main.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Automação de preenchimento de tabelas e geração de gráficos\n",
    "\n",
    "O script faz o scraping de dados sobre inflação, preço do petróleo e diesel, gerando gráficos e preenchendo tabelas utilizadas no Boletim Econômico e Regulatório da AGEPAR.\n",
    "\n",
    "> Autor: Matheus Brasil"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Navegação <a id=\"nav\"></a>\n",
    "\n",
    "O notebook está estrutura da seguinte e forma e você pode utilizar os links abaixos para navegação.  \n",
    "\n",
    "- [Pacotes](#pacotes)\n",
    "- [Coleta e Tratamento de Dados](#coleta-tratamento)\n",
    "    - [IPCA](#coleta-tratamento-ipca)\n",
    "        - [Nacional](#coleta-tratamento-ipca-nacional)\n",
    "        - [Regiões](#coleta-tratamento-ipca-regioes)\n",
    "        - [Curitiba](#coleta-tratamento-ipca-curitiba)\n",
    "    - [INPC](#tratamento-inpc)\n",
    "        - [Nacional](#coleta-tratamento-inpc-nacional)\n",
    "        - [Regiões](#coleta-tratamento-inpc-regioes)\n",
    "        - [Curitiba](#coleta-tratamento-inpc-curitiba)\n",
    "    - [Preços Monitorados](#coleta-tratamento-monitorados)\n",
    "    - [IGP-DI](#coleta-tratamento-igpdi)\n",
    "    - [IPG-M](#coleta-tratamento-igpm)\n",
    "    - [Brent](#coleta-tratamento-brent)\n",
    "    - [Diesel](#coleta-tratamento-diesel)\n",
    "- [Gráficos e Tabelas](#graficos)\n",
    "    - [IPCA](#graficos-ipca)\n",
    "        - [Nacional](#graficos-ipca-nacional)\n",
    "        - [Regiões](#graficos-ipca-regioes)\n",
    "        - [Curitiba](#graficos-ipca-curitiba)\n",
    "    - [INPC](#graficos-inpc)\n",
    "        - [Nacional](#graficos-inpc-nacional)\n",
    "        - [Regiões](#graficos-inpc-regioes)\n",
    "        - [Curitiba](#graficos-inpc-curitiba)\n",
    "    - [Preços Monitorados](#graficos-monitorados)\n",
    "    - [IGP-DI](#graficos-igpdi)\n",
    "    - [IGP-M](#graficos-igpm)\n",
    "    - [Brent](#graficos-brent)\n",
    "    - [Diesel-S10](#graficos-diesel)\n",
    "        - [Capitais](#graficos-diesel-capitais)\n",
    "        - [Curitiba](#graficos-diesel-curitiba)\n",
    "        - [Regiões](#graficos-diesel-regioes)\n",
    "\n",
    "_Para voltar ao início, clique em voltar abaixo do título de cada seção._"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pacotes <a id=\"Pacotes\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd             # manipulação dos dados tabulares e scraping\n",
    "import numpy as np              # manipulação séries temporais\n",
    "import ssl                      # conexão de segurança http\n",
    "import datetime as dt           # manipulação de objetos com data\n",
    "import urllib                   # pacote para requerimento de download\n",
    "import matplotlib.pyplot as plt # pacote para criar gráficos\n",
    "import openpyxl as oxl          # pacote para manipulação de arquivos .xlsx (preenchimento)\n",
    "import requests                 # pacote para requisitar informações por API\n",
    "from dateutil.relativedelta import relativedelta # pacote para realizar operações com datas\n",
    "from bs4 import BeautifulSoup as BS # pacote para scraping\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Coleta e tratamento dos dados <a id=\"coleta-tratamento\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## IPCA <a id=\"coleta-tratamento-ipca\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Nacional <a id=\"coleta-tratamento-ipca-nacional\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'requests' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32mc:\\Users\\est.matheus.brasil\\Documents\\BOLETIM\\Automação boletim\\scripts\\main.ipynb Cell 8\u001b[0m in \u001b[0;36m<cell line: 2>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      <a href='vscode-notebook-cell:/c%3A/Users/est.matheus.brasil/Documents/BOLETIM/Automa%C3%A7%C3%A3o%20boletim/scripts/main.ipynb#X10sZmlsZQ%3D%3D?line=0'>1</a>\u001b[0m \u001b[39m#Requisição da API do SIDRA, e transformação em DataFrame\u001b[39;00m\n\u001b[1;32m----> <a href='vscode-notebook-cell:/c%3A/Users/est.matheus.brasil/Documents/BOLETIM/Automa%C3%A7%C3%A3o%20boletim/scripts/main.ipynb#X10sZmlsZQ%3D%3D?line=1'>2</a>\u001b[0m ipca_brasil \u001b[39m=\u001b[39m requests\u001b[39m.\u001b[39mget(\u001b[39m'\u001b[39m\u001b[39mhttps://apisidra.ibge.gov.br/values/t/7060/n1/all/v/all/p/last12/c315/7169/d/v63\u001b[39m\u001b[39m%\u001b[39m\u001b[39m202\u001b[39m\u001b[39m'\u001b[39m)\n\u001b[0;32m      <a href='vscode-notebook-cell:/c%3A/Users/est.matheus.brasil/Documents/BOLETIM/Automa%C3%A7%C3%A3o%20boletim/scripts/main.ipynb#X10sZmlsZQ%3D%3D?line=2'>3</a>\u001b[0m ipca_brasil \u001b[39m=\u001b[39m ipca_brasil\u001b[39m.\u001b[39mjson()\n\u001b[0;32m      <a href='vscode-notebook-cell:/c%3A/Users/est.matheus.brasil/Documents/BOLETIM/Automa%C3%A7%C3%A3o%20boletim/scripts/main.ipynb#X10sZmlsZQ%3D%3D?line=3'>4</a>\u001b[0m ipca_brasil \u001b[39m=\u001b[39m pd\u001b[39m.\u001b[39mDataFrame(ipca_brasil)\n",
      "\u001b[1;31mNameError\u001b[0m: name 'requests' is not defined"
     ]
    }
   ],
   "source": [
    "#Requisição da API do SIDRA, e transformação em DataFrame\n",
    "ipca_brasil = requests.get('https://apisidra.ibge.gov.br/values/t/7060/n1/all/v/all/p/last12/c315/7169/d/v63%202')\n",
    "ipca_brasil = ipca_brasil.json()\n",
    "ipca_brasil = pd.DataFrame(ipca_brasil)\n",
    "\n",
    "#Tratamento\n",
    "ipca_brasil.columns = ipca_brasil.iloc[0] \n",
    "ipca_brasil = ipca_brasil[1:]\n",
    "ipca_brasil['Valor'] = ipca_brasil['Valor'].astype(float)\n",
    "ipca_brasil['Mês (Código)'] = pd.to_datetime(ipca_brasil['Mês (Código)'], format='%Y%m')\n",
    "\n",
    "#Transformação em tabela dinâmica para facilitar a visualização e manipulação\n",
    "ipca_brasil = pd.crosstab(ipca_brasil['Mês (Código)'], ipca_brasil['Variável'], ipca_brasil['Valor'], aggfunc='sum')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Regiões <a id=\"coleta-tratamento-ipca-regioes\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Criação de variáveis tipo date para facilitar a manipulação das séries temporais\n",
    "data_referencia = dt.datetime.now()\n",
    "data_atual = data_referencia - relativedelta(months=1)\n",
    "data_anterior = data_referencia - relativedelta(months=2)\n",
    "data_atual = data_atual.strftime('%Y/%m')\n",
    "data_anterior = data_anterior.strftime('%Y/%m')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Pesos de cada região do IPCA para inserir na visualização.\n",
    "regioes = ['Belém','Fortaleza', 'Recife', 'Salvador', 'Belo Horizonte', 'Grande Vitória', 'Rio de Janeiro', 'São Paulo', 'Curitiba', 'Porto Alegre', 'Rio Branco', 'São Luís', 'Aracaju', 'Campo Grande', 'Goiânia', 'Brasília']\n",
    "pesos_ipca = [3.94, 3.23, 3.92, 5.99, 9.96, 1.86, 9.46, 32.28, 8.09, 8.61, 0.51, 1.62, 1.03, 1.57, 4.17, 4.06]\n",
    "pesos_regioes_ipca = pd.DataFrame({'Região':regioes, 'Peso':pesos_ipca})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Requisição do IPCA dos últimos 2 meses para regiões e capitais através da API do SIDRA e transformação em DataFrame\n",
    "ipca_regioes = requests.get('https://apisidra.ibge.gov.br/values/t/7060/n1/all/n7/all/n6/all/v/all/p/last2/c315/7169/d/v63%202')\n",
    "ipca_regioes = ipca_regioes.json()\n",
    "ipca_regioes = pd.DataFrame(ipca_regioes)\n",
    "\n",
    "#Tratamento\n",
    "ipca_regioes.columns = ipca_regioes.iloc[0] \n",
    "ipca_regioes = ipca_regioes[1:]\n",
    "ipca_regioes['Valor'] = ipca_regioes['Valor'].astype(float)\n",
    "ipca_regioes['Mês (Código)'] = pd.to_datetime(ipca_regioes['Mês (Código)'], format='%Y%m')\n",
    "\n",
    "#Criação de dataframe com a variação do IPCA do mês anterior para cada região\n",
    "ipca_regioes_anterior = ipca_regioes[\n",
    "    (ipca_regioes['Nível Territorial'].isin(['Município', 'Região Metropolitana'])) \\\n",
    "        & (ipca_regioes['Mês (Código)']==data_anterior) \\\n",
    "            & (ipca_regioes['Variável']=='IPCA - Variação mensal')][\n",
    "                ['Brasil, Região Metropolitana e Município', \n",
    "                'Variável', \n",
    "                'Valor']]\n",
    "        \n",
    "#Tratamento do texto das regiões\n",
    "ipca_regioes_anterior['Brasil, Região Metropolitana e Município'] = ipca_regioes_anterior['Brasil, Região Metropolitana e Município'].map(lambda x: x[:-5])\n",
    "\n",
    "#Criação de tabela dinâmica para facilitar a visualização e manipulação\n",
    "ipca_regioes_anterior = pd.crosstab(\n",
    "    ipca_regioes_anterior['Brasil, Região Metropolitana e Município'], \n",
    "    ipca_regioes_anterior['Variável'], ipca_regioes_anterior['Valor'], \n",
    "    aggfunc=sum)\n",
    "\n",
    "#Criação de dataframe com a variação mais recente do IPCA para cada região\n",
    "ipca_regioes_atual = ipca_regioes[\n",
    "    (ipca_regioes['Nível Territorial'].isin(\n",
    "        ['Município', \n",
    "        'Região Metropolitana']\n",
    "        )) \\\n",
    "        & (ipca_regioes['Mês (Código)']==data_atual)][\n",
    "            ['Brasil, Região Metropolitana e Município', \n",
    "            'Variável', \n",
    "            'Valor']]\n",
    "\n",
    "#Tratamento do texto das regiões\n",
    "ipca_regioes_atual['Brasil, Região Metropolitana e Município'] = ipca_regioes_atual['Brasil, Região Metropolitana e Município'].map(lambda x: x[:-5])\n",
    "\n",
    "#Criação de tabela dinâmica para facilitar a visualização e manipulação\n",
    "ipca_regioes_atual = pd.crosstab(\n",
    "    ipca_regioes_atual['Brasil, Região Metropolitana e Município'], \n",
    "    ipca_regioes_atual['Variável'], \n",
    "    ipca_regioes_atual['Valor'], \n",
    "    aggfunc=sum)\n",
    "\n",
    "#Concatena as duas tabelas para criar visualização\n",
    "ipca_regioes = pd.merge(\n",
    "    ipca_regioes_atual.reset_index(), \n",
    "    ipca_regioes_anterior.reset_index(), \n",
    "    on='Brasil, Região Metropolitana e Município', \n",
    "    suffixes=[' - atual',' - anterior'])\n",
    "\n",
    "#Agrega a coluna de pesos para cada região\n",
    "ipca_regioes = pd.merge(ipca_regioes, pesos_regioes_ipca, left_on='Brasil, Região Metropolitana e Município', right_on='Região')\n",
    "\n",
    "#Ordenação do maior para o menor com base na coluna da variação mensal antual\n",
    "ipca_regioes = ipca_regioes.sort_values(by='IPCA - Variação mensal - atual', ascending=False).reset_index()\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Curitiba <a id=\"coleta-tratamento-ipca-curitiba\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Requisição dos grupos do IPCA dos últimos 2 meses para Curitiba através da API do SIDRA e transformação em DataFrame\n",
    "ipca_curitiba = requests.get('https://apisidra.ibge.gov.br/values/t/7060/n1/all/n7/all/n6/all/v/all/p/last2/c315/7170,7445,7486,7558,7625,7660,7712,7766,7786/d/v63%202')\n",
    "ipca_curitiba = ipca_curitiba.json()\n",
    "ipca_curitiba = pd.DataFrame(ipca_curitiba)\n",
    "\n",
    "#Tratamento\n",
    "ipca_curitiba.columns = ipca_curitiba.iloc[0] \n",
    "ipca_curitiba = ipca_curitiba[1:]\n",
    "ipca_curitiba['Valor'] = ipca_curitiba['Valor'].astype(float)\n",
    "ipca_curitiba['Mês (Código)'] = pd.to_datetime(ipca_curitiba['Mês (Código)'], format='%Y%m')\n",
    "\n",
    "#Criação de dataframe com a variação do IPCA do mês anterior para Curitiba\n",
    "ipca_curitiba_anterior = ipca_curitiba[\n",
    "    (ipca_curitiba['Brasil, Região Metropolitana e Município'] == 'Curitiba - PR') \\\n",
    "        & (ipca_curitiba['Mês (Código)']==data_anterior) \\\n",
    "            & (ipca_curitiba['Variável']=='IPCA - Variação mensal')][\n",
    "                ['Variável', \n",
    "                'Geral, grupo, subgrupo, item e subitem',\n",
    "                'Valor']]\n",
    "\n",
    "#Tratamento de texto nos nomes de cada grupo\n",
    "ipca_curitiba_anterior['Geral, grupo, subgrupo, item e subitem'] = ipca_curitiba_anterior['Geral, grupo, subgrupo, item e subitem'].map(lambda x: x[2:])\n",
    "\n",
    "#Criação de tabela dinâmica para facilitar a visualização e manipulação\n",
    "ipca_curitiba_anterior = pd.crosstab(\n",
    "    ipca_curitiba_anterior['Geral, grupo, subgrupo, item e subitem'], \n",
    "    ipca_curitiba_anterior['Variável'], ipca_curitiba_anterior['Valor'], \n",
    "    aggfunc=sum)\n",
    "\n",
    "#Criação de dataframe com a variação do IPCA do mês atual para Curitiba\n",
    "ipca_curitiba_atual = ipca_curitiba[\n",
    "    (ipca_curitiba['Brasil, Região Metropolitana e Município'] == 'Curitiba - PR') \\\n",
    "        & (ipca_curitiba['Mês (Código)']==data_atual)][\n",
    "                ['Variável', \n",
    "                'Geral, grupo, subgrupo, item e subitem',\n",
    "                'Valor']]\n",
    "\n",
    "#Tratamento de texto nos nomes de cada grupo\n",
    "ipca_curitiba_atual['Geral, grupo, subgrupo, item e subitem'] = ipca_curitiba_atual['Geral, grupo, subgrupo, item e subitem'].map(lambda x: x[2:])\n",
    "\n",
    "#Criação de tabela dinâmica para facilitar a visualização e manipulação\n",
    "ipca_curitiba_atual = pd.crosstab(\n",
    "    ipca_curitiba_atual['Geral, grupo, subgrupo, item e subitem'], \n",
    "    ipca_curitiba_atual['Variável'], \n",
    "    ipca_curitiba_atual['Valor'], \n",
    "    aggfunc=sum)\n",
    "\n",
    "#Concatena as duas tabelas para criar visualização\n",
    "ipca_curitiba = pd.merge(\n",
    "    ipca_curitiba_atual.reset_index(), \n",
    "    ipca_curitiba_anterior.reset_index(), \n",
    "    on='Geral, grupo, subgrupo, item e subitem', \n",
    "    suffixes=[' - atual',' - anterior'])\n",
    "\n",
    "#Ordenação do maior para o menor com base na coluna da variação mensal antual\n",
    "ipca_curitiba = ipca_curitiba.sort_values('IPCA - Variação mensal - atual', ascending=False).reset_index()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## INPC <a id=\"coleta-tratamento-inpc\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Brasil <a id=\"graficos-ipca-nacional\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Requisição do INPC do Brasil dos últimos 12 meses através da API do SIDRA e transformação em DataFrame\n",
    "inpc_brasil = requests.get('https://apisidra.ibge.gov.br/values/t/7063/n1/all/v/all/p/last12/c315/7169/d/V44%202')\n",
    "inpc_brasil = inpc_brasil.json()\n",
    "inpc_brasil = pd.DataFrame(inpc_brasil)\n",
    "\n",
    "#Tratamento\n",
    "inpc_brasil.columns = inpc_brasil.iloc[0] \n",
    "inpc_brasil = inpc_brasil[1:]\n",
    "inpc_brasil['Valor'] = inpc_brasil['Valor'].astype(float)\n",
    "inpc_brasil['Mês (Código)'] = pd.to_datetime(inpc_brasil['Mês (Código)'], format='%Y%m')\n",
    "\n",
    "#Criação de tabela dinâmica para facilitar a visualização e manipulação\n",
    "inpc_brasil = pd.crosstab(inpc_brasil['Mês (Código)'], inpc_brasil['Variável'], inpc_brasil['Valor'], aggfunc='sum')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Regiões <a id=\"coleta-tratamento-inpc-regioes\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Criação de dataframe com o peso de cada região e capital no INPC do Brasil\n",
    "regioes = [\"Brasília\", \"Goiânia\", \"Belo Horizonte\", \"Porto Alegre\", \"São Paulo\", \"Rio de Janeiro\", \"Recife\", \"São Luís\", \"Fortaleza\", \"Campo Grande\", \"Salvador\", \"Curitiba\", \"Belém\", \"Rio Branco\", \"Grande Vitória\", \"Aracaju\"]\n",
    "pesos_inpc = [1.97, 4.43, 10.35, 7.15, 24.6, 9.38, 5.6, 3.47, 5.16, 1.73, 7.92, 7.37, 6.95, 0.72, 1.91, 1.29]\n",
    "pesos_regioes_inpc = pd.DataFrame({'Região':regioes, 'Pesos':pesos_inpc})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Requisição do INPC das regiões e capitais dos últimos 12 meses através da API do SIDRA e transformação em DataFrame\n",
    "inpc_regioes = requests.get('https://apisidra.ibge.gov.br/values/t/7063/n1/all/n7/all/n6/all/v/all/p/last2/c315/7169/d/v44%202')\n",
    "inpc_regioes = inpc_regioes.json()\n",
    "inpc_regioes = pd.DataFrame(inpc_regioes)\n",
    "\n",
    "#Tratamento\n",
    "inpc_regioes.columns = inpc_regioes.iloc[0] \n",
    "inpc_regioes = inpc_regioes[1:]\n",
    "inpc_regioes['Valor'] = inpc_regioes['Valor'].astype(float)\n",
    "inpc_regioes['Mês (Código)'] = pd.to_datetime(inpc_regioes['Mês (Código)'], format='%Y%m')\n",
    "\n",
    "#\n",
    "inpc_regioes_anterior = inpc_regioes[\n",
    "    (inpc_regioes['Nível Territorial'].isin(['Município', 'Região Metropolitana'])) \\\n",
    "        & (inpc_regioes['Mês (Código)']==data_anterior) \\\n",
    "            & (inpc_regioes['Variável']=='INPC - Variação mensal')][\n",
    "                ['Brasil, Região Metropolitana e Município', \n",
    "                'Variável', \n",
    "                'Valor']]\n",
    "        \n",
    "\n",
    "inpc_regioes_anterior['Brasil, Região Metropolitana e Município'] = inpc_regioes_anterior['Brasil, Região Metropolitana e Município'].map(lambda x: x[:-5])\n",
    "\n",
    "inpc_regioes_anterior = pd.crosstab(\n",
    "    inpc_regioes_anterior['Brasil, Região Metropolitana e Município'], \n",
    "    inpc_regioes_anterior['Variável'], \n",
    "    inpc_regioes_anterior['Valor'], \n",
    "    aggfunc=sum)\n",
    "\n",
    "#Variação do INPC nas regiões - mês atual\n",
    "inpc_regioes_atual = inpc_regioes[\n",
    "    (inpc_regioes['Nível Territorial'].isin(\n",
    "        ['Município', \n",
    "        'Região Metropolitana']\n",
    "        )) \\\n",
    "        & (inpc_regioes['Mês (Código)']==data_atual)][\n",
    "            ['Brasil, Região Metropolitana e Município', \n",
    "            'Variável', \n",
    "            'Valor']]\n",
    "\n",
    "inpc_regioes_atual['Brasil, Região Metropolitana e Município'] = inpc_regioes_atual['Brasil, Região Metropolitana e Município'].map(lambda x: x[:-5])\n",
    "\n",
    "inpc_regioes_atual = pd.crosstab(\n",
    "    inpc_regioes_atual['Brasil, Região Metropolitana e Município'], \n",
    "    inpc_regioes_atual['Variável'], \n",
    "    inpc_regioes_atual['Valor'], \n",
    "    aggfunc=sum)\n",
    "\n",
    "\n",
    "inpc_regioes = pd.merge(\n",
    "    inpc_regioes_atual.reset_index(), \n",
    "    inpc_regioes_anterior.reset_index(), \n",
    "    on='Brasil, Região Metropolitana e Município', \n",
    "    suffixes=[' - atual',' - anterior'])\n",
    "\n",
    "\n",
    "inpc_regioes = pd.merge(inpc_regioes, pesos_regioes_inpc, left_on='Brasil, Região Metropolitana e Município', right_on='Região')\n",
    "\n",
    "inpc_regioes = inpc_regioes.sort_values(by='INPC - Variação mensal - atual', ascending=False).reset_index()\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Curitiba <a id=\"coleta-tratamento-inpc-curitiba\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Importa os dados de subitens do INPC\n",
    "\n",
    "inpc_curitiba = requests.get('https://apisidra.ibge.gov.br/values/t/7063/n1/all/n7/all/n6/all/v/all/p/last2/c315/7170,7445,7486,7558,7625,7660,7712,7766,7786/d/v44%202')\n",
    "inpc_curitiba = inpc_curitiba.json()\n",
    "inpc_curitiba = pd.DataFrame(inpc_curitiba)\n",
    "\n",
    "#tratamento\n",
    "\n",
    "inpc_curitiba.columns = inpc_curitiba.iloc[0] \n",
    "inpc_curitiba = inpc_curitiba[1:]\n",
    "inpc_curitiba['Valor'] = inpc_curitiba['Valor'].astype(float)\n",
    "inpc_curitiba['Mês (Código)'] = pd.to_datetime(inpc_curitiba['Mês (Código)'], format='%Y%m')\n",
    "\n",
    "#Variação dos INPC por subitens - mês anterior\n",
    "\n",
    "inpc_curitiba_anterior = inpc_curitiba[\n",
    "    (inpc_curitiba['Brasil, Região Metropolitana e Município'] == 'Curitiba - PR') \\\n",
    "        & (inpc_curitiba['Mês (Código)']==data_anterior) \\\n",
    "            & (inpc_curitiba['Variável']=='INPC - Variação mensal')][\n",
    "                ['Variável', \n",
    "                'Geral, grupo, subgrupo, item e subitem',\n",
    "                'Valor']]\n",
    "\n",
    "inpc_curitiba_anterior = pd.crosstab(\n",
    "    inpc_curitiba_anterior['Geral, grupo, subgrupo, item e subitem'], \n",
    "    inpc_curitiba_anterior['Variável'], inpc_curitiba_anterior['Valor'], \n",
    "    aggfunc=sum)\n",
    "    \n",
    "#Variação dos INPC por subitens - mês atual\n",
    "inpc_curitiba_atual = inpc_curitiba[\n",
    "    (inpc_curitiba['Brasil, Região Metropolitana e Município'] == 'Curitiba - PR') \\\n",
    "        & (inpc_curitiba['Mês (Código)']==data_atual)][\n",
    "                ['Variável', \n",
    "                'Geral, grupo, subgrupo, item e subitem',\n",
    "                'Valor']]\n",
    "\n",
    "\n",
    "inpc_curitiba_atual = pd.crosstab(\n",
    "    inpc_curitiba_atual['Geral, grupo, subgrupo, item e subitem'], \n",
    "    inpc_curitiba_atual['Variável'], \n",
    "    inpc_curitiba_atual['Valor'], \n",
    "    aggfunc=sum)\n",
    "\n",
    "\n",
    "inpc_curitiba = pd.merge(\n",
    "    inpc_curitiba_atual.reset_index(), \n",
