COMP 4447 final Project Presentation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pycoingecko as pycoin\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import Coin_Table_Code as ctc\n",
    "from rich.console import Console\n",
    "from rich.table import Table\n",
    "import matplotlib.pyplot as plt\n",
    "import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_token_list(cg):\n",
    "    cg.get_coins_list()\n",
    "    print((cg.get_coins_list()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def testing_coin_connection(cg):\n",
    "    test_con_value = cg.ping()\n",
    "    if test_con_value == {'gecko_says': '(V3) To the Moon!'}:\n",
    "        return 'Connection is good'\n",
    "    else:\n",
    "        return ['Connection not good',test_con_value]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def main():\n",
    "    cg = pycoin.CoinGeckoAPI()\n",
    "    print(ctc.testing_coin_connection(cg))\n",
    "    ctc.make_top_5_table(cg,['bitcoin', 'tether', 'ethereum','solana','binance coin'])\n",
    "    ctc.top_7_table(cg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_token_list(cg):\n",
    "    return_data = cg.get_coins_list()\n",
    "    return_data = pd.DataFrame(return_data)\n",
    "    return return_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "def pull_in_top_5_data(cg,cryp_list):\n",
    "    data_pull = cg.get_price(ids =cryp_list,vs_currencies = 'usd')\n",
    "    data_pull_DF =pd.DataFrame.from_dict(data_pull,orient='index')\n",
    "    data_pull_DF.index.name = 'coin_name'\n",
    "    data_pull_DF.reset_index(inplace=True)\n",
    "    data_pull_DF = data_pull_DF.sort_values(by=['usd'],ascending=False)\n",
    "    return data_pull_DF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_top_5_table(cg,cryp_list):\n",
    "    data_pull_DF = pull_in_top_5_data(cg,cryp_list)\n",
    "    \n",
    "    table = Table(title=\"Top 5 Coins\")\n",
    "    table.add_column(\"Coin\",justify=\"right\",style=\"cyan\")\n",
    "    table.add_column(\"Price\",justify=\"right\",style=\"green\")\n",
    "    \n",
    "    table.add_row(str(data_pull_DF.iloc[0][\"coin_name\"]),str(data_pull_DF.iloc[0][\"usd\"]))\n",
    "    table.add_row(str(data_pull_DF.iloc[1][\"coin_name\"]),str(data_pull_DF.iloc[1][\"usd\"]))\n",
    "    table.add_row(str(data_pull_DF.iloc[2][\"coin_name\"]),str(data_pull_DF.iloc[2][\"usd\"]))\n",
    "    table.add_row(str(data_pull_DF.iloc[3][\"coin_name\"]),str(data_pull_DF.iloc[3][\"usd\"]))\n",
    "    table.add_row(str(data_pull_DF.iloc[4][\"coin_name\"]),str(data_pull_DF.iloc[4][\"usd\"]))\n",
    "    console = Console()\n",
    "    console.print(table)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "def top_7_table(cg):\n",
    "    raw_data = cg.get_search_trending()\n",
    "    bt_price = cg.get_price('bitcoin',vs_currencies = 'usd')\n",
    "    bt_price = ((pd.json_normalize(bt_price)))\n",
    "    #top_7_data_DF =pd.DataFrame.from_dict(raw_data['coins'],orient='index')\n",
    "    top_7_data_DF = (pd.json_normalize(raw_data,record_path = ['coins']))\n",
    "    top_7_data_DF['US_Value'] = top_7_data_DF['item.price_btc']/int(bt_price['bitcoin.usd'])\n",
    "\n",
    "    table = Table(title=\"Top 7 Searched Coins on CoinGecko\")\n",
    "    table.add_column(\"Rank\",justify=\"center\",style=\"white\")\n",
    "    table.add_column(\"Coin Name\",justify=\"center\",style=\"cyan\")\n",
    "    table.add_column(\"Coin ID\",justify=\"center\",style=\"white\")\n",
    "    table.add_column(\"Coin Symbol\",justify=\"center\",style=\"white\")\n",
    "    table.add_column(\"Market Cap\",justify=\"center\",style=\"white\")\n",
    "    table.add_column(\"Price BTC\",justify=\"center\",style=\"green\")\n",
    "    table.add_column(\"Price USD\",justify=\"center\",style=\"green\")\n",
    "\n",
    "    for i in top_7_data_DF.index:\n",
    "        table.add_row(str(top_7_data_DF.iloc[i][\"item.score\"]+1),\n",
    "                    str(top_7_data_DF.iloc[i][\"item.name\"]),\n",
    "                    str(top_7_data_DF.iloc[i][\"item.id\"]),\n",
    "                    str(top_7_data_DF.iloc[i][\"item.symbol\"]),\n",
    "                    str(top_7_data_DF.iloc[i][\"item.market_cap_rank\"]),\n",
    "                    str(top_7_data_DF.iloc[i][\"item.price_btc\"]),\n",
    "                    \"$\" + str(top_7_data_DF.iloc[i][\"US_Value\"].round(2)))\n",
    "\n",
    "    console = Console()\n",
    "    console.print(table)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "def Chart_Analysis(api_key,days_back,Coin,info):\n",
    "    if info == [] or type(info) != list:\n",
    "        raise ValueError('Check if info list is populated.')\n",
    "    info_set = ['Price','Total Volumes','Market Cap']\n",
    "    if not(set(info).issubset(info_set)):\n",
    "        raise ValueError('Check all items in info variable.')\n",
    "    \n",
    "    raw_data = api_key.get_coin_market_chart_by_id(id = Coin,vs_currency= 'usd',days = days_back)\n",
    "    \n",
    "    fig, axs = plt.subplots(1,len(info),squeeze=False)\n",
    "    for plot in range(len(info)):\n",
    "        if info[plot] == 'Price':\n",
    "            price_data = pd.json_normalize(raw_data,record_path = 'prices')\n",
    "            price_data['clean_time'] = pd.to_datetime(price_data[0],unit = 'ms')\n",
    "            price_data['clean_time'] = pd.to_datetime(price_data['clean_time'],format = '%Y-%m-%d')\n",
    "            price_data['price'] = price_data[1]\n",
    "            axs[0,plot].plot(price_data['clean_time'],price_data['price'])\n",
    "            axs[0,plot].set_title(f'{Coin.capitalize()} Price Vs Time')\n",
    "            axs[0,plot].tick_params(labelrotation=45)\n",
    "            axs[0,plot].yaxis.set_major_formatter('${x:,.0f}')\n",
    "        elif info[plot] == 'Market Cap':\n",
    "            MC_data = pd.json_normalize(raw_data,record_path = 'market_caps')\n",
    "            MC_data['clean_time'] = (pd.to_datetime(MC_data[0],unit = 'ms'))\n",
    "            MC_data['Market_Cap'] = MC_data[1]\n",
    "            axs[0,plot].plot(MC_data['clean_time'],MC_data['Market_Cap'])\n",
    "            axs[0,plot].set_title(f'{Coin.capitalize()} Market Cap Vs Time')\n",
    "            axs[0,plot].tick_params(labelrotation=45)\n",
    "        elif info[plot] == 'Total Volumes':\n",
    "            TV_data = pd.json_normalize(raw_data,record_path = 'total_volumes')\n",
    "            TV_data['clean_time'] = (pd.to_datetime(TV_data[0],unit = 'ms'))\n",
    "            TV_data['total_volumes'] = TV_data[1]\n",
    "            axs[0,plot].plot(TV_data['clean_time'],TV_data['total_volumes'])\n",
    "            axs[0,plot].set_title(f'{Coin.capitalize()} Total Volumes VS Time')\n",
    "            axs[0,plot].tick_params(labelrotation=45)\n",
    "    plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "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>coin_name</th>\n",
       "      <th>usd</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>bitcoin</td>\n",
       "      <td>39192.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ethereum</td>\n",
       "      <td>2590.670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>binancecoin</td>\n",
       "      <td>375.660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>solana</td>\n",
       "      <td>82.620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>tether</td>\n",
       "      <td>1.001</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     coin_name        usd\n",
       "1      bitcoin  39192.000\n",
       "2     ethereum   2590.670\n",
       "0  binancecoin    375.660\n",
       "3       solana     82.620\n",
       "4       tether      1.001"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cg = pycoin.CoinGeckoAPI()\n",
    "pull_in_top_5_data(cg,['bitcoin', 'tether', 'ethereum','solana','binance coin'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">       Top 5 Coins       </span>\n",
       "┏━━━━━━━━━━━━━┳━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\">        Coin </span>┃<span style=\"font-weight: bold\">   Price </span>┃\n",
       "┡━━━━━━━━━━━━━╇━━━━━━━━━┩\n",
       "│<span style=\"color: #008080; text-decoration-color: #008080\">     bitcoin </span>│<span style=\"color: #008000; text-decoration-color: #008000\"> 39192.0 </span>│\n",
       "│<span style=\"color: #008080; text-decoration-color: #008080\">    ethereum </span>│<span style=\"color: #008000; text-decoration-color: #008000\"> 2590.67 </span>│\n",
       "│<span style=\"color: #008080; text-decoration-color: #008080\"> binancecoin </span>│<span style=\"color: #008000; text-decoration-color: #008000\">  375.66 </span>│\n",
       "│<span style=\"color: #008080; text-decoration-color: #008080\">      solana </span>│<span style=\"color: #008000; text-decoration-color: #008000\">   82.62 </span>│\n",
       "│<span style=\"color: #008080; text-decoration-color: #008080\">      tether </span>│<span style=\"color: #008000; text-decoration-color: #008000\">   1.001 </span>│\n",
       "└─────────────┴─────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[3m       Top 5 Coins       \u001b[0m\n",
       "┏━━━━━━━━━━━━━┳━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1m       Coin\u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m  Price\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━╇━━━━━━━━━┩\n",
       "│\u001b[36m \u001b[0m\u001b[36m    bitcoin\u001b[0m\u001b[36m \u001b[0m│\u001b[32m \u001b[0m\u001b[32m39192.0\u001b[0m\u001b[32m \u001b[0m│\n",
       "│\u001b[36m \u001b[0m\u001b[36m   ethereum\u001b[0m\u001b[36m \u001b[0m│\u001b[32m \u001b[0m\u001b[32m2590.67\u001b[0m\u001b[32m \u001b[0m│\n",
       "│\u001b[36m \u001b[0m\u001b[36mbinancecoin\u001b[0m\u001b[36m \u001b[0m│\u001b[32m \u001b[0m\u001b[32m 375.66\u001b[0m\u001b[32m \u001b[0m│\n",
       "│\u001b[36m \u001b[0m\u001b[36m     solana\u001b[0m\u001b[36m \u001b[0m│\u001b[32m \u001b[0m\u001b[32m  82.62\u001b[0m\u001b[32m \u001b[0m│\n",
       "│\u001b[36m \u001b[0m\u001b[36m     tether\u001b[0m\u001b[36m \u001b[0m│\u001b[32m \u001b[0m\u001b[32m  1.001\u001b[0m\u001b[32m \u001b[0m│\n",
       "└─────────────┴─────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "make_top_5_table(cg,['bitcoin', 'tether', 'ethereum','solana','binance coin'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                              Top 7 Searched Coins on CoinGecko                              </span>\n",
       "┏━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Rank </span>┃<span style=\"font-weight: bold\">  Coin Name  </span>┃<span style=\"font-weight: bold\">   Coin ID    </span>┃<span style=\"font-weight: bold\"> Coin Symbol </span>┃<span style=\"font-weight: bold\"> Market Cap </span>┃<span style=\"font-weight: bold\">   Price BTC    </span>┃<span style=\"font-weight: bold\"> Price USD </span>┃\n",
       "┡━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━┩\n",
       "│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">  1   </span>│<span style=\"color: #008080; text-decoration-color: #008080\"> Metis Token </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\"> metis-token  </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">    METIS    </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">    150     </span>│<span style=\"color: #008000; text-decoration-color: #008000\"> 0.00397235223… </span>│<span style=\"color: #008000; text-decoration-color: #008000\">   $0.0    </span>│\n",
       "│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">  2   </span>│<span style=\"color: #008080; text-decoration-color: #008080\">   Fantom    </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">    fantom    </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">     FTM     </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">     44     </span>│<span style=\"color: #008000; text-decoration-color: #008000\"> 3.06100854783… </span>│<span style=\"color: #008000; text-decoration-color: #008000\">   $0.0    </span>│\n",
       "│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">  3   </span>│<span style=\"color: #008080; text-decoration-color: #008080\">    JUNO     </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\"> juno-network </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">    JUNO     </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">     68     </span>│<span style=\"color: #008000; text-decoration-color: #008000\"> 0.00089471351… </span>│<span style=\"color: #008000; text-decoration-color: #008000\">   $0.0    </span>│\n",
       "│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">  4   </span>│<span style=\"color: #008080; text-decoration-color: #008080\">    Gala     </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">     gala     </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">    GALA     </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">     63     </span>│<span style=\"color: #008000; text-decoration-color: #008000\"> 6.03110548849… </span>│<span style=\"color: #008000; text-decoration-color: #008000\">   $0.0    </span>│\n",
       "│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">  5   </span>│<span style=\"color: #008080; text-decoration-color: #008080\">    STEPN    </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">    stepn     </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">     GMT     </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">    275     </span>│<span style=\"color: #008000; text-decoration-color: #008000\"> 7.63004102076… </span>│<span style=\"color: #008000; text-decoration-color: #008000\">   $0.0    </span>│\n",
       "│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">  6   </span>│<span style=\"color: #008080; text-decoration-color: #008080\">    Terra    </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">  terra-luna  </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">    LUNA     </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">     7      </span>│<span style=\"color: #008000; text-decoration-color: #008000\"> 0.00224116522… </span>│<span style=\"color: #008000; text-decoration-color: #008000\">   $0.0    </span>│\n",
       "│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">  7   </span>│<span style=\"color: #008080; text-decoration-color: #008080\">     BNB     </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\"> binancecoin  </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">     BNB     </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">     4      </span>│<span style=\"color: #008000; text-decoration-color: #008000\"> 0.00958929067… </span>│<span style=\"color: #008000; text-decoration-color: #008000\">   $0.0    </span>│\n",
