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gilberto-009199/analytics.ipynb

Last active September 20, 2023 00:39
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analytics.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/gilberto-009199/1ecf5efb0b1cc299d88e98069a56b6b3/analytics.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "M1kB-_M0Mio7"
},
"source": [
"\n",
"Faculdade Impacta de Tecnologia \"Prof. Ms. Arthur Schneider Figueira\"\n",
"> AC1 - Turma: 202302 - CC 5A NOITE - Análise Exploratória de Dados\n",
"---\n",
"**GRUPO 7**\n",
"\n",
" + Gilberto Ramos de Oliveira (RA: 1903991)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"id": "d6XN4lMVAv65"
},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "stsGlCCxS11c",
"outputId": "3463f6db-ef03-45d7-d077-0f798c657e33"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
]
}
],
"source": [
"from google.colab import drive\n",
"drive.mount('/content/drive')\n",
"dir_root = \"/content/drive/MyDrive/analise_exploratoria\"\n",
"dir_data = dir_root + \"/AC1\""
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 255
},
"id": "iWn7xU_SA9d3",
"outputId": "d3d9cd66-b5c2-4f77-ac1e-fefd6cb0c154"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" PRT_ID AREA INT_SQFT DATE_SALE DIST_MAINROAD N_BEDROOM \\\n",
"0 P07697 Anna Nagar 1724 30-08-2008 173 1.0 \n",
"1 P05314 Velachery 1545 19-03-2010 70 2.0 \n",
"2 P05415 Chrompet 973 28-02-2010 17 1.0 \n",
"3 P03189 Karapakkam 1013 08-05-2011 180 1.0 \n",
"4 P03976 Chrompet 1294 02-12-2010 90 2.0 \n",
"\n",
" N_BATHROOM N_ROOM SALE_COND PARK_FACIL ... UTILITY_AVAIL STREET MZZONE \\\n",
"0 1.0 4 Partial Yes ... NoSeWa Gravel RL \n",
"1 1.0 4 Family No ... ELO Paved I \n",
"2 1.0 3 Partial No ... ELO Paved RM \n",
"3 1.0 3 AbNormal No ... ELO Gravel RM \n",
"4 1.0 4 AbNormal Yes ... NoSewr Gravel RH \n",
"\n",
" QS_ROOMS QS_BATHROOM QS_BEDROOM QS_OVERALL REG_FEE COMMIS SALES_PRICE \n",
"0 3.3 3.1 3.1 3.17 401541 220200 12952940 \n",
"1 2.1 4.9 3.6 3.81 332349 166175 8308730 \n",
"2 3.3 3.7 3.7 3.58 207910 91480 8316400 \n",
"3 3.7 2.9 3.8 3.50 391350 148713 7827000 \n",
"4 3.5 5.0 2.9 3.92 440783 258390 15199400 \n",
"\n",
"[5 rows x 22 columns]"
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" <th>REG_FEE</th>\n",
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" </tr>\n",
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" <th>0</th>\n",
" <td>P07697</td>\n",
" <td>Anna Nagar</td>\n",
" <td>1724</td>\n",
" <td>30-08-2008</td>\n",
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" <td>Yes</td>\n",
" <td>...</td>\n",
" <td>NoSeWa</td>\n",
" <td>Gravel</td>\n",
" <td>RL</td>\n",
" <td>3.3</td>\n",
" <td>3.1</td>\n",
" <td>3.1</td>\n",
" <td>3.17</td>\n",
" <td>401541</td>\n",
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" <th>1</th>\n",
" <td>P05314</td>\n",
" <td>Velachery</td>\n",
" <td>1545</td>\n",
" <td>19-03-2010</td>\n",
" <td>70</td>\n",
" <td>2.0</td>\n",
" <td>1.0</td>\n",
" <td>4</td>\n",
" <td>Family</td>\n",
" <td>No</td>\n",
" <td>...</td>\n",
" <td>ELO</td>\n",
" <td>Paved</td>\n",
" <td>I</td>\n",
" <td>2.1</td>\n",
" <td>4.9</td>\n",
" <td>3.6</td>\n",
" <td>3.81</td>\n",
" <td>332349</td>\n",
" <td>166175</td>\n",
" <td>8308730</td>\n",
" </tr>\n",
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" <th>2</th>\n",
" <td>P05415</td>\n",
" <td>Chrompet</td>\n",
" <td>973</td>\n",
" <td>28-02-2010</td>\n",
" <td>17</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>3</td>\n",
" <td>Partial</td>\n",
" <td>No</td>\n",
" <td>...</td>\n",
" <td>ELO</td>\n",
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" <td>RM</td>\n",
" <td>3.3</td>\n",
" <td>3.7</td>\n",
" <td>3.7</td>\n",
" <td>3.58</td>\n",
" <td>207910</td>\n",
" <td>91480</td>\n",
" <td>8316400</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>P03189</td>\n",
" <td>Karapakkam</td>\n",
" <td>1013</td>\n",
" <td>08-05-2011</td>\n",
" <td>180</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>3</td>\n",
" <td>AbNormal</td>\n",
" <td>No</td>\n",
" <td>...</td>\n",
" <td>ELO</td>\n",
" <td>Gravel</td>\n",
" <td>RM</td>\n",
" <td>3.7</td>\n",
" <td>2.9</td>\n",
" <td>3.8</td>\n",
" <td>3.50</td>\n",
" <td>391350</td>\n",
" <td>148713</td>\n",
" <td>7827000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>P03976</td>\n",
" <td>Chrompet</td>\n",
" <td>1294</td>\n",
" <td>02-12-2010</td>\n",
" <td>90</td>\n",
" <td>2.0</td>\n",
" <td>1.0</td>\n",
" <td>4</td>\n",
" <td>AbNormal</td>\n",
" <td>Yes</td>\n",
" <td>...</td>\n",
" <td>NoSewr</td>\n",
" <td>Gravel</td>\n",
" <td>RH</td>\n",
" <td>3.5</td>\n",
" <td>5.0</td>\n",
" <td>2.9</td>\n",
" <td>3.92</td>\n",
" <td>440783</td>\n",
" <td>258390</td>\n",
" <td>15199400</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 22 columns</p>\n",
"</div>\n",
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"\n",
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"\n",
" async function convertToInteractive(key) {\n",
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" const dataTable =\n",
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
" [key], {});\n",
" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
" dataTable['output_type'] = 'display_data';\n",
" await google.colab.output.renderOutput(dataTable, element);\n",
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" }\n",
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]
},
"metadata": {},
"execution_count": 15
}
],
"source": [
"# Editar o caminho da tabela\n",
"# df = pd.read_csv( dir_data + '/treino.csv')\n",
"df = pd.read_csv('https://gist.githubusercontent.com/gilberto-009199/1ecf5efb0b1cc299d88e98069a56b6b3/raw/188c6689651fd67950dd54c81e3215811452898b/treino.csv')\n",
"df.head()"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "sRI339pJBrXb",
"outputId": "26021e8a-28bc-494e-b102-a042027c3feb"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"PRT_ID object\n",
"AREA object\n",
"INT_SQFT int64\n",
"DATE_SALE object\n",
"DIST_MAINROAD int64\n",
"N_BEDROOM float64\n",
"N_BATHROOM float64\n",
"N_ROOM int64\n",
"SALE_COND object\n",
"PARK_FACIL object\n",
"DATE_BUILD object\n",
"BUILDTYPE object\n",
"UTILITY_AVAIL object\n",
"STREET object\n",
"MZZONE object\n",
"QS_ROOMS float64\n",
"QS_BATHROOM float64\n",
"QS_BEDROOM float64\n",
"QS_OVERALL float64\n",
"REG_FEE int64\n",
"COMMIS int64\n",
"SALES_PRICE int64\n",
"dtype: object"
]
},
"metadata": {},
"execution_count": 16
}
],
"source": [
"df.dtypes"
]
},
{
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"execution_count": 17,
"metadata": {
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"height": 300
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"id": "v2ZsM8_74Pe-",
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{
"output_type": "execute_result",
"data": {
"text/plain": [
" INT_SQFT DIST_MAINROAD N_BEDROOM N_BATHROOM N_ROOM \\\n",
"count 5000.000000 5000.000000 5000.000000 4996.000000 5000.000000 \n",
"mean 1382.115200 99.598600 1.639000 1.215973 3.690000 \n",
"std 457.869482 57.377207 0.808214 0.411537 1.022404 \n",
"min 500.000000 0.000000 1.000000 1.000000 2.000000 \n",
"25% 994.000000 51.000000 1.000000 1.000000 3.000000 \n",
"50% 1364.000000 99.000000 1.000000 1.000000 4.000000 \n",
"75% 1744.000000 148.000000 2.000000 1.000000 4.000000 \n",
"max 2499.000000 200.000000 4.000000 2.000000 6.000000 \n",
"\n",
" QS_ROOMS QS_BATHROOM QS_BEDROOM QS_OVERALL REG_FEE \\\n",
"count 5000.000000 5000.000000 5000.000000 4971.000000 5000.000000 \n",
"mean 3.513600 3.503760 3.489260 3.502875 377082.693200 \n",
"std 0.892326 0.902051 0.879391 0.527007 144381.953526 \n",
"min 2.000000 2.000000 2.000000 2.060000 71177.000000 \n",
"25% 2.700000 2.700000 2.700000 3.120000 271254.000000 \n",
"50% 3.500000 3.500000 3.500000 3.500000 348784.500000 \n",
"75% 4.300000 4.300000 4.300000 3.890000 450823.750000 \n",
"max 5.000000 5.000000 5.000000 4.970000 983922.000000 \n",
"\n",
" COMMIS SALES_PRICE \n",
"count 5000.00000 5.000000e+03 \n",
"mean 140633.69460 1.090564e+07 \n",
"std 79436.45689 3.799634e+06 \n",
"min 5055.00000 2.156875e+06 \n",
"25% 83473.25000 8.271050e+06 \n",
"50% 127466.00000 1.036300e+07 \n",
"75% 183549.25000 1.298852e+07 \n",
"max 495405.00000 2.366734e+07 "
],
"text/html": [
"\n",
" <div id=\"df-556c6708-e794-47c3-9a67-2357487ddef3\" class=\"colab-df-container\">\n",
" <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>INT_SQFT</th>\n",
" <th>DIST_MAINROAD</th>\n",
" <th>N_BEDROOM</th>\n",
" <th>N_BATHROOM</th>\n",
" <th>N_ROOM</th>\n",
" <th>QS_ROOMS</th>\n",
" <th>QS_BATHROOM</th>\n",
" <th>QS_BEDROOM</th>\n",
" <th>QS_OVERALL</th>\n",
" <th>REG_FEE</th>\n",
" <th>COMMIS</th>\n",
" <th>SALES_PRICE</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>5000.000000</td>\n",
" <td>5000.000000</td>\n",
" <td>5000.000000</td>\n",
" <td>4996.000000</td>\n",
" <td>5000.000000</td>\n",
" <td>5000.000000</td>\n",
" <td>5000.000000</td>\n",
" <td>5000.000000</td>\n",
" <td>4971.000000</td>\n",
" <td>5000.000000</td>\n",
" <td>5000.00000</td>\n",
" <td>5.000000e+03</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>1382.115200</td>\n",
" <td>99.598600</td>\n",
" <td>1.639000</td>\n",
" <td>1.215973</td>\n",
" <td>3.690000</td>\n",
" <td>3.513600</td>\n",
" <td>3.503760</td>\n",
" <td>3.489260</td>\n",
" <td>3.502875</td>\n",
" <td>377082.693200</td>\n",
" <td>140633.69460</td>\n",
" <td>1.090564e+07</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>457.869482</td>\n",
" <td>57.377207</td>\n",
" <td>0.808214</td>\n",
" <td>0.411537</td>\n",
" <td>1.022404</td>\n",
" <td>0.892326</td>\n",
" <td>0.902051</td>\n",
" <td>0.879391</td>\n",
" <td>0.527007</td>\n",
" <td>144381.953526</td>\n",
" <td>79436.45689</td>\n",
" <td>3.799634e+06</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>500.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>2.000000</td>\n",
" <td>2.000000</td>\n",
" <td>2.000000</td>\n",
" <td>2.000000</td>\n",
" <td>2.060000</td>\n",
" <td>71177.000000</td>\n",
" <td>5055.00000</td>\n",
" <td>2.156875e+06</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>994.000000</td>\n",
" <td>51.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>3.000000</td>\n",
" <td>2.700000</td>\n",
" <td>2.700000</td>\n",
" <td>2.700000</td>\n",
" <td>3.120000</td>\n",
" <td>271254.000000</td>\n",
" <td>83473.25000</td>\n",
" <td>8.271050e+06</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>1364.000000</td>\n",
" <td>99.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>4.000000</td>\n",
" <td>3.500000</td>\n",
" <td>3.500000</td>\n",
" <td>3.500000</td>\n",
" <td>3.500000</td>\n",
" <td>348784.500000</td>\n",
" <td>127466.00000</td>\n",
" <td>1.036300e+07</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>1744.000000</td>\n",
" <td>148.000000</td>\n",
" <td>2.000000</td>\n",
" <td>1.000000</td>\n",
" <td>4.000000</td>\n",
" <td>4.300000</td>\n",
" <td>4.300000</td>\n",
" <td>4.300000</td>\n",
" <td>3.890000</td>\n",
" <td>450823.750000</td>\n",
" <td>183549.25000</td>\n",
" <td>1.298852e+07</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>2499.000000</td>\n",
" <td>200.000000</td>\n",
" <td>4.000000</td>\n",
" <td>2.000000</td>\n",
" <td>6.000000</td>\n",
" <td>5.000000</td>\n",
" <td>5.000000</td>\n",
" <td>5.000000</td>\n",
" <td>4.970000</td>\n",
" <td>983922.000000</td>\n",
" <td>495405.00000</td>\n",
" <td>2.366734e+07</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>\n",
" <div class=\"colab-df-buttons\">\n",
"\n",
" <div class=\"colab-df-container\">\n",
" <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-556c6708-e794-47c3-9a67-2357487ddef3')\"\n",
" title=\"Convert this dataframe to an interactive table.\"\n",
" style=\"display:none;\">\n",
"\n",
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"\n",
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"\n",
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" background-color: #E8F0FE;\n",
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"\n",
" .colab-df-convert:hover {\n",
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" box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
" fill: #174EA6;\n",
" }\n",
"\n",
" .colab-df-buttons div {\n",
" margin-bottom: 4px;\n",
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"\n",
" [theme=dark] .colab-df-convert {\n",
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" }\n",
"\n",
" [theme=dark] .colab-df-convert:hover {\n",
" background-color: #434B5C;\n",
" box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
" fill: #FFFFFF;\n",
" }\n",
" </style>\n",
"\n",
" <script>\n",
" const buttonEl =\n",
" document.querySelector('#df-556c6708-e794-47c3-9a67-2357487ddef3 button.colab-df-convert');\n",
" buttonEl.style.display =\n",
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
"\n",
" async function convertToInteractive(key) {\n",
" const element = document.querySelector('#df-556c6708-e794-47c3-9a67-2357487ddef3');\n",
" const dataTable =\n",
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
" [key], {});\n",
" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
" dataTable['output_type'] = 'display_data';\n",
" await google.colab.output.renderOutput(dataTable, element);\n",
" const docLink = document.createElement('div');\n",
" docLink.innerHTML = docLinkHtml;\n",
" element.appendChild(docLink);\n",
" }\n",