    "    inpc_curitiba_anterior.reset_index(), \n",
    "    on='Geral, grupo, subgrupo, item e subitem', \n",
    "    suffixes=[' - atual',' - anterior'])\n",
    "\n",
    "inpc_curitiba['Geral, grupo, subgrupo, item e subitem'] = inpc_curitiba['Geral, grupo, subgrupo, item e subitem'].map(lambda x: x[2:])\n",
    "\n",
    "inpc_curitiba = inpc_curitiba.sort_values(by='INPC - Variação mensal - atual', ascending=False).reset_index()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Preços Monitorados <a id=\"graficos-monitorados\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### IPCA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "precos_monit_ipca = requests.get('https://apisidra.ibge.gov.br/values/t/7060/n7/all/v/all/p/last12/c315/7659,7451,7649,7484,7483/d/v2265%202')\n",
    "precos_monit_ipca = precos_monit_ipca.json()\n",
    "precos_monit_ipca = pd.DataFrame(precos_monit_ipca)\n",
    "\n",
    "#tratamento\n",
    "\n",
    "precos_monit_ipca.columns = precos_monit_ipca.iloc[0] \n",
    "precos_monit_ipca = precos_monit_ipca[1:]\n",
    "precos_monit_ipca['Valor'] = precos_monit_ipca['Valor'].replace('-', np.nan) \n",
    "precos_monit_ipca['Valor'] = precos_monit_ipca['Valor'].astype(float)\n",
    "precos_monit_ipca['Mês (Código)'] = pd.to_datetime(precos_monit_ipca['Mês (Código)'], format='%Y%m')\n",
    "\n",
    "precos_monit_ipca = precos_monit_ipca[\n",
    "    (precos_monit_ipca['Mês (Código)']==data_atual) \\\n",
    "    & (precos_monit_ipca['Variável']=='IPCA - Variação acumulada em 12 meses') \\\n",
    "    & (precos_monit_ipca['Região Metropolitana']=='Curitiba - PR')][['Variável', \n",
    "                                                                    'Geral, grupo, subgrupo, item e subitem',\n",
    "                                                                    'Valor']] \n",
    "\n",
    "precos_monit_ipca['Geral, grupo, subgrupo, item e subitem'] = precos_monit_ipca['Geral, grupo, subgrupo, item e subitem'].map(lambda x: x.split('.')[1])\n",
    "\n",
    "\n",
    "precos_monit_ipca = pd.crosstab(\n",
    "    precos_monit_ipca['Geral, grupo, subgrupo, item e subitem'], \n",
    "    precos_monit_ipca['Variável'], \n",
    "    precos_monit_ipca['Valor'], \n",
    "    aggfunc=sum)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### INPC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "precos_monit_inpc = requests.get('https://apisidra.ibge.gov.br/values/t/7063/n7/all/v/all/p/last12/c315/7659,7451,7649,7484,7483/d/v2292%202')\n",
    "precos_monit_inpc = precos_monit_inpc.json()\n",
    "precos_monit_inpc = pd.DataFrame(precos_monit_inpc)\n",
    "\n",
    "#tratamento\n",
    "\n",
    "precos_monit_inpc.columns = precos_monit_inpc.iloc[0] \n",
    "precos_monit_inpc = precos_monit_inpc[1:]\n",
    "precos_monit_inpc['Valor'] = precos_monit_inpc['Valor'].replace('-', np.nan) \n",
    "precos_monit_inpc['Valor'] = precos_monit_inpc['Valor'].astype(float)\n",
    "precos_monit_inpc['Mês (Código)'] = pd.to_datetime(precos_monit_inpc['Mês (Código)'], format='%Y%m')\n",
    "\n",
    "precos_monit_inpc = precos_monit_inpc[\n",
    "    (precos_monit_inpc['Mês (Código)']==data_atual) \\\n",
    "    & (precos_monit_inpc['Variável']=='INPC - Variação acumulada em 12 meses') \\\n",
    "    &   (precos_monit_inpc['Região Metropolitana']=='Curitiba - PR')][\n",
    "                ['Variável', \n",
    "                'Geral, grupo, subgrupo, item e subitem',\n",
    "                'Valor']]\n",
    "\n",
    "precos_monit_inpc['Geral, grupo, subgrupo, item e subitem'] = precos_monit_inpc['Geral, grupo, subgrupo, item e subitem'].map(lambda x: x.split('.')[1])\n",
    "\n",
    "\n",
    "precos_monit_inpc = pd.crosstab(\n",
    "    precos_monit_inpc['Geral, grupo, subgrupo, item e subitem'], \n",
    "    precos_monit_inpc['Variável'], \n",
    "    precos_monit_inpc['Valor'], \n",
    "    aggfunc=sum)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "precos_monitorados = pd.merge(\n",
    "    precos_monit_ipca.reset_index(), \n",
    "    precos_monit_inpc.reset_index(), \n",
    "    on='Geral, grupo, subgrupo, item e subitem')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## IGP-DI <a id=\"graficos-igpdi\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "url_igpdi = 'http://www.ipeadata.gov.br/ExibeSerie.aspx?serid=33593'\n",
    "\n",
    "pagina_igpdi = pd.read_html(url_igpdi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\est.matheus.brasil\\AppData\\Local\\Temp\\ipykernel_16344\\1871963093.py:6: FutureWarning: The default value of regex will change from True to False in a future version. In addition, single character regular expressions will *not* be treated as literal strings when regex=True.\n",
      "  igpdi['IGP-DI Indice'] = igpdi['IGP-DI Indice'].str.replace('.','')\n"
     ]
    }
   ],
   "source": [
    "igpdi = pagina_igpdi[2]\n",
    "igpdi.columns = ['Data','IGP-DI Indice']\n",
    "igpdi = igpdi.drop(range(0,105))\n",
    "\n",
    "igpdi['IGP-DI Indice'] = igpdi['IGP-DI Indice'].str.replace(',','.')\n",
    "igpdi['IGP-DI Indice'] = igpdi['IGP-DI Indice'].str.replace('.','')\n",
    "igpdi['IGP-DI Indice'] = pd.to_numeric(igpdi['IGP-DI Indice']) / 10000\n",
    "igpdi['Data'] = pd.to_datetime(igpdi['Data'])\n",
    "igpdi.set_index('Data', inplace=True)\n",
    "\n",
    "igpdi['Variação Mensal'] = 0.0\n",
    "for i in range(-1, -21, -1):\n",
    "    igpdi['Variação Mensal'][i] = ((igpdi['IGP-DI Indice'][i] / igpdi['IGP-DI Indice'][i-1]) - 1)*100\n",
    "\n",
    "igpdi['Acumulado 12 meses'] = 0.0\n",
    "for i in range(-1, -100, -1):\n",
    "    igpdi['Acumulado 12 meses'][i] = ((igpdi['IGP-DI Indice'][i] / igpdi['IGP-DI Indice'][i-12]) - 1)*100\n",
    "\n",
    "igpdi['Acumulado no Ano'] = 0.0\n",
    "for i in range(832, len(igpdi)):\n",
    "    igpdi['Acumulado no Ano'][i] = (igpdi['IGP-DI Indice'][i] / igpdi['IGP-DI Indice'][831] - 1)*100\n",
    "\n",
    "igpdi = igpdi.round(2)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## IGP-M <a id=\"graficos-igpm\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "url_igpm = 'http://www.ipeadata.gov.br/ExibeSerie.aspx?serid=37796'\n",
    "\n",
    "pagina_igpm = pd.read_html(url_igpm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\est.matheus.brasil\\AppData\\Local\\Temp\\ipykernel_16344\\2338524234.py:6: FutureWarning: The default value of regex will change from True to False in a future version. In addition, single character regular expressions will *not* be treated as literal strings when regex=True.\n",
      "  igpm['IGP-M Indice'] = igpm['IGP-M Indice'].str.replace('.','')\n"
     ]
    }
   ],
   "source": [
    "igpm = pagina_igpm[2]\n",
    "igpm.columns = ['Data','IGP-M Indice']\n",
    "igpm = igpm.drop(range(0,3))\n",
    "\n",
    "igpm['IGP-M Indice'] = igpm['IGP-M Indice'].str.replace(',','.')\n",
    "igpm['IGP-M Indice'] = igpm['IGP-M Indice'].str.replace('.','')\n",
    "igpm['IGP-M Indice'] = pd.to_numeric(igpm['IGP-M Indice']) / 10000\n",
    "igpm['Data'] = pd.to_datetime(igpm['Data'])\n",
    "igpm.set_index('Data', inplace=True)\n",
    "\n",
    "igpm['Variação Mensal'] = 0.0\n",
    "for i in range(-1, -21, -1):\n",
    "    igpm['Variação Mensal'][i] = ((igpm['IGP-M Indice'][i] / igpm['IGP-M Indice'][i-1]) - 1)*100\n",
    "\n",
    "igpm['Acumulado 12 meses'] = 0.0\n",
    "for i in range(-1, -100, -1):\n",
    "    igpm['Acumulado 12 meses'][i] = ((igpm['IGP-M Indice'][i] / igpm['IGP-M Indice'][i-12]) - 1)*100\n",
    "\n",
    "igpm['Acumulado no Ano'] = 0.0\n",
    "for i in range(390, len(igpm)):\n",
    "    igpm['Acumulado no Ano'][i] = (igpm['IGP-M Indice'][i] / igpm['IGP-M Indice'][389] - 1)*100\n",
    "\n",
    "igpm = igpm.round(2)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Brent <a id=\"graficos-brent\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "from chave import chave\n",
    "# Obtém o token de acesso \n",
    "api_key = chave.get('api')\n",
    "\n",
    "brent = requests.get(f'https://api.eia.gov/v2/steo/data/?api_key={api_key}&frequency=monthly&data[0]=value&facets[seriesId][]=BREPUUS&sort[0][column]=period&sort[0][direction]=asc&offset=0&length=5000')\n",
    "brent = brent.json()\n",
    "brent = pd.DataFrame(brent['response']['data'])\n",
    "brent = brent.rename(columns={'period': 'date', 'value': 'price'})\n",
    "brent = brent[['date', 'price']]\n",
    "brent['price'] = brent['price'].astype(float)\n",
    "brent['date'] = pd.to_datetime(brent['date'], format='%Y-%m')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Diesel-S10 <a id=\"graficos-diesel\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Capitais"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_referencia = dt.datetime.now()\n",
    "\n",
    "#scraping na página de preços da ANP \n",
    "\n",
    "url = \"https://www.gov.br/anp/pt-br/assuntos/precos-e-defesa-da-concorrencia/precos/precos-revenda-e-de-distribuicao-combustiveis/serie-historica-do-levantamento-de-precos\"\n",
    "\n",
    "soup = requests.get(url)\n",
    "html = BS(soup.text, \"html.parser\")\n",
    "\n",
    "#encontra todos os links presentes na página\n",
    "\n",
    "lista_links = []\n",
    "\n",
    "for link in html.find_all('a'):\n",
    "    lista_links.append(link.get('href'))\n",
    "\n",
    "#transforma em dataframe para facilitar a manipulação\n",
    "\n",
    "df_links = pd.DataFrame({'links':lista_links})\n",
    "df_links = df_links[df_links['links'].str.contains('precos-revenda')]\n",
    "\n",
    "#encontra os links de 2022 o ano de referência\n",
    "precos_2022 = df_links[df_links['links'].str.contains(str(data_referencia.year-1))]\n",
    "\n",
    "#procura o link dos preços semanais e armazena em variável\n",
    "link_semanal = precos_2022[precos_2022['links'].str.contains('semanal')].values[0][0]\n",
    "\n",
    "#procura o link dos preços mensais e armazena em variável\n",
    "link_mensal = precos_2022[precos_2022['links'].str.contains('mensal')].values[0][0]\n",
    "#baixa os arquivos e salva no diretório\n",
    "\n",
    "mensal_xlsx = requests.get(link_mensal)\n",
    "\n",
    "arquivo = open('precos_combustiveis_mensal.xlsx', 'wb')\n",
    "arquivo.write(mensal_xlsx.content)\n",
    "arquivo.close()\n",
    "\n",
    "semanal_xlsx = requests.get(link_semanal)\n",
    "\n",
    "arquivo = open('precos_combustiveis_semanal.xlsx', 'wb')\n",
    "arquivo.write(semanal_xlsx.content)\n",
    "arquivo.close()\n",
    "\n",
    "#capitais do Brasil\n",
    "capitais = ['ARACAJU','BELEM','BELO HORIZONTE','BRASILIA','CAMPO GRANDE','CURITIBA','FORTALEZA','GOIANIA','PORTO ALEGRE','RECIFE','RIO BRANCO','RIO DE JANEIRO','SALVADOR','SAO LUIS','SAO PAULO','VITORIA']\n",
    "\n",
    "precos_mensal = pd.read_excel('precos_combustiveis_mensal.xlsx', header=16)\n",
    "ultimos_3_meses = data_referencia - relativedelta(months=4)\n",
    "precos_capitais = precos_mensal[(precos_mensal['PRODUTO']=='OLEO DIESEL S10') & (precos_mensal['MUNICÍPIO'].isin(capitais)) &(precos_mensal['MÊS'] >= f'{ultimos_3_meses.year}-{ultimos_3_meses.month}-01')][['MÊS', 'MUNICÍPIO', 'PREÇO MÉDIO REVENDA']]\n",
    "\n",
    "precos_capitais['MÊS'] = precos_capitais['MÊS'].dt.strftime('%Y-%m')\n",
    "\n",
    "precos_capitais = pd.crosstab(\n",
    "    precos_capitais['MÊS'],\n",
    "    precos_capitais['MUNICÍPIO'],\n",
    "    precos_capitais['PREÇO MÉDIO REVENDA'],\n",
    "    aggfunc='mean').T\n",
    "\n",
    "precos_capitais['MÉDIA'] = round(np.mean(precos_capitais, axis=1), 2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Curitiba"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "ultimos12meses = data_referencia - relativedelta(months=12)\n",
    "diesel_curitiba = precos_mensal[(precos_mensal['PRODUTO']=='OLEO DIESEL S10') & (precos_mensal['MUNICÍPIO'] == 'CURITIBA') &(precos_mensal['MÊS'] >= f'{ultimos12meses.year}-{ultimos12meses.month}-01')][['MÊS', 'MUNICÍPIO', 'PREÇO MÉDIO REVENDA']]\n",
    "diesel_curitiba.set_index('MÊS', inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Regiões do Brasil"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "precos_semanal = pd.read_excel('precos_combustiveis_semanal.xlsx', header=11)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "diesel_regioes = precos_semanal[(precos_semanal['PRODUTO']=='OLEO DIESEL S10') \\\n",
    "        &(precos_semanal['DATA INICIAL'] >= f'{ultimos12meses.year}-{ultimos12meses.month}-01')][['DATA INICIAL', 'DATA FINAL', 'REGIÃO', 'PREÇO MÉDIO REVENDA']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "ultima_semana = diesel_regioes[diesel_regioes['DATA FINAL'] == diesel_regioes['DATA FINAL'].max()]\n",
    "ultima_semana = ultima_semana.groupby('REGIÃO').mean()"
   ]
  },
  {
   "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",
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       "\n",
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       "        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>SEMANAL</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>REGIÃO</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CENTRO OESTE</th>\n",
       "      <td>-0.007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NORDESTE</th>\n",
       "      <td>-0.013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NORTE</th>\n",
       "      <td>-0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SUDESTE</th>\n",
       "      <td>-0.012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SUL</th>\n",
       "      <td>-0.012</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              SEMANAL\n",
       "REGIÃO               \n",
       "CENTRO OESTE   -0.007\n",
       "NORDESTE       -0.013\n",
       "NORTE          -0.001\n",
       "SUDESTE        -0.012\n",
       "SUL            -0.012"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#calcular a variação percentual de preço entre a última semana e a semana anterior do preco_semanal\n",
    "\n",
    "ultima_semana = diesel_regioes[diesel_regioes['DATA FINAL'] == diesel_regioes['DATA FINAL'].max()]\n",
    "ultima_semana = ultima_semana.groupby('REGIÃO').mean()\n",
    "\n",
    "penultima_semana = diesel_regioes[diesel_regioes['DATA FINAL'] == diesel_regioes['DATA FINAL'].max() - relativedelta(weeks=1)]\n",
    "penultima_semana = penultima_semana.groupby('REGIÃO').mean()\n",
    "\n",
    "var_semanal_brasil = ((ultima_semana.mean() - penultima_semana.mean() )/ ultima_semana.mean())\n",
    "\n",
    "var_semanal = ((ultima_semana - penultima_semana )/ ultima_semana )\n",
    "var_semanal['SEMANAL'] = round(var_semanal['PREÇO MÉDIO REVENDA'], 3)\n",
    "var_semanal = var_semanal[['SEMANAL']]\n",
    "var_semanal\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "ultimo_mes =  diesel_regioes[diesel_regioes['DATA FINAL'] == diesel_regioes['DATA FINAL'].max() - relativedelta(month=1)]\n",
    "ultimo_mes = ultimo_mes.groupby('REGIÃO').mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "        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>MENSAL</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>REGIÃO</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CENTRO OESTE</th>\n",
       "      <td>-0.030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NORDESTE</th>\n",
       "      <td>-0.030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NORTE</th>\n",
       "      <td>-0.027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SUDESTE</th>\n",
       "      <td>-0.022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SUL</th>\n",
       "      <td>-0.035</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              MENSAL\n",
       "REGIÃO              \n",
       "CENTRO OESTE  -0.030\n",
       "NORDESTE      -0.030\n",
       "NORTE         -0.027\n",
       "SUDESTE       -0.022\n",
       "SUL           -0.035"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ultima_semana = diesel_regioes[diesel_regioes['DATA FINAL'] == diesel_regioes['DATA FINAL'].max()]\n",
    "ultima_semana = ultima_semana.groupby('REGIÃO').mean()\n",
    "\n",
    "ultimo_mes =  diesel_regioes[diesel_regioes['DATA FINAL'] == diesel_regioes['DATA FINAL'].max() - relativedelta(weeks=4)]\n",
    "ultimo_mes = ultimo_mes.groupby('REGIÃO').mean()\n",
    "\n",
    "ultimo_mes_brasil = ((ultima_semana.mean() - ultimo_mes.mean()) / ultima_semana.mean())\n",
    "\n",
    "var_mensal = ((ultima_semana - ultimo_mes) / ultima_semana)\n",
    "var_mensal['MENSAL'] = round(var_mensal['PREÇO MÉDIO REVENDA'], 3)\n",
    "var_mensal = var_mensal[['MENSAL']]\n",
    "var_mensal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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>SEIS MESES</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>REGIÃO</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CENTRO OESTE</th>\n",
       "      <td>-0.108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NORDESTE</th>\n",
       "      <td>-0.135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NORTE</th>\n",
       "      <td>-0.084</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SUDESTE</th>\n",
       "      <td>-0.124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SUL</th>\n",
       "      <td>-0.129</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              SEIS MESES\n",
       "REGIÃO                  \n",
       "CENTRO OESTE      -0.108\n",
       "NORDESTE          -0.135\n",
       "NORTE             -0.084\n",
       "SUDESTE           -0.124\n",
       "SUL               -0.129"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ultima_semana = diesel_regioes[diesel_regioes['DATA FINAL'] == diesel_regioes['DATA FINAL'].max()]\n",
    "ultima_semana = ultima_semana.groupby('REGIÃO').mean()\n",
    "\n",
    "ultimo_6_meses =  diesel_regioes[diesel_regioes['DATA FINAL'] == diesel_regioes['DATA FINAL'].max() - relativedelta(weeks=24)]\n",
    "ultimo_6_meses = ultimo_6_meses.groupby('REGIÃO').mean()\n",
    "\n",
    "ultimo_6_meses_brasil =   ((ultima_semana.mean() - ultimo_6_meses.mean()) / ultima_semana.mean())\n",
    "\n",
    "var_6_meses = ((ultima_semana - ultimo_6_meses) / ultima_semana)\n",
    "var_6_meses['SEIS MESES'] = round(var_6_meses['PREÇO MÉDIO REVENDA'], 3)\n",
    "var_6_meses = var_6_meses[['SEIS MESES']]\n",
    "var_6_meses"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "variacao_regiao = pd.merge(\n",
    "    ultima_semana.reset_index(), \n",
    "    var_semanal.reset_index(), \n",
    "    on='REGIÃO')\n",
    "\n",
    "variacao_regiao = pd.merge(\n",
    "    variacao_regiao, \n",
    "    var_mensal.reset_index(), \n",
    "    on='REGIÃO')\n",
    "\n",
    "variacao_regiao = pd.merge(\n",
    "    variacao_regiao,\n",
    "    var_6_meses.reset_index(),\n",
    "    on='REGIÃO')\n",
    "\n",
    "variacao_regiao = variacao_regiao.sort_values('PREÇO MÉDIO REVENDA', ascending=False)\n",
    "\n",
    "variacao_regiao.loc[5] = ['MÉDIA NACIONAL', ultima_semana.mean().values[0], var_semanal_brasil.values[0], ultimo_mes_brasil.values[0], ultimo_6_meses_brasil.values[0]]\n",
    "    "
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Gráficos e Tabelas <a id=\"graficos\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## IPCA <a id=\"graficos-ipca\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Brasil <a id=\"graficos-ipca-nacional\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Acumulado 12 meses e variação mensal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\est.matheus.brasil\\AppData\\Local\\Temp\\ipykernel_16344\\2442679775.py:7: MatplotlibDeprecationWarning: The 'b' parameter of grid() has been renamed 'visible' since Matplotlib 3.5; support for the old name will be dropped two minor releases later.\n",
      "  plt.grid(b=None)\n"
     ]
    },
    {
     "data": {