       "└──────┴─────────────┴──────────────┴─────────────┴────────────┴────────────────┴───────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[3m                              Top 7 Searched Coins on CoinGecko                              \u001b[0m\n",
       "┏━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mRank\u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m Coin Name \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m  Coin ID   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mCoin Symbol\u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mMarket Cap\u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m  Price BTC   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mPrice USD\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━┩\n",
       "│\u001b[37m \u001b[0m\u001b[37m 1  \u001b[0m\u001b[37m \u001b[0m│\u001b[36m \u001b[0m\u001b[36mMetis Token\u001b[0m\u001b[36m \u001b[0m│\u001b[37m \u001b[0m\u001b[37mmetis-token \u001b[0m\u001b[37m \u001b[0m│\u001b[37m \u001b[0m\u001b[37m   METIS   \u001b[0m\u001b[37m \u001b[0m│\u001b[37m \u001b[0m\u001b[37m   150    \u001b[0m\u001b[37m \u001b[0m│\u001b[32m \u001b[0m\u001b[32m0.00397235223…\u001b[0m\u001b[32m \u001b[0m│\u001b[32m \u001b[0m\u001b[32m  $0.0   \u001b[0m\u001b[32m \u001b[0m│\n",
       "│\u001b[37m \u001b[0m\u001b[37m 2  \u001b[0m\u001b[37m \u001b[0m│\u001b[36m \u001b[0m\u001b[36m  Fantom   \u001b[0m\u001b[36m \u001b[0m│\u001b[37m \u001b[0m\u001b[37m   fantom   \u001b[0m\u001b[37m \u001b[0m│\u001b[37m \u001b[0m\u001b[37m    FTM    \u001b[0m\u001b[37m \u001b[0m│\u001b[37m \u001b[0m\u001b[37m    44    \u001b[0m\u001b[37m \u001b[0m│\u001b[32m \u001b[0m\u001b[32m3.06100854783…\u001b[0m\u001b[32m \u001b[0m│\u001b[32m \u001b[0m\u001b[32m  $0.0   \u001b[0m\u001b[32m \u001b[0m│\n",
       "│\u001b[37m \u001b[0m\u001b[37m 3  \u001b[0m\u001b[37m \u001b[0m│\u001b[36m \u001b[0m\u001b[36m   JUNO    \u001b[0m\u001b[36m \u001b[0m│\u001b[37m \u001b[0m\u001b[37mjuno-network\u001b[0m\u001b[37m \u001b[0m│\u001b[37m \u001b[0m\u001b[37m   JUNO    \u001b[0m\u001b[37m \u001b[0m│\u001b[37m \u001b[0m\u001b[37m    68    \u001b[0m\u001b[37m \u001b[0m│\u001b[32m \u001b[0m\u001b[32m0.00089471351…\u001b[0m\u001b[32m \u001b[0m│\u001b[32m \u001b[0m\u001b[32m  $0.0   \u001b[0m\u001b[32m \u001b[0m│\n",
       "│\u001b[37m \u001b[0m\u001b[37m 4  \u001b[0m\u001b[37m \u001b[0m│\u001b[36m \u001b[0m\u001b[36m   Gala    \u001b[0m\u001b[36m \u001b[0m│\u001b[37m \u001b[0m\u001b[37m    gala    \u001b[0m\u001b[37m \u001b[0m│\u001b[37m \u001b[0m\u001b[37m   GALA    \u001b[0m\u001b[37m \u001b[0m│\u001b[37m \u001b[0m\u001b[37m    63    \u001b[0m\u001b[37m \u001b[0m│\u001b[32m \u001b[0m\u001b[32m6.03110548849…\u001b[0m\u001b[32m \u001b[0m│\u001b[32m \u001b[0m\u001b[32m  $0.0   \u001b[0m\u001b[32m \u001b[0m│\n",
       "│\u001b[37m \u001b[0m\u001b[37m 5  \u001b[0m\u001b[37m \u001b[0m│\u001b[36m \u001b[0m\u001b[36m   STEPN   \u001b[0m\u001b[36m \u001b[0m│\u001b[37m \u001b[0m\u001b[37m   stepn    \u001b[0m\u001b[37m \u001b[0m│\u001b[37m \u001b[0m\u001b[37m    GMT    \u001b[0m\u001b[37m \u001b[0m│\u001b[37m \u001b[0m\u001b[37m   275    \u001b[0m\u001b[37m \u001b[0m│\u001b[32m \u001b[0m\u001b[32m7.63004102076…\u001b[0m\u001b[32m \u001b[0m│\u001b[32m \u001b[0m\u001b[32m  $0.0   \u001b[0m\u001b[32m \u001b[0m│\n",
       "│\u001b[37m \u001b[0m\u001b[37m 6  \u001b[0m\u001b[37m \u001b[0m│\u001b[36m \u001b[0m\u001b[36m   Terra   \u001b[0m\u001b[36m \u001b[0m│\u001b[37m \u001b[0m\u001b[37m terra-luna \u001b[0m\u001b[37m \u001b[0m│\u001b[37m \u001b[0m\u001b[37m   LUNA    \u001b[0m\u001b[37m \u001b[0m│\u001b[37m \u001b[0m\u001b[37m    7     \u001b[0m\u001b[37m \u001b[0m│\u001b[32m \u001b[0m\u001b[32m0.00224116522…\u001b[0m\u001b[32m \u001b[0m│\u001b[32m \u001b[0m\u001b[32m  $0.0   \u001b[0m\u001b[32m \u001b[0m│\n",
       "│\u001b[37m \u001b[0m\u001b[37m 7  \u001b[0m\u001b[37m \u001b[0m│\u001b[36m \u001b[0m\u001b[36m    BNB    \u001b[0m\u001b[36m \u001b[0m│\u001b[37m \u001b[0m\u001b[37mbinancecoin \u001b[0m\u001b[37m \u001b[0m│\u001b[37m \u001b[0m\u001b[37m    BNB    \u001b[0m\u001b[37m \u001b[0m│\u001b[37m \u001b[0m\u001b[37m    4     \u001b[0m\u001b[37m \u001b[0m│\u001b[32m \u001b[0m\u001b[32m0.00958929067…\u001b[0m\u001b[32m \u001b[0m│\u001b[32m \u001b[0m\u001b[32m  $0.0   \u001b[0m\u001b[32m \u001b[0m│\n",
       "└──────┴─────────────┴──────────────┴─────────────┴────────────┴────────────────┴───────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top_7_table(cg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>symbol</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td></td>\n",
       "      <td>aapt</td>\n",
       "      <td>AAptitude</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>01coin</td>\n",
       "      <td>zoc</td>\n",
       "      <td>01coin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0-5x-long-algorand-token</td>\n",
       "      <td>algohalf</td>\n",
       "      <td>0.5X Long Algorand Token</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0-5x-long-altcoin-index-token</td>\n",
       "      <td>althalf</td>\n",
       "      <td>0.5X Long Altcoin Index Token</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0-5x-long-ascendex-token-token</td>\n",
       "      <td>asdhalf</td>\n",
       "      <td>0.5X Long AscendEx Token Token</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13087</th>\n",
       "      <td>zyro</td>\n",
       "      <td>zyro</td>\n",
       "      <td>Zyro</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13088</th>\n",
       "      <td>zyrri</td>\n",
       "      <td>zyr</td>\n",
       "      <td>Zyrri</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13089</th>\n",
       "      <td>zytara-dollar</td>\n",
       "      <td>zusd</td>\n",
       "      <td>Zytara Dollar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13090</th>\n",
       "      <td>zyx</td>\n",
       "      <td>zyx</td>\n",
       "      <td>ZYX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13091</th>\n",
       "      <td>zzz-finance-v2</td>\n",
       "      <td>zzzv2</td>\n",
       "      <td>zzz.finance v2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>13092 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   id    symbol  \\\n",
       "0                                          aapt   \n",
       "1                              01coin       zoc   \n",
       "2            0-5x-long-algorand-token  algohalf   \n",
       "3       0-5x-long-altcoin-index-token   althalf   \n",
       "4      0-5x-long-ascendex-token-token   asdhalf   \n",
       "...                               ...       ...   \n",
       "13087                            zyro      zyro   \n",
       "13088                           zyrri       zyr   \n",
       "13089                   zytara-dollar      zusd   \n",
       "13090                             zyx       zyx   \n",
       "13091                  zzz-finance-v2     zzzv2   \n",
       "\n",
       "                                 name  \n",
       "0                           AAptitude  \n",
       "1                              01coin  \n",
       "2            0.5X Long Algorand Token  \n",
       "3       0.5X Long Altcoin Index Token  \n",
       "4      0.5X Long AscendEx Token Token  \n",
       "...                               ...  \n",
       "13087                            Zyro  \n",
       "13088                           Zyrri  \n",
       "13089                   Zytara Dollar  \n",
