{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Data Science Academy - Python Fundamentos - Capítulo 9\n", "\n", "## Download: http://github.com/dsacademybr" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Análise Exploratória de Dados" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Neste notebook usaremos uma pesquisa recente nos EUA sobre o mercado de trabalho para programadores de software. Nosso objetivo é fazer uma investigação inicial dos dados a fim de detectar problemas com os dados, necessidade de mais variáveis, falhas na organização e necessidades de transformação." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Pesquisa Salarial realizada pelo site https://www.freecodecamp.com/ com programadores de software nos EUA que frequentaram treinamentos Bootcamp." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# Importando os pacotes \n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import pandas as pd\n", "import colorsys\n", "plt.style.use('seaborn-talk')\n", "import warnings\n", "warnings.filterwarnings(\"ignore\")\n", "%matplotlib inline" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# Carregando o dataset\n", "df = pd.read_csv(\"Dados-Pesquisa.csv\", sep = ',', low_memory=False)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " Age AttendedBootcamp BootcampFinish BootcampFullJobAfter \\\n", "0 28.0 0.0 NaN NaN \n", "1 22.0 0.0 NaN NaN \n", "2 19.0 0.0 NaN NaN \n", "3 26.0 0.0 NaN NaN \n", "4 20.0 0.0 NaN NaN \n", "\n", " BootcampLoanYesNo BootcampMonthsAgo BootcampName BootcampPostSalary \\\n", "0 NaN NaN NaN NaN \n", "1 NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN \n", "3 NaN NaN NaN NaN \n", "4 NaN NaN NaN NaN \n", "\n", " BootcampRecommend ChildrenNumber ... ResourceSoloLearn \\\n", "0 NaN NaN ... NaN \n", "1 NaN NaN ... NaN \n", "2 NaN NaN ... NaN \n", "3 NaN NaN ... NaN \n", "4 NaN NaN ... NaN \n", "\n", " ResourceStackOverflow ResourceTreehouse ResourceUdacity ResourceUdemy \\\n", "0 NaN NaN NaN NaN \n", "1 NaN NaN NaN 1.0 \n", "2 NaN NaN NaN NaN \n", "3 NaN NaN NaN NaN \n", "4 NaN NaN NaN NaN \n", "\n", " ResourceW3Schools ResourceYouTube \\\n", "0 NaN NaN \n", "1 NaN NaN \n", "2 NaN NaN \n", "3 NaN NaN \n", "4 NaN NaN \n", "\n", " SchoolDegree SchoolMajor \\\n", "0 some college credit, no degree NaN \n", "1 some college credit, no degree NaN \n", "2 high school diploma or equivalent (GED) NaN \n", "3 bachelor's degree Cinematography And Film \n", "4 some college credit, no degree NaN \n", "\n", " StudentDebtOwe \n", "0 20000.0 \n", "1 NaN \n", "2 NaN \n", "3 7000.0 \n", "4 NaN \n", "\n", "[5 rows x 113 columns]\n" ] } ], "source": [ "print(df.head())" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
AgeAttendedBootcampBootcampFinishBootcampFullJobAfterBootcampLoanYesNoBootcampMonthsAgoBootcampNameBootcampPostSalaryBootcampRecommendChildrenNumber...ResourceSoloLearnResourceStackOverflowResourceTreehouseResourceUdacityResourceUdemyResourceW3SchoolsResourceYouTubeSchoolDegreeSchoolMajorStudentDebtOwe
028.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNsome college credit, no degreeNaN20000.0
122.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaN1.0NaNNaNsome college credit, no degreeNaNNaN
219.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNhigh school diploma or equivalent (GED)NaNNaN
326.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNbachelor's degreeCinematography And Film7000.0
420.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNsome college credit, no degreeNaNNaN
534.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNbachelor's degreeEnglishNaN
623.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNbachelor's degreeComputer ScienceNaN
735.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNmaster's degree (non-professional)EducationNaN
833.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaN1.0NaNNaNNaNbachelor's degreeBusiness AdministrationNaN
933.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNmaster's degree (non-professional)Business Administration180000.0
1057.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNbachelor's degreeComputer ScienceNaN
1123.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNsome college credit, no degreeNaNNaN
1247.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaN1.01.0NaNNaNbachelor's degreeMechanical EngineeringNaN
13NaN0.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNbachelor's degreeBusiness Administration12000.0
1437.00.0NaNNaNNaNNaNNaNNaNNaN1.0...NaNNaNNaN1.0NaNNaNNaNsome college credit, no degreeNaNNaN
1531.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNprofessional degree (MBA, MD, JD, etc.)MathNaN
1627.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaN1.0NaNNaNNaNbachelor's degreeEconomicsNaN
1729.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNbachelor's degreeMusicNaN
1830.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNbachelor's degreeMusicNaN
1930.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaN1.0NaNNaNNaNsome college credit, no degreeNaNNaN
2032.00.0NaNNaNNaNNaNNaNNaNNaN1.0...NaNNaNNaN1.01.0NaNNaNmaster's degree (non-professional)GeologyNaN
2125.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNbachelor's degreeComputer ScienceNaN
2229.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNbachelor's degreeComputer ScienceNaN
2344.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaN1.01.0NaNNaNbachelor's degreePolitical Science50000.0
2421.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaN1.0NaNNaNNaNbachelor's degreeComputer ScienceNaN
2521.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNsome college credit, no degreeNaN40000.0
2628.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNhigh school diploma or equivalent (GED)NaNNaN
2728.00.0NaNNaNNaNNaNNaNNaNNaN2.0...NaNNaN1.0NaNNaNNaNNaNtrade, technical, or vocational trainingNaNNaN
2825.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNbachelor's degreePolitical ScienceNaN
2935.00.0NaNNaNNaNNaNNaNNaNNaN1.0...NaNNaNNaNNaNNaNNaNNaNmaster's degree (non-professional)PhysicsNaN
..................................................................