      "image/png": 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+AeD+/fvcvn2bmJgYMmXKhLOzM8ePH6dUqVIAREREcPr0aSpXrvzyvwxJEake0mNiYpg5cyZr1qzh/fffj21ftWoVU6dOZcSIEXh4eHDo0CFGjhyJnZ0dzZo1S+0yX1r+/MYQ9/icPWsca9Y8bcuS5Wlgf3KULg2v2xSRGjVq0LNnT5P51sHBwWTNmjXe60eNGsX06dP54osvuH//PhUqVGDlypW4uLikUsUiIiIi8jqxtbWlYcOGTJ06FRcXF0qXLk1ERATp06fnxx9/xNnZmcuXLzNq1CgAk4XjEpI1a1YuXLjA8ePHyZIlC99++y0nT54kT548ALRt25Z27dpRsWJFKleuzA8//MDt27cpX7482bJl4+DBg9SrV4+HDx/y5ZdfEhEREfu5//vf/5g9ezYuLi4UKFCAhQsXEhYWxrvvvgvAP//8Q1RUVIL/3pbUl6ohPTAwkMGDB+Pv7x/7P7gnvv32Wz7++GOaNm0KQP78+Tl69Cjr1q1LkyF97FjTOekAjo4wezaULQsnTjw9jh+Hv/+GAweM41mFCsXtdS9cGGxsUvd5XtTLLnwGcOTIkQTv7+joyODBgxk8ePCLFykiIiIikgRNmjRh5cqV9OrVCzCGo0+ePJmJEyeycuVK8uXLR9euXZk1axZnzpyhWLFiz71fmzZtOHPmDB06dMDe3p6KFSvSs2dPNm3aBICnpyejR49m4MCBAJQrV4558+aRJUsWBg8ejI+PD82bNydbtmw0bNiQDBkyxPa8t2/fntDQUIYPH84///xDuXLlWL58OTly5ACMrYyvXbuW4L/bJfVZxSRm/EUy2bRpE7///jt9+/bls88+I3/+/LHD3f/44w9y584du/IhwJAhQzh16hQbNmwwuY+fnx+enp6pVfYLS+zq7jExEBT0NLSfPGn8eeYMxPfFW/r0Ri/7s73uZcpA9uwp/0wiIiIiknaklX83S+KsWLGCDRs2MHHiRK3BlAb4+fmxf/9+evTo8dx1Bf4tVXvSvby88PLyivfcv1fuvn79Olu3bqV169apUVqK8PZO3EruVlaQK5dx1K//tD0iAi5cMO11P3EC/voLDh82jmflzWva4+7uDsWLg7a8FhERERFJ28LDw3n77bc5cOAAq1evZsiQIeYuSVKIRW7BFhISwieffEKOHDno8mTfsteQnR2UKmUcH330tD0k5Glv+7N/XrtmHNu3m97jjTdMe93d3Y0vBLRQnYiIiIhI2vDbb7/x6aef4urqSp8+fcxdjqQgiwvpgYGBdOrUicePH7NixQoyvW4rpyWCkxPUrm0cT0RHw59/xu11Dwh4+vOzcuSIu1BdqVLGUHpJuxI7xUJERERE0pY6depw8uRJc5chqcCiQvqZM2fo3LkzmTNn5ttvvyV37tzmLinNsLaGIkWM4733nraHhsKpU6a97idOGAvV7dljHM/eo2jRuL3ubm7qdbdUMTFw/74xumLVKhg9GsLCjHNXrhiLF4KCuoiIiIhIWmExIT0gIIAOHTqQP39+5s+fT7Zs2cxd0ishY0aoUsU4noiJMea1/7vX/fz5p8f33z+9PlOmuL3uZcpA5syp/zyvqogIuHPHCNshIaY/P+/1nTsQFZXwfR8+NHrWFdJFRERERNIGiwnpAwYMwN7enkmTJhEZGUlwcDAANjY2ODk5mbm6V4uVFbi6Gkfjxk/bHz829m//d697UBD89ptxPKtAgbi97kWKpJ3t4ZJbTIwRip8N04kN3P/88+KfmzGjMQXi6tX4zyfULiIiIiIilsciQvqlS5di51c0aNDA5Fz+/Pn56aefzFHWa8fBATw8jONZQUGmof3ECTh9Gi5fNo7/374x9h6lSsUN7/+/DWOaEBUFd+/GDdOJCdwRES/2mdbWkC2bEbafHP9+HV9b1qxPV+8vUMAY4v5vtrbG/50KFHix2kREREREJPWYLaQvX7489ueCBQty/vx5c5Ui/8HFxTjefvtpW2Tk0+3hng3wV6+Cn59xPCt37rjBvUSJuNvDJefCZ48fJxymnxe47959sc8DY+G9+ML0fwXuTJmMoP4yxo415qA/fPi0zcrK+OKgQgX44QeoU+flPkNERERERFKWRfSkS9pjawslSxpHq1ZP2+/ejdvrfvIk3LhhHDt3mt6jRImnof32bZg9Gx49Ms4/Wfjs0SOoWzfpgfvJfV5E1qxJ69HOls04zLk6/pMvM579ksPHB9atgx07oF49mDEDunXTQoAiIiIiIpbKKiYmJsbcRSSVn58fnp6e5i5DEik6Gi5ditvrfvGiMY87pdjZxQ3XienlzpLl1ZpXHxUFgwbB5MnG6y5dYNasuKMYRERE5NWjfzeLmI+fnx/79++nR48e2NnZJfp96kmXFGdtDYULG0fz5k/bHzww5rY/Ce2zZiV8Dze3xPdoP/nZ0VE9xmB84TBpkjFaoVMnmD8fzpyBtWshZ05zVyciIiLyfG+99RbXrl1j+PDhfPzxx3HOd+zYkQMHDjBp0iSaNm1qhgpNFS9e3GJqkbRJIV3MJkMGqFTJOMBYgC6+hc/c3IyFz+TltG4NxYoZX5QcOAAVK8KGDXEXChQRERGxNHZ2duzcuTNOSL979y6HDh0yU1UiKeMll6oSST5jxxq9389ydDTaJXlUqgS+vlClijFvvXp1WLPG3FWJiIhIWrDy5EoKTC+A9UhrCkwvwMqTK1Pts6tUqcLhw4cJCQkxaf/pp58oW7ZsqtUhkhoU0sVieHsbQ7Hd3Ixh6m5uxusXXd1d4pc7N+zZA+3bG4vrtWplLDAXHW3uykRERMRSrTy5ki6bu3Dl3hViiOHKvSt02dwl1YK6h4cHOXLk4OeffzZp3759O40aNTJp+/nnn/Hy8qJMmTI0aNCAb775huj//4fOX3/9RfHixdm5cyfNmzenbNmyNG3a1OS+x44do1WrVpQrV47KlSvTv39/7j6z/c/OnTtp0aIF7u7ulC1bllatWnHixImUe3h57Wi4u1gUb2+F8tTg4ACLFkHZstCvH4wbZyzqt2IFZM5s7upEREQkJTVe1Zht/tte+j4PIx7Sel1rWq9rnej3NCraiK0fb03yZ1lZWVG/fn127txJy5YtAQgJCeHw4cNMmjSJUaNGAbBv3z4+//xzhgwZQqVKlfD392fUqFE8evSInj17xt5v0qRJDB8+nFy5cjFt2jQGDBjA/v37SZcuHd26daNVq1ZMmTKF27dvM2DAACZOnMj48eM5ceIEffr0YciQIdSuXZuQkBDGjRvH0KFD2bhxY5KfSyQ+6kkXeU1ZWUGfPsb2bNmywebNxjD4ixfNXZmIiIhIXA0aNODQoUPcu3cPgB9//JHy5cuTI0eO2Gvmzp3LRx99xPvvv0/+/PmpW7cu/fr1Y8GCBbG96WAsNlerVi2KFStG7969CQ0N5eLFi/zzzz/cuXOHHDlykDdvXsqWLctXX31Fu3btAGNu/PDhw/H29iZfvny4u7vzwQcfcOHChdT9ZcgrTT3pIq+5evXgjz/AywvOnjXmra9ZY7SLiIjIq+dFerILTC/AlXtxV/h1y+LG5T6Xk6Gq/+bp6Um2bNnYtWsX7733XrxD3c+ePcvJkyf59ttvY9uio6N5/Pgx165dw+r/t/4pWLBg7PlMmTIBEBERQdasWenQoQOjRo1i1qxZVK9enTfffJOGDRsC8MYbb5ApUybmzZvHxYsXuXLlCmfPnjX5AkDkZaknXUQoUgR+/x2aNIE7d6BBA/jyy5Tdx15ERETSjrF1x+JoZ7rCr6OdI2Prpt4Kv1ZWVrzzzjvs3LmTkJAQjhw5Qr1/9SrY2dnRtWtXNmzYEHts2rSJH3/8ERcXF5Pr/i3m///hM2DAAHbt2sWnn37Kw4cPGTRoEN26dQPg999/p2HDhpw9e5YyZcrw2Wef4ePjk4JPLa8jhXQRAYy56Bs2PF1E7rPPoEMHePzY3JWJiIiIuXmX8WZ+k/m4ZXHDCivcsrgxv8l8vMuk7mJCDRo04LfffmPDhg1UqlQJJycnk/NFihTh8uXLuLm5xR4XLlzgyy+/TNT9r169yvDhw3F2dsbb25s5c+YwceJE9u3bx+3bt1m1ahXVq1dn+vTptG3blipVqnDt2jXgacgXeVka7i4isaytYcwYcHc3Vn9fuhTOnYP1641V4UVEROT15V3GO9VD+b+VL1+eLFmyMHv27Hh7sLt168Ynn3xCsWLFqF+/PpcvX2bYsGHUrl0be3v7/7x/tmzZ2L59O+Hh4XTq1AkwVpDPnz8/2bJlw8nJiX379nHs2DGyZ8/O3r17Wbp0KQDh4eGkS5cueR9YXkvqSReROFq2hF9/BVdXOHQIKlSAw4fNXZWIiIi87qytrXnnnXcIDw/n7bffjnO+Vq1aTJo0ic2bN/Puu+8ybNgwmjVrFrv6+3/JlCkTCxYsIDAwkJYtW/L+++8TFhbG/Pnzsba2plevXrzxxht07NiRFi1a8OOPPzJhwgQATp48mazPKq8vq5g0OC7Dz88PT09Pc5ch8sq7dQtatIADByBdOli4EFonfpcVERERMTP9u1nEfPz8/Ni/fz89evSIdx2EhKgnXUQSlDMn7NoFXbpAWBi0aQP9+0NUlLkrExERERF5NSmki8hz2dvDvHnw9ddgawtTpkDjxsYq8CIiIiIikrwU0kUkUbp1g59/hhw5YOdOqFzZWFRORERERESSj0K6iCRa7drGAnLu7uDvbwT1bdvMXZWIiIiIyKtDIV1EkqRAAWPl9xYt4P59ePddmDgR0t4SlCIiIiIilkchXUSSLGNG+O47GDXKCOcDB4K3Nzx8aO7KRERERETSNoV0EXkh1tYwdCisX2+E9tWroWZNCAw0d2UiIiIiImmXQrqIvJRmzeDgQShYEI4cgYoV4bffzF2ViIiIiEjapJAuIi+tdGljQbm33oKgIKhTB775xtxViYiIiIikPQrpIpIssmeHHTvg008hIgI6dYJevYyfRURERJJDcHAwJUuWpFGjRuYu5T/99ddfFC9eHF9f3xe+h4+PD23atEnGqlKWn58fpUuXjtN++vRp2rdvT4UKFahRowY+Pj7cvXs3wfsMHDiQ4sWL06dPn3jPz58/n+LFi+Pj45NMlVsWhXQRSTZ2djBzJixcaPw8axY0aAC3b5u7MhEREXkVbNy4EVdXVwICAl4q/EryO378ON27dyc6OtqkPSgoiA4dOpAvXz7WrFnDjBkzOHHiRIIB/Ak7Ozv27dvH48eP45zbvn07VlZWyVm+RVFIF5Fk17Ej7N0LLi6we7cxT/3kSXNXJSIiIi9j5UpjK1Zra+PPlStTv4YNGzbQqFEjSpYsyZo1a1K/AInXlClT8Pb2Jk+ePHHObd++HXt7e0aOHEnhwoXx9PRk+PDhHDx4kOvXryd4zzJlymBlZcX+/ftN2q9evcqff/5JyZIlk/05LIVCuoikiGrVjHnqnp5w6RJUrQobNpi7KhEREXkRK1dCly5w5Yqx/eqVK8br1AzqJ06cwN/fn2rVqlG/fn127tzJvXv3Ys+HhoYycuRIqlWrhoeHBx07duTPP/8EYNasWdSrV8/kfs+2PRmavnfvXry8vChTpgzvv/8+ly5dYtasWVSpUoVKlSoxZsyYeN//vLYn7t69y6BBg6hRowalSpWiRo0aTJw40aTneeXKlbz11luULVuWzz//PE4v8qFDh2jdujUeHh6ULl2apk2b8ssvvyT4O4uOjmbu3Lm8+eablCtXjhYtWrBv377Y8+vWraNBgwZs2LCBOnXqULZsWXr37k1QUBD9+vWjXLly1K5dm/Xr1yf4GQAHDx5k/vz58Q7Nf+utt5g+fTo2NjaxbU96we/fv5/gPdOlS8ebb77Jjh07TNq3bdtG7dq1yZAhg0n7hQsX6NixI2XLlqVWrVoMGzbM5P579+6lWbNmuLu7U6NGDUaPHk1YWFjseV9fX1q1aoW7uzt169Zl6tSpJufXrVtHw4YNKV26NG+++SYzZ86MM2oguSiki0iKcXWF/fvho4/gwQNo3tzYWz2F/j4TERGRRGjcGKyskna0bg0PH5re5+FDoz0p92nc+MXrXr9+PTly5MDT05OGDRsSFhbGhmd6APr06cPBgweZOnUqa9euxdHRkU6dOhGRhAVyxo8fz5AhQ/j++++5e/cuH374IX/99RerVq2ib9++LF++3CTkJsWAAQMICAhgzpw57Nixg27durF48WJ2794NGKMExo8fT9euXVm/fj25cuViy5Ytse+/ceMGnTt3xtPTk02bNvHDDz+QO3duBgwYQHh4eLyfOXXqVNatW8eoUaPYuHEjzZs3p2fPnhw6dCj2mr/++otNmzYxf/58Zs6cyc8//4yXlxfu7u6sW7eOmjVrMmzYMJMvRP5t7dq1VKtWLd5z+fPnp0KFCiZtCxYswMXFhaJFiz73d9agQQP27t1r8nzbt2+PsyZBUFAQbdq0oVixYqxfv56ZM2dy8eJFevbsCUBISAg9e/akVatWbN++ncmTJ7Nt2zYWLFgAwNmzZ+nYsSP16tVj8+bNjBkzhj179jBixAgAzp07x7Bhw+jbty8//vgjgwcP5ptvvmHTpk3Prf9FKaSLSIpKn974ln3CBOM/zsOHQ8uWEBpq7spEREQkrQgPD2fbtm3Ur18fa2trChQoQKlSpfjuu+8A+PPPP9m/fz8jR46katWqFCpUiFGjRlG/fv3nLlD2bx07dqRSpUqUKFGCevXq8ejRI0aNGkWhQoX46KOPyJ49O/7+/i/0DDVr1mTs2LGUKVMGV1dXvL29yZ07N+fPnweMXnQvLy9atmxJoUKF+PzzzylTpkzs+yMiIujduzd9+vTB1dWVEiVK0L59e0JCQrgdzwJADx48YNmyZQwePJiaNWvi5uZG69atadq0KfPnzze577BhwyhWrBi1a9emRIkSFC1alHbt2lGoUCE6dOhAeHg4V65ceaHn/rcpU6awd+9ehg8fbtK7Hp9atWoRHR3Nr7/+CsClS5e4evUqderUMblu1apV5MuXjwEDBlCoUCHKlSvHl19+yaFDhzh69Cg3b94kIiKCXLlykTdvXqpWrcrChQtp/P/fGn3zzTfUrl2bjh074ubmRtWqVRk5ciTr1q3j1q1bBAYGYmVlRZ48eciTJw/16tVj8eLFVKpUKVl+J/9mmyJ3FRF5hpUVDBhgbNX28cewdi34+8PGjcacNhEREUk9W7cm/T0FChhD3P/NzQ0uX37Ziv7brl27uHv3Lg0aNIhta9iwIVOmTMHX15e///4bAHd399jz2bJlY+DAgUn6nPz588f+7OjoSM6cOUmXLl1sm4ODQ4K91v/lo48+YteuXXz//fdcvnyZ8+fPc/Pmzdgh0/7+/jRr1szkPeXKlYsN8fnz56dZs2YsXbqU8+fPc+XKFc6ePQtAVFRUnM8LCAggPDyc3r17Y239tG82IiKCHDlyPPe58+XLF/v6yfO/6HM/ERUVxahRo1izZg0jRoygbt26//meJ0Ped+7cyZtvvsm2bdt46623cHBwMLnu7NmznD17Fg8Pjzj3CAgIoEWLFjRs2JBPPvmEXLlyUb16derVq8ebb74Z+/4rV66YvD8mJib2/TVr1qRs2bK0aNECNzc3atSoQaNGjeKdg58cFNJFJNU0bgyHDkHTpnDiBFSoAD/8YOyrLiIiIpZr7FhjDvqzQ94dHY321PBkTnSHDh1i256EqO+++4769esn+Z6RkZFx2mxtTePRs+H2Re8JRq1dunTh0qVLNGnShKZNm+Lu7k67du1ir4lvtXI7O7vYn/39/fn4448pW7YsVatWpVGjRkRGRtK1a9d4P9Pe3h4w5sm7ubkl+Fw2NjZxnjOpz/1fwsLC6N27NwcOHGDy5Mk0adIk0e9t0KABQ4YMISIigh07dtC7d+8419jZ2VG9enWGDBkS55yTkxNWVlZMnz6dnj17sm/fPg4cOECPHj1o2bIlI0aMwM7OjmbNmtG5c+c473d2dsbBwYEVK1Zw8uRJfvnlF/bv38+qVavo169fvO95WRruLiKpqkQJI6g/2ZqtXj2YM8fcVYmIiMjzeHvD/PlGz7mVlfHn/PlGe0oLDg7mwIEDfPzxx2zYsCH22LhxIzVq1GDHjh04OzsDcOrUqdj3hYaGUrVqVXx9fbGzs+PBgwcm933Z4dtJuefFixc5cOAAs2bNom/fvjRu3Jhs2bIRHBwc+2VDiRIlOHLkiMn7nn2edevWkTt3bhYuXEjHjh2pWbMmQUFBwNMvLJ7l5uaGnZ0dQUFBuLm5xR6bN29m3bp1L/XsSREdHU3v3r35/fffmTNnTpICOhhD3iMiIlizZg3Xr1+nVq1aca4pUqQIAQEB5MmTJ/Y5ra2tGTduHDdu3ODkyZOMHz+eIkWK0LFjRxYvXkzfvn1jv/x58v5nf08hISFMnDiRBw8e8Ouvv/LVV19RpkwZevTowbfffkurVq3+c0G9F6WQLiKpLmtW2LIFPv8cIiOhe3fo2hVechSViIiIpCBvb2Noe3S08WdqBHQw9kaPiYmhU6dOFCtWzOTo1KkTYWFhHD9+nLp16zJy5Eh8fX0JCAhg0KBBZMqUCXd3d8qVK8ft27dZsmRJ7EJwz1sVPTGScs/MmTNja2vL9u3b+euvvzh69Cjdu3cnPDw8dhh5x44d2b59O0uXLuXSpUt8/fXX+Pn5xd7DycmJa9eu8euvv3Lt2jU2btzIl19+CcQ/FD19+vS0b9+eqVOnsm3bNgIDA1m2bBlfffUVrq6uL/XsSbF69Wr27NmDj48PJUqUIDg4OPZIzKJ+Dg4O1KlTh2nTpvH222/HjhB4VuvWrbl//z4DBw7k/PnznDx5ks8++4zLly9ToEABMmXKxMqVK5k2bRpXr17l7Nmz7NmzJ3Z6ROfOnTlx4gTjx48nICCAP/74gwEDBvDPP//g7OyMnZ0dX331FcuWLSMwMJCjR49y6NAhypYtm+y/L1BIFxEzsbGByZNh2TJIlw7mzYO334Zbt8xdmYiIiFiSJ9uD5c2bN865qlWrUqJECb777jsmTJhAmTJl6N69Oy1btiQiIoKFCxdib29PlSpV+PTTT1mwYAGNGzfm4MGD9OrV66XqSso9XVxcGDduHDt27KBhw4b079+fsmXL4uXlxcmTJwF4++23GT9+PKtWrcLLy4vjx4/TsmXL2Hu0bduWevXq0bdvX7y8vFi5ciUjR47E0dEx9h7/1qdPHz766CMmTZpEw4YNWb16NaNGjeK99957qWdPis2bNwMwZMgQatSoYXIcP348Ufdo0KABDx48oGHDhvGed3Z2ZvHixfz999+0bNmSTp06kTt3bhYvXoy9vT0FChTgq6++4tdff8XLy4u2bduSK1cupk2bBkDx4sWZN28eR44coVmzZvTp04eKFSsye/ZsACpVqsS4ceP47rvvaNy4MT169KBixYr4+Pgkw28oLquY+MZGWDg/Pz88PT3NXYaIJJM//jC2Z7t+HfLnN/ZTj2fdDxEREUki/btZxHz8/PzYv38/PXr0MFlf4L+oJ11EzK5SJfD1hSpV4OpVqF4d1qwxd1UiIiIiIqlPIV1ELELu3LBnD7RvD48eQatWMGSIMe9NREREROR1oZAuIhbDwQEWLYIvvwRra2Nbl2bN4P79xN9j2LBhceYHHThwIHarkyZNmrBv377n3uPRo0cMHTqUypUrU6FCBYYMGWKyemvx4sXjPUqUKJGUxxURERERiUMhXUQsipUV9OkDO3ZAtmyweTNUrQoXLz7/fTExMcyYMYM1/xonf/HiRbp160aDBg1Yv349devWpUePHvj7+yd4r2HDhuHn58e8efOYO3cuf/zxB8OGDYs9f+DAAZNj/fr1ZMyYkU8++eRlHl1ERERERCFdRCxTvXrGgnJvvAFnzhjz1n/6Kf5rAwMDadu2LatXryZPnjwm55YtW0a5cuXo1q0bhQsXpk+fPnh4eLBs2bJ47xUUFMSWLVsYPnw45cqVo0KFCowZM4atW7fG7kXq7OxsckybNo2iRYvSu3fvZP0diIiIiMjrRyFdRCxWkSLw++/QpAncuQMNGsD06fDvPSmOHj2Kq6srmzdvJl++fCbnfH19qVSpkklb5cqV8fX1jfcz/fz8sLa2pnz58rFt5cuXx8bGxmSv0if27NnDb7/9xogRI7C21l+pIiJieaK1wItIqnuZ/7/TvyhFxKJlzmxsyebjYywi17cv/O9/EBb29BovLy/GjRuHs7NznPffvHkTFxcXk7acOXNy8+bNeD8vKCgIJycnk20ybG1tcXJy4saNG3GunzlzJk2aNNF8dBERsUj29vY8fPjQ3GWIvHYePnz4wkFdIV1ELJ61NYwZY2zLlj49LFkCdepAPJk5jsePH2Nvb2/SZm9vT9izKf8Zjx49Il26dHHa43vPH3/8wdmzZ+nSpUtiH0VERCRV5c2bl4sXLxIaGqoedZFUEB0dTWhoKBcuXCAwMJD06dMnaY90ANsUqk1EJNm1bAlFi0LTpsYw+AoVjF72ihUTfk+6dOmIiIgwaQsPDyd9+vTxXu/g4EB4eHic9vDwcBwdHU3aNm7cSIUKFShcuHCSn0VERCQ1ODk5ERUVxblz5wCwsrIyc0Uir77o6GgCAwO5cuUK77zzTpLfr5AuImmKhwf4+kKLFnDgANSsCQsXQuvW8V+fO3dubt26ZdJ269atOEPgn8iVKxchISFERUVhY2MDQGRkJCEhIeTMmTP2upiYGPbs2UPPnj2T58FERERSiLOzM1myZOHHH3/k0qVLREdHE/PvBV5EJFmlT5+ed955h5IlSyb5vQrpIpLm5MwJu3bBp5/C/PnQpg0cPw4TJsS91tPTk8OHD5u0HTp0iAoVKsR7b09PTyIjIzl69GjsNX5+fkRHR+Pp6Rl73Z9//snt27epUqVK8j2YiIhICrG3t+fdd98lOjqayMhIc5cj8kqzsrJK8hD3Zymki0iaZG8P8+ZBuXLQqxdMmQKnTkHWrKbXtW7dmhYtWjBz5kwaN27Mli1bOH78OCNGjIi9JiQkBDs7OzJlyoSLiwsNGzbEx8eHcePGERMTw9ChQ2natKlJ7/vZs2ext7enYMGCqfK8IiIiycHa2jrOWi0iYlm0cJyIpGndusHPP0P27LBjBxw5AnfvPj1fvHhxZs+ezc6dO2nWrBm7d+9m7ty5JvPI33//fcaOHRv7esyYMZQvX54uXbrQo0cPqlSpYhLqAYKDg8mSJYvm9omIiIhIsrKKSYMTUvz8/EyGnYqIXL5sLCh34oSxbdvq1dCokbmrEhERERFJGvWki8groUAB+PVXY0G5+/fh3Xdh4kRIe19DioiIiMjrTCFdRF4ZGTPCd9/BqFFGOB840Fj1/dEjc1cmIiIiIpI4Cuki8kqxtoahQ2H9eiO0r1plbNP211/mrkxERERE5L8ppIvIK6lZMzh4EAoWBD8/qFABfvvN3FWJiIiIiDyfQrqIvLJKl4bDh+GttyAoCOrUgW++MXdVIiIiIiIJU0gXkVfak63ZPv0UIiKgUydjX/WICHNXJiIiIiISl0K6iLzy7Oxg5kxYuND4edYsaNAAbt82d2UiIiIiIqYU0kXktdGxI+zdCy4usHs3VKoEp06ZuyoRERERkacU0kXktVKtmjFP3dMT/vwTqlaFvn2NfdatrY0/V640d5UiIiIi8royW0gfNmwYPj4+Jm0HDhygadOmuLu706RJE/bt22em6kTkVebqCr/8Ah99BKGhMH06XLli7K1+5Qp06aKgLiIiIiLmkeohPSYmhhkzZrBmzRqT9osXL9KtWzcaNGjA+vXrqVu3Lj169MDf3z+1SxSR14CjoxHEs2aNe+7hQ/jXd4giIiIiIqkiVUN6YGAgbdu2ZfXq1eTJk8fk3LJlyyhXrhzdunWjcOHC9OnTBw8PD5YtW5aaJYrIa8TKCu7di//c1aupW4uIiIiICKRySD969Ciurq5s3ryZfPnymZzz9fWlUqVKJm2VK1fG19c3NUsUkddM/vwJn5s2DcLDU68WEREREZFUDeleXl6MGzcOZ2fnOOdu3ryJi4uLSVvOnDm5efNmapUnIq+hsWONoe/PsrY25qf36wfu7sY+6yIiIiIiqcFiVnd//Pgx9vb2Jm329vaEhYWZqSIReR14e8P8+eDmZgx/d3ODZctgyxYoWhTOn4eGDeHdd0FLZIiIiIhISrOYkJ4uXToiIiJM2sLDw0mfPr2ZKhKR14W3N1y+DNHRxp/e3tC4sbGH+uTJkCkTbN0KpUrBF1/A/fvmrlhEREREXlUWE9Jz587NrVu3TNpu3boVZwi8iEhqsbeHzz+HCxegQweIiDBCe7FisGSJEepFRERERJKTxYR0T09PDh8+bNJ26NAhKlSoYKaKREQMuXLBokXwxx9QpQoEBRmhvWpVOHTI3NWJiIiIyKvEYkJ669at8fX1ZebMmQQEBDBjxgyOHz9Ou3btzF2aiAgAFSvCr7/C8uWQO/fT0N62LVy/bu7qRERERORVYDEhvXjx4syePZudO3fSrFkzdu/ezdy5cylcuLC5SxMRiWVtDa1bG0PgBw0yhsQvX24MgZ8wAbTWpYiIiIi8DKuYmJgYcxeRVH5+fnh6epq7DBERAgKMrdo2bjReFy4MU6eCl5exWryIiIiISFJYTE+6iEhaVLgwbNgAP/4Ib7xhhPZmzeCdd+DMGXNXJyIiIiJpjUK6iEgyqFcPjh+HGTMga1b46Sdwd4c+feDuXTMXJyIiIiJphkK6iEgysbODXr2M+eqffGJs0TZjBhQtCvPnQ1SUuSsUEREREUunkC4iksycnWHuXDhyBGrVgr//NkJ7hQqwf7+5qxMRERERS6aQLiKSQsqVg717Yc0acHWFY8eM0N6qFVy9aubiRERERMQiKaSLiKQgKyto2RLOnYPhw8HBwQjtJUrAyJHw6JG5KxQRERERS6KQLiKSChwdYcQII6y3bGmE8xEjjLD+/feQ9jbDFBEREZGUoJAuIpKK3NyMnvS9e6FsWWPYe8uW8NZbcOKEuasTEREREXNTSBcRMYPatcHPD+bMgezZjdDu4QHduxsLzYmIiIjI60khXUTETGxsoGtX8Pc3tm6zsjJCe7FiMGsWREaau0IRERERSW0K6SIiZpYtm7Gf+vHj8PbbcOeOEdrLlYNdu8xdnYiIiIikJoV0ERELUaoU/PgjrF8PBQvC6dNGaH/vPbh0ydzViYiIiEhqUEgXEbEgVlbQrBmcOQNjx0KGDEZof+MN8PGB0FBzVygiIiIiKUkhXUTEAjk4wODBcP48tG4NYWEwbhwULw4rV6b8lm0PHz5k9OjR1KhRgwoVKtCpUycuXrwY77Vt2rShePHi8R6HDx8G4OLFi3Ts2JHy5ctTpUoVhg0bxj///JOyDyEiIiKSBlnFxKS93Xn9/Pzw9PQ0dxkiIqnm4EFjnrqvr/G6WjWYORNS6q9CHx8fjhw5wpgxY8iaNSvTpk3j9OnT7Ny5k3Tp0plce/fuXSIiImJfR0dH07VrVzJmzMjixYsJCwvjnXfeoXLlynTv3p379+8zZMgQChYsyOzZs1PmAURERETSKPWki4ikAVWrwqFDsGgRuLjAb79BxYrQqRMEBSX/5/388898/PHHeHp6UrhwYfr27cuNGzfi7U3PmjUrzs7OscfGjRsJDAxk2rRp2Nracv36dTw9PRk9ejSFCxfGw8ODli1bcvDgweQvXERERCSNU0gXEUkjrK2hQwe4cAE+/xxsbeGbb4wt26ZOhfDw5PssJycntm3bxu3btwkPD+eHH34gS5YsuLq6Pvd9wcHBzJkzh759++Ls7AxA0aJFmTFjBo6OjgBcunSJjRs3Ur169eQrWEREROQVoeHuIiJp1IUL0LcvbNtmvC5eHL78Eho2fPl7+/r60r9/f65fv46NjQ0ODg4sWrSIcuXKPfd948aNY/fu3ezcuRMbG5s455s2bcq5c+fImzcvq1atIleuXC9frIiIiMgrRD3pIiJpVLFisHWrcRQrZiwy16gRNG5sBPiXceXKFXLkyMH8+fNZvXo1NWrUoFevXty8eTPB94SGhrJ27Vo6deoUb0AHI8SvXLmSnDlz0rZtWx49evRyhYqIiIi8YhTSRUTSuEaN4ORJmDIFMmUyetZLl4b+/eH+/aTfLzAwkKFDh+Lj40Pt2rUpW7YsU6dOJV26dCxZsiTB9+3atYuoqCiaNGmS4DWlSpWiQoUKzJw5k8DAQH7++eekFygiIiLyClNIFxF5BdjbQ79+4O8P//sfREYaob1YMVi8GKKjE3+vU6dOERUVRenSpWPb7OzseOONN7hy5UqC79u1axd16tQhQ4YMJu1//fVXnDCeM2dOsmbNSlBKrHonIiIikoYppIuIvEJcXIzF5P74w1gRPijICO2VKxvbuCXGk3ni58+fj22LiYkhICCAAgUKJPi+I0eOUKVKlTjtJ06coFevXvz999+xbYGBgYSEhFCkSJHEFSUiIiLymlBIFxF5BVWoAL/+CitWQJ48xv7q1apBmzZw/frz3+vu7o6HhwcDBw7E19eXgIAAhg8fzvXr12ndujXh4eEEBwcT/sxy8rdu3SI4OJhixYrFud+bb76Jq6srn3/+OefPn+fIkSP07t0bDw8PatWqldyPLiIiIpKmKaSLiLyirKzA29tYUG7wYEiXzgjtxYrB+PHw+HH877OxseHrr7+mbNmyfPbZZ3z44YdcvXqV1atXkzdvXo4ePUqNGjU4evRo7HuCg4MBY8/0f0ufPj3ffPMNGTJkoHXr1nTt2pUSJUqwYMECrK31nyERERGRZ2kLNhGR18Sffxrz1jdsMF4XKmTsr960qRHoRURERMT81IUhIvKaKFQI1q+Hn36CUqWM0N68ObzzDpw5Y+7qRERERAQU0kVEXjtvvw3HjsHMmZA1qxHa3d2hd2+4c8fc1YmIiIi83hTSRUReQ7a28OmnxpZt3bpBTIwR2osWhblzISrK3BWKiIiIvJ4U0kVEXmM5csDXX8ORI1C7Nty+bYR2T0/45RdzVyciIiLy+lFIFxERypaFPXvgu+8gf344ftwI7R9+CFevmrs6ERERkdeHQrqIiADGCu8ffADnzsHIkZA+vRHaS5QwXj98aO4KRURERF59CukiImIifXoYNswI6x9+CI8ewYgR8MYbRmhPext3ioiIiKQdCukiIhKv/Pnh229h3z4oV84Y9v7hh/Dmm8ZweBERERFJfgrpIiLyXLVqga8vzJtnLDS3bx+ULw9du8Lff8PKlVCgAFhbG3+uXGnuikVERETSLquYmLQ3cNHPzw9PT09zlyEi8tq5c8eYnz57trFNW/r0EBkJERFPr3F0hPnzwdvbfHWKiIiIpFXqSRcRkUTLlg2mT4cTJ6BePWO++rMBHYwF5nx8zFKeiIiISJqnkC4iIklWsiTs3GmsCB8fbdsmIiIi8mIU0kVE5IVYWRmLy8XHxSV1axERERF5VSiki4jICxs71piD/m83bxpD3sPCUr8mERERkbRMIV1ERF6Yt7exSJybm9Gz7uoKjRoZP48bBxUrwrFj5q5SREREJO1QSBcRkZfi7Q2XL0N0tDEXfetW2L8fihSBkyeNoD56dNwF5kREREQkLoV0ERFJdtWrGz3oPXsaW7QNGwZVq8Lp0+auTERERMSyKaSLiEiKyJABZs2CXbuM4fB+flC+PEyaZOyxLiIiIiJxKaSLiEiKeustY1/1zp0hPBwGDICaNeHCBXNXJiIiImJ5FNJFRCTFZc5sLDC3bRvkyQMHD0K5cjBzpjGXXUREREQMCukiIpJqGjaEU6egTRt49Ah694a6deHSJXNXJiIiImIZFNJFRCRVZcsGy5bBhg2QMyfs3Qvu7kZPe0yMuasTERERMS+FdBERMYumTY3V3j/4AEJD4ZNPjJ72v/4yd2UiIiIi5qOQLiIiZpMjB3z3HXz7LTg5wc6dULo0LF2qXnURERF5PSmki4iI2X34odGr7uUF9+5B+/ZGT/vNm+auTERERCR1KaSLiIhFyJXLmKe+ZAlkyQKbN0OpUrBmjbkrExEREUk9CukiImIxrKygXTtjBfj69SEkBFq1gpYt4e+/zV2diIiISMpTSBcREYuTLx/s2AHz5kHGjPD990av+oYN5q5MREREJGUppIuIiEWysoIuXeDECahdG27dgubNoW1buHPH3NWJiIiIpAyFdBERsWgFC8Lu3TBjBqRPD8uXGyvA79hh7spEREREkp9CuoiIWDxra+jVC44dg6pV4fp1Y0/1zp3h/n1zVyciIiKSfBTSRUQkzShWDPbvh4kTwd4eFi4Ed3ejp11ERETkVWBRIf3hw4eMHj2aGjVqUKFCBTp16sTFixfNXZaIiFgQGxv44gs4cgQ8PeHKFahbFz79FB48MHd1IiIiIi/HokL62LFj+e2335gxYwZr1qwhXbp0dOrUibCwMHOXJiIiFqZUKTh4EEaNAltbmD0bypWDX381d2UiIiIiL86iQvrPP//Mxx9/jKenJ4ULF6Zv377cuHFDvekiIhIvOzsYOhT++APKlIGLF6FmTejfHx4/Nnd1IiIiIklnUSHdycmJbdu2cfv2bcLDw/nhhx/IkiULrq6u5i5NREQsmIcHHD4MgwcbW7dNmQLlyxttIiIiImmJVUxMTIy5i3jC19eX/v37c/36dWxsbHBwcGDRokWUK1fO5Do/Pz88PT3NU6SIiFi0P/6Adu3g3Dlj/vrAgTBsmLHQnIiIiIils6ie9CtXrpAjRw7mz5/P6tWrqVGjBr169eLmzZvmLk1ERNKISpWMReU++wyio2HsWKPt+HFzVyYiIiLy3ywmpAcGBjJ06FB8fHyoXbs2ZcuWZerUqaRLl44lS5aYuzwREUlD0qeHqVNh3z4oXNgI6BUrwpgxEBlp7upEREREEmYxIf3UqVNERUVRunTp2DY7OzveeOMNrly5YsbKREQkrapZ0wjoPXpARISxyFzVqnDmjLkrExEREYmfxYT0XLlyAXD+/PnYtpiYGAICAihQoICZqhIRkbQuQwZje7aff4b8+cHX11hUbsoUiIoyd3UiIiIipiwmpLu7u+Ph4cHAgQPx9fUlICCA4cOHc/36dVq3bm3u8kREJI2rWxdOnoSOHSEszNimrVYt8Pc3d2UiIiIiT1nU6u4hISFMmzaNX375hYcPH1K6dGkGDhxIiRIlTK7T6u4iIvIytm6Fzp3hxg1j/vqkSdC9O1gnw1fXhw4dom3btvGeq1y5MsuWLUvwvVevXsXLy4sdO3bEjjBbt24dgwYNivf69957j/Hjx7980SIiImIxLCqkJ5ZCuoiIvKyQEOjVC1auNF6/+SYsWgQvO8MqPDyce/fumbT9+uuvDBo0iPnz51OzZs1433fp0iU6d+5MYGAg+/btiw3pjx8/5p9//jG5du3atcyZM4c1a9bE+SJbRERE0jaLGe4uIiKSmpycYMUKWLcOnJ1hzx4oUwYWLICX+fra3t4eZ2fn2MPBwYEpU6bQsWPHBAP60qVLadGiBZkzZ45zzsHBweR+jx8/Zu7cufGONBMREZG0TyFdRERea82bw+nT0KIFhIZCly7QqBFcu5Y89//666+xt7enR48eCV7zyy+/MGbMGAYMGPCf95s8eTJFixblww8/TJ4CRURExKIopIuIyGvP2Rm+/x5WrYJs2WDHDihdGpYvf7le9du3b7NixQp69OhB+vTpE7zum2++oVGjRv95v3PnzrFz50769euHdXJMoBcRERGLo//Ci4iIAFZW8NFHRq/6u+/C3bvQtq3R0x4U9GL3XL16NdmzZ8fLyytZaly6dClly5alSpUqyXI/ERERsTwK6SIiIs/InRs2bTIWkcucGTZuhFKljJ72pNq0aRPvvfcednZ2L11XWFgYO3bs0DB3ERGRV5xCuoiIyL9YWUGHDnDqFNSrB7dvQ8uW0KoV/P134u7h7+/PlStXaNy4cbLUdPDgQSIiIqhXr16y3E9EREQsk0K6iIhIAlxdYedOmDMHMmSANWuMueqbNv33e319fXF2dqZw4cLJUouvry+lSpWKdwV4EREReXUopIuIiDyHlRV07QonTkCtWsb89KZNoV07Y956Qs6ePUuxYsXitIeHhxMcHEx4eHiS6kjofiIiIvJqUUgXERFJhEKFjL3Uv/wSHBxg2TKjV33nzvivv3XrFlmzZo3TfvToUWrUqMHRo0eT9PkJ3U9EREReLVYxMS+zuYx5+Pn54enpae4yRETkNXX+PLRvD7//brzu0gWmTIFMmcxaloiIiLwC1JMuIiKSRMWLw/79MH482NvD/Png7g5795q7MhEREUnrFNJFRERegK0tDBwIfn7g4QGXL8Obb0KvXvDwobmrExERkbRKIV1EROQllC4Nhw7BiBFGcJ81C8qVg99+M3dlIiIikhYppIuIiLwkOzsYPtwI66VLg78/1KwJX3wBjx+buzoRERFJSxTSRUREkkn58uDrawyDB5g8GTw9jTYRERGRxFBIFxERSUbp0hkLyv36KxQrBmfOQJUqMGwYJHFrdBEREXkNKaSLiIikgCpV4OhR6NsXoqNh9GioXBlOnDB3ZSIiImLJFNJFRERSiKMjTJtmbM1WsCAcOwYVKsDYsRAZae7qRERExBIppIuIiKSwWrWMHvRu3SAiAoYMgWrV4OxZc1cmIiIilkYhXUREJBVkzAhffw0//giurnD4sLG/+scfg5sbWFtDgQKwcqW5KxURERFzUkgXERFJRfXqwcmT0KEDhIXB6tVw9SrExMCVK9Cli4K6iIjI68wqJiYmxtxFJJWfnx+enp7mLkNEROSl5MwJwcFx23PkgMuXIUOGVC9JREREzEw96SIiImby998Jt+fIAU2bwuLFCV8nIiIirx6FdBERETPJnz/+dnt7ePwYNm2C//0PXFygTh2YPt3oYX9Vff/997zzzju4u7vz3nvvcfDgwUS975NPPqFNmzaxr9etW0fx4sXjPQYNGpRS5YuIiCQLhXQREREzGTvW2KbtWY6OsGgRXLsGc+ZA/frGonL79hl7rhcsaCw4N3KksWJ82pu0Fr/169czcuRIOnfuzObNm6lYsSLdu3fnr7/+eu77vv32W/bu3WvS1qhRIw4cOGBy9O3bFwcHB9q1a5eCTyEiIvLyNCddRETEjFauBB8fY/G4/PmN4O7tbXrN3buwfTusX2/8GRr69FzBgtCsmXFUrw42NqlYfDKJiYmhbt26NG3alN69ewMQHR1N8+bN6dSpE02aNIn3fVeuXKFly5YULFgQOzs7li9fHu91gYGBNGnShAEDBvDRRx+l2HOIiIgkB4V0ERGRNOTxY9i92wjsmzbBrVtPz+XIAV5e0Lw5vP02ODiYr86kCAgIoFGjRmzZsoWiRYsm6j1RUVF4e3tTt25dLl++zNWrVxMM6b169eLGjRusWbMGa2sNIhQREcum/1KJiIikIQ4O0KgRLFgA16/DgQPQrx8UKmQsMLdoETRpYgT29983eurv3DF31c93+f8n2t+/f5+2bdtStWpVvL29OXLkSILvmTdvHgAdO3Z87r3PnTvHzp076devnwK6iIikCfqvlYiISBplY2MMcZ8yBS5eNPZfHzUKypeHBw9g7Vpo3drY6q1ePfj6a2Ouu6UJ/f/x+wMHDuSDDz5g4cKFFC1alHbt2hEQEBDn+tOnT7N48WImTpz4n8F76dKllC1blipVqqRI7SIiIslNIV1EROQVYGUFpUvD0KHg52esAj9jBrz5prG43M8/Q48ekC8fVKoE48fD2bOWsfCcnZ0dAF27dqVJkyaUKlWK4cOHU6BAAVavXm1ybVhYGP3796dPnz64ubk9975hYWHs2LGDDz/8MMVqFxERSW4K6SIiIq8gNzfo1cuYvx4UBEuWGIvLpU8Phw/D4MFQsiSUKAEDB8Lvv0N0tHlqzZkzJwDFihWLbbOysqJQoUJxVnc/fvw4AQEBTJkyBQ8PDzw8PNiwYQO+vr54eHhw/fr12GsPHjxIREQE9erVS50HERERSQa2ibkoIiKCI0eOcPz4cf7++29sbGxwdnbG3d0dT09PrKysUrpOEREReUHZs0O7dsbx8CH8+CNs2ACbN8OFCzBxonHkzg1Nmxph/s03jf3aU0OpUqVwdHTk5MmTlClTBjBWfA8ICKBq1aom17q7u/Pjjz+atE2bNo3r168zZcqU2MAP4OvrS6lSpcicOXPKP4SIiEgyeW5Iv3//PkuWLGHVqlXcv3+ffPny4eTkRGRkJHfu3GHy5MlkzZoVb29v2rZtq/8IioiIWDhHx6dbtkVGwv79RmDfsMHYBm7uXOPInBkaNzaua9gQMmVKuZrSp09Pu3btmD59Ojly5KBYsWKsWrWKq1evMnPmTMLDw7l37x5ZsmTBwcEhzjD3jBkzxtt+9uxZk955ERGRtCDBkL5z507Gjx9P+fLlGTVqFLVq1cLhX3u53L9/n0OHDrF+/XoaNWrEkCFDaNCgQYoXLSIiIi/P1tboMX/zTZg+HY4efRrYT56E1auNw97e2NKtWTNjizcXl+SvpXfv3qRPn55x48Zx+/Zt3njjDRYtWkShQoU4dOgQbdu2ZdmyZVSuXDnR97x16xYlS5ZM/mJFRERSUIL7pH/22Wf069ePvHnzJupGV69eZdq0aUyfPj0564uX9kkXERFJWQEBTwP7r78+XWDOygqqVXvaG1+kiPlqFBEReRUlGNItmUK6iIhI6gkKMuavb9gAP/0E4eFPz5Uu/TSwly9vhHgRERF5cUkO6eHh4Vy+fJmYmBgKFiyIfWqtKvMMhXQRERHz+Ocf2LHDCOxbtsD9+0/Pubo+Dey1ahnD6UVERCRpkhTSf//9dz7//HNiYmKIjIzE2tqaSZMmUbNmzZSsMQ6FdBEREfMLD4e9e58Oi79x4+k5Jyd4910jsL/zjrFgnYiIiPy3JIX0Jk2aMHbsWNzd3QHYtGkT06dPZ/fu3SlWYHwU0kVERCxLdLSx//qGDbB+PZw///Rc+vRQv74R2Js0MbaEExERkfhZJ3Tif//7H6dOnTJpi4yMxMbGJva1ra0tkZGRKVediIiIpAnW1lC5MowfD+fOwdmzxs+VK8OjR7BxI3ToADlzGqvJz5gBV66Yu2oRERHLk2BP+k8//cSMGTMoVKgQffr0oVChQuzbt4+BAwdiY2NDdHQ0UVFRjBkzhnr16qVq0epJFxERSTuuXYNNm4xe9t27jf3Zn/DwMHrYmzc3FqHTwnMiIvK6e+5w9+joaNauXcucOXOoXLkyn376KTly5CAgIAArKysKFCgQZ+/01KCQLiIikjbdvQvbthmBfds2ePDg6blChZ4G9qpV4ZnBeyIiIq+NRM1JDw8PZ9myZSxZsoRGjRrRtWtXnJycUqO+eCmki4iIpH2PH8OuXUZg37gRgoOfnnN2Bi8vI7DXrQtm6BMQERExiwTnpAMEBASwc+dO/P396dSpE9u2bSNdunQ0adKEmTNnEhoamlp1ioiIyCvGwQEaN4YFC4yV4ffvh379jB714GD45htjhfgcOeCDD2DVKqMnfuVKKFDAmAdfoIDx+nXn7+9P8eLF4xy+vr7xXv/LL7/w3nvv4eHhQZMmTdiyZYvJ+UePHjF06FAqV65MhQoVGDJkCA+eHfYgIiIpJsGe9KVLlzJz5kyKFCnC5cuX8fLywsfHB4CgoCC++uordu/eTYcOHejYsWOqFq2edBERkVdXTAycOvV0pfijR5+es7Iyjujop22OjjB/Pnh7p3qpFmPbtm2MGjWKzZs3m7RnzZoVOzs7kzY/Pz+8vb1p06YNrVq14syZMwwfPpxhw4bRrFkzAPr378/p06cZN24ckZGRDB48mDJlyjB16tTUeiQRkddWgiG9evXqfPXVV5QrV47g4GDefPNNfv/9dzJmzBh7zaVLl5g+fTozZsxItYJBIV1EROR1cuWKMRx+/XpjX/b4ZM8Ofn7g5paqpVmM6dOn4+vry4oVK/7z2u7du3Pnzh1Wr14d2zZnzhy+//57du/eTVBQEHXq1GHJkiVUrlwZgD/++IO2bduyb98+XFxcUuw5RETkOcPdra2tuXfvHgD//PMPMTExJtuvARQsWDDVA7qIiIi8XtzcoFcv2LMn4dXfb982hr4XKADt28PixfDnn0av/OvA39+fQoUKJeraK1euUKFCBZO2kiVLcu3aNa5fv46fnx/W1taUL18+9nz58uWxsbHBz88vWes2t6RME2jTpk281