       "13090                             ZYX  \n",
       "13091                  zzz.finance v2  \n",
       "\n",
       "[13092 rows x 3 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_token_list(cg)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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VvV9E7gUuEJGfqervRCQHfBR4t6p+W0R+BXSp6r0AIhJR1cJ8P7PD16Kgrz0ZwFFYLJYgsKVtmou6udREZIOIdDlP/w6cAawVEXF6vH8C+ICI9KrqYZ+ykWqUDdgmbBZLWMlbl1pTUReF4yzq/A7waRH5sKp+3Xnp9cCJAKr6I2AHMKWPgAaQL2mbsFks4WQyLbrBgljqQs1dak4sZiNwHmZx5yUi8l1VvUhEPgK8VkQEk5GWrkVHRNuEzWIJJzYturmoRwznHuAaVZ0A7gYeKSJ/EZGvq+pLReREjHstpapfAM+NFtgM9JqwpW0TNktjEJEVwP4g5/ViwFaLbi7q4VIbwyiZ490NqnoOsFJEnqmqt6jq13zKJhL0SdmWcJuw2bRoS/0RkccCP8csA7D4cBVNvqoorWWhUBOF47jIAFDVazHpzleJyDG+3X4LTKsOXW2CQCmScaNw0lmrcCz1RUTOAz4GrMSk/1t8TLYnsBZOM1ATheNaKK7iUdVPYSpA/15Enigi64HHY2I6NScZM4eZztnbKEv9EJFHA18CnoepDXi8iJzTWKnChV342VwEqnBE5LMi8gT3uaqqiESc//8HeA/wZODzwD5VfW+Qn18Oq3AsDSIKvEBVbwXagDuAB8BUL0ApKq2EvtCxpW2ai8CSBkTkc8BqVf1N0UuutdOjqt8Vke8Brao66myvalFnhbKRjEWsS81SV1T1CvDm+KCIXAZ8S0T+qqo3z/LeS4BLALZs2bJoL8dqs9SaikAsHBH5MnCBqj7deX68iDzQaS0gItIGvE1EHu+42yac/ape1FkpyVjEWjiWhuDOcVW9HKNEniSGsFRrbxgFuw6nqQhqwn8P6BSRx4jIc4AvA1/HnFynO9bMPuDlAKqad/7WbZol41FbvNMSBm4EngjU3LJfCNi06OaiKoUjIueISLuq/g14AnAF8AHgmcDZwGHg1QCq+mlgq7Meoe6k4hHS2aY/vy0NRlV/CuzBpkgDtsV0szHvGI7TYmBMVf/i+KivEZGTMQs4Dzj7fBL4lIh0q+qgqn44GLHnTjIWZcJaOJYG4i5oVtVnNlqWsGBL2zQX81I4IvJtoE1VXRdZQURiqnpTkV/6U8BhVR2sXtTqMEkD1sKxNA5bZWA6trRNczFnhSMiJwHHYBZz4sRsNmMqB3xaVbeJSA8mjjOhqq9x9gu0XM1cScWjNmnAYgkZtlp0czEfC+duzMrps0TkKsz6gs86Y/1ZRB6CSRC4xGk7UJfU59lIxiJM2LRoiyVUqO2H01RUrHCcWminAl3ApUAC2AC8SFV3Ovv0AMer6n1AaJQNGIVj2xNYLOFiMi3aapxmYC5Zas8APgSIqh7EFCN8ratsHI4BWvxvCoOyAZM0YNOiLZZw4RbtzFuF0xRUZOE4nTrPAN4HbHesnXYgIiKjqjoqIj8B7lPVn9VO3PmTituFnxZL2PBqqdlTsymo1KVWALqBXmAEuBgTyzkI3CMiB4D7VfWNEB43mp9kLGpjOBZLyFCbNNBUVKRwVHVYRN4DfBLYhlngeTWwCtNi4OuqmoVwKhuApLVwLJbQ4SYLWH3THFScNKCqV4rI2c7/w06nzjcAd/iUTd1qo82VVDxq1+FYLCHDlrZpLuaUFq2qwwAishJTwmYPcJmIxFU1G+aFbaZ4Zx5VZZbK8BaLpU5Yl1pzMedaak4lgV5gq6peCPwTiActWNAkYxEKCtm8ndgWS1iYrDTQWDks9WHOCz8dl9mtzgNgt1v9OcwkY06b6VyeRKzpq8JbLKHAutSai6qvvAtB2YBJiwbb9dNiCRO2xXRz0TS3+q6FY1OjLZbw4HX8tPeBTUHzKBxr4VgsocOWtmkumkfhuDEcmxptsYSGvC3e2VQ0j8LxLBzrUrNYwoJr2Nhaas1B8ygcJzNtog4Wzj39I7zm+9fztp/exD39I6gq2/YO2Ta6FksRhYJ1qTUT824xvdDwp0XXmj/efoDLbt5LKh7h+vsHeMIDV/KZK+9i0/IOPvPskzl+ZWfNZbBYFgLWpdZcNI2FUyot+vBohn/fPxD4Zx0ZzxKNCF963oO5c/8In7nyLs46po/dg+Nc8pftgX+exbJQsS2mm4umUTiTFo5ROGOZHM/96rU89UvX8JHfbAvU3TU4lqWrJc4jNy/nJWcdxWkbevjqC7awtrfVNoFrUkSkrdEyhBGvtI01cZqCJnKpuTEc41J7x89u5s79wzxq8zIu/st2zji6j0dsWhbIZw2OZ+luMdV+3vPkE7zt7ckoo2mrcJoNETkfeIyIvF9VDzRanjAxmRbdYEEsdaFpLJxUfNLCyeUL/OqmvVx0xnred/4DAOgfSgf2WYNjGTpbppeXa0vGGMtYhdNMiMjDgY8Bv7TKZjpux0/rUmsOmkbheGnR2Tx7j0yQLygnrOqkI2kUw9BENrDPOjKepbu1hMJJxBixFk6zcSrwNVX9vYisEpHHiMjpThfdsojIK0Rkq4hs7e/vr5Oo9cd1qdm06OYgVC41EYnWqjab61JL5wrsGhgHYE1PK+0p8xUEqQgGx7JsXDLdZd+WjDKWseuAmowckHD+/wmww9kmIvJaVS2ZtaKqlwCXAGzZsmXRXo0LNkutqQiNhSMilwBfEpFvOneCgbY8SEQjiBgLZ9fAGABrelqIRoTWRJSRomD+T6/bxf9cfvu8PstYOIlp21uthdOM/BF4uYj8L/BVVX0O8N+YVu0PaahkIcB1qdl1OM1BKBSOiLwDWIc5EaPAe4FHiUhqlvdV7HYQEacJm7FwRGBlVwsAHanYtOyx//3X/fzs+t1zPpZ8QRmaMFlqxbQnY4ymc/bkaiJU9WbgzcDpwFHOtu2Yeb60gaKFAmvhNBcNVzhi2m8uB36hqvtU9QXAncD5wBbfPtNQ1UtUdYuqblm6dPZzNxmLegpnRWfK64vTnpxqeagqt+8dnleAf3giiyolYzitySgFtQVEm5DfYm6mni8iLxWRlwKnAH9vrFiNx3b8bC4arnCcttRXAKeJyGZn2yeAfcBrfPtUTTIWYcJxqa3tafW2t6fiU5IGdg2MM5zOzSveMjhmxiln4UCw8SJL+FHVnKp+B7gQOBo4AXixqt7TWMkaj2vZqFq3WjPQsKQBEbkI2IlRLFcBT8C40dKqeq+qvk9E/iIi56nq74L4zFR80sI5/aheb3tnaqqFc+ueIQByBSWTK8ypQ+jguFE4JS2chPm6x9J5aJ/XIVgWMKp6PXB9o+UIE/7stIJCtKQvw7JYaIiFIyJfB14FnAf8DpM6+l3gZOB8ETnL2XUCk9ETCMlYhNF0jn1DE6zpafG2tyenxnC27R3y/h+fo5VzZNy1cKYnDbQnzVoga+FYLAadonCshbPYqbuFIyInAJuAh6lqQUS2At/AKKCPY9wOnxeRg8Coqv4hqM9OxiPsODRGvqCs8bnUOlKxKVlqfoUzmsnRVcJaKcfgWAaYxcKxiz8tFmBqp0+rcBY/jXCp3QfcATxYRG5Q1Z+JSAH4IfBkVf2wiHwLWKWqWwFEJKKqVUfak7Eod+47AlBk4cQZ9sVwtu0bIh4VsnmdcxzHtXC6y1QaAGvhWCwufpea1TeLn7q51ERkmYiIqo4B/cBFgAKo6i+AdwFvEZE2Vd3jUzYShLIBUzE6ky/Q0xrnhFWTLQI6UjFGM3nyBWUim2fn4XGvhUClLjVV5fJb9nLAKZFTKmmgzXGp2cWfFouhYF1qTUVdFI6IXIyxYD4tIi8D3glsBD4jIh3ObpcBWSDjf29QGWoA5xy7lMc+YDm/ed3DpizM7HCqDYxmcgw4LrH1fW3etkq4fd8wr/re9XzrmvtoT8aIRad/tW0Ja+FYgkdV+drV2zkwPNFoUeaM/+y2a3EWPzV3qYnImzAxm2dj1h68CpMaegHwA+ATInIvcCZwRFWDK2pWxCsffnTJ7a7CGZ7IeTGY1d3G5eZaOAeGJti6wzRTK8XBEWPZjKRz3nuLcV1qY1bhWALkwHCaD162jWQ8ykVnrG+0OHPCb9XYjriLn3pYOLuAn6rqPuD3wMswiufdGCX0G4xVs1VVL4LyCz1rRbtTwHNkIsfAqNF3q50Yj+v++uxVd/Hq718/JdbjZ2BscnuphAGYdKmNWpeaJUDclhvZBbig2K9k7DqcxU89kgZGgTeIyK9U9T6gX0ReDnwCOE1Vf+nfOagEgbkwaeFkPZfaGsdKGc2YUjR/usOUztkzOMGmFdMVimsZRSNSMn4Dpp5bLCK2J44lUDKOoskVFp7CsS615qLmFo6q/hr4GvAzEdnobNsJ7MXUTyvev+5njVsxejg9GcNxLZzxTJ57+kfZPWgqTO8eHCs5hmsZfeiCE3nJWUeV3EdEaHPqqVksQeGWSsrmF94V2yYNNBc1tXDcdgNOqrMCV4rIs4AbMHGd+2r5+ZXS6YvhHB41CmeVz8L50x2TfbN2O60NihkYy9CRjPHsh0zToVMwddusS80SHJMKZ+FZOH6XmlU4i59AFY6IPAaIqurlTjpz3qd0PiIiI8B7MJVyB1T1M0F+/nzxx3AGx7J0pmK0JaKIGAvn7zsPsXFJG7sGxtk9WDoTaHAsQ3fb7AtEWxNRu/DTEijpnLmByS1IC2fyf6tvFj+BKRwR+TnQAnSLyAXAH0Tk/1R1wnm9TVU/LyLfwyilg872usdsivHHcA6PZuhtSyAitMZNw7Rte4d51OZl5PWQ51orZmAsS3eJcjbFtCVtTxxLsLgxnOyCjOHYLLVmIpAYjogcCyRU9XGqegZwE/BQ4NkikhKRHuDjIrLZ6XA44LwvsEWd1dCaiBIRk9I8MJahp80ojtakKXlzeDTNss4kq7tb2D1QOoYzWKatdDG266claDyXWm7hXbBtDKe5CCppYAw4TkTOcZ5fglE6DwI2OUpmAvgYgNtGOshFndUgIl4Bz4GxDL3OotDWRJQ9R8YpKPS1JVjV3VLWwhkcy9BTostnMW0JmzRgCZaFnKWWty61pqIqhSMiDxORVlXdDXwKeLyIHK+qOcyiziTwagBVfSPwNxFZUq3QtaAjFTcKZ3SyPXRLPMrOw8aiWdJhLJwDw2nvBPczMJqhpyILJ1Zx9QKLpRIyCzhLzVaLbi7mrXBE5KvAhU5tNIB/YmqjPVNEHqSqaeD9QJeIdAGo6v+4sZuwYdpMuzEcozjakjF2OVlpfW1JVve0oAr7jkxNHMjlCwxN5KaUyylHWzLKaIkstUyuQMH6sC3zwHWp5RZgllqhqB+OZXEzL4UjIt8GelT1de42Vb0O09MmBnzIqZn2LWBYVY8EIGtNWdfbyo27BhnP5idjOIkoOecsWNKe8BaD7ipai+NWiK7IwinjUnvMp//MZ6+6q6pjsDQnGSdLzaZFW8LOnBWOiJwEHANc7Tx/joh8QES+DIyr6ruBLwPHA39V1Zc7+4W6l99Dj+5jv1Pp2R/DcVnSnvTW5hSvxXHL2lRi4XSkYqRzBa8cCZj+ODsOjXHpv3ZaK8cyZ7ykgQU4d6amRS88+S1zYz4Wzt2Y4P8qEbkKeB1wGzAI/ENEjlbV3wD/T1U/BF7qc6hn05lHT4aWuj2FY9Kl3XI1K7pSwHSX2kxN14pZ0WWU1l7fGG5Lg31DE/zzvsPzPQRLk5JZwC61qWnRDRTEUhcqXocjIsdjWkF3AZcCCWAD8CKnVM0PnVjNJuAef7pzGFKfZ+O45e30tSU45KzDAWhxLJzetgSRiJCKROlrS7B3aKrCcS2cSrLU3MZvuwfGOWqJaYGw3zfe/924hzM29lV/QJamIZNfuEkD1qXWXMzFwnkG8CFAnMD/z4HXOsrG5RhMZtqCQ0Q442hzofeSBhyFs6R98pBWdKXKWjiVKBy3dcEu33qeA8PGwtm8ooMrbtlnXQuLDBF5soi8bvY958dCLm3jd6lZhbP4qUjhOJbLGcD7gFsca+fBwFEi0ubs8xPgPlX9ea2ErTXnnbCctkSU5Z3GddbiuNSWtE8qkpVdqSnuMIBBN4ZTQWmbFV0pIgK7B8fZd2SCXQNjnoXz+BNXcmg04ykgy8JHRM4DPoBxO9eESZfawrtgq20x3VRU6lIrAN1ALzACXIyJ5RwE7hGRA8D9zlqbUJSrmQ9POWkV552wwnOluUkDfW2TCmdFV4rrdgxMed/AWIZoROhIzv51xqMRVna1sHtgnDf9+AZG0nnOOKqXRCzCQ47qBUz3UFfpWRYuInImJnPzyar6T+fGrRvo9y0nKPfeVwCvAFi3buaCsF4ttQW48NNaOM1FRQpHVYdF5D3AJ4FtwBWYLLVVQCfwdbdT50JVNmDcai2+zDTXpdbnc6mt7GphYCzLWCbH/YfHOG5ZB7+/bT/HLe+g0kS81d0t3HdolNv2DlFQk5K9rCPJ5hWm2/Yd+4Z4+HFLAzwyS4M4hGmbvlJE+oCfAOPAiIj8CNOYsORVVlUvwVTsYMuWLTNeiV2XWmYBWjj5ghKLCLmC2nU4TUDFSQOqeqWInO38PywiJwJvAO7wKZtQ1EYLikmXmi+G41ge3/jrvXzid3fy6OOXcdeBET777JMrHnd1Twu/vGG3d4Jtve8wq7pb6GlLsKwjyR37RgI7BkvjUNU7ROSJmHhnAuOS/jrwIuDpwB+AqtMSF/rCz6ijcGzxzsXPnNKiVXXYUTYrMX7pPcBlIhJ3Xl9UM2bSwpkawwH4+b93A3DltgOs72vliQ9cWfG4a3paptzN7T0ywfJOo9Q2rejgjv1D1YpuCQmqeiPwJOCjqvpVVS2o6jeAHko0IJwPCzuGA7GIOP8vPPktc2PO7QlEJIKJ5WxV1Q+JyDogjnEdLCpavCy1qTEcgHv6R3noxj5OWNXJozYvIxatXHe7mWrdrXGOjGdRhWUdZtxNyzv47rU7yBfMnZ9l4aOqt+FLGhCRpwNLMV1vq2YhtyfIqzrnTt661JqAOSscx2V2q/MA2O1Wf15snLK2hwtOXsWp63q9ba7CATjz6D5e+6hj5zzump5WALas7+WuA8PsODTGMp+Fk84V2HFolI1L26s8AkuYcKptvBh4M/AMVd0fxLjpBVzapqDqWTg2aWDxU3V7gsWqbAC6WuN85tmn0OWrINCaiNHVYp5v2dBb7q0zsrbXWDinrOvm2GUmUcC1cDav6ATg