" </script>\n",
" </div>\n",
"\n",
"\n",
"<div id=\"df-bc64171b-0eb9-4507-ad33-404221c64d3e\">\n",
" <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-bc64171b-0eb9-4507-ad33-404221c64d3e')\"\n",
" title=\"Suggest charts.\"\n",
" style=\"display:none;\">\n",
"\n",
"<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
" width=\"24px\">\n",
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" </g>\n",
"</svg>\n",
" </button>\n",
"\n",
"<style>\n",
" .colab-df-quickchart {\n",
" --bg-color: #E8F0FE;\n",
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" --hover-bg-color: #E2EBFA;\n",
" --hover-fill-color: #174EA6;\n",
" --disabled-fill-color: #AAA;\n",
" --disabled-bg-color: #DDD;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-quickchart {\n",
" --bg-color: #3B4455;\n",
" --fill-color: #D2E3FC;\n",
" --hover-bg-color: #434B5C;\n",
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"\n",
" .colab-df-quickchart {\n",
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"\n",
" .colab-df-quickchart:hover {\n",
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"\n",
" .colab-df-quickchart-complete:disabled,\n",
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" background-color: var(--disabled-bg-color);\n",
" fill: var(--disabled-fill-color);\n",
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"\n",
" .colab-df-spinner {\n",
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" border-color: transparent;\n",
" border-bottom-color: var(--fill-color);\n",
" animation:\n",
" spin 1s steps(1) infinite;\n",
" }\n",
"\n",
" @keyframes spin {\n",
" 0% {\n",
" border-color: transparent;\n",
" border-bottom-color: var(--fill-color);\n",
" border-left-color: var(--fill-color);\n",
" }\n",
" 20% {\n",
" border-color: transparent;\n",
" border-left-color: var(--fill-color);\n",
" border-top-color: var(--fill-color);\n",
" }\n",
" 30% {\n",
" border-color: transparent;\n",
" border-left-color: var(--fill-color);\n",
" border-top-color: var(--fill-color);\n",
" border-right-color: var(--fill-color);\n",
" }\n",
" 40% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" border-top-color: var(--fill-color);\n",
" }\n",
" 60% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" }\n",
" 80% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" border-bottom-color: var(--fill-color);\n",
" }\n",
" 90% {\n",
" border-color: transparent;\n",
" border-bottom-color: var(--fill-color);\n",
" }\n",
" }\n",
"</style>\n",
"\n",
" <script>\n",
" async function quickchart(key) {\n",
" const quickchartButtonEl =\n",
" document.querySelector('#' + key + ' button');\n",
" quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
" quickchartButtonEl.classList.add('colab-df-spinner');\n",
" try {\n",
" const charts = await google.colab.kernel.invokeFunction(\n",
" 'suggestCharts', [key], {});\n",
" } catch (error) {\n",
" console.error('Error during call to suggestCharts:', error);\n",
" }\n",
" quickchartButtonEl.classList.remove('colab-df-spinner');\n",
" quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
" }\n",
" (() => {\n",
" let quickchartButtonEl =\n",
" document.querySelector('#df-bc64171b-0eb9-4507-ad33-404221c64d3e button');\n",
" quickchartButtonEl.style.display =\n",
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
" })();\n",
" </script>\n",
"</div>\n",
" </div>\n",
" </div>\n"
]
},
"metadata": {},
"execution_count": 17
}
],
"source": [
"df.describe()"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "fs16pWEI4Xdq",
"outputId": "2a3fe4e5-6c03-4ed2-d032-8fe42ff10cd5"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Valores nullados: \n",
"PRT_ID 0\n",
"AREA 0\n",
"INT_SQFT 0\n",
"DATE_SALE 0\n",
"DIST_MAINROAD 0\n",
"N_BEDROOM 0\n",
"N_BATHROOM 4\n",
"N_ROOM 0\n",
"SALE_COND 0\n",
"PARK_FACIL 0\n",
"DATE_BUILD 0\n",
"BUILDTYPE 0\n",
"UTILITY_AVAIL 0\n",
"STREET 0\n",
"MZZONE 0\n",
"QS_ROOMS 0\n",
"QS_BATHROOM 0\n",
"QS_BEDROOM 0\n",
"QS_OVERALL 29\n",
"REG_FEE 0\n",
"COMMIS 0\n",
"SALES_PRICE 0\n",
"dtype: int64\n",
"PRT_ID \t \t0.0%\n",
"AREA \t \t0.0%\n",
"INT_SQFT \t \t0.0%\n",
"DATE_SALE \t \t0.0%\n",
"DIST_MAINROAD \t \t0.0%\n",
"N_BEDROOM \t \t0.0%\n",
"N_BATHROOM \t \t0.08%\n",
"N_ROOM \t \t0.0%\n",
"SALE_COND \t \t0.0%\n",
"PARK_FACIL \t \t0.0%\n",
"DATE_BUILD \t \t0.0%\n",
"BUILDTYPE \t \t0.0%\n",
"UTILITY_AVAIL \t \t0.0%\n",
"STREET \t \t0.0%\n",
"MZZONE \t \t0.0%\n",
"QS_ROOMS \t \t0.0%\n",
"QS_BATHROOM \t \t0.0%\n",
"QS_BEDROOM \t \t0.0%\n",
"QS_OVERALL \t \t0.58%\n",
"REG_FEE \t \t0.0%\n",
"COMMIS \t \t0.0%\n",
"SALES_PRICE \t \t0.0%\n"
]
}
],
"source": [
"print(\"Valores nullados: \\n%s\" % df.isnull().sum())\n",
"for col in df.columns:\n",
" print(col, \"\\t \\t\"+str(round(100* df[col].isnull().sum() / len(df), 2)) + '%')"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "ETGt9hGaEoz1"
},
"source": [
"### Tratamento de Datas"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "6TsxOinZEthq",
"outputId": "7072e9bd-5dfa-40d3-c0a6-97cf800687e5"
},
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"<ipython-input-19-5818743cd40c>:3: UserWarning: Parsing dates in DD/MM/YYYY format when dayfirst=False (the default) was specified. This may lead to inconsistently parsed dates! Specify a format to ensure consistent parsing.\n",
" df['DATE_BUILD'] = pd.to_datetime(df['DATE_BUILD'])\n",
"<ipython-input-19-5818743cd40c>:4: UserWarning: Parsing dates in DD/MM/YYYY format when dayfirst=False (the default) was specified. This may lead to inconsistently parsed dates! Specify a format to ensure consistent parsing.\n",
" df['DATE_SALE'] = pd.to_datetime(df['DATE_SALE'])\n"
]
}
],
"source": [
"from datetime import datetime\n",
"\n",
"df['DATE_BUILD'] = pd.to_datetime(df['DATE_BUILD'])\n",
"df['DATE_SALE'] = pd.to_datetime(df['DATE_SALE'])\n",
"\n",
"df['DATE_BUILD_UNIX'] = df['DATE_BUILD'].apply(lambda x: int((x - datetime(1970, 1, 1)).total_seconds()))\n",
"df['DATE_SALE_UNIX'] = df['DATE_SALE'].apply(lambda x: int((x - datetime(1970, 1, 1)).total_seconds()))\n",
"\n",
"df['PARK_FACIL'] = df['PARK_FACIL'].apply(lambda x: 'No' if x == 'Noo' else x )\n",
"\n",
"df['STREET'] = df['STREET'].apply(lambda x: 'Paved' if x == 'Pavd' else x )\n",
"df['STREET'] = df['STREET'].apply(lambda x: 'No Access' if x == 'NoAccess' else x )\n",
"\n",
"df['AREA'] = df['AREA'].apply(lambda x: 'Chrompt' if x == 'Chrompet' else x )\n",
"df['AREA'] = df['AREA'].apply(lambda x: 'Chrompt' if x == 'Chrmpet' else x )\n",
"df['AREA'] = df['AREA'].apply(lambda x: 'Karapakkam' if x == 'Karapakam' else x )\n",
"df['AREA'] = df['AREA'].apply(lambda x: 'Anna Nagar' if x == 'Ann Nagar' else x )\n",
"df['AREA'] = df['AREA'].apply(lambda x: 'Anna Nagar' if x == 'Ana Nagar' else x )\n",
"\n",
"df['AREA'] = df['AREA'].apply(lambda x: 'Adyar' if x == 'Adyr' else x )\n",
"df['AREA'] = df['AREA'].apply(lambda x: 'KK Nagar' if x == 'KKNagar' else x )\n",
"df['AREA'] = df['AREA'].apply(lambda x: 'T Nagar' if x == 'TNagar' else x )"
]
},
{
"cell_type": "code",
"source": [
"len(list(df.AREA.unique()))"
],
"metadata": {
"id": "THy3G-8eAV9h",
"outputId": "b5b06588-00c4-404c-c13b-325ce3fc93d5",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
"execution_count": 13,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"9"
]
},
"metadata": {},
"execution_count": 13
}
]
},
{
"cell_type": "code",
"source": [
"list(df.N_ROOM.unique())"
],
"metadata": {
"id": "RHsWJbIkAUp_",
"outputId": "1b621750-2c18-4970-c208-20bf15f9c168",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
"execution_count": 10,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"[4, 3, 2, 6, 5]"
]
},
"metadata": {},
"execution_count": 10
}
]
},
{
"cell_type": "code",
"source": [
"list(df.SALE_COND.unique())"
],
"metadata": {
"id": "0me1sLHdBAzB",
"outputId": "16fbf5f2-9948-4ee9-f713-0a356c3b3229",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
"execution_count": 20,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"['Partial',\n",
" 'Family',\n",
" 'AbNormal',\n",
" 'Normal Sale',\n",
" 'AdjLand',\n",
" 'Ab Normal',\n",
" 'Adj Land']"
]
},
"metadata": {},
"execution_count": 20
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "074hb3GbFFz4"
},
"source": [
"### Tratamento de Missings"
]
},
{
"cell_type": "code",
"source": [
"import missingno as msno\n",
"%matplotlib inline\n",
"msno.matrix(df)"
],
"metadata": {
"id": "Vd71Y9XgBV5A",
"outputId": "b3ee8a81-4830-4f9b-ff5b-e8cda02db68e",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 802
}
},
"execution_count": 23,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<Axes: >"
]
},
"metadata": {},
"execution_count": 23
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 2500x1000 with 2 Axes>"
],
"image/png": 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},
"metadata": {}
}
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"id": "u3ciT_EIFL1m"
},
"outputs": [],
"source": [
"# Dropina na linha com campo zerados abaixo de 5%\n",
"\n",
"# QS_OVERALL == Estrelinhas, total: 29 < 250\n",
"df.dropna(subset=['QS_OVERALL'], inplace=True)\n",
"\n",
"# N_BATHROOM == Numero de Balheiros, total: 4 < 250\n",
"df.dropna(subset=['N_BATHROOM'], inplace=True)\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "j3RkTxrC2rCJ"
},
"source": [
"## Qualitativos:\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 430
},
"id": "g0-fKJeQ2VFJ",
"outputId": "26d40005-fe2d-4b06-c679-71317ca430a5"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"AREA: \n",
"\t\t17 valores unicos\n",
"SALE_COND: \n",
"\t\t7 valores unicos\n",
"PARK_FACIL: \n",
"\t\t2 valores unicos\n",
"BUILDTYPE: \n",
"\t\t5 valores unicos\n",
"UTILITY_AVAIL: \n",
"\t\t5 valores unicos\n",
"STREET: \n",
"\t\t3 valores unicos\n",
"MZZONE: \n",
"\t\t6 valores unicos\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
" AREA SALE_COND PARK_FACIL BUILDTYPE UTILITY_AVAIL STREET MZZONE\n",
"count 4967 4967 4967 4967 4967 4967 4967\n",
"unique 17 7 2 5 5 3 6\n",
"top Chrompet Normal Sale Yes House AllPub Paved RL\n",
"freq 1172 1006 2501 1743 1336 1785 1314"
],
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" width=\"24px\">\n",
" <g>\n",
" <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
" </g>\n",
"</svg>\n",
" </button>\n",
"\n",
"<style>\n",
" .colab-df-quickchart {\n",
" --bg-color: #E8F0FE;\n",
" --fill-color: #1967D2;\n",
" --hover-bg-color: #E2EBFA;\n",
" --hover-fill-color: #174EA6;\n",
" --disabled-fill-color: #AAA;\n",
" --disabled-bg-color: #DDD;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-quickchart {\n",
" --bg-color: #3B4455;\n",
" --fill-color: #D2E3FC;\n",
" --hover-bg-color: #434B5C;\n",
" --hover-fill-color: #FFFFFF;\n",
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" --disabled-fill-color: #666;\n",
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"\n",
" .colab-df-quickchart {\n",
" background-color: var(--bg-color);\n",
" border: none;\n",
" border-radius: 50%;\n",
" cursor: pointer;\n",
" display: none;\n",
" fill: var(--fill-color);\n",
" height: 32px;\n",
" padding: 0;\n",
" width: 32px;\n",
" }\n",
"\n",
" .colab-df-quickchart:hover {\n",
" background-color: var(--hover-bg-color);\n",
" box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
" fill: var(--button-hover-fill-color);\n",
" }\n",
"\n",
" .colab-df-quickchart-complete:disabled,\n",
" .colab-df-quickchart-complete:disabled:hover {\n",
" background-color: var(--disabled-bg-color);\n",
" fill: var(--disabled-fill-color);\n",
" box-shadow: none;\n",
" }\n",
"\n",
" .colab-df-spinner {\n",
" border: 2px solid var(--fill-color);\n",
" border-color: transparent;\n",
" border-bottom-color: var(--fill-color);\n",
" animation:\n",
" spin 1s steps(1) infinite;\n",
" }\n",
"\n",
" @keyframes spin {\n",
" 0% {\n",
" border-color: transparent;\n",
" border-bottom-color: var(--fill-color);\n",
" border-left-color: var(--fill-color);\n",
" }\n",
" 20% {\n",
" border-color: transparent;\n",
" border-left-color: var(--fill-color);\n",
" border-top-color: var(--fill-color);\n",
" }\n",
" 30% {\n",
" border-color: transparent;\n",
" border-left-color: var(--fill-color);\n",
" border-top-color: var(--fill-color);\n",
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" 40% {\n",
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" border-top-color: var(--fill-color);\n",
" }\n",
" 60% {\n",
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" border-right-color: var(--fill-color);\n",
" }\n",
" 80% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" border-bottom-color: var(--fill-color);\n",
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" const quickchartButtonEl =\n",
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" quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
" quickchartButtonEl.classList.add('colab-df-spinner');\n",
" try {\n",
" const charts = await google.colab.kernel.invokeFunction(\n",
" 'suggestCharts', [key], {});\n",
" } catch (error) {\n",
" console.error('Error during call to suggestCharts:', error);\n",
" }\n",
" quickchartButtonEl.classList.remove('colab-df-spinner');\n",
" quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
" }\n",
" (() => {\n",
" let quickchartButtonEl =\n",
" document.querySelector('#df-64a162f6-1404-4278-984d-fcaccd0b1c61 button');\n",
" quickchartButtonEl.style.display =\n",
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
" })();\n",
" </script>\n",
"</div>\n",
