbT5ARHYDF7XWWkSeihHL4TUck8VCojTHhyrT1oGCSJFrTGTHByuMVkNuu6ybXMqjXI/nvKWcSbkec26sRnduakaccAMWaxE7CmY2X+yfLgzgscOm39FCFlOcwO/+fsyJu3u5/vtG+O1f83EcZtXEWy2uuT7h7IMpjpyqcMOVrU8df/mBgG98ug+0sP9Jo5ORg8shDIzFBHDzrVN9oLp7TY+mkWFBYwrcXn7V+rv0wCRDJ8kycp00pFIbmsHbVnP2momT1joWkV8A/g3jTP6A1vqQiLy1sf/9wCuBnxORGKgBr9ZaW7edZU0ZLNaJEjVZ1UEQqqHpPBvGisFSnZTrcv/pMW490M1gKSDdQmmD8+M1gFlFW7uzqZarBlTKcPghlyRZOEw8TuDt7zCuvBufM8Lv/Ia/ah1q5+OO2xz+85Nw971Jy+L0r18L+can++i7qsTP/peY229afm6X1jBedLjx5oSOzunh4Z4HN9ys0Bry+dZCx9eKVAqS5eiigO9tnDi125y9pkZkw+z74oxt7296/D7gfWs5Bsv2phYmlIMYpRR9hTSVMOHIpdK0ckN+U7TdWDVEaShkPKphzP1nRtEaOtILT6q+6zBYDunNzfYjtbK+VK0YV9Txxx0yGU1+gTDxb94T8g8f8hk53sMtPzDM2341tebCBHDrTT7iJzx2eOE3qweaf/9WxLf/r3Ds3i7S3XX+4A8UPZ3LFyaAUlHYtVuxY9fcc+FSkpHXkuXmOmltkng3knaaszd5yphlu1ILEzK+s2gi68EzY9TjBK0h7VcIIkUh7c1aFyo3ou3OjtUmAx9yKSNQ9ShZVGCyvkuc6GnnbQWt4cwp4dRxF8fRdHToOaO8lIKvfDPkM//oM3qyDycV88wfG+KX3rw2Lry58D3oOVDh5KE8YRzSHB+iFHz8cwHf/abPpWN5dGRC0fuuKPNffzFZsTApZazFjXLVLQXP1S25gWciyFoGQ2w6rDhZNiWPXypx9Y7CZMuJuahHCUGs6MubCTxKFNm5kmgdYbQac+xSmdFKyI6OqZX+XMprqU265zr0LLFBoNZw+qRw6rhDb5+a1/r56jcDPvbBDOXzfbjZkKf+8DBvfJ1LT9fqClO5BGFomgmm05p8YXbrjR94Ucg//VUnn/1iiVf96NT7/9n/Drn/S/24uZDLbynx1GcmvODZPp15h9WIu6pWTPfapfaR2ghcj7nj3hZAJSBua1Gc2wUrTpZNR5woRqsh9ShZUJzKQYxqcofPZ9UY60tzfrxOb35pE36pCAOnHK65Xi0pMkwpOPG4w8AZU7R1PmG688MB//6JPrx8yHNeOcTrf9KnMIfrcCloDWNjQqEwVc1hdFTo7tZcvc+I5PmzJuG3e0aJopf9UJrPfSTgq19M86ofhcOPR3z2nzUPfrWP/U8a5Y9/38NzPVZ7aglDYefu9reaoFEQd4lDVQp8X2O1aQorTpZNRz1W1MKEapjQt8BxI5WQdIvFWJcqShPuuJPHXJTS9O0Qdu6ePpHHsUkUzRemvzYK4fHHTJh4/465WyxEMfzBn0Y89q1+eq8s8od/qJZlKSWJEaKe7qk+StUKFDo09ZpQLIJWpp379TepyVDmdFpz73c9Zkac+R7c9uwy3/tCHz/9mjph0XQ33HndOH/wDnfZNfAW+wyuCx3LqGy+EbheozD5EkgSU7PQWk5TWHGybDrqUUKioBRECx43XA7IrrAtxVxMWD1nB4TePkUUwtnT08UpSeCxRxxKY8KTn57g+yY3Z3xMOH3SIVqgI+y374v4yAc8Rk70cs3TR/i9t/mkWpz1VTJVATyKYHzcYfcexYVzU67Del24/saEbB4qZSGJobNLT8uxyeWho1NNS2yd4HU/6fLQd6tkO2NufmGZH3iOyw1Xr91UUikLu/aoJfeC2ig8b8lePZLEJO8utxjwVsSKk2XTUa7H5FMuxQXKDtWjpBH8sLKF+JkoBUcfc7h43rjjRExey/CwQ6WsyBeMKBx9zFR2ALh0Qejq1jx4n4tSJtQ5n5997ovDCX/w+8Lg472In/CcVw7xc29s3VqqVaFSkUaZJWNt3PTEhL5+TSarOXnMJZUy793RZY5ZqILCvgOaxw6b6EEw1qKISc79uw8lmCl49QMy4giKJdNlFi3g6Hkj9NoREVO6aKGeVzOJFSyheMe2wIqTZdNhatR5VKN4Vtmh8VrE0Utl485b5ZvQKILjRxwGL5nk2OabXM/VnDnp0N2rOXPKWEa9vZokgZPHHTzPuMpmFmwdKyre/4GYoYsuF45nias+d7x4mDf+lEtfd+uzVRQZi+j2pyYksRCG0NM3ZQ1ddoWmozPh2BGHy65SLeVddfeaCgsjDZFVCjIZTaGj5WEtSr1uLCNxmOwB5blw7fWKbM68v+expErn7UA+rxkdEdJpTRwJmZxesKJGEpsmj5YprDhZNhVaa0r1iELapxaZkkET0XTFesQDp0fJ+C5hpBZtnV6rmU6y/Ts0u/YsfGdeHIMjj7oEgUmOnZjcv3m3KaL2zCenGBsVhoeEbG7KMnJdM9mKzBamr34r4EPvKxAWO/E7QjIdEW/4jTLf95TWAx60Np1ptTJJqEY45v4sPb2a25+atJwT5ftw+1MSSiXj+nNceOQhZ97zt4pSxsqr14VsDm58ohHLiZI/nV1L7wfVblx/o2JsVCiOg5/SnD4xZYHORZyYNvGWKaw4WTYVYaKIm6ylibJD1TDm4OkxcimvpcaBoyPC4QfNLF2vCTt3J9OsiWoVTp9wcFzjZhoadCjkFT09Zv837wn58P9JURzoQ/yYmz9cobtr7ll/5kL+0Kjiz9+jOHFPP35HnZ992wgv/L4JQWpdmGpVqFQd9u5THLhckW6h1t1Sk3X91FRy64Sbqnlda6mEARSLDrv2KK7aoejq0RtdT25N8FOwY5dmx65Gq/qz5u9ovkrlidJk17l/U7uzBf8sLFuRepQwWgkRkUlv3UTZoVza5cGBcXzXWVSYtDbCdOigQ0enJpWC4WGhXIKOTjN5XjhvghZ8z4R4aw19febuvlLT/Om7Yx77di9uNuLaZ4zw+Ld7+eTnIt78+qlb3699O+STH/N5zgvCyXygWqD55F0h//aJTpKaz/XfN8Kv/6JLZ2HpoeFjY0ImDbc+Oaaza/HjVwPXNblGQ4PmWi2FsTFBJ4KX0jzx9mRDqoVvFI4De/cr4/ad53NrNL6/DmU+NhFWnCxtTT1KGK+GHLlYJlbGnTZhNfmew1A55NRIFa1Z0I2nNVw4Z0QnDISOTsVEa7CUr7l43qFS0Rw7YiaIufomPXI04s/+ME31UidXPWWUX/8VoafT501vqPLtr2b52dcpjp2O+au/FM4fNkHunzkdc8uNRe76gubg17pQYSe5nRXe/LYyz7i99YUUlZhcpInOs/07tcmtWue1mP6dmvPnlubaGxkW+nZorrg6IZ1efofYzUzfDs3JYwsUg1VC2t8+gt0KVpwsbcV4NaIWxZSDmMFSQBApECM8M5No055jeiVl/QUtpjCAY487DF40SaUdHWYSOH8p4fP/FvPaV6YYOG3KB3XP42b6+OcCPvd33YjAq35+iJe/ZMpKetrzqvznP/Xzi79SZPhkF4Lmic8f5kU/JPzZ2zt51693oWOXHdeN84IXR7zkB9L4LXaiKxaFOAIErrhasXe/acfg+bOrN6wHHY31oDBgznWhODbh8tKIR9HaTMzXPWHzhIKvBbkc9O5QjI+ayM2ZaDRpazlNw4qTpS2oRwnHB8tcKAa4IniOkE25C4aC+67D7s75F1q0hqFLwtHHnMk2ChN8/sshH7uzg6SaYnRsmF97q+D5Zn3gc18K+OKn01THffZfX2NwwKd8vp/87gq/+Tsh1105fVZ+9cs9vvHPEaNns1x9xxhveoPD1ZcZs+ylrx/j8x/p5rmvGuItr0/jOK2tekdRoyfRTs2BA4pMdkoMNnKSdxy49gbFQ/e79PUrwqAR9OGbahlRLFxzg6K/f6pGoE3dMVx3g+Lwgw5jY7MrbyitbV29Gchm61CRz+d1pVLZ6GFYVokoUZwfq3F8qILvOotG2LVKcQyOHzU9kbq6TZkepUx03T9+1Gf4WCeZ3hrpfEzxfI4/+N8l7r4v5t8+m6M2mMPLB3TtDhg5mSfVGXL7s6v8l5/x5wz31RrGignZrENmjn48ccKClROSxFSNyGSnLI90Bi6/UrFz99wVJDaaI484nBtw6OpShJEQBjRcd4pcbvHXb1ei0PTqGhsVunumyladOZ/wshf7XLt3jgS4VUJEqlrrtXuDVcaKk2VDSJTmzEiV0yNVlNZ0Z1NLKt0ykRA6k+I4nDruMDbqkM2ZiTJO4BN3BXzpMznqwzmcVMxTfnCcN/+Mx8B5xTt+pQsRjU5cUt01nvPDFV73ihSZtBAn4Mj86yTVKhTHHXp6WouWm0mtCtWaqXNXKhp32HU3mLYQ7bw2E0WNbrQd5rsIAta9KKvWmmI9ntY0crnUo4S0t3iV+9VAKZP7dn5AJnt2nT6X8JofT7O/b+0u4mYTJ+vWs6w7tTDh0LlxykG8ZFECI0BHDrtcc4OajH6q1eDEUYfhQYdsVtHXr1AKPv+VkE9/NEP1Uj+ZvirPf/UQr3yZR0+ncbvdcLXD014ywuH7Mjz/h+u84qVpfG/K9TafxaOU6S/kuHDdExJOHHNIz5HHMlfYtdbmtXEs5POK2+5IyBdgeFBIZ/SSI+E2At+fSowVWX9hAghiRSWIyaXcJbcqaSZRmuFKQHc2tWAh4dXCcWD/AcW5AVMxxOihdevNxFpOlnUlShT3nx4lTjQdS3DhKQXFcWFkUDg7YDLvk0S4+daEsVHh9AkHzzMTez3U/POXQr70uQylcwX8jjov+PEyr31FesXN3KIIyiUziezeo9l3mSKVhnu+Y0oDpVJGkKpVqAcOKOjuUbieaUkRx4LWpsL2vgOKXN6uySyX8VpExneohQndLVRqL9UjkoaVPtd5KkG85ALAK+HIIw5jI5DNwYXhiJ9+ZZ7+wtq9v7WcLJYZKKU5N14zFkM9ohYmLU0CUWRK2xTH4fyAQxiau/WuLo0WCGqa++928TxTVeChIxGfeLdw8sECKujE76jz/a8Y4k2vS5GdJ/2+XjcL+jNDslUCYWRK5zhixCYIzFrQVdcp+vqmVzG47ErFow+5eClwRNO3U/OEfTFBXTj0kIug2blbs2OnIpPVsyqVryda68lE5pkt5TcTsVLs6MhyYmjxm1WtNUGscITJNiqlekxnxiNKFFftyPP4xdJaD3kau/cqLp53SaXN39Jm/i7WAitOljVBa81IJcQRYWCsylApnHTfLSZMUQRDg8KpYw5xbNwghYJGO4rP/kvEv/9zjrjm8fNvK3PHE33+7WshX/ysz8iJXnAVe24o8v3PjXnpD6ZJebPfq16HMBCiyJy3XDIlh3zftJOIImOF5QuaWs2U7unfqdm5S9HRNfda0I6dmtSTEzIZTSY7tUbV0am55jpTMmj33o0PbhitmnJLGc+hEioSpSebMYaxItVii5G2QENfIc358TpRohZ07VXChP5CiozvcrEYECtT3upiqU5fIU1/Ic2RZYpTECek3KWvV3V0mlYl5ZLQ1atsL6cZWHGyrAmDpaBRtUFwHJnXXaG16XnkOGaB/dJFh4sXTDfWzg7N0dMxX/ma4tD9PqOnOyBxyPTWwNH8xTu7cDMxcbkDNxty2w8O89Ovcdmz0wWmL/QkiQk+COpCR6dmzz5FR5epyl0pw+GHXKLQRJzt2hNT6Jhyt80XfNGM606V+ZnJvgPt4TrXWqO05plX95PyHJTSfPfEMFFiRKoURDgi9OZSbd+6QWsNAlnfZW9XhhNDlQVveupRwo17OnFd4fRIlULa44n7uygHMa4jpDyHrO/OErkoUYzVQvrz6TmvSZQoxqoRGd9dcmCGCNxym6k8MlJROFadpmHFybLqxIni6GCZnlxq3jvxShkGLwoXLzjEYaM5mzYul3sfDvj2d4QTD2cJRk0J7HR3jeufPsYzn6V5/velOHcx4U//WNAIz3hVmVe81Cebnr6WoLV5nzAUPA96d2h27VJ0dk+3YDo64Y6nG+tmrjm5XeZprTWVICFIElxH6Mr4kxNmPTLbfNehHiVUwpiOtD/t+teihJ7c1DbHES7vzfPYpSIC3LKvm6FywIXxGlnfW5fggOUSJZp8ysV1hF1dGQbGatTChGzK3JTUI1NFNuO7lOsxnVmPzqyHiLC/J8ee7gye60xbq+rJpxguhdPEqViP6MqmGK9Fc65rjdcjrttV4NhgBaX1kl1zzYdbt9502vevz7JpCGNFlKhGE0BNKYgJY0VHUwJtFJqIukpZOD/gUK7AQ4+EfO9+bTqxdmkeO+xx6WgBFXaAo+i5rMwdz63w/Oc43HitD0yd77K9Lu/7i4lnU5OGSsz7hKGgtKkFt2dvQqFz4bI5rSa2aq1X3aqIEtPZt3ORO+/xWkRn1ufangLD5YCB0Ro9uRQClMMYNGQ8l1Aprt5R4OxYjWI5ojNjBKkWJVzRNz0JaUdnmscvOXRmPfoLKfoLKXZ3Zjg9UmWoHNCXn21F1aOkpeK6y2GwVKcjs3DFDzB/c30d5ntPey437+vi3pOj1OMEpTVpzyReVysxjiPcuqd38nNcv3vunh/dOZ9zYzUKjWkxjBVpz+HGPZ3ce2pkllVVCUwY+4HeHEGsODNaxRHBd5xFv8u5sIbTdKw4WZZFGCuGSgGnR6rU44SJqmHm/0vozqZMi/BRYeA0PHxYMV6Eo8cTjh0TzjyaIy4Xpr3KzYXsv6nEU56W8ILnePR0usxsZhdHUK4IKhEc15QiMjk3glJGZHr6Nb29Zn1osRDn0WqAIC1Fe8WJYrhi1s66srPLKS2HRGlGqyEp15k2+U1YP2BcV7mUR6w0V+8sUEh79BfS9ORSPHyuCMANuzrIplwOny/ypP1ddOdS7OvOMlQOOHKxRBg3agbO+Jy+63DtrgIdGW9y8u7Jp+jK+jx+qcTAaI18o9K76wilekTQEICJViULEcbmpiWf9malDJTqESJCPuUiIsbycEwx38XEKUgSujJT79+Z8bn98h7K9QgN7O7MECvN0UtlDvTkJi2qhcj67mRYuQCx0tyyr4tsyuXanQUeuVCaXJ8DqEYxT9hrRO9Ab44wVnRmfY4Plhd9r9ls7uCUtcCKk6UlTHmhCmGS4IgwUjEL6x1pf9L9EwZQLgtjI3D3cc1X/iPhwftcLp3IkdSn7iTFS+i/ssytTy3xoud7dHc6nLuYcOUBD8/1mPiznLCCgkCYUL9UGvYdUPT2aYYHhXMDprr4jl2Krm4TBdeqFaS0RmtjUTULQ7keEytFNuUykWmR8V3G6xHX7+7Ac4STwxWK9QjPEboaoclBnBAnmpTn4LsO1TCmFiU4QLohMInSkz2olNaMVAOu2VHAdYWjl8qTk18piLhlXzeeIzxwZgyloCfnU2hyte3szHBDohmphuzpziAiPOOqvsm1C8cRdnZm6Mz6HDwzRsGfu53I3u7ZCu44wrU7O+jM+IxWQy4WA2OVJYqb9nbx8NlxMr674IQaJYpiPWJvd4YLxToZz50UtJFKQHcuhe8K58fr9BfS1MKEQtqjHMzf4Xjie0uUJjNDHLuy/rR1H8+Fm/e1XrI9n/Imxch1hCjWdGbNe/Tk0wilScu5HMT0FdKT75fxXW7a1zVZhmvJyNJdglsdK06WScJY4btClGiGywGua1wUxVrE6ZEqjiOkXAelFZ2pFMMjmi99K+GB+2Mef8zlwlmX4pBLbSyNCs2flpOO2XVNmetviunugisvd7jtFuNmUkmaegBxKFy2W1AxjBWNBYSA70FXj+bq3Yp02lQJzzTNox2dptJ1KyRKUw5ifFcmJ8hSPWZPd5aOtMdjF0tkfZdKkNBXSNGZTTNcDvE9IY41F0t1unM++7qzOI6wpztLPUq4+6Rx95TqjUXxnM9IJWSsGpFPuzxxfzcAh86NQ2gK2nZmfQbLAQBX9OW5rC9HrDQnhirEiaIaJuzqyLCjwwjVNTsLHDo3znW7e2d9rr09Wfb2TF2UuRbVM77LrZd1EyVLC8yY+Jx7urMc6I04fK7I9f0d7OzMcKAWcXasNs2SaCaMTSDBLfu62NmZYU93lntPjpL1XUarIf2FNDfs6cR1BNcRhkohkVLc0N/BkYvlOddvokQRRIpanHDVjjydmdWdvibEfJImIzPlOfQV0pTrMfm0Rz2KuXHv7GzptOfgODKrQ/NiaG3dejOx4mShEsScHqlyoVjHFUFrPa2w/+io5sgROHIEThxTHDnsc+lEhqicbkQyGNxcSKEv4PInlti9T/HEm+Ept6ZQkUeSmD81DZTHTS8mx9V09WjyecXoiICGA1couro02fzyW3NPiMXEZxBMm43dXVnGKiHDlYDOjE+UKPZ0ZcilPM6O1fBd4cr+PDs6TGTWlf3m9VprRqsmUbN58s/4LtfsKPDg2TH6cmmedFk3vusQJ4rxWkRX1sdrWGNP3N/NA2dGuX53B/u6swyWAtKeETMA3xWu6s9zfKiCAFfumMqV3NewbHpacD3OR9pzWUl8Q0fG5ylX9E5+/iv681TCZLKyAky1MinWI7TWPHF/Fzs6zGTfmfHZ053h1HCV/kKK63d3TB6/pzvLubEagrFCu3M+tTAhTBRJohteX03ac+nrSLOrIzN53daT3V0ZHi6PEyaKnR2ZOaPzRITOjE8QGct7KSK11EopWx1bIWIbUqpHDJUD6lFCsRZzdjDi2AnTb+b4ceHsaYfBcz7FIZ/6eAoVTP8ndLMhfQdq7NqXsGev5ooDDlcdcOjudFGNY0QLWsyaz45dajI0WynjbkllNJlMa5FwUaLwHJl0p4RxMik8k+sxiWK8HiGYdZQr+vJ0NKKzvIbF5zhCnChODVcZLgdkUx637Ddun+UGOiilOTZYZn8L6xpBnJBeqAIsE+Hem2OiihPFkYslxmoRYazINtx8sVLcdlnPLBdiPUp47EKJ63d3TNuntebeU6PESvP0q/o4P1bj0LkiGd/hlv3dVBrWykS03UYRJYpvHR2ikPZ40oHuedccTw9XODVcxXcdxushuzuzC7rstNaM1UKefd3OtRo6sPkqRKypOInIi4D3YpJO/kZr/ccz9ktj/0uAKvAGrfV9C53TitPi1OoJJ85HnByIOXk+5OTZiItDmuFhzcgIjI86jA16FAdT1EbSJPXpd+TiJviFiFxXRGdPQv9Oxc5dmr27HS7f79LX4+A6xsWWyynyHZDJgNJGeLI5jeOaG17xk8m7xzBWhInCQVBopLGQNPEXmPZc8imXKNHUowTfdahFMa7jECuF1pruXIor+vJkUy6VIObMSJXRaoQIXL+rg558at0KeFqmKAcx954cIdGaJ1/eu+Scn6FSnWqYcFlfnlI94u6TI9y8t2u6m60NuDheoyuXWjBgY7gc8NDZccBYjPUoWbBUV6I0lTDmWdf0r/p4m2lFnNZizl4ua+bWExEX+EvghcAAcLeI3KW1Ptx02IuBaxs/TwP+uvF7S6CUJow0tUBTDzX1uqIaaOqBoh5APVCEoWnfHYSaeuN3FJn6cMWSZrykKZU0pbL5qVSEagVqVaFWFYKaENYdwrpLWHGJa35jvWf+fx7xErxsTLYjZvdVdXr6K+zao9m/V9i3V9izS/AzmpQP6RSIK/i+kMkpHC/B9TR+2lRKEGQyITLtOCitqWvNhAlVwCOX9giihP6ONN05nyg2wQcdGR8RExVVCxMulepcKgZkUy67utJUgoT+jhyX9Zo1mXqU0JWdyu3J+C59hTSVRiLlWoU3WxankPa49UAPlXB5VcL7O6ZEKJ/yuHFP5+SaWzuxq2vxCrcT7rxsyuWqHXnuPz3G3MHrBqU1XhtYyu02Z6/lmtNTgaNa6+MAIvJx4GVA8wd9GfBhbcy374hIt4js0VqfX+3B/NnfjvGO3/bR2qxtTBqM2lQjQDcaKDc9h3kea2kcy+Sai256bM4voBwmwqRXDUfh+AmOp3B8hesp3JTG8xW5PTGZbI1cXpPLQ75gQq07u6CnC3buhJ07hUIBPF/wUxrX1WRSDo6rcH1NPuvQkfXJ+i5xoqnHCb7jkPIcHAd8x0Siea5D2nfIpzzCWFEOYkqN6LWdnZnJfzavxXDrQtpjR0ea63ZNufCa8VzmFZ92ThbdTnTl/FVZC3Ia64OblYzn4rnCgZ4cXVmfXMqlFib47txzQZxovPboj9JWc/Za/lfvA840PR9gtsLOdcw+YNoHFZG3AG8BSKWWtyjc3+PQuyckDmVqnUMaETICiDa/nIn3nFoPmShpL44gGCuheb8JAzXnkYnzOuC6xr3leeC4xtLwPBPqPFFs1HHA9wTXM+3Bfc9sT6eEzoLQ1yf0dDr09Qg9XQ6ZjIBjLJpcxsF3HHM+z8N1THuGTMq43TQTvYjMuotgcklETDa6CHiOM7m+oZReVgmVbMolm3JX5U53NXKHLJaNxHGEK3qbA2vyHB8ss1CEfG9uXdyXnojc0/T8Tq31nU3PV23OXg3WUpzmmuVmLnC1cgyNC3gnmDWn5QzmjS/v5I0vX84rtw+2tpfFsjpc3j+1tLOzM9Mua2ex1vqOBfav2py9GqzlbeoAcKDp+X7g3DKOsVgsFsva01Zz9lqK093AtSJypYikgFcDd8045i7gp8XwdGB8LXyXFovFYlmUtpqz18ytp7WOReQXgH/DhI59QGt9SETe2tj/fuCLmJDEo5iwxDeu1XgsFovFMj/tNmfbJFyLxWLZBmy2JFwbGmWxWCyWtsOKk8VisVjaDitOFovFYmk7rDhZLBaLpe3YdAERIqKA2jJf7gELdzJrD+w4V4/NMEbYHOPcDGOEzTHOjRhjVmu9aQySTSdOK0FE7lkkQ7otsONcPTbDGGFzjHMzjBE2xzg3wxg3mk2johaLxWLZPlhxslgsFkvbsd3E6c7FD2kL7DhXj80wRtgc49wMY4TNMc7NMMYNZVutOVksFotlc7DdLCeLxWKxbAKsOFksFoul7dg24iQiLxKRx0TkqIj81kaPB0BEDojIf4jIIyJySER+ubH9HSJyVkQeaPy8pA3GelJEHmqM557Gtl4R+bKIPN743bPBY7y+6Zo9ICJFEfmVjb6eIvIBEbkkIg83bZv32onI2xp/p4+JyA9t8Dj/TEQeFZEHReQzItLd2H6FiNSarun7N3CM836/bXYt/7FpjCdF5IHG9g25lm2P1nrL/2DKvx8DrgJSwEHgxjYY1x7g9sbjDuAIcCPwDuA3Nnp8M8Z6Euifse1Pgd9qPP4t4E82epwzvvMLwOUbfT2BZwO3Aw8vdu0a3/9BIA1c2fi7dTdwnD8IeI3Hf9I0ziuaj9vgaznn99tu13LG/j8Hfm8jr2W7/2wXy+mpwFGt9XGtdQh8HHjZBo8JrfV5rfV9jccl4BFg38aOakm8DPhQ4/GHgB/buKHM4vnAMa31qY0eiNb668DIjM3zXbuXAR/XWgda6xOYvjlP3ahxaq2/pLWeqGTwHUzn0w1jnms5H211LScQEQFeBXxsPcayWdku4rQPONP0fIA2EwERuQK4DfhuY9MvNFwpH9hod1kDDXxJRO4Vkbc0tu3SjS6Yjd87N2x0s3k10//52+16znft2vlv9U3AvzQ9v1JE7heR/xSR79+oQTWY6/tt12v5/cBFrfXjTdva6Vq2BdtFnGSObW0TQy8iBeBTwK9orYvAXwNXA7cC5zEugI3mWVrr24EXAz8vIs/e6AHNh5gW0z8KfLKxqR2v53y05d+qiLwdUwvuo41N54HLtNa3Ab8G/IOIdG7Q8Ob7ftvyWgKvYfqNUztdy7Zhu4jTAHCg6fl+4NwGjWUaIuJjhOmjWutPA2itL2qtE621Av4P6+SKWAit9bnG70vAZzBjuigiewAavy9t3Ain8WLgPq31RWjP68n8167t/lZF5GeAlwKv041FkoarbLjx+F7Mes51GzG+Bb7fdryWHvBy4B8ntrXTtWwntos43Q1cKyJXNu6qXw3ctcFjmvA9/y3wiNb63U3b9zQd9uPAwzNfu56ISF5EOiYeYxbJH8Zcw59pHPYzwOc2ZoSzmHZn2m7Xs8F81+4u4NUikhaRK4Frge9twPgAE+UK/Cbwo1rratP2HSLiNh5fhRnn8Q0a43zfb1tdywYvAB7VWg9MbGina9lWbHRExnr9AC/BRMMdA96+0eNpjOn7MG6GB4EHGj8vAT4CPNTYfhewZ4PHeRUm6ukgcGji+gF9wFeBxxu/e9vgmuaAYaCraduGXk+MUJ4HIszd/M8udO2Atzf+Th8DXrzB4zyKWbeZ+Pt8f+PYVzT+Fg4C9wE/soFjnPf7badr2dj+QeCtM47dkGvZ7j+2fJHFYrFY2o7t4tazWCwWyybCipPFYrFY2g4rThaLxWJpO6w4WSwWi6XtsOJksVgslrbDipPFsgQaFbB/Y6PHYbFsdaw4WSwWi6XtsOJksSyCiLy90Q/oK8D1jW1vFpG7ReSgiHxKRHIi0iEiJxolqRCRzkbfHl9EfklEDjeKk358Qz+QxbIJsOJksSyAiDwZU+7qNkxNtKc0dn1aa/0UrfWTMK1OflabtidfA364ccyrgU9prSNMz6bbtNZPBN66jh/BYtmUWHGyWBbm+4HPaK2r2lSMn6jJeLOIfENEHgJeB9zU2P43wBsbj98I/F3j8YPAR0XkpzDVvS0WywJYcbJYFmeuGl8fBH5Ba30L8E4gA6C1/hZwhYg8B9N1daII6Q8Dfwk8Gbi3UZ3aYrHMgxUni2Vhvg78uIhkG5XZf6SxvQM431hfet2M13wYU/jz7wBExAEOaK3/A/h/gW6gsA5jt1g2Lbbwq8WyCI1Gez8NnMJUmD4MVDBCcwpTEbtDa/2GxvG7gROY6thjDQH7D6AL0wDv77XWf7zen8Ni2UxYcbJYVhkReSXwMq316zd6LBbLZsX6vS2WVURE/jemE+9LNnosFstmxlpOFovFYmk7bECExWKxWNoOK04Wi8ViaTusOFksFoul7bDiZLFYLJa2w4qTxWKxWNqO/x+JsP59KQSfWwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#try to display more than one confident interval\n",
    "ax = sns.lineplot(data=df,x='days',y='energy',ci=100)\n",
    "\n",
    "ax2 = plt.twinx()\n",
    "\n",
    "sns.lineplot(data=df, x='days',y='energy',ci=75,color=\"b\", ax=ax2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "voluntary-bowling",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[None]"
      ]
     },
     "execution_count": 9,
     "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": [
    "# No of players after some time, changed to log scale\n",
    "ax = sns.lineplot(data=stat1['id']['count'])\n",
    "ax.set(yscale=\"symlog\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "invisible-ending",
   "metadata": {},
   "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": [
    "#only max - level is kind of smooth\n",
    "ax = sns.lineplot(data=stat1['level']['max'])\n",
    "ax = sns.lineplot(data=stat1['level']['75%'])\n",
    "ax = sns.lineplot(data=stat1['level']['50%'])\n",
    "ax = sns.lineplot(data=stat1['level']['25%'])\n",
    "ax = sns.lineplot(data=stat1['level']['min'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "postal-convention",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(25.0, 180.0), (1000.0, 10000000.0)]"
      ]
     },
     "execution_count": 11,
     "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": [
    "# Energy / day plot in log scale, still not smooth - not usable for comparison\n",
    "ax = sns.lineplot(data=df,x='days',y='energy',ci=75)\n",
    "ax.set(yscale=\"symlog\")\n",
    "ax.set(xlim=(25, 180),ylim=(1000, 10000000))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "moral-broadway",
   "metadata": {},
   "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": [
    "ax = sns.lineplot(data=df,x='days',y='level',ci=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "sudden-football",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>days</th>\n",
       "      <th>level</th>\n",
       "      <th>energy</th>\n",