xYvXpzDhw8DEBwcTN++falSpQrVqlVj9OjRPHz4MLUfS0TSONuETvTr148+ffqQMWNG7t+/T+/evUmfPn1q1iYiIiJiIn/++PdXT58e0qUzzi1dahwArq5Qu/bTo0iRV3ObN39/f8LCwmjZsiXXrl2jaNGifPbZZ7i7u8e5NmfOnNy4ccOk7a+//gLg9u3bBAUF4eTkZDJM3tbWFicnpzjvS+v8/f3Jli1bvNME/m3WrFlERETEvo6OjqZr165kzJgRDw8PIiIi+N///oeVlRVfffUVDg4OjB49mu7du7NkyZIUfhLz8Pf35913343TvnLlyjhfBLVp04Y//vgj3vusWLGCwMBABg0aFO/59957j/Hjx798wSJpRIIhvVmzZtSpU4erV6+SJ08ecuTIkZp1iYiIiMQxdix06QLPdk4+mZPeqhWcOAH79hnHL79AYCCsWGEcAHnyPA3sdepAsWJpP7Q/fvyYwMBAnJyc+OKLL7C3t2fFihW0bt2a9evXU7hwYZPrmzZtio+PD2+99Rb169fH39+fRYsWARAREcGjR49Ily5dnM+xt7cnLCwsVZ4ptVy4cIEiRYrg7Oz8n9f+O7jPnz+fwMBAtm/fjq2tLT///DMXLlxg586dFChQADCmIdSpU4c//viDSpUqpcATmFdyfslRpkwZatasafKeJ1tBt2vXLkXqF7FUCYb0e/fukTVr1nj/nywhd+/eTdL1IiIiIknxZHE4Hx+4etXoWR879mm7h4dx9OljLC536tTT0L5vH1y/DqtXGweAi8vTwF67NrzxRtoL7Q4ODhw+fBh7e3vs7e0BmDBhAqdPn2bVqlUMHTrU5PpmzZpx7do1Bg0aRL9+/cidOzcdO3Zk1KhRZMqUCQcHB8LDw+N8Tnh4OI6OjqnyTKklKdMEnhUcHMycOXP4/PPPYwP+5cuXcXZ2jg3oALly5SJbtmyvbEhPzi85bG1tcXhmr8XAwEDmzp3LwIEDKVGiRHKXLmLREgzprVq1omXLlrRq1eo/h7nfv3+f1atXs379enbs2JHsRYqIiIg84e2duJXcra3B3d04Pv3UmJ9+5szTwL53LwQFwXffGQcY+7PXqvU0tJcqZdzH0j27sC8YawsVKVIkweHpPXr04JNPPuH27dvkzJmT3bt3Y2NjQ548eciVKxchISFERUXFrkcUGRlJSEgIOXPmTPFnSU1JmSbwrAULFpA9e3ZatWoV25YzZ07u3r3Lw4cPY7/MCA0N5d69e4SEhKToc5hLcn7J8W+TJ0+maNGifPjhhy9bpkiak+B/dlavXs25c+eoVq0avXv3Zt26dZw4cYLAwECuXr3KsWPHWLVqFb1796Z27dpcvHiRVatWpWbtIiIiIolmZWWE7u7dYc0auHkTzp6FuXONofK5cxv7s69da4R6d3fImRPeew9mzIBjx0y3frMUp06donz58pw+fTq2LSoqinPnzlG0aNE4169YsYKxY8dia2uLi4sLVlZW/Pzzz3h4eJAhQwY8PT2JjIzk6DN73/n5+REdHf1K7a7zZJpAaGgoX3zxBXPmzCFnzpy0bt2agICABN8XGhrK2rVr6dSpk8miyrVq1SJjxowMHTqU+/fv888//zB8+HCsrKxMhnm/Svz9/bl+/TotW7akevXqtG/fnhMnTvzn++L7kuNZ586dY+fOnfTr1w/rtPAtmUgyS3ALticCAgJYunQpe/bsITg4GKv/HwMWExODi4sLb775Jq1bt6ZIkSKpUjBoCzYRERFJfjExcPHi0172ffvg/9dTi5U1q9HT/mRee7ly8K/Nb1JdZGQkzZs3x87OjuHDh+Po6MiCBQvYu3cv27dvJ1OmTNy7d48sWbJgb2/Pb7/9RufOnRk3bhyenp5s3bqVWbNmsWjRotgh2X379uXMmTOMGzeOmJgYBg8eTPny5ZkwYYJ5HzaZhYaGmkwTiI6OpkmTJlSpUiXONIEnNm7cyPDhw/n111/JkCGDybmjR48ycOBArly5goODA61bt+bgwYNUqlSJAQMGpPjzpKbHjx/j4eFB2bJl+fzzz2PXQtixY0e8ayE8ERoaSu3atenfv3+CIX3QoEEEBATw3ZMhLiKvmf8M6c+6ceMGf//9N1ZWVjg7O5ttn0yFdBEREUlpMTFw6dLTwL5vX9yV5TNnhpo1n4b28uXBNsHJhCknKCiISZMm8dtvv/Ho0SPKly/PwIEDKVasGIcOHaJt27YsW7Ysdt/z77//nvnz53Pr1i2KFi1K7969TRbtevDgAWPGjOHHH3/E1taWd955h8GDB5vMGX5V9e7dm4iICL7++ut4z/fq1Qtra2umT5+e4D1u375NhgwZcHBwoHLlyvTp04ePPvoohSo2n+T+kgMgLCyMKlWqMGTIEFq0aJGi9ZtbUlbHB7h58ybjxo1j//79ODg48M477zBgwIDYqcmPHj1i3Lhx/Pjjj0RFRdGgQQMGDRoU7+9ZLFuS/jOSO3ducufOnVK1iIiIiFgMKysoVMg4/vc/o+3yZdOF6P78E7ZuNQ6ATJmgevWni9F5esIzO5mlGBcXF6ZOnRrvucqVK3P+/HmTtg8++IAPPvggwftlyJCB8ePHv9LbXp06dYq2bduyfPlySpUqBTydJtCgQYME33fkyBF69uwZp/3y5csMGjSIOXPmkD17dgAOHz7M/fv3qVatWso8hJkldS0EgF27dlGnTp0Eg+PBgweJiIigXr16yVqrJUrK6vjh4eF06NABZ2dnVq9ezd27dxk4cCDW1tYMGzYMgGHDhnH69GnmzZtHZGQkgwcPZtiwYQn+3SCWS5M8RERERBKpQAFo1w4WLYKAAGOF+eXLoVMnYw/2f/6BHTtg0CCoWhWyZYP69Y0V6H/9FeJZNF3MpESJEuTNm5ehQ4dy/Phx/P39GTRoEHfu3KFt27aEh4cTHBxsstL9rVu3CA4OplixYnHuly9fPoKCghg9ejRXrlzh999/p1+/frz//vu4ubml5qOliqSuhfDEkSNHqFKlSoLnfX19KVWqFJkzZ07Wei3Rs6vjP3vYxfPN3ubNmwkODmbWrFmUKFGCKlWq0LNnz9g1AIKCgtiyZQvDhw+nXLlyVKhQgTFjxrB161aCgoJS+9HkJSmki4iIiLwgV1do3RoWLAB/f7h2DVatgk8+geLF4cED+OknGDIEatQw5rTXrQujRxv7uL9i246nKba2tixcuJCCBQvStWtXPvjgA/7++29WrFhB9uzZOXr0KDVq1DBZQC84OBiIv6fT1taWefPmERwcTLNmzRgwYADNmzdn+PDhqfVIqSq5v+R44uzZs889/ypJyur4Bw4coFq1amTJkiW27f333+eHH34AjOnA1tbWlC9fPvZ8+fLlsbGxwc/PL3kLlxRnhllTIiIiIq+mPHngo4+MA4wV5H/55em89jNnYPdu4wBIl87ocX8yp71KFfiPnW8lGSV1mkCpUqXitD2raNGiLFu2LFlrtFRPvuSYNGkSXbt2jV0L4cmXHPGthfC8LzmeuHXrFiVLlkyNRzC7pGwBePnyZapUqcL06dPZtGkTVlZW1K9fnz59+pAuXTqCgoJwcnIy6YW3tbXFycnpudMPxDIlKaSHhoby559/Ymdnh6ura5x5KMnh+++/Z+HChdy4cYMiRYrQv39/qlatmuyfIyIiIpLScuWCli2NA4wt3p4N7SdPGj/v3Wuct7eHypWfhvZq1eD/t9wWsTjJ/SUHEGd+9qvqyRaATk5OfPHFF7Gr47du3Tre1fFDQ0P54YcfqFWrFjNmzIidWhESEsLEiRN59OgR6dKli/M59vb2hGnITpqTqJAeFRXF+PHj+fbbb4mKiiImJgZ7e3tatmzJ4MGDk23/wvXr1zNy5EhGjBhBxYoVWbVqFd27d2fz5s3ky5cvWT5DRERExFycnaFFC+MA+Ptv2L//6UJ0x48br/fvhzFjjEXnKlZ8GtqrV4cU6CMRkVTm4ODA4cOHTVbHnzBhAqdPn2bVqlVxVse3tbUlS5YsTJo0CRsbG8qUKUNkZCS9e/dm4MCBODg4mEwteCI8PBxHfdOX5iQqpM+ZM4fNmzfj4+NDxYoViYqKwtfXl1mzZpEjRw66du360oXExMQwa9YsOnfuzPvvvw/AgAED+P333zl69KhCuoiIiLxycuSA5s2NA+DOHdPQfvQo/PabcYwfb+zJXqHC09Xjq1c3toETkbQnKavju7i4kC5dOmxsbGLbihQpAsC1a9fIlSsXISEhREVFxV4TGRlJSEgIOXPmTMGnkJSQqJC+du1aRowYQcOGDWPbihcvjpOTE1OnTk2WkP7nn39y7do1GjVqFNtmbW3Nxo0bX/reIiIiImlBtmzg5WUcAPfuwYEDRmDfuxeOHIFDh4xj0iSwtjb2Zq9TxwjuTxanExHLltQtACtUqMB3331HRERE7LzzCxcuYGNjQ968eXF2diYyMpKjR4/G7rHu5+dHdHQ0np6eqfdgkiwSNU79zp078S7gULJkyWRb0v/y5csA3L9/n7Zt21K1alW8vb05cuRIstxfREREJK3JkgUaNzYC+R9/GD3t27fDgAHGInPW1uDrC1OmQJMm4ORkhPbPPoONGyEkxNxPICLxSerq+K1atSIsLIyBAwcSEBDAb7/9xuTJk2natCnZsmXDxcWFhg0b4uPjg5+fH76+vgwdOpSmTZvi4uJi5qeVpEpUSC9cuDC7du2K0/7TTz9RoECBZCkkNDQUgIEDB/LBBx+wcOFCihYtSrt27QgICEiWzxARERFJyzJlggYNYMIEOHjQCO0//giDBxtD321tjSHyX34JzZoZw+nLlYPevWHdOmMO/MqVxn7v1tbGnytXmveZRF5HSd0CMEeOHKxcuZK7d+/y3nvv0a9fP+rXr8/IkSNj7zlmzBjKly9Ply5d6NGjB1WqVGHEiBFmekJ5GVYxMTEx/3XRrl276NWrF40aNcLDwwMwhk/s2LGDiRMn8u677750Idu2baNv376MGzeOFv+/mkpMTAxeXl5UrlyZIUOGxF7r5+enYRsiIiIi//LwoRHen8xp//13+PdaUlZW8Oy//tKlgy++MBazy5TJWJguUyZwcDCuFRGR1JWoOel169blyy+/ZMGCBfz000+kS5eOIkWKMG/ePGrUqJEshTxZ0KBYsWKxbVZWVhQqVIi//vorWT5DRERE5FXm6Ah16xoHwKNHxvz1J6F9zx7TgA4QFgajRxvHs2xsngb2f/+Z0M/PO58hg9F7LyIiz5fofdLr169P/fr1U6yQUqVK4ejoyMmTJylTpgxg9KQHBARon3QRERGRF5A+vbGoXJ06xmtr67gh/YkyZeCffyA01PgzLMxYuO7eveSrJ0OGpIf85wV/20T/S/blrVwJPj5w9Srkzw9jx4K3d+p9voi8PhL9V9uuXbu4cOECUVFRsW3h4eGcPHmSxYsXv3Qh6dOnp127dkyfPp0cOXJQrFgxVq1axdWrV5k5c+ZL319ERETkdZc/P1y5ErfdzQ1OnDBti4h4Gtif/Pnsz/G1Pe/8gwdPj5s3k+d5HBxerHc/offY28c/xH/lSujSxZhOAMbvsEsX42cF9cTRlxwiiZdgSP/kk09o3rw5DRo0YNKkSSxevJjcuXNz48YN8uTJQ3BwMBEREXg92SMkGfTu3Zv06dMzbtw4bt++zRtvvMGiRYsoVKhQsn2GiIiIyOtq7FjTsAnGEPmxY+Nea2dnbAmXLVvyfHZUlBHQXzTkx3f+8WPj+Pvv5KnR1jb+EP/bb8bUgWc9fAjdusHx48bUAGtr0+Pfba/CNc++trJK/JoF+pJDJGkSXDjul19+oUePHhw+fJh69erRvXt3PvroI+rUqcOKFSvImjUrPXr0oFy5cvTt2zdVi9bCcSIiIiIv5lXp0YyJMYJzUkL+fwX/iAhzP1XaYmWVuPB/+zZER8d9f8aM0LMnZM/+9HByMv05Nac0iFiKBP9nHxISQvny5XFwcODOnTvUqlULgOLFi3PixAkaNWpEnz59GDBgQKqHdBERERF5Md7eaTOU/5uVlTEKwNERkmsb6PDw+EO8t3f8vfVZs8LAgUYAfXJERZm+jq8tpa5Jzc+OiTGOyMgX/32HhhrbCT5PliwJh/iEjowZtTOBpG0JhvQpU6Ywf/58ALJmzcq9e/fImzcvBQoU4MKFCzRq1IicOXMSFBSUasWKiIiIiKQUe/unQe9Z06fHP01g9uxX4wuPFxETk/iw7+kJ167FvYeTE3z2mdHTHt9x587TxQv//DPxtdnZPT/Mx3fOycn4v7+IJUgwpL/zzjt06NCB7du3U7NmTUaNGsXYsWOpUKECEyZMoEGDBmzduhWX5PrqUkRERETEAj0J4q/CNIHk8mSou43Nf187cWL8X3LMnPn832F0NNy9m3CIDwmJv/3hQwgKMo6kyJQpaT32Tk5GT7967SW5JTgnHeDu3btkzpyZf/75hwEDBlCzZk0++ugjOnfuzK+//oqtrS3jx4+nSZMmqVmz5qSLiIiIiKQhqbkWwuPHzw/x8YX8kBCj5z+pbGwSDvTPC/rp0iXtc16VtSQkcZ4b0p/n3LlzODk5kTNnzuSu6T8ppIuIiIiISHKJjob79xPfW//kCA19sc/LkCHxvfW//gpDh5ruMODoCPPnK6i/qhIV0kNDQxk2bBiFChWiZ8+eANSuXZtKlSoxatQo0qdPn+KFPkshXUREREREzC08/PlBPqFzL7Pg3hNubnD58svfRyxPojY1GDduHP7+/rRv3z62bezYsUycOJHJkyczbNgwrl27Rt68eVOqThEREREREYtibw+5chlHYsXEGLsGJHZI/uHD8d/n6lVjiH5i1gWQtCVRIX3v3r3MmzePMmXKxLbVqFGDjBkz0qFDB5ydnZkxYwatW7dmyJAhKVasiIiIiIhIWmZlBZkzG0fBgv99fYECcOVK3PaYGChRAvr1g3btIJUHN0sKsk7MRWFhYdjHsydBhgwZePToEatWrWLevHls2LAhuesTERERERF5bY0da8xBf5adHeTIARcvQrduxmJyI0fC33+bp0ZJXokK6RUrVuTLL7/kwYMHsW2PHj1i9uzZVK9enW3btlGmTBnSJXWZQhEREREREUmQt7exSJybm9EL7+YGixfDjRuwZg1UqGCE8xEjjLDeo4cR3iXtStTCcVeuXKF169Y8evSIQoUKAXDp0iUyZMjAN998Q+HChVO80Gdp4TgRERERERFj2Pu+fTB5MmzbZrRZWcF770H//lC5snnrk6RL9BZs//zzD1u3bsXf3x9bW1sKFy5MkyZNUn1ld1BIFxERERER+bfTp2HqVFixAiIijLaaNeHzz+Hdd8E6UeOoxdxeeJ/0J8LCwlJ9mLtCuoiIiIiISPyuX4eZM2HuXLh3z2h7sshc69bg4GDe+uT5EhXS79y5w9y5c7lw4QJRUVEAxMTEEBERwcWLF/H19U3xQp+lkC4iIiIiIvJ8//wDCxbA9OkQGGi0ubhAr17GgnPZspm1PElAogY8DB8+nC1btuDi4oKvry958uQhIiKCY8eO0bVr15SuUURERERERJIoUyb47DMICDCGwJctC0FB4OMDrq7QuzdcvmzuKuXfEhXSDx48yIQJE5gwYQKFCxemXbt2fPvtt3z88cecPXs2pWsUERERERGRF2RnZ6wSf/Qo/Pgj1KsHDx4YQ+KLFIGPPoIjR8xdpTyRqJD+6NEjihQpAkDBggU5c+YMAB999BGHDx9OuepEREREREQkWVhZGQH9xx/h2DFjfrqVFXz7LXh6Qt26sH27sWK8JTl27BglS5bk0KFDCV5z8+ZNevXqhYeHB1WrVmXEiBE8evQo9vzevXspXrx4nOPmzZup8QhJkqiQnjdvXv7880/ACOlPes9tbGy4f/9+ylUnIiIiIiIiya5sWVi+HP780xgSnzEj7N4NjRqBuzssXQrh4eauEh4+fMgXX3wRuzZafMLDw+nQoQN3795l9erVfPnll+zdu5fJkyfHXnPhwgVKlizJgQMHTI6cOXOmxmMkSaJCetOmTenfvz+//PILb775JmvXrmXJkiWMGzeO4sWLp3SNIiIiIiIikgJcXY1t2wIDYcIEyJ0bTp2C9u2hUCFj//UnK8Sbw4QJE3BxcXnuNZs3byY4OJhZs2ZRokQJqlSpQs+ePTlx4kTsNf7+/hQrVgxnZ2eTw9oC96VLVEXdunWjU6dOREdHU65cObp06cK8efO4ceMGQ4cOTekaRUREREREJAVlzQoDBhgLyS1eDKVKwbVr8MUXRpD//HP466/UrWnfvn3s3buXIUOGPPe6AwcOUK1aNbJkyRLb9v777/PDDz/Evvb396dw4cIpVmtyeul90s1BW7CJiIiIiIiknJgYY3765Mmwd6/RZmtrLDL3+efGkPiUFBISgpeXF+PGjaNYsWLUrl2bZcuWUbly5TjXNm/enCpVqpAuXTo2bdqElZUV9evXp0+fPqRLl46oqCg8PDyoU6cOly9fJiQkhDJlytC/f38KFSqUsg/yAmwTOjF37lzat2+Pg4MDc+fOfe5NtA2biIiIiIjIq8PKypif3qgR+PrClCnw/ffGPPbly+Gdd4ywXreucW1yGz58OG+99Ra1atX6z8XdQkND+eGHH6hVqxYzZswgKCiI0aNHExISwsSJE7l69SphYWGEh4czZswYwsPDmTNnDt7e3mzZsoXs2bMn/wO8hAR70t966y3Wrl1LtmzZeOuttxK+gZUVu3btSrEC46OedBERERERkdR16RJ8+SV88w08fGi0lSsH/fvDBx8YW70lh/Xr1zN79mw2bdpEhgwZuHnz5nN70hs2bEhERAQ7d+7ExsYGgB07dtC7d29+//13smXLxp07d8iSJUvsHPRHjx5Rp04dPvnkE/73v/8lT+HJJMGe9N27d8f+PHv2bN544w2sUuIrEhEREREREbF4BQsae6sPHw5z5xo/Hztm7ME+aBD06QOdOkGmTC/3OevWrSMoKIgaNWoA8KRfuXPnzjRr1oxRo0aZXO/i4kK6dOliAzoQu4X4tWvXyJYtG9myZTN5T/r06XF1deXGjRsvV2wKSNTCcZ06deLkyZMpXYuIiIiIiIhYuOzZwccHrlyB+fOheHG4etXYyi1/fiOwv0z2nTJlClu3bmXDhg1s2LCBhQsXAjBmzBh69+4d5/oKFSpw9uxZIiIiYtsuXLiAjY0NefPm5eeff8bDw4OQkJDY86GhoVy+fJmiRYu+eKEpJFEhPXPmzIRbwiZ5IiIiIiIiYhEcHKBzZzhzBjZuhBo14O5dYyu3AgWgY0fjXFK5uLjg5uYWe+TLly+2PXv27ISHhxMcHBybUVu1akVYWBgDBw4kICCA3377jcmTJ9O0aVOyZctGxYoVyZgxI/379+fcuXOcPn2a3r17ky1bNpo2bZp8v5BkkqjV3SdOnMi3337LW2+9haurKw4ODibnU3vhOM1JFxERERERsTy//26sCL9+vbFCPEDjxsa89Vq1XmyRuX/PST906BBt27Y1maN+8eJFxo8fj6+vL46Ojnh5edGvXz/s7e0BCAgIYPLkyRw5coTIyEiqV6/OoEGDyJMnT3I9erJJVEjXwnEiIiIiIiKSWP7+xiJzixfD48dGW8WKRlhv3tzYzk3ip33SRUREREREJEUEB8NXX8Hs2XD7ttFWsKAxf71DB8iQwbz1WaJEh/TIyEhu375NVFQUYKywFx4ezsmTJ/Hy8krRIv9NIV1ERERERCTtePgQliyBadMgIMBoc3KCHj2gZ0/ImdOs5VmURIX0/fv3M3DgQJPV8J5Inz49R44cSZHiEqKQLiIiIiIikvZERcGGDca89UOHjDYHB2jXzuhdL1bMrOVZhESt7j516lTc3d1ZvHgxDg4OzJkzh+HDh5M5c2YmTJiQ0jWKiIiIiIjIK8DGBlq0gIMH4ZdfoEkTY876vHlQooQxX/2338xdpXklKqQHBATQt29fqlSpQsmSJbGzs6NVq1YMHjyYRYsWpXSNIiIiIiIi8gqxsoKaNWHTJmObto4dwc7O6GWvXt04NmyA6GhzV5r6EhXSbW1tyfD/M/rd3Ny4cOECABUrViTgyYQCERERERERkSR64w1YuBCuXIHBgyFrVqM3vXlzo3d93jx49MjcVaaeRIX00qVLs3btWgCKFSvGwYMHAbh8+TLW1om6hYiIiIiIiEiCcuWCsWMhMBCmTwc3N2Mrt65djZ9Hj366QvyrLFEJu2fPnnzzzTcsXrwYLy8vjh07RrNmzejdu/dz91AXERERERERSYqMGaF3b7h4EVavhvLlja3chg0DV1djNfg//zR3lSknwdXdu3fvTosWLahTpw42NjbcvHmTiIgIXF1duXjxIuvWrcPJyYm2bdtib2+fqkVrdXcREREREZHXQ0wM7NljrAi/Y4fRZm1tLEDXvz9cuAA+PnD1KuTPb/TGe3ubt+aXkWBIb9OmDb6+vmTPnh0vLy9atGhB4cKFU7u+eCmki4iIiIiIvH5OnoSpU2HVKoiIMNqsrU0XmHN0hPnz025Qf+4+6Tdv3mTjxo1s3ryZgIAA3N3dadGiBY0aNSJjxoypWacJhXQREREREZHX17VrMGMGTJli9LT/m5sbXL6c6mUli+eG9GedOnWKjRs3sn37dh48eEC9evVo0aIFlStXTuka41BIFxEREREREWvr+EO6lVXa3b4t0SH9iaioKA4cOMC2bdvYu3cvmTNn5qeffkqp+uKlkC4iIiIiIiIFChhbt/1bWu5JT/L+aTY2NmTLlo3s2bOTOXNm7t+/nxJ1iYiIiIiIiDzX2LHGHPRnOToa7WmVbWIvvHjxIlu3bmXr1q1cv36datWq8dlnn1G3bt2UrE9EREREREQkXk8Wh3stVncHuHbtGlu3bmXLli34+/vj5ubGe++9R9OmTXFxcUnNOk1ouLuIiIiIiIi8ihLsSW/VqhXHjx/H0dGRhg0bMmLECMqXL5+atYmIiIiIiIi8VhIM6XZ2dowfP54GDRrg4OCQmjWJiIiIiIiIvJYSDOnLly9PzTpEREREREREXntJXt1dRERERERERFKGQrqIiIiIiIiIhVBIFxEREREREbEQCukiIiIiIiIiFkIhXURERERERMRCKKSLiIiIiIiIWAiFdBERERERERELoZAuIiIiIiIiYiEU0kVEREREREQshEK6iIiIiIiIiIWw2JB+7NgxSpYsyaFDh8xdioiIiIiIiEiqsMiQ/vDhQ7744guioqLMXYqIiIiIiIhIqrHIkD5hwgRcXFzMXYaIiIiIiIhIqrK4kL5v3z727t3LkCFDzF2KiIiIiIiISKqyNXcBzwoJCcHHx4dx48aRJUsWc5cjIiIiIiIikqosqid9+PDhvPXWW9SqVcvcpYiIiIiIiIikOovpSV+/fj1nzpxh06ZN5i5FRERERERExCwsJqSvW7eOoKAgatSoAUBMTAwAnTt3plmzZowaNcqc5YmIiIiIiIikOIsJ6VOmTOHx48exr4ODg/H29mbMmDFUr17djJWJiIiIiIiIpA6LCen/3nItXbp0se3Zs2c3R0kiIiIiIiIiqcqiFo4TEREREREReZ1ZTE/6v+XKlYvz58+buwwRERERERGRVKOedBERERERERELoZAuIiIiIiIiYiEU0kVEREREREQshEK6iIiIiIiIiIVQSBcRERERERGxEArpIiIiIiIiIhZCIV1ERERERETEQiiki4iIiIiIiFgIhXQRERERERERC6GQLiIiIiIiImIhFNJFRERERERELIRCuoiIiIiIiIiFUEgXERERERERsRAK6SIiIiIiIiIWQiFdRERERERExEIopIuIiIiIiIhYCIV0EREREREREQuhkC4iIiIiIiJiIRTSRURERERERCyEQrqIiIiIiIiIhVBIFxEREREREbEQCukiIiIiIiIiFkIhXURERERERMRCKKSLiIiIiIiIWAiFdBERERERERELoZAuIiIiIiIiYiEU0kVEREREREQshEK6iIiIiIiIiIVQSBcRERERERGxEArpIiIiIiIiIhZCIV1ERERERETEQiiki4iIiIiIiFgIhXQRERERERERC6GQLiIiIiIiImIhFNJFRERERERELIRCuoiIiIiIiIiFUEgXERERERERsRAK6SIiIiIiIiIWQiFdRERERERExEIopIuIiIiIiIhYCIV0EREREREREQuhkC4iIiIiIiJiIRTSRURERERERCyEQrqIiIiIiIiIhVBIFxEREREREbEQCukiIiIiIiIiFkIhXURERERERMRCKKSLiIiIiIiIWAiFdBERERERERELoZAuIiIiIiIiYiEU0kVEREREREQshEK6iIiIiIiIiIVQSBcRERERERGxEArpIiIiIiIiIhZCIV1ERERERETEQiiki4iIiIiIiFgIhXQRERERERERC2FRIf3vv/9mwIAB1KhRgwoVKtCxY0cuXLhg7rJEREREREREUoXFhPTo6Gh69uzJ5cuX+frrr/n222/JmDEj7du3586dO+YuT0RERERERCTFWUxIP3fuHEePHmXcuHG4u7tTpEgRJk+ezMOHD9m3b5+5yxMRERERERFJcRYT0nPnzs28efMoWLBgbJuVlRUxMTHcu3fPjJWJiIiIiIiIpA5bcxfwRLZs2ahTp45J2/LlywkLC6NGjRrmKUpEREREREQkFVlMT/q/7dq1i2nTptGhQwcKFy5s7nJEREREREREUpxFhvR169bRq1cvGjZsSP/+/c1djoiIiIiIiEiqsLiQPmfOHAYNGkSrVq2YNGkS1tYWV6KIiIiIiIhIirCYOekACxYsYPr06fTq1YsePXqYuxwRERERERGRVGUxIf3cuXN8+eWXtGjRgpYtWxIcHBx7LkOGDDg6OpqxOhEREREREZGUZzEhfdu2bURFRbF27VrWrl1rcq537950797dTJWJiIiIiIiIpA6rmJiYGHMXkVR+fn54enqauwwRERERERGRZKVV2UREREREREQshEK6iIiIiIiIiIVQSBcRERERERGxEArpIiIiIiIiIhZCIV1ERERERETEQiiki4iIiIiIiFgIhfSXMGzYMHx8fJ57zcmTJ2nVqhVly5alfv36bNiwweR8TEwM8+bN480336RcuXJ4e3tz9uzZFKxaRERERERELJVC+guIiYlhxowZrFmz5rnXhYSE0KlTJ0qVKsW6deto06YNPj4+HDhwIPaar776igULFuDj48O6detwcXGhc+fOhIaGpvRjiIiIiIiIiIVRSE+iwMBA2rZty+rVq8mTJ89zr/3+++/JmDEjPj4+FC5cmDZt2uDl5cWiRYsAePDgAQsXLmTgwIG8/fbbFCpUiFGjRmFvb8+ZM2dS43FERERERETEgiikJ9HRo0dxdXVl8+bN5MuX77nX+vr6UrFiRaytn/6aK1WqxJEjR4iOjsbPz4+wsDAaNGgQez5jxozs3r2bSpUqpdgziIiIiIiIiGVSSE8iLy8vxo0bh7Oz839ee/PmTVxcXEzacubMyaNHj7h79y6XL1/GycmJ48eP07JlS6pVq0bHjh25ePFiSpUvIiIiIiIiFkwhPQU9fvwYe3t7k7Ynr8PDwwkNDeXBgweMHj2arl27MnfuXBwdHfH29iYkJMQcJYuIiIiIiIgZKaSnIAcHB8LDw03anrxOnz49tra2PHr0iBEjRvDWW2/h7u7OlClTsLKyYuPGjeYoWURERERERMxIIT0F5cqVi+DgYJO2W7du4ejoSKZMmWKHwhcrViz2fLp06ciXLx9//fVXqtYqIiIiIiKpJyoqiqlTp1KjRg08PDzo1asXf//9d4LXHzx4kPfff59y5crx9ttvs2DBAmJiYuK9dseOHRQvXlyZIo1SSE9Bnp6e+Pr6mvw/z6FDhyhfvjzW1tZ4enoCxl7qT4SFhREYGIirq2uq1ysiIiIiIqlj1qxZrF+/nokTJ7JixQpu3rzJp59+Gu+1V65coWvXrtSpU4fNmzfz+eef89VXX7Fq1ao41966dYvhw4endPmSghTSk1F4eDjBwcGxQ9rff/99QkJCGD58OAEBASxfvpwtW7bQqVMnAPLly4eXlxcjR47kt99+IyAggEGDBmFtbY2Xl5c5H0VERERERFJIeHg4y5Yt47PPPqN69eqUKlWKadOmceTIEY4cORLn+v379+Pg4EDPnj1xdXWlQYMG1K5dm/3798e5dvDgwSYjdSXtUUhPRkePHqVGjRocPXoUgBw5crBw4ULOnDlDs2bNWLFiBRMnTqRq1aqx7xk7dizvvPMO/fv357333uP27dssW7YMJycncz2GiIiIiIikoHPnzvHgwQOTbZfz5ctH3rx58fX1jXO9k5MTd+/eZcuWLURHR3PhwgV8fX0pXbq0yXUrV64kODiY7t27p/gzSMqxikloIoMF8/Pzix0qLiIiIiIikpb8+OOPfPrpp5w6dQo7O7vY9latWlGyZEmGDRtmcn1kZCTDhw9n7dq1WFtbExUVRcOGDZk2bRrW1ka/66VLl2jZsiXLly8nNDQUb29vdu3aRb58+VL12eTlqSddREREREQkFT169Ahra2uTgA7Gds1hYWFxrr9//z7Xr1+nU6dO/PDDD0ycOJHffvuN2bNnA0aI/+KLL+jUqRMlSpRIlWdIaUlZWK9NmzYUL1483uPw4cMm18bExNCpUye+/vrr1HiMF2Jr7gJE5PmioqKYPn0669ev58GDB9SsWZNhw4aRI0eOeK+/efMm48aNi5279M477zBgwADSp0/PunXrGDRoULzve++99xg/fnxKPoqIiIiIYGzVHB0dTWRkJLa2TyNZeHg46dOnj3P9lClTsLa25vPPPwegZMmSREZGMmLECNq0acPKlSuxtraOXfvqVfDswnpZs2Zl5MiRfPrpp6xevTreayMiImJfR0dH07VrVzJmzIiHh0dse3h4OCNGjGD//v2UL18+VZ7jRSiki1i4pPwFFR4eTocOHXB2dmb16tXcvXuXgQMHYm1tzbBhw2jUqBE1a9Y0ec/atWuZM2cO7dq1S61HEhEREXmt5c6dG4Dg4ODYn8FYmf3JNs3POn78OG+//bZJW9myZYmIiODGjRusW7eOW7duUaFCBcAIqQDvvvsuXbt2pWvXrin1KCniycJ6Q4YMoXr16gBMmzaNunXrcuTIkTgBO2vWrCav58+fT2BgINu3b4/9EuT06dP4+Pjwzz//kDlz5lR5jhel4e4iFiypK39u3ryZ4OBgZs2aRYkSJahSpQo9e/bkxIkTgPGtrbOzc+zx+PFj5s6dy8CBA1+ZoVEiIiKJldR9qm/evEmvXr3w8PCgatWqjBgxgkePHsWev3LlCt27d6dy5cpUqVKFXr16cf369dR4FEljSpQoQYYMGfjjjz9i2/766y+uXbtGxYoV41yfK1cuzp8/b9Lm7++PtbU1+fPnZ/ny5WzdupUNGzawYcOG2NGR8+fPp1WrVin7MCkgqQvrPSs4OJg5c+bQt29fnJ2dY9sPHjxI1apV2bhxI5kyZUqx2pODQrqIBUvqX1AHDhygWrVqZMmSJbbt/fff54cffoj3/pMnT6Zo0aJ8+OGHyV+8iEgSJDUs9erVK868w/bt28eeDw4Opm/fvlSpUoVq1aoxevRoHj58mApPImlJUvapfjJa7e7du6xevZovv/ySvXv3MnnyZAAePnxIx44diY6OZunSpXzzzTfcuXOHzp07x27PK/KEvb09H3/8MZMmTeKXX37h9OnTfPbZZ1SqVIly5crF2dq5bdu27N27l6+//prAwED27NnD+PHj+fjjj8mYMSN58+bFzc0t9siZMycAefLkidPLnBbcvHkTIM6ogpw5c8aeS8j/tXffYVEdXx/Av0tvShMRwW5QRJFmi9jA2CLYYtRYYgGNvb9qwBZiQU0Au6A/jQ1jUAyJGlQUosaOsaFBREBQepO67O68fxBuWHZpCuzCns/z7APMLTv3cLecO3Nn/P39YWhoKHFxwtXVFatWrYKOjk7tVrYOUJJeh048OYG2Pm2htFEJbX3a4sSTE7KuEmlgavoGFRsbC1NTU/j4+MDR0RFOTk7w8vKSOgDJixcvEBISguXLl3OjghJCiKzUJFkCSlqQli9fjhs3bnAPX19fAEBxcTFmzpyJV69eYc+ePfD398ezZ89oSiIiprZ7q928eRPv3r3Djh070LlzZ1haWmLbtm2Ijo7Go0eP6vvwSAOwZMkSODs7Y+XKlZg2bRpatmzJvY+Vn9p5wIAB2L17N65cuQIXFxds3rwZEyZMwOrVq2V5CHWmpgPrlcrNzcWZM2fg6uoKZWXluq5mnaF70uvIiScnMPu32cgvLrlqH5cdh9m/zQYATO42WZZVIw1ITd+gcnNzERgYiP79+8PX1xfJycnw9PRERkYGvLy8xNb96aef0L17d/Tu3btOj4EQQqpS03sP+Xw+4uPjYWVlJdaVsVR4eDiioqIQEhKCtm3bAgB8fHwwcOBA3L17V6x3ElFcVfVWK3/eVdRb7YsvvgAAWFlZwc/PT6yVrvQieHZ2dl0eiszUdHDbRYsWISQkRKysT58+OHLkCAAgOjoaW7ZswcOHD6GmpoYhQ4Zg5cqVct81+UOpqKhg9erVUhPtXr16SXRvHzx4sMR96RWxt7eX2L4hqenAeqVCQ0MhFArh7OxcH9WsM9R8VkfcQ925BL1UfnE+llxcguTcZBnVijQ0Zd+gyqroDUpFRQW6urrYtm0bunXrhsGDB2PNmjU4d+4cMjMzufWKiorwxx9/UDd3QohcqOmtPTExMRAIBOjQoYPU/cXGxsLIyIhL0IGS+zn19fXF7v8kiq22e6sZGxtzF5lK+fn5QVNTE3Z2dnV0FLJVmz1g8vLyMH36dOjp6eGXX37Bvn378ODBgwpnpSGNW9mB9cqqaGC9UqGhoRg4cCC0tbXrtH51jZL0OhKfHS+1PK0gDS1+aIHu+7tjWcgyXHh5Abn83HquXf2q6X2GZc2ZMwdTp07l/j579myFcyA2xjfxmr5BGRsbo0OHDmLdezp27AgASExM5Mpu3bqF4uJifPbZZ3VRbUIIqZGaJktRUVFQVVXFrl27MHDgQAwdOhTe3t5cstS8eXNkZWWJ3YOem5uL7OxsZGRk1OGRkIbkQ3urvXnzBr6+vlizZg0uXLiAdevWSd3/yZMncfz4caxYsQL6+vp1cgyyVNPbBcr3gCl9lPZMePv2Lezs7ODp6YkOHTrAxsYGX375JW7dulXfh0bkQE0H1isVERHRKHqJUpJeR1rrtpZarqGiAQ0VDTxOfgzv2974/OTn0PfSR//D/bExbCNuxt9EsbBY6rYNVU2vspY6deoUwsLCxMpGjBghdvX1xo0bWLp0KTQ0NBrlFGI1fYOyt7fH8+fPxeaJjIqKgrKyMkxNTbmy+/fvw9LSUu6nnyCEKIaaJkvR0dEAgHbt2uHAgQNYsGABAgMDuWSpf//+0NHRwdq1a5GTk4P3799j/fr14PF4Yu+PRLHVVW81ANi3bx82btyIOXPmYMqUKXV6HLJS2z1gPvnkE/j6+kJLSwsA8Pr1a/z6668SvROIYqjpwHpASSNWamoqzM3NZVjz2kFJeh3Z5LQJWqpaYmVaqlo46HIQmasycXXaVbj3c0cv014QMRGux1/HhvANcDjsAINtBhh5ciR8bvvgacpTMMZkdBQfr6ZXWUvFxcXB29sbNjY2YuWKNoVYTd+gJk6ciKKiIqxevRqvXr3CX3/9he3bt2PUqFFiV/GfP3/eKN7ACCGNQ02TpSVLluDGjRuYMWMGOnXqBGdnZ7i7u3PJkp6eHvbt24enT5+iZ8+e6NevH0xMTNC5c+cGMarvh6jNXmtlMcbg6uqKvXv31mZ15UJd9FYTiURYt24dfHx8sGLFCixbtqyuqi9ztd0DpqxRo0Zh2LBhyMrKwrfffls3B0DkXk0G1gP+ey03xNHsy6OB4+pI6eBw7qHuiM+OR2vd1tjktIkrH9RuEAa1G4TvHb9HVmEWwmLDEBoTiiuvr+BF2gucf3ke51+eBwAYaxvDqb0TBrcbDKf2ThW20sujmg7KApR80Vi1ahVcXV0RGxuL+Hjptw4AijGF2JIlSyAQCLBy5UoIBAJuUBag5A1q2rRpOHr0KHr16oVmzZrhxIkT2LJlC8aOHQstLS24uLhg+fLlYvtMSUlBly5dZHE4hBAioWyyVPo7UHGypKSkJPElrPTCY1JSEvT19WFjY4OQkBCkp6dDW1sbGhoa6NWrFzfIV2NTtteanp4eNm7ciIULFyIgIKDS7Up7rUkbTI/P52PDhg24fv261M/rhq5sb7VRo0YBqLq32unTp1FcXMz1+ijfW+27775DYGAg9zncmH1MD5jJkycjKioKW7duRVJSksTgtps3b0ZBQQF27NiBadOm4ddff610sDDSONV0YD1LS8tqD5Z39erVWqljnWEN0P3792VdhTqVkJ3Afvr7Jzb17FRmssOEYQPEHp/s/ITN/X0uC3wWyNLz02Vd3UqFhIQwc3NzxufzxconTJjANm7cKHWbPXv2sAkTJjChUMi+/fZbNmXKFKnrPX/+nJmbm7Nbt27Ver0JIYTUn6KiImZjY8POnTvHlb1584aZm5uzhw8fSqy/aNEiNm/ePLGyoKAg1rVrV5abm8tev37NJk6cyDIzM7nld+/eZZ07d2axsbF1dRgyUxq/M2fOcGWl8Xvw4EGF28XGxrKePXuyCRMmSHzWPn36lI0aNYo5Ojoye3t7tmfPnjqrvyxt376dffrppyw8PJw9ffqUjR8/notFUVERS0lJYUVFRYwxxlJTU1nPnj3ZsmXLWHR0NLt58yYbOHAgW716NWOMsbCwMGZubs527tzJUlJSxB6FhYUyO8a68scffzBzc3NWXFwsVj5hwgTm6ekpsb5QKBR7TTLG2Pnz55m5uTnLyMiQ+hzJycmsc+fOLDg4uNbq3VAdf3yctfFuw3gbeKyNdxt2/PFxWVeJ1CFqSZdDpk1NMa37NEzrPg2MMbxIe4ErMVdw5fUVXHt9DS8zXuJlxkvsu78PPPBg19IOTu2cMLj9YPRt1ReaqvJzpbGmV1mfPXuGw4cPIzAwsMq5u2kKMUIIaRzK3tqjr68PQ0NDbNy4UezWnuzsbOjq6kJNTQ1Dhw7FsmXLcPjwYTg5OSEyMhJeXl6YOXMmtLW1oa6uzk1BuWjRIrx79w7/93//hy+++AJt2rSR9eHWurrotXbr1i306dMH8+fPh4uLS50fg6zUZm+14OBgAMDu3buxe/dusefZtm0b11rfWNR2D5i8vDy8ePFCbIqx5s2bQ09PD8nJij0zEk3trHgoSZdzPB4PFkYWsDCywMJeCyEQCXD/7f2SpD3mCv568xfuv72P+2/vw+umF9SV1eHQ2oFL2m1NbKGspFz1E9WRmsxxWFRUhJUrV2LJkiVVfokqnULMw8OjTupNCCGkftUkWRoxYgT4fD4OHToEb29vGBoaYtq0aZgzZw6Aki6SBw4cgKenJ0aPHo2mTZtizJgx1Rq0tCGq6b3BAHDgwAEAwKxZs7B27VqJ5a6urrVcS/lU0+60HTt2xKFDh6Tu64cffsAPP/xQJ/WURzW9XWDx4sUQCATYs2cPV/b06VOoqamhdevWCA8Px4oVK/Dnn39y86y/efMGGRkZ3L3/iiS/OB+vM18jJjMGCy8slDq184LzC5BdmA09DT2pD00VTfB4PBkdAfkYlKQ3MCpKKuht1hu9zXrDo78H8vh5uBF/A1diriD0dSgeJj1E6OtQhL4OxbdXv4Wehh4GtR2Ewe0HY3D7wfjE4JN6fbHW5Crro0eP8OrVK+zYsQM7duwAUJLMi0Qi2NjY4Pz582jZsiUAmkKMEEIam5omS6NHj8bo0aMr3N8nn3yCo0eP1nY15VJd9lojpCK13QNm0KBBaNWqFVasWIE1a9YgLy8P33//PWxsbNC/f39ZH26tY4whOS8ZMZkxiMmMwauMV4jJ+vdnZgze5b6rch9ZRVmYf2F+hctVlVQrTOCr86AkX3YoSW/gtNW0MbTjUAztOBQAkJqXimux17ikPSYzBkEvghD0IggA0KppK7FB6FrotKjT+tXkKquVlRUuXbokVvbjjz/i7du32LFjB5o3b86V0xRihBBCSIm66rVGSFVqsweMpqYmDh06hC1btmDKlCng8XjcNHcN9WJSkaAIsVmx/yXima/EfpZvHS9LVUkVbfXaor1+e9x8cxO5/FyJdZqqN8WkrpOQVZgl8cgszARfyEdqfipS81OlPEPVKMmXHR5jDW9+rwcPHsDOzk7W1WgQYjJjEBoTyrWup+WLT8diaWTJtbIPaDMATdSb1HodduzYgaCgIGzZsoW7yqquro5jx45JXGUtz93dHfHx8Th27JhY+axZs9CyZUt4enrWen0JIYSQhuTx48cYP348wsLCxHqtOTo6YtKkSXBzc+PK7t69i6lTp3JzUQP/9VrT0NAQ67VWdj9ffPEF5s2bV/cHQ0gDwhhDRkHGf8n3v63gpS3iCTkJYKg41dLX0EcHgw5or98eHfRLfpb+btbUjLtltfw96UDJ1M5+zn6V3pNeKCiUmsBnFWYhuzD7v7+LpK9TKCj8qPjUZ5J/4smJCmfVaoioJb2Ra6/fHu3t2sPNzg0iJsLj5MfcVG9/xv2JZ6nP8Cz1GXzv+EKZp4xeZr0wuF1J0t7LrBfUlCUT55qqyVXW6qIpxKRrbG9QhBBCqlZXvdYIIUCxsBhvct5wCXhpQl76e05RToXbKvGU0Ea3DZeAl03E2+u3h76mfrXqUNXUzhXRUNFAC50WH9xztlBQKJ7MV/SoJMmvj5b8ZynPcOjhIRQJS27vaQwD61FLugIrEhThdsJthL4OxZWYK7ibeBdCJuSWa6tqo3+b/hjcfjCc2jmhm3E3KPEaZncjRfChV1kJIYQ0fHXRa60UtaSTxi67MFu8O/q/94fHZMYgLitO7PtxeTpqOuig36GkRVyvvVjLeGvd1lBVVq1w28auNpL8j9FGtw1il8TWzsHUM2pJV2DqKuoY0HYABrQdgO8GfYecohyEx4Zz071FpkbiYvRFXIy+CAAw0jKCU3snbuT