" </div>\n",
" </div>\n"
]
},
"metadata": {},
"execution_count": 9
}
],
"source": [
"columnsQualitativos = []\n",
"for coluna in list(df.columns):\n",
" if df[coluna].dtype == 'object':\n",
" if coluna != 'PRT_ID':\n",
" print(f'{coluna}: \\n\\t\\t{len(df[coluna].unique())} valores unicos')\n",
" columnsQualitativos.append(coluna)\n",
"df[columnsQualitativos].describe()"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "rjHDKV6i3gN5"
},
"source": [
"### Ordinal(Interpretação)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "RiCvh7eD3nQa"
},
"outputs": [],
"source": [
"columnsQualitativosOrdinal = []\n",
"# não encontrei nenhuma"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "7tznxB1W3n5h"
},
"source": [
"### Nominal(O que sobrou doque não é Ordinal)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 449
},
"id": "uj61xLYd3qQS",
"outputId": "b4636f27-1349-4d24-e793-e783724e02a1"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Qualitativo Nominal:\n",
"\tAREA: \n",
"\t\t17 valores unicos\n",
"\tSALE_COND: \n",
"\t\t7 valores unicos\n",
"\tPARK_FACIL: \n",
"\t\t2 valores unicos\n",
"\tBUILDTYPE: \n",
"\t\t5 valores unicos\n",
"\tUTILITY_AVAIL: \n",
"\t\t5 valores unicos\n",
"\tSTREET: \n",
"\t\t3 valores unicos\n",
"\tMZZONE: \n",
"\t\t6 valores unicos\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
" AREA SALE_COND PARK_FACIL BUILDTYPE UTILITY_AVAIL STREET MZZONE\n",
"count 4967 4967 4967 4967 4967 4967 4967\n",
"unique 17 7 2 5 5 3 6\n",
"top Chrompet Normal Sale Yes House AllPub Paved RL\n",
"freq 1172 1006 2501 1743 1336 1785 1314"
],
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" element.innerHTML = '';\n",
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" @keyframes spin {\n",
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" }\n",
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" border-color: transparent;\n",
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},
"metadata": {},
"execution_count": 11
}
],
"source": [
"columnsQualitativosNominal = []\n",
"print('Qualitativo Nominal:')\n",
"for coluna in columnsQualitativos:\n",
" if df[coluna].dtype == 'object' and not coluna in columnsQualitativosOrdinal:\n",
" if coluna != 'PRT_ID':\n",
" print(f'\\t{coluna}: \\n\\t\\t{len(df[coluna].unique())} valores unicos')\n",
" columnsQualitativosNominal.append(coluna)\n",
"df[columnsQualitativos].describe()"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "-p5M_4uN2-Yp"
},
"source": [
"## Quantitativos:\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 830
},
"id": "B2RwIe6k3DK9",
"outputId": "91577b34-e463-4840-e79b-5a04d2b34929"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Quantitativo:\n",
"\tINT_SQFT: \n",
"\t\t1589 valores unicos\n",
"\tDIST_MAINROAD: \n",
"\t\t201 valores unicos\n",
"\tN_BEDROOM: \n",
"\t\t4 valores unicos\n",
"\tN_BATHROOM: \n",
"\t\t2 valores unicos\n",
"\tN_ROOM: \n",
"\t\t5 valores unicos\n",
"\tQS_ROOMS: \n",
"\t\t31 valores unicos\n",
"\tQS_BATHROOM: \n",
"\t\t31 valores unicos\n",
"\tQS_BEDROOM: \n",
"\t\t31 valores unicos\n",
"\tQS_OVERALL: \n",
"\t\t452 valores unicos\n",
"\tREG_FEE: \n",
"\t\t4937 valores unicos\n",
"\tCOMMIS: \n",
"\t\t4923 valores unicos\n",
"\tSALES_PRICE: \n",
"\t\t4942 valores unicos\n",
"\tDATE_BUILD_UNIX: \n",
"\t\t4299 valores unicos\n",
"\tDATE_SALE_UNIX: \n",
"\t\t2425 valores unicos\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
" INT_SQFT DIST_MAINROAD N_BEDROOM N_BATHROOM N_ROOM \\\n",
"count 4967.000000 4967.000000 4967.000000 4967.000000 4967.000000 \n",
"mean 1381.446547 99.670626 1.638816 1.216026 3.687940 \n",
"std 458.366421 57.378633 0.809483 0.411573 1.023319 \n",
"min 500.000000 0.000000 1.000000 1.000000 2.000000 \n",
"25% 993.000000 51.000000 1.000000 1.000000 3.000000 \n",
"50% 1362.000000 99.000000 1.000000 1.000000 4.000000 \n",
"75% 1743.000000 148.000000 2.000000 1.000000 4.000000 \n",
"max 2499.000000 200.000000 4.000000 2.000000 6.000000 \n",
"\n",
" QS_ROOMS QS_BATHROOM QS_BEDROOM QS_OVERALL REG_FEE \\\n",
"count 4967.000000 4967.000000 4967.000000 4967.000000 4967.000000 \n",
"mean 3.513932 3.503141 3.488766 3.502996 376946.924300 \n",
"std 0.892685 0.902169 0.879039 0.527104 144481.127774 \n",
"min 2.000000 2.000000 2.000000 2.060000 71177.000000 \n",
"25% 2.700000 2.700000 2.700000 3.120000 270797.000000 \n",
"50% 3.500000 3.500000 3.500000 3.500000 348705.000000 \n",
"75% 4.300000 4.300000 4.250000 3.890000 450337.500000 \n",
"max 5.000000 5.000000 5.000000 4.970000 983922.000000 \n",
"\n",
" COMMIS SALES_PRICE DATE_BUILD_UNIX DATE_SALE_UNIX \n",
"count 4967.000000 4.967000e+03 4.967000e+03 4.967000e+03 \n",
"mean 140735.602980 1.089820e+07 5.063038e+08 1.270164e+09 \n",
"std 79467.381483 3.801751e+06 3.982235e+08 6.977234e+07 \n",
"min 5055.000000 2.156875e+06 -6.367680e+08 1.073261e+09 \n",
"25% 83516.000000 8.263490e+06 2.059776e+08 1.223122e+09 \n",
"50% 127635.000000 1.035325e+07 5.267808e+08 1.272758e+09 \n",
"75% 183609.500000 1.296997e+07 8.370864e+08 1.315786e+09 \n",
"max 495405.000000 2.366734e+07 1.292026e+09 1.449014e+09 "
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" .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>INT_SQFT</th>\n",
" <th>DIST_MAINROAD</th>\n",
" <th>N_BEDROOM</th>\n",
" <th>N_BATHROOM</th>\n",
" <th>N_ROOM</th>\n",
" <th>QS_ROOMS</th>\n",
" <th>QS_BATHROOM</th>\n",
" <th>QS_BEDROOM</th>\n",
" <th>QS_OVERALL</th>\n",
" <th>REG_FEE</th>\n",
" <th>COMMIS</th>\n",
" <th>SALES_PRICE</th>\n",
" <th>DATE_BUILD_UNIX</th>\n",
" <th>DATE_SALE_UNIX</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>4967.000000</td>\n",
" <td>4967.000000</td>\n",
" <td>4967.000000</td>\n",
" <td>4967.000000</td>\n",
" <td>4967.000000</td>\n",
" <td>4967.000000</td>\n",
" <td>4967.000000</td>\n",
" <td>4967.000000</td>\n",
" <td>4967.000000</td>\n",
" <td>4967.000000</td>\n",
" <td>4967.000000</td>\n",
" <td>4.967000e+03</td>\n",
" <td>4.967000e+03</td>\n",
" <td>4.967000e+03</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>1381.446547</td>\n",
" <td>99.670626</td>\n",
" <td>1.638816</td>\n",
" <td>1.216026</td>\n",
" <td>3.687940</td>\n",
" <td>3.513932</td>\n",
" <td>3.503141</td>\n",
" <td>3.488766</td>\n",
" <td>3.502996</td>\n",
" <td>376946.924300</td>\n",
" <td>140735.602980</td>\n",
" <td>1.089820e+07</td>\n",
" <td>5.063038e+08</td>\n",
" <td>1.270164e+09</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>458.366421</td>\n",
" <td>57.378633</td>\n",
" <td>0.809483</td>\n",
" <td>0.411573</td>\n",
" <td>1.023319</td>\n",
" <td>0.892685</td>\n",
" <td>0.902169</td>\n",
" <td>0.879039</td>\n",
" <td>0.527104</td>\n",
" <td>144481.127774</td>\n",
" <td>79467.381483</td>\n",
" <td>3.801751e+06</td>\n",
" <td>3.982235e+08</td>\n",
" <td>6.977234e+07</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>500.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>2.000000</td>\n",
" <td>2.000000</td>\n",
" <td>2.000000</td>\n",
" <td>2.000000</td>\n",
" <td>2.060000</td>\n",
" <td>71177.000000</td>\n",
" <td>5055.000000</td>\n",
" <td>2.156875e+06</td>\n",
" <td>-6.367680e+08</td>\n",
" <td>1.073261e+09</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>993.000000</td>\n",
" <td>51.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>3.000000</td>\n",
" <td>2.700000</td>\n",
" <td>2.700000</td>\n",
" <td>2.700000</td>\n",
" <td>3.120000</td>\n",
" <td>270797.000000</td>\n",
" <td>83516.000000</td>\n",
" <td>8.263490e+06</td>\n",
" <td>2.059776e+08</td>\n",
" <td>1.223122e+09</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>1362.000000</td>\n",
" <td>99.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>4.000000</td>\n",
" <td>3.500000</td>\n",
" <td>3.500000</td>\n",
" <td>3.500000</td>\n",
" <td>3.500000</td>\n",
" <td>348705.000000</td>\n",
" <td>127635.000000</td>\n",
" <td>1.035325e+07</td>\n",
" <td>5.267808e+08</td>\n",
" <td>1.272758e+09</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>1743.000000</td>\n",
" <td>148.000000</td>\n",
" <td>2.000000</td>\n",
" <td>1.000000</td>\n",
" <td>4.000000</td>\n",
" <td>4.300000</td>\n",
" <td>4.300000</td>\n",
" <td>4.250000</td>\n",
" <td>3.890000</td>\n",
" <td>450337.500000</td>\n",
" <td>183609.500000</td>\n",
" <td>1.296997e+07</td>\n",
" <td>8.370864e+08</td>\n",
" <td>1.315786e+09</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>2499.000000</td>\n",
" <td>200.000000</td>\n",
" <td>4.000000</td>\n",
" <td>2.000000</td>\n",
" <td>6.000000</td>\n",
" <td>5.000000</td>\n",
" <td>5.000000</td>\n",
" <td>5.000000</td>\n",
" <td>4.970000</td>\n",
" <td>983922.000000</td>\n",
" <td>495405.000000</td>\n",
" <td>2.366734e+07</td>\n",
" <td>1.292026e+09</td>\n",
" <td>1.449014e+09</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>\n",
" <div class=\"colab-df-buttons\">\n",
"\n",
" <div class=\"colab-df-container\">\n",
" <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7ff3a9ca-67fb-4351-be9f-21a0a3bab7ef')\"\n",
" title=\"Convert this dataframe to an interactive table.\"\n",
" style=\"display:none;\">\n",
"\n",
" <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
" <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
" </svg>\n",
" </button>\n",
"\n",
" <style>\n",
" .colab-df-container {\n",
" display:flex;\n",
" gap: 12px;\n",
" }\n",
"\n",
" .colab-df-convert {\n",
" background-color: #E8F0FE;\n",
" border: none;\n",
" border-radius: 50%;\n",
" cursor: pointer;\n",
" display: none;\n",
" fill: #1967D2;\n",
" height: 32px;\n",
" padding: 0 0 0 0;\n",
" width: 32px;\n",
" }\n",
"\n",
" .colab-df-convert:hover {\n",
" background-color: #E2EBFA;\n",
" box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
" fill: #174EA6;\n",
" }\n",
"\n",
" .colab-df-buttons div {\n",
" margin-bottom: 4px;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-convert {\n",
" background-color: #3B4455;\n",
" fill: #D2E3FC;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-convert:hover {\n",
" background-color: #434B5C;\n",
" box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
" fill: #FFFFFF;\n",
" }\n",
" </style>\n",
"\n",
" <script>\n",
" const buttonEl =\n",
" document.querySelector('#df-7ff3a9ca-67fb-4351-be9f-21a0a3bab7ef button.colab-df-convert');\n",
" buttonEl.style.display =\n",
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
"\n",
" async function convertToInteractive(key) {\n",
" const element = document.querySelector('#df-7ff3a9ca-67fb-4351-be9f-21a0a3bab7ef');\n",
" const dataTable =\n",
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
" [key], {});\n",
" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
" dataTable['output_type'] = 'display_data';\n",
" await google.colab.output.renderOutput(dataTable, element);\n",
" const docLink = document.createElement('div');\n",
" docLink.innerHTML = docLinkHtml;\n",
" element.appendChild(docLink);\n",
" }\n",
" </script>\n",
" </div>\n",
"\n",
"\n",
"<div id=\"df-9de7382c-cdd0-43e7-a690-0b279bcf8a05\">\n",
" <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-9de7382c-cdd0-43e7-a690-0b279bcf8a05')\"\n",
" title=\"Suggest charts.\"\n",
" style=\"display:none;\">\n",
"\n",
"<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
" width=\"24px\">\n",
" <g>\n",
" <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
" </g>\n",
"</svg>\n",
" </button>\n",
"\n",
"<style>\n",
" .colab-df-quickchart {\n",
" --bg-color: #E8F0FE;\n",
" --fill-color: #1967D2;\n",
" --hover-bg-color: #E2EBFA;\n",
" --hover-fill-color: #174EA6;\n",
" --disabled-fill-color: #AAA;\n",
" --disabled-bg-color: #DDD;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-quickchart {\n",
" --bg-color: #3B4455;\n",
" --fill-color: #D2E3FC;\n",
" --hover-bg-color: #434B5C;\n",
" --hover-fill-color: #FFFFFF;\n",
" --disabled-bg-color: #3B4455;\n",
" --disabled-fill-color: #666;\n",
" }\n",
"\n",
" .colab-df-quickchart {\n",
" background-color: var(--bg-color);\n",
" border: none;\n",
" border-radius: 50%;\n",
" cursor: pointer;\n",
" display: none;\n",
" fill: var(--fill-color);\n",
" height: 32px;\n",
" padding: 0;\n",
" width: 32px;\n",
" }\n",
"\n",
" .colab-df-quickchart:hover {\n",
" background-color: var(--hover-bg-color);\n",
" box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
" fill: var(--button-hover-fill-color);\n",
" }\n",
"\n",
" .colab-df-quickchart-complete:disabled,\n",
" .colab-df-quickchart-complete:disabled:hover {\n",
" background-color: var(--disabled-bg-color);\n",
" fill: var(--disabled-fill-color);\n",
" box-shadow: none;\n",
" }\n",
"\n",
" .colab-df-spinner {\n",
" border: 2px solid var(--fill-color);\n",
" border-color: transparent;\n",
" border-bottom-color: var(--fill-color);\n",
" animation:\n",
" spin 1s steps(1) infinite;\n",
" }\n",
"\n",
" @keyframes spin {\n",
" 0% {\n",
" border-color: transparent;\n",
" border-bottom-color: var(--fill-color);\n",
" border-left-color: var(--fill-color);\n",
" }\n",
" 20% {\n",
" border-color: transparent;\n",
" border-left-color: var(--fill-color);\n",
" border-top-color: var(--fill-color);\n",
" }\n",
" 30% {\n",
" border-color: transparent;\n",
" border-left-color: var(--fill-color);\n",
" border-top-color: var(--fill-color);\n",
" border-right-color: var(--fill-color);\n",
" }\n",
" 40% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" border-top-color: var(--fill-color);\n",
" }\n",
" 60% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" }\n",