       "      <th>material</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>77.000000</td>\n",
       "      <td>77.000000</td>\n",
       "      <td>77.0</td>\n",
       "      <td>7.700000e+01</td>\n",
       "      <td>77.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1014.181818</td>\n",
       "      <td>93.727273</td>\n",
       "      <td>100.0</td>\n",
       "      <td>2.376213e+06</td>\n",
       "      <td>147661.801182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>870.882065</td>\n",
       "      <td>19.898186</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.494698e+05</td>\n",
       "      <td>75099.458320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>10.000000</td>\n",
       "      <td>56.000000</td>\n",
       "      <td>100.0</td>\n",
       "      <td>1.456358e+06</td>\n",
       "      <td>103852.422324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>115.000000</td>\n",
       "      <td>82.000000</td>\n",
       "      <td>100.0</td>\n",
       "      <td>1.921597e+06</td>\n",
       "      <td>106636.453927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>943.000000</td>\n",
       "      <td>89.000000</td>\n",
       "      <td>100.0</td>\n",
       "      <td>2.317386e+06</td>\n",
       "      <td>125377.876701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1725.000000</td>\n",
       "      <td>114.000000</td>\n",
       "      <td>100.0</td>\n",
       "      <td>2.809708e+06</td>\n",
       "      <td>145891.515267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2131.000000</td>\n",
       "      <td>125.000000</td>\n",
       "      <td>100.0</td>\n",
       "      <td>3.514512e+06</td>\n",
       "      <td>367537.210283</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                id        days  level        energy       material\n",
       "count    77.000000   77.000000   77.0  7.700000e+01      77.000000\n",
       "mean   1014.181818   93.727273  100.0  2.376213e+06  147661.801182\n",
       "std     870.882065   19.898186    0.0  5.494698e+05   75099.458320\n",
       "min      10.000000   56.000000  100.0  1.456358e+06  103852.422324\n",
       "25%     115.000000   82.000000  100.0  1.921597e+06  106636.453927\n",
       "50%     943.000000   89.000000  100.0  2.317386e+06  125377.876701\n",
       "75%    1725.000000  114.000000  100.0  2.809708e+06  145891.515267\n",
       "max    2131.000000  125.000000  100.0  3.514512e+06  367537.210283"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.level==100].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "accepting-failing",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "      <th>943</th>\n",
       "      <td>56</td>\n",
       "      <td>100.0</td>\n",
       "      <td>1.456358e+06</td>\n",
       "      <td>123780.233863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>473</th>\n",
       "      <td>72</td>\n",
       "      <td>100.0</td>\n",
       "      <td>2.446820e+06</td>\n",
       "      <td>329918.668293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1725</th>\n",
       "      <td>81</td>\n",
       "      <td>100.0</td>\n",
       "      <td>1.497741e+06</td>\n",
       "      <td>104686.290141</td>\n",
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       "    <tr>\n",
       "      <th>2131</th>\n",
       "      <td>83</td>\n",
       "      <td>100.0</td>\n",
       "      <td>1.715615e+06</td>\n",
       "      <td>122683.815539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>84</td>\n",
       "      <td>100.0</td>\n",
       "      <td>1.765505e+06</td>\n",
       "      <td>126718.891422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>104</td>\n",
       "      <td>100.0</td>\n",
       "      <td>2.277671e+06</td>\n",
       "      <td>103852.422324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2105</th>\n",
       "      <td>115</td>\n",
       "      <td>100.0</td>\n",
       "      <td>2.268873e+06</td>\n",
       "      <td>145891.515267</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      days  level        energy       material\n",
       "id                                            \n",
       "943     56  100.0  1.456358e+06  123780.233863\n",
       "473     72  100.0  2.446820e+06  329918.668293\n",
       "1725    81  100.0  1.497741e+06  104686.290141\n",
       "2131    83  100.0  1.715615e+06  122683.815539\n",
       "115     84  100.0  1.765505e+06  126718.891422\n",
       "10     104  100.0  2.277671e+06  103852.422324\n",
       "2105   115  100.0  2.268873e+06  145891.515267"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Finalists \n",
    "stat4=df[df.level == 100].groupby('id').min('days').sort_values('days')\n",
    "stat4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "stable-firmware",
   "metadata": {},
   "outputs": [
    {
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       "      <td>17.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>5.049752</td>\n",
       "      <td>38.0</td>\n",
       "      <td>42.00</td>\n",