4tnptZXsACkjERMgqzEJybjJS8lLEHj/e/lHqyJ/uoe6UpBNCSCNXF73WiDjqrdZwCUVCJL5PFOuSXvb+8IyCjEq3N2tqJtYSzv006ABDTUO677oCGioa0NDRgLGO5JR81VHdJH//g/1St4/Pjpda3hBQSzqp0Nv3b3H19VVuurfE94liyzvod+AS9kHtBqGZVjMZ1bRhKxQUcom2RPKdL16Wmp8KgUhQo/3zwINovaiOak8IIfWPkiVS36i3mvzL5edyU5aVH6AtNisWfCG/wm01VTTF7gcvTcDb67dHW7220FDRqMcjITXV1qct4rLjJMobcks6JemkWhhjiEqP4lrZr72+huyibG45DzxYt7DmBqFzaO0ALVWtSvbYeImYCBkFGWLJtljynS9e9p7/vkb719PQQ3Pt5v89tJrDWMcYO+/sRGZhpsT6yjxlnJt4DiPNR9bWIRJCiMxQskRqW35xPpJyk5CUm4R3799xvyflJiEpr+Tnw3cPpXZ5VuIpwbSJKbRUtaClqgVNVU3udy1VLWipaIn/XcOHmrIatdL+izGGd7nvpA7QFpMZg+S85Eq3b6HTQjIR//dnC50WFOcGrDF+LlCSTj6IQCRAxLsIrpX95pubYlco1ZTV8GmrT7lB6Oxa2kFFqeHeXVFQXIDkPMku5sm5yVzSzbV256VWeu9SeapKqlzCbaxjzCXeEmXazWGkZQR1FXWp+5H2BsUDjxtV1KWTC3yH+dJtCoSQBs3sRzOJnl0AoK6sjqEdh6KZZjM006r4oauhS+OrKACBSIDUvNT/ku/ccsl3mUdNL5bXJyWeUvUS+o+8GFA6inhdqk4PmEJBoURreOnvrzNfo0BQUOH+1ZTV0E6vneRI6QYd0E6vHbTVtOv6EIkMNbYeVpSkk1qRX5yPm/E3ufnZI95FiE050VS9KQa1HcQNQte5WWeZXrEUioRca7fU5LtcmbS5KSujr6Ev1tptrG0s3vpdJvnWVdettViUf4PyHOSJ9IJ0rLu2Du/576Gpogn3fu5Y8emKCpN9QgiRN8XCYlx4eQH+Ef44//L8R+1LmacMQy1D8eS9isReR02HWtnkAGMM2UXZEkn2u/fvuBbv0kdqXmqlU1+Vpa6sjhY6LWDSxKRkJGztFtyI2KWPcafHSb04ZNbUDDdn3kR+cX6dPIpFxbUdRqnUlNXq9GJA8D/BWHBxgVhDgpqyGpzNndFEvQnXGi4txmUZahpWOGVZyyYt6+ViAyH1gZJ0UifS89NxLfYaN91bdEa02PKWTVqWdI1vNxhO7Z3QsknJnKwfcxUsj59XaaJdtiwtPw0iVv37tNWU1aQn2lLKjLSNamXqutr09v1brLi0AgFPAwAA5obm2D18Nz7r8JmMa0YIIRWLyYzBwYiDOPL3EbzLfVfpusbaxtg/cj/S8tMqfZS9Vau61JTVJJP3KhJ7TVXNDz1shVMoKERybrJk8i2l9bt0iqWq8MCDkbZRSfKtYyKRdJd9VOdiuay60xYLi1EgKKiziwClj+pe0KhryjxltNGreMoyXQ1dWVeRkHpBSTqpF7FZsQiNCeWmeys/X6JFMwu0atoK4XHhYh/AmiqaWDdgHXq07FFl8l1+ZPOqGGgaVNzKXa6sqXrTRtGKcvX1Vcy/MB8v0l4AAMZ3GY8fh/4Is6ZmMq4ZIYSUKBIU4dyLc/CP8Efo61CuvHOzznCzdYOWqhaWX1r+wckSX8hHRkFGlcl82UdecV6Nj0NLVatGib2hlqHcXeD9GCImQlp+mtTu5eWT76zCrGrvt4laEy65NmliIrXVu4VOCxhpG9X6bXaNrTttKcYYioRFdXoRQNqYOaUOjDzAJeGtdVs36NsjCaktlKSTeidiIjxNecq1sofHhn/QF6Dy1JXVxe7friz5bqbVTGHnreQL+fC+5Y3v/vwO+cX50FbVxvoB67Gk9xKFjQkhRPZepL2A/wN/HH18FGn5aQBKpu/50vJLuNm6oW+rvtzF0vpOlgqKC5BekF7tpD41P7XSkaQr0lS9aY0SewNNgw/q3vuh8WOMIZefW+G93WWT75S8lGqPz6KipCKWYFfU8m2sbUz3FTdQjXH0bULqEiXpROb4Qj7uJt5Fv8P9KlxnYNuBYgOqlU3GS5NvumewZuKz47EsZBnOPD8DAOhi1AV7R+zFgLYDZFwzQoiiKCguwC+Rv8A/wh834m9w5d2Nu8PN1g2TrSZDT0NPdhX8QIwx5BXn1ai1Pi0/rUaDjgIlXbr1NfVr1A3//MvzmPP7HImeCFudtqJPqz5VJuA16bVmqGlYreRbX1OfBvNr5Brj6NuE1CVK0oncoKussvFH9B9YeHEhN27A5G6TsWPIDrTQaSHjmhFCGqtHSY/gH+GP44+Pc/eI66jpYFLXSXCzdYN9S3uFu+haOihaTZL6jIKMer+XWFNF878B1v4dZE3s738fzbWbN6ru++TjNdbbBQipC5SkE7lBV1llp1BQiO03t2Pzjc0oFBSiqXpTeA7yxLwe8+jeMEJIrXhf9B6nnp6Cf4Q/7r29x5X3NO0JN1s3TOw6ETpqOjKsYcMjFAmRWZhZo8S+soHzbFrYVNnqTb3WCCGk7lGSTuQKXWWVrZjMGCz+YzF+j/odAGDdwhp7R+xFn1Z9ZFwzQkhDxBjDvbf34P/AH6eeneKms9TT0MOUblPgZucGK2MrGddSsbTxaYP47HjJcuq1RgghcoOSdEKIhOB/grHo4iLu9oOZ1jOxdfBWGGkbybhmhJCGILMgEyeenIB/hD8eJz/myvu17gc3Wzd80eULmqJMRqjXGiGEyD9K0gkhUuUX52Pz9c3Y/td28IV86GvoY4vTFrjaun7QaMKEkMaNMYYb8TfgH+GPXyJ/QaGgEADQTKsZvu7+NVxtXdG5WWcZ15IA1GuNEELkHSXphJBKRaVHYcGFBbgccxkA0KNlD+z9fC/sW9rLuGaEyDehUAgfHx8EBQUhLy8P/fr1w7p169CsWbMKt7lw4QIOHDiAuLg4GBkZYfz48Zg1axaUlUsujKWmpmLz5s24desWlJSUMHz4cCxfvhxaWlr1dVgSUvNScfTRURx8eBAv0l5w5YPbD4abrRtGdRoFdRV1mdWPEEIIaWgoSSeEVIkxhsDIQCwNWYrE94nggYdv7L/BJsdN0NfUl3X1CJFLPj4+CAwMhJeXF/T09LBx40YoKysjICBA6vrh4eGYO3cuvv32W/Tv3x+RkZFYu3Ytpk+fjvnz56O4uBhjx44Fj8fD+vXroaGhAU9PT2hoaODIkSP1emwiJsLV11fhH+GPoOdBKBYVAwBMdEwww3oGZtnOQnv99vVaJ0IIIaSxoCSdEFJt74ve47vw7+BzxwcCkQDNtJph2+Bt+Nr6a5rjlpAy+Hw+evfuDQ8PD4wdOxYAkJCQACcnJwQEBMDW1lZim7lz50JdXR0+Pj5c2Z49e3D27FmEhobiypUrmD9/PkJCQtC2bVsAQFJSEgYOHIijR4+iZ8+edX5cb9+/xZG/j+BgxEG8znoNAFDiKWF4x+Fws3XD5+af04wQhBBCyEeib9WEkGprot4E24dsx99z/saANgOQlp+GmcEz0e9wPzxKeiTr6pFaJhQK8cMPP8DBwQE2NjZYtGgR0tLSKt0mMDAQw4cPR7du3TBixAicOXNGbDljDAcOHMCgQYNgbW2NyZMn4/nz53V5GDLx4sUL5OXliSXOZmZmMDU1xf3796VuM3fuXCxYsECsTElJCTk5OQCA2NhYGBkZcQk6ALRo0QL6+vq4e/du7R/Ev4QiIX6P+h2jTo1Ca+/WcL/qjtdZr9FatzU2DtyIuCVx+P2r3zGq8yhK0AkhhJBaQEk6IaTGLJtb4trX13B8zHEYaxvjrzd/wdbPFkv+WILsworn4CUNy65duxAUFAQvLy8cP34cSUlJWLhwYYXrh4SEYMOGDXBzc8OFCxcwY8YMrF27FqGhodw6e/bsgb+/P9zd3XH27FkYGxvDzc0Nubm59XFI9SYpKQkAYGxsLFbevHlzbll5VlZW6NixI/d3bm4uAgIC0K9fP27brKws5Ofni62TnZ2NjIyM2j4ExGXFYd21dWjj0wbOAc4I/icYPB4PYy3G4uLki4hZFIN1A9bBrKlZrT83IYQQosgoSSeEfBAej4fJVpPxz4J/sKjnIgCA7x1fdN7TGScen0ADvJOGlMHn83H06FEsW7YMffv2haWlJX788UdEREQgIiJC6jYZGRlYuHAhxo4di1atWmH8+PEwNzfHrVu3AAB5eXk4ePAgVq9ejcGDB6N9+/b47rvvoKamhsjIyPo8vDpXUFAAJSUlqKqqipWrqamhqKioWtvPmzcPRUVFWL58OQCgf//+0NHRwdq1a5GTk4P3799j/fr14PF4KC4urpV6FwuLcSbyDIYdH4Z2vu3g+acnEt8noqNBR2x12oqEpQk48+UZDOs4jGZ5IIQQQuqIXCXpH9K1khAiW7oauvAd7osHsx+gj1kfJOUmYUrQFDgedURkauNKvBTJh3TXnjRpEubMmQMAEAgEuHjxIl69eoW+ffsCKBlPpKioCMOGDeO20dHRwdWrV+vlfuq6tH//ftjY2HCPt2/fQiQSQSAQiK3H5/OhqVn5/OAZGRmYMWMGIiMj4e/vD1NTUwCAnp4e9u3bh6dPn6Jnz57o168fTExM0LlzZ+jo6HxU/V+mv8Sqy6tg5m2GL375AiGvQqCqrIpJXSfh6rSriFoQhVUOq2CsY1z1zgghhBDyUeTq5rGyXStLR8JduHBhhSPhEkLkh3ULa9yYeQNH/j6CVVdWISw2DN33d8fS3kuxbsA66Kh9XBJB6teHdNcu9eTJE0yYMAFCoRDjx4/HwIEDAZTcU21gYIBHjx7B19cXCQkJsLCwwJo1a8S6eTdEEydOxPDhw7m/s7Oz4ePjg9TUVJiYmHDlKSkpEjEtKyEhAbNmzUJeXh6OHz+Ozp3F5xW3sbFBSEgI0tPToa2tDQ0NDfTq1QtffPFFjetcKCjE2edn4R/hj7DYMK68i1EXuNm6YarVVBhqGdZ4v4QQQgj5OHLTkv4hXSsJIfJFiaeEmTYz8c+CfzDHbg6EIiG2/7UdFnssEBgZSF3gG5CP6a5tZmaGM2fOYPPmzbhw4QI3Wnlubi7y8vLg6emJb775Bvv374eWlhYmT55cJ/dU1yc9PT20adOGe3Tu3Bna2tpiA7olJCQgMTERPXr0kLqP9PR0TJs2DSKRCAEBARIJemxsLCZNmoSsrCwYGhpCQ0MD9+7dQ05ODj799NNq1/VZyjMs+WMJTH80xeSzkxEWGwZNFU1Mt56OmzNv4uncp1jSewkl6IQQQoiMyE2S/iFdKwkh8slA0wD7R+7HHdc7sDOxQ0JOAsb/Mh7DTgzDy/SXsq4ekaI2u2vr6+vDwsIC48aNwzfffIMjR45AKBRCRUUFBQUF2LBhAxwdHWFlZYUdO3aAx+Ph119/rcvDq3dqamr46quvsG3bNvz555949uwZli1bhp49e8La2hpASSxTU1PB5/MBABs3bkRmZiZ++OEHaGhoIDU1FampqdxtX2ZmZkhOToanpyfi4uJw+/ZtLF++HF988QXatGlTaX3y+Hk4/PAwPj30Kbru6wrfO77IKMiATQsb7B2xF++Wv8PhUYfxaatPwePx6jQ2hBBCCKmc3HR3/5iulYQQ+dTDtAfuuN6B3wM/fHv1W1x6dQld93XF/336f1jTbw20VLVkXUXyr9rorn337l00adIEFhYWXFmnTp1QWFiI7Oxsbjtzc3Nuubq6OszMzJCQkFDbhyRzS5YsgUAgwMqVKyEQCNCvXz+sW7eOW/7w4UNMmzYNR48eRffu3XH58mWIRCKMHz9ebD/KysqIjIyEiooKDhw4AE9PT4wePRpNmzbFmDFjKh1xP+JdBPwf+OPk05PIKSqZyq2JWhNM7jYZbnZusDWRnK+dEEIIIbIlN0n6x46ESwiRT8pKypjbYy7GdRmHVVdW4cjfR/D99e9x/Mlx7By2E86dnGVdRYKS7tp6enrc33w+n+uuPWrUKABVd9f29/eHkpISDhw4wJU9fvwYhoaG0NfXh52dHYCSe9YHDBgAACgqKsKbN28wcuTIOjoy2VFRUcHq1auxevVqqct79eqFf/75h/u7OvPFf/LJJzh69Gil6+QU5eDkk5Pwj/BHxLv/bhfrY9YHbrZu+NLyS2iraVfzKAghhBBS3+QmSdfQ0OC6Vqqo/Fet6nStJITIv+bazXF41GG42rhi3oV5eJz8GC6nXOBs7gzfYb5op99O1lUkZZTtrq2vrw9DQ0Ns3LhRort2dnY2dHV1oaamhunTp2PWrFk4ePAgPvvsM9y9e5ebco3H48HMzAwuLi7YuHEjvv/+exgbG2PPnj1QUlKCi4uLbA+4gWOM4XbCbfhH+OPnZz8jv7hkLnV9DX1M6z4Nrrau6Nq8q4xrSQghhJDq4DE5Gcnp8ePHGD9+PMLCwsS6Vjo6OmLSpElwc3Pjyh48eMC1yBBCGh6BSIA9d/dg7bW1eM9/Dw0VDbj3c8fKT1dCXUVd1tUj/xIIBNixYweCgoLEumsbGBgAAO7cucN11+7VqxcA4NKlS9i9ezdiY2NhYmICV1dXse7bfD4f3t7eCA4ORm5uLqytreHh4YFPPvlEJsfY0GUUZODYo2Pwj/DHs9RnXPnAtgPhZuuGsRZjoaGiIcMaEkIIIaSm5CZJ5/P56N27N9avXy/WtdLJyQk///wz13IDUJJOSGPx7v07rLi8AiefnAQAdDToiN3Dd2Nox6G1sn+hUAgfHx8EBQUhLy+PSzKbNWtW4TZJSUnYvHkzrl+/Dg0NDQwdOhSrVq3ievRkZGRgy5YtuH79Ohhj6N27N9asWYMWLVrUSp0JqQpjDOFx4fCP8MeZyDMoEpbcEtZcuzmmd58OV1tXfGJIFz0IIYSQhkpuknQAXIvNli1buK6V6urqOHbsmNh6lKQT0rhce30N8y/Mx/O0kntyx1mMg/dQb7TSbfVR+/Xx8UFgYCC8vLygp6eHjRs3QllZGQEBAVLX5/P5GDVqFIyMjPDtt98iKysLq1evhqOjIzfg1/Tp01FUVIS1a9eCx+Phu+++A5/Px5kzZz6qroRUJTk3GT89+gkHIw7iZUbJLAk88DCkwxC42brBuZMz1JTVZFxLQgghhHwsuUrSq+paWYqSdEIaH76QD9/bvtgYvhF5xXnQVtXGugHrsKT3kg9KPEp753h4eGDs2LEA/uudExAQAFtbyVGtz5w5gy1btiA0NBS6uroAgMDAQJw6dQqBgYHIzc2Fvb099u7dC0dHRwBAeHg4Zs+ejdu3b0NfX/8jIkCIJBET4fKry/CP8Mev//wKgahkSjzTJqaYaTMTM21moq1eW9lWkhBCCCG1Sq6S9OqiJJ2QxutN9hssu7QMgZGBAACLZhbYM2IPBrUbVKP9lI5zERoaCjMzM67c0dEREydOxOzZsyW2Wbp0KYRCIXbu3Cl1n8XFxejVqxccHBywefNm8Hg8eHh44NmzZ/jjjz+gpKRUozoSUpGEnAQcfngYhx4eQlx2HABAmaeMz80/h5utG4Z1HAYVJbkZ+5UQQgghtYg+4QkhcqWVbiv8Mv4XhESHYOHFhXie9hyORx0xqesk/DDkB5g0Mal6Jyi5txyAxJzezZs355aVFxsbi969e8PHxwfBwcHg8XgYMmQIlixZAnV1daiqqmLr1q1Yu3Yt7O3twePxYGhoiBMnTlCCTj7YiScn4B7qjvjseDTTagbTpqZ4nPwYIiYCALTVawtXG1fMsJmBlk1ayri2hBBCCKlrlKQTQuTS0I5D8WTuE2z/azs2Xd+EgKcB+D3qd3w36Dss6LmgylbEgoICKCkpQVVVVaxcTU0NRUVFUrfJzc1FYGAg+vfvD19fXyQnJ8PT0xMZGRnw8vICAMTExMDc3BwLFy6EkpISfH19sWDBAgQEBEBHR6d2Dp40OIwxFIuKUSgoRJGgCIWCQu5RJBT/u+w61+Ou4+TTkygWFQMAUvNTkZqfCiUoYXyX8XCzdYNTeyco8egiECGEEKIoKEknhMgtdRV1ePT3wORuk7H4j8X4Leo3LA1ZisN/H8beEXvRt3Vfbt39+/fjwIED3N+zZ8+GSCSCQCCAisp/b3V8Pp8bqb08FRUV6OrqYtu2bVBWVka3bt0gEAiwePFirF69Gq9evYKvry/CwsK4Fvo9e/Zg0KBBCAoKwtSpU+soEvKtbEtwa93W2OS0CZO7Ta6352eMQSASVJoY1yRxLhQUolAouU1V+2WovbvHWjZtidPjT9fa/gghhBDScFCSTgiRe+302yF4UjB+++c3LPpjER4nP4bDYQdMt54Or8FeaK7dHBMnTsTw4cO5bbKzs+Hj44PU1FSYmPzXRT4lJUWiC3wpY2NjqKurQ1lZmSvr2LEjACAxMRF///03jIyMxLZv2rQp2rZti7i4uNo+7AbhxJMTmP3bbOQX5wMA4rLj4BrsioTsBAxuP7hGibPUdapKpv9dp7RruCypKqlCQ0UD6irq0FDR4B7qyuX+Ll2urIH//f0/qftKzEms59oTQgghRF5Qkk4IaTCcOznDqb0Ttlzfgm1/bcORv4/g3Itz2Oy4GbPtZkNPT49bl8/nQ1tbG3fv3sWoUaMAlIzunpiYiB49ekjdv729PU6fPo3i4mKum3xUVBSUlZVhamqKFi1aID09Henp6TA0NARQ0q0+ISEBY8aMqduDlzHGGNLy0/Aq8xWiM6LxKuMVojOjcfrZafCFfLF1CwWFWB26Ggitv/qpKKlUmBRXJ3GuNJmuxjrqyupQVlKuuqLlhL4O5QaGK6u1buvaCAshhBBCGiAa3Z0Q0iC9TH+JBRcX4NKrSwAA+5b22DtiL3qY/peAl07puGXLFhgaGmLjxo1QV1fHsWPHAJQk8tnZ2dDV1YWamhrS0tLw+eefw8HBAfPmzUNycjLc3d3Ru3dvbNmyBXl5eRg1ahRMTEywatUqqKqqYufOnXjy5AkuXLjQ4O9JFzER3r5/W5KAZ0SXJOOlSXnmK+QU5dRof7YmtnWWFJdf50MSZHlQvicCAGipasHP2a9ebxkghBBCiPygJJ0Q0mAxxnD2+VksCVmChJwE8MDDbLvZ2Oy0GQaaBhAIBFyiLhAI0K9fP6xbtw4GBgYAgDt37mDatGk4evQoevXqBQCIjo7Gli1bcP/+fWhpacHFxQXLly+HmlrJXO2JiYnYtm0b7t69C8YYbG1tsWbNGrRq1UpmcagJgUiAuKw4iQQ8OiMaMZkxKBQUVrhtU/Wm6GjQER30O3A/3a+6IzkvWWLdNrptELsktg6PpPGQ9T39hBBCCJEvlKQTQhq8XH4uPMM98ePtHyEQCdBMqxm8BnthuvV0hRwVu6C4AK+zXv/XLT0jGtGZJb/HZsVCyIQVbttcu7lYEt7RoCM6GJT8NNQ0BI/HE1ufWoIJIYQQQmoXJemEkEYjMjUS8y/MR1hsGACgj1kf7P18L6xbWMu0XnUhpyhHLAkv2yqekJNQ4XY88GDW1Kwk8dbvKJaEt9dvj6bqTWtcF2oJJoQQQgipPZSkE0IaFcYYAp4GYPml5UjKTYISTwnze8yH5yBP6Groyrp61VY6UJu0bunRGdFIy0+rcFsVJRW01Wsr0TW9o0FHtNNvBw0VjXo8EkIIIYQQUhOUpBNCGqXswmysD1uPXXd3QcREMNY2xo4hOzC522SJLtuyUjpQGzdI278jppe2jr/nv69wW00VTXQw6CC1a3pr3dZQUaLJOwghhBBCGiJK0gkhjdqjpEeYd2Ee/nrzFwBgQJsB2DNiDyybW9bL8xcLixGXHSe1W/qrjFcoEhZVuK2uuu5/3dH1/+uW3kG/A0yamCjk/faEEEIIIY0dJemEkEZPxET46e+f8H9X/g9p+WlQUVLBkl5LsH7geuioffy0aQXFBYjJjBHrjl76e1xWXKUDtRlrG4sl32V/GmgayE2rPyGEEEIIqR+UpBNCFEZGQQbcQ91x4MEBMDCYNjGF91Bv8IV8uF+tfOCz7MLs/1rBy7WKJ75PrPA5eeChlW4riQS8dKC2JupN6vqwCSGEEEJIA0JJOiFE4dxLvId5F+bh/tv7AAAlnhJETMQtV1NWw8hPRkJTVZNLxqsaqK2dXjup05a11WtLA7URQgghhJBqoySdEKKQhCIhDkYcxLzz8yCCqMr1SwdqK98a3kG/A1rptqKB2gghhBBCSK2gJJ0QotCUNiqBQfrb4P9c/se1ipvomND94YQQQgghpM5R0w8hRKG11m2NuOw4ifI2um0ww2aGDGpECCGEEEIUGc3fQwhRaJucNkFLVUusTEtVC5ucNsmoRoQQQgghRJFRkk4IUWiTu02Gn7Mf2ui2AQ88tNFtAz9nP4nR3QkhhBBCCKkPdE86IYQQQgghhBAiJ6glnRBCCCGEEEIIkROUpBNCCCGEEEIIIXKCknRCCCGEEEIIIUROUJJOCCGEEEIIIYTICUrSCSGEEEIIIYQQOUFJOiGEEEIIIYQQIicoSSeEEEIIIYQQQuQEJemEEEIIIYQQQoicoCSdEEIIIYQQQgiRE5SkE0IIIYQQQgghcoKSdEIIIYQQQgghRE5Qkk4IIYQQQgghhMgJStIJIYQQQgghhBA5QUk6IYQQQgghhBAiJyhJJ4QQQgghhBBC5AQl6YQQQgghhBBCiJygJJ0QQgghhBBCCJETKrKuwId68OCBrKtACCGEEEIIIYR8EDs7O6nlPMYYq+e6EEIIIYQQQgghRArq7k4IIYQQQgghhMgJStIJIYQQQgghhBA5QUk6IYQQQgghhBAiJxQ6SRcKhfjhhx/g4OAAGxsbLFq0CGlpaRLrFRcXY/To0Vi9erXEsvDwcEyYMAEAEBcXh3nz5qFXr17o3bs3Fi1ahLdv34qtHxwcjKFDh8LKygpffvklHj9+LLb8r7/+woQJE2BjY4NBgwbBy8sLhYWF3PK0tDSsWrUKDg4OsLe3x6xZsxAVFVUb4aiWqmI2btw4dOrUSezh7u4utg9Fi1l5VcUwOjoaM2fORPfu3dGvXz/4+PhAJBKJ7UPRYlhZzBwdHSXOudJH2TgoWszKquqcu3jxIpydnWFtbY0RI0bgzJkzEvug+FUcv3PnzmHkyJGwtrbG+PHjcfPmTYl9KHL81q1bJ/E5cOPGDYwaNQpWVlZwdnZGeHi4xHaKHLPypMUQAH7//Xd89tlnUrc5efIkli1bBgB49uwZpk+fDnt7ezg4OMDd3R1ZWVli6x85cgSDBg1C9+7dMWPGDMTGxootv3DhAkaNGgVra2t89tln8PPzg1Ao5JZX539Un6TF7Pjx4xg2bBj3XvfLL79IbKfI5111vxc/ePAAXbt2lbqP+o5fUlISFi1ahJ49e8Le3h5Lly5FcnLyx4big1QVP3k8/+ozfpXFhzEGPz8/ODo6wsrKCmPHjkVYWJjEPhpzfCQwBebt7c369u3Lbty4wZ4+fcrGjx/PJk6cKLHejh07mLm5OVu1apXEMk9PT7Zr1y6Wl5fHnJyc2Jw5c9jz58/Z06dP2ZQpU9iIESNYUVERY4yxmzdvMktLS3bq1CkWHR3N3N3dmb29PUtPT2eMMfb8+XNmaWnJvL292evXr9mff/7JBgwYwNasWcMYY0woFLIJEyawL7/8kj169Ii9fPmSLVq0iPXp04dlZGTUYaT+U1nMRCIRs7a2ZsHBwSwlJYV7vH//XqFjVl5lMUxPT2e9e/dmS5YsYa9evWKXL19mdnZ27ODBg2L7ULQYVhWzsudbXFwcGzBgAFu+fLlCx6ysyuJ37949ZmlpyQICAlh8fDwLCAhgFhYW7Nq1a2L7oPhJj19wcDDr1KkT279/P4uJiWHHjx9n3bp1Y7dv3xbbhyLGTyQSMR8fH2Zubs6+/fZbrvzly5esa9eubO/evSw6Opp5e3szS0tLFhUVJba9IsasvIpiyBhjV69eZVZWVmzw4MFSt/3mm2/Y2bNnWVJSEuvRowdzd3dn0dHR7P79+2zkyJHs66+/5tY9ffo0s7GxYRcvXmQvXrxgc+bMYU5OTlx8w8LCmIWFBTt27BiLi4tjFy9eZPb29mz37t2MMVat/1F9qShmJ06cYNbW1uzcuXMsLi6OnT59mllaWrKgoCCx7RX5vKvO9+K///6b9ezZk1lYWEjdR33GTyQSMWdnZ/b111+z58+fs+fPn7PJkyezMWPG1GGUKlZZ/OTx/Kvv+FUWn0OHDjE7Ozt2+fJlFh8fz/bu3cssLCzY06dPFSY+5Slskl5UVMRsbGzYmTNnuLI3b94wc3Nz9uDBA67s/v37rE+fPmzkyJFSk/QhQ4awR48esUuXLrEuXbqIJaRv375l5ubm7O7du4wxxmbOnCm2D6FQyJycnNi+ffsYYyUn3rhx48T2HxQUxCwtLRmfz2fPnj1j5ubmLDo6Wuw4unfvLvEirwtVxSwuLo6Zm5uz+Pj4SvejSDErr6oY+vr6ssGDBzM+n88t37VrF5s/f77YfhQphtV9rZZat24dc3R0ZPn5+WLlihSzsqqK39atWyU+cMaNG8c8PT3Fyih+0uPn4uIicUHI3d2dTZkyRaxM0eIXHx/PpkyZwnr16sUGDhwoliytXbtWIj5TpkxhHh4eYmWKFrPyKophQUEB8/DwYJaWlszZ2Vlqks7n85mtrS1LSUlhhw8fZn379mUCgYBbfu/ePWZubs4SExMZYyWx3rlzJ7c8NzeXu+jOWEnCv3jxYrHn2L17N3N0dGSMsWr9j+pDZeeds7Mz27Ztm9j6a9asYVOnThUrU9Tzrjqftdu3b2eWlpZs9OjRFSbp9Rm/lJQUtmTJEvbmzRtu+eXLl5m5uTnLysr6yIjUTFXxk8fzrz7jV1V8du/ezU6fPi22jb29PTt8+LBYWWONjzQK2939xYsXyMvLQ8+ePbkyMzMzmJqa4v79+wCAvLw8rFq1Ch4eHjA0NJTYx5s3b5CVlYWuXbvCysoKfn5+0NHR4ZYrKZWENzs7GyKRCBEREWLPp6SkhB49enDP9+WXX2L9+vViz6GkpITi4mIUFBTAxMQEBw4cQLt27bjlPB4PjDFkZ2fXQlQqV1XMoqKioKGhAVNT0wr3oWgxK6+qGN64cQODBw+Gqqoqt3zBggXYvXs397eixbA6r9Wy654+fRrr1q2DpqYmV65oMSurqvjp6+vj5cuXuH37NhhjuHfvHl6+fCnWlZHiV3H84uLiYG9vL7aNhYUFHj58CIFAAEAx4/fw4UO0atUKv/32G8zMzMSW3b9/X+z4AKBXr15ir2dFjFl5FcUwPT0d8fHxOHXqVIVd3e/fv4/WrVvDyMgIjo6O8PHxgbKyMrecx+MBAHJycpCeno7Y2Fix+Glra6Nr165c/ObOnYsFCxaIPYeSkhJycnIAoMr/UX2p7Lzz8PDAxIkTxcrKHgOg2OdddT5rb926BT8/P0ydOlXqPuo7fkZGRvD29ub+10lJSfj555/RrVs36Orq1kJUqq+q+Mnj+Vef8asqPvPnz8f48eMBAEVFRThx4gQKCgrE1m/M8ZFGpc6fQU4lJSUBAIyNjcXKmzdvzi3bvHkzunXrhhEjRuD06dMS+/jzzz/h4OAAJSUlGBsbS+zLz88PmpqasLOzQ05ODvLz86U+35MnTwAA5ubmYsuKi4tx5MgRWFtbo2nTpgCAgQMHiq1z7NgxFBUVwcHBoYYRqLmqYiYUCtGkSROsWLECd+/ehb6+PsaOHYuvv/6ae+EoWszKqyqGsbGxGDp0KDw9PXHp0iVoa2tjzJgxcHV15b5gKVoMq/NaLbVr1y7Y2dlhwIABYuWKFrOyqorf8uXLERERga+//hrKysoQCoWYOXMmRo8eza1L8as4fs2bN8e7d+/EliUmJqK4uBg5OTkwMDBQyPi5uLjAxcVF6rKkpKQqX8+KGLPyKoqhqakpfvrpJwDAtWvXpG57/fp19OvXDwDQunVrtG7dWmy5v78/jI2N8cknn+DFixcAKn+PtbKyEluWm5uLgIAA7jmq+h/Vl8rOu/IXht6+fYvz589jypQpXJkin3fV+awtHa/k7NmzUvchi/iVmjdvHkJDQ6Grq4ujR4/W5NBrRVXxk9fzr1Rdx6+63+UuXbqERYsWgTGGxYsXo0uXLtyyxhwfaRS2Jb2goABKSkpiLZYAoKamhqKiIly9ehXh4eESV1jKKvshWN7Jkydx/PhxrFixAvr6+twgBOrq6mLrqaqqoqioSGJ7oVCI1atX4+XLl/Dw8JD6HKGhofjxxx8xY8YMdOjQodLjrQ1VxSw6Ohr5+flwcHDAoUOH8NVXX2Hnzp1ircCKFrPyqophbm4u9u/fD2VlZezfvx/ffPMN/P39sWfPHm5dRYthVTEr9ebNG1y9ehVz5syR2IeixaysquKXkZGB9PR0rFy5EmfOnIGHhwdOnjyJwMBAbl2KX8Xxc3FxwYkTJ3Dr1i0IhULcvn2b+yJbXFwMQLHjJ01hYSHU1NTEysq/nilmH+f69evo37+/1GU7duxAWFgY1q9fD2VlZRQUFACQjF/5/0mpgoICzJs3D0VFRVi+fLnU5yj/P5I3GRkZmDNnDpo1a4bZs2dz5Yp83lX3s7YysozfokWL8Msvv8DW1hYzZsyo98HjahI/eTz/6jp+1Y1P9+7dce7cOaxZswZ79+4VayRtzPGRRmGTdA0NDYhEIq47Yik+nw81NTV4eHjg+++/h56entTt+Xw+7t69K/Vk2bdvHzZu3Ig5c+ZwV8hKTxI+ny+2bnFxsVi3XKDkRF6wYAEuXbqEnTt3olu3bhLPcfbsWSxatAjDhw/HypUrq33cH6OymGlqasLLywthYWEYO3YsOnXqhEmTJmHu3Lk4cuQIGGMKGbPyqoqhiooKOnXqhG+//RaWlpYYPXo05s6dy7WaKGIMq4pZqd9++w0mJiYSrQ+KGLOyqoqfh4cHLCws4OrqCgsLC0ydOhUzZ87E9u3b6XWLquM3e/ZsuLi4wM3NDV27dsWmTZswa9YsAECTJk0UPn7SqKurcxcwSpV9PVPMPk5ycjLevXsHa2trsXKhUIj169fj4MGD2LBhA5ycnACUnOOAZPzKv8cCJcnFjBkzEBkZCX9/f6m3t0n7H8mTN2/eYNKkScjJycH//vc/NGnSBACdd9X9rK2IrOPXuXNnWFlZwdvbGyKRCEFBQVXWuTZVN37yev7VdfyqGx9jY2N07twZ06dPx7hx43Do0CFuvcYcH2kUtru7iYkJACA1NZX7HQBSUlLg4OCA9PR0LF26lCsvKioCj8dDSEgIHj58iAcPHqBt27Zi96qLRCJs2LABP//8M1asWAE3NzdumZ6eHrS0tJCSkiJWj5SUFLGuGJmZmZgzZw6io6Ph5+eHPn36SNR937598PHxwZQpU+Dh4cHdW1bXKouZsbExVFRUJLqHdOrUCXl5eXj//j2ePXumcDErr6oYGhsbS3S/6dixI3Jzc5GZmYkXL14oXAyrilmp0NBQDB8+XKJeivhaLauq+AUGBmLkyJFi23Tv3h179+5FTk4OIiMjKX6oOH5qampYt24dVq9ejezsbBgZGeHo0aNo1qwZtLS0cOvWLYWOnzQmJiaVHp+iv2Y/1p9//ok+ffpAReW/r3hFRUVYvHgxbty4ge3bt8PZ2ZlbVvYcb9OmDVeekpIi1pqbkJCAWbNmIS8vD8ePH0fnzp3Fnrey/5G8iIyMhJubG5o2bYpTp06JvaYV/byr7mdtRWQRv7S0NNy5cweff/45V6apqYlWrVrVe0t6deInb+dffcavqviEhYWhXbt2Yu9B5ubm+PXXXwE0/vhIo7At6Z07d4a2tjbu3r3LlSUkJCAxMRG9e/fGpUuXcO7cOe5hZWUFR0dHnDt3DkDJh2D5qznfffcdAgMDsWXLFokPJx6PBxsbG9y7d48rE4lEuHfvHnr06AGgpAvgrFmz8ObNGxw7dkzqG7m/vz98fHywaNEirF27tl7fyCuLWY8ePfDll19i06ZNYts8efIEzZs3R9OmTRUyZuVVFUN7e3vuXplSUVFR0NXVha6urkLGsKqYAUB+fj6eP3+O3r17S2yviDErq6r4GRsb459//hHbJioqCnp6egp7zpVVVfy8vb3h5+cHNTU1GBkZAQCuXLmCvn37AqDzTxo7Ozux4wOAO3fucAPwUcw+Tvmu7iKRCIsXL8bt27exb98+sQQdAAwNDdG2bVuxczwvLw9Pnz7l4peeno5p06ZBJBIhICBAIkEHKv8fyYNXr15hxowZaNmyJU6ePCmWKAB03lXns7Yysojf27dvsWzZMrHvTe/fv8fr16/RsWPH6h98LagqfvJ4/tVn/KqKz7Zt27heo6WePHnCXShs7PGRqs7Hj5dj27dvZ59++ikLDw/n5usrPy1Mqa+//lpsGP/PP/+c3bt3j/s7LCyMmZubs507d4rN2ZySksIKCwsZY4yFh4ezLl26sOPHj3Pz9fXs2ZObr2/r1q3MwsKChYWFSexDKBSy58+fMwsLC7ZmzRqJ5Xl5eXUYqf9UFjM/Pz/WtWtXFhQUxM0B2b17d25KBUWNWXmVxTAqKop169aNbdq0icXGxrKQkBBmb2/Pdu3axRhT3BhW9VqNiIhg5ubmLCkpSWJbRY1ZWZXF7/jx48zS0pKdPHmSxcfHs+DgYGZra8sOHTrEGKP4MVZ5/E6fPs1sbW1ZWFgYi4+PZ56ensza2pq9evWKMUbxY6xkerWyU2G9ePGCWVpaMl9fXxYdHc18fHxYt27duGmoKGaSysew1M6dO8WmYBMIBMze3p69e/eOKzt+/DgzNzdnp0+flji20uk+T548yaytrdnvv//O/vnnHzZnzhw2ZMgQbr7hhQsXMmtra/bo0SOx7VNTUxlj1fsf1bfyMRs3bhxzcHBgMTExYvUrPUfovKv+9+IzZ85ITMEmi/gJhUL21VdfMRcXF/bo0SP27NkzNnPmTDZ48GCWm5tbh5GSrrL4yeP5V9/xq+qz1NLSkp05c4bFxsYyf39/1qVLFxYWFqYw8SmPxxhjdX8pQD4JBALs2LEDQUFBEAgE6NevH9atWwcDAwOJdadPn44WLVpg69atSEpKgrOzM27dusV1J1u+fDl+//13qc+zbds2jBo1CkDJyJh79+5FamoqunTpgrVr18LS0hIA4ODggNTUVKn7CA8Px8mTJ3HgwAGpyxcvXox58+bVOAY1VVnMGGM4cuQITp06hbdv36Jly5aYOXMmJkyYoNAxK6+q8+7BgwfYvn07nj17BgMDA0ycOBFz5sxBSkqKwsawqphdunQJCxcuxJMnT8QGpKLzrkRV8fvll1/w008/ISEhAaampvjqq6/w1VdfITk5meKHquO3d+9e/Pzzz8jJyUHXrl2xcuVKWFlZ0fn3r6lTp6J169ZiPa3CwsKwfft2xMfHo3379li1ahU+/fRTilkFpMUQKJnRIjg4GJcvXwZQMvXahg0bxOI1ceJEPHz4UOp+T5w4wfVg8PPzw9GjR5GXlwdbW1ts2LABrVq1QmFhIWxsbCASiSS2V1ZWRmRkZLX/R/WpbMxev36NYcOGSV2vdevWOHbsGJ13qP734rNnz8LDwwORkZEAZPdZ26JFC2RkZGDbtm0IDw/nRsV3d3evVhf92lZR/LKzs+Xy/Kvv+FV1fgUEBODIkSN4+/Yt2rVrh8WLF8PJyUlhzy+FTtIJIYQQQgghhBB5orD3pBNCCCGEEEIIIfKGknRCCCGEEEIIIUROUJJOCCGEEEIIIYTICUrSCSGEEEIIIYQQOUFJOiGEEEIIIYQQIicoSSeEEEIIIYQQQuQEJemEEEJIA+fo6IhOnTrh5MmTUpfPmjULnTp1wq+//lrPNSOEEEJITVGSTgghhDQCqqqqCAkJkSjPysrCnTt3ZFAjQgghhHwIStIJIYSQRqB37964d+8eMjIyxMovX76M7t27y6hWhBBCCKkpStIJIYSQRsDGxgbNmjXDlStXxMovXryIESNGiJVduXIFLi4u6NatG4YNG4ZDhw5BJBJxy/38/ODk5ISuXbti6NChOHHihNj2p0+fxtChQ2FlZQVnZ2cEBQVxy4RCIby8vNCvXz907doVzs7OuHjxYh0cMSGEENI4UZJOCCGENAI8Hg9DhgwR6/KekZGBe/fuYejQoVxZeHg4VqxYgWnTpuH8+fNYuXIljh49ir179wIArl69ikOHDuH7779HSEgIXF1d4enpiXv37gEATp48CW9vbyxduhS///47XF1dsWnTJi5RP3nyJC5fvoxdu3bhjz/+wLBhw7B8+XK8efOmHqNBCCGENFwqsq4AIYQQQmrHsGHDMH36dGRnZ0NXVxeXLl2Cra0tmjVrxq2zf/9+TJo0CV988QUAoHXr1sjLy8PatWsxb948xMfHQ1VVFS1btoSpqSnGjx8PMzMztG/fntt+wYIFGDZsGLf927dvsX//fowZMwZxcXHQ1NSEqakpjIyMMG/ePFhZWUFPT6/e40EIIYQ0RJSkE0IIIY2EnZ0d9PX1ERoairFjx0rt6v78+XM8efIEp06d4spEIhEKCwuRmJgIZ2dnBAYGYsiQITA3N4eDgwNcXFxgaGiIjIwMJCcnw8vLCzt27OC2FwgEEAqF4PP5+Oqrr3D58mX0798fXbt2Rb9+/TBq1Cg0adKk3uJACCGENGSUpBNCCCGNBI/Hw9ChQxESEoKBAwciIiIC3t7eYuuoqqrC1dUVzs7OEtsbGxtDTU0NwcHBePDgAW7cuIHw8HD89NNP8PLywsCBAwEAa9euRc+ePSW2V1FRQfv27XHlyhXcunULN2/exPnz5/G///0PBw4cQK9everkuAkhhJDGhO5JJ4QQQhqRYcOG4a+//sK5c+fQs2dPGBgYiC3v2LEjYmNj0aZNG+4RFRXFJfMXLlxAQEAAevTogaVLl+LcuXPo27cvgoOD0aRJExgbGyMhIUFs+7/++guHDh2CkpISTpw4gUuXLqF///5Ys2YNLl68CDMzMxo8jhBCCKkmStIJIYSQRsTW1ha6urrYvXu3RFd3AJg7dy7Onz8PPz8/xMbGIiwsDOvWrYOGhgbU1NTA5/Ph5eWF4OBgJCYm4tatW4iMjOSmcZs7dy6OHDmCn3/+GfHx8fjtt9+wdetWGBkZAQAyMzPh6emJa9euITExEaGhoUhISKBp4AghhJBqou7uhBBCSCOipKSEoUOH4ueff8bgwYMllvfv3x/btm2Dn58fdu7cCQMDA4wePRpLly4FAIwePRrp6enYtWsX3r17B0NDQ4wdOxbffPMNAGDSpEng8/k4dOgQPD09YWxsjHnz5mH27NkAgG+++QaFhYXYuHEj0tLSYGJigoULF2LMmDH1FwRCCCGkAeMxxpisK0EIIYQQQgghhBDq7k4IIYQQQgghhMgNStIJIYQQQgghhBA5QUk6IYQQQgghhBAiJyhJJ4QQQgghhBBC5AQl6YQQQgghhBBCiJygJJ0QQgghhBBCCJETlKQTQgghhBBCCCFygpJ0QgghhBBCCCFETvw/RaNpLdpNGjwAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1224x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('seaborn-whitegrid')\n",
    "\n",
    "ax, fig = plt.subplots(figsize=(17, 9))\n",
    "fig.plot(ipca_brasil['IPCA - Variação mensal'], label = 'Mensal', linewidth=2, marker='o', color='green')\n",
    "fig.plot(ipca_brasil['IPCA - Variação acumulada em 12 meses'], label = 'Acumulada em 12 Meses', linewidth=2, marker='o', color='blue')\n",
    "\n",
    "plt.grid(b=None)\n",
    "\n",
    "plt.legend(\n",
    "    title='Variação:',\n",
    "    title_fontsize=14,\n",
    "    loc='best',\n",
    "    ncol = 1,\n",
    "    #bbox_to_anchor=(0.70,0.55),\n",
    "    frameon=True,\n",
    "    facecolor='white',\n",
    "    shadow=True,\n",
    "    fontsize=15)\n",
    "fig.set_xlabel('Meses', fontsize=15)\n",
    "fig.set_ylabel('Variação (%)', fontsize=15)\n",
    "\n",
    "# Hide the right and top spines\n",
    "fig.spines.right.set_visible(False)\n",
    "fig.spines.top.set_visible(False)\n",
    "\n",
    "plt.yticks(fontsize=15)\n",
    "str_month_list = list(ipca_brasil.index.strftime(\"%m/%Y\"))\n",
    "plt.xticks(ipca_brasil.index,str_month_list, fontsize=15)\n",
    "\n",
    "# Remove all spines\n",
    "\n",
    "# Valores em cada ponto do gráfico\n",
    "for x,y in zip(ipca_brasil['IPCA - Variação mensal'].index,ipca_brasil['IPCA - Variação mensal'].values):\n",
    "\n",
    "    label = \"{:.2f}\".format(y)\n",
    "\n",
    "    plt.annotate(label, # this is the text\n",