" 80% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" border-bottom-color: var(--fill-color);\n",
" }\n",
" 90% {\n",
" border-color: transparent;\n",
" border-bottom-color: var(--fill-color);\n",
" }\n",
" }\n",
"</style>\n",
"\n",
" <script>\n",
" async function quickchart(key) {\n",
" const quickchartButtonEl =\n",
" document.querySelector('#' + key + ' button');\n",
" quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
" quickchartButtonEl.classList.add('colab-df-spinner');\n",
" try {\n",
" const charts = await google.colab.kernel.invokeFunction(\n",
" 'suggestCharts', [key], {});\n",
" } catch (error) {\n",
" console.error('Error during call to suggestCharts:', error);\n",
" }\n",
" quickchartButtonEl.classList.remove('colab-df-spinner');\n",
" quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
" }\n",
" (() => {\n",
" let quickchartButtonEl =\n",
" document.querySelector('#df-9de7382c-cdd0-43e7-a690-0b279bcf8a05 button');\n",
" quickchartButtonEl.style.display =\n",
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
" })();\n",
" </script>\n",
"</div>\n",
" </div>\n",
" </div>\n"
]
},
"metadata": {},
"execution_count": 12
}
],
"source": [
"columnsQuantitativos = []\n",
"print('Quantitativo:')\n",
"for coluna in list(df.columns):\n",
" if df[coluna].dtype == 'int64' or df[coluna].dtype == 'float64':\n",
" if coluna != 'PRT_ID':\n",
" print(f'\\t{coluna}: \\n\\t\\t{len(df[coluna].unique())} valores unicos')\n",
" columnsQuantitativos.append(coluna)\n",
"df[columnsQuantitativos].describe()"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "qjRot8ZW3U9J"
},
"source": [
"### Discreto"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "Me5XuNhx3avl",
"outputId": "24385d5a-43bc-4143-ef3a-cfe5a807c3d8"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Quantitativo Discreto:\n",
"\tINT_SQFT: \n",
"\t\t1589 valores unicos\n",
"\tDIST_MAINROAD: \n",
"\t\t201 valores unicos\n",
"\tN_ROOM: \n",
"\t\t5 valores unicos\n",
"\tREG_FEE: \n",
"\t\t4937 valores unicos\n",
"\tCOMMIS: \n",
"\t\t4923 valores unicos\n",
"\tSALES_PRICE: \n",
"\t\t4942 valores unicos\n",
"\tDATE_BUILD_UNIX: \n",
"\t\t4299 valores unicos\n",
"\tDATE_SALE_UNIX: \n",
"\t\t2425 valores unicos\n"
]
}
],
"source": [
"columnsQuantitativosDiscreto = []\n",
"print('Quantitativo Discreto:')\n",
"for coluna in columnsQuantitativos:\n",
" if df[coluna].dtype == 'int64':\n",
" print(f'\\t{coluna}: \\n\\t\\t{len(df[coluna].unique())} valores unicos')\n",
" columnsQuantitativosDiscreto.append(coluna)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "WdJLBvwQ3bd7"
},
"source": [
"### Continuo"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "3c0lwBiF3fCE",
"outputId": "096b5b3c-d454-4ce9-b4f7-9f639e24436f"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Quantitativo Continuo:\n",
"\tN_BEDROOM: \n",
"\t\t4 valores unicos\n",
"\tN_BATHROOM: \n",
"\t\t2 valores unicos\n",
"\tQS_ROOMS: \n",
"\t\t31 valores unicos\n",
"\tQS_BATHROOM: \n",
"\t\t31 valores unicos\n",
"\tQS_BEDROOM: \n",
"\t\t31 valores unicos\n",
"\tQS_OVERALL: \n",
"\t\t452 valores unicos\n"
]
}
],
"source": [
"columnsQuantitativosContinuo = []\n",
"print('Quantitativo Continuo:')\n",
"for coluna in columnsQuantitativos:\n",
" if df[coluna].dtype == 'float64':\n",
" print(f'\\t{coluna}: \\n\\t\\t{len(df[coluna].unique())} valores unicos')\n",
" columnsQuantitativosContinuo.append(coluna)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "6DVgzQSXMQ7Q"
},
"source": [
"### Tratamento 5%"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "v27rwoYPR7QE",
"outputId": "4e3ab19d-d4ec-4fe7-da83-b0e021cb2438"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Min values: 248.35 \n",
" AREA \n",
"\t Chrompt => 6 \n",
"\t Velchery => 2 \n",
"\t Ann Nagar => 1 \n",
"\t Chormpet => 3 \n",
"\t Chrompt => 6 \n",
"\t Chrompt => 6 \n",
"\t Chormpet => 3 \n",
"\t TNagar => 4 \n",
"\t Chrmpet => 3 \n",
"\t TNagar => 4 \n",
"\t Velchery => 2 \n",
"\t Ana Nagar => 3 \n",
"\t Chrompt => 6 \n",
"\t Karapakam => 2 \n",
"\t Chrmpet => 3 \n",
"\t Chormpet => 3 \n",
"\t Ana Nagar => 3 \n",
"\t TNagar => 4 \n",
"\t Adyr => 1 \n",
"\t Chrompt => 6 \n",
"\t Chrompt => 6 \n",
"\t KKNagar => 1 \n",
"\t Ana Nagar => 3 \n",
"\t TNagar => 4 \n",
"\t Karapakam => 2 \n",
"\t Chrmpet => 3 \n",
" SALE_COND \n",
"\t Ab Normal => 2 \n",
"\t Adj Land => 3 \n",
"\t Adj Land => 3 \n",
"\t Ab Normal => 2 \n",
"\t Adj Land => 3 \n",
" PARK_FACIL \n",
" BUILDTYPE \n",
"\t Other => 16 \n",
"\t Other => 16 \n",
"\t Other => 16 \n",
"\t Other => 16 \n",
"\t Other => 16 \n",
"\t Other => 16 \n",
"\t Other => 16 \n",
"\t Comercial => 2 \n",
"\t Other => 16 \n",
"\t Other => 16 \n",
"\t Comercial => 2 \n",
"\t Other => 16 \n",
"\t Other => 16 \n",
"\t Other => 16 \n",
"\t Other => 16 \n",
"\t Other => 16 \n",
"\t Other => 16 \n",
"\t Other => 16 \n",
" UTILITY_AVAIL \n",
"\t All Pub => 1 \n",
" STREET \n",
" MZZONE \n"
]
}
],
"source": [
"min_percentage = len(df.values) / 100 * 5\n",
"print(\"Min values: %.2f \" % min_percentage)\n",
"\n",
"for coluna in columnsQualitativosNominal:\n",
"\n",
" if coluna == 'SALES_PRICE' or coluna == 'DATE_BUILD_UNIX' or coluna == 'DATE_SALE_UNIX':\n",
" continue;\n",
"\n",
" sumaryColuna = df[coluna].value_counts()[~df[coluna].value_counts().isin([0])]\n",
" print(' %s ' % (coluna))\n",
" for index_to_remove, tipo in enumerate(df[coluna].values):\n",
" if sumaryColuna[tipo] < min_percentage:\n",
" print('\\t %s => %s ' % (tipo, sumaryColuna[tipo]))\n",
" df = df[df[coluna] != tipo]\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "rb8Xmdc5t0N-"
},
"source": [
"## Distribuição dos Dados"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "bXIDs6S99_Bm"
},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "iCCj7p2F8GcO"
},
"source": [
"### Valores Nominais"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"id": "CC_ETTxVttpf",
"outputId": "20026976-b969-42fd-e2c0-0e89a1aef4c6"
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1500x1000 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1500x1000 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1500x1000 with 1 Axes>"
],
"image/png": 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},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1500x1000 with 1 Axes>"
],
"image/png": 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},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1500x1000 with 1 Axes>"
],
"image/png": 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},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1500x1000 with 1 Axes>"
],
"image/png": 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lb7p165a77747Z511Vr7//e/ntddeS//+/fOrX/0qw4cPf9O5TJkyJZtvvnmmTp2aW265JXvssUduu+22ddYT39D5rM9BBx2UV155JdOmTcvMmTPzwgsvpFOnTvnkJz+ZM844I7vvvvubXuOt2GWXXTJ48OBcdtllGTNmTOV/J8uXL89RRx213nOefPLJehH99W/nr3XOOeeI6AAAzVBV3ev/u0oAAKDZ2HPPPfP1r389e+21V2NPBQAA3pOsiQ4AAM3YvvvuW1xmBAAAePss5wIAAM3QT37ykyxbtiw33nhjunbt2tjTAQCA9yxvogMAQDM0b968nHTSSfnb3/6Wr33ta409HQAAeM+yJjoAAAAAABR4Ex0AAAAAAAqsib6B1qxZk2effTbt2rVLVVVVY08HAAAAAIC3oa6uLq+88kp69uyZFi3K75uL6Bvo2WefTa9evRp7GgAAAAAAbERPP/10tthii+JxEX0DtWvXLsm//oG2b9++kWcDAAAAAMDbUVtbm169elXab4mIvoHWLuHSvn17ER0AAAAA4D3izZbv9sWiAAAAAABQIKIDAAAAAECBiA4AAAAAAAUiOgAAAAAAFIjoAAAAAABQIKIDAAAAAECBiA4AAAAAAAUiOgAAAAAAFIjoAAAAAABQIKIDAAAAAECBiA4AAAAAAAUiOgAAAAAAFIjoAAAAAABQIKIDAAAAAECBiA4AAAAAAAUiOgAAAAAAFIjoAAAAAABQIKIDAAAAAECBiA4AAAAAAAUiOgAAAAAAFIjoAAAAAABQIKIDAAAAAECBiA4AAAAAAAUiOgAAAAAAFIjoAAAAAABQIKIDAAAAAECBiA4AAAAAAAUiOgAAAAAAFIjoAAAAAABQIKIDAAAAAECBiA4AAAAAAAUiOgAAAAAAFIjoAAAAAABQIKIDAAAAAECBiA4AAAAAAAUiOgAAAAAAFIjoAAAAAABQIKIDAAAAAECBiA4AAAAAAAUiOgAAAAAAFLRq7AnQfPT5xm2NPQUANtCCC4Y39hQAAADgPcGb6AAAAAAAUCCiAwAAAABAgYgOAAAAAAAFIjoAAAAAABQ0ekSfNWtW9t133/Ts2TNVVVW55ZZb6h2vqqpa7+fCCy+sjOnTp886xy+44IJ615k7d24GDRqU1q1bp1evXpk4ceK78XgAAAAAADRjjR7Rly1blh122CGXXnrpeo8vWrSo3mfKlCmpqqrKQQcdVG/c+PHj6407+eSTK8dqa2uz1157pXfv3rn//vtz4YUXZty4cbniiive0WcDAAAAAKB5a9XYExg2bFiGDRtWPN69e/d627/4xS+y++6758Mf/nC9/e3atVtn7FpTp07NihUrMmXKlFRXV2e77bbLnDlzMmnSpIwcOfLtPwQAAAAAAO9Jjf4m+luxZMmS3HbbbRkxYsQ6xy644IJ06dIlH//4x3PhhRdm1apVlWOzZ8/Obrvtlurq6sq+oUOHZv78+XnxxRfXe6/ly5entra23gcAAAAAgPeXRn8T/a24+uqr065duxx44IH19p9yyinZaaed0rlz59x9990ZM2ZMFi1alEmTJiVJFi9enC233LLeOd26dasc69Sp0zr3mjBhQs4999x36EkAAAAAAGgOmlVEnzJlSo444oi0bt263v7Ro0dXfu7fv3+qq6vzla98JRMmTEhNTU2D7jVmzJh6162trU2vXr0aNnEA4D2rzzdua+wpALCBFlwwvLGnAAA0Q80mot91112ZP39+brjhhjcdO2DAgKxatSoLFixI375907179yxZsqTemLXbpXXUa2pqGhzgAQAAAAB4b2g2a6L/6Ec/ys4775wddtjhTcfOmTMnLVq0SNeuXZMkAwcOzKxZs7Jy5crKmOnTp6dv377rXcoFAAAAAACSJhDRly5dmjlz5mTOnDlJkieffDJz5szJwoULK2Nqa2tz44035stf/vI658+ePTuTJ0/Ogw8+mL/+9a+ZOnVqTj/99Bx55JGVQH744Yenuro6I0aMyLx583LDDTfk4osvrrdcCwAAAAAAvF6jL+dy3333Zffdd69srw3bxxxzTK666qokyfXXX5+6urocdthh65xfU1OT66+/PuPGjcvy5cuz5ZZb5vTTT68XyDt06JBp06Zl1KhR2XnnnbPZZptl7NixGTly5Dv7cAAAAAAANGtVdXV1dY09ieagtrY2HTp0yMsvv5z27ds39nQahS9OA2g+fHHau8fvR4Dmw+9HAODfbWjzbfTlXAAAAAAAoKkS0QEAAAAAoEBEBwAAAACAAhEdAAAAAAAKRHQAAAAAACgQ0QEAAAAAoEBEBwAAAACAAhEdAAAAAAAKRHQAAAAAACgQ0QEAAAAAoEBEBwAAAACAAhEdAAAAAAAKRHQAAAAAACgQ0QEAAAAAoEBEBwAAAACAAhEdAAAAAAAKRHQAAAAAACgQ0QEAAAAAoEBEBwAAAACAAhEdAAAAAAAKRHQAAAAAACgQ0QEAAAAAoEBEBwAAAACAAhEdAAAAAAAKRHQAAAAAACgQ0QEAAAAAoEBEBwAAAACAAhEdAAAAAAAKRHQAAAAAACgQ0QEAAAAAoEBEBwAAAACAAhEdAAAAAAAKRHQAAAAAACgQ0QEAAAAAoEBEBwAAAACAAhEdAAAAAAAKRHQAAAAAACgQ0QEAAAAAoEBEBwAAAACAAhEdAAAAAAAKRHQAAAAAACgQ0QEAAAAAoEBEBwAAAACAAhEdAAAAAAAKRHQAAAAAACgQ0QEAAAAAoEBEBwAAAACAAhEdAAAAAAAKRHQAAAAAACgQ0QEAAAAAoEBEBwAAAACAAhEdAAAAAAAKRHQAAAAAACgQ0QEAAAAAoEBEBwAAAACAAhEdAAAAAAAKRHQAAAAAACgQ0QEAAAAAoEBEBwAAAACAAhEdAAAAAAAKRHQAAAAAACgQ0QEAAAAAoEBEBwAAAACAAhEdAAAAAAAKRHQAAAAAACgQ0QEAAAAAoEBEBwAAAACAAhEdAAAAAAAKRHQAAAAAACgQ0QEAAAAAoEBEBwAAAACAAhEdAAAAAAAKRHQAAAAAACgQ0QEAAAAAoEBEBwAAAACAAhEdAAAAAAAKRHQAAAAAACgQ0QEAAAAAoEBEBwAAAACAAhEdAAAAAAAKRHQAAAAAACgQ0QEAAAAAoEBEBwAAAACAAhEdAAAAAAAKRHQAAAAAACgQ0QEAAAAAoEBEBwAAAACAAhEdAAAAAAAKRHQAAAAAACgQ0QEAAAAAoEBEBwAAAACAAhEdAAAAAAAKRHQAAAAAACgQ0QEAAAAAoEBEBwAAAACAAhEdAAAAAAAKRHQAAAAAACgQ0QEAAAAAoEBEBwAAAACAAhEdAAAAAAAKRHQAAAAAACgQ0QEAAAAAoEBEBwAAAACAAhEdAAAAAAAKRHQAAAAAACgQ0QEAAAAAoEBEBwAAAACAAhEdAAAAAAAKRHQAAAAAACgQ0QEAAAAAoEBEBwAAAACAgkaP6LNmzcq+++6bnj17pqqqKrfccku948cee2yqqqrqffbee+96Y1544YUcccQRad++fTp27JgRI0Zk6dKl9cbMnTs3gwYNSuvWrdOrV69MnDjxnX40AAAAAACauUaP6MuWLcsOO+yQSy+9tDhm7733zqJFiyqfn/zkJ/WOH3HEEZk3b16mT5+eW2+9NbNmzcrIkSMrx2tra7PXXnuld+/euf/++3PhhRdm3LhxueKKK96x5wIAAAAAoPlr1dgTGDZsWIYNG/aGY2pqatK9e/f1HnvkkUdy++23549//GN22WWXJMn3v//97LPPPvnud7+bnj17ZurUqVmxYkWmTJmS6urqbLfddpkzZ04mTZpUL7YDAAAAAMC/a/Q30TfEb3/723Tt2jV9+/bNiSeemOeff75ybPbs2enYsWMloCfJnnvumRYtWuTee++tjNltt91SXV1dGTN06NDMnz8/L7744nrvuXz58tTW1tb7AAAAAADw/tLkI/ree++da665JnfccUf+67/+K7/73e8ybNiwrF69OkmyePHidO3atd45rVq1SufOnbN48eLKmG7dutUbs3Z77ZjXmzBhQjp06FD59OrVa2M/GgAAAAAATVyjL+fyZg499NDKz/369Uv//v2z1VZb5be//W2GDBnyjt13zJgxGT16dGW7trZWSAcAAAAAeJ9p8m+iv96HP/zhbLbZZnn88ceTJN27d89zzz1Xb8yqVavywgsvVNZR7969e5YsWVJvzNrt0lrrNTU1ad++fb0PAAAAAADvL80uoj/zzDN5/vnn06NHjyTJwIED89JLL+X++++vjJk5c2bWrFmTAQMGVMbMmjUrK1eurIyZPn16+vbtm06dOr27DwAAAAAAQLPR6BF96dKlmTNnTubMmZMkefLJJzNnzpwsXLgwS5cuzZlnnpl77rknCxYsyB133JEvfOEL2XrrrTN06NAkycc+9rHsvffeOeGEE/KHP/whv//973PSSSfl0EMPTc+ePZMkhx9+eKqrqzNixIjMmzcvN9xwQy6++OJ6y7UAAAAAAMDrNXpEv++++/Lxj388H//4x5Mko0ePzsc//vGMHTs2LVu2zNy5c7Pffvtlm222yYgRI7LzzjvnrrvuSk1NTeUaU6dOzUc/+tEMGTIk++yzT3bddddcccUVleMdOnTItGnT8uSTT2bnnXfOGWeckbFjx2bkyJHv+vMCAAAAANB8NPoXiw4ePDh1dXXF4//zP//zptfo3Llzrrvuujcc079//9x1111veX4AAAAAALx/Nfqb6AAAAAAA0FSJ6AAAAAAAUCCiAwAAAABAgYgOAAAAAAAFIjoAAAAAABSI6AAAAAAAUCCiAwAAAABAgYgOAAAAAAAFIjoAAAAAABSI6AAAAAAAUCCiAwAAAABAgYgOAAAAAAAFIjoAAAAAABSI6AAAAAAAUCCiAwAAAABAgYgOAAAAAAAFIjoAAAAAABSI6AAAAAAAUCCiAwAAAABAgYgOAAAAAAAFIjoAAAAAABSI6AA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},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1500x1000 with 1 Axes>"
],
"image/png": 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},
"metadata": {}
}
],
"source": [
"for coluna in columnsQualitativosNominal:\n",
" frequencias = df[coluna].value_counts()\n",
" plt.figure(figsize=(15, 10))\n",
" plt.bar(frequencias.index, frequencias.values)\n",
" plt.xlabel('Valores')\n",
" plt.ylabel('Frequência')\n",
" plt.title(f'Distribuição da {coluna}')\n",
" plt.tight_layout()\n",
" plt.show()\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "g2P-cqsc-8XP"
},
"source": [
"### Valores Quantitativos"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"id": "46SzeWz5_VR9",
"outputId": "d8077d0e-77be-454b-bba0-fdeede7b881e"
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1500x600 with 1 Axes>"
],