       "      <td>46.0</td>\n",
       "      <td>50.00</td>\n",
       "      <td>54.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>93.588235</td>\n",
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       "      <td>4.744808e+05</td>\n",
       "      <td>6.174603e+05</td>\n",
       "      <td>17.0</td>\n",
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       "      <td>81439.354714</td>\n",
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       "      <th>10</th>\n",
       "      <td>64.0</td>\n",
       "      <td>90.5</td>\n",
       "      <td>18.618987</td>\n",
       "      <td>59.0</td>\n",
       "      <td>74.75</td>\n",
       "      <td>90.5</td>\n",
       "      <td>106.25</td>\n",
       "      <td>122.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>97.484375</td>\n",
       "      <td>...</td>\n",
       "      <td>2.426939e+06</td>\n",
       "      <td>3.477373e+06</td>\n",
       "      <td>64.0</td>\n",
       "      <td>84939.095278</td>\n",
       "      <td>23926.299562</td>\n",
       "      <td>36202.882652</td>\n",
       "      <td>65753.422889</td>\n",
       "      <td>93295.653785</td>\n",
       "      <td>104997.833429</td>\n",
       "      <td>111413.771380</td>\n",
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       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>37.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>10.824355</td>\n",
       "      <td>54.0</td>\n",
       "      <td>63.00</td>\n",
       "      <td>72.0</td>\n",
       "      <td>81.00</td>\n",
       "      <td>90.0</td>\n",
       "      <td>37.0</td>\n",
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       "      <td>2.317253e+06</td>\n",
       "      <td>37.0</td>\n",
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       "      <td>24455.344732</td>\n",
       "      <td>54625.715185</td>\n",
       "      <td>75109.995330</td>\n",
       "      <td>96448.891679</td>\n",
       "      <td>119666.108458</td>\n",
       "      <td>128067.559709</td>\n",
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       "    <tr>\n",
       "      <th>221</th>\n",
       "      <td>22.0</td>\n",
       "      <td>91.5</td>\n",
       "      <td>6.493587</td>\n",
       "      <td>81.0</td>\n",
       "      <td>86.25</td>\n",
       "      <td>91.5</td>\n",
       "      <td>96.75</td>\n",
       "      <td>102.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>93.181818</td>\n",
       "      <td>...</td>\n",
       "      <td>6.857206e+05</td>\n",
       "      <td>8.180813e+05</td>\n",
       "      <td>22.0</td>\n",
       "      <td>63516.158137</td>\n",
       "      <td>7774.669251</td>\n",
       "      <td>52294.913356</td>\n",
       "      <td>56665.299247</td>\n",
       "      <td>63280.699673</td>\n",
       "      <td>70198.480211</td>\n",
       "      <td>75623.865126</td>\n",
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       "    <tr>\n",
       "      <th>225</th>\n",
       "      <td>41.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>11.979149</td>\n",
       "      <td>43.0</td>\n",
       "      <td>53.00</td>\n",
       "      <td>63.0</td>\n",
       "      <td>73.00</td>\n",
       "      <td>83.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>94.487805</td>\n",
       "      <td>...</td>\n",
       "      <td>9.569739e+05</td>\n",
       "      <td>1.238753e+06</td>\n",
       "      <td>41.0</td>\n",
       "      <td>67469.871745</td>\n",
       "      <td>16509.358223</td>\n",
       "      <td>38342.183561</td>\n",
       "      <td>53431.467675</td>\n",
       "      <td>68645.056172</td>\n",
       "      <td>82966.349456</td>\n",
       "      <td>90232.547409</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     days                                                    level             \\\n",
       "    count  mean        std   min    25%   50%     75%    max count       mean   \n",
       "id                                                                              \n",
       "0    17.0  46.0   5.049752  38.0  42.00  46.0   50.00   54.0  17.0  93.588235   \n",
       "10   64.0  90.5  18.618987  59.0  74.75  90.5  106.25  122.0  64.0  97.484375   \n",
       "115  37.0  72.0  10.824355  54.0  63.00  72.0   81.00   90.0  37.0  96.918919   \n",
       "221  22.0  91.5   6.493587  81.0  86.25  91.5   96.75  102.0  22.0  93.181818   \n",
       "225  41.0  63.0  11.979149  43.0  53.00  63.0   73.00   83.0  41.0  94.487805   \n",
       "\n",
       "     ...        energy               material                              \\\n",
       "     ...           75%           max    count          mean           std   \n",
       "id   ...                                                                    \n",
       "0    ...  4.744808e+05  6.174603e+05     17.0  69904.326867  15363.117516   \n",
       "10   ...  2.426939e+06  3.477373e+06     64.0  84939.095278  23926.299562   \n",
       "115  ...  1.507375e+06  2.317253e+06     37.0  96194.561494  24455.344732   \n",