    "                 (x,y), # this is the point to label\n",
    "                 textcoords=\"offset points\", # how to position the text\n",
    "                 xytext=(0,10), # distance from text to points (x,y)\n",
    "                 ha='center',\n",
    "                 size=15) # horizontal alignment can be left, right or center\n",
    "\n",
    "for x,y in zip(ipca_brasil['IPCA - Variação acumulada em 12 meses'].index,ipca_brasil['IPCA - Variação acumulada em 12 meses'].values):\n",
    "\n",
    "    label = \"{:.2f}\".format(y)\n",
    "\n",
    "    plt.annotate(label, # this is the text\n",
    "                 (x,y), # this is the point to label\n",
    "                 textcoords=\"offset points\", # how to position the text\n",
    "                 xytext=(0,13), # distance from text to points (x,y)\n",
    "                 ha='center',\n",
    "                 size=15) # horizontal alignment can be left, right or center\n",
    "\n",
    "plt.savefig('graficos/GRÁFICO 1 - IPCA 12M E MENSAL.svg', dpi=600)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Acumulado no Ano"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "#criar uma variável com os 12 meses do ano atual com o pacote datetime\n",
    "ano_atual = dt.datetime.now().year\n",
    "meses_ano_atual = pd.DataFrame({'data':pd.date_range(f'{ano_atual}-01-01', periods=12, freq='MS'), 'Values': range(0, 12)})\n",
    "meses_ano_atual.set_index('data', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1224x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('seaborn-whitegrid')\n",
    "ax, fig = plt.subplots(figsize=(17, 9))\n",
    "\n",
    "fig.plot(meses_ano_atual, alpha=0)\n",
    "fig.plot(\n",
    "    ipca_brasil[ipca_brasil.index.year == ano_atual]['IPCA - Variação acumulada no ano'],\n",
    "    marker='o', \n",
    "    label = 'Acumulado no Ano', \n",
    "    linewidth=2, \n",
    "    color='blue')\n",
    "\n",
    "#fig.plot(acumulado, marker='o', label = 'Acumulado no Ano', linewidth=2, color='blue')\n",
    "\n",
    "#fig.set_title('Variação Acumulado no Ano do IPCA')\n",
    "\n",
    "plt.grid(False)\n",
    "\n",
    "plt.legend(\n",
    "    title='Variação:',\n",
    "    title_fontsize=14,\n",
    "    loc='upper left',\n",
    "    ncol = 1,\n",
    "    #bbox_to_anchor=(0.05,0.97),\n",
    "    frameon=True,\n",
    "    facecolor='white',\n",
    "    shadow=True,\n",
    "    fontsize=15)\n",
    "\n",
    "fig.set_xlabel('Meses', fontsize=15)\n",
    "fig.set_ylabel('Variação (%)', fontsize=15)\n",
    "\n",
    "# Hide the right and top spines\n",
    "fig.spines.right.set_visible(False)\n",
    "fig.spines.top.set_visible(False)\n",
    "\n",
    "plt.yticks(fontsize=15)\n",
    "str_month_list = list(meses_ano_atual.index[-12:].strftime(\"%m/%Y\"))\n",
    "plt.xticks(meses_ano_atual.index,str_month_list, fontsize=15)\n",
    "\n",
    "#Valores em cada ponto do gráfico\n",
    "for x,y in zip(ipca_brasil['IPCA - Variação acumulada no ano'].index, ipca_brasil['IPCA - Variação acumulada no ano'].values):\n",
    "\n",
    "    label = \"{:.2f}\".format(y)\n",
    "\n",
    "    plt.annotate(label, # this is the text\n",
    "                 (x,y), # this is the point to label\n",
    "                 textcoords=\"offset points\", # how to position the text\n",
    "                 xytext=(0,13), # distance from text to points (x,y)\n",
    "                 ha='center',\n",
    "                 size=15) # horizontal alignment can be left, right or center\n",
    "    \n",
    "plt.savefig('graficos/GRÁFICO 2 - IPCA NO ANO.svg', dpi=600)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Regiões <a id=\"graficos-ipca-regioes\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Seleciona somente as linha com a variação regional, inverte, e renomeia as colunas"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Preenchimento da tabela no Excel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "workbook = oxl.load_workbook(filename='tabela_regioes.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "sheet = workbook.active"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in ipca_regioes.index:\n",
    "    sheet[f\"A{i+4}\"] = ipca_regioes.loc[i,'Brasil, Região Metropolitana e Município']\n",
    "    sheet[f\"B{i+4}\"] = ipca_regioes.loc[i,'Peso']\n",
    "    sheet[f\"C{i+4}\"] = ipca_regioes.loc[i,'IPCA - Variação mensal - anterior']\n",
    "    sheet[f\"D{i+4}\"] = ipca_regioes.loc[i,'IPCA - Variação mensal - atual']\n",
    "    sheet[f\"E{i+4}\"] = ipca_regioes.loc[i,'IPCA - Variação acumulada no ano']\n",
    "    sheet[f\"F{i+4}\"] = ipca_regioes.loc[i,'IPCA - Variação acumulada em 12 meses']\n",
    "\n",
    "sheet[f\"A20\"] = 'Brasil'\n",
    "sheet[f\"B20\"] = 100.00\n",
    "sheet[f\"C20\"] = ipca_brasil.loc[data_anterior,'IPCA - Variação mensal'][0]\n",
    "sheet[f\"D20\"] = ipca_brasil.loc[data_atual,'IPCA - Variação mensal'][0]\n",
    "sheet[f\"E20\"] = ipca_brasil.loc[data_atual,'IPCA - Variação acumulada no ano'][0]\n",
    "sheet[f\"F20\"] = ipca_brasil.loc[data_atual,'IPCA - Variação acumulada em 12 meses'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "workbook.save(filename=\"tabelas\\IPCA REGIÕES.xlsx\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Curitiba <a id=\"graficos-ipca-curitiba\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Preenchimento da tabela no Excel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "workbook = oxl.load_workbook(filename='tabela_curitiba.xlsx') #Substituir Valores no Excel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "sheet = workbook.active"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Preenche a tabela das categorias do ipca de curitiba\n",
    "for i in ipca_curitiba.index:\n",
    "    sheet[f\"A{i+4}\"] = ipca_curitiba.loc[i, 'Geral, grupo, subgrupo, item e subitem']\n",
    "    sheet[f\"B{i+4}\"] = ipca_curitiba.loc[i, 'IPCA - Variação mensal - anterior']\n",
    "    sheet[f\"C{i+4}\"] = ipca_curitiba.loc[i, 'IPCA - Variação mensal - atual']\n",
    "    sheet[f\"D{i+4}\"] = ipca_curitiba.loc[i, 'IPCA - Variação acumulada no ano']\n",
    "    sheet[f\"E{i+4}\"] = ipca_curitiba.loc[i, 'IPCA - Variação acumulada em 12 meses']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "workbook.save(filename=\"tabelas\\IPCA CURITIBA.xlsx\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## INPC <a id=\"graficos-inpc\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Brasil <a id=\"graficos-inpc-nacional\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Acumulado 12 Meses e Variação Mensal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 936x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('seaborn-whitegrid')\n",
    "\n",
    "ax, fig = plt.subplots(figsize=(13, 6))\n",
    "fig.plot(\n",
    "    inpc_brasil['INPC - Variação mensal'], \n",
    "    label = 'Mensal', \n",
    "    linewidth=2, \n",
    "    marker='o', \n",
    "    color='green')\n",
    "\n",
    "fig.plot(\n",
    "    inpc_brasil['INPC - Variação acumulada em 12 meses'], \n",
    "    label = 'Acumulada em 12 Meses', \n",
    "    linewidth=2, \n",
    "    marker='o', \n",
    "    color='blue')\n",
    "#fig.set_title('Variação Mensal e Acumulada dos Últimos 12 meses do INPC')\n",
    "\n",
    "plt.grid(False)\n",
    "\n",
    "plt.legend(\n",
    "    title='Variação:',\n",
    "    title_fontsize=14,\n",
    "    loc='center left',\n",
    "    ncol = 1,\n",
    "    #bbox_to_anchor=(0.65,0.55),\n",
    "    frameon=True,\n",
    "    facecolor='white',\n",
    "    shadow=True,\n",
    "    fontsize=15)\n",
    "fig.set_xlabel('Meses', fontsize=15)\n",
    "fig.set_ylabel('Variação (%)', fontsize=15)\n",
    "\n",
    "# Hide the right and top spines\n",
    "fig.spines.right.set_visible(False)\n",
    "fig.spines.top.set_visible(False)\n",
    "\n",
    "plt.yticks(fontsize=14)\n",
    "plt.xticks(fontsize=12)\n",
    "\n",
    "str_month_list = list(inpc_brasil.index.strftime(\"%m/%Y\"))\n",
    "plt.xticks(inpc_brasil.index,str_month_list, fontsize=15)\n",
    "\n",
    "# Valores em cada ponto do gráfico\n",
    "for x,y in zip(inpc_brasil['INPC - Variação mensal'].index, inpc_brasil['INPC - Variação mensal'].values):\n",
    "\n",
    "    label = \"{:.2f}\".format(y)\n",
    "\n",
    "    plt.annotate(label, # this is the text\n",
    "                 (x,y), # this is the point to label\n",
    "                 textcoords=\"offset points\", # how to position the text\n",
    "                 xytext=(0,10), # distance from text to points (x,y)\n",
    "                 ha='center',\n",
    "                 size=15) # horizontal alignment can be left, right or center\n",
    "\n",
    "for x,y in zip(inpc_brasil['INPC - Variação acumulada em 12 meses'].index, inpc_brasil['INPC - Variação acumulada em 12 meses'].values):\n",
    "\n",
    "    label = \"{:.2f}\".format(y)\n",
    "\n",
    "    plt.annotate(label, # this is the text\n",
    "                 (x,y), # this is the point to label\n",
    "                 textcoords=\"offset points\", # how to position the text\n",
    "                 xytext=(0,13), # distance from text to points (x,y)\n",
    "                 ha='center',\n",
    "                 size=15) # horizontal alignment can be left, right or center\n",
    "\n",
    "plt.savefig('graficos/GRÁFICO 3 - INPC 12M E MENSAL.svg', dpi=600)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Acumulado no Ano"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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stt/f/sOC2yUkJNit929ubm53rCe5fd5a9u9eSP/8OYwcOVIjR460W7Z8+XK1atUqVa/r7u6eZFl8fHyyrwsAAADA+XAm/S7GjJFy5rQfy5kzcTy93XpQ2XPPPafQ0FDb1+rVqxUYGKivvvrKdrZ8z549tu2ioqJUu3ZthYWFKVu2bLp27Zrdfo/c6acO9+Be9hkREaGtW7dq2rRpGjhwoJ544gkVKFBAZ8+etQXXChUqaMeOHXbb3X485cqV08GDB+0u379w4YIOHTokT0/P+zqGcuXKaefOnXZj4eHhkpRkn7duOWjSpIndn0NoaKjatGmjsLCwJA+QS46np6ftdW5/3WzZstldzQAAAADAeRHS76JjR2n27MQz5y4uib/Onp04nt5Wr14tY4x69uwpLy8vu6+ePXsqJiZGu3btUuPGjfXWW2/ZwuLw4cOVJ08e+fr6ys/PT+fPn9eCBQtsD4L7/vvv/1Nd97LPvHnzKmvWrFq/fr2OHz+unTt3ql+/foqNjbVdPt+jRw+tX79en3zyiQ4dOqQZM2bYBdng4GAVLFhQgwYN0t69e/XHH39o0KBByps3r564z5v9e/Xqpd27d2vcuHF29/XXr18/SUi/dctBt27dkvw59O7dW66urqmejq1v375av3695syZo8OHD2v9+vWaOnWqnn32WeXJk+e+jgUAAABA5kJIT0HHjomXtickJP6aEQFdSnxQWYMGDVS8ePEky2rXrq0KFSpo+fLleu+991S5cmX169dPbdu2VVxcnObOnSs3NzfVqlVLL7/8subMmaMnnnhC27ZtU//+/f9TXfeyTw8PD7377rv66quv1KJFCw0dOlRVqlRRcHCwdu/eLUlq0qSJxo4dqyVLlig4OFi7du1S27ZtbfvInj275s2bJzc3N3Xs2FFdu3ZVnjx5FBISorx5897XMXh5eWnmzJn69ddfFRwcrOHDh6tp06aaMmVKknVDQ0NVvnx52z3rtytdurQaNGig0NDQVN2zX7duXY0bN06hoaF68sknNX78eHXp0kUjRoy4r+MAAAAAkPm4mFvXHT9AwsPDFRAQcN/LgQdJeHi4fvzxR3Xs2FGFChVydDkAAAAA0hFn0gEAAAAAsAhCOgAAAAAAFkFIBwAAAADAIgjpAAAAAABYBCEdAAAAAACLyLQhPSEhwdElAP8Z72MAAADAuWTKkO7m5qbr1687ugzgP7t+/TpBHQAAAHAimTKkFy9eXBEREYqKiiLg4IGUkJCgqKgo7d+/X6dPn5YxRtmyZXN0WQAAAADSWVZHF5AeChYsqIsXL+qPP/5Q1qyZ8hDhBBISEnT69GkdP35cefLkUa5cuRxdEgAAAIB0lmkTrKenp27cuKFvvvlGkuTqmikvGkAmFx8frzx58uipp55SlixZHF0OAAAAgHTmsJA+atQoxcfHa8yYMbaxrVu3avz48Tp06JBKly6tIUOGqH79+vf9Gt7e3ipQoIDOnj2rGzdupEXZQIZxcXFRnjx5VLx4ceXNm9fR5QAAAADIABke0o0xmjp1qj799FM988wztvGIiAj17dtX/fr1U7NmzbR27Vq9+OKLWrVqlR599NH7fr2HH35YDz/8cFqUDgAAAABAusrQa8CPHTumLl26aOnSpUmC88KFC+Xn56e+ffvK09NTAwYMkL+/vxYuXJiRJQIAAAAA4DAZGtJ37typkiVLau3atSpRooTdsrCwMNWoUcNurGbNmgoLC8vIEgEAAAAAcJgMvdw9ODhYwcHBd1x2+vRpeXh42I0VLVpUp0+fzojSAAAAAABwOMs88vzGjRtyc3OzG3Nzc1NMTIyDKgIAAAAAIGNZJqRnz55dcXFxdmOxsbHKkSOHgyoCAAAAACBjWSakFytWTGfOnLEbO3PmTJJL4AEAAAAAyKwsE9IDAgK0fft2u7FffvlF1apVc1BFAAAAAABkLMuE9E6dOiksLExTp05VZGSkpkyZol27dqlr166OLg0AAAAAgAxhmZBevnx5TZ8+XV9//bVat26tTZs2aebMmfL09HR0aQAAAAAAZAgXY4xxdBH3Kjw8XAEBAY4uAwAAAACANGWZM+kAAAAAADg7QjoAAAAAABZBSAcAAAAAwCII6QAAAAAAWAQhHQAAAAAAiyCkAwAAAABgEYR0AAAAAAAsgpAOAAAAAIBFENIBAAAAALAIQjoAAAAAABZBSAcAAAAAwCII6QAAAAAAWAQhHQAAAAAAiyCkAwAAAABgEYR0AAAAAAAsgpAOAAAAAIBFENIBAAAAALAIQjoAAAAAABZBSAcAAAAAwCII6QAAAAAAWAQhHQAAAAAAiyCkAwAAAABgEYR0AAAAAAAsgpAOAAAAAIBFENIBAAAAALAIQjoAAAAAABZBSAcAAAAAwCII6QAAAAAAWAQhHQAAAAAAiyCkAwAAAABgEYR0AAAAAAAsgpAOAAAAAIBFENIBAAAAALAIQjoAAAAAABZBSAcAAAAAwCII6QAAAAAAWAQhHQAAAAAAiyCkAwAAAABgEYR0AAAAAAAsgpAOAAAAAIBFENIBAAAAALAIQjoAAAAAABZBSAcAAAAAwCII6QAAAAAAWAQhHQAAAAAAiyCkAwAAAABgEYR0AAAAAAAsgpAOAAAAAIBFENIBAAAAALAIQjoAAAAAABZBSAcAAAAAwCII6QAAAAAAWAQhHQAAAAAAiyCkAwAAAABgEYR0AAAAAAAsgpAOAAAAAIBFENIBAAAAALAIQjoAAAAAABZBSAcAAAAAwCII6QAAAAAAWAQhHQAAAAAAiyCkAwAAAABgEYR0AAAAAAAsgpAOAAAAAIBFENIBAAAAALAIQjoAAAAAABZBSAcAAAAAwCII6QAAAAAAWAQhHQAAAAAAi7BUSL9+/bpGjx6twMBAVatWTT179lRERISjywIAAAAAIENYKqSPGTNGP/30k6ZMmaJPP/1U2bNnV8+ePRUTE+Po0gAAAAAASHeWCunffvutnnvuOQUEBMjT01MDBw7UqVOnOJsOAAAAAHAKlgrpBQsW1Jdffqnz588rNjZWn3/+ufLly6eSJUs6ujQAAAAAANJdVkcXcLvRo0dr6NCheuyxx5QlSxa5u7tr/vz5yps3r6NLAwAAAAAg3VnqTPqRI0dUuHBhzZ49W0uXLlVgYKD69++v06dPO7o0AAAAAADSnWVC+rFjx/T6669rxIgRql+/vqpUqaKJEycqe/bsWrBggaPLAwAAAAAg3VkmpO/Zs0fx8fHy8fGxjWXLlk0VK1bUkSNHHFgZAAAAAAAZwzIh/aGHHpIk/fXXX7YxY4wiIyNVpkwZB1UFAAAAAEDGsUxI9/X1lb+/v4YNG6awsDBFRkbqjTfe0MmTJ9WpUydHlwcAAAAAQLqzTEjPkiWLZsyYoSpVqmjQoEFq166djh49qqVLl6p48eKOLg8AAAAAgHTnYowxji7iXoWHhysgIMDRZQAAAAAAkKYscyYdAAAAAABnR0gHAAAAAMAiCOkAAAAAAFgEIR0AAAAAAIsgpAMAAAAAYBGEdAAAAAAALIKQDgAAAACARRDSAQAAAACwCEI6AAAAAAAWQUgHAAAAAMAiCOkAAAAAAFgEIR0AAAAAAIsgpAMAAAAAYBGEdAAAAAAALIKQDgAAAACARRDSAQAAAACwCEI6AAAAAAAWQUgHAAAAAMAiCOkAAAAAAFgEIR0AAAAAAIsgpAMAAAAAYBGEdAAAAAAALIKQDgAAAACARRDSAQAAAACwCEI6AAAAAAAWQUgHAAAAAMAiCOkAAAAAAFgEIR0AAAAAAIsgpAMAAAAAYBGEdAAAAAAALIKQDgAAAACARRDSAQAAAACwCEI6AAAAAAAWQUgHAAAAAMAiCOkAAAAAAFgEIR0AAAAAAIsgpAMAAAAAYBGEdAAAAAAALIKQDgAAAACARRDSAQAAAACwCEI6AAAAAAAWQUgHAAAAAMAiCOkAAAAAAFgEIR0AAAAAAIsgpAMAAAAAYBGEdAAAAAAALIKQDgAAAACARRDSAQAAAACwCEI6AAAAAAAWQUgHAAAAAMAiCOkAAAAAAFgEIR0AAAAAAIsgpAMAAAAAYBFZU7NSXFycduzYoV27duncuXPKkiWLihQpIl9fXwUEBMjFxSW96wQAAAAAINO7a0i/cuWKFixYoCVLlujKlSsqUaKEChYsqJs3b+rixYsaP3688ufPr44dO6pLly7KmzdvRtUNAAAAAECmk2xI//rrrzV27FhVrVpVb7/9turVqyd3d3e7da5cuaJffvlFq1atUsuWLTVy5Eg1b9483YsGAAAAACAzumtIDwkJUfHixZPdOG/evGratKmaNm2qo0ePatKkSYR0AAAAAADuk4sxxji6iHsVHh6ugIAAR5cBAAAAAECaStWD424XGxurw4cPyxijRx55RG5ubulRFwAAAAAATueeQvrPP/+sIUOGyBijmzdvytXVVe+//77q1q2bXvUBAAAAAOA07imkjxkzRjNmzJCvr68kac2aNXrjjTe0adOmdCkOAAAAAABn4prcgu7du2vPnj12Yzdv3lSWLFls32fNmlU3b95Mv+oAAAAAAHAiyZ5J79Chg4YNG6ayZctqwIABKlu2rIYNG6aePXsqS5YsSkhIUHx8vN55552MrBcAAAAAgEzrrk93T0hI0IoVK/TRRx+pZs2aevnll1W4cGFFRkbKxcVFZcqUSTJ3ekbg6e4AAAAAgMwo2cvdJcnV1VXPPvusvvrqK3l6eqpt27aaMGGCPDw8VKFCBYcEdAAAAAAAMqu7hvTIyEh9/fXXOnDggHr27Kkvv/xS2bNnV1BQkKZOnaqoqKiMqhMAAAAAgEwv2ZD+ySefqG3btpo/f766d++uMWPGKG/evBo8eLBWrlypc+fOqXnz5po3b15G1gsAAAAAQKaV7D3pderU0Ycffig/Pz+dPXtWDRs21M8//6zcuXPb1jl06JA++OADTZkyJcMKlrgnHQAAAACQOSV7Jt3V1VWXL1+WJF29elXGGLvp1yTpkUceyfCADgAAAABAZpXsFGyDBw/WgAEDlDt3bl25ckWvvPKKcuTIke4FffbZZ5o7d65OnTqlcuXKaejQoapdu3a6vy4AAAAAAI521ynYLl26pKNHj+rhhx9W4cKF072YVatW6fXXX9ebb76p6tWra8mSJVq+fLnWrl2rEiVK2NbjcncAAAAAQGaU7Jn0y5cvK3/+/MqfP3+qd3bp0qV7Wv92xhhNmzZNvXr10jPPPCNJeu211/Tzzz9r586ddiEdAAAAAIDMKNl70tu3b6+PP/5Y0dHRKe7kypUrmjVrltq3b3/fhRw8eFAnTpxQy5Yt/ynO1VWrV69WUFDQfe8XAAAAAIAHRbJn0pcuXaqxY8fqscceU7169VS/fn2VK1dOBQoUkDFGFy5c0N69e/XLL7/o+++/V5MmTbRkyZL7LuTw4cOSEgN/ly5ddODAAZUtW1aDBw9W1apV73u/AAAAAAA8KO56T7okRUZG6pNPPtF3332ns2fPysXFRVLi5ekeHh5q2LChOnXqpHLlyv2nQlavXq1XX31VpUqVUv/+/VW2bFl99tlnWrFihUJDQ+Xp6Wlbl3vSAQAAAACZUbJn0m/x9PTU22+/LUk6deqUzp07JxcXFxUpUkQeHh5pVki2bNkkSX369LFd3l6pUiWFh4dr6dKlGjlyZJq9FgAAAAAAVpRiSL9dsWLFVKxYsXQppGjRopIkLy8v25iLi4vKli2r48ePp8trAgAAAABgJck+OC6jeXt7K2fOnNq9e7dtzBijyMhIlSxZ0oGVAQAAAACQMe7pTHp6ypEjh7p27aoPPvhAhQsXlpeXl5YsWaKjR49q6tSpji4PAAAAAIB0Z5mQLkmvvPKKcuTIoXfffVfnz59XxYoVNX/+fJUtW9bRpQEAAAAAkO5SfLr77aKionTw4EFly5ZNJUuWVO7cudOztmTxdHcAAAAAQGaUqjPp8fHxGjt2rJYtW6b4+HgZY+Tm5qa2bdvqf//7n1xdLXNrOwAAAAAAD6xUhfSPPvpIa9eu1YgRI1S9enXFx8crLCxM06ZNU+HChdWnT5/0rhMAAAAAgEwvVSF9xYoVevPNN9WiRQvbWPny5VWwYEFNnDiRkA4AAAAAQBpI1XXqFy9eVKVKlZKMV6pUSX///XeaFwUAAAAAgDNKVUj39PTUxo0bk4x/8803KlOmTFrXBAAAAACAU0rV5e79+vVT//799eeff8rf319S4hPWv/rqK40bNy5dCwQAAAAAwFmkegq2DRs2aM6cOTpw4ICyZ8+ucuXKqW/fvgoMDEzvGpNgCjYAAAAAQGZ0T/OkWwUhHQAAAACQGaXqcndJ2rhxo/bv36/4+HjbWGxsrHbv3q2PP/44XYoDAAAAAMCZJBvSe/furaeeekrNmzfX+++/r48//ljFihXTqVOn9PDDD+vs2bOKi4tTcHBwRtYLAAAAAECmlezT3Tt27KihQ4fqxo0bWrt2rUaNGqVNmzbJw8NDn3zyiX766SfVqFFDDz30UEbWCwAAAABAppVsSL9w4YKqVq0qd3d3Xbx4UfXq1ZMklS9fXr///rty586tAQMGaP369RlWLAAAAAAAmVmyIX3ChAl67bXXJEn58+fX5cuXJUllypTR/v37JUlFixbV33//nQFlAgAAAACQ+SUb0h9//HF169ZNFy5cUN26dfX2228rMjJS1apV09q1a7Vv3z4tW7ZMHh4eGVkvAAAAAACZ1l2nYLt06ZLy5s2rq1ev6rXXXlPdunXVoUMH9erVSz/++KOyZs2qsWPHKigoKCNrZgo2AAAAAECmdN/zpO/bt08FCxZU0aJF07qmFBHSAQAAAACZUbKXu98uKipKgwYN0vTp021jvXv31vjx4xUdHZ1uxQEAAAAA4ExSFdLfffddHThwwPaEd0kaM2aM9u3bp/Hjx0uSTpw4kT4VAgAAAADgJLKmZqXNmzdr1qxZqly5sm0sMDBQuXPnVrdu3VSkSBFNmTJFnTp10siRI9OtWAAAAAAAMrNUnUmPiYmRm5tbkvFcuXIpOjpaS5Ys0axZsxQaGprW9QEAAAAA4DRSFdKrV6+uyZMn69q1a7ax6OhoTZ8+XXXq1NGXX36pypUrK3v27OlWKAAAAAAAmV2qnu5+5MgRderUSdHR0Spbtqwk6dChQ8qVK5fmzZsnT0/PdC/0djzdHQAAAACQGaV6CrarV69q3bp1OnDggLJmzSpPT08FBQUpR44c6V1jEoR0AAAAAEBmlKoHx0lSnjx51L59+yTjMTExXOYOAAAAAEAaSFVIv3jxombOnKn9+/crPj5ekmSMUVxcnCIiIhQWFpauRQIAAAAA4AxS9eC4N954Q1988YU8PDwUFhamhx9+WHFxcfrtt9/Up0+f9K4RAAAAAACnkKoz6du2bdOkSZNUt25d/fHHH+ratasqVqyot99+W3/++Wd61wgAAAAAgFNI1Zn06OholStXTpL0yCOPaO/evZKkDh06aPv27elXHQAAAAAATiRVIb148eI6ePCgpMSQfuvseZYsWXTlypX0qw4AAAAAACeSqsvdW7VqpaFDh+q9995Tw4YN1a1bN5UoUUJbt25V+fLl07tGAAAAAACcQqpCet++feXu7q6EhAT5+fnphRde0KxZs1SwYEGNGzcuvWsEAAAAAMApuBhjjKOLuFfh4eEKCAhwdBkAAAAAAKSpZM+kz5w5U88//7zc3d01c+bMu+6EadgAAAAAAPjvkg3py5cvV7t27eTu7q7ly5cnuwMXFxdCOgAAAAAAaSBVl7vv3btXFStWlIuLS0bUlCIudwcAAAAAZEapmoKtZ8+e2r17d3rXAgAAAACAU0tVSM+bN69iY2PTuxYAAAAAAJxaqqZga9iwoXr16qVGjRqpZMmScnd3t1vOPekAAAAAAPx3qbonvVGjRsnvwMVFGzduTNOiUsI96QAAAACAzChVZ9I3bdqU3nUAAAAAAOD0UhXSJenmzZs6f/684uPjJUnGGMXGxmr37t0KDg5OtwIBAAAAAHAWqQrpP/zwg4YNG6YLFy4kWZYjRw5COgAAAAAAaSBVT3efOHGifH199fHHH8vd3V0fffSR3njjDeXNm1fvvfdeetcIAAAAAIBTSNWZ9MjISL3//vvy8vJSpUqVlC1bNrVv3145cuTQ/Pnz1axZs/SuEwAAAACATC9VZ9KzZs2qXLlySZJKly6t/fv3S5KqV6+uyMjI9KsOAAAAAAAnkqqQ7uPjoxUrVkiSvLy8tG3bNknS4cOH5eqaql0AAAAAAIAUpOpy95deekkvvPCC8uTJo1atWmnGjBlq3bq1Tpw4oSZNmqR3jQAAAAAAOAUXY4y504J+/fqpTZs2atCggbJkyaLTp08rLi5OJUuWVEREhFauXKmCBQuqS5cucnNzy9Ciw8PDFRAQkKGvCQAAAABAeks2pHfu3FlhYWEqVKiQgoOD1aZNG3l6emZ0fXdESAcAAAAAZEbJhnRJOn36tFavXq21a9cqMjJSvr6+atOmjVq2bKncuXNnZJ12COkAAAAAgMzoriH9dnv27NHq1au1fv16Xbt2TU2bNlWbNm1Us2bN9K4xCUI6AAAAACAzSnVIvyU+Pl5bt27Vl19+qc2bNytv3rz65ptv0qu+OyKkAwAAAAAyo3uePy1LliwqUKCAChUqpLx58+rKlSvpURcAAAAAAE4nVVOwSVJERITWrVundevW6eTJk3rsscc0aNAgNW7cOD3rAwAAAADAadw1pJ84cULr1q3TF198oQMHDqh06dJ65pln1KpVK3l4eGRUjQAAAAAAOIVkQ3r79u21a9cu5cyZUy1atNCbb76pqlWrZmRtAAAAAAA4lWRDerZs2TR27Fg1b95c7u7uGVkTAAAAAABOKdmQvmjRooysAwAAAAAAp3fPT3cHAAAAAADpg5AOAAAAAIBFENIBAAAAALAIQjoAAAAAABZBSAcAAAAAwCII6QAAAAAAWAQhHQAAAAAAiyCkAwAAAABgEYR0AAAAAAAsgpAOAAAAAIBFENIBAAAAALAIy4b03377TZUqVdIvv/zi6FIAAAAAAMgQlgzp169f16uvvqr4+HhHlwIAAAAAQIaxZEh/77335OHh4egyAAAAAADIUJYL6Vu2bNHmzZs1cuRIR5cCAAAAAECGyuroAm534cIFjRgxQu+++67y5cvn6HIAAAAAAMhQljqT/sYbb6hRo0aqV6+eo0sBAAAAACDDWeZM+qpVq7R3716tWbPG0aUAAAAAAOAQlgnpK1eu1N9//63AwEBJkjFGktSrVy+1bt1ab7/9tiPLAwAAAAAg3VkmpE+YMEE3btywfX/27Fl17NhR77zzjurUqePAygAAAAAAyBiWCen/nnIte/bstvFChQo5oiQAAAAAADKUpR4cBwAAAACAM7PMmfR/e+ihh/TXX385ugwAAAAAADIMZ9IBAAAAALAIQjoAAAAAABZBSAcAAAAAwCII6QAAAAAAWAQhHQAAAAAAiyCkAwAAAABgEYR0AAAAAAAsgpAOAAAAAIBFENIBAAAAALAIQjoAAAAAABZBSAcAAAAAwCII6QAAAAAAWAQhHQAAAAAAiyCkAwAAAABgEYR0AAAAAAAsgpAOAAAAAIBFENIBAAAAALAIQjoAAAAAABZBSAcAAAAAwCII6QAAAAAAWAQhHQAAAAAAiyCkAwAAAABgEYR0AAAAAAAsgpAOAAAAAIBFENIBAAAAALAIQjoAAAAAABZBSAcAAAAAwCII6QAAAAAAWAQhHQAAAAAAiyCkAwAAAABgEYR0AAAAAAAsgpAOAAAAAIBFENIBAAAAALAIQjoAAAAAABZBSAcAAAAAwCII6QAAAAAAWAQhHQAAAAAAiyCkAwAAAABgEYR0AAAAAAAsgpAOAAAAAIBFENIBAAAAALAIQjoAAAAAABZBSAcAAAAAwCII6QAAAAAAWAQhHQAAAAAAiyCkAwAAAABgEYR0AAAAAAAsgpAOAAAAAIBFENIBAAAAALAIQjoAAAAAABZBSAcAAAAAwCII6QAAAAAAWAQhHQAAAAAAiyCkAwAAAABgEYR0AAAAAAAsgpAOWNSoUaM0YsSIu66zbds2PfPMM/Lz81OTJk00Z84cGWNsyy9cuKChQ4eqVq1aqlmzpl555RWdPn06vUsHAAAAcJ8I6YDFGGM0ZcoUffrpp3dd78iRI+rTp48aNGigtWvXasiQIfrwww+1ZMkS2zqDBg3S8ePHNX/+fC1YsEBnzpzRiy++mN6HAAAAAOA+EdIBCzl27Ji6dOmipUuX6uGHH77ruj/88IPc3d310ksvqWTJkmrevLnq16+vH374QZIUFRWln3/+Wb169VKlSpVUsWJF9enTR3v27NHFixcz4nAAAAAA3CNCOmAhO3fuVMmSJbV27VqVKFHirusWLFhQly5d0hdffKGEhATt379fYWFh8vHxkSRlz55dOXPmVGhoqKKionTt2jWFhoaqdOnSypcvX0YcDgAAAIB75GJuv4H1AREeHq6AgABHlwGkq86dO6tUqVIaM2bMHZffvHlTb7zxhlasWCFXV1fFx8erRYsWmjRpklxdE3/+tmHDBr3++uu6fPmyXFxcVKhQIYWEhKh06dIZeSgAAAAAUokz6cAD6sqVKzp58qR69uypzz//XOPGjdNPP/2k6dOn29Y5ePCgvLy8tHDhQi1atEiPPPKIXnrpJUVFRTmwcgAAAADJyeroAgDcnwkTJsjV1VVDhgyRJFWqVEk3b97Um2++qc6dOysyMlJTpkzR5s2b5eHhIUn68MMP1bBhQ61atUqdO3d2ZPkAAAAA7oAz6cADateuXbb7z2+pUqWK4uLidOrUKf32228qUqSILaBLUt68eVWmTBkdOXIko8sFAAAAkAqEdOAB9dBDD+mvv/6yGztw4IBcXV1VqlQpPfTQQzp//rzOnz9vWx4dHa3jx4+rTJkyGVwtAAAAgNQgpAMPiNjYWJ09e1axsbGSpC5dumjz5s2aMWOGjh07pu+++05jx47Vc889p9y5c6thw4YqVqyYBgwYoD179uivv/7SkCFDlD17drVu3dqxBwMAAADgjgjpwANi586dCgwM1M6dOyVJ9evX1/Tp0/Xtt98qODhY7777rtq1a6dhw4ZJknLlyqVPPvlEBQsWVK9evdS1a1cZYxQSEqLcuXM78lAAAAAAJIMp2AAAAAAAsAjOpAMAAAAAYBGEdAAAAAAALMJSIf3cuXN67bXXFBgYqGrVqqlHjx7av3+/o8sCAAAAACBDWCakJyQk6KWXXtLhw4c1Y8YMLVu2TLlz59bzzz+vixcvOro8AAAAAADSnWVC+r59+7Rz5069++678vX1Vbly5TR+/Hhdv35dW7ZscXR5AAAAAACkO8uE9GLFimnWrFl65JFHbGMuLi4yxujy5csOrAwAAAAAgIyR1dEF3FKgQAE1aNDAbmzRokWKiYlRYGCgY4oCAAAAACADWeZM+r9t3LhRkyZNUrdu3eTp6enocgAAAAAASHeWDOkrV65U//791aJFCw0dOtTR5QAAAAAAkCEsF9I/+ugjDR8+XO3bt9f7778vV1fLlQhYQkiIVKaM5Oqa+GtIiKMrAgAAAPBfWeaedEmaM2eOPvjgA/Xv318vvviio8sBLCskRHrhBen69cTvjxxJ/F6SOnZ0XF0AAAAA/hsXY4xxdBFS4hRsTz/9tFq3bq2BAwfaLcuVK5dy5sxp+z48PFwBAQEZXSJgGcWLSydPJh0vXVo6fDjDywEAAACQRixzJv3LL79UfHy8VqxYoRUrVtgte+WVV9SvXz8HVQZYw7lz0qefSgsX3jmgS9LRoxlbEwAAAIC0ZZkz6feCM+lwFjduSF98IS1aJH35pXTzZuK4i4t0p08uZ9IBAACABxtPZYPDjBo1SiNGjLjrOl9++aVatWolPz8/NW3aVLNnz1Z8fLxteUREhHr06KGqVauqVq1aGjVqlK5evZrepaerhATphx8S7zF/6CHp2WelNWsSQ3mLFtKSJdK8edJtd4BISvx+zBjH1AwAAAAgbRDSkeGMMZoyZYo+/fTTu663ZcsWDRkyRM8++6zWrFmjwYMHa86cOZo5c6Yk6dq1a3r++eeVP39+ffbZZ/roo48UHh6u4cOHZ8RhpLn9+6XXX5c8PaV69aQ5c6TLl6WqVaXJk6UTJxLPpnfoIHXrJs2enXjm3MUl8dfZs3loHAAAAPCgs8w96XAOx44d0//+9z8dOHBADz/88F3XXbZsmZo1a6ZOnTpJkkqVKqXIyEitXLlSL774ok6ePKmAgACNHj3a9mDBtm3baurUqel+HGnl3Dlp2bLEy9l//fWf8RIlEgN3586St/edt+3YkVAOAAAAZDaEdGSonTt3qmTJkpo0aZIGDRp013X79u1r91R/SXJ1ddWVK1ckSY8++qimTJliW3bo0CGtXr1aderUSfvC09CNG9LatYnBfP36f+4zz51beuaZxGDeoEHi/OcAAAAAnAshHRkqODhYwcHBqVrX19fX7vuoqCgtXbpUdevWTbJuq1attG/fPhUvXlwzZsxIk1rTUkKC9OOPicF8+fLEy9glKUuWxPvMO3eWWrVKep85AAAAAOdCSMcDITo6Wv369VNMTIwGDx6cZPm7776r6OhoTZgwQV26dNHq1auVI0cOB1Rqb//+xGC+eLH9U9erVk0M5h06SB4eDisPAAAAgMUQ0mF5Fy5cUL9+/RQREaH58+erePHiSdbx/v8bt6dOnar69evr22+/VVBQUEaXKunu95l36pQYzitVckhpAAAAACyOkA5LO378uHr06KFr165p8eLFqlChgt2yffv2qUmTJraxokWLKn/+/Pr7778ztM6U7jPv0kWqX5/7zAEAAADcHSEdlnX+/Hl16dJFWbJk0dKlS1WyZEm75b///ruGDBmi77//XoULF5aU+PT4CxcuqFy5culeX0KCtHVrYjD/7DPuMwcAAADw3xHSYRmxsbG6fPmy8uXLJzc3N7311lu6ePGiPvnkE7m7u+vs2bOSJBcXFxUuXFgNGzZUyZIlNWTIEA0fPlzXrl3TO++8I39/f9WrVy/d6uQ+cwAAAADphZAOy9i5c6e6dOmihQsXqkqVKvrmm2+UkJCgZ5991m69LFmyaO/evcqRI4fmzZunsWPHqlOnTnJxcVGTJk00fPhwuabxdeXJ3WdesuQ/85lznzkAAACA/8rFGGMcXcS9Cg8PV0BAgKPLQCaX3H3mefL8M58595kDAAAASEucSQduc7f7zFu2TAzmwcHcZw4AAAAgfRDSAUl//fXPfeZHjvwzzn3mAAAAADISIR1O6+zZf+4z3779n3HuMwcAAADgKIR0OBXuMwcAAABgZYR0ZHrcZw4AAADgQUFIR6aV3H3mAQGJwbx9e+4zBwAAAGAthHRkKtxnDgAAAOBBRkjHA+/GDWnNmsRg/tVX3GcOAAAA4MFFSMcD6fb7zJcvl65cSRznPnMAAAAADzJCOiwrJEQaMUI6elQqVUoaM0aqVo37zAEAAABkXoR0WFJIiPTCC9L164nfHzkidemSeAb9lpIlpU6dEsN5xYqOqRMAAAAA0hIhHZb0v//9E9BvSUiQXFykbt0Sg3m9etxnDgAAACBzIaTDUv76S5o3L/ES9+TMm5dx9QAAAABARiKkw+GuXZM+/zwxfP/ww93XLVUqY2oCAAAAAEcgpMMhjJHCw6W5c6WlS/95OnuuXIkPfytRQho/3v6S95w5Ex8eBwAAAACZFSEdGerChcSHws2bJ+3a9c94rVpSz55S27aJ85tL0qOPJn26e8eOjqkbAAAAADKCizHGOLqIexUeHq6AgABHl4FUSkiQNm9OPGu+cqUUE5M4XqhQ4hPbe/SQvL0dWiIAAAAAWAJn0pFuTpyQFixIPGt+6FDimIuL1KxZ4lnz4GApe3aHlggAAAAAlkJIR5qKi5PWrUs8a75+/T/zmpcqlTh1WrduUunSjq0RAAAAAKyKkI40sX9/4hnzTz6R/v47cSxbNqlNm8TL2Zs0kbJkcWyNAAAAAGB1ro4u4EETHx+viRMnKjAwUP7+/urfv7/OnTuXqm179+6tzp07240ZYzRr1iw1bNhQfn5+6tixo/7888/0KD3NXb8uLVwo1asnlS8vvf9+YkCvVEmaODHxcvfly6XHHyegAwAAAEBqENLv0bRp07Rq1SqNGzdOixcv1unTp/Xyyy+nuN2yZcu0efPmJOMffvih5syZoxEjRmjlypXy8PBQr169FBUVlQ7V/3fGSGFhUt++UrFiUteuiXOb58qVeMb8p5+kPXukQYOkIkUcXS0AAAAAPFgI6fcgNjZWCxcu1KBBg1SnTh15e3tr0qRJ2rFjh3bs2JHsdkeOHNHkyZPl7+9vN37t2jXNnTtXw4YNU5MmTVS2bFm9/fbbcnNz0969e9P7cO7JxYvS9OmSv79Uvbo0c2bi3Oa1aklz5kinTiXeh167duLD4QAAAAAA94570u/Bvn37dO3aNdWoUcM2VqJECRUvXlxhYWGqWrVqkm3i4+P12muvqWfPnjp8+LCOHj1qWxYeHq6YmBg1b97cNpY7d25t2rQpfQ8klW5NnTZvnrRiBVOnAQAAAEB640z6PTh9+rQkycPDw268aNGitmX/NmvWLElSjx49kiw7fPiwChYsqF27dqlt27Z67LHH1KNHD0VERKRx5ffmxAlpzBjp0Uelxo2lJUuk2NjEqdOWL09cPmkSAR0AAAAA0hpn0u9BdHS0XF1dlS1bNrtxNzc3xdw6zXybP/74Qx9//LE+//xzubom/XlIVFSUrl27ptGjR+vVV19V4cKFNWfOHHXs2FHr169XwYIF0+1Y/i25qdNKlpS6d2fqNAAAAADICIT0e+Du7q6EhATdvHlTWbP+07rY2FjlyJHDbt2YmBgNHTpUAwYMUOlk0m3WrFkVHR2tN998U7Vq1ZIkTZgwQfXr19fq1avVrVu39DuY/5fc1GlPPy317MnUaQAAAACQkQjp96BYsWKSpLNnz9p+L0lnzpxJcgn8rl27FBkZqQkTJmjChAmSEsN8QkKC/P39tW7dOts2Xl5etu2yZ8+uEiVK6Pjx4+l2HNevS59/nnjW/Icf/hmvWDExmHfuzJPZAQAAAMARCOn3oEKFCsqVK5d+/fVXtWrVSpJ0/PhxnThxQtWrV7db19fXVxs2bLAbmzRpkk6ePKkJEyaoaNGiCggIkCTt3r1b9evXl5R4Bv7YsWN68skn07R2Y6QdOxKD+ZIliU9mlxKnTmvXLjGc16rFk9kBAAAAwJEI6ffAzc1Nzz33nN5//30VKFBAhQoV0ltvvaUaNWrIz89PsbGxunz5svLlyyd3d/ckl7nnzp3bbrxEiRIKDg7WW2+9pXfeeUceHh768MMP5erqquDg4DSp+eJFKSQkMZzv2vXPeK1aiU9nb9dOypMnTV4KAAAAAPAfEdLv0YABA3Tz5k0NHTpUN2/eVN26dTVq1ChJ0s6dO9WlSxctXLhQNWvWTNX+xowZo8mTJ2vo0KGKioqSn5+fFi5c+J8eGpeQIG3ZkhjMmToNAAAAAB4cLsYY4+gi7lV4eLjtUnH848SJxAfAzZsnHTyYOObiIjVtmhjMW7WSsmd3bI0AAAAAgORxJv0Bd2vqtHnzpC+/ZOo0AAAAAHiQEdIfUPv3S/PnSwsWJJ06rUePxLPnTJ0GAAAAAA8WQvoD5NbUafPmSd9//884U6cBAAAAQOZASLe4W1OnzZuX+JT2f0+d1qOHVLs2U6cBAAAAQGZASLeoW1OnzZsn/fbbP+M1ayaeNWfqNAAAAADIfAjpFnJr6rR58xIva7996rTOnRPPmvv4OLZGAAAAAED6IaRbwMmTiQ+Amz9fioxMHLs1dVrPnkydBgAAAADOgpDuIHFxiVOmzZ2bdOq0bt0Sv8qUcWiJAAAAAIAMRkhPRyEh0ogR0tGjUqlS0pgxUo0aiZez/3vqtKeeSjxrztRpAAAAAOC8COnpJCREeuGFxGnTJOnIEalLl3/OmEuJU6f16JF4v3nRoo6pEwAAAABgHYT0dDJixD8B/ZaEhMR7zbt1Y+o0AAAAAEBShPR0cvRo8svmzcu4OgAAAAAADw5XRxeQWZUqdW/jAAAAAAAQ0tPJmDFSzpz2YzlzJo4DAAAAAHAnhPR00rGjNHu2VLp04n3npUsnft+xo6MrAwAAAABYlYsxxji6iHsVHh6ugIAAR5cBAAAAAECa4kw6AAAAAAAWQUgHAAAAAMAiCOkAAAAAAFgEIR0AAAAAAIsgpAMAAAAAYBGEdAAAAAAALIKQDgAAAACARRDSAQAAAACwCEI6AAAAAAAWYamQHh8fr4kTJyowMFD+/v7q37+/zp075+iyAAAAAADIEJYK6dOmTdOqVas0btw4LV68WKdPn9bLL7/s6LIAAAAAAMgQlgnpsbGxWrhwoQYNGqQ6derI29tbkyZN0o4dO7Rjxw5HlwcAAAAAQLqzTEjft2+frl27pho1atjGSpQooeLFiyssLMyBlQEAAAAAkDEsE9JPnz4tSfLw8LAbL1q0qG0ZAAAAAACZmWVCenR0tFxdXZUtWza7cTc3N8XExDioKgAAAAAAMo5lQrq7u7sSEhJ08+ZNu/HY2FjlyJHDQVUBAAAAAJBxLBPSixUrJkk6e/as3fiZM2eSXAIPAAAAAEBmZJmQXqFCBeXKlUu//vqrbez48eM6ceKEqlev7sDKAAAAAADIGFkdXcAtbm5ueu655/T++++rQIECKlSokN566y3VqFFDfn5+ji4PAAAAAIB0Z5mQLkkDBgzQzZs3NXToUN28eVN169bVqFGjHF0WAAAAAAAZwsUYYxxdxL0KDw9XQECAo8sAAAAAACBNWeaedAAAAAAAnB0hHQAAAAAAiyCkAwAAAABgEYR0AAAAAAAsgpAOAAAAAIBFENIBAAAAALAIQjoAAAAAABZBSAcAAAAAwCII6QAAAAAAWAQhHQAAAAAAiyCkAwAAAABgEYR0AAAAAAAsgpAOAAAAAIBFENIBAAAAALAIQjoAAAAAABaR1dEF3K/w8HBHlwAAAAAAwH0JCAi447iLMcZkcC0AAAAAAOAOuNwdAAAAAACLIKQDAAAAAGARTh3S4+PjNXHiRAUGBsrf31/9+/fXuXPnkqwXHh4uHx+fO+5jy5YtateunSTpyJEj6tevn2rWrKlatWqpf//+OnnypN36a9as0eOPPy5fX1+1bdtWv//+u93yn376Se3atZO/v78aNmyocePG6caNG7blp0+fVv/+/VWjRg1Vq1ZNAwcO1N9///1fW3FfUurf4sWL1bx5c/n5+ally5b67LPPkuwjM/fvbv0xxmj27Nlq1KiRfH199fTTT2vz5s1J9pGZ+5OS1H4+4+Li1Lp1aw0bNizJMmfsX0p9a9OmjcqXL2/3NWLECLt9OGPfbkmpfxEREerevbuqVKmiunXr6oMPPlBCQoLdPpytf3frWaNGjZK832593d4HZ+vZ7VJ6z61fv15BQUG2f0tXrFiRZB/0L/n+hYaG6sknn5Sfn5+effZZ/fjjj0n24cz9k6RRo0Yl+Xdg69atatWqlXx9fRUUFKQtW7Yk2c7Z+3bLnfonSV988YWaNm16x22WLFmiQYMGSZL++OMPPf/886pWrZoCAwM1YsQIXbp0yW79BQsWqGHDhqpSpYq6deumw4cP2y3/8ssv1apVK/n5+alp06aaPXu24uPjbcsjIiLUo0cPVa1aVbVq1dKoUaN09erV/3bg/8GdeubsuSEJ48QmT55s6tSpY7Zu3Wr27Nljnn32WdO+fXu7dX777TdTo0YNU7FixTvuY/To0WbatGnm2rVrpnHjxqZ3797mzz//NHv27DGdOnUyLVu2NDExMcYYY3788Ufj7e1tli1bZiIiIsyIESNMtWrVzPnz540xxvz555/G29vbTJ482Rw6dMh8//33pn79+mb48OHGGGMSEhJMUFCQ6dq1q/nzzz/Nn3/+aTp27GieeuqpdOxS8u7Wv5CQEOPn52dCQ0PNkSNHzPLly423t7dZtWqV3T4yc//u1p958+aZgIAA880335ijR4+aGTNmmIoVK5o9e/Y4TX9SkprPpzHGTJgwwXh5eZnXXnstyTJn7N/d+paQkGD8/PzMmjVrzJkzZ2xfV69etduHM/btlrv17/z586ZWrVpmwIABJjIy0nzzzTcmICDAzJ07124fzta/lHp2+3vtyJEjpn79+mbw4MFO3bPb3a1/27dvN97e3mbp0qXm6NGjZunSpaZixYrmu+++s9sH/btz/9asWWPKly9vZs6caQ4ePGgWL15sKleubH7++We7fThr/xISEswHH3xgvLy8zP/+9z/b+IEDB4yPj4+ZMWOGiYiIMJMnTzbe3t5m//79dts7a99uSa5/xhizadMm4+vra5o0aXLHbfv06WNWrlxpTp8+bapXr25GjBhhIiIiTFhYmHnyySdN165dbesuX77c+Pv7m/Xr15t9+/aZ3r17m8aNG9t6u3nzZlOxYkWzaNEic+TIEbN+/XpTrVo1M336dGOMMVFRUaZOnTpm0KBBJiIiwuzYscO0bNnSvPjii+nTmLtIrmfkhqScNqTHxMQYf39/s2LFCtvYsWPHjJeXlwkPDzfGGDN+/Hjj7e1tWrdunWxIb9asmdm1a5fZsGGDqVSpkt1/dk+ePGm8vLzMr7/+aowxpnv37nZBIj4+3jRu3Nh89NFHxpjEN16bNm3s9r9q1Srj7e1tYmNjzZkzZ8yAAQPMsWPHbMu/+eYb4+XlZS5duvQfO3JvUupfUFCQef/99+22GT58uOncubPdWGbtX0r9mT59ulm+fLndNtWqVTMff/yx3Vhm7U9KUvP5NMaYsLAwU7t2bfPkk0/eMaQ7W/9S6tuRI0eMl5eXOXr06F3342x9uyWl/k2ZMsU0adLExMbG2pZPmzYtyX90nKl/qf2s3jJq1CjTqFEjc/36dbtxZ+rZ7VLq33vvvZfkP4Rt2rQxo0ePthujf3fuX3BwcJIfCI0YMcJ06tTJbswZ+3f06FHTqVMnU7NmTdOgQQO7wPT6668n6VGnTp3MyJEj7cacsW+3JNe/6OhoM3LkSOPt7W2CgoLuGNJjY2NN1apVzZkzZ8zHH39s6tSpY27evGlbvn37duPl5WVOnDhhjEns89SpU23Lo6KibD9wNyYx8L/yyit2rzF9+nTTqFEjY4wx+/fvN/379zfXrl2zLV+wYIGpWrVq2jQjle72nnP23HAnTnu5+759+3Tt2jXVqFHDNlaiRAkVL15cYWFhkqRt27Zp9uzZ6ty58x33cezYMV26dEk+Pj7y9fXV7NmzlTt3bttyV9fE9l6+fFkJCQnasWOH3eu5urqqevXqttdr27at3njjDbvXcHV1VVxcnKKjo1WkSBFNnjxZJUqUkJR4Ccann36qypUrK1++fGnQldRLqX8jR45U+/btkxzLlStXbN9n5v6l1J8XX3xRzz77rCQpJiZGISEhio6Otls/M/cnJan5fF67dk2vvfaaRo4cqUKFCiXZhzP2L6W+7d+/X+7u7ipevHiy+3DGvt2SUv+2bt2qJk2aKFu2bLblL730kqZPn2773tn6l5rP6u3rLl++XKNGjVKOHDls487Ws9ul1L8CBQrowIED+vnnn2WM0fbt23XgwAG7W/DoX/L9O3LkiKpVq2a3TcWKFbVz507dvHlTkvP2b+fOnSpZsqTWrl1rq+WWsLAwu2OUpJo1a9p9pp21b7ck17/z58/r6NGjWrZsWbKXuoeFhalUqVIqUqSIGjVqpA8++EBZsmSxLXdxcZEkXblyRefPn9fhw4ftepcrVy75+PjYete3b1+99NJLdq9x+/+5H330UU2ZMkU5c+aUJB06dEirV69WnTp10qATqXe395yz54Y7eWDnSf+vTp8+LUny8PCwGy9atKht2a37vlauXHnHfXz//fcKDAyUq6urPDw8kuxr9uzZypEjhwICAnTlyhVdv379jq+3e/duSZKXl5fdsri4OC1YsEB+fn7Kmzev3bJ+/fpp48aNypcvnxYuXHgvh54mUurfv/9yP3nypNatW6dOnTrZxjJz/1Lz/pKkDRs2qH///jLG6JVXXlGlSpVsyzJzf1KSmv69++67qly5slq2bKnly5cn2Ycz9i+lvsXHxytPnjwaMmSIfv31VxUoUEBPP/20unbtavvHzRn7dktK/Tt8+LAef/xxjR49Whs2bFCuXLn01FNPqWfPnrb/YDlb/1L7d50kTZs2TQEBAapfv77duLP17HYp9W/w4MHasWOHunbtqixZsig+Pl7du3dX69atbevSv+T7V7RoUZ06dcpu2YkTJxQXF6crV66oYMGCTtu/4OBgBQcH33HZ6dOnU/xMO2vfbkmuf8WLF9cnn3wiSfruu+/uuO0PP/ygunXrSpJKlSqlUqVK2S2fM2eOPDw89Oijj2rfvn2S7v53rK+vr92yqKgoLV261PYat2vVqpX27dun4sWLa8aMGak51DRzt/ecs+eGO3HaM+nR0dFydXW1OyMiSW5uboqJiUnVPm7/kP3bkiVLtHjxYg0ZMkQFChSwPYQge/bsdutly5btjq8XHx+vYcOG6cCBAxo5cmSS5f3799dnn32mqlWrqlu3bhn+4Ix76d+FCxfUu3dvFS5cWC+88IJtPDP3L7X9qVKlikJDQzV8+HDNmDHDLmxm5v6kJKX+bdq0SVu2bEnyE9DbOWP/UupbRESErl+/rsDAQM2bN0/PPfecpk6dancm2Bn7dktK/YuKitLMmTOVJUsWzZw5U3369NGcOXP04Ycf2tZ1tv6l9u+6Y8eOadOmTerdu3eSfThbz26XUv8uXLig8+fPa+jQoVqxYoVGjhypJUuW6PPPP7etS/+S719wcLBCQkK0bds2xcfH6+eff7adgImLi5Pk3P1Lzo0bN+Tm5mY39u/PNH27fz/88IPq1at3x2UTJkzQ5s2b9cYbbyhLliyKjo6WlLR3yeWV6Oho9evXTzExMRo8eHCS5e+++65CQkJUtGhRdenSxbZ/K3HG3HAnThvS3d3dlZCQYLvc6ZbY2Fi7y/CSExsbq19//fWOb5aPPvpIb731lnr37m37CdCtN0lsbKzdunFxcUleLzo6Wi+99JI2bNigqVOnqnLlykleo0KFCvL19dXkyZOVkJCgVatWpVhzWkpt/44dO6YOHTroypUrmj9/vvLkyWNbLzP3L7X98fDwUIUKFfT888+rTZs2mjdvnm29zNyflNytf25ubho5cqTeeecd5c+f/47bO2v/UnrfjRs3Tps3b9bTTz+t8uXLq0OHDurbt68WLFggY4zT9u2WlPqXNWtWlS9fXv/73//k7e2t1q1bq2/fvrazJs7Yv9T+Xbd27VoVK1ZMgYGBSdZztp7dLqX+jRw5UhUrVlTPnj1VsWJFde7cWd27d9f48eP5zCrl/r3wwgsKDg5Wr1695OPjozFjxqhHjx6SpDx58jh9/5KTPXt22w8xbrn9M03f7t/ff/+tU6dOyc/Pz248Pj5eb7zxhubOnas333xTjRs3lpT4HpeS9u5OeeXChQvq1q2b9u7dqzlz5tzx1jZvb29Vq1ZNU6dO1bFjx/Ttt9+m4dH9d86aG+7EaUN6sWLFJElnz561Gz9z5kySSyPuJDw8XGXKlLG7FzYhIUGjRo3SBx98oCFDhtimVpCk/PnzK2fOnDpz5sxdX+/ixYvq2rWrfvnlF82ePVsNGza0LTt37pzWrVtnt32OHDlUsmTJDP8pYmr6t3fvXrVv316urq5atmyZSpYsaVsvs/cvpf5s3rxZR44csVvm5eVlqyOz9ycld+tfoUKFdP78eQ0cOFD+/v7y9/fXr7/+qrVr18rf31+S8/Yvpfdd1qxZk1zCVb58eV27dk1Xr1512r7dklL/PDw8klweV65cOUVFRenixYtO2b/U/lu6ceNGtWjRwnav5S3O2LPbpdS/Xbt2JfkPY5UqVXTp0iVduXKF/qXQPzc3N40aNUo7duzQ999/r7Vr18rd3V2FCxdWzpw5nb5/ySlWrNhdj5G+3b/vv/9etWvXVtas/9xxHBMToxdffFErVqzQ+PHj7e7NTu3fscePH1eHDh10/PhxLV682O4S+OPHjycJ40WLFlX+/Pkt1Ttnzg134rQhvUKFCsqVK5d+/fVX29jx48d14sQJVa9ePcXtv//++yQ/zXn77bf1+eefa+zYserVq5fdMhcXF/n7+2v79u22sYSEBG3fvt32ejdu3FCPHj107NgxLVq0SLVr17bbx8mTJzVo0CDbvRSSdPXqVR06dEjlypVL/cGngZT6FxkZqW7duunhhx/WkiVLbH/J3JLZ+5dSf95//33b2bdbdu/eLU9PT0mZvz8puVv/atWqpQ0bNig0NNT25evrq0aNGik0NFSS8/Yvpfdd27ZtNWbMGLttdu/eraJFiypv3rxO27dbUupftWrV7OqUpP379ytfvnzKly+fU/YvNf+WXr9+XX/++adq1aqVZHtn7NntUuqfh4eH/vrrL7tt9u/fr/z58zvte+52KfVv8uTJmj17ttzc3FSkSBFJ0rfffmt7YJaz9y85AQEBdscoSb/88ovtIXz07f79+1L3hIQEvfLKK/r555/10UcfKSgoyG79QoUKqUyZMnbv8WvXrmnPnj223p0/f15dunRRQkKCli5dqgoVKtjt4/fff1f//v117tw529ixY8d04cIFy/TO2XPDHaX78+MtbPz48eaxxx4zW7Zssc2t+e8pJ4wxZsWKFUmmYHviiSfM9u3bbd9v3rzZeHl5malTp9rNCXvmzBlz48YNY4wxW7ZsMZUqVTKLFy+2zddXo0YN23x97733nqlYsaLZvHlzkn3Ex8eb+Ph489xzz5ng4GCza9cu88cff5ju3bubJk2amKioqHTs1J3drX9t2rQxgYGB5uDBg3bHcetYnaF/d+vPrfkfV6xYYQ4fPmzmzJljKlWqZDZv3uw0/UlJaj+fxhjTtWtXu2k2nLl/d+vb7NmzjY+Pj1m1apVtHtIqVarYpgN05r7dcrf+7d+/31SuXNmMGTPGHD582Hz99demWrVqZtq0acYY5+1fSp/VHTt2GC8vL3P69Okk2zprz253t/4tXrzYeHt7myVLlpijR4+aNWvWmKpVq5p58+YZY+ifMSn/W1u1alWzefNmc/ToUTN69Gjj5+dnIiMjjTH075ZOnTrZTYe1b98+4+3tbaZMmWIiIiLMBx98YCpXrmwiIiKMMfTt3/7dv1umTp1qNwXbzZs3TbVq1cypU6dsY4sXLzZeXl5m+fLlSY771nSfS5YsMX5+fuaLL74wf/31l+ndu7dp1qyZbT7wl19+2fj5+Zldu3bZbX/27FljjDHXr183zZo1M127djX79u0z4eHh5qmnnjLt2rUz8fHx6dmaZP27Z+SGpJw6pMfFxZmxY8eaGjVqmKpVq5pXXnnF9gd3u3+H9FOnTplq1aqZuLg429igQYOMl5fXHb9CQ0Nt633++eemUaNGpnLlyqZdu3Zmz549tmV16tRJdh+3PtDnz583r732mqlVq5bx9/c3L7/88h3/45MRkuvfwYMHkz2OJk2aOE3/Unp/LVmyxDRr1sz4+PiYoKAg8+233xpjeH/dktrPpzH2Id3Z+3e3viUkJJj58+fb3nfNmjUzy5YtM8bQt1tSet+FhYWZdu3aGR8fH1OvXj0zY8YMEx8f79T9S6lnX3/9tfHy8rL9h/IWZ+7Z7VLq3/Lly80TTzxhqlSpYlq2bGkWL15sEhIS6N//S6l/H374oalXr57x8/MznTp1Mrt27TLG8P673Z1C5nfffWdatmxpfHx8THBwsPnxxx+NMfTtTlIb0rdv326eeOIJu3XatWuX7HHfHkpnzZpl6tSpY/z8/Ez37t3N0aNHjTGJ87JXqFDhjtvfnl2OHTtm+vXrZ6pVq2aqV69uhg8fbq5cuZLWrUi123tGbrgzF2OMSf/z9QAAAAAAICVOe086AAAAAABWQ0gHAAAAAMAiCOkAAAAAAFgEIR0AAAAAAIsgpAMAAAAAYBGEdAAAAAAALIKQDgDAA65Ro0YqX768lixZcsflPXr0UPny5bV69eoMrgwAANwrQjoAAJlAtmzZ9PXXXycZv3Tpkn755RcHVAQAAO4HIR0AgEygVq1a2r59uy5cuGA3/s0336hKlSoOqgoAANwrQjoAAJmAv7+/ChcurG+//dZufP369WrZsqXd2Lfffqvg4GBVrlxZzZs317x585SQkGBbPnv2bDVu3Fg+Pj56/PHHFRISYrf98uXL9fjjj8vX11dBQUFatWqVbVl8fLzGjRununXrysfHR0FBQVq/fn06HDEAAJkTIR0AgEzAxcVFzZo1s7vk/cKFC9q+fbsef/xx29iWLVs0ZMgQdenSRevWrdPQoUO1cOFCzZgxQ5K0adMmzZs3T++8846+/vpr9ezZU6NHj9b27dslSUuWLNHkyZM1cOBAffHFF+rZs6fGjBljC+pLlizRN998o2nTpumrr75S8+bNNXjwYB07diwDuwEAwIMrq6MLAAAAaaN58+Z6/vnndfnyZeXLl08bNmxQ1apVVbhwYds6M2fOVIcOHfTMM89IkkqVKqVr167p9ddfV79+/XT06FFly5ZNDz/8sIoXL65nn31WJUqUUNmyZW3bv/TSS2revLlt+5MnT2rmzJl66qmndOTIEeXIkUPFixdXkSJF1K9fP/n6+ip//vwZ3g8AAB5EhHQAADKJgIAAFShQQBs3btTTTz99x0vd//zzT+3evVvLli2zjSUkJOjGjRs6ceKEgoKC9Pnnn6tZs2by8vJSYGCggoODVahQIV24cEF///23xo0bpwkTJti2v3nzpuLj4xUbG6vnnntO33zzjerVqycfHx/VrVtXrVq1Up48eTKsDwAAPMgI6QAAZBIuLi56/PHH9fXXX6tBgwbasWOHJk+ebLdOtmzZ1LNnTwUFBSXZ3sPDQ25ublqzZo3Cw8O1detWbdmyRZ988onGjRunBg0aSJJef/111ahRI8n2WbNmVdmyZfXtt99q27Zt+vHHH7Vu3TrNnz9fs2bNUs2aNdPluAEAyEy4Jx0AgEykefPm+umnnxQaGqoaNWqoYMGCdsvLlSunw4cPq3Tp0rav/fv328L8l19+qaVLl6p69eoaOHCgQkNDVadOHa1Zs0Z58uSRh4eHjh8/brf9Tz/9pHnz5snV1VUhISHasGGD6tWrp+HDh2v9+vUqUaIED48DACCVCOkAAGQiVatWVb58+TR9+vQkl7pLUt++fbVu3TrNnj1bhw8f1ubNmzVq1Ci5u7vLzc1NsbGxGjdunNasWaMTJ05o27Zt2rt3r20at759+2rBggX69NNPdfToUa1du1bvvfeeihQpIkm6ePGiRo8ere+++04nTpzQxo0bdfz4caaBAwAglbjcHQCATMTV1VWPP/64Pv30UzVp0iTJ8nr16un999/X7NmzNXXqVBUsWFCtW7fWwIEDJUmtW7fW+fPnNW3aNJ06dUqFChXS008/rT59+kiSOnTooNjYWM2bN0+jR4+Wh4eH+vXrpxdeeEGS1KdPH924cUNvvfWWzp07p2LFiunll1/WU089lXFNAADgAeZijDGOLgIAAAAAAHC5OwAAAAAAlkFIBwAAAADAIgjpAAAAAABYBCEdAAAAAACLIKQDAAAAAGARhHQAAAAAACyCkA4AAAAAgEUQ0gEAAAAAsAhCOgAAAAAAFvF/G90NrsyK24sAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1224x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('seaborn-whitegrid')\n",
    "ax, fig = plt.subplots(figsize=(17, 9))\n",
    "\n",
    "fig.plot(meses_ano_atual, alpha=0)\n",
    "fig.plot(\n",
    "    inpc_brasil[inpc_brasil.index.year == ano_atual]['INPC - Variação acumulada no ano'],\n",
    "    marker='o', \n",
    "    label = 'Acumulado no Ano', \n",
    "    linewidth=2, \n",
    "    color='blue')\n",
    "\n",
    "#fig.plot(acumulado, marker='o', label = 'Acumulado no Ano', linewidth=2, color='blue')\n",
    "\n",
    "#fig.set_title('Variação Acumulado no Ano do IPCA')\n",
    "\n",
    "plt.grid(False)\n",
    "\n",
    "plt.legend(\n",
    "    title='Variação:',\n",
    "    title_fontsize=14,\n",
    "    loc='upper left',\n",
    "    ncol = 1,\n",
    "    #bbox_to_anchor=(0.05,0.97),\n",
    "    frameon=True,\n",
    "    facecolor='white',\n",
    "    shadow=True,\n",
    "    fontsize=15)\n",
    "\n",
    "fig.set_xlabel('Meses', fontsize=15)\n",
    "fig.set_ylabel('Variação (%)', fontsize=15)\n",
    "\n",
    "# Hide the right and top spines\n",
    "fig.spines.right.set_visible(False)\n",
    "fig.spines.top.set_visible(False)\n",
    "\n",
    "plt.yticks(fontsize=15)\n",
    "str_month_list = list(meses_ano_atual.index[-12:].strftime(\"%m/%Y\"))\n",
    "plt.xticks(meses_ano_atual.index,str_month_list, fontsize=15)\n",
    "\n",
    "#Valores em cada ponto do gráfico\n",
    "for x,y in zip(inpc_brasil['INPC - Variação acumulada no ano'].index, inpc_brasil['INPC - Variação acumulada no ano'].values):\n",
    "\n",
    "    label = \"{:.2f}\".format(y)\n",
    "\n",
    "    plt.annotate(label, # this is the text\n",
    "                 (x,y), # this is the point to label\n",
    "                 textcoords=\"offset points\", # how to position the text\n",
    "                 xytext=(0,13), # distance from text to points (x,y)\n",
    "                 ha='center',\n",
    "                 size=15) # horizontal alignment can be left, right or center\n",
    "    \n",
    "plt.savefig('graficos/GRÁFICO 4 - INPC NO ANO.svg', dpi=600)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Regiões <a id=\"graficos-inpc-regioes\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Preechimento da tabela no Excel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "workbook = oxl.load_workbook(filename='tabela_regioes.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "sheet = workbook.active"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Preenche a tabela das categorias do inpc de curitiba\n",
    "for i in inpc_regioes.index:\n",
    "    sheet[f\"A{i+4}\"] = inpc_regioes.loc[i,'Brasil, Região Metropolitana e Município']\n",
    "    sheet[f\"B{i+4}\"] = inpc_regioes.loc[i,'Pesos']\n",
    "    sheet[f\"C{i+4}\"] = inpc_regioes.loc[i,'INPC - Variação mensal - anterior']\n",
    "    sheet[f\"D{i+4}\"] = inpc_regioes.loc[i,'INPC - Variação mensal - atual']\n",
    "    sheet[f\"E{i+4}\"] = inpc_regioes.loc[i,'INPC - Variação acumulada no ano']\n",
    "    sheet[f\"F{i+4}\"] = inpc_regioes.loc[i,'INPC - Variação acumulada em 12 meses']\n",
    "\n",
    "sheet[f\"A20\"] = 'Brasil'\n",
    "sheet[f\"B20\"] = 100.00\n",
    "sheet[f\"C20\"] = inpc_brasil.loc[data_anterior,'INPC - Variação mensal'][0]\n",
    "sheet[f\"D20\"] = inpc_brasil.loc[data_atual,'INPC - Variação mensal'][0]\n",
    "sheet[f\"E20\"] = inpc_brasil.loc[data_atual,'INPC - Variação acumulada no ano'][0]\n",
    "sheet[f\"F20\"] = inpc_brasil.loc[data_atual,'INPC - Variação acumulada em 12 meses'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "workbook.save(filename=\"tabelas/INPC REGIÕES.xlsx\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Curitiba <a id=\"graficos-inpc-curitiba\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Preenchimento da tabela no Excel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "workbook = oxl.load_workbook(filename='tabela_curitiba.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "sheet = workbook.active"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Preenche a tabela das categorias do ipca de curitiba\n",
    "for i in inpc_curitiba.index:\n",
    "    sheet[f\"A{i+4}\"] = inpc_curitiba.loc[i,'Geral, grupo, subgrupo, item e subitem']\n",
    "    sheet[f\"B{i+4}\"] = inpc_curitiba.loc[i,'INPC - Variação mensal - anterior']\n",
    "    sheet[f\"C{i+4}\"] = inpc_curitiba.loc[i,'INPC - Variação mensal - atual']\n",
    "    sheet[f\"D{i+4}\"] = inpc_curitiba.loc[i,'INPC - Variação acumulada no ano']\n",
    "    sheet[f\"E{i+4}\"] = inpc_curitiba.loc[i,'INPC - Variação acumulada em 12 meses']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "workbook.save(filename=\"tabelas/INPC CURITIBA.xlsx\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Preços Monitorados <a id=\"graficos-monitorados\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Variação mensal e acumulada em 12 meses do IPCA E INPC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1224x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax, fig = plt.subplots(figsize=(17, 9))\n",
    "\n",
    "fig.plot(ipca_brasil['IPCA - Variação mensal'], label = 'Mensal (IPCA)', linewidth=2, color='blue', marker='o')\n",
    "fig.plot(ipca_brasil['IPCA - Variação acumulada em 12 meses'], label = 'Acumulada em 12 Meses (IPCA)', linewidth=2, color='blue', marker='o')\n",
    "\n",
    "fig.plot(inpc_brasil['INPC - Variação mensal'], label = 'Mensal (INPC)', linewidth=2, color='green', marker='o')\n",
    "fig.plot(inpc_brasil['INPC - Variação acumulada em 12 meses'], label = 'Acumulada em 12 Meses (INPC)', linewidth=2, color='green', marker='o')\n",
    "\n",
    "plt.grid(False)\n",
    "\n",
    "plt.legend(\n",
    "    title='Variação:',\n",
    "    title_fontsize=14,\n",
    "    loc='best',\n",
    "    ncol = 1,\n",
    "    #bbox_to_anchor=(0.65,0.50),\n",
    "    frameon=True,\n",
    "    facecolor='white',\n",
    "    shadow=True,\n",
    "    fontsize=15)\n",
    "fig.set_xlabel('Meses', fontsize=15)\n",
    "fig.set_ylabel('Variação (%)', fontsize=15)\n",
    "plt.yticks(fontsize=15)\n",
    "plt.xticks(fontsize=15)\n",
    "\n",
    "fig.spines.right.set_visible(False)\n",
    "fig.spines.top.set_visible(False)\n",
    "\n",
    "str_month_list = list(inpc_brasil.index[-12:].strftime(\"%m/%Y\"))\n",
    "plt.xticks(inpc_brasil.iloc[-12:].index,str_month_list, fontsize=15)\n",
    "\n",
    "# Valores em cada ponto do gráfico\n",
    "for x,y in zip(ipca_brasil['IPCA - Variação mensal'][-1:].index,ipca_brasil['IPCA - Variação mensal'][-1:].values):\n",
    "\n",
    "    label = \"{:.2f}\".format(y)\n",
    "\n",
    "    plt.annotate(label, # this is the text\n",