1j3WrbZI2Q48TVVvnXXPClnwLrWoVTjNQlD9cJqKlV0pYhHh5LXd83r/ut5WPn7hg3j+GevZtMJYMW4MZ/PKDtoSUf5x76GgxLWEBDX8SVVvD3Lc9AJuT2AsHHMZsvpm8RNYi+lmYtOKDnrbElNSqOeCiPCMLWsBOGlNNyKwvteUuYlHI2zZ0Mu1221NNUtlLOgGbAX1LBybpbb4sQpnHnzs6Q8K7G7sMScs509vPpd1fa3etoce3cdHf3s7B4YnPFebxVKOyRbTC0/hqOIlx1iX2uLHutTmQSoenbd1U4yIsL6vbco2t3jnP6yVY6mAzIJuT6C+tOjafY7JBl14389iwyqcEHLiqk7akzH+vt3GcSyz41aLXogLP02lAXMZqpWFc2Q8y+kfvpIrtx2oyfiWyrEKJ4TEohE2rehgx6HRRotiWQCknWZ+BV14cZDClCy12nzGwZE0E9kCe4+Mz76zpaZYhRNSulriXutqi2UmMvkCbhm/hbYWR+uwDmcsbRRyZgHGuBYbVuGElM5UzCocy6wUCko2r7Q5df9yC87CUa9KR63aq4+kc8DCTBtfbFiFE1K6WuIMjecaLYYl5LjxG7eVxkKL47jVoqF2LrWxjKtwFtZ3sxixCiekdLXEGZrI1uyuz7I4cFOi251eTJkFdlGtR1q0a+FYl1rjsQonpHS2xFGF4bS1cizlceuotTkKZ6GVtymoEo/OnKX2j+2H+Mud/fP+jLHMwq01t9gI1cJPEYku5tpsc6HTqdc2NJ71ardZLMW4d+1tSdeltrAUTl4nq6KXM3C+8Me7GZrIcc48mxKOuhaOVTgNJzQKR0QuAVREEsA7MW14mzZq7iqZI+NZ1jZYFkt4cV1qbtLAQmtRUPD1wyln4Uxk81VVURi1WWqhIRQuNRF5B6YZ1X8DUeC9wKNEpGnrunSmJi0ci6UckxaOo3AW2F28+rPUylg46VyhqjpxNmkgPDRc4Tg9QpYDv1DVfar6AuBO4Hxgi2+fUu99hYhsFZGt/f3z9/GGEb+FY7GUI12kcBaaS62gEHctnDIaJ50tVHVcNi06PDRc4Thtqa8AThORzc62TwD7gNf49in13ktUdYuqblm6dH7+3bDi9uAZmrAKx1Iez8Jx0qIX2l28v7NtOZdaOpevylXoJg3YGE7jaZjCEZGLRORcR8lcBYxj3GhHAajq+4DVInJeo2RsJJ0pc8faDBaOLao4f4pdagtp4af7u89W2iaTK5DNVW/h2BhO42mIwhGRrwOvAs4DfgecCnwXOBk4X0TOcnadAJoyL7g9GSMakUWvcD7629t51sXXNlqMBYubFu2uw1lILQpcBTNb8U4bw1k81F3hiMgJwCbgYar6DuD1wDeAFuDjQCvweRH5HTCqqn+ot4xhQEQWRXmbuw8MMzyDW/C2vUP8877D7BoYq/qz7ukf4fQPX8ndB0aqHmuhMC1pYAFZOG6h0cm06PIKp5r4y0jarsMJC42wcO4D7gAeLCIxVf0Z8Dbgh0Cnqn4YeBLwDlV9KoCINDzW1Ag6F3h5mxt2DvL4z17NZ6+8q+w+A6MZAP54e/Wl42+4f5D9Q2n+78Y9VY9VK8olwMyX9LR1OAvnoupaNPFZXGrpXL6q4xpbIC61G3YO8p2/39doMWpK3S7kIrJMRERVx4B+4CJAAVT1F8C7gLeISJuq7lHVrc77RFXDPVNqxEKuGH1kPMt//uB6snnlhp2DZfcbGHMUzh3VZxnuHjTl5393676qxwoSETlbRC4CkwATpNJxL6KtiYWXFu0aNG5adKnWCm5x0most8mFn+G2/n563S4+fvkdjRajptRF4YjIxRgL5tMi8jLMws6NwGdEpMPZ7TIgC2T87y2XodYMLGSF85kr72TP4DgPOaqXW/cMle3T4lo419xzkIlsdUUmdg8YhXP7vmF2Hq7eRVctIhIRkXbgYuDtIvIq8JROIOfeZGkbN0tt4ZwuroUz08LPIJrLjbqlbUJu4WTzhUWfSVdzhSMib8LEbJ6HSX9+MvBB4AJgGfAJEXkbcAlQaObqAsV0puIVpUVfW2WtqaC5/9AY37t2B886bS3P2rKW8Wyeew9Oj6ukc3lGM3lOXtvNRLbArXuOVPW5uwfHWdaRBOCKEFg5qlpQ1RHg28DXgTNF5A3ua0F8RnHxzmqC6/Umr8UxnOn7pLPmeObbXE5VF0xpm2xeyeQLizprsx4Wzi7gp6q6D/g98DLgFODdwLOB32Csmq2qehEE7+deqJgYzuwK5+NX3MGHf7OtDhJVxhf+eBexSITXP/o4TlzdBcDNu6crk8Exc2xHL20HYHiiunjV7sFxTtvQy9reFm7cVZ3yCpgcsBajeB4iIp8SkY+IoeQ5WOmi5vQ0l9rCuVi5KncmC8e14GB+7sJMvuCliofd3ZjNF1BdWKntc6UeCmcUeIOIbFDVnKr2Ay8HjgdOU9VfquqnVPX9YNwQzexG8+O61Gb7OnYNjLH3yESdpJqd2/YOccbGXpZ3pjh6aRupeIRbdg9N2++w405b3W0qGI1n5u9SKxSU3YPjrO5pYWVnCweGwvN9AL8E9qnqVcBWzJKATjWUvApWuqh5/9AEHanYZFp0yC+qfjyX2gylbdI+N9h8LsRuHTUIv0vNtU4X0m84V2qucFT118DXgJ+JyEZn205gL6Z+WvH+i/fbniOdLTGyeWUiW/4rSefy7B9Kc2Q8W9UFO0j2D6VZ0WWUSCwa4fiVnSUtHDd+s7qnBZhcET4fDo6myeQKrO5uYVlnkgPD6XmPVQPGgU0i8nKMsvkosE5EXlntwPceHGXjkjYv02shlbbJVxDDmaJw5nEhdt1piWgk9EkDrnUa9my6aqipwnHdBU6q84+BK0XkNBGJY+I6a2r5+QudVV3mQrxt33TrwGXv4OSd/L4Q3NVn8wUOjqRZ1jFZd/UBqzrZtreEheNkqK3qdhROFUkDbsLA6u4Wlnem2D80ERpfuKruAXZi3MhvdKz5T2HcyVVx78FRNixp86yEhXR3PC1poIQFM9WlNvvvOTSRZb/vPBh1Fn12t8bJ5MJxQ1YO97ezCqdCROS9InK2+9xvrajqR4BPA+/BuBgGVPUzQX7+YuMRm5eRiEb49Y17y+6zy7nQAuw9Ml52v3rRP5xGFc/CAVjf28bwRI4jY1PjUQPO89WOwhnPzD+G46ZEr+5pYVlHkrFM3itpEhK+CjxVVX/lPP+zY+nPm4lsnt2D4xzlt3AWkP+/OC16dpfa7Bfij/32dp73tX94z12XWk9rIvTxLdc6DXtyQzUEpnBE5AvAiar616LtUedvm6p+HngB8AJVfa6zvSkXdVZCV0uch29ayq9v2lM2Q8e/Qn9fCOI47t3l8s6kt21tr1EoO4uqCbguNc/CqcKl5lk4PcbCAULlVlPVnap6nZsQE4Tr+P7DY6jiKBzHwllAd8eFoiy1ki61rN+lNrvCODya4e4DI97NhutS626Nh976y1gLpzJE5MvAY1T1Quf5el8RzryILAE+LiKbVXUAGHD2a9pFnZXylJNWcWA4zT/uPVTy9V0D4zjnq5c48Le7D/K1q7c3ZOJOKpxJC2dNTysw1RoDc3HoSMZIxaMkYpGqYlC7B8fpSMXoTMVZ5ii7/SFwMRYTZELM9v5RwCgc1y21IEvbiCBSurSN/26/kjt/d87ftX8YmKyj1t0aJ1fQsi0QwoAbo7IWzuz8CZgQkVNF5PmYJIGfiMhXRWS5qh7EFOL8GBgl5PwN768fEh51/DIA/nnv4ZKv7x4cZ2VXC10tcfYPTfDJ393B8772Dz542TYu/Mo109xYtca1svwKZ62ncKZaOINjGXraEgC0JqJVWTiHRjIsddbguPGjA0PhsXBqwX2HjMLZsKQNESEWkQVV2sY9+yMRISJS2qXmi+tVYuG4F+s7HYUz4nOp+V8PI67Lr5rK2GGnKoXjWC6o6qWYgOgfMDGalwCPBHowizxR1TcCf3PfY6mM1kSMntY4h0YyJV/fNTDGmp4WVnaluHHXET7/h7t50oNW8olnnMRNu47w21vKx39qwf7hNPGo0Ouc4GCy7TqSsekWzliWHqfvT2s8yngVSQPpXIFkzKy2d915B4bDZ+EEyb39oyxpT3rdYWNRWVAxHNeFFhHzmC1LrRKXmLv/nfvNQuNJCydR8RiNwksayIc7uaEa5q1wROTTwGUicpzjGvs/4JnAMxx/9RFMCZuCiCQBVPV/HGvHMgf62pMcHCl9t75rYJw1Pa2s6Epxo1Oz7D/OPZqnnbKatkSU2/cN11FS2H9kgmUdKSKRybW7IsLqnpZpFs7A6KSF05KIVuVSy+QLJGJmOrcnY7Qmouxf5BbOvQdHOWpJq/c8Ho0sKP+/61KLiLFw8rOlRVegTDO5qRaOmzTQ7dzYhDlxwFU46QX0G86VaiycAWAJ8J+YFGdU9QpVvdG3z/uBMVVd3Gd+jVnSniipcDK5AvuGJljd08IKx4W1ojPFCSs7iUSETSs6uK1EOnIt2Tc0MSVhwGVtbys7D0+1cAbGMp4l1JqIeXej8yGTy5N0Auci4qVGL2Z2Doxx1JI273k8GuHWPUd49Kf+7CVkhBlXf4gYpVOytE3O71KrPIZzh3Oj5WY+djgNDcOskCcrIoRXKVZLNQrnSuCLQBR4h4gsddbYJESkR0QuxSibN4AtV1MNfe3Jki613YPjqMLanhYvDfkRm5fiftXHrzTrX+oZKts/NDElJdpljWPh+GUZGM14ro6WKmM46dykhQOwtCN0iz8D5+q3PIJ3PekE73ksIvzrvgHuPjDCPf3h7wmkviy1iJReh5OZ4lKrPIZzYDjNwGiGiVyBVDxCYgGsU3IzDMOsFKtlzgrHTXPGKJrjVPU1wEFMyY6PqWoGSAE/UtUXO++x5WqqYGl7kv4SFo6biXPs8g5Wugpn0zLv9c0rOxmeyLGnjunS+4emLvp0WdPTymgm79VPGxzLMJrJ09c+mTRQTQwnU6RwlnemwlbeJnBi0YgXvwG81GiYLBsUZlz94rrUZluHU1kMJ++5z7YfHGEim/eyICHkSQMFW2nAQ0SOF5HnAq8XkaSqXg24TnnXh7JbRFao6l5V/anzvohNfa6OJe0Jhidy08r33+V0tjxmWTuPPn45rz73aB6+abLu1gkrTeeHbXvq41YbSecYSedKWjhre6auxXGbpD38OCNvtVlqmVzBu4sFWN6RXPQxnGLcxZ8w2WcozEzGcIxbbdZ1OBUs/MzkCixtN5ejkXSe8UyeVCzqzY0wX8xdhRpmK6xa5mLhPAP4CDCuqmnHRdYlIjdhCnFuBPLAU/1vssqmevqcE6j4rvXuAyOs6krRnozR157kLY/b7GVqAWxa0QnA5/9wFy/4xj+r7jczG25SgLuQ088xy0xF6Ev/ZRbX/2jrTk5Y2elVk26JxwJLGgDoaUswns2H+gITNDGfwj20ICwcX9JAREq6fuda2iaTK9DVYiyc8Uzec6nFF4BLLdcEtdRilewkIl3AGcD7gO0icjym5PofgCWqer6z30usggmeJY7COTiSnnIxv+vAMMcs7yj3NtqTMdb3tXql+v99/yAPPbqvZnK6CxE3+gLZLhuXtvPKczZy8V+2MzSR45bdQ7zvKQ/wXjcWTjVJA1MVTkvcKN6xTI5ELFHubYuKmC8zcCEkDWgFLjX/xbeidTi5Ap2Owknn8tNcamFWOF6WWohlrJZKLZwC0A30Ypqm/QL4AvAQ4J8AIpJylY1NEAgWN87hz1QrFJS7D4xwnGM5lOPjF57EF557CgDX7Si9eDQotjuB6o1LpyscgP/32E084YEruGrbflZ0pjj/5FXea4G41HwKx+2AORqSCtr1wH/8h0crX/A7kc03ZMGomwYdiVBhWnQFLrV8kYWTzZOMRz0LJxPiRZWeS63ZLRxVHRaR9wCfBLZhOnf+FVgBrHL2mfDtH95fdQGy1LNwJu9adw+OM5EtcOzymRXOQ47qBeBzV93F1h0DtRMSY+Gs7Ep5zcCKiUUjfOl5p5Z8rSURJZ0rkC+oV1trLhTHcFwZqikIutBwLZxYROYUw3nWJddy+lG9vOMJx9dKNJ70+at5xqlreeGZG7xtU1xqZUrbzMWlVigo2bx6CmcimyedLZCKRUjEzHcT1qSBfEE9Cy+sMgZBxTEcVb0SOBt4uar+F3AbpmNn+e5QlkAoZeHcdcBkqB2zrLxLzc+p63u5bsdATWtJ3XNwtKx1MxutCWORzDdTLZ0vkIz5FY5j4aRLj7fvyAQnvOdybinRp2eh4sZwTljVWXGWWi5f4NbdR9jhlMmpFXfsG/bmrItOUThCKQPGn+4+mxXmXqg7nTU349kCEznjUgt7cVO/q28xx3DmlBatqsOOtbMS+ACwB/it09/GUiNaE2bl/MHhDHfuH+apX/obr/zudcBkMH42tqzvYXgix50HalN5QFXZ3j/CxiWVyVOMG3OZT+KAqk5zqbkWzmgZC2fnwBhjmfy0i+BCJh4VulvjHLWkrWILZ++RCXIFrWkrh7xjeRS7TKemRZfPUmtzbh5mi7+4CqfDSRUfz7oxnEjoYzj+KgphlTEIKnKp+XHaCfQCW1X1QyKyDogD9a0S2WQsaU/y17v7+f4/dtCejPHis45i84oOz30wG6dtMK6163YMsNnJXguKI2NZRjM5hidy87ZwWjwX2NwVjutqKWXhlBvPLVs/PLF4XG6ru1tIRCP0tiU4XKb2XjFumvpIGUswCNw79uIsyalp0WWSBvIF2lMxBsays7rU3M9JxiOk4hHS2TwT2cIUCyes7iq/5bWYLZw5KxwnMeBW5wGw263+bKkdS9oTXH//IKu7W/jFa87yKiNXytreFtqTMe7aH/wK9Gdd8ndvQefGpfOzcFwFMZaduwJwLyJzSRpwFdHQ+OK5T/rwUx9IQeHiP9/DcDo3zeorxc7DjsKZqN334MZhipW/F8OJCJFI+RhOm3MzMlvSgHuhTkQjtDjFYCeyC2MdTtZ3bLaW2gxYZVMf3LU4H3rqiXNWNmDuINf3tXol7YOkfzjttbculRJdCS2uwpmHheO/0LjMljTgKqLFZOHEosZ15BZEHazArebWtysX6woC9wLqj8/dsHOQbXuNO3PG4p3ZAu1J81tWauEkYhFS8aiXpTZ1HU4485n8clmXmqXhXHTGeh66sY9zfaVr5sqGJW3cWoMgeTpXYEVniu7WuNcueq60VhHDmbzQTC56nS1pwF3zM7SIFI5Lr6NwDo9lWNY5veqDn/sdC2e0hjEc15Xm/23f9YubvQKbETFN2MqVtnEV6GzrcPyWbks8ykSu4Cz8DP86nJxNGrCEiXOOW8pLzj6qqjE29LWyc2A88JMuncvz1Aev5vLXnzOlLcFccC2SqiycEkkD5RaTuopouIaupEbhNhurJFPNVTgjmVzNiryWsnAOj2S8u/pIRMqWtsnkCrTGo4jMzaVmLBzjVjTrcGTKPmFjSpZaSJViEFiF00Rs6GsjX1B2FzVCqwY3Aynlsy7mw6RLbT4xHHMh8yucRCxCLCJlFZjraltMLjUX18IZqGDxp1uOSHV+yr4S3HpofoUz6IuduS61cjGcRCxCPBKZ9UKcnuJSi3hxRb9LLawX82ZxqVmF00S4vVPuDTCO4waEk/HqptJsWWUzyzA9huOOWe4iOhnDqb2FIyIPEJGHi0jt6gr56GkzmYuHR2cuXjqaznFwJOO5QQ+NZLjgi38LvCLFZNLAZPl9/+8ScfrhlFuHk4xFiEdldpeaT+G0JKJearg/aSCsF/Ny63DyBeVJn7+aK27d1wixAscqnCZifZ9ROPcdDE7hTDh3r8lZsqFmozWApIFiGdqSsbKxiXrFcETk8cAPgTcA3xGRFTX9QPwutZmV6Y5Dxro5fqVJk7993xA37Bzk+h2DgcrjudSc7/xIUWZgRMq71NK5Asl4hFg0UvHCz2QsQioW9T4nFY8SiQixiITYpTZ57P4stRGn7uAfbz/QCLECxyqcJmJJe4L2ZCxQhePevabiwbjU5lNpoFQMxx1zrMx49YjhiMi5wGeBl6nqBUAGOLFmH+gQj0boaonTP1K+H9BYJsc7fn4ziViEs44xhpcbzylWCNXiJQ1k86hqSYVjineWylLLk4yZGEx2lioZkzGcKKlEdIpLDcz3ElYLx69M/TK6ywTu2L84FihbhdNEiAgblrRy36Gx2XeukHRAFk4iGiEakXnGcEornLZEjLGyFk5d0qL3A69U1X86ls3pwH+KyMUicuFMRW5F5BUislVEtvb398/5g9f1tnK/r6X3G390Ax+67Dbv+WeuvIubdg3yuWef4lk47pqcIZ8S3jM4XrGb89O/v5Nf37Rn2nb3jr2g5rc6Mj41mSESMV0/yy38NPG4Ciwcv0stHvVW77s3Q/GohD4tOhmLTLHC3Hl6577hunburRVW4TQZ63pbvdXlQTDhxnCqTBoQEVrj86sYXWodDhg3XbmFn65iG8vUrlKyqm5T1T86T18KfMmxdP4OXAgsmeG9l6jqFlXdsnTp3MsVrutr5X4nVpcvKJffso9/3jdZvPX+Q2Mcu6yDx524wlvnUsrCueCLf+Pzf7iros/8/j92eP2O/PgLcE5kCmUsnOkuNTchJRmLEKskhuNLHkn5Yoru/4lYNJCkgYMj6cC7yboLP9uSsSkyusp+NJNn92BlyT6X37KXt/7kpkDlCwqrcJoMc9cfXDaSa+GkqkwaAOMCm896kHIutdZEtHxpG9/2WtYRc1HVD6nqB53/vwV0Amtr9XnrelvZNTBOLl9ge/8IY5k8B4cnkwhGMzlanWoMbWUUTjqX58BwmjsrcOeoKoNjWe4t4a71d+0cz062GXcxMZzpFs5kbM6UpplNWRRbOC5uBmUiGkwM520/vZk3/OiGqsfx45a2aU1EyfpaKPhvwCr5HQCu3HaAS7fuLPlbNBqrcJqMlkTUs0qCIO27KFTLphUdbPXdhVdKOZdaazJWtnin39VW69ToYteZiDwdWI4pflsT1ve2kisoe49McJPTgK9/OO25ZUbTOc+ycf/udNLl3XI/rmJwFdFMjKRz5ArqtM2YOr/8z8cyuRIWDiXbE3gZkHPNUosWKRwnPhiPBRPD2XFolAMBty933X9tiakWjt/FfMe+yspSub/bVdv2ByhhMFiF02Sk4tFAW027Y1WbFg3wmBOWs/3gKPf0z63eW9m06Hh5C2csk6fDudAO1Tg12u0PJSJJEXkp8H7ghapas1zXdX2tgFEWNzvVJUz8xBzraDrvZQa6Cse9YLv7uGnF9x8emzV+4F7kVKcrKH/Wld/CcdcLFScN7B+aYHgiO2VdTSwSmXXhp3//ZEkLJxiFc2A4HXhlBleu1mR0ihU2Pg8Lx42R/f42q3AsDSYVizCRLQQWgHRP8moXfgI8+vjlAFx+yz4uu2lvxYpxvmnRy7tM2Zeh8bot/iwAe4GnqeottfwgNwV+x6FJhQPmYgnGpeYWxUzFI1Oa3h1xvg934ehEtkD/yMx39H6rZXvRDYNf4Uxk8xwZz9KRirHMqQkYjTi11Jy7/Bd8/Z987PLbvUoJPa2JigL+/rToKRaOL0utWpeaK/+wM69e8I1/8tPrdlU1JkwmDUy3cMw5sHFJG9v2DlU0lqvQt+4YCF2rcatwmgz3zi+oirRBLfwEWNXdwgNWdfKJ393Ba35wPT//9+6K3jdTDGemhZ8rnDpj9Spvo6pZVf2Nqt5R689a0ZkiEY1w78ERbt1zhBNXm0y0flfhpHNe7EZEvJ4zMGnx+Yt/7pzFreaPy2wvih34kwbGnaSBrpa411hQBGcdjtln//AEOw6NcchpsbCkPWHW4cylWnTCr3AmXWqZKrPU/N9foaBcfVc/19xzqKoxYdLCaSu2cJybrtM29HLXgZGKbsIGxrJsXtFBvqD8497atpWfK6FROCLyORH5kIh8otGyLGbcky8ot5q78DMICwfggpNXe66xfUcqywQqG8NJmNTY4rvabL5AJldgWae5w16M5W2iEWFNbwu/vGEPE9kCjznerDc9MGy+09FM3ksagMmmZWAu3BPZPId9Cme2OM6gL9X53v4ihZOdGpM4Mp6luzVOX5v5/iMiRCOTpW3G0nn6h9Mcciol9LUniUUqsHByBWIRIRKRoiy1yaSBajt+ut9fQeHgaBrVyW3V4GZKtiViJV1qZxzdS76g3Lpn5uK7Zp1ThlPW9QCTpYvCQigUjoh8GDgW+DFwooj8QEQ2V/C+qtYqNCPuiTiRDZ+FA/Cyhx3Fjf99Hj2t8SkttWeifFp06QKertWzsqu+Fk69Wd/byoHhNCes7OSih64HzB26q3DbE5PF4t3+Qa6lc2Q8O8Vq2Xl45pRcd9+jlrRNy47yJ6mYGE6G7pYES9onFU7EyVLL5Apk8gUOjqQ9a2JJe4J4JZUGfP1/SrnUErHZM91mw58ssHfQKJpKb4xmwrW8WpPRqQs/XYWz0SzOvWHnzApnLJMnm1c29LXSmoiyZzDY9O1qabjCcTJ4VgIXq+oNqvo4oB94q1sGpNwCuWrXKjQjriUSlIUT1MJPFxEhFY+ypD3puVRmlSGXJyKmH4wfr0VBkVvNvWucdKktPgsH4NjlHSRjET7z7JPpaY3TEo9yYCjtpcW3Jv0Kx/y/wam3NzSeZWA0Q0s8yorOlGfhXPqv+/nVjdOT69wYzilru6cpnHS2gHsGuzEQv0stEsErbeP+NodHM/QPp4lFhK6WOLEKYziuwimVNNCejFXdcO+AL7V8r6No9gewJsdv4eQKSsHxL45lcyRiEVZ2tbCyK8VNuwZnHMdN9OhpTbCqu4U9Fa7dqRcNVzhOBs/fgAeLyDJn2+sAwZQF8bJ8LNXjudQCSo2eCKi0TTFL2pNzsnBKdbZ0L6jFTdjcVOnOljipeMQLAC82XveoY/n9Gx7Occs7EBGWdiTpH0kz4hx/u8+l1l6kcI6MZxkYy9LTGneqFhiFc/Gft/PNv9077bMGx4xyOmFVJ4dGMxwaSTOWyTGazpHOFbxW6OMZR+G0xjljYy+nru+hqyXuWTiubAU1WVl97QlEpKKyNJlcwbNyW+KTmWluy4zlnakpCmM++N1n+444aeQTuXkVnfXjZak5VqdriY1nJrMJT1rTzY07B2ccx7U0u1rjRuEcsQoHABE536miuxK4ClNj6iwR6QBQ1RcBvSJyaqNkXIy0JAJ2qWVLu7OqZUnH3BROqXVAbWWasHl3+IkYnan4omoz7actGfPSowGWdSTpH057a5BafS41V+Fs9CmcwbEMPW0J1va2cv8hkxq9b2ii5Ir3wTETl9m8wi0EOswbL72R//j+9aRzebodhTPms3BOXd/LT//jTJKxqLcOx78+6vZ9w57bLR4Vb61KOUq51Pyu3uWdKY6MZ6uy7qe41HyutGqtHNd6c5WLq3DGMnmvOeFJa7u579DYjJ1cXUuzu8U0QwyyFUkQNEThiMg3gbcC/wH8FGgHPgG8AniCiBzj7BptlIyLlaBdahO5/JS7yKDoa0twsEKXmt+V4sfNVPretTv4iS911bVw2hJROlKxRetSK2ZpR5IDw2mvskJ7crrC2eCkUw9NZDk8lqGnNcGanhb2D09weDTDWMZUH0gXWciDjhI5fmUHALfuOcLf7jnIzsNjTGQLdLbEETEtELJ59RSQi5sW7Xd/7j0y4bVWr6SWWto3D1yL2295u2nYlS7anMjm+cIf7ppyrAeG014KuV/h7JuHwlFVLxU8VzAJD66CdOOS45m8N48fuLoLgFv3lE+P9lxqbQlWd6c4NJoJdN1dtdT9Yi4iDwE2q+qZqvqfwBeBPwGjwHuAc4AvishVwGFV/Ve9ZVzMJAPOUktnC4ElDPhZ2pFkJJ0rK+eOQ6NesDbtc6X4cdeZ/Pi6XXzpT3d72133R2syxuqe1jkvNF2oeBaOe/y+1OHiGM6RsaxntazpaUEVbnDcOaqTAXOXI86+fe1JlnUk+fVNexmeMBlp6VyeVCxKSzzqXZi7ihWOU7yzuNjqEifOU1EMp4RLLVVk4YBJu66Ef9x7mE/87k6u81W/ODCcZl2vsRr3VWnhvOUnN/Hq718HGAsnFhVPflfhjGVyniV69DKnn9XBUS6/ZR/PvuTv09bTuS617hbjUgNCFcdphPWwG7hNRLpERFT1+8BrgMuAIeB1wGuBj6vqhQAiYq2cgAg+S620O6ta3AtNObfaq753Pc+8+O+MuW2ES8VwfBfUnYfHvDtk18JpTUQ5eW03d+4fDnzleBhZ2pHkyHjWW1DZ5rNwOlLm/6M8l1qOAcfCWd1jLlxbd0xeeIvdaoPjJvMMTH8dt5yOcWGZm5KWeJRdjounx6ky4OK61IoTPDyXWgWVBvzzIOW4jv3p+p7CqVA5jDiWrz/G1z884X1He4cmv4P5KJx7+kf4p7NOJpsvEI9OdibN+lxqrvJc3pEiFY9w78FRfnfbPq7dfthbT5fO5fnj7Qc8l5obw4Hpv1UjqduFXES6nH/3A13A+91kAFX9X4xL7SXmqd6pqpc77xNVDWcTiwVIylv4GZSFkw8sQ82Pe6Ep5VbL5QvcfWCY+w+P8fEr7iibNNDbliAaEY5b3k42r96JNxnDiXLK2m4KCjftOsKP/rWTI2OLM54DsKzDXHDdfkh+hfPIzcu46Iz19LTGaXO6ZR4ZN0kDa3vMHf11foVTFBtwrSGYbOgGpuLz4dEMyViUVDzK7c5qeTdW5OKWtilW/H1tc7RwZnCpLXfWXe2v0KU2kjZzwXW5ZvMFDo5kPIWz/0iaeFRoTUQrHtPPaDrPwFiWQyNpT+G48rsWzkR20qUWiQgb+tq47+Aod+wbdsYwsv3+tv28+Fv/4s939NOaiJKMRb1Ork1n4YjI54DvicgHgIcDzwPOFZHP+3a7FuhV1SlXQpuhFizuCVhtVo1LOlcIpFJ0MZ7CKZFVtHNgnGxeWdmV4lvX3MeB4XRJhdPXnuRPbz6XD17wQAAvXXcyhhPjpLXdAHzt6u285ac3cdnNewM/lrCw1Lng3uspnMmL8SnrevjABSciInS2xNk1MIaqsURWdKWICF6GlMjUBYWqamI4nsLpmPK5B4YnjIWTiJLOFYhGxCu94+Jmqbm/jTunJpMGKshSy09PGvDPza6WOIlYpOLWAiPOjcmIs07LtQw3OIkYmXyBjlSc5Z2pecVw3Fja3QdGyOWVeFQ8+dM5X9KAz1LfuLSNu/tHuOvAiPe6X7Z/7TjsxcdWdKUQgd0hWotTc4UjIv8NnAC8GTiAsWJeDDwEeIiIfEVEngG8HVj8fo0Gk4q5LrWgFE6+Ji61vhlcavc4J9v5J69G1bgmymXJre1t9e5I3QutF8NIRultS7C+r5Wrbj9AV0ucC05ZFfixhIXljoXjlp5p82Wp+elqiXtN+kwdswgrOlOkcwW6W+Os7Eyxy3fXPJE1C0ldl9oJjoXzoDVd3uvJWMS7cK7vbZ12g+Cuw3Gtz/W95jdz50Gl1aLdeRB3Gvr5LRwRYXlnsmL3l2s9jBT97WyJe8fSkYqxvDM5r/44nsLpHyGTLxCLRDz5p7jUfApnQ18bOw6NeRaQq6DdTEtV6Gp1v7MIyztSocpUq4eFMwR8xakf9W3M2ppHAc/FJAjcCTwAuEdV/wPKL/S0VM/kOpz5eSnHM3ku+vo/uPouU9lhIltbC+dQieKDbpD/Ycea/mXDE7mSFs7kWAk6fK21xzI5opHJAO3JjpXz7NPWTkkVXmws81k4IlNX4/vpbIl7625cN5kbx1nekWJ1T4sXi4HJzCh332OWtfPRpz2QV597jLeP61ID2Li0fdpnRkQoFNS7gK51AvPuPKi0lpp/HrTEo9NuhpZ1pCp2f7kKx43huF6BlnjUc0cahTN3C0d97kPXwknEprvUxrNTLZyjilyRbsr/kC/Tsqd1MiFjaUfSKxEUBuqhcA4D7xeR1ao6BNwIfA44C+hU1U+p6ntV9Y1gEgSsG612VFtL7Rt/u5er7zrItdtNwcJaWTipeJSOZMwrb+Lnnv4RlrQn2bxi0nUzk8IxrbXbvDv7kYkcrYko7n3NWUcvIRmL8Pwz1gd8FOGitzVBLCIcGc/SGo+WTWV/9PHLvAtej3O3vMaJ4yzvSk1b3+FmRrkXOhHh2Q9Zx3rfGqBUfLKC8zHLpiuctmSUkXSe0XSOVDzCii6jaCaTBkwMZ6ZLg3GpTS3aWXwztLwzWXGWmmfZTEx2hwWzfsltbdGRjJtFysNzq8qczhW8dUV3Hxghmzdp0Z7CyU/PUoPpCsdVgv61ZN0+hdMyQxPCRlBzhaOq3wYuBT4nImtUNQ38G1gKnFxif5sgUEPcO/v5ZKkNjmX4yp/vASZ9xulcbdKiofziz3v6RzlmWRu9bQkvYWG2hadHLWnjPqfl8rZ9w1OC1heeuoZr3/4o7656sRKJiLcWxZ8wUMwrzjma7770IbzgoevZ7MRj3AD0is4ka3pa2Tc04WX9uXOhq2Vq5pn/wpd00qIBjl469aIJRrEcHk0zPGEaw23oa6MtEfV65rhli/IzLP7MFKXHb+hrnaL0wFg4la7DKXaluTX5WhJTLZzOVJzxbH5OvXb8yRFG4ei0LLVCQR0PwnQLx/UBeS61iaynXP2/Q0vA/a+qpWYKR0QiPtfYl4Gbge+KyCZVHQESmK6HljqTjEfmNQl/ct0uhidydLXEvTpnE9l8YJWii1nSnpimcFSVuw+McPTSdkTEuxDOZOGAWV+ye2Cc0XSOG3cOcur6Xu+1SESmpekuVpY6qcEzKRyAhx27lPeff6Jnva7pcRVOilXdLeQL6pWJ2XHYKPLii7t/rY0/hlPKwlnSnqSgJoW3NRHjooeu54o3nOP9rrGouZTMlKmWLnKpXfrKh/Kmx2yass/yzhQj6VxFbcU9l9