       "221  ...  6.857206e+05  8.180813e+05     22.0  63516.158137   7774.669251   \n",
       "225  ...  9.569739e+05  1.238753e+06     41.0  67469.871745  16509.358223   \n",
       "\n",
       "                                                                             \n",
       "              min           25%           50%            75%            max  \n",
       "id                                                                           \n",
       "0    45826.078341  57401.444913  70655.856134   81439.354714   95168.961195  \n",
       "10   36202.882652  65753.422889  93295.653785  104997.833429  111413.771380  \n",
       "115  54625.715185  75109.995330  96448.891679  119666.108458  128067.559709  \n",
       "221  52294.913356  56665.299247  63280.699673   70198.480211   75623.865126  \n",
       "225  38342.183561  53431.467675  68645.056172   82966.349456   90232.547409  \n",
       "\n",
       "[5 rows x 32 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stat2=df[df.level>90].groupby(['id']).describe()\n",
    "stat2.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "exterior-jacksonville",
   "metadata": {},
   "source": [
    "### looking on the subset of players who reached Lv 90"
   ]
  },
  {
   "cell_type": "raw",
   "id": "going-typing",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "portable-dragon",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([   0,   10,  115,  221,  225,  254,  420,  473,  547,  549,  661,\n",
       "        700,  799,  814,  943, 1102, 1122, 1513, 1631, 1641, 1725, 1842,\n",
       "       2105, 2131], dtype=int64)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "id_selected=df[df.level>90]['id'].unique()\n",
    "id_selected"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "overall-roads",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>days</th>\n",
       "      <th>level</th>\n",
       "      <th>energy</th>\n",
       "      <th>material</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>15.0</td>\n",
       "      <td>19.315345</td>\n",
       "      <td>6.575597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>16.0</td>\n",
       "      <td>164.275327</td>\n",
       "      <td>46.729636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>23.0</td>\n",
       "      <td>448.717153</td>\n",
       "      <td>153.574486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>25.0</td>\n",
       "      <td>685.119133</td>\n",
       "      <td>240.709294</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id  days  level      energy    material\n",
       "0   0     0    0.0    0.000000    0.000000\n",
       "1   0     1   15.0   19.315345    6.575597\n",
       "2   0     2   16.0  164.275327   46.729636\n",
       "3   0     3   23.0  448.717153  153.574486\n",
       "4   0     4   25.0  685.119133  240.709294"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# new dataframe with a selection of id's\n",
    "df_players_lv90=df[df.id.isin(id_selected)]\n",
    "df_players_lv90.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "corrected-fetish",
   "metadata": {},
   "outputs": [],
   "source": [
    "stat3 = df_players_lv90.groupby(['days']).describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "atomic-breakdown",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th colspan=\"8\" halign=\"left\">id</th>\n",
       "      <th colspan=\"2\" halign=\"left\">level</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"2\" halign=\"left\">energy</th>\n",
       "      <th colspan=\"8\" halign=\"left\">material</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
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       "      <td>24.0</td>\n",
       "      <td>897.625</td>\n",
       "      <td>672.889668</td>\n",
       "      <td>0.0</td>\n",
       "      <td>378.5</td>\n",
       "      <td>749.5</td>\n",
       "      <td>1542.5</td>\n",
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       "    <tr>\n",
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       "      <td>24.0</td>\n",
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       "      <td>672.889668</td>\n",
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       "      <td>378.5</td>\n",
       "      <td>749.5</td>\n",
       "      <td>1542.5</td>\n",
       "      <td>2131.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>12.166667</td>\n",
       "      <td>...</td>\n",
       "      <td>152.299621</td>\n",
       "      <td>1348.148867</td>\n",
       "      <td>24.0</td>\n",
       "      <td>35.135973</td>\n",
       "      <td>112.665624</td>\n",
       "      <td>0.004882</td>\n",
       "      <td>0.822029</td>\n",
       "      <td>3.200235</td>\n",
       "      <td>19.057002</td>\n",
       "      <td>555.946310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>24.0</td>\n",
       "      <td>897.625</td>\n",
       "      <td>672.889668</td>\n",
       "      <td>0.0</td>\n",
       "      <td>378.5</td>\n",