    "                 (x,y), # this is the point to label\n",
    "                 textcoords=\"offset points\", # how to position the text\n",
    "                 xytext=(0,-17), # distance from text to points (x,y)\n",
    "                 ha='center',\n",
    "                 size=15,\n",
    "                 color='blue') # horizontal alignment can be left, right or center\n",
    "\n",
    "for x,y in zip(ipca_brasil['IPCA - Variação acumulada em 12 meses'][-1:].index, ipca_brasil['IPCA - Variação acumulada em 12 meses'][-1:].values):\n",
    "\n",
    "    label = \"{:.2f}\".format(y)\n",
    "\n",
    "    plt.annotate(label, # this is the text\n",
    "                 (x,y), # this is the point to label\n",
    "                 textcoords=\"offset points\", # how to position the text\n",
    "                 xytext=(7,-15), # distance from text to points (x,y)\n",
    "                 ha='center',\n",
    "                 size=15,\n",
    "                 color='blue') # horizontal alignment can be left, right or center\n",
    "\n",
    "# Valores em cada ponto do gráfico\n",
    "for x,y in zip(inpc_brasil['INPC - Variação mensal'][-1:].index,inpc_brasil['INPC - Variação mensal'][-1:].values):\n",
    "\n",
    "    label = \"{:.2f}\".format(y)\n",
    "\n",
    "    plt.annotate(label, # this is the text\n",
    "                (x,y), # this is the point to label\n",
    "                textcoords=\"offset points\", # how to position the text\n",
    "                xytext=(0,5), # distance from text to points (x,y)\n",
    "                ha='center',\n",
    "                size=15,\n",
    "                color='green') # horizontal alignment can be left, right or center\n",
    "\n",
    "for x,y in zip(inpc_brasil['INPC - Variação acumulada em 12 meses'][-1:].index, inpc_brasil['INPC - Variação acumulada em 12 meses'][-1:].values):\n",
    "\n",
    "    label = \"{:.2f}\".format(y)\n",
    "\n",
    "    plt.annotate(label, # this is the text\n",
    "                (x,y), # this is the point to label\n",
    "                textcoords=\"offset points\", # how to position the text\n",
    "                xytext=(0,5), # distance from text to points (x,y)\n",
    "                ha='center',\n",
    "                size=15,\n",
    "                color='green') # horizontal alignment can be left, right or center\n",
    "\n",
    "plt.savefig('graficos/GRÁFICO 5 - IPCA X INPC VAR 12M.svg', dpi=600)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Variação acumulada em 12 meses de itens selecionados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = precos_monitorados['Geral, grupo, subgrupo, item e subitem'].values\n",
    "ipca_monitorado = precos_monitorados['IPCA - Variação acumulada em 12 meses'].values\n",
    "inpc_monitorado = precos_monitorados['INPC - Variação acumulada em 12 meses'].values\n",
    "\n",
    "X_axis = np.arange(len(X))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x570.24 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax, fig = plt.subplots(figsize=(15, 7.92))\n",
    "baripca = plt.barh(X_axis - 0.2, ipca_monitorado, 0.4, label = 'IPCA', color='blue')\n",
    "barinpc = plt.barh(X_axis + 0.2, inpc_monitorado, 0.4, label = 'INPC', color='green')\n",
    "\n",
    "fig.set_frame_on(False)\n",
    "\n",
    "plt.yticks(X_axis, X)\n",
    "\n",
    "plt.yticks(fontsize=15)\n",
    "plt.xticks(fontsize=14)\n",
    "\n",
    "plt.bar_label(baripca, fontsize=23)\n",
    "plt.bar_label(barinpc, fontsize=23)\n",
    "\n",
    "plt.grid(False)\n",
    "\n",
    "plt.legend(\n",
    "    title='Variação:',\n",
    "    title_fontsize=20,\n",
    "    loc='best',\n",
    "    ncol = 1,\n",
    "    bbox_to_anchor=(0.70,0.70),\n",
    "    frameon=True,\n",
    "    facecolor='white',\n",
    "    shadow=True,\n",
    "    fontsize=20)\n",
    "fig.set_xlabel('Variação (%)', fontsize=20)\n",
    "\n",
    "plt.yticks(fontsize=20)\n",
    "plt.xticks(fontsize=20)\n",
    "\n",
    "plt.tight_layout(pad=0)\n",
    "\n",
    "\n",
    "\n",
    "plt.savefig('graficos/GRÁFICO 6 - PREÇOS MONITORADOS.svg', dpi=600)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## IGP-DI <a id=\"graficos-igpdi\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1224x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax, fig = plt.subplots(figsize=(17, 9))\n",
    "fig.plot(igpdi.iloc[-12:,1], label = 'Mensal', linewidth=2, marker='o', color='blue')\n",
    "fig.plot(igpdi.iloc[-12:,2], label = 'Acumulada em 12 Meses', linewidth=2, marker='o', color='green')\n",
    "#fig.set_title('Variação Mensal e Acumulada dos Últimos 12 meses do IGP-DI')\n",
    "\n",
    "fig.spines.right.set_visible(False)\n",
    "fig.spines.top.set_visible(False)\n",
    "\n",
    "\n",
    "plt.grid(False)\n",
    "\n",
    "plt.legend(\n",
    "    title='Variação:',\n",
    "    title_fontsize=14,\n",
    "    loc='upper left',\n",
    "    ncol = 1,\n",
    "    bbox_to_anchor=(0.70,0.97),\n",
    "    frameon=True,\n",
    "    facecolor='white',\n",
    "    shadow=True,\n",
    "    fontsize=15)\n",
    "fig.set_xlabel('Meses', fontsize=20)\n",
    "fig.set_ylabel('Variação (%)', fontsize=20)\n",
    "plt.yticks(fontsize=15)\n",
    "plt.xticks(fontsize=15)\n",
    "\n",
    "str_month_list = list(igpdi.index[-12:].strftime(\"%m/%Y\"))\n",
    "plt.xticks(igpdi.iloc[-12:].index,str_month_list, fontsize=15)\n",
    "\n",
    "\n",
    "# Valores em cada ponto do gráfico\n",
    "for x,y in zip(igpdi['Variação Mensal'][-12:].index,igpdi['Variação Mensal'][-12:].values):\n",
    "\n",
    "    label = \"{:.2f}\".format(y)\n",
    "\n",
    "    plt.annotate(label, # this is the text\n",
    "                (x,y), # this is the point to label\n",
    "                textcoords=\"offset points\", # how to position the text\n",
    "                xytext=(0,10), # distance from text to points (x,y)\n",
    "                ha='center',\n",
    "                size=15) # horizontal alignment can be left, right or center\n",
    "\n",
    "for x,y in zip(igpdi['Acumulado 12 meses'][-12:].index,igpdi['Acumulado 12 meses'][-12:].values):\n",
    "\n",
    "    label = \"{:.2f}\".format(y)\n",
    "\n",
    "    plt.annotate(label, # this is the text\n",
    "                (x,y), # this is the point to label\n",
    "                textcoords=\"offset points\", # how to position the text\n",
    "                xytext=(0,13), # distance from text to points (x,y)\n",
    "                ha='center',\n",
    "                size=15) # horizontal alignment can be left, right or center\n",
    "plt.savefig('graficos/GRÁFICO 7 - IGP-DI.svg', dpi=600)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## IGP-M <a id=\"graficos-igpm\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1224x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('seaborn-whitegrid')\n",
    "ax, fig = plt.subplots(figsize=(17, 9))\n",
    "fig.plot(igpm.iloc[-12:,1], label = 'Mensal', linewidth=2, marker='o', color='blue')\n",
    "fig.plot(igpm.iloc[-12:,2], label = 'Acumulada em 12 Meses', linewidth=2, marker='o', color='green')\n",
    "#fig.set_title('Variação Mensal e Acumulada dos Últimos 12 meses do IGP-M')\n",
    "\n",
    "fig.spines.right.set_visible(False)\n",
    "fig.spines.top.set_visible(False)\n",
    "\n",
    "plt.grid(False)\n",
    "\n",
    "plt.legend(\n",
    "    title='Variação:',\n",
    "    title_fontsize=14,\n",
    "    loc='upper left',\n",
    "    ncol = 1,\n",
    "    bbox_to_anchor=(0.70,0.97),\n",
    "    frameon=True,\n",
    "    facecolor='white',\n",
    "    shadow=True,\n",
    "    fontsize=15)\n",
    "fig.set_xlabel('Meses', fontsize=15)\n",
    "fig.set_ylabel('Variação (%)', fontsize=15)\n",
    "plt.yticks(fontsize=15)\n",
    "plt.xticks(fontsize=15)\n",
    "\n",
    "str_month_list = list(igpm.index[-12:].strftime(\"%m/%Y\"))\n",
    "plt.xticks(igpm.iloc[-12:].index,str_month_list, fontsize=15)\n",
    "\n",
    "# Valores em cada ponto do gráfico\n",
    "for x,y in zip(igpm['Variação Mensal'][-12:].index, igpm['Variação Mensal'][-12:].values):\n",
    "\n",
    "    label = \"{:.2f}\".format(y)\n",
    "\n",
    "    plt.annotate(label, # this is the text\n",
    "                (x,y), # this is the point to label\n",
    "                textcoords=\"offset points\", # how to position the text\n",
    "                xytext=(0,10), # distance from text to points (x,y)\n",
    "                ha='center',\n",
    "                size=15) # horizontal alignment can be left, right or center\n",
    "\n",
    "for x,y in zip(igpm['Acumulado 12 meses'][-12:].index, igpm['Acumulado 12 meses'][-12:].values):\n",
    "\n",
    "    label = \"{:.2f}\".format(y)\n",
    "\n",
    "    plt.annotate(label, # this is the text\n",
    "                (x,y), # this is the point to label\n",
    "                textcoords=\"offset points\", # how to position the text\n",
    "                xytext=(0,13), # distance from text to points (x,y)\n",
    "                ha='center',\n",
    "                size=15) # horizontal alignment can be left, right or center\n",
    "\n",
    "plt.savefig('graficos/GRÁFICO 8 - IGP-M.svg', dpi=600)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Brent <a id=\"graficos-brent\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "brent.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\est.matheus.brasil\\AppData\\Local\\Temp\\ipykernel_16344\\2071783409.py:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  brent_12meses['date'] = pd.to_datetime(brent_12meses['date'])\n"
     ]
    }
   ],
   "source": [
    "#filtrar brent com os 12 meses do ano atual\n",
    "brent_12meses = brent[(brent['date'] >= ultimos12meses) & (brent['date'] < data_referencia)]\n",
    "brent_12meses['date'] = pd.to_datetime(brent_12meses['date'])\n",
    "brent_12meses.set_index('date', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1224x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('seaborn-whitegrid')\n",
    "ax, fig = plt.subplots(figsize=(17, 9))\n",
    "fig.plot(brent_12meses, label = 'Mensal', linewidth=2, marker='o', color='blue')\n",
    "#fig.set_title('Evolução do Preço por Barril de Petróleo Bruto Tipo Brent - Em US$ (FOB)')\n",
    "fig.set_xlabel('Meses', fontsize=15)\n",
    "fig.set_ylabel('Preço (US$)', fontsize=15)\n",
    "plt.yticks(fontsize=15)\n",
    "plt.xticks(fontsize=15)\n",
    "\n",
    "fig.spines.right.set_visible(False)\n",
    "fig.spines.top.set_visible(False)\n",
    "\n",
    "plt.grid(False)\n",
    "\n",
    "str_month_list = list(brent_12meses.index.strftime(\"%m/%Y\"))\n",
    "plt.xticks(brent_12meses.index,str_month_list, fontsize=15)\n",
    "\n",
    "# Valores em cada ponto do gráfico\n",
    "for x, y in zip(brent_12meses.index, brent_12meses.price.values):\n",
    "\n",
    "    label = \"{:.2f}\".format(y)\n",
    "\n",
    "    plt.annotate(label, # this is the text\n",
    "                (x,y), # this is the point to label\n",
    "                textcoords=\"offset points\", # how to position the text\n",
    "                xytext=(0,20), # distance from text to points (x,y)\n",
    "                ha='center',\n",
    "                size=15) # horizontal alignment can be left, right or center\n",
    "\n",
    "plt.savefig('graficos/GRÁFICO 9 - BRENT.svg', dpi=600)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Diesel-S10 <a id=\"graficos-diesel\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Capitais <a id=\"graficos-diesel-capitais\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "precos_capitais.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "precos_capitais.sort_values(by='MÉDIA', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "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>MÊS</th>\n",
       "      <th>MUNICÍPIO</th>\n",
       "      <th>2022-12</th>\n",
       "      <th>2023-01</th>\n",
       "      <th>2023-02</th>\n",
       "      <th>2023-03</th>\n",
       "      <th>MÉDIA</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BELO HORIZONTE</td>\n",
       "      <td>6.42</td>\n",
       "      <td>6.23</td>\n",
       "      <td>5.92</td>\n",
       "      <td>5.83</td>\n",
       "      <td>6.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>PORTO ALEGRE</td>\n",
       "      <td>6.34</td>\n",
       "      <td>6.27</td>\n",
       "      <td>6.05</td>\n",
       "      <td>5.76</td>\n",
       "      <td>6.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>SAO LUIS</td>\n",
       "      <td>6.59</td>\n",
       "      <td>6.25</td>\n",
       "      <td>5.86</td>\n",
       "      <td>5.70</td>\n",
       "      <td>6.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>RECIFE</td>\n",
       "      <td>6.49</td>\n",
       "      <td>6.26</td>\n",
       "      <td>6.03</td>\n",
       "      <td>5.73</td>\n",
       "      <td>6.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>GOIANIA</td>\n",
       "      <td>6.43</td>\n",
       "      <td>6.26</td>\n",
       "      <td>5.97</td>\n",
       "      <td>5.97</td>\n",
       "      <td>6.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>RIO DE JANEIRO</td>\n",
       "      <td>6.43</td>\n",
       "      <td>6.31</td>\n",
       "      <td>6.08</td>\n",
       "      <td>5.93</td>\n",
       "      <td>6.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CAMPO GRANDE</td>\n",
       "      <td>6.36</td>\n",
       "      <td>6.39</td>\n",
       "      <td>6.19</td>\n",
       "      <td>5.91</td>\n",
       "      <td>6.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ARACAJU</td>\n",
       "      <td>6.56</td>\n",
       "      <td>6.46</td>\n",
       "      <td>5.99</td>\n",
       "      <td>5.96</td>\n",
       "      <td>6.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>CURITIBA</td>\n",
       "      <td>6.52</td>\n",
       "      <td>6.46</td>\n",
       "      <td>6.14</td>\n",
       "      <td>5.94</td>\n",
       "      <td>6.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>SAO PAULO</td>\n",
       "      <td>6.51</td>\n",
       "      <td>6.49</td>\n",
       "      <td>6.23</td>\n",
       "      <td>6.04</td>\n",
       "      <td>6.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BRASILIA</td>\n",
       "      <td>6.64</td>\n",
       "      <td>6.56</td>\n",
       "      <td>6.20</td>\n",
       "      <td>5.96</td>\n",
       "      <td>6.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>VITORIA</td>\n",
       "      <td>6.58</td>\n",
       "      <td>6.47</td>\n",
       "      <td>6.37</td>\n",
       "      <td>6.05</td>\n",
       "      <td>6.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>SALVADOR</td>\n",
       "      <td>6.40</td>\n",
       "      <td>6.64</td>\n",
       "      <td>6.47</td>\n",
       "      <td>6.16</td>\n",
       "      <td>6.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>FORTALEZA</td>\n",
       "      <td>6.88</td>\n",
       "      <td>6.68</td>\n",
       "      <td>6.45</td>\n",
       "      <td>6.06</td>\n",
       "      <td>6.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BELEM</td>\n",
       "      <td>7.00</td>\n",
       "      <td>6.92</td>\n",
       "      <td>6.45</td>\n",
       "      <td>6.06</td>\n",
       "      <td>6.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>RIO BRANCO</td>\n",
       "      <td>7.49</td>\n",
       "      <td>7.25</td>\n",
       "      <td>7.05</td>\n",
       "      <td>6.84</td>\n",
       "      <td>7.16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "MÊS       MUNICÍPIO  2022-12  2023-01  2023-02  2023-03  MÉDIA\n",
       "2    BELO HORIZONTE     6.42     6.23     5.92     5.83   6.10\n",
       "8      PORTO ALEGRE     6.34     6.27     6.05     5.76   6.10\n",
       "13         SAO LUIS     6.59     6.25     5.86     5.70   6.10\n",
       "9            RECIFE     6.49     6.26     6.03     5.73   6.13\n",
       "7           GOIANIA     6.43     6.26     5.97     5.97   6.16\n",
       "11   RIO DE JANEIRO     6.43     6.31     6.08     5.93   6.19\n",
       "4      CAMPO GRANDE     6.36     6.39     6.19     5.91   6.21\n",
       "0           ARACAJU     6.56     6.46     5.99     5.96   6.24\n",
       "5          CURITIBA     6.52     6.46     6.14     5.94   6.26\n",
       "14        SAO PAULO     6.51     6.49     6.23     6.04   6.32\n",
       "3          BRASILIA     6.64     6.56     6.20     5.96   6.34\n",
       "15          VITORIA     6.58     6.47     6.37     6.05   6.37\n",
       "12         SALVADOR     6.40     6.64     6.47     6.16   6.42\n",
       "6         FORTALEZA     6.88     6.68     6.45     6.06   6.52\n",
       "1             BELEM     7.00     6.92     6.45     6.06   6.61\n",
       "10       RIO BRANCO     7.49     7.25     7.05     6.84   7.16"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "precos_capitais"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'BELO HORIZONTE'"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "precos_capitais.iloc[0,0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "workbook = oxl.load_workbook(filename='PREÇO DIESEL REGIOES.xlsx')\n",
    "sheet = workbook.active\n",
    "#Preenche a tabela das categorias do inpc de curitiba\n",
    "for i in precos_capitais.index:\n",
    "    sheet[f\"A{i+4}\"] = precos_capitais.iloc[i,0] #capitais\n",
    "    sheet[f\"B{i+4}\"] = precos_capitais.iloc[i,1] #mês 1\n",
    "    sheet[f\"C{i+4}\"] = precos_capitais.iloc[i,2] #mês 2\n",
    "    sheet[f\"D{i+4}\"] = precos_capitais.iloc[i,3] #mês 3\n",
    "    sheet[f\"E{i+4}\"] = precos_capitais.iloc[i,4] #média\n",
    "\n",
    "\n",
    "workbook.save(filename='tabelas/PREÇO DIESEL REGIOES.xlsx')\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Curitiba <a id=\"graficos-diesel-curitiba\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1224x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('seaborn-whitegrid')\n",
    "ax, fig = plt.subplots(figsize=(17,9))\n",
    "fig.plot(diesel_curitiba['PREÇO MÉDIO REVENDA'], linewidth=2, marker='o', color='green') #variação de preço curitiba\n",
    "\n",
    "fig.set_xlabel('Meses', fontsize=15)\n",
    "fig.set_ylabel('Preço (R$)', fontsize=15)\n",
    "plt.yticks(fontsize=15)\n",
    "plt.xticks(fontsize=15)\n",
    "#plt.xticks(x.iloc[-12:].index,str_month_list, fontsize=15)\n",
    "\n",
    "plt.grid(False)\n",
    "\n",
    "fig.spines.right.set_visible(False)\n",
    "fig.spines.top.set_visible(False)\n",
    "\n",
    "plt.yticks(fontsize=15)\n",
    "str_month_list = list(diesel_curitiba.index.strftime(\"%m/%Y\"))\n",
    "plt.xticks(diesel_curitiba.index,str_month_list, fontsize=15)\n",
    "\n",
    "\n",
    "# Valores em cada ponto do gráfico\n",
    "for x,y in zip(diesel_curitiba['PREÇO MÉDIO REVENDA'].index, diesel_curitiba['PREÇO MÉDIO REVENDA'].values):\n",
    "\n",
    "    label = \"{:.2f}\".format(y)\n",
    "\n",
    "    plt.annotate(label, # this is the text\n",
    "                (x,y), # this is the point to label\n",
    "                textcoords=\"offset points\", # how to position the text\n",
    "                xytext=(0,20), # distance from text to points (x,y)\n",
    "                ha='center',\n",
    "                size=15) # horizontal alignment can be left, right or center\n",
    "\n",
    "plt.savefig('graficos/GRÁFICO 10 - DIESEL CURITIBA.svg', dpi=600)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Regiões <a id=\"graficos-diesel-regioes\"></a>\n",
    "\n",
    "[Voltar](#nav)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "DataInicialReferencia = precos_semanal['DATA INICIAL'].max().strftime(\"%d/%m/%Y\")\n",
    "DataFinalReferencia = precos_semanal['DATA FINAL'].max().strftime(\"%d/%m/%Y\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "variacao_regiao.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 1, 2, 3, 4, 5], dtype=int64)"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "variacao_regiao.index.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "workbook = oxl.load_workbook(filename='REGIÕES DO BRASIL MODELO.xlsx')\n",
    "sheet = workbook.active\n",
    "#Preenche a tabela das categorias do inpc de curitiba\n",
    "for i in variacao_regiao.index.values:\n",
    "    sheet[f\"B{i+5}\"] = variacao_regiao.loc[i,'REGIÃO'] \n",
    "    sheet[f\"C{i+5}\"] = variacao_regiao.loc[i,'PREÇO MÉDIO REVENDA'] \n",
    "    sheet[f\"D{i+5}\"] = variacao_regiao.loc[i,'SEMANAL']\n",
    "    sheet[f\"E{i+5}\"] = variacao_regiao.loc[i,'MENSAL'] \n",
    "    sheet[f\"F{i+5}\"] = variacao_regiao.loc[i,'SEIS MESES'] \n",
    "\n",
    "sheet['C12'] = DataInicialReferencia\n",
    "sheet['D12'] = DataFinalReferencia\n",
    "\n",
    "workbook.save(filename='tabelas/REGIÕES DO BRASIL.xlsx')"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3.10.4 ('boletim')",
   "language": "python",
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.4"
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