rEVJdaayLqJVx0pOJ0tpjvcqTMAuLRdI6P/GbbFCXjfv7RS9vYe2SCI+MZ4lHxlPJ4puC1JvC71HrbEnSmYhzrfIdjXgwnxwkrO3nQmi5OWtPl7d8SL9+ioxEEqnBE5DQROQOMpeJLez4AfAS4Avi+iPwWGFfV7wX5+ZbKSMWj80qLvvqugxy9tI0TVnbWxcJZ1jFZ+2qP07r48KhJ1z3aiQOsqlDhHLOsnYLCpf/aSTpX4NT1PTWROews9yycud0keDGcrtS0NVLb+0eNG8xRZi4t8ahncSTjEa/V89ElFI6bHLDj0JiX1uu68cCswwHIzhDHyeSmpuhHnVYFftzU6EoqPBe71EZ9Cqe9yMKB8p1j/37PIS7+y3auuv3AtLEftKYbgDv3jxCPRmh31kMNT2RLLtAVEf7nwpN4+xOONzJ5MRxT6eH//vNsnv2Qdd7+LYmop7jCQGBXChH5GfBh4EtO5tmpIuK/jSqo6keBZwCvVNWnOe+zizrrTCo+N5farXuOkM7l+ee9hznrmCX0ticmFU629KLLIFjWmeTAUBpV5Ymfu5ov/vFu7nF6rWx03DJui4HZZHjEpqW0JqJ86vd3AjStwnETB+aaHPGAVV0cu6ydU9f3sKTDXSNlFM69B0c5akn7tIu7m2INxqX24HU9PHLzMu8C7ceN1eweHC9pfcUdC2emTLVyJY78uJUUiruSlsK9mE8mDUx3qXWmYt6i2XIlktzv6XrfOiZ3bDeF/Mh4llhU6PSN5U9S8PO4E1dw2gZjoY/5stQ6W6Z/ry2JRehSE5GHAm2q+hjgdGAEeAFwtohERWQV8A0R6VTVe4Fdzvvsos4GkIpVPgn/fs8hnvi5v/KfP/g349k8Zx69hL62hJc9NpHLB14p2sV1f+w8PM7AWJZbdh/xLhTTLJxZYjgdqTgXnLKakXSO1d0trOhKzbj/YsVNjW6fxaVWTG9bgt+/8eFsXtHJUm+NlJkD2/tHpi3kdHHjOKl4hAtPXcM3XnRayf1chZMvaEmF48ZwytVTU9VpMZxSuK4odx3LTEzGcIzl4locbYmYz8KJexf6ckVg3XPl3/f7FY4Z2y12CiaNuS0RQ8RYLGPZ6UVWXVwl5Mo0NJErqchb4oszaeAgsFxEHqiqWeCdwADwVEwm2h5Mu4GvwmRigM1GawypeOVm9g/+eT9gVjKLwEM39tHbluDIeJZsvlBTC8d1f/x7pzlRtx8c5d6DoyRiEU/RVBrDAXiu42poVusGJsu7+N00c8VVDv0jaTK5AjsHxj2Ls5gun4UzE64SA6a0u3ZxLZxsmaSBXEEp6OzzoCMVZ1VXirv2D8+4H5TPUmuJT3WpuRZOOZeam2l5654h70bPtZpWdac8qybuFMFtT8amWDilfqtoRLz4jOnymfViSX5a4lHGsvkZs/vqSVVXChFZAqCqdwG/wLQXWOlkon0E2IApyAlmsec1ItJZYihLHUlVmDRweDTDFbfs47wTlpOMRThxVRddrXGv3MjAWKbmFg7Av+8fBEw9tG37htnQ1+pV7F3ZbfapROGcuLqLtz9+My972FE1kbccInKMiGwRkeTse9cWt9rAXC0cPy2JKG2JKAdH0tx/eIx8Qael67pMKpyZf5/OlphnnZS6o49FZrZw3Jpk5RSfn2OXd3Dn/kpcapNZaqrKeDZPKm6UgudSa4n7YjilXWquhZMrKDfvPjJl7LZkzMuOjDlzujMVZ2gi6ymccudXWzLKaDrHWCZPvqClLZxEFNXJygWNZt4KR0Q+DVwmIsc5m64FTgUeJyJHOUrnLUDSieXkgC87a3EsDSQVj1YUw/n5v3eTyRd443nH8bUXbuEDF5wIQG/bZJl31eC6fRYzqXCMhVNQuHb7ITYumQw6T7rUKlN6r3z40V6gth6IyJOAnwEfB77lO18agutSq3aBq0lZz3jVG0ot5gS8MiuzzRER8RIHSiU0TGaplZ63P71+Fx3JGI8+fvbE1+OWt3NP/8iMKdaFgjKWMUkI2bySzhWmrImZkhY9i0vt4HDaU8huHGeKwnGSI+LOd+S2zCiVNOCnNRFjLJP3LKuSMZyAq8NXSzVXigFgCfBaETnWKbb5K+AU4C0i8jTg0wCqmlPD3FZHWWpCqsLc/D/cvp9NyzvYvKKThx271FuR39NmJrZbFLAWCz9hUuH4+39kcgWO8t3Fru5uoTMV85IHwoSInIlRNC9U1Udgzpm3NVKm5Z6FU91vZhY7pr2YWjkLx0saqMAKdl11pWI4rkU2kp4+b8cyOS6/ZR9PfNDKiqztY5d1kM4VvGoKpXDXt7ixPlcBuBfwdl9atCtbcdLA72/bz6GRNIdG02xa3sGKzhR3OK48113XloixttfcNMX9Fs54lrESadF+WhPGwhkaz3nvK8YtixOWTLVqFM6VmF42EeC/RaQXuBv4DvBX4EnAv1X11WDL1YQJkxY9s4Uzkc2z9b4BzjpmybTX+hwLx21AVYvSNmAuMm2JKLmCTlEo/gB1Kh7l6rc+kqefuqYmMgTAx1T1387//43pYjura01EXiEiW0Vka39/f2DC9LYleNqDV/Ow45ZWNY67Rmp7/yh9bYlp/W1cvKSBCqxgN926VAzHbcR2qMRC4F/8ew9jmTxPPWV1RbIfu9xJHJghjuMqBDfVeySdm9Lu+ZhlHbTEo6zpaSEaETqSsSkxnJ2Hx3j5d7by7Wvu4+BIhr72BN2tcU8pudUuohHx0r/dRZ+uhePPiitFayJaZOFMV9SuvGFZizPnK4WIuEcfBY5T1ddginK6JWuuc3rcvFJV3+m8x5arCRGp2OwxnOvvHyCdK3Dm0X3TXnNXf9fawgGz7gPMOhpX6RT76bta4l5MJ2T8A+NOc8+bJLAe6HS2Tf9yHVT1ElXdoqpbli6tTjn4ERE+9cyTvbTa+bKkPcmh0Qy37j3iVSMoRdc8LJxS7j43bnioqF3FgeEJPnb57WxZ31PxMR273Mg7U6aa6/JyLZyRiRyjPoVz6voetn3gcZ7MnS1xz9IA+ItTa/C2vcMMjGVY0p50FIlRDqOZnGfJuRZOzK9w0llPOZWLt7UlY4xlcp4rr5SFE3R1+GqpWOGIyPEi8lzg9SKSVNWrAdcmTQIFYB+w0lEwWed9NvU5ZFTiUvv7PYeICDxk4/ST2K2ZtcexcGq18BMmYw6rulq8VGh/DCfMqGreF7MUYBDTxbZfRJ4HfFBEWhomYBWYUjQZ7tg3zImru8ru51o4lcT5XCum1AXWqx5eVIjyA7/exng2z8cufFDFbc7bkzGWtCemFCAtxnXduRbOcDrLeCZX1trwKxOAv9xpFM7WHYdRdQrIpuK+VOu8d5xuDCfhxKk6UsYS6h9Jk4hGylqP0y2cxRXDeQYm82xcVdOOi6xLRG4Cjgc2YhIDnuJXMNayCR+VLPz8290HedCa7pJ3TbFohO7WOHvrYeE4MYdV3S2cvLabtb0tC7IMjRPHHAF2ishHgDcCX1LV8NSOnwPu4s9sXnngDArnkZuW81+PPIbjlpe3grwxHaXSWiK+1JqI0ZqIcthn4ew7MsFlN+3hxWdt8G5GKmVpR4r+GYp4uhaOG0d0Yzjlki3czDIwiQ3X3H0IkcnCpn3tSS/dGUyPHVfhuC4118LpbDH7HRhKs7QjSbloRFsixmjGH8Mp71ILSwynolQVp1vnGcD7gO0icjxGufwBWKKq5zv7vcRaM+EnFY8ykTO5+aUm84HhCW7cdYRXn3t02TF6WxNeDKemFo5zwq/qTnH+yat55cM31uyzaolzgxYHHub8fZSznGBBsrR9UunPpHC6WuO88bxNZV+fMqZbdqfMRb3Xt+AY4Mdbd1LQyfVVc2FpR7JkJXIXVzGs9LnU/DGcYjpbYt75cMPOQYbTOc47YTm/u20/gOdS88rkpPNeNl5LIspLzz6KR25eBhgLJ19Qdhwa9b6TUrQmo4yl855LrWMGl9pCi+EUgG6gF1iGWXPzBUwTtX8CiEjKVTY2QSDcpOImNz9TJsX0/27YQ76gnH9y+WZkvW0JrwdIrdKiYVLhrO5uIRGLlDypFgK+LM0PAI9fyMoGJuMtHakY6wKqsu26SstVgehrn6weXigo//uvnZx1TN+07qGVsLR9qsK5Yecg2/ZOZkNOi+Gkc9O6b/rp8Fk4N+0ya22ec/qkIuxrT9Ce8lk46dwU1+G7n3SCl6DjLiS9+8CIV927FK2uhTORNXXrSpyHrgswLC61iiwcVR0WkfcAnwS2YYpw/hVYAaxy9pnw7W/daCHG64mTKUxxh339r/dyYGiCP9/Zz0lrujhmWXk3SF97gnxBOWFlp5cuXQseuKaLjmTMC/QuAr69GM4PV+GcuKqrrMtnrjxwTRfXvv1RZRXOkrZJq/rWPUPsHhznTefNb1nT0o4k/SNpz8p/x89uZvfgOJf919ms6WmdlhZtFE5uBpdazHNtHRpJE43IlCSGJe1JOlNxMvkC6Vx+StJAMR2+haRu7btStCbMerqBsdJVBgBf9ekFpHAAVPVKETnb+X9YRE4EXo9RQJYFhJvGPJHL04WZ3NfcfZAP/Po2b5/3PeUBM47xinM28tCNfTz39PUVrfKfL6dt6OXm9z22ZuPXm8WgbGDS/fWgNeXdafNhphp3fe0JbtljrIftB02G2UwJCzOxtCNJNm9KwnS3JugfSXNkPMurv38933vZ6V5wv6c1QSIWMWnK2fwMSQNxhieyqCoDYxl6WhO0J2Os7m7hwPDEtCKfIxPlFY4/FrOso/z34boe9w9NlIy1wgKN4bio6jCAiKzEuAb2AL8VkbiblWYJP27/GtfMnsjmefOPb2Tjkjb+61HH8qsb98zoTgM4dX3vlJ4yluaiLRnjK88/ta516fqczDhV9dpkz9ed57qq+ofTdLXEGRjNcNKaLm7dM8TTvnQNJ67qJBoRkrEIHckYA6MZsnmltWxb7hgFNS0MDo1k6HUWRx+9rJ18wVhR3uLVCdOPp2MWC8cvZync5Ir7Do2ysrN0smPYYjhzrm/htBPoBbaq6odEZB0mCGoVzgJhss20ieH8+c5+9hyZ4FsvPo1zNy3jggoX0Fmam8eduKKun9fXliCbV4Ymctx7cJRVXS3zruPnWmgHhtMs60yRKyhPPmkVb3v88bzyu1v5xYERulriiJjmfG5VgnIWjldPbTzLwFjGW6v22kce47kBXUUyMJYhnStUZOEs75zdwtl5eJzHHF/6t0jGIoiEJ4YzZ1+I01jtVlX9kLNpt6qWrxFhCR2eS82ZhFfcso/u1njJqgIWS1hw1+IcGklz38HRigp1lmOpz8IZcDLfeloTPPToPr7y/FOJRiYtknW9rV5JmnIxHFeZDE/kODQ6qXBO29DLU04y3gJ3vP1Oss1sMRy/nKXwK79T1nWX3EdEaA1Ri4Kqne+qGo4jsVSMe9KMpnNkcgWu3LafRx+/3CutYbGEEbek0sGRDNsPjrJhHtlpLn6F46Za9zoK7cxjlvC5Z5/Cy52q4ut6W72GgzOlRYNpUTDgUzh+3BiOu+C01LoZ/37AjEkD/vTxcgoHwtX1s7qSsZYFiddmd2iCa7cfYmgix+MeUF/3iMUyV1wL564DwwxP5MoWDK2EjmSMVDxC/8ikhdPbOqkknvigld7//jjRbC61gdEMg+PZKWN5n+kokjsda2llV+m4i1tjTVU9JVtyPyeGs7Qj6fWFKkUqRBaOVThNiDvR9x6Z4O4DI8QiwtnHWneaJdy4qdjX3WdK/FejcETEW/zpWi+lrBKYqnDKWThudt1te4dQLT2W6ypze/GUy8gTETpSpj/QTDUCXQvnlLXdM6amt1oLx9JIWhJRelrj7Bkc58h4ljU98w++Wiz1osexGv7hNFurRuGAWfx5YHiCw2MzK5z1fX6FU/qSuawjSUs8yvVOs8BS5ZfcGM5dnoVTPiGgIxUrW0PNG8+xmE5ZN3OmYMscOvzWGqtwmpSVXS3sPTLBoZG013HQYgkziViE45a3c+d+Y5Wv6amu7unSjiT3Hhzl8GiGZCxS1npxa51BeQtHRFjf18oNTrPAUq6wRCxCMhZhNJOnMxUrmzQApljtshky1MBU3/ifpz+Ix86SLWhdapaGs7Irxe7BcfYPTfCEB66c/Q0WSwj4v/88m9/cvBfVyWKX82VZR4pr7jnEoZEMfW2Jsm6plkSUZR1JDgynyyocMBbX7fuM9eI2KSymIxUjPZLxOtWW48vPP9XrcjoTzzxt7az7tCSintuw0ViF06Ss7E7xt3sOMpEtBFYLy2KpNal4lKc9OJhme8et6GB4Isete47MWoF8fV8rB4bTZZMGzD6TLr5ywf6OVJyDI5kZKypAeffefGhNRNk9EA4Lx+bBNikru1q8hZ9W4ViaEbfK9e37hme9wLtu53IxHICjlkyeR+UsHDeOUy5DrRakQhTDsQqnSVnVPXmHZWM4lmZk84oOYk4W2GwK54SVnXS1xL1imKVwLZz2ZKxsjyg3NXrVLBZOkLRU0HCxXliXWpOywld7aV2fVTiW5iMVj3Lc8g5u2zs0q8J54ZkbuOCU1TOmKbtZc+WsG5i0cGZzqQWJ2xk0DFgLp0lxLZzu1njZSrMWy2LHdauVWqjpJx6NeOuAyuGmRvfOsFjTXYszW9JAkLTEo+TyShgKlVuF06S4d1g2fmNpZk502iv0tlcfpBcRNq3oYM0MysR1qdXTwnn9o4/jzg89PrC+RdUQKpeaiERtbbb6kIxFWdqRtArH0tSc6iyanKk0zFy4+KJTZ6xJaCpQz7zoM2giM7gB601oFI6IXAKoiCSAdwL9tsdObfnss09mxSyLyyyWxcwJqzr5/RvO4Zhl7YGMN1M7AYDnnb6OB67umjHbbTETCpeaiLwDWAf8NxAF3gs8SkRm/PVE5BUislVEtvb399de0EXGmUcvYePSYE40i2Whcuzyjrq5m5Z1pnj0Ccvr8llhpOEKR8wvvRz4haruU9UXAHcC5wNbfPtMQ1UvUdUtqrpl6dKldZPZYpkrImKL1VmanoYrHKfH+xXAaSKy2dn2CWAf8BrfPhbLgkNEjgPTN8oqHUuz0zCFIyIXici5jpK5ChjHuNGOAlDV9wGrReS8RslosVSDiDwJuEFEfgBW6VgsDVE4IvJ14FXAecDvgFOB7wInA+eLyFnOrhNArhEyWizVICJtwH8CrwcyIvI9qFzp2PikZTFSd4UjIicAm4CHqeo7MCfkN4AW4ONAK/B5EfkdMKqqf6i3jBZLtajqKPAS4AfAm4GUX+lU8H4bn7QsOhph4dwH3AE8WERiqvoz4G3AD4FOVf0w8CTgHar6VAARaXisyWKZK6q6R1VHVPUg8EqgxVU6IvJgN2ZpsTQLdbuQi8gyERFVHQP6gYsABVDVXwDvAt4iIm3OibrVeZ+oaqFeclostUBVD2GUTlZEbgcuBUYaK5XFUl/qonBE5GKMBfNpEXkZZmHnRuAzItLh7HYZkAWmdAqyGWqWxYJj6dwEdANPU9VdjZXIYqkvUuvruYi8CXgy8GzgFEyywG0Yi+YHwCBwL3AmcERVL5rn5/QDO3yblgAH5y34dIIer5ZjN6ustR5rvarOO6AiIj3Aj4A3qepNc3hfLed2LedK0OM3s6y1lK2qeT0X6qFwngUsU9XPi0gM6MFkpF0LvA94CnA00K6q73feI9VaNiKyVVW3VCd97car5djNKmtYxyoaN6WqE1WOEfrjrMX4zSxrmGWbC/Uo6DMKvEFEfqWq9wH9IvJy4BPAaar6S//OIhKxMRvLYqVaZWOxLGRqHsNR1V8DXwN+JiIbnW07gb2Y+mnF+1tlY7FYLIuQmiocN53ZSXX+MXCliJwmInHMWpw1Nfz4S0I+Xi3HblZZwzpW0Cyk47Syhm+8hs3tQGM4IvJe4EpV/WuZ11+LqS4QBQZV9bmBfbjFYrFYQk1gCkdEvgCsUNULi7ZHnXIebao66mTqRJ0UURuzsVgsliYhEJeaiHwZeIyrbERkva8IZ15ElgAfF5HNqjoADDj72UWdFovF0iQEFcP5E5AWkVNF5PmYJIGfiMhXRWS5Y81MAB+DyVpSYV3U6cSYghrr4c53UhOCLPsjImeIyOOCGq/E+AtG1moQkVNE5LRGy1FMkPPaGa9mczvocla1nC8LSdZqqXZuV/VFiUjEWVdwKaZb5x+A92CKFj4Ss+bmgwCq+kbgb461E1pE5DHAW10LrcqxHgt8GrOw1b89kPaCIvJI4LmOm7LasR4LfJmixWXNIKuInCMiZwdx4XAuFN/E3GBVLVtQBDmvnfFqNreDnCvOeDWb22GWNch57YxX/dxW1Xk9gC8CFwM/BzY62x4LnOTbZ5OzT3K+n1PPB3A6przOzzEVfo+qYqxzMLWyHug878Asbg1K1rOAAvB74FlATxVjnYuZ4Kc4z1tx4nvOc1mssgIPd2T7O/BQIFKFbI8EdmPWl1E876sZu8rvP7B57YxXs7kd5FypxXxZKLIGOa+d8QKZ2/Na+Cki3wA6gbdjen48DNiuqlcUabv3A3tUNT2fz2kACrwA2ANcADxTRH6kqvfCnCsgTGC6lh4lIndjijWOi0gLprTJtvlWVPBVbHiWI/P5QERELlcTI6tYVuf3WgJsB+Ii0g58y5G1HXiOqk4sRllFJAEcAzwdWImxzj8oIn/XOcYWHXfVKcDNwD4R6cbUCjwCtKnqy1S1MN/vsUqCnNdQo7kd5Fxx96VGczvMsgY5r53xgpvb89B0ZwOf9z2/xHm8E9jkbFuCmYTfnI92buQDaHH+Pgr4FEapHjWfYwC2YIo1DmPaZbdh3BC/C0DOlPNjAzwP+I7zt3ceY7VhSgxdhbnDegOwHvgp8NvFLKszV9ud/98M/AZzAxWt8P3+O9B1mFqBP8TcDb4Vc3f5B+DSxTKvazm3g5wrtZ7bYZa12nldq7k957RoMZ0MC6o6LiJPBD4MfNQR6K3AgzHlbM5R1Z867wlt6rOYFtaPBbYB16vq9b7XHgM8Hrgd88P3qup/zDDWJmC/qg76tp2BMUM/79v2G+BlqrpnjrI+HKPwrwfuUtW7fa9dBDwGU6fuFIx5//YZxlqvqjt8z9swfYj6VPVLzrYYZrJfpKpDi0VW5zd5EPAPjAXe73vt/wGPAP4Lc4L2qOqnZhhrparu9T1fBzwHGPbJtgr4EOY3n7X5WhAEOa+d99Rsbgc5V5z31Gxuh1nWIOe1857g5/YctN3xGO39Bia1+slAt2+fLwJPKnpfQ/zWFR7TOcCdzjG9A2POFst/AnA1sBN48AxjPQnjM/0osGSGO4XnAP9kjv5ezES+x/lxP4W5szi3xD43OrKeMsNYT3FkfXfR9iS+OyCMG+avQMdikRV4IqYJ4Jcxd6TfBLYU7fMiZ58dwIkzjHW+I9ubi7Z3ATHf85djWqm3LrR5Xeu5HeRcqfXcDrOsQc7rWs7tuUzi9ziCvnqGfS4HLgzipKnHw/khP+l7/mTMGqEn+rY9FWOxnTDDOF3AZzCdSy/FVMHuK9onimk6dyvwgHnI+jrgLc7/ncDznbHOLZJ1eBZZlwHfxrhUrgPeXmKfiCPrLYtNVuC9wPOc/zdhYpCXAaf69rkAODKLbGswboq3AruA/+d7zX8RfiHG9VR2rLDO63rM7aDmSj3mdphlDWpe13puV/pFdzkCvASTSbEZOAN4iPOaYPp8XFzrkynIB8at8M2ibU/CtMA+2Xl+AnB8BWO5GTvrnB/6vcBS3+sp5/vbPE9ZXwF8u2jb84ErmMwSfEwFk0mAM53/j8X0Jnp70T7dzokw63EvNFkxLuCv+p4vcU7Oi53/U5g7wdlO8AjwWN8c6fefmM72FcDn5nJChm1e13puBzVX6jG3wyxrUPO61nO70i+6A7gGE3x6pjNxL8No6Pc62z/rF3iuP2YjHkAC+AvwlaLt7wOeVcW47on5Puf5U4HjApD1RuATvm29wBeAh7mTeJYxpr3um+zvcJ4/GlhVzW8YZlmdk/gv+FwFwInA/7q/EbMEVmF6qirG5eydmJhU5E4gXs857fv+A5/XzhiBzu0g5kot58tCkTWIeV0sWy3m9ly+7Ec7X/b/YjTbMzAm5ruAhG+/haJsIs7fFueHvtj3Bf8P8P55jhtz/q5zvqsrMX7TY6uQNer8XYXxu3/K99rFwOurlPVYjFl/hfNdrF+Msvp+8zMwa1Le6nvt+zguiXnIFnf+Ho9xQfwW2AqsrMXcrfAYA53XRb9BIHO7VnMlqPmyUGSt1bx23h/o3J7rh3fgBK4w2vMaFmbqs3sCJp2/KSYttm85P3al7gbx/y167d2Y9MY5x0FKjOVOyuWYLJTvYgKXdzLHO8wysr7PkXXGYGKF30XVss7yvc5Z1uJxgNMwQd9vYNwW91DhgshZZHu/I9sDazmHZ5Gr6nldwXEGMreDnNdBzpcy30MgsgY5t4Oc1xXIVvXcntPCT1UdBpMuB3wAs5DsMhGJq2pWHanChog8DPND7Af+qKp7xFSxTjtpjsdiMkbOxPgmP6Sqd81xrLyInIkxrT8mIiswd0OPVtVb5yDrClXdV7Qtoqo5ETndke8szKKuTozf9s45jCWqqiKyBVMV4usicgwmLvcoVb1lDrKejrnzuRe4WVUPO9/FfGQtN1Z+PrI6v9PJmGyhv6rqQd94J2IW7T0FeDVm4d4F6iyErHCsiJrFbg/CnNC/FJGTMGsTHqmqN1f6Pc6XIOf1LONVPbeDnNczjBfI3A5yXs8y3pzndpDzeobxaje356qhMAGlBwDvdJ6vo07pnvN5YIKlN2LcCV/ApG67C6IejDFhzw9wLH8mUMscZb0Ak4r4ohKvPRS4AXhcgGM9ynkuQOc8vtebMYVavwG8ick7wLnKWslYFcuKCZrfiCkW+0Pgub7XHul81rkVylbJWGf5zo0llYwbpnld67kd5Lyu9dwOcl4HPbeDnNeNmttBTPyKV67W+wEcjfG3uvV/HozxPff5JsMj3B87wLHmHMfC3DH+FGOi34pZ5OV//XnAEyqUdS5jzfn3w9xw3MBkzaenAr9g0pUzF1nnMlYlQc8HYupHuRlA78akd67BuISfBTyjQtnmMlbdzoMg53Wt53aQ87rWczvIeR303A5yXjdybtflBGnUw/ninuc/STDp3U8u2q+SC1lgY5UZvxVjroJZEby9+GSag6yBjVVm/D5Miqh/cdrvmb7QrBJZAxvL2a8HZ+0BJh30HuDXmDv2H+Ck81Z4UgY2VljndS3Gq+VcrOXcrsFcDPI8CXQuNmpu1+0kadSDSfPV/ftt4PHO/2czBzMxyLF8Y67AdEot3n6uczK9wHl+zmzjBznWDOOvLNrm3q39FjjD+f9koKteY5U7dswd5Qud/1cDX6foIlrrsWr1CHou1mC8QOdiLed2jeZikOdJYHOx0XO7ISdLLR8Yv+TnfM+jRX8/hskjvwDjRlhdj7HKjP90533XYszZxxa9/ghMZtEPMKb5mnqMNc/xvwFsBJ7mnFTL6jFWifHeUjyeb7+vUeJuuFZjhXVe13puBz0Xazm3azwXgzxPqp6LYZjbdTlZ6vXAZOPsweSJf8+33e8qeB/G9/svZq6TFdhYZcbvA/6NKfJ3Iqbu1VcoWpiHCeD2M0MqYpBjzXd8jE/9jxV8r4GNNct4zyna7+nOfhvrMVZY53Wt53bQc7GWc7uOczHI82ReczEsc3te/XBCTBum8sG3ge+JyA9U9blqUvziqpoFMpgv/3z1VXqt8ViliAJDwL2qOigihzCLa88VkX5V/YOIHI+5G3q0zpyKGORYcx3/kKpeiVlxfSqmEORM30WQY8003jkist859ldgTrALVXV7ncYKkqDnYi3ndtBzsZZzu15zMcjzZL5zMRRze87tCcKOiHSq6pCI9GI0eF5Vn+O8lsKcbD2VnERBjlVm/M86Y7xOVUedUt8vADKq+ikRacX4fgfqOdYcx8+q6ied0uXtqnpbPceaZTz32FdgUvdnPYmCHCtIgp6LtZzbQc/FWs7tOs7FIM+Tec3FUMxtrYNLoFEPTPbFjzEn1Iswfun5ZmYFOZZbiuI4jIn9fiZbPpwC/Jmiirz1GKuK8ZfWe6w5jFdRADnIsRbSvA5yvKDnYi3ndoPmYpDnyVySnUIztyMsYlT1oKo+AxNU/DTwfZ1nA6wgxhIx7bd1shndPcDPMHWvviIiSzCTIofpQV+XsQIYf8YW4kGONY/xMvUaq14EOa+DGC/ouVjLud3guRjkeTLrXAzl3K6HVqvlg6k57q4mX8lkzbcLMGmTlZTlDmysonG7KarGwGT66RpMl75PYrJW/sHMjd4CG2uhyRpm2cI8r2s1t8P8+y4kWcMsW+Dzul4fFKjQcB6+3hFMza55OEaLu/3anwBsqsdYZcZ/MmZB1Z+B52IW2bmxs0dgXBnrnOddOKZurcdaaLKGWbYwzutaz+0w/74LSdYwy1aTOV7PDwtEYLOw6wCmH7u/L0UUkwHyD+Bp9R6rzPiPwXTr24Jp5/Ab4HTntb45yhrYWAtN1jDLFsZ5Xeu5HebfdyHJGmbZajbPG/nh85xAz8H00e4DrsLXStd5faXzN8LstbICG6vE2FHMWoYX+ba9rejk98av11gLTdYwyxbWeV3LuR3m33chyRpm2Wo6zxv1wVUJPVnnZwOmCdRnfK91N2qsEmP3Oie8OI8XAN/xvZ5qxFgLTdYwyxbkI+i5WKu5HebfdyHJGmbZavVYEAs/ReQsTNOjlKr+QFX7RURU9T5nsdIlIvIeTHmLo0XkU2oWr9V0rFnGj6nqj5xtbp+OOzC+c0TkOUBcRMpmBAU51kKTNcyyBUXQc7GWczvMv+9CkjXMstWFRmu82R6YYOatwHucv/9TYp8EsBsYYOYSMIGNNZ/xMb7Vr2LWOmwDNtdjrIUma5hlC+O8rvXcDvPvu5BkDbNs9Xo09MMrmDzHYuo9ne083wD8EliKz+8MXIjprV42pTPIseYxfgRj4p4EDGNac880MQMba6HJGmbZwjivaz23w/z7LiRZwyxbPR8NF6CCL/WZzv9RjH/y7+4J455MGA0+Y6/2IMeaz/jO9hZM5shsd6uBjbXQZA2zbGGc17We22H+fReSrGGWrZ6PhgtQ5stcB8SBuG+be9J8j8m1AyfXc6wgxsfpi1HrsRaarGGWLYzzutZzO8y/70KSNcyyNeIRutI2IvJEjFb+EqaS7WbnJTfBoRdoE5HnAz8WkWVuCYdajhXA+D8RkaWqWrK8RZBjLTRZwyxbUAQ9F2s5t8P8+y4kWcMsW8NotMbza2lgLXAzpovfcuBNwF6mmonfAH4C/JUyvuggx7Ky1k7WMMsWxnld6+O0soZzLoZ1bs/rfGi0AEVfbBS4BNPm1DUTX4fJrNnkPP8kcDezB9UCG8vKWjtZwyxbGOd1rY/TyhrOuRjWuT3nc6HRAjhf1DHAaZjA16XAW4pefwumWVQU0xp3pq6NgY1lZa2drGGWLYzzutbHaWUN51wM69ye9znRcAHgScBNmGJzXwCegknd9Bcd3AB8tZ5jWVlrJ2uYZQvjvK71cVpZwzkXwzq3qzovGvrhprf6NuAU5/klwAeBVcD9wLswGv5FmJzz3nqMZWWtnaxhli2M87rWx2llDedcDOvcrvrcaOiHmy/1Rb7nS4HLnP83YoJgXwKuY/Y898DGsrLWTtYwyxbGeV3r47SyhnMuhnVuV31uNPTDjd+x0/f/GuDfTFY1XY9J+euq51hW1trJGmbZwjiva32cVtZwzsWwzu1qHw1dh6OqeVUdcp4KMAgcVtW9Ti75OzALnI7Ucywra+1kDbNsQRHm78zKWpvxwixbmHDT60KDiHwLk19+HsakvDkMY9V6/GaWNcyyBUWYv7Naj92ssoZZtkYRGoXjrIKOYwJlceBRqnpXo8eystZO1jDLFhRh/s6srLUZL8yyNZrQKBwXEXkR8C9VvTVMY9V6/GaWNcyyBUWYv7Naj92ssoZZtkYRRoUjGpBQQY5V6/GbWdYwyxYUYf7Oaj12s8oaZtkaRegUjsVisVgWJ6GrFm2xWCyWxYlVOBaLxWKpC1bhWCwWi6UuWIVjsVgslrpgFY7FYrFY6oJVOBaLxWKpC1bhWCwWi6Uu/H8CnEEXH7iUAAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cg = pycoin.CoinGeckoAPI()\n",
    "Chart_Analysis(cg,100,'bitcoin',['Price','Total Volumes'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "Chart_Analysis(cg,100,'bitcoin',['Price','Total Volumes','Market Cap'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.5"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": false,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  },
  "varInspector": {
   "cols": {
    "lenName": 16,
    "lenType": 16,
    "lenVar": 40
   },
   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
    },
    "r": {
     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
    "instance",
    "_Feature"
   ],
   "window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}