       "      <td>749.5</td>\n",
       "      <td>1542.5</td>\n",
       "      <td>2131.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>15.583333</td>\n",
       "      <td>...</td>\n",
       "      <td>272.788551</td>\n",
       "      <td>2637.723075</td>\n",
       "      <td>24.0</td>\n",
       "      <td>106.889006</td>\n",
       "      <td>265.136632</td>\n",
       "      <td>0.483743</td>\n",
       "      <td>4.967754</td>\n",
       "      <td>18.349061</td>\n",
       "      <td>54.023567</td>\n",
       "      <td>1249.245544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>24.0</td>\n",
       "      <td>897.625</td>\n",
       "      <td>672.889668</td>\n",
       "      <td>0.0</td>\n",
       "      <td>378.5</td>\n",
       "      <td>749.5</td>\n",
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       "      <td>2131.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>18.666667</td>\n",
       "      <td>...</td>\n",
       "      <td>441.090189</td>\n",
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       "      <td>24.0</td>\n",
       "      <td>187.419029</td>\n",
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       "      <td>9.032518</td>\n",
       "      <td>46.691242</td>\n",
       "      <td>172.695362</td>\n",
       "      <td>1930.565915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24.0</td>\n",
       "      <td>897.625</td>\n",
       "      <td>672.889668</td>\n",
       "      <td>0.0</td>\n",
       "      <td>378.5</td>\n",
       "      <td>749.5</td>\n",
       "      <td>1542.5</td>\n",
       "      <td>2131.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>21.333333</td>\n",
       "      <td>...</td>\n",
       "      <td>686.025646</td>\n",
       "      <td>6305.039513</td>\n",
       "      <td>24.0</td>\n",
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       "      <td>0.982989</td>\n",
       "      <td>22.075278</td>\n",
       "      <td>70.449008</td>\n",
       "      <td>317.691997</td>\n",
       "      <td>3280.442760</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        id                                                         level  \\\n",
       "     count     mean         std  min    25%    50%     75%     max count   \n",
       "days                                                                       \n",
       "0     24.0  897.625  672.889668  0.0  378.5  749.5  1542.5  2131.0  24.0   \n",
       "1     24.0  897.625  672.889668  0.0  378.5  749.5  1542.5  2131.0  24.0   \n",
       "2     24.0  897.625  672.889668  0.0  378.5  749.5  1542.5  2131.0  24.0   \n",
       "3     24.0  897.625  672.889668  0.0  378.5  749.5  1542.5  2131.0  24.0   \n",
       "4     24.0  897.625  672.889668  0.0  378.5  749.5  1542.5  2131.0  24.0   \n",
       "\n",
       "                 ...      energy              material              \\\n",
       "           mean  ...         75%          max    count        mean   \n",
       "days             ...                                                 \n",
       "0      0.000000  ...    0.000000     0.000000     24.0    0.000000   \n",
       "1     12.166667  ...  152.299621  1348.148867     24.0   35.135973   \n",
       "2     15.583333  ...  272.788551  2637.723075     24.0  106.889006   \n",
       "3     18.666667  ...  441.090189  4120.757000     24.0  187.419029   \n",
       "4     21.333333  ...  686.025646  6305.039513     24.0  331.688300   \n",
       "\n",
       "                                                                           \n",
       "             std       min        25%        50%         75%          max  \n",
       "days                                                                       \n",
       "0       0.000000  0.000000   0.000000   0.000000    0.000000     0.000000  \n",
       "1     112.665624  0.004882   0.822029   3.200235   19.057002   555.946310  \n",
       "2     265.136632  0.483743   4.967754  18.349061   54.023567  1249.245544  \n",
       "3     409.727725  0.933800   9.032518  46.691242  172.695362  1930.565915  \n",
       "4     710.094765  0.982989  22.075278  70.449008  317.691997  3280.442760  \n",
       "\n",
       "[5 rows x 32 columns]"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stat3.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "complete-choir",
   "metadata": {},
   "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": [
    "ax = sns.lineplot(data=df_players_lv90,x='days', y='energy', hue='id',palette='hls')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "minimal-austria",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[None]"
      ]
     },
     "execution_count": 19,
     "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": [
    "#plot changed to log\n",
    "ax = sns.lineplot(data=df_players_lv90,x='level', y='energy', hue='id',palette='hls')\n",
    "ax.set(yscale=\"symlog\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "moderate-cigarette",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[None]"