"image/png": 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n58gjj8y8efNy9dVXL3OI/qMf/SjPPPNMzj333Lz33nvZaaedcvnll6d58+aVmr59++ZnP/tZLrzwwhx77LHp2bNn7rjjjpxwwglLPP9mm22WRx99NKeeemouu+yyzJo1Kz169Mg+++xTqbn44ouz0kor5frrr89HH32UrbfeOvfdd98iS9906tQpjzzySE488cRceuml+eijj7Lpppvmz3/+c/r377/EXq666qqsssoquf7663Pbbbdlxx13zJ133pmuXbvWqFvafj6rhg0b5pRTTslhhx1Wq+f9uIEDB+a9997LvffemzFjxmT69Olp165dvvrVr+aEE07IDjvsUKP+6KOPzhZbbJELLrggI0eOzDvvvJOiKNKxY8c8/fTT6dy583LrFQCAz0dVURcLCgIAAEulT58++eEPf5idd965rlthKZ111lk57bTT8uMf/zg/+clP6rodAAA+I2uiAwBAPbb77rvnt7/9bV23wadw6qmn5sgjj8zZZ5+dK6+8sq7bAQDgM/IkOgAA1EM33nhj3n///YwaNSodO3bMrbfeWtctrdDmz5+ff//7359Y07Jly7Rs2fJz6ggAgBWFNdEBAKAemjhxYi644IKsuuqqGTFiRF23s8J77bXXlrgO/umnn17jg0MBACDxJDoAAPAl8NFHH+Xvf//7J9astdZaWWuttT6njgAAWFEI0QEAAAAAoIQPFgUAAAAAgBLWRF9KCxYsyJtvvplWrVqlqqqqrtsBAAAAAOAzKIoi7733Xrp06ZIGDcqfNxeiL6U333wzXbt2res2AAAAAACoRa+99lpWX3310nEh+lJq1apVkv9+QVu3bl3H3QAAAAAA8FnMmjUrXbt2rWS/ZYToS2nhEi6tW7cWogMAAAAAfEEsafluHywKAAAAAAAlhOgAAAAAAFBCiA4AAAAAACWE6AAAAAAAUEKIDgAAAAAAJYToAAAAAABQQogOAAAAAAAlhOgAAAAAAFBCiA4AAAAAACWE6AAAAAAAUEKIDgAAAAAAJYToAAAAAABQQogOAAAAAAAlhOgAAAAAAFBCiA4AAAAAACWE6AAAAAAAUEKIDgAAAAAAJYToAAAAAABQQogOAAAAAAAlhOgAAAAAAFBCiA4AAAAAACUa1nUDrDjWPOnOum4BvlBeOa9/XbcAAAAAwBJ4Eh0AAAAAAEoI0QEAAAAAoIQQHQAAAAAASgjRAQAAAACghBAdAAAAAABKCNEBAAAAAKCEEB0AAAAAAEoI0QEAAAAAoIQQHQAAAAAASgjRAQAAAACghBAdAAAAAABKCNEBAAAAAKCEEB0AAAAAAErUeYj+0EMPZffdd0+XLl1SVVWV2267rbT2yCOPTFVVVUaOHFlj//Tp0zNo0KC0bt06bdu2zeDBgzN79uwaNc8880y23XbbNG3aNF27ds2IESOWw90AAAAAAPBFUuch+vvvv5/NNtssl1122SfW/fGPf8yjjz6aLl26LDI2aNCgTJw4MaNHj84dd9yRhx56KEOGDKmMz5o1KzvvvHO6deuW8ePH5/zzz88ZZ5yRK6+8stbvBwAAAACAL46Gdd3ALrvskl122eUTa954440cddRR+ctf/pL+/fvXGJs0aVLuueeePP744+nZs2eS5NJLL82uu+6aCy64IF26dMn111+fOXPm5Kqrrkrjxo2z0UYbZcKECbnwwgtrhO0AAAAAAPBxdf4k+pIsWLAgBx10UH7wgx9ko402WmR87Nixadu2bSVAT5I+ffqkQYMGGTduXKVmu+22S+PGjSs1ffv2zYsvvph33313+d8EAAAAAAArpDp/En1JfvrTn6Zhw4Y5+uijFzs+derUdOzYsca+hg0bpn379pk6dWqlpnv37jVqOnXqVBlr167dIuetrq5OdXV15fWsWbM+030AAAAAALDiqddPoo8fPz4XX3xxRo0alaqqqs/12ueee27atGlT2bp27fq5Xh8AAAAAgLpXr0P0v/3tb3n77bezxhprpGHDhmnYsGFeffXVnHDCCVlzzTWTJJ07d87bb79d47h58+Zl+vTp6dy5c6Vm2rRpNWoWvl5Y879OPvnkzJw5s7K99tprtXx3AAAAAADUd/V6OZeDDjooffr0qbGvb9++Oeigg3LYYYclSXr37p0ZM2Zk/Pjx2XLLLZMkY8aMyYIFC9KrV69KzY9//OPMnTs3jRo1SpKMHj06PXr0WOxSLknSpEmTNGnSZHndGgAAAAAAK4A6D9Fnz56df/zjH5XXkydPzoQJE9K+ffusscYa6dChQ436Ro0apXPnzunRo0eSZIMNNki/fv1y+OGH54orrsjcuXMzbNiw7LfffunSpUuS5IADDsiZZ56ZwYMH58QTT8xzzz2Xiy++OBdddNHnd6MAAAAAAKxw6jxEf+KJJ7LDDjtUXh9//PFJkkMOOSSjRo1aqnNcf/31GTZsWHbaaac0aNAgAwcOzCWXXFIZb9OmTe69994MHTo0W265ZVZeeeWcdtppGTJkSK3eCwAAAAAAXyxVRVEUdd3EimDWrFlp06ZNZs6cmdatW9d1O3VizZPurOsW4AvllfP613ULAAAAAF9aS5v51usPFgUAAAAAgLokRAcAAAAAgBJCdAAAAAAAKCFEBwAAAACAEkJ0AAAAAAAoIUQHAAAAAIASQnQAAAAAACghRAcAAAAAgBJCdAAAAAAAKCFEBwAAAACAEkJ0AAAAAAAoIUQHAAAAAIASQnQAAAAAACghRAcAAAAAgBJCdAAAAAAAKCFEBwAAAACAEkJ0AAAAAAAoIUQHAAAAAIASQnQAAAAAACghRAcAAAAAgBJCdAAAAAAAKCFEBwAAAACAEkJ0AAAAAAAoIUQHAAAAAIASQnQAAAAAACghRAcAAAAAgBJCdAAAAAAAKCFEBwAAAACAEkJ0AAAAAAAoIUQHAAAAAIASQnQAAAAAACghRAcAAAAAgBJCdAAAAAAAKCFEBwAAAACAEkJ0AAAAAAAoIUQHAAAAAIASQnQAAAAAACghRAcAAAAAgBJCdAAAAAAAKCFEBwAAAACAEkJ0AAAAAAAoIUQHAAAAAIASQnQAAAAAACghRAcAAAAAgBJCdAAAAAAAKCFEBwAAAACAEkJ0AAAAAAAoIUQHAAAAAIASQnQAAAAAACghRAcAAAAAgBJCdAAAAAAAKCFEBwAAAACAEkJ0AAAAAAAoIUQHAAAAAIASQnQAAAAAAChR5yH6Qw89lN133z1dunRJVVVVbrvttsrY3Llzc+KJJ2aTTTZJixYt0qVLlxx88MF58803a5xj+vTpGTRoUFq3bp22bdtm8ODBmT17do2aZ555Jttuu22aNm2arl27ZsSIEZ/H7QEAAAAAsAKr8xD9/fffz2abbZbLLrtskbEPPvggTz75ZE499dQ8+eSTufXWW/Piiy9mjz32qFE3aNCgTJw4MaNHj84dd9yRhx56KEOGDKmMz5o1KzvvvHO6deuW8ePH5/zzz88ZZ5yRK6+8crnfHwAAAAAAK66qoiiKum5ioaqqqvzxj3/MgAEDSmsef/zxfPWrX82rr76aNdZYI5MmTcqGG26Yxx9/PD179kyS3HPPPdl1113z+uuvp0uXLvnFL36RH//4x5k6dWoaN26cJDnppJNy22235YUXXliq3mbNmpU2bdpk5syZad269We+1xXRmifdWdctwBfKK+f1r+sWAAAAAL60ljbzrfMn0T+tmTNnpqqqKm3btk2SjB07Nm3btq0E6EnSp0+fNGjQIOPGjavUbLfddpUAPUn69u2bF198Me++++7n2j8AAAAAACuOhnXdwKfx0Ucf5cQTT8z+++9f+c3A1KlT07Fjxxp1DRs2TPv27TN16tRKTffu3WvUdOrUqTLWrl27Ra5VXV2d6urqyutZs2bV6r0AAAAAAFD/rTBPos+dOzf77LNPiqLIL37xi+V+vXPPPTdt2rSpbF27dl3u1wQAAAAAoH5ZIUL0hQH6q6++mtGjR9dYn6Zz5855++23a9TPmzcv06dPT+fOnSs106ZNq1Gz8PXCmv918sknZ+bMmZXttddeq81bAgAAAABgBVDvQ/SFAfrLL7+c++67Lx06dKgx3rt378yYMSPjx4+v7BszZkwWLFiQXr16VWoeeuihzJ07t1IzevTo9OjRY7FLuSRJkyZN0rp16xobAAAAAABfLnUeos+ePTsTJkzIhAkTkiSTJ0/OhAkTMmXKlMydOzff+ta38sQTT+T666/P/PnzM3Xq1EydOjVz5sxJkmywwQbp169fDj/88Dz22GN5+OGHM2zYsOy3337p0qVLkuSAAw5I48aNM3jw4EycODG/+93vcvHFF+f444+vq9sGAAAAAGAFUFUURVGXDTz44IPZYYcdFtl/yCGH5IwzzljkA0EXeuCBB7L99tsnSaZPn55hw4blz3/+cxo0aJCBAwfmkksuScuWLSv1zzzzTIYOHZrHH388K6+8co466qiceOKJS93nrFmz0qZNm8ycOfNL+1T6mifdWdctwBfKK+f1r+sWAAAAAL60ljbzrfMQfUUhRBeiQ20TogMAAADUnaXNfOt8ORcAAAAAAKivhOgAAAAAAFBCiA4AAAAAACWE6AAAAAAAUEKIDgAAAAAAJYToAAAAAABQQogOAAAAAAAlGtZ1AwB8cax50p113QJ8obxyXv+6bgEAAOBLT4gOAMDnxi/boHb5ZRsAwPJnORcAAAAAACghRAcAAAAAgBJCdAAAAAAAKCFEBwAAAACAEkJ0AAAAAAAoIUQHAAAAAIASQnQAAAAAACghRAcAAAAAgBJCdAAAAAAAKCFEBwAAAACAEkJ0AAAAAAAoIUQHAAAAAIASQnQAAAAAACghRAcAAAAAgBJCdAAAAAAAKCFEBwAAAACAEkJ0AAAAAAAoIUQHAAAAAIASQnQAAAAAACghRAcAAAAAgBJCdAAAAAAAKCFEBwAAAACAEkJ0AAAAAAAoIUQHAAAAAIASQnQAAAAAACghRAcAAAAAgBJCdAAAAAAAKCFEBwAAAACAEkJ0AAAAAAAoIUQHAAAAAIASQnQAAAAAACghRAcAAAAAgBJCdAAAAAAAKCFEBwAAAACAEkJ0AAAAAAAoIUQHAAAAAIASQnQAAAAAACghRAcAAAAAgBJCdAAAAAAAKCFEBwAAAACAEkJ0AAAAAAAoIUQHAAAAAIASQnQAAAAAACghRAcAAAAAgBJCdAAAAAAAKCFEBwAAAACAEnUeoj/00EPZfffd06VLl1RVVeW2226rMV4URU477bSsuuqqadasWfr06ZOXX365Rs306dMzaNCgtG7dOm3bts3gwYMze/bsGjXPPPNMtt122zRt2jRdu3bNiBEjlvetAQAAAACwgqvzEP3999/PZpttlssuu2yx4yNGjMgll1ySK664IuPGjUuLFi3St2/ffPTRR5WaQYMGZeLEiRk9enTuuOOOPPTQQxkyZEhlfNasWdl5553TrVu3jB8/Pueff37OOOOMXHnllcv9/gAAAAAAWHE1rOsGdtlll+yyyy6LHSuKIiNHjswpp5ySPffcM0ly7bXXplOnTrntttuy3377ZdKkSbnnnnvy+OOPp2fPnkmSSy+9NLvuumsuuOCCdOnSJddff33mzJmTq666Ko0bN85GG22UCRMm5MILL6wRtgMAAAAAwMfV+ZPon2Ty5MmZOnVq+vTpU9nXpk2b9OrVK2PHjk2SjB07Nm3btq0E6EnSp0+fNGjQIOPGjavUbLfddmncuHGlpm/fvnnxxRfz7rvvfk53AwAAAADAiqbOn0T/JFOnTk2SdOrUqcb+Tp06VcamTp2ajh071hhv2LBh2rdvX6Ome/fui5xj4Vi7du0WuXZ1dXWqq6srr2fNmvUZ7wYAAAAAgBVNvX4SvS6de+65adOmTWXr2rVrXbcEAAAAAMDnrF6H6J07d06STJs2rcb+adOmVcY6d+6ct99+u8b4vHnzMn369Bo1izvHx6/xv04++eTMnDmzsr322muf/YYAAAAAAFih1OsQvXv37uncuXPuv//+yr5Zs2Zl3Lhx6d27d5Kkd+/emTFjRsaPH1+pGTNmTBYsWJBevXpVah566KHMnTu3UjN69Oj06NFjsUu5JEmTJk3SunXrGhsAAAAAAF8udR6iz549OxMmTMiECROS/PfDRCdMmJApU6akqqoqxx57bH7yk5/k9ttvz7PPPpuDDz44Xbp0yYABA5IkG2ywQfr165fDDz88jz32WB5++OEMGzYs++23X7p06ZIkOeCAA9K4ceMMHjw4EydOzO9+97tcfPHFOf744+vorgEAAAAAWBHU+QeLPvHEE9lhhx0qrxcG24ccckhGjRqVH/7wh3n//fczZMiQzJgxI9tss03uueeeNG3atHLM9ddfn2HDhmWnnXZKgwYNMnDgwFxyySWV8TZt2uTee+/N0KFDs+WWW2bllVfOaaedliFDhnx+NwoAAAAAwAqnzkP07bffPkVRlI5XVVVl+PDhGT58eGlN+/btc8MNN3zidTbddNP87W9/W+Y+AQAAAAD48qnz5VwAAAAAAKC+EqIDAAAAAEAJIToAAAAAAJQQogMAAAAAQAkhOgAAAAAAlBCiAwAAAABACSE6AAAAAACUEKIDAAAAAEAJIToAAAAAAJQQogMAAAAAQAkhOgAAAAAAlBCiAwAAAABACSE6AAAAAACUEKIDAAAAAEAJIToAAAAAAJQQogMAAAAAQAkhOgAAAAAAlBCiAwAAAABACSE6AAAAAACUEKIDAAAAAEAJIToAAAAAAJQQogMAAAAAQAkhOgAAAAAAlBCiAwAAAABACSE6AAAAAACUaFjXDQAAAMBCa550Z123AF8or5zXv65bAFjheRIdAAAAAABKCNEBAAAAAKCEEB0AAAAAAEoI0QEAAAAAoIQQHQAAAAAASgjRAQAAAACghBAdAAAAAABKCNEBAAAAAKCEEB0AAAAAAEoI0QEAAAAAoIQQHQAAAAAASgjRAQAAAACgRMPPcvATTzyRm2++OVOmTMmcOXNqjN16662fqTEAAAAAAKhry/wk+k033ZStttoqkyZNyh//+MfMnTs3EydOzJgxY9KmTZva7BEAAAAAAOrEMofo55xzTi666KL8+c9/TuPGjXPxxRfnhRdeyD777JM11lijNnsEAAAAAIA6scwh+j//+c/0798/SdK4ceO8//77qaqqynHHHZcrr7yy1hoEAAAAAIC6sswhert27fLee+8lSVZbbbU899xzSZIZM2bkgw8+qJ3uAAAAAACgDi3zB4tut912GT16dDbZZJPsvffeOeaYYzJmzJiMHj06O+20U232CAAAAAAAdWKZQ/Sf//zn+eijj5IkP/7xj9OoUaM88sgjGThwYE455ZRaaxAAAAAAAOrKMofo7du3r/y5QYMGOemkk2qlIQAAAAAAqC8+VYg+a9astG7duvLnT7KwDgAAAAAAVlSfKkRv165d3nrrrXTs2DFt27ZNVVXVIjVFUaSqqirz58+vtSYBAAAAAKAufKoQfcyYMZVlXB544IHl0hAAAAAAANQXnypE//rXv77YPwMAAAAAwBdRg2U98Oqrr84tt9yyyP5bbrkl11xzzWdqCgAAAAAA6oNlDtHPPffcrLzyyovs79ixY84555zP1BQAAAAAANQHyxyiT5kyJd27d19kf7du3TJlypTP1BQAAAAAANQHyxyid+zYMc8888wi+59++ul06NDhMzUFAAAAAAD1wTKH6Pvvv3+OPvroPPDAA5k/f37mz5+fMWPG5Jhjjsl+++1Xmz0CAAAAAECdWOYQ/ayzzkqvXr2y0047pVmzZmnWrFl23nnn7LjjjrW6Jvr8+fNz6qmnpnv37mnWrFnWXnvtnHXWWSmKolJTFEVOO+20rLrqqmnWrFn69OmTl19+ucZ5pk+fnkGDBqV169Zp27ZtBg8enNmzZ9danwAAAAAAfPE0XNYDGzdunN/97nc566yz8vTTT6dZs2bZZJNN0q1bt9rsLz/96U/zi1/8Itdcc0022mijPPHEEznssMPSpk2bHH300UmSESNG5JJLLsk111yT7t2759RTT03fvn3z/PPPp2nTpkmSQYMG5a233sro0aMzd+7cHHbYYRkyZEhuuOGGWu0XAAAAAIAvjmUO0Rdab731st5669VGL4v1yCOPZM8990z//v2TJGuuuWZuvPHGPPbYY0n++xT6yJEjc8opp2TPPfdMklx77bXp1KlTbrvttuy3336ZNGlS7rnnnjz++OPp2bNnkuTSSy/NrrvumgsuuCBdunRZbv0DAAAAALDiWublXObPn5/f/OY3OeCAA9KnT5/suOOONbbastVWW+X+++/PSy+9lOS/H1z697//PbvsskuSZPLkyZk6dWr69OlTOaZNmzbp1atXxo4dmyQZO3Zs2rZtWwnQk6RPnz5p0KBBxo0bV2u9AgAAAADwxbLMT6Ifc8wxGTVqVPr375+NN944VVVVtdlXxUknnZRZs2Zl/fXXz0orrZT58+fn7LPPzqBBg5IkU6dOTZJ06tSpxnGdOnWqjE2dOjUdO3asMd6wYcO0b9++UvO/qqurU11dXXk9a9asWrsnAAAAAABWDMscot900025+eabs+uuu9ZmP4u4+eabc/311+eGG27IRhttlAkTJuTYY49Nly5dcsghhyy365577rk588wzl9v5AQAAAACo/5Z5OZfGjRtnnXXWqc1eFusHP/hBTjrppOy3337ZZJNNctBBB+W4447LueeemyTp3LlzkmTatGk1jps2bVplrHPnznn77bdrjM+bNy/Tp0+v1Pyvk08+OTNnzqxsr732Wm3fGgAAAAAA9dwyh+gnnHBCLr744hRFUZv9LOKDDz5IgwY121xppZWyYMGCJEn37t3TuXPn3H///ZXxWbNmZdy4cendu3eSpHfv3pkxY0bGjx9fqRkzZkwWLFiQXr16Lfa6TZo0SevWrWtsAAAAAAB8uSzzci5///vf88ADD+Tuu+/ORhttlEaNGtUYv/XWWz9zc0my++675+yzz84aa6yRjTbaKE899VQuvPDCfPvb306SVFVV5dhjj81PfvKTrLvuuunevXtOPfXUdOnSJQMGDEiSbLDBBunXr18OP/zwXHHFFZk7d26GDRuW/fbbL126dKmVPgEAAAAA+OJZ5hC9bdu22WuvvWqzl8W69NJLc+qpp+Z73/te3n777XTp0iVHHHFETjvttErND3/4w7z//vsZMmRIZsyYkW222Sb33HNPmjZtWqm5/vrrM2zYsOy0005p0KBBBg4cmEsuuWS59w8AAAAAwIprmUP0q6++ujb7KNWqVauMHDkyI0eOLK2pqqrK8OHDM3z48NKa9u3b54YbblgOHQIAAAAA8EW1zGuiJ//9cM777rsvv/zlL/Pee+8lSd58883Mnj27VpoDAAAAAIC69KmfRF+wYEEaNGiQV199Nf369cuUKVNSXV2db3zjG2nVqlV++tOfprq6OldcccXy6BcAAAAAAD43n+pJ9GeffTbbbbddkuSYY45Jz5498+6776ZZs2aVmr322iv3339/7XYJAAAAAAB1YKmfRP/973+f4cOH57e//W2S5G9/+1seeeSRNG7cuEbdmmuumTfeeKN2uwQAAAAAgDqw1E+iL1iwIPPnz09VVVWN1//r9ddfT6tWrWqvQwAAAAAAqCNLHaLvs88+ue666zJkyJAkyTe+8Y2MHDmyMl5VVZXZs2fn9NNPz6677lrrjQIAAAAAwOftU32w6BZbbJG//e1vSZILL7wwffv2zYYbbpiPPvooBxxwQF5++eWsvPLKufHGG5dLswAAAAAA8Hn6VCF6kjRs+N9DVl999Tz99NO56aab8swzz2T27NkZPHhwBg0aVOODRgEAAAAAYEX1qUP0Ggc3bJgDDzywtnoBAAAAAIB6ZZlD9GuvvfYTxw8++OBlPTUAAAAAANQLyxyiH3PMMTVez507Nx988EEaN26c5s2bC9EBAAAAAFjhNVjWA999990a2+zZs/Piiy9mm2228cGiAAAAAAB8ISxziL446667bs4777xFnlIHAAAAAIAVUa2G6Ml/P2z0zTffrO3TAgAAAADA526Z10S//fbba7wuiiJvvfVWfv7zn2frrbf+zI0BAAAAAEBdW+YQfcCAATVeV1VVZZVVVsmOO+6Yn/3sZ5+1LwAAAAAAqHPLHKIvWLCgNvsAAAAAAIB6p9bXRAcAAAAAgC+KZX4S/fjjj1/q2gsvvHBZLwMAAAAAAHVmmUP0p556Kk899VTmzp2bHj16JEleeumlrLTSStliiy0qdVVVVZ+9SwAAAAAAqAPLHKLvvvvuadWqVa655pq0a9cuSfLuu+/msMMOy7bbbpsTTjih1poEAAAAAIC6sMxrov/sZz/LueeeWwnQk6Rdu3b5yU9+kp/97Ge10hwAAAAAANSlZQ7RZ82alX//+9+L7P/3v/+d99577zM1BQAAAAAA9cEyh+h77bVXDjvssNx66615/fXX8/rrr+cPf/hDBg8enG9+85u12SMAAAAAANSJZV4T/Yorrsj3v//9HHDAAZk7d+5/T9awYQYPHpzzzz+/1hoEAAAAAIC6sswhevPmzXP55Zfn/PPPzz//+c8kydprr50WLVrUWnMAAAAAAFCXlnk5l4XeeuutvPXWW1l33XXTokWLFEVRG30BAAAAAECdW+YQ/Z133slOO+2U9dZbL7vuumveeuutJMngwYNzwgkn1FqDAAAAAABQV5Y5RD/uuOPSqFGjTJkyJc2bN6/s33fffXPPPffUSnMAAAAAAFCXlnlN9HvvvTd/+ctfsvrqq9fYv+666+bVV1/9zI0BAAAAAEBdW+Yn0d9///0aT6AvNH369DRp0uQzNQUAAAAAAPXBMofo2267ba699trK66qqqixYsCAjRozIDjvsUCvNAQAAAABAXVrm5VxGjBiRnXbaKU888UTmzJmTH/7wh5k4cWKmT5+ehx9+uDZ7BAAAAACAOrHMT6JvvPHGeemll7LNNttkzz33zPvvv59vfvObeeqpp7L22mvXZo8AAAAAAFAnlulJ9Llz56Zfv3654oor8uMf/7i2ewIAAAAAgHphmZ5Eb9SoUZ555pna7gUAAAAAAOqVZV7O5cADD8xvfvOb2uwFAAAAAADqlWX+YNF58+blqquuyn333Zctt9wyLVq0qDF+4YUXfubmAAAAAACgLn3qEP1f//pX1lxzzTz33HPZYostkiQvvfRSjZqqqqra6Q4AAAAAAOrQpw7R11133bz11lt54IEHkiT77rtvLrnkknTq1KnWmwMAAAAAgLr0qddEL4qixuu7774777//fq01BAAAAAAA9cUyf7DoQv8bqgMAAAAAwBfFpw7Rq6qqFlnz3BroAAAAAAB8EX3qNdGLosihhx6aJk2aJEk++uijHHnkkWnRokWNultvvbV2OgQAAAAAgDryqUP0Qw45pMbrAw88sNaaAQAAAACA+uRTh+hXX3318ugDAAAAAADqnc/8waIAAAAAAPBFJUQHAAAAAIASQnQAAAAAACghRAcAAAAAgBJCdAAAAAAAKCFEBwAAAACAEkJ0AAAAAAAoIUQHAAAAAIASQnQAAAAAACixQoTob7zxRg488MB06NAhzZo1yyabbJInnniiMl4URU477bSsuuqqadasWfr06ZOXX365xjmmT5+eQYMGpXXr1mnbtm0GDx6c2bNnf963AgAAAADACqTeh+jvvvtutt566zRq1Ch33313nn/++fzsZz9Lu3btKjUjRozIJZdckiuuuCLjxo1LixYt0rdv33z00UeVmkGDBmXixIkZPXp07rjjjjz00EMZMmRIXdwSAAAAAAAriIZ13cCS/PSnP03Xrl1z9dVXV/Z179698ueiKDJy5Miccsop2XPPPZMk1157bTp16pTbbrst++23XyZNmpR77rknjz/+eHr27JkkufTSS7PrrrvmggsuSJcuXT7fmwIAAAAAYIVQ759Ev/3229OzZ8/svffe6dixY77yla/kV7/6VWV88uTJmTp1avr06VPZ16ZNm/Tq1Stjx45NkowdOzZt27atBOhJ0qdPnzRo0CDjxo37/G4GAAAAAIAVSr0P0f/1r3/lF7/4RdZdd9385S9/yXe/+90cffTRueaaa5IkU6dOTZJ06tSpxnGdOnWqjE2dOjUdO3asMd6wYcO0b9++UvO/qqurM2vWrBobAAAAAABfLvV+OZcFCxakZ8+eOeecc5IkX/nKV/Lcc8/liiuuyCGHHLLcrnvuuefmzDPPXG7nBwAAAACg/qv3T6Kvuuqq2XDDDWvs22CDDTJlypQkSefOnZMk06ZNq1Ezbdq0yljnzp3z9ttv1xifN29epk+fXqn5XyeffHJmzpxZ2V577bVauR8AAAAAAFYc9T5E33rrrfPiiy/W2PfSSy+lW7duSf77IaOdO3fO/fffXxmfNWtWxo0bl969eydJevfunRkzZmT8+PGVmjFjxmTBggXp1avXYq/bpEmTtG7dusYGAAAAAMCXS71fzuW4447LVlttlXPOOSf77LNPHnvssVx55ZW58sorkyRVVVU59thj85Of/CTrrrtuunfvnlNPPTVdunTJgAEDkvz3yfV+/frl8MMPzxVXXJG5c+dm2LBh2W+//dKlS5c6vDsAAAAAAOqzeh+i/9///V/++Mc/5uSTT87w4cPTvXv3jBw5MoMGDarU/PCHP8z777+fIUOGZMaMGdlmm21yzz33pGnTppWa66+/PsOGDctOO+2UBg0aZODAgbnkkkvq4pYAAAAAAFhB1PsQPUl222237LbbbqXjVVVVGT58eIYPH15a0759+9xwww3Loz0AAAAAAL6g6v2a6AAAAAAAUFeE6AAAAAAAUEKIDgAAAAAAJYToAAAAAABQQogOAAAAAAAlhOgAAAAAAFBCiA4AAAAAACWE6AAAAAAAUEKIDgAAAAAAJYToAAAAAABQQogOAAAAAAAlhOgAAAAAAFBCiA4AAAAAACWE6AAAAAAAUEKIDgAAAAAAJYToAAAAAABQQogOAAAAAAAlhOgAAAAAAFBCiA4AAAAAACWE6AAAAAAAUEKIDgAAAAAAJYToAAAAAABQQogOAAAAAAAlhOgAAAAAAFBCiA4AAAAAACWE6AAAAAAAUEKIDgAAAAAAJYToAAAAAABQQogOAAAAAAAlhOgAAAAAAFBCiA4AAAAAACWE6AAAAAAAUEKIDgAAAAAAJYToAAAAAABQQogOAAAAAAAlhOgAAAAAAFBCiA4AAAAAACWE6AAAAAAAUEKIDgAAAAAAJYToAAAAAABQQogOAAAAAAAlhOgAAAAAAFBCiA4AAAAAACWE6AAAAAAAUEKIDgAAAAAAJYToAAAAAABQQogOAAAAAAAlhOgAAAAAAFBCiA4AAAAAACWE6AAAAAAAUEKIDgAAAAAAJYToAAAAAABQQogOAAAAAAAlhOgAAAAAAFBCiA4AAAAAACVWuBD9vPPOS1VVVY499tjKvo8++ihDhw5Nhw4d0rJlywwcODDTpk2rcdyUKVPSv3//NG/ePB07dswPfvCDzJs373PuHgAAAACAFckKFaI//vjj+eUvf5lNN920xv7jjjsuf/7zn3PLLbfkr3/9a958881885vfrIzPnz8//fv3z5w5c/LII4/kmmuuyahRo3Laaad93rcAAAAAAMAKZIUJ0WfPnp1BgwblV7/6Vdq1a1fZP3PmzPzmN7/JhRdemB133DFbbrllrr766jzyyCN59NFHkyT33ntvnn/++fz2t7/N5ptvnl122SVnnXVWLrvsssyZM6eubgkAAAAAgHpuhQnRhw4dmv79+6dPnz419o8fPz5z586tsX/99dfPGmuskbFjxyZJxo4dm0022SSdOnWq1PTt2zezZs3KxIkTP58bAAAAAABghdOwrhtYGjfddFOefPLJPP7444uMTZ06NY0bN07btm1r7O/UqVOmTp1aqfl4gL5wfOHY4lRXV6e6urryetasWZ/lFgAAAAAAWAHV+yfRX3vttRxzzDG5/vrr07Rp08/tuueee27atGlT2bp27fq5XRsAAAAAgPqh3ofo48ePz9tvv50tttgiDRs2TMOGDfPXv/41l1xySRo2bJhOnTplzpw5mTFjRo3jpk2bls6dOydJOnfunGnTpi0yvnBscU4++eTMnDmzsr322mu1f3MAAAAAANRr9T5E32mnnfLss89mwoQJla1nz54ZNGhQ5c+NGjXK/fffXznmxRdfzJQpU9K7d+8kSe/evfPss8/m7bffrtSMHj06rVu3zoYbbrjY6zZp0iStW7eusQEAAAAA8OVS79dEb9WqVTbeeOMa+1q0aJEOHTpU9g8ePDjHH3982rdvn9atW+eoo45K796987WvfS1JsvPOO2fDDTfMQQcdlBEjRmTq1Kk55ZRTMnTo0DRp0uRzvycAAAAAAFYM9T5EXxoXXXRRGjRokIEDB6a6ujp9+/bN5ZdfXhlfaaWVcscdd+S73/1uevfunRYtWuSQQw7J8OHD67BrAAAAAADquxUyRH/wwQdrvG7atGkuu+yyXHbZZaXHdOvWLXfddddy7gwAAAAAgC+Ser8mOgAAAAAA1BUhOgAAAAAAlBCiAwAAAABACSE6AAAAAACUEKIDAAAAAEAJIToAAAAAAJQQogMAAAAAQAkhOgAAAAAAlBCiAwAAAABACSE6AAAAAACUEKIDAAAAAEAJIToAAAAAAJQQogMAAAAAQAkhOgAAAAAAlBCiAwAAAABACSE6AAAAAACUEKIDAAAAAEAJIToAAAAAAJQQogMAAAAAQAkhOgAAAAAAlBCiAwAAAABACSE6AAAAAACUEKIDAAAAAEAJIToAAAAAAJQQogMAAAAAQAkhOgAAAAAAlBCiAwAAAABACSE6AAAAAACUEKIDAAAAAEAJIToAAAAAAJQQogMAAAAAQAkhOgAAAAAAlBCiAwAAAABACSE6AAAAAACUEKIDAAAAAEAJIToAAAAAAJQQogMAAAAAQAkhOgAAAAAAlBCiAwAAAABACSE6AAAAAACUEKIDAAAAAEAJIToAAAAAAJQQogMAAAAAQAkhOgAAAAAAlBCiAwAAAABAiYZ13QAAAAAALK01T7qzrluAL5RXzutf1y3Ue55EBwAAAACAEkJ0AAAAAAAoIUQHAAAAAIASQnQAAAAAACghRAcAAAAAgBJCdAAAAAAAKCFEBwAAAACAEkJ0AAAAAAAoIUQHAAAAAIAS9T5EP/fcc/N///d/adWqVTp27JgBAwbkxRdfrFHz0UcfZejQoenQoUNatmyZgQMHZtq0aTVqpkyZkv79+6d58+bp2LFjfvCDH2TevHmf560AAAAAALCCqfch+l//+tcMHTo0jz76aEaPHp25c+dm5513zvvvv1+pOe644/LnP/85t9xyS/7617/mzTffzDe/+c3K+Pz589O/f//MmTMnjzzySK655pqMGjUqp512Wl3cEgAAAAAAK4iGdd3Aktxzzz01Xo8aNSodO3bM+PHjs91222XmzJn5zW9+kxtuuCE77rhjkuTqq6/OBhtskEcffTRf+9rXcu+99+b555/Pfffdl06dOmXzzTfPWWedlRNPPDFnnHFGGjduXBe3BgAAAABAPVfvn0T/XzNnzkyStG/fPkkyfvz4zJ07N3369KnUrL/++lljjTUyduzYJMnYsWOzySabpFOnTpWavn37ZtasWZk4ceLn2D0AAAAAACuSev8k+sctWLAgxx57bLbeeutsvPHGSZKpU6emcePGadu2bY3aTp06ZerUqZWajwfoC8cXji1OdXV1qqurK69nzZpVW7cBAAAAAMAKYoV6En3o0KF57rnnctNNNy33a5177rlp06ZNZevatetyvyYAAAAAAPXLChOiDxs2LHfccUceeOCBrL766pX9nTt3zpw5czJjxowa9dOmTUvnzp0rNdOmTVtkfOHY4px88smZOXNmZXvttddq8W4AAAAAAFgR1PsQvSiKDBs2LH/84x8zZsyYdO/evcb4lltumUaNGuX++++v7HvxxRczZcqU9O7dO0nSu3fvPPvss3n77bcrNaNHj07r1q2z4YYbLva6TZo0SevWrWtsAAAAAAB8udT7NdGHDh2aG264IX/605/SqlWryhrmbdq0SbNmzdKmTZsMHjw4xx9/fNq3b5/WrVvnqKOOSu/evfO1r30tSbLzzjtnww03zEEHHZQRI0Zk6tSpOeWUUzJ06NA0adKkLm8PAAAAAIB6rN6H6L/4xS+SJNtvv32N/VdffXUOPfTQJMlFF12UBg0aZODAgamurk7fvn1z+eWXV2pXWmml3HHHHfnud7+b3r17p0WLFjnkkEMyfPjwz+s2AAAAAABYAdX7EL0oiiXWNG3aNJdddlkuu+yy0ppu3brlrrvuqs3WAAAAAAD4gqv3a6IDAAAAAEBdEaIDAAAAAEAJIToAAAAAAJQQogMAAAAAQAkhOgAAAAAAlBCiAwAAAABACSE6AAAAAACUEKIDAAAAAEAJIToAAAAAAJQQogMAAAAAQAkhOgAAAAAAlBCiAwAAAABACSE6AAAAAACUEKIDAAAAAEAJIToAAAAAAJQQogMAAAAAQAkhOgAAAAAAlBCiAwAAAABACSE6AAAAAACUEKIDAAAAAEAJIToAAAAAAJQQogMAAAAAQAkhOgAAAAAAlBCiAwAAAABACSE6AAAAAACUEKIDAAAAAEAJIToAAAAAAJQQogMAAAAAQAkhOgAAAAAAlBCiAwAAAABACSE6AAAAAACUEKIDAAAAAEAJIToAAAAAAJQQogMAAAAAQAkhOgAAAAAAlBCiAwAAAABACSE6AAAAAACUEKIDAAAAAEAJIToAAAAAAJQQogMAAAAAQAkhOgAAAAAAlBCiAwAAAABACSE6AAAAAACUEKIDAAAAAEAJIToAAAAAAJQQogMAAAAAQAkhOgAAAAAAlBCiAwAAAABACSE6AAAAAACUEKIDAAAAAEAJIToAAAAAAJQQogMAAAAAQAkhOgAAAAAAlBCiAwAAAABACSE6AAAAAACU+FKF6JdddlnWXHPNNG3aNL169cpjjz1W1y0BAAAAAFCPfWlC9N/97nc5/vjjc/rpp+fJJ5/MZpttlr59++btt9+u69YAAAAAAKinvjQh+oUXXpjDDz88hx12WDbccMNcccUVad68ea666qq6bg0AAAAAgHrqSxGiz5kzJ+PHj0+fPn0q+xo0aJA+ffpk7NixddgZAAAAAAD1WcO6buDz8J///Cfz589Pp06dauzv1KlTXnjhhcUeU11dnerq6srrmTNnJklmzZq1/Bqt5xZUf1DXLcAXyhdxPjFPQO0yTwBLYp4AlsQ8ASzJF3GeWFoL770oik+s+1KE6Mvi3HPPzZlnnrnI/q5du9ZBN8AXUZuRdd0BUN+ZJ4AlMU8AS2KeAJbEPJG89957adOmTen4lyJEX3nllbPSSitl2rRpNfZPmzYtnTt3XuwxJ598co4//vjK6wULFmT69Onp0KFDqqqqlmu/sKxmzZqVrl275rXXXkvr1q3ruh2gHjJPAEtingCWhrkCWBLzBCuCoijy3nvvpUuXLp9Y96UI0Rs3bpwtt9wy999/fwYMGJDkv6H4/fffn2HDhi32mCZNmqRJkyY19rVt23Y5dwq1o3Xr1v4HBXwi8wSwJOYJYGmYK4AlMU9Q333SE+gLfSlC9CQ5/vjjc8ghh6Rnz5756le/mpEjR+b999/PYYcdVtetAQAAAABQT31pQvR99903//73v3Paaadl6tSp2XzzzXPPPfcs8mGjAAAAAACw0JcmRE+SYcOGlS7fAl8ETZo0yemnn77IUkQAC5kngCUxTwBLw1wBLIl5gi+SqqIoirpuAgAAAAAA6qMGdd0AAAAAAADUV0J0AAAAAAAoIUQHAAAAAIASQnT4/x166KGpqqpKVVVVGjVqlE6dOuUb3/hGrrrqqixYsOAzn//JJ5/MN77xjbRt2zYdOnTIkCFDMnv27Bo1U6ZMSf/+/dO8efN07NgxP/jBDzJv3rwaNQ8++GC22GKLNGnSJOuss05GjRr1mXv7Xx999FEOPfTQbLLJJmnYsGEGDBiwSM3f//73bL311unQoUOaNWuW9ddfPxdddNEidZdddlnWXHPNNG3aNL169cpjjz22yLWGDh2aDh06pGXLlhk4cGCmTZtW6/cEy2J5zwtnn312ttpqqzRv3jxt27ZdZHzUqFGV6//v9vbbb1fqlmZeWNL3Ym341a9+lW233Tbt2rVLu3bt0qdPn0Wuc+utt2bnnXdOhw4dUlVVlQkTJixynqWZF5ZmvoTPQ13PE++880769euXLl26pEmTJunatWuGDRuWWbNm1airL/PExIkTM3DgwKy55pqpqqrKyJEjF6lZOPa/29ChQys15gm+aJb3XLK476vzzjuvRs0zzzyTbbfdNk2bNk3Xrl0zYsSIRc5zyy23ZP3110/Tpk2zySab5K677vrMvS3OZZddlg022CDNmjVLjx49cu21137qXoqiyGmnnZZVV101zZo1S58+ffLyyy8vl37hs1qec8Arr7ySwYMHp3v37mnWrFnWXnvtnH766ZkzZ06lZmkygKT+vJ9Ymp87Pv41Xbj169evRs306dMzaNCgtG7dOm3bts3gwYMXyWmWZm7ky0GIDh/Tr1+/vPXWW3nllVdy9913Z4cddsgxxxyT3Xbb7TP90PXmm2+mT58+WWeddTJu3Ljcc889mThxYg499NBKzfz589O/f//MmTMnjzzySK655pqMGjUqp512WqVm8uTJ6d+/f3bYYYdMmDAhxx57bL7zne/kL3/5y2e57UXMnz8/zZo1y9FHH50+ffostqZFixYZNmxYHnrooUyaNCmnnHJKTjnllFx55ZWVmt/97nc5/vjjc/rpp+fJJ5/MZpttlr59+9YI/4477rj8+c9/zi233JK//vWvefPNN/PNb36zVu8HPovlNS8kyZw5c7L33nvnu9/97mLH991337z11ls1tr59++brX/96OnbsmGTp5oWl+V6sDQ8++GD233//PPDAAxk7dmy6du2anXfeOW+88Ual5v33388222yTn/70p6XnWdK8sDTzJXye6nKeaNCgQfbcc8/cfvvteemllzJq1Kjcd999OfLIIys19Wme+OCDD7LWWmvlvPPOS+fOnRdb8/jjj9eY90aPHp0k2XvvvSs15gm+iJbnXJIkw4cPr/G9ddRRR1XGZs2alZ133jndunXL+PHjc/755+eMM86o8d7+kUceyf7775/BgwfnqaeeyoABAzJgwIA899xzn7m3j/vFL36Rk08+OWeccUYmTpyYM888M0OHDs2f//znT9XLiBEjcskll+SKK67IuHHj0qJFi/Tt2zcfffRRrfYLtWV5zQEvvPBCFixYkF/+8peZOHFiLrroolxxxRX50Y9+VKlZmgygPr2fWJqfO5L/9zVduN144401xgcNGpSJEydm9OjRueOOO/LQQw9lyJAhlfGlmRv5EimAoiiK4pBDDin23HPPRfbff//9RZLiV7/6VWXfu+++WwwePLhYeeWVi1atWhU77LBDMWHChNJz//KXvyw6duxYzJ8/v7LvmWeeKZIUL7/8clEURXHXXXcVDRo0KKZOnVqp+cUvflG0bt26qK6uLoqiKH74wx8WG220UY1z77vvvkXfvn1Lr/2f//yn2G+//YouXboUzZo1KzbeeOPihhtu+OQvxseUfV0WZ6+99ioOPPDAyuuvfvWrxdChQyuv58+fX3Tp0qU499xzi6IoihkzZhSNGjUqbrnllkrNpEmTiiTF2LFjl7pHWF6W57zwcVdffXXRpk2bJda9/fbbRaNGjYprr722sm9p5oUlfS8uzmOPPVb06dOn6NChQ9G6detiu+22K8aPH79U97PQvHnzilatWhXXXHPNImOTJ08ukhRPPfVUjf1LMy8szXwJn5f6Nk8URVFcfPHFxeqrr155XV/niW7duhUXXXTREuuOOeaYYu211y4WLFhQFIV5gi+m5T2XLOn77fLLLy/atWtX4/vjxBNPLHr06FF5vc8++xT9+/evcVyvXr2KI444ovS8//jHP4o99tij6NixY9GiRYuiZ8+exejRoz+x1969exff//73a+w7/vjji6233nqpe1mwYEHRuXPn4vzzz6+Mz5gxo2jSpElx4403fuL1oS58Xu8nFhoxYkTRvXv3T9VLfX0/URSL/7ljSVnG888/XyQpHn/88cq+u+++u6iqqireeOONoiiWbm7ky8OT6LAEO+64YzbbbLPceuutlX1777133n777dx9990ZP358tthii+y0006ZPn36Ys9RXV2dxo0bp0GD//ct16xZsyT/XRYlScaOHZtNNtkknTp1qtT07ds3s2bNysSJEys1//tb4b59+2bs2LGl/X/00UfZcsstc+edd+a5557LkCFDctBBB9X6X6l66qmn8sgjj+TrX/96kv8+OTd+/Pga/TZo0CB9+vSp9Dt+/PjMnTu3Rs3666+fNdZY4xPvCepabcwLy+Laa69N8+bN861vfauyb0nzwtJ8Ly7Oe++9l0MOOSR///vf8+ijj2bdddfNrrvumvfee2+p+/3ggw8yd+7ctG/ffqmPWZp5YWnmS6hrdTVPvPnmm7n11lsr/z9O6vc8sSRz5szJb3/723z7299OVVVVEvMEXy61OZecd9556dChQ77yla/k/PPPr/Fk69ixY7PddtulcePGlX19+/bNiy++mHfffbdS82l/Fpk9e3Z23XXX3H///XnqqafSr1+/7L777pkyZUrpMdXV1WnatGmNfc2aNctjjz2WuXPnLlUvkydPztSpU2vUtGnTJr169fJzBiuU5fV+YubMmZ/qPXpSv99PlP3c8eCDD6Zjx47p0aNHvvvd7+add96pcT9t27ZNz549K/v69OmTBg0aZNy4cZWaJc2NfHkI0WEprL/++nnllVeS/Df0fuyxx3LLLbekZ8+eWXfddXPBBRekbdu2+f3vf7/Y43fcccdMnTo1559/fubMmZN33303J510UpLkrbfeSpJMnTq1xg96SSqvp06d+ok1s2bNyocffrjYa6+22mr5/ve/n8033zxrrbVWjjrqqPTr1y8333zzsn0x/sfqq6+eJk2apGfPnhk6dGi+853vJEn+85//ZP78+Yvt9+P307hx40XWeP14DdRXn3VeWBa/+c1vcsABB1R+CZcseV5Ymu/Fxdlxxx1z4IEHZv31188GG2yQK6+8Mh988EH++te/LnW/J554Yrp06VL6V0IXZ2nmhaWZL6E++Dznif333z/NmzfPaqutltatW+fXv/51Zaw+zxNLctttt2XGjBk1lsAzT/BlUxtzydFHH52bbropDzzwQI444oicc845+eEPf1gZ/yw/i3zS99Rmm22WI444IhtvvHHWXXfdnHXWWVl77bVz++23lx7Tt2/f/PrXv8748eNTFEWeeOKJ/PrXv87cuXPzn//8Z6l6WfjPT9sv1Ee1/X7iH//4Ry699NIcccQRn6qP+vx+YnE/d/Tr1y/XXntt7r///vz0pz/NX//61+yyyy6ZP39+5X4WLpG5UMOGDdO+fXvvJ1ishnXdAKwIiqKoPP309NNPZ/bs2enQoUONmg8//DD//Oc/F3v8RhttlGuuuSbHH398Tj755Ky00ko5+uij06lTpxpPpy8P8+fPzznnnJObb745b7zxRubMmZPq6uo0b968Vs7/t7/9LbNnz86jjz6ak046Keuss07233//Wjk31GefdV74tMaOHZtJkybluuuuq5XzLcm0adNyyimn5MEHH8zbb7+d+fPn54MPPvjEJ8c+7rzzzstNN92UBx98cJGnyeDL4vOcJy666KKcfvrpeemll3LyySfn+OOPz+WXX/6Zz/tJPus8sTR+85vfZJdddkmXLl1q7ZywoqmNueT444+v/HnTTTdN48aNc8QRR+Tcc89NkyZNlk/j+e+T6GeccUbuvPPOvPXWW5k3b14+/PDDT5wnTj311EydOjVf+9rXUhRFOnXqlEMOOSQjRoxY7j87QX1Um+8n3njjjfTr1y977713Dj/88OXS76e1vH7u2G+//Sp/3mSTTbLppptm7bXXzoMPPpiddtqp1u+DLz4hOiyFSZMmpXv37kn++0Zw1VVXzYMPPrhI3f8+EfVxBxxwQA444IBMmzYtLVq0SFVVVS688MKstdZaSZLOnTsvssTKtGnTKmML/7lw38drWrduXePJ1I87//zzc/HFF2fkyJHZZJNN0qJFixx77LE1Pon7s1j4ddlkk00ybdq0nHHGGdl///2z8sorZ6WVVlpsvx+/nzlz5mTGjBk1vnYfr4H6qjbmhU/j17/+dTbffPNsueWWNfYvaV5YaaWVlvi9uDiHHHJI3nnnnVx88cXp1q1bmjRpkt69ey/V3HHBBRfkvPPOy3333ZdNN930U9zl0s0LSzNfQn3wec4TnTt3TufOnbP++uunffv22XbbbXPqqadm1VVXrZfzxNJ49dVXc99999X4K+wL79U8wZfJ8phLevXqlXnz5uWVV15Jjx49SueJZMk/i3zS99T3v//9jB49OhdccEHWWWedNGvWLN/61rc+cZ5o1qxZrrrqqvzyl7/MtGnTsuqqq+bKK69Mq1atssoqqyxVLwv/ufD4j9dsvvnmn/SlgXqntuaAN998MzvssEO22mqrZfpgzPr4fuLT/Nyx1lprZeWVV84//vGP7LTTTuncufMiH3g6b968TJ8+fYnz3sIxvlz8GheWYMyYMXn22WczcODAJMkWW2yRqVOnpmHDhllnnXVqbCuvvPISz9epU6e0bNkyv/vd79K0adN84xvfSJL07t07zz77bI1JfPTo0WndunU23HDDSs39999f43yjR49O7969S6/38MMPZ88998yBBx6YzTbbLGuttVZeeumlT/11WBoLFixIdXV1kqRx48bZcssta/S7YMGC3H///ZV+t9xyyzRq1KhGzYsvvpgpU6Z84j1BXavteWFJZs+enZtvvjmDBw9eZGxJ88LSfC8uzsMPP5yjjz46u+66azbaaKM0adKk8leoP8mIESNy1lln5Z577qmxvuDSWpp5YWnmS6hrn/c88XELFixIksr/k+vbPLG0rr766nTs2DH9+/evsd88wZfJ8ppLJkyYkAYNGlSWMujdu3ceeuihyprjyX+/Z3r06JF27dpVapblZ5FDDz00e+21VzbZZJN07ty5sizFkjRq1Cirr756Vlpppdx0003ZbbfdKk+iL6mX7t27p3PnzjVqZs2alXHjxvk5gxVKbc0Bb7zxRrbffvtsueWWufrqq5fpb3XUt/cTn/bnjtdffz3vvPNO5RdrvXv3zowZMzJ+/PhKzZgxY7JgwYL06tWrUrOkuZEvkTr8UFOoVw455JCiX79+xVtvvVW8/vrrxfjx44uzzz67aNmyZbHbbrsV8+bNK4riv5/0vs022xSbbbZZ8Ze//KWYPHly8fDDDxc/+tGPanyq8/+69NJLi/Hjxxcvvvhi8fOf/7xo1qxZcfHFF1fG582bV2y88cbFzjvvXEyYMKG45557ilVWWaU4+eSTKzX/+te/iubNmxc/+MEPikmTJhWXXXZZsdJKKxX33HNP6XWPO+64omvXrsXDDz9cPP/888V3vvOdonXr1p/4KdVFURQTJ04snnrqqWL33Xcvtt9+++Kpp54qnnrqqcr4z3/+8+L2228vXnrppeKll14qfv3rXxetWrUqfvzjH1dqbrrppqJJkybFqFGjiueff74YMmRI0bZt22Lq1KmVmiOPPLJYY401ijFjxhRPPPFE0bt376J3796f2Bt8Xpb3vPDqq68WTz31VHHmmWcWLVu2rHyfvffeezXqfv3rXxdNmzYt3n333UXOsTTzwtJ8L/6vr3zlK8U3vvGN4vnnny8effTRYtttty2aNWtWXHTRRaXHnHfeeUXjxo2L3//+98Vbb71V2T5+P++8807x1FNPFXfeeWeRpLjpppuKp556qnjrrbcqNUuaF5ZmvoTPS13PE3feeWdx1VVXFc8++2wxefLk4o477ig22GCDYuutt66coz7NE9XV1ZV7WHXVVYvvf//7xVNPPVW8/PLLNermz59frLHGGsWJJ5642POYJ/iiWZ5zySOPPFJcdNFFxYQJE4p//vOfxW9/+9tilVVWKQ4++OBKzYwZM4pOnToVBx10UPHcc88VN910U9G8efPil7/8ZaXm4YcfLho2bFhccMEFxaRJk4rTTz+9aNSoUfHss8+W3tdee+1VbL755sVTTz1VTJgwodh9992LVq1aFcccc0zpMS+++GJx3XXXFS+99FIxbty4Yt999y3at29fTJ48+VP1ct555xVt27Yt/vSnPxXPPPNMseeeexbdu3cvPvzwwyX964DP3fKcA15//fVinXXWKXbaaafi9ddfr/E+/eOWlAHUp/cTS/q547333iu+//3vF2PHji0mT55c3HfffcUWW2xRrLvuusVHH31UOU+/fv2Kr3zlK8W4ceOKv//978W6665b7L///pXxpZkb+fIQosP/75BDDimSFEmKhg0bFqusskrRp0+f4qqrrirmz59fo3bWrFnFUUcdVXTp0qVo1KhR0bVr12LQoEHFlClTSs9/0EEHFe3bty8aN25cbLrppsW11167SM0rr7xS7LLLLkWzZs2KlVdeuTjhhBOKuXPn1qh54IEHis0337xo3LhxsdZaaxVXX331J97XO++8U+y5555Fy5Yti44dOxannHJKcfDBBy8xRO/WrVvl6/HxbaFLLrmk2GijjYrmzZsXrVu3Lr7yla8Ul19++SJfq0svvbRYY401isaNGxdf/epXi0cffbTG+Icfflh873vfK9q1a1c0b9682GuvvRb5nznUleU9L3z8/B/fHnjggRp1vXv3Lg444IDS8yzNvLCk78X/9eSTTxY9e/YsmjZtWqy77rrFLbfcUnTr1u0T38yWzRunn356pebqq69eYs3SzAtLM1/C56Gu54kxY8YUvXv3Ltq0aVP5fj3xxBMX+aVbfZknJk+evNj7+frXv16j7i9/+UuRpHjxxRcXex7zBF80y3MuGT9+fNGrV6/KPLHBBhsU55xzTo0gqSiK4umnny622WabokmTJsVqq61WnHfeeYuc6+abby7WW2+9onHjxsVGG21U3HnnnZ94X5MnTy522GGHolmzZkXXrl2Ln//858XXv/71TwzRn3/++WLzzTcvmjVrVnn454UXXvjUvSxYsKA49dRTi06dOhVNmjQpdtppp9I5Bera8pwDyt5//+9ztUvKAIqi/ryfWNLPHR988EGx8847F6usskrRqFGjolu3bsXhhx++SJj/zjvvFPvvv3/RsmXLonXr1sVhhx22yANNSzM38uVQVRRFUVtPtQMAAAAAwBeJNdEBAAAAAKCEEB0AAAAAAEoI0QEAAAAAoIQQHQAAAAAASgjRAQAAAACghBAdAAAAAABKCNEBAAAAAKCEEB0AAAAAAEoI0QEA4Etm++23z7HHHlvXbQAAwApBiA4AACuQ3XffPf369Vvs2N/+9rdUVVXlmWee+Zy7AgCALy4hOgAArEAGDx6c0aNH5/XXX19k7Oqrr07Pnj2z6aabLtce5s+fnwULFizXawAAQH0hRAcAgBXIbrvtllVWWSWjRo2qsX/27Nm55ZZbMmDAgOy///5ZbbXV0rx582yyySa58cYbP/Gc7777bg4++OC0a9cuzZs3zy677JKXX365Mj5q1Ki0bds2t99+ezbccMM0adIkU6ZMSXV1db7//e9ntdVWS4sWLdKrV688+OCDleNeffXV7L777mnXrl1atGiRjTbaKHfddVdtfjkAAGC5E6IDAMAKpGHDhjn44IMzatSoFEVR2X/LLbdk/vz5OfDAA7PlllvmzjvvzHPPPZchQ4bkoIMOymOPPVZ6zkMPPTRPPPFEbr/99owdOzZFUWTXXXfN3LlzKzUffPBBfvrTn+bXv/51Jk6cmI4dO2bYsGEZO3ZsbrrppjzzzDPZe++9069fv0oAP3To0FRXV+ehhx7Ks88+m5/+9Kdp2bLl8vviAADAclBVfPydNwAAUO+98MIL2WCDDfLAAw9k++23T5Jst9126datW6677rpF6nfbbbesv/76ueCCC5L894NFN99884wcOTIvv/xy1ltvvTz88MPZaqutkiTvvPNOunbtmmuuuSZ77713Ro0alcMOOywTJkzIZpttliSZMmVK1lprrUyZMiVdunSpXKtPnz756le/mnPOOSebbrppBg4cmNNPP305f0UAAGD5aVjXDQAAAJ/O+uuvn6222ipXXXVVtt9++/zjH//I3/72twwfPjzz58/POeeck5tvvjlvvPFG5syZk+rq6jRv3nyx55o0aVIaNmyYXr16VfZ16NAhPXr0yKRJkyr7GjduXGOt9WeffTbz58/PeuutV+N81dXV6dChQ5Lk6KOPzne/+93ce++96dOnTwYOHLjc12sHAIDaZjkXAABYAQ0ePDh/+MMf8t577+Xqq6/O2muvna9//es5//zzc/HFF+fEE0/MAw88kAkTJqRv376ZM2fOZ7pes2bNUlVVVXk9e/bsrLTSShk/fnwmTJhQ2SZNmpSLL744SfKd73wn//rXv3LQQQfl2WefTc+ePXPppZd+pj4AAODzJkQHAIAV0D777JMGDRrkhhtuyLXXXptvf/vbqaqqysMPP5w999wzBx54YDbbbLOstdZaeemll0rPs8EGG2TevHkZN25cZd8777yTF198MRtuuGHpcV/5ylcyf/78vP3221lnnXVqbJ07d67Ude3aNUceeWRuvfXWnHDCCfnVr35VO18AAAD4nAjRAQBgBdSyZcvsu+++Ofnkk/PWW2/l0EMPTZKsu+66GT16dB555JFMmjQpRxxxRKZNm1Z6nnXXXTd77rlnDj/88Pz973/P008/nQMPPDCrrbZa9txzz9Lj1ltvvQwaNCgHH3xwbr311kyePDmPPfZYzj333Nx5551JkmOPPTZ/+ctfMnny5Dz55JN54IEHssEGG9Tq1wEAAJY3IToAAKygBg8enHfffTd9+/atfLjnKaecki222CJ9+/bN9ttvn86dO2fAgAGfeJ6rr746W265ZXbbbbf07t07RVHkrrvuSqNGjZZ43MEHH5wTTjghPXr0yIABA/L4449njTXWSJLMnz8/Q4cOzQYbbJB+/fplvfXWy+WXX14r9w4AAJ+XqqIoirpuAgAAAAAA6iNPogMAAAAAQAkhOgAAAAAAlBCiAwAAAABACSE6AAAAAACUEKIDAAAAAEAJIToAAAAAAJQQogMAAAAAQAkhOgAAAAAAlBCiAwAAAABACSE6AAAAAACUEKIDAAAAAEAJIToAAAAAAJT4/wCys1FDl9gFfQAAAABJRU5ErkJggg==\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1500x600 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1500x600 with 1 Axes>"