      ]
     },
     "execution_count": 20,
     "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": [
    "#same mess, different color\n",
    "ax = sns.scatterplot(data=df,x='level', y='energy')\n",
    "ax.set(yscale=\"symlog\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "smart-unknown",
   "metadata": {},
   "source": [
    "### maybe fitting a curve?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "ahead-wonder",
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.optimize import curve_fit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "tough-breast",
   "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>level</th>\n",
       "      <th>energy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>15.0</td>\n",
       "      <td>19.315345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>16.0</td>\n",
       "      <td>164.275327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23.0</td>\n",
       "      <td>448.717153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>25.0</td>\n",
       "      <td>685.119133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18598</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18599</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.976839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18600</th>\n",
       "      <td>2.0</td>\n",
       "      <td>1.953678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18601</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.827326</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18602</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7.028074</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>18603 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       level      energy\n",
       "0        0.0    0.000000\n",
       "1       15.0   19.315345\n",
       "2       16.0  164.275327\n",
       "3       23.0  448.717153\n",
       "4       25.0  685.119133\n",
       "...      ...         ...\n",
       "18598    0.0    0.000000\n",
       "18599    1.0    0.976839\n",
       "18600    2.0    1.953678\n",
       "18601    NaN    3.827326\n",
       "18602    NaN    7.028074\n",
       "\n",
       "[18603 rows x 2 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "level=df['level'].dropna\n",
    "energy=df['energy'].dropna\n",
    "new = df[['level', 'energy']].copy()\n",
    "new\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "clean-wisconsin",
   "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>level</th>\n",
       "      <th>energy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>15.0</td>\n",
       "      <td>19.315345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>16.0</td>\n",
       "      <td>164.275327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23.0</td>\n",
       "      <td>448.717153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>25.0</td>\n",
       "      <td>685.119133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18591</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18597</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18598</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18599</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.976839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18600</th>\n",
       "      <td>2.0</td>\n",
       "      <td>1.953678</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>11686 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       level      energy\n",
       "0        0.0    0.000000\n",
       "1       15.0   19.315345\n",
       "2       16.0  164.275327\n",
       "3       23.0  448.717153\n",
       "4       25.0  685.119133\n",
       "...      ...         ...\n",
       "18591    0.0    0.000000\n",
       "18597    0.0    0.000000\n",
       "18598    0.0    0.000000\n",
       "18599    1.0    0.976839\n",
       "18600    2.0    1.953678\n",
       "\n",
       "[11686 rows x 2 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#NAN must be removed\n",
    "new_df = new.dropna()\n",
    "new_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "medical-plaza",
   "metadata": {},
   "outputs": [],
   "source": [
    "def func(x, a, b, c):\n",
    "    return a * np.exp(-b * x) + c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "threatened-empty",
   "metadata": {},
   "outputs": [],
   "source": [
    "popt, pcov = curve_fit(func, new_df['level'], new_df['energy'],p0=[1,0,1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "further-password",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(new_df['level'], new_df['energy'], 'ro', label=\"original data\")\n",
    "t = np.linspace(1, 100, 100)\n",
    "plt.plot(t, func(t, *popt), label=\"Fitted Curve\")\n",
    "plt.legend(loc='upper left')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "congressional-fashion",
   "metadata": {},
   "source": [
    "no further ideas at the moment ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dated-potter",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": 5
}