],
"image/png": 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9a1/7WmbPnp3x48fnzTffzL777purr746zZs3L48ZMmRILr300lx22WU566yzsvvuu+f222/P2Wef/b7z77TTTvnTn/6Ub3zjG7nqqqtSVVWVPn365PDDDy+Pufzyy7PJJptk6tSpeeedd/KZz3wm99xzzxpb33Tu3DkPPvhgzj333Fx55ZV555130rdv3/zmN7/J8OHD37eWyZMnp2PHjpk6dWp++ctfZp999skdd9yR7t27Vxu3vvVsqHHjxmXQoEEfaI736tatW0aMGJEbbrgh8+bNK/9hY/To0dl9991z6aWXZtKkSVm8eHG6du2aww47LF//+tfXuvVNTa4BAKBhqCi99/9rCQAA1Ev77bdfzjnnnAwePLiuSwEAgI8Ne6IDAEADceCBB+YnP/lJXZcBAAAfK7ZzAQCAeu6nP/1p3nrrrdx6663p1KlTXZdTLyxbtmytXyb7bq1bt06zZs0+pIoAAPioEqIDAEA9N2fOnHz3u99N165dM3HixLoup1548MEH33eP9ClTpuT444//cAoCAOAjy57oAABAg/P666/n0UcfXeeY7bffPl27dv2QKgIA4KNKiA4AAAAAAAV8sSgAAAAAABSwJ/p6WrVqVV5++eW0bNkyFRUVdV0OAAAAAAAfQKlUyptvvplu3bqlUaPi982F6Ovp5ZdfTvfu3eu6DAAAAAAAatHf//73bL755oX9QvT11LJlyyT/+YG2atWqjqsBAAAAAOCDqKqqSvfu3cvZbxEh+npavYVLq1athOgAAAAAAB8R77d9ty8WBQAAAACAAkJ0AAAAAAAoIEQHAAAAAIACQnQAAAAAACggRAcAAAAAgAJCdAAAAAAAKCBEBwAAAACAAkJ0AAAAAAAoIEQHAAAAAIACQnQAAAAAACggRAcAAAAAgAJCdAAAAAAAKCBEBwAAAACAAkJ0AAAAAAAoIEQHAAAAAIACQnQAAAAAACggRAcAAAAAgAJCdAAAAAAAKCBEBwAAAACAAkJ0AAAAAAAoIEQHAAAAAIACjeu6ABqOnl+9o65LABqQFyYMr+sSAAAAAD4wb6IDAAAAAEABIToAAAAAABSo8xB9xowZOfDAA9OtW7dUVFTkl7/8ZbX+ioqKtR6XXHJJeUzPnj3X6J8wYUK1eWbPnp299torm266abp3756JEyd+GI8HAAAAAEADVuch+ltvvZWddtopV1111Vr7FyxYUO2YPHlyKioqcuihh1Ybd9FFF1Ubd/rpp5f7qqqqMnjw4PTo0SOPPvpoLrnkkowbNy7XXnvtRn02AAAAAAAatjr/YtFhw4Zl2LBhhf1dunSpdv6rX/0qgwYNyic/+clq7S1btlxj7GpTp07NsmXLMnny5DRt2jTbb799Zs2alcsuuyyjRo364A8BAAAAAMBHUp2/ib4hFi1alDvuuCMjR45co2/ChAlp3759dtlll1xyySVZsWJFuW/mzJkZMGBAmjZtWm4bMmRI5s6dm9dff/1DqR0AAAAAgIanzt9E3xDXX399WrZsmc9//vPV2s8444zsuuuuadeuXR588MGMHTs2CxYsyGWXXZYkWbhwYXr16lXtms6dO5f72rZtu8a9li5dmqVLl5bPq6qqavtxAAAAAACo5xpUiD558uQcffTR2XTTTau1jxkzpvy5b9++adq0aU466aSMHz8+lZWVNbrX+PHjc+GFF36gegEAAAAAaNgazHYu999/f+bOnZsvf/nL7zu2X79+WbFiRV544YUk/9lXfdGiRdXGrD4v2kd97NixWbx4cfn4+9///sEeAAAAAACABqfBhOg/+tGPsttuu2WnnXZ637GzZs1Ko0aN0qlTpyRJ//79M2PGjCxfvrw8Ztq0aenTp89at3JJksrKyrRq1araAQAAAADAx0udh+hLlizJrFmzMmvWrCTJ888/n1mzZmX+/PnlMVVVVbn11lvX+hb6zJkzM2nSpDz++OP529/+lqlTp2b06NE55phjygH5iBEj0rRp04wcOTJz5szJzTffnMsvv7zaNjAAAAAAAPBedb4n+iOPPJJBgwaVz1cH28cdd1yuu+66JMlNN92UUqmUo446ao3rKysrc9NNN2XcuHFZunRpevXqldGjR1cLyFu3bp277747p556anbbbbd06NAh559/fkaNGrVxHw4AAAAAgAatolQqleq6iIagqqoqrVu3zuLFiz+2W7v0/OoddV0C0IC8MGF4XZcAAAAAUGh9M986384FAAAAAADqKyE6AAAAAAAUEKIDAAAAAEABIToAAAAAABQQogMAAAAAQAEhOgAAAAAAFBCiAwAAAABAASE6AAAAAAAUEKIDAAAAAEABIToAAAAAABQQogMAAAAAQAEhOgAAAAAAFBCiAwAAAABAASE6AAAAAAAUEKIDAAAAAEABIToAAAAAABQQogMAAAAAQAEhOgAAAAAAFBCiAwAAAABAASE6AAAAAAAUEKIDAAAAAEABIToAAAAAABQQogMAAAAAQAEhOgAAAAAAFBCiAwAAAABAASE6AAAAAAAUEKIDAAAAAEABIToAAAAAABQQogMAAAAAQAEhOgAAAAAAFBCiAwAAAABAASE6AAAAAAAUEKIDAAAAAEABIToAAAAAABQQogMAAAAAQAEhOgAAAAAAFBCiAwAAAABAASE6AAAAAAAUEKIDAAAAAEABIToAAAAAABQQogMAAAAAQAEhOgAAAAAAFBCiAwAAAABAASE6AAAAAAAUEKIDAAAAAEABIToAAAAAABQQogMAAAAAQAEhOgAAAAAAFBCiAwAAAABAASE6AAAAAAAUEKIDAAAAAEABIToAAAAAABQQogMAAAAAQAEhOgAAAAAAFBCiAwAAAABAASE6AAAAAAAUEKIDAAAAAECBOg/RZ8yYkQMPPDDdunVLRUVFfvnLX1brP/7441NRUVHtGDp0aLUxr732Wo4++ui0atUqbdq0yciRI7NkyZJqY2bPnp299torm266abp3756JEydu7EcDAAAAAKCBq/MQ/a233spOO+2Uq666qnDM0KFDs2DBgvLx05/+tFr/0UcfnTlz5mTatGm5/fbbM2PGjIwaNarcX1VVlcGDB6dHjx559NFHc8kll2TcuHG59tprN9pzAQAAAADQ8DWu6wKGDRuWYcOGrXNMZWVlunTpsta+p556KnfddVcefvjh7L777kmSK6+8Mvvvv3+++93vplu3bpk6dWqWLVuWyZMnp2nTptl+++0za9asXHbZZdXCdgAAAAAAeLc6fxN9ffz+979Pp06d0qdPn5xyyil59dVXy30zZ85MmzZtygF6kuy3335p1KhRHnroofKYAQMGpGnTpuUxQ4YMydy5c/P666+v9Z5Lly5NVVVVtQMAAAAAgI+Xeh+iDx06ND/+8Y9z77335jvf+U7+8Ic/ZNiwYVm5cmWSZOHChenUqVO1axo3bpx27dpl4cKF5TGdO3euNmb1+eox7zV+/Pi0bt26fHTv3r22Hw0AAAAAgHquzrdzeT9HHnlk+fOOO+6Yvn37pnfv3vn973+ffffdd6Pdd+zYsRkzZkz5vKqqSpAOAAAAAPAxU+/fRH+vT37yk+nQoUOee+65JEmXLl3yyiuvVBuzYsWKvPbaa+V91Lt06ZJFixZVG7P6vGiv9crKyrRq1araAQAAAADAx0uDC9FfeumlvPrqq+natWuSpH///nnjjTfy6KOPlsdMnz49q1atSr9+/cpjZsyYkeXLl5fHTJs2LX369Enbtm0/3AcAAAAAAKDBqPMQfcmSJZk1a1ZmzZqVJHn++ecza9aszJ8/P0uWLMlXvvKV/OlPf8oLL7yQe++9NwcffHC23HLLDBkyJEmy7bbbZujQoTnxxBPz5z//OQ888EBOO+20HHnkkenWrVuSZMSIEWnatGlGjhyZOXPm5Oabb87ll19ebbsWAAAAAAB4rzoP0R955JHssssu2WWXXZIkY8aMyS677JLzzz8/m2yySWbPnp2DDjooW2+9dUaOHJnddtst999/fyorK8tzTJ06Ndtss0323Xff7L///tlzzz1z7bXXlvtbt26du+++O88//3x22223nH322Tn//PMzatSoD/15AQAAAABoOCpKpVKprotoCKqqqtK6dessXrz4Y7s/es+v3lHXJQANyAsThtd1CQAAAACF1jfzrfM30QEAAAAAoL4SogMAAAAAQAEhOgAAAAAAFGhc1wUAwEed75QANoTvlAAAgPrFm+gAAAAAAFBAiA4AAAAAAAWE6AAAAAAAUECIDgAAAAAABYToAAAAAABQQIgOAAAAAAAFhOgAAAAAAFBAiA4AAAAAAAWE6AAAAAAAUECIDgAAAAAABYToAAAAAABQQIgOAAAAAAAFhOgAAAAAAFBAiA4AAAAAAAWE6AAAAAAAUECIDgAAAAAABYToAAAAAABQQIgOAAAAAAAFhOgAAAAAAFBAiA4AAAAAAAWE6AAAAAAAUECIDgAAAAAABYToAAAAAABQQIgOAAAAAAAFhOgAAAAAAFBAiA4AAAAAAAWE6AAAAAAAUECIDgAAAAAABYToAAAAAABQQIgOAAAAAAAFhOgAAAAAAFBAiA4AAAAAAAWE6AAAAAAAUECIDgAAAAAABYToAAAAAABQQIgOAAAAAAAFhOgAAAAAAFBAiA4AAAAAAAWE6AAAAAAAUECIDgAAAAAABYToAAAAAABQQIgOAAAAAAAFhOgAAAAAAFBAiA4AAAAAAAWE6AAAAAAAUECIDgAAAAAABYToAAAAAABQQIgOAAAAAAAFhOgAAAAAAFBAiA4AAAAAAAWE6AAAAAAAUECIDgAAAAAABYToAAAAAABQoM5D9BkzZuTAAw9Mt27dUlFRkV/+8pflvuXLl+fcc8/NjjvumBYtWqRbt2459thj8/LLL1ebo2fPnqmoqKh2TJgwodqY2bNnZ6+99sqmm26a7t27Z+LEiR/G4wEAAAAA0IDVeYj+1ltvZaeddspVV121Rt/bb7+dxx57LN/4xjfy2GOP5bbbbsvcuXNz0EEHrTH2oosuyoIFC8rH6aefXu6rqqrK4MGD06NHjzz66KO55JJLMm7cuFx77bUb9dkAAAAAAGjYGtd1AcOGDcuwYcPW2te6detMmzatWtv//u//5lOf+lTmz5+fLbbYotzesmXLdOnSZa3zTJ06NcuWLcvkyZPTtGnTbL/99pk1a1Yuu+yyjBo1qvYeBgAAAACAj5Q6fxN9Qy1evDgVFRVp06ZNtfYJEyakffv22WWXXXLJJZdkxYoV5b6ZM2dmwIABadq0abltyJAhmTt3bl5//fW13mfp0qWpqqqqdgAAAAAA8PFS52+ib4h33nkn5557bo466qi0atWq3H7GGWdk1113Tbt27fLggw9m7NixWbBgQS677LIkycKFC9OrV69qc3Xu3Lnc17Zt2zXuNX78+Fx44YUb8WkAAAAAAKjvGkyIvnz58hx++OEplUr5/ve/X61vzJgx5c99+/ZN06ZNc9JJJ2X8+PGprKys0f3Gjh1bbd6qqqp07969ZsUDAAAAANAgNYgQfXWA/uKLL2b69OnV3kJfm379+mXFihV54YUX0qdPn3Tp0iWLFi2qNmb1edE+6pWVlTUO4AEAAAAA+Gio93uirw7Qn3322dxzzz1p3779+14za9asNGrUKJ06dUqS9O/fPzNmzMjy5cvLY6ZNm5Y+ffqsdSsXAAAAAABI6sGb6EuWLMlzzz1XPn/++ecza9astGvXLl27ds0XvvCFPPbYY7n99tuzcuXKLFy4MEnSrl27NG3aNDNnzsxDDz2UQYMGpWXLlpk5c2ZGjx6dY445phyQjxgxIhdeeGFGjhyZc889N08++WQuv/zyfO9736uTZwYAAAAAoGGo8xD9kUceyaBBg8rnq/chP+644zJu3Lj8+te/TpLsvPPO1a677777MnDgwFRWVuamm27KuHHjsnTp0vTq1SujR4+utp9569atc/fdd+fUU0/Nbrvtlg4dOuT888/PqFGjNv4DAgAAAADQYNV5iD5w4MCUSqXC/nX1Jcmuu+6aP/3pT+97n759++b+++/f4PoAAAAAAPj4qvd7ogMAAAAAQF0RogMAAAAAQAEhOgAAAAAAFBCiAwAAAABAASE6AAAAAAAUEKIDAAAAAEABIToAAAAAABQQogMAAAAAQAEhOgAAAAAAFBCiAwAAAABAASE6AAAAAAAUEKIDAAAAAEABIToAAAAAABQQogMAAAAAQAEhOgAAAAAAFBCiAwAAAABAASE6AAAAAAAUEKIDAAAAAEABIToAAAAAABQQogMAAAAAQAEhOgAAAAAAFBCiAwAAAABAASE6AAAAAAAUEKIDAAAAAEABIToAAAAAABQQogMAAAAAQAEhOgAAAAAAFBCiAwAAAABAASE6AAAAAAAUEKIDAAAAAEABIToAAAAAABQQogMAAAAAQAEhOgAAAAAAFBCiAwAAAABAASE6AAAAAAAUEKIDAAAAAEABIToAAAAAABQQogMAAAAAQAEhOgAAAAAAFBCiAwAAAABAASE6AAAAAAAUEKIDAAAAAEABIToAAAAAABQQogMAAAAAQAEhOgAAAAAAFGj8QS5+5JFHcsstt2T+/PlZtmxZtb7bbrvtAxUGAAAAAAB1rcZvot90003ZY4898tRTT+UXv/hFli9fnjlz5mT69Olp3bp1bdYIAAAAAAB1osYh+sUXX5zvfe97+c1vfpOmTZvm8ssvz9NPP53DDz88W2yxRW3WCAAAAAAAdaLGIfq8efMyfPjwJEnTpk3z1ltvpaKiIqNHj861115bawUCAAAAAEBdqXGI3rZt27z55ptJks022yxPPvlkkuSNN97I22+/XTvVAQAAAABAHarxF4sOGDAg06ZNy4477pjDDjssZ555ZqZPn55p06Zl3333rc0aAQAAAACgTtQ4RP/f//3fvPPOO0mSr3/962nSpEkefPDBHHrooTnvvPNqrUAAAAAAAKgrNQ7R27VrV/7cqFGjfPWrX62VggAAAAAAoL7YoBC9qqoqrVq1Kn9el9XjAAAAAACgodqgEL1t27ZZsGBBOnXqlDZt2qSiomKNMaVSKRUVFVm5cmWtFQkAAAAAAHVhg0L06dOnl7dxue+++zZKQQAAAAAAUF802pDBe++9dxo3blz+vK5jfc2YMSMHHnhgunXrloqKivzyl7+s1l8qlXL++eena9euadasWfbbb788++yz1ca89tprOfroo9OqVau0adMmI0eOzJIlS6qNmT17dvbaa69suumm6d69eyZOnLghjw4AAAAAwMfQBoXo7zZlypTceuuta7Tfeuutuf7669d7nrfeeis77bRTrrrqqrX2T5w4MVdccUWuueaaPPTQQ2nRokWGDBmSd955pzzm6KOPzpw5czJt2rTcfvvtmTFjRkaNGlXur6qqyuDBg9OjR488+uijueSSSzJu3Lhce+21G/DEAAAAAAB83NQ4RB8/fnw6dOiwRnunTp1y8cUXr/c8w4YNy7e+9a187nOfW6OvVCpl0qRJOe+883LwwQenb9+++fGPf5yXX365/Mb6U089lbvuuiv/93//l379+mXPPffMlVdemZtuuikvv/xykmTq1KlZtmxZJk+enO233z5HHnlkzjjjjFx22WU1e3gAAAAAAD4Wahyiz58/P7169VqjvUePHpk/f/4HKmq1559/PgsXLsx+++1XbmvdunX69euXmTNnJklmzpyZNm3aZPfddy+P2W+//dKoUaM89NBD5TEDBgxI06ZNy2OGDBmSuXPn5vXXX6+VWgEAAAAA+OipcYjeqVOnzJ49e432xx9/PO3bt/9ARa22cOHCJEnnzp2rtXfu3Lnct3DhwnTq1Klaf+PGjdOuXbtqY9Y2x7vv8V5Lly5NVVVVtQMAAAAAgI+XGofoRx11VM4444zcd999WblyZVauXJnp06fnzDPPzJFHHlmbNdaJ8ePHp3Xr1uWje/fudV0SAAAAAAAfshqH6N/85jfTr1+/7LvvvmnWrFmaNWuWwYMHZ5999tmgPdHXpUuXLkmSRYsWVWtftGhRua9Lly555ZVXqvWvWLEir732WrUxa5vj3fd4r7Fjx2bx4sXl4+9///sHfyAAAAAAABqUGofoTZs2zc0335ynn346U6dOzW233ZZ58+Zl8uTJ1fYe/yB69eqVLl265N577y23VVVV5aGHHkr//v2TJP37988bb7yRRx99tDxm+vTpWbVqVfr161ceM2PGjCxfvrw8Ztq0aenTp0/atm271ntXVlamVatW1Q4AAAAAAD5eGn/QCbbeeutsvfXWNb5+yZIlee6558rnzz//fGbNmpV27dpliy22yFlnnZVvfetb2WqrrdKrV6984xvfSLdu3XLIIYckSbbddtsMHTo0J554Yq655posX748p512Wo488sh069YtSTJixIhceOGFGTlyZM4999w8+eSTufzyy/O9733vAz07AAAAAAAfbTUO0VeuXJnrrrsu9957b1555ZWsWrWqWv/06dPXa55HHnkkgwYNKp+PGTMmSXLcccfluuuuyznnnJO33noro0aNyhtvvJE999wzd911VzbddNPyNVOnTs1pp52WfffdN40aNcqhhx6aK664otzfunXr3H333Tn11FOz2267pUOHDjn//PMzatSomj4+AAAAAAAfAxWlUqlUkwtPO+20XHfddRk+fHi6du2aioqKav0ftbe8q6qq0rp16yxevPhju7VLz6/eUdclAA3ICxOG13UJ9Yb1E9gQ1k8AAPhwrG/mW+M30W+66abccsst2X///Ws6BQAAAAAA1Gsf6ItFt9xyy9qsBQAAAAAA6pUah+hnn312Lr/88tRwNxgAAAAAAKj3arydyx//+Mfcd999+e1vf5vtt98+TZo0qdZ/2223feDiAAAAAACgLtU4RG/Tpk0+97nP1WYtAAAAAABQr9Q4RJ8yZUpt1gEAAAAAAPVOjfdET5IVK1bknnvuyQ9+8IO8+eabSZKXX345S5YsqZXiAAAAAACgLm3wm+irVq1Ko0aN8uKLL2bo0KGZP39+li5dms9+9rNp2bJlvvOd72Tp0qW55pprNka9AAAAAADwodmgN9GfeOKJDBgwIEly5plnZvfdd8/rr7+eZs2alcd87nOfy7333lu7VQIAAAAAQB1Y7zfRf/azn+Wiiy7KT37ykyTJ/fffnwcffDBNmzatNq5nz575xz/+UbtVAgAAAABAHVjvN9FXrVqVlStXpqKiotr5e7300ktp2bJl7VUIAAAAAAB1ZL1D9MMPPzw33HBDRo0alST57Gc/m0mTJpX7KyoqsmTJklxwwQXZf//9a71QAAAAAAD4sG3QF4vuuuuuuf/++5Mkl112WYYMGZLtttsu77zzTkaMGJFnn302HTp0yE9/+tONUiwAAAAAAHyYNihET5LGjf9zyeabb57HH388N910U2bPnp0lS5Zk5MiROfroo6t90SgAAAAAADRUGxyiV7u4ceMcc8wxtVULAAAAAADUKzUO0X/84x+vs//YY4+t6dQAAAAAAFAv1DhEP/PMM6udL1++PG+//XaaNm2a5s2bC9EBAAAAAGjwGtX0wtdff73asWTJksydOzd77rmnLxYFAAAAAOAjocYh+tpstdVWmTBhwhpvqQMAAAAAQENUqyF68p8vG3355Zdre1oAAAAAAPjQ1XhP9F//+tfVzkulUhYsWJD//d//zWc+85kPXBgAAAAAANS1GofohxxySLXzioqKdOzYMfvss08uvfTSD1oXAAAAAADUuRqH6KtWrarNOgAAAAAAoN6p9T3RAQAAAADgo6LGb6KPGTNmvcdedtllNb0NAAAAAADUmRqH6H/5y1/yl7/8JcuXL0+fPn2SJM8880w22WST7LrrruVxFRUVH7xKAAAAAACoAzUO0Q888MC0bNky119/fdq2bZskef3113PCCSdkr732ytlnn11rRQIAAAAAQF2o8Z7ol156acaPH18O0JOkbdu2+da3vpVLL720VooDAAAAAIC6VOMQvaqqKv/85z/XaP/nP/+ZN9988wMVBQAAAAAA9UGNQ/TPfe5zOeGEE3LbbbflpZdeyksvvZSf//znGTlyZD7/+c/XZo0AAAAAAFAnarwn+jXXXJP/+Z//yYgRI7J8+fL/TNa4cUaOHJlLLrmk1goEAAAAAIC6UuMQvXnz5rn66qtzySWXZN68eUmS3r17p0WLFrVWHAAAAAAA1KUab+ey2oIFC7JgwYJstdVWadGiRUqlUm3UBQAAAAAAda7GIfqrr76afffdN1tvvXX233//LFiwIEkycuTInH322bVWIAAAAAAA1JUah+ijR49OkyZNMn/+/DRv3rzcfsQRR+Suu+6qleIAAAAAAKAu1XhP9Lvvvju/+93vsvnmm1dr32qrrfLiiy9+4MIAAAAAAKCu1ThEf+utt6q9gb7aa6+9lsrKyg9UFAAAQM+v3lHXJQANyAsThtd1CQB8RNV4O5e99torP/7xj8vnFRUVWbVqVSZOnJhBgwbVSnEAAAAAAFCXavwm+sSJE7PvvvvmkUceybJly3LOOedkzpw5ee211/LAAw/UZo0AAAAAAFAnavwm+g477JBnnnkme+65Zw4++OC89dZb+fznP5+//OUv6d27d23WCAAAAAAAdaJGb6IvX748Q4cOzTXXXJOvf/3rtV0TAAAAAADUCzV6E71JkyaZPXt2bdcCAAAAAAD1So23cznmmGPyox/9qDZrAQAAAACAeqXGXyy6YsWKTJ48Offcc0922223tGjRolr/ZZdd9oGLAwAAAACAurTBIfrf/va39OzZM08++WR23XXXJMkzzzxTbUxFRUXtVAcAAAAAAHVog0P0rbbaKgsWLMh9992XJDniiCNyxRVXpHPnzrVeHAAAAAAA1KUN3hO9VCpVO//tb3+bt956q9YKAgAAAACA+qLGXyy62ntDdQAAAAAA+KjY4BC9oqJijT3P7YEOAAAAAMBH0QbviV4qlXL88censrIySfLOO+/k5JNPTosWLaqNu+2222qnQgAAAAAAqCMbHKIfd9xx1c6POeaYWisGAAAAAADqkw0O0adMmbIx6gAAAAAAgHrnA3+xKAAAAAAAfFQJ0QEAAAAAoIAQHQAAAAAACgjRAQAAAACggBAdAAAAAAAK1PsQvWfPnqmoqFjjOPXUU5MkAwcOXKPv5JNPrjbH/PnzM3z48DRv3jydOnXKV77ylaxYsaIuHgcAAAAAgAakcV0X8H4efvjhrFy5snz+5JNP5rOf/WwOO+ywctuJJ56Yiy66qHzevHnz8ueVK1dm+PDh6dKlSx588MEsWLAgxx57bJo0aZKLL774w3kIAAAAAAAapHofonfs2LHa+YQJE9K7d+/svffe5bbmzZunS5cua73+7rvvzl//+tfcc8896dy5c3beeed885vfzLnnnptx48aladOmG7V+AAAAAAAarnq/ncu7LVu2LD/5yU/ypS99KRUVFeX2qVOnpkOHDtlhhx0yduzYvP322+W+mTNnZscdd0znzp3LbUOGDElVVVXmzJlTeK+lS5emqqqq2gEAAAAAwMdLvX8T/d1++ctf5o033sjxxx9fbhsxYkR69OiRbt26Zfbs2Tn33HMzd+7c3HbbbUmShQsXVgvQk5TPFy5cWHiv8ePH58ILL6z9hwAAAAAAoMFoUCH6j370owwbNizdunUrt40aNar8eccdd0zXrl2z7777Zt68eendu3eN7zV27NiMGTOmfF5VVZXu3bvXeD4AAAAAABqeBhOiv/jii7nnnnvKb5gX6devX5LkueeeS+/evdOlS5f8+c9/rjZm0aJFSVK4j3qSVFZWprKy8gNWDQAAAABAQ9Zg9kSfMmVKOnXqlOHDh69z3KxZs5IkXbt2TZL0798/TzzxRF555ZXymGnTpqVVq1bZbrvtNlq9AAAAAAA0fA3iTfRVq1ZlypQpOe6449K48f8ved68ebnxxhuz//77p3379pk9e3ZGjx6dAQMGpG/fvkmSwYMHZ7vttssXv/jFTJw4MQsXLsx5552XU0891ZvmAAAAAACsU4MI0e+5557Mnz8/X/rSl6q1N23aNPfcc08mTZqUt956K927d8+hhx6a8847rzxmk002ye23355TTjkl/fv3T4sWLXLcccfloosu+rAfAwAAAACABqZBhOiDBw9OqVRao7179+75wx/+8L7X9+jRI3feeefGKA0AAAAAgI+wBrMnOgAAAAAAfNiE6AAAAAAAUECIDgAAAAAABYToAAAAAABQQIgOAAAAAAAFhOgAAAAAAFBAiA4AAAAAAAWE6AAAAAAAUECIDgAAAAAABYToAAAAAABQQIgOAAAAAAAFhOgAAAAAAFBAiA4AAAAAAAWE6AAAAAAAUECIDgAAAAAABYToAAAAAABQQIgOAAAAAAAFhOgAAAAAAFBAiA4AAAAAAAWE6AAAAAAAUECIDgAAAAAABYToAAAAAABQQIgOAAAAAAAFhOgAAAAAAFBAiA4AAAAAAAWE6AAAAAAAUECIDgAAAAAABYToAAAAAABQQIgOAAAAAAAFhOgAAAAAAFBAiA4AAAAAAAWE6AAAAAAAUECIDgAAAAAABYToAAAAAABQQIgOAAAAAAAFhOgAAAAAAFBAiA4AAAAAAAWE6AAAAAAAUECIDgAAAAAABYToAAAAAABQQIgOAAAAAAAFhOgAAAAAAFBAiA4AAAAAAAWE6AAAAAAAUECIDgAAAAAABYToAAAAAABQQIgOAAAAAAAFhOgAAAAAAFBAiA4AAAAAAAWE6AAAAAAAUECIDgAAAAAABYToAAAAAABQQIgOAAAAAAAFhOgAAAAAAFBAiA4AAAAAAAWE6AAAAAAAUKDeh+jjxo1LRUVFtWObbbYp97/zzjs59dRT0759+3ziE5/IoYcemkWLFlWbY/78+Rk+fHiaN2+eTp065Stf+UpWrFjxYT8KAAAAAAANTOO6LmB9bL/99rnnnnvK540b//+yR48enTvuuCO33nprWrdundNOOy2f//zn88ADDyRJVq5cmeHDh6dLly558MEHs2DBghx77LFp0qRJLr744g/9WQAAAAAAaDgaRIjeuHHjdOnSZY32xYsX50c/+lFuvPHG7LPPPkmSKVOmZNttt82f/vSnfPrTn87dd9+dv/71r7nnnnvSuXPn7LzzzvnmN7+Zc889N+PGjUvTpk0/7McBAAAAAKCBqPfbuSTJs88+m27duuWTn/xkjj766MyfPz9J8uijj2b58uXZb7/9ymO32WabbLHFFpk5c2aSZObMmdlxxx3TuXPn8pghQ4akqqoqc+bM+XAfBAAAAACABqXev4ner1+/XHfddenTp08WLFiQCy+8MHvttVeefPLJLFy4ME2bNk2bNm2qXdO5c+csXLgwSbJw4cJqAfrq/tV9RZYuXZqlS5eWz6uqqmrpiQAAAAAAaCjqfYg+bNiw8ue+ffumX79+6dGjR2655ZY0a9Zso913/PjxufDCCzfa/AAAAAAA1H8NYjuXd2vTpk223nrrPPfcc+nSpUuWLVuWN954o9qYRYsWlfdQ79KlSxYtWrRG/+q+ImPHjs3ixYvLx9///vfafRAAAAAAAOq9BheiL1myJPPmzUvXrl2z2267pUmTJrn33nvL/XPnzs38+fPTv3//JEn//v3zxBNP5JVXXimPmTZtWlq1apXtttuu8D6VlZVp1apVtQMAAAAAgI+Xer+dy//8z//kwAMPTI8ePfLyyy/nggsuyCabbJKjjjoqrVu3zsiRIzNmzJi0a9curVq1yumnn57+/fvn05/+dJJk8ODB2W677fLFL34xEydOzMKFC3Peeefl1FNPTWVlZR0/HQAAAAAA9Vm9D9FfeumlHHXUUXn11VfTsWPH7LnnnvnTn/6Ujh07Jkm+973vpVGjRjn00EOzdOnSDBkyJFdffXX5+k022SS33357TjnllPTv3z8tWrTIcccdl4suuqiuHgkAAAAAgAai3ofoN9100zr7N91001x11VW56qqrCsf06NEjd955Z22XBgAAAADAR1yD2xMdAAAAAAA+LEJ0AAAAAAAoIEQHAAAAAIACQnQAAAAAACggRAcAAAAAgAJCdAAAAAAAKCBEBwAAAACAAkJ0AAAAAAAoIEQHAAAAAIACQnQAAAAAACggRAcAAAAAgAJCdAAAAAAAKCBEBwAAAACAAkJ0AAAAAAAoIEQHAAAAAIACQnQAAAAAACggRAcAAAAAgAJCdAAAAAAAKCBEBwAAAACAAkJ0AAAAAAAoIEQHAAAAAIACQnQAAAAAACggRAcAAAAAgAJCdAAAAAAAKCBEBwAAAACAAkJ0AAAAAAAoIEQHAAAAAIACQnQAAAAAACggRAcAAAAAgAJCdAAAAAAAKCBEBwAAAACAAkJ0AAAAAAAoIEQHAAAAAIACQnQAAAAAACggRAcAAAAAgAJCdAAAAAAAKCBEBwAAAACAAkJ0AAAAAAAoIEQHAAAAAIACQnQAAAAAACggRAcAAAAAgAJCdAAAAAAAKCBEBwAAAACAAkJ0AAAAAAAoIEQHAAAAAIACQnQAAAAAACggRAcAAAAAgAJCdAAAAAAAKCBEBwAAAACAAkJ0AAAAAAAoIEQHAAAAAIACQnQAAAAAACggRAcAAAAAgAJCdAAAAAAAKCBEBwAAAACAAkJ0AAAAAAAoIEQHAAAAAIAC9T5EHz9+fP7rv/4rLVu2TKdOnXLIIYdk7ty51cYMHDgwFRUV1Y6TTz652pj58+dn+PDhad68eTp16pSvfOUrWbFixYf5KAAAAAAANDCN67qA9/OHP/whp556av7rv/4rK1asyNe+9rUMHjw4f/3rX9OiRYvyuBNPPDEXXXRR+bx58+blzytXrszw4cPTpUuXPPjgg1mwYEGOPfbYNGnSJBdffPGH+jwAAAAAADQc9T5Ev+uuu6qdX3fddenUqVMeffTRDBgwoNzevHnzdOnSZa1z3H333fnrX/+ae+65J507d87OO++cb37zmzn33HMzbty4NG3adKM+AwAAAAAADVO9387lvRYvXpwkadeuXbX2qVOnpkOHDtlhhx0yduzYvP322+W+mTNnZscdd0znzp3LbUOGDElVVVXmzJmz1vssXbo0VVVV1Q4AAAAAAD5e6v2b6O+2atWqnHXWWfnMZz6THXbYodw+YsSI9OjRI926dcvs2bNz7rnnZu7cubntttuSJAsXLqwWoCcpny9cuHCt9xo/fnwuvPDCjfQkAAAAAAA0BA0qRD/11FPz5JNP5o9//GO19lGjRpU/77jjjunatWv23XffzJs3L717967RvcaOHZsxY8aUz6uqqtK9e/eaFQ4AAAAAQIPUYLZzOe2003L77bfnvvvuy+abb77Osf369UuSPPfcc0mSLl26ZNGiRdXGrD4v2ke9srIyrVq1qnYAAAAAAPDxUu9D9FKplNNOOy2/+MUvMn369PTq1et9r5k1a1aSpGvXrkmS/v3754knnsgrr7xSHjNt2rS0atUq22233UapGwAAAACAhq/eb+dy6qmn5sYbb8yvfvWrtGzZsryHeevWrdOsWbPMmzcvN954Y/bff/+0b98+s2fPzujRozNgwID07ds3STJ48OBst912+eIXv5iJEydm4cKFOe+883LqqaemsrKyLh8PAAAAAIB6rN6/if79738/ixcvzsCBA9O1a9fycfPNNydJmjZtmnvuuSeDBw/ONttsk7PPPjuHHnpofvOb35Tn2GSTTXL77bdnk002Sf/+/XPMMcfk2GOPzUUXXVRXjwUAAAAAQANQ799EL5VK6+zv3r17/vCHP7zvPD169Midd95ZW2UBAAAAAPAxUO/fRAcAAAAAgLoiRAcAAAAAgAJCdAAAAAAAKCBEBwAAAACAAkJ0AAAAAAAoIEQHAAAAAIACQnQAAAAAACggRAcAAAAAgAJCdAAAAAAAKCBEBwAAAACAAo3rugAAAAAAak/Pr95R1yUADcgLE4bXdQn1njfRAQAAAACggBAdAAAAAAAKCNEBAAAAAKCAEB0AAAAAAAoI0QEAAAAAoIAQHQAAAAAACgjRAQAAAACggBAdAAAAAAAKCNEBAAAAAKCAEB0AAAAAAAoI0QEAAAAAoIAQHQAAAAAACgjRAQAAAACggBAdAAAAAAAKCNEBAAAAAKCAEB0AAAAAAAoI0QEAAAAAoIAQHQAAAAAACgjRAQAAAACggBAdAAAAAAAKCNEBAAAAAKCAEB0AAAAAAAoI0QEAAAAAoIAQHQAAAAAACgjRAQAAAACggBAdAAAAAAAKCNEBAAAAAKCAEB0AAAAAAAoI0QEAAAAAoIAQHQAAAAAACgjRAQAAAACggBAdAAAAAAAKCNEBAAAAAKCAEB0AAAAAAAoI0QEAAAAAoIAQHQAAAAAACgjRAQAAAACggBAdAAAAAAAKCNEBAAAAAKCAEB0AAAAAAAoI0QEAAAAAoIAQHQAAAAAACgjRAQAAAACggBAdAAAAAAAKCNEBAAAAAKDAxypEv+qqq9KzZ89suumm6devX/785z/XdUkAAAAAANRjH5sQ/eabb86YMWNywQUX5LHHHstOO+2UIUOG5JVXXqnr0gAAAAAAqKc+NiH6ZZddlhNPPDEnnHBCtttuu1xzzTVp3rx5Jk+eXNelAQAAAABQT30sQvRly5bl0UcfzX777Vdua9SoUfbbb7/MnDmzDisDAAAAAKA+a1zXBXwY/vWvf2XlypXp3LlztfbOnTvn6aefXus1S5cuzdKlS8vnixcvTpJUVVVtvELruVVL367rEoAG5OO8Xr6X9RPYENbP/8/6CWwI6+f/Z/0ENsTHef1c/eylUmmd4z4WIXpNjB8/PhdeeOEa7d27d6+DagAantaT6roCgIbJ+glQM9ZPgJqxfiZvvvlmWrduXdj/sQjRO3TokE022SSLFi2q1r5o0aJ06dJlrdeMHTs2Y8aMKZ+vWrUqr732Wtq3b5+KioqNWi80FFVVVenevXv+/ve/p1WrVnVdDkCDYf0EqDlrKEDNWD9hTaVSKW+++Wa6deu2znEfixC9adOm2W233XLvvffmkEMOSfKfUPzee+/NaaedttZrKisrU1lZWa2tTZs2G7lSaJhatWrlX8AANWD9BKg5ayhAzVg/obp1vYG+2sciRE+SMWPG5Ljjjsvuu++eT33qU5k0aVLeeuutnHDCCXVdGgAAAAAA9dTHJkQ/4ogj8s9//jPnn39+Fi5cmJ133jl33XXXGl82CgAAAAAAq31sQvQkOe200wq3bwE2XGVlZS644II1tj4CYN2snwA1Zw0FqBnrJ9RcRalUKtV1EQAAAAAAUB81qusCAAAAAACgvhKiAwAAAABAASE6AAAAAAAUEKLDR8zxxx+fioqKVFRUpEmTJuncuXM++9nPZvLkyVm1atUHnv+ggw7KFltskU033TRdu3bNF7/4xbz88su1UPnalUqlDBs2LBUVFfnlL3+50e4DsDHXzxdeeCEjR45Mr1690qxZs/Tu3TsXXHBBli1bVkvV/38nnXRSevfunWbNmqVjx445+OCD8/TTT9f6fQBW29i/f662dOnS7LzzzqmoqMisWbNqbd7VBg4cWH6O1cfJJ59c6/cBWG1jr589e/ZcY12bMGFCLVS+ppkzZ2afffZJixYt0qpVqwwYMCD//ve/N8q9oC4I0eEjaOjQoVmwYEFeeOGF/Pa3v82gQYNy5pln5oADDsiKFSs+0NyDBg3KLbfckrlz5+bnP/955s2bly984Qu1VPmaJk2alIqKio02P8C7baz18+mnn86qVavygx/8IHPmzMn3vve9XHPNNfna175Wi9X/x2677ZYpU6bkqaeeyu9+97uUSqUMHjw4K1eurPV7Aay2MX//XO2cc85Jt27damWuIieeeGIWLFhQPiZOnLhR7wewsdfPiy66qNq6dvrpp9dC1dXNnDkzQ4cOzeDBg/PnP/85Dz/8cE477bQ0aiR25COkBHykHHfccaWDDz54jfZ77723lKT0wx/+sNz2+uuvl0aOHFnq0KFDqWXLlqVBgwaVZs2atUH3+9WvflWqqKgoLVu2rHDMpZdeWtphhx1KzZs3L22++ealU045pfTmm2++79x/+ctfSptttllpwYIFpSSlX/ziFxtUG8CG+LDXz4kTJ5Z69eq1zjE1XT/f7fHHHy8lKT333HMbdB3A+vow1s8777yztM0225TmzJlTSlL6y1/+ss7xNVk/995779KZZ575vrUA1JaNvX726NGj9L3vfW+DaqrJ+tmvX7/Seeedt0H3gYbGn4TgY2KfffbJTjvtlNtuu63cdthhh+WVV17Jb3/72zz66KPZdddds+++++a1115brzlfe+21TJ06NXvssUeaNGlSOK5Ro0a54oorMmfOnFx//fWZPn16zjnnnHXO/fbbb2fEiBG56qqr0qVLl/V7SICNYGOsn0myePHitGvXbp1jarJ+vttbb72VKVOmpFevXunevft6XwdQG2pr/Vy0aFFOPPHE3HDDDWnevPl63bum6+fUqVPToUOH7LDDDhk7dmzefvvt9bofQG2qzd8/J0yYkPbt22eXXXbJJZdc8r5vt2/o+vnKK6/koYceSqdOnbLHHnukc+fO2XvvvfPHP/5xwx4a6ru6TvGB2lX0l+xSqVQ64ogjSttuu22pVCqV7r///lKrVq1K77zzTrUxvXv3Lv3gBz9Y5z3OOeecUvPmzUtJSp/+9KdL//rXvzaoxltvvbXUvn37dY4ZNWpUaeTIkeXzeBMd2Mg+jPVztWeffbbUqlWr0rXXXrtBNa7P+lkqlUpXXXVVqUWLFqUkpT59+ngLHdioNub6uWrVqtLQoUNL3/zmN0ulUqn0/PPPr9eb6O+1PuvnD37wg9Jdd91Vmj17duknP/lJabPNNit97nOf26D7AGyIjf3756WXXlq67777So8//njp+9//fqlNmzal0aNHb1CN77d+zpw5s5Sk1K5du9LkyZNLjz32WOmss84qNW3atPTMM89s0L2gPmtcpwk+8KEqlUrl/cUff/zxLFmyJO3bt6825t///nfmzZu3znm+8pWvZOTIkXnxxRdz4YUX5thjj83tt99euHf5Pffck/Hjx+fpp59OVVVVVqxYkXfeeSdvv/32Wt8m+vWvf53p06fnL3/5Sw2fFKB21db6mST/+Mc/MnTo0Bx22GE58cQT1zl2Q9fP1Y4++uh89rOfzYIFC/Ld7343hx9+eB544IFsuumm6/G0ALXng66fV155Zd58882MHTt2g+5bk/Vz1KhR5c877rhjunbtmn333Tfz5s1L7969N+j+AB9Ubfz+OWbMmPLnvn37pmnTpjnppJMyfvz4VFZWrvWaDV0/V38B6kknnZQTTjghSbLLLrvk3nvvzeTJkzN+/PgNe3Cop4To8DHy1FNPpVevXkmSJUuWpGvXrvn973+/xrg2bdqsc54OHTqkQ4cO2XrrrbPtttume/fu+dOf/pT+/fuvMfaFF17IAQcckFNOOSXf/va3065du/zxj3/MyJEjs2zZsrX+S3j69OmZN2/eGnUceuih2WuvvdZaM8DGVFvr58svv5xBgwZljz32yLXXXrvOsTVZP1dr3bp1Wrduna222iqf/vSn07Zt2/ziF7/IUUcd9b7PClCbPuj6OX369MycOXONsGf33XfP0Ucfneuvv36Naz7I+vlu/fr1S5I899xzQnTgQ1dbv3++W79+/bJixYq88MIL6dOnzxr9NVk/u3btmiTZbrvtqrVvu+22mT9//nrXBvWdEB0+JqZPn54nnngio0ePTpLsuuuuWbhwYRo3bpyePXvWeN7Vf3VeunTpWvsfffTRrFq1Kpdeemn5m7lvueWWdc751a9+NV/+8perte2444753ve+lwMPPLDGtQLURG2tn//4xz8yaNCg7LbbbpkyZUp5TSxSk/VzbUqlUkqlUuE6DbCx1Mb6ecUVV+Rb3/pW+fzll1/OkCFDcvPNN5dD7veqrfVz1qxZSf5/QATwYdlY//t91qxZadSoUTp16rTW/pqsnz179ky3bt0yd+7cau3PPPNMhg0bVuNaob4RosNH0NKlS7Nw4cKsXLkyixYtyl133ZXx48fngAMOyLHHHpsk2W+//dK/f/8ccsghmThxYrbeeuu8/PLLueOOO/K5z30uu++++xrzPvTQQ3n44Yez5557pm3btpk3b16+8Y1vpHfv3mt9Cz1JttxyyyxfvjxXXnllDjzwwDzwwAO55ppr1ll/ly5d1vploltssUX5L/EAG8PGWj//8Y9/ZODAgenRo0e++93v5p///Ge5r+jLk2uyfv7tb3/LzTffnMGDB6djx4556aWXMmHChDRr1iz777//B/jJAKzbxlo/t9hii2rnn/jEJ5IkvXv3zuabb77WWmqyfs6bNy833nhj9t9//7Rv3z6zZ8/O6NGjM2DAgPTt27cmPxKA9bKx1s+ZM2fmoYceyqBBg9KyZcvMnDkzo0ePzjHHHJO2bduutZaarJ8VFRX5yle+kgsuuCA77bRTdt5551x//fV5+umn87Of/eyD/4CgvqjLDdmB2nfccceVkpSSlBo3blzq2LFjab/99itNnjy5tHLlympjq6qqSqeffnqpW7dupSZNmpS6d+9eOvroo0vz589f69yzZ88uDRo0qNSuXbtSZWVlqWfPnqWTTz659NJLL62zpssuu6zUtWvXUrNmzUpDhgwp/fjHPy4lKb3++uvr/VzxxaLARrYx188pU6aU537vsS4bun7+4x//KA0bNqzUqVOnUpMmTUqbb755acSIEaWnn366Rj8TgPWxMdfP91rfLxbd0PVz/vz5pQEDBpR/z91yyy1LX/nKV0qLFy9er7oAamJjrp+PPvpoqV+/fqXWrVuXNt1009K2225buvjii9f4ctL3qun/fh8/fnxp8803LzVv3rzUv3//0v33379BPwuo7ypKpVLpw43tAQAAAACgYVj3ZpwAAAAAAPAxJkQHAAAAAIACQnQAAAAAACggRAcAAAAAgAJCdAAAAAAAKCBEBwAAAACAAkJ0AAAAAAAoIEQHAAAAAIACQnQAAPiYGThwYM4666y6LgMAABoEIToAADQgBx54YIYOHbrWvvvvvz8VFRWZPXv2h1wVAAB8dAnRAQCgARk5cmSmTZuWl156aY2+KVOmZPfdd0/fvn03ag0rV67MqlWrNuo9AACgvhCiAwBAA3LAAQekY8eOue6666q1L1myJLfeemsOOeSQHHXUUdlss83SvHnz7LjjjvnpT3+6zjlff/31HHvssWnbtm2aN2+eYcOG5dlnny33X3fddWnTpk1+/etfZ7vttktlZWXmz5+fpUuX5n/+53+y2WabpUWLFunXr19+//vfl6978cUXc+CBB6Zt27Zp0aJFtt9++9x55521+eMAAICNTogOAAANSOPGjXPsscfmuuuuS6lUKrffeuutWblyZY455pjstttuueOOO/Lkk09m1KhR+eIXv5g///nPhXMef/zxeeSRR/LrX/86M2fOTKlUyv7775/ly5eXx7z99tv5zne+k//7v//LnDlz0qlTp5x22mmZOXNmbrrppsyePTuHHXZYhg4dWg7gTz311CxdujQzZszIE088ke985zv5xCc+sfF+OAAAsBFUlN79mzcAAFDvPf3009l2221z3333ZeDAgUmSAQMGpEePHrnhhhvWGH/AAQdkm222yXe/+90k//li0Z133jmTJk3Ks88+m6233joPPPBA9thjjyTJq6++mu7du+f666/PYYcdluuuuy4nnHBCZs2alZ122ilJMn/+/Hzyk5/M/Pnz061bt/K99ttvv3zqU5/KxRdfnL59++bQQw/NBRdcsJF/IgAAsPE0rusCAACADbPNNttkjz32yOTJkzNw4MA899xzuf/++3PRRRdl5cqVufjii3PLLbfkH//4R5YtW5alS5emefPma53rqaeeSuPGjdOvX79yW/v27dOnT5889dRT5bamTZtW22v9iSeeyMqVK7P11ltXm2/p0qVp3759kuSMM87IKaeckrvvvjv77bdfDj300I2+XzsAANQ227kAAEADNHLkyPz85z/Pm2++mSlTpqR3797Ze++9c8kll+Tyyy/Pueeem/vuuy+zZs3KkCFDsmzZsg90v2bNmqWioqJ8vmTJkmyyySZ59NFHM2vWrPLx1FNP5fLLL0+SfPnLX87f/va3fPGLX8wTTzyR3XffPVdeeeUHqgMAAD5sQnQAAGiADj/88DRq1Cg33nhjfvzjH+dLX/pSKioq8sADD+Tggw/OMccck5122imf/OQn88wzzxTOs+2222bFihV56KGHym2vvvpq5s6dm+22267wul122SUrV67MK6+8ki233LLa0aVLl/K47t275+STT85tt92Ws88+Oz/84Q9r5wcAAAAfEiE6AAA0QJ/4xCdyxBFHZOzYsVmwYEGOP/74JMlWW22VadOm5cEHH8xTTz2Vk046KYsWLSqcZ6uttsrBBx+cE088MX/84x/z+OOP55hjjslmm22Wgw8+uPC6rbfeOkcffXSOPfbY3HbbbXn++efz5z//OePHj88dd9yRJDnrrLPyu9/9Ls8//3wee+yx3Hfffdl2221r9ecAAAAbmxAdAAAaqJEjR+b111/PkCFDyl/ued5552XXXXfNkCFDMnDgwHTp0iWHHHLIOueZMmVKdttttxxwwAHp379/SqVS7rzzzjRp0uR9rzv22GNz9tlnp0+fPjnkkEPy8MMPZ4sttkiSrFy5Mqeeemq23XbbDB06NFtvvXWuvvrqWnl2AAD4sFSUSqVSXRcBAAAAAAD1kTfRAQAAAACggBAdAAAAAAAKCNEBAAAAAKCAEB0AAAAAAAoI0QEAAAAAoIAQHQAAAAAACgjRAQAAAACggBAdAAAAAAAKCNEBAAAAAKCAEB0AAAAAAAoI0QEAAAAAoIAQHQAAAAAACvw/gPr7jGUy69YAAAAASUVORK5CYII=\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1500x600 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1500x600 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1500x600 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1500x600 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1500x600 with 1 Axes>"
],
"image/png": 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},
"metadata": {}
}
],
"source": [
"# Discreto\n",
"for coluna in columnsQuantitativosDiscreto:\n",
"# if coluna == \"DATE_BUILD_UNIX\" or coluna == \"DATE_SALE_UNIX\":\n",
"# continue;\n",
"\n",
" minColunm = df[coluna].min()\n",
" maxColunm = df[coluna].max()\n",
"\n",
" # versao ignore pf\n",
" amplitude = maxColunm - minColunm\n",
" stepCount = round( amplitude / 5 )\n",
" if stepCount <= 0:\n",
" stepCount = 1 # Defina um valor mínimo para evitar erros de range()\n",
"\n",
" bins = list(range(int(minColunm), int(maxColunm) + stepCount, stepCount))\n",
" labels = [\"De {} a {}\".format(b, b + stepCount) for b in bins[:-1]]\n",
"\n",
" df[f'FAIXA_{coluna}'] = pd.cut(df[coluna], bins=bins, labels=labels)\n",
"\n",
"# Grafico\n",
"for coluna in columnsQuantitativosDiscreto:\n",
"# if coluna == \"DATE_BUILD_UNIX\" or coluna == \"DATE_SALE_UNIX\":\n",
"# continue;\n",
" frequencias = df[f'FAIXA_{coluna}'].value_counts()\n",
" plt.figure(figsize=(15, 6))\n",
" plt.bar(frequencias.index, frequencias.values)\n",
" plt.xlabel('Valores')\n",
" plt.ylabel('Frequência')\n",
" plt.title(f'Distribuição da {coluna}')\n",
" plt.tight_layout()\n",
" plt.show()\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"id": "wQlnZAC9_BuK",
"outputId": "56c2619e-6b36-4960-a79f-7f22d5da4d7e"
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1000x600 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1000x600 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1000x600 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1000x600 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1000x600 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1000x600 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"# Continuo\n",
"for coluna in columnsQuantitativosContinuo:\n",
" minColunm = df[coluna].min()\n",
" maxColunm = df[coluna].max()\n",
"\n",
" # versao ignore pf\n",
" amplitude = maxColunm - minColunm\n",
" stepCount = round( amplitude / 5 )\n",
"\n",
" if stepCount <= 0:\n",
" stepCount = 1 # Defina um valor mínimo para evitar erros de range()\n",
"\n",
" bins = list(range(int(minColunm), int(maxColunm) + stepCount , stepCount))\n",
" labels = [\"De {} a {}\".format(b, b + stepCount) for b in bins[:-1]]\n",
"\n",
"\n",
" df[f'FAIXA_{coluna}'] = pd.cut(df[coluna], bins=bins, labels=labels)\n",
"\n",
"# Grafico\n",
"for coluna in columnsQuantitativosContinuo:\n",
" frequencias = df[f'FAIXA_{coluna}'].value_counts()\n",
" plt.figure(figsize=(10, 6))\n",
" plt.bar(frequencias.index, frequencias.values)\n",
" plt.xlabel('Valores')\n",
" plt.ylabel('Frequência')\n",
" plt.title(f'Distribuição da {coluna}')\n",
" plt.tight_layout()\n",
" plt.show()\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "_z_C1b08QE0J"
},
"source": [
"## Distribuição Baseado no price"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 446
},
"id": "MEvlY4EhXJv-",
"outputId": "885fe143-f6c7-42b5-fde4-18fc38fcdd16"
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 3000x800 with 1 Axes>"
],
"image/png": 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treino.csv
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