1559025.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNbachelor's degreeComputer ScienceNaN
1559125.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNprofessional degree (MBA, MD, JD, etc.)Computer Systems Networking and Telecommunicat...NaN
1559243.00.0NaNNaNNaNNaNNaNNaNNaN1.0...NaNNaNNaNNaNNaNNaNNaNhigh school diploma or equivalent (GED)NaNNaN
1559329.01.00.0NaN0.0NaNCamp Code AwayNaN0.0NaN...NaNNaNNaNNaNNaNNaNNaNbachelor's degreeAccountingNaN
1559436.00.0NaNNaNNaNNaNNaNNaNNaN2.0...NaNNaNNaNNaNNaNNaNNaNbachelor's degreeEngineeringNaN
1559530.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNsome high schoolNaNNaN
1559630.00.0NaNNaNNaNNaNNaNNaNNaN2.0...NaNNaNNaNNaNNaNNaNNaNhigh school diploma or equivalent (GED)NaNNaN
1559730.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNprofessional degree (MBA, MD, JD, etc.)LawNaN
1559828.00.0NaNNaNNaNNaNNaNNaNNaN1.0...NaNNaNNaN1.0NaNNaNNaNassociate's degreeComputer and Information Systems Security12000.0
1559937.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNsome college credit, no degreeNaNNaN
1560028.01.01.01.00.04.0Epicodus36000.01.0NaN...NaNNaNNaNNaNNaNNaNNaNbachelor's degreeMarketingNaN
1560125.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaN1.01.0NaNNaNbachelor's degreeCriminal Justice and Safety StudiesNaN
1560222.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaN1.0NaNNaNNaNbachelor's degreeMathematicsNaN
1560333.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNbachelor's degreeComputer ScienceNaN
1560435.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaN1.0NaNNaNsome college credit, no degreeNaNNaN
1560531.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNhigh school diploma or equivalent (GED)NaNNaN
1560643.00.0NaNNaNNaNNaNNaNNaNNaN3.0...NaNNaNNaNNaN1.0NaNNaNbachelor's degreePhysicsNaN
1560725.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaN1.0NaNNaNno high school (secondary school)NaNNaN
1560843.00.0NaNNaNNaNNaNNaNNaNNaN2.0...NaNNaNNaN1.0NaNNaNNaNprofessional degree (MBA, MD, JD, etc.)Electrical EngineeringNaN
1560933.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNbachelor's degreeSoftware Engineering15000.0
1561029.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNmaster's degree (non-professional)Religious Studies26000.0
1561137.00.0NaNNaNNaNNaNNaNNaNNaN1.0...NaNNaNNaN1.0NaNNaNNaNprofessional degree (MBA, MD, JD, etc.)Electrical and Electronics EngineeringNaN
1561245.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaN1.0NaNNaNsome college credit, no degreeNaN30000.0
1561330.00.0NaNNaNNaNNaNNaNNaNNaN2.0...NaNNaNNaNNaN1.0NaNNaNtrade, technical, or vocational trainingNaNNaN
1561447.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNtrade, technical, or vocational trainingNaNNaN
1561539.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaN1.0NaNNaNbachelor's degreeChemistryNaN
1561627.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaN1.0NaNNaNNaNNaNbachelor's degreeElectrical EngineeringNaN
1561737.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNbachelor's degreeChemistryNaN
1561826.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaN1.0NaNNaNmaster's degree (non-professional)MathNaN
1561922.00.0NaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNbachelor's degreeGraphic Design40000.0
\n", "

15620 rows × 113 columns

\n", "
" ], "text/plain": [ " Age AttendedBootcamp BootcampFinish BootcampFullJobAfter \\\n", "0 28.0 0.0 NaN NaN \n", "1 22.0 0.0 NaN NaN \n", "2 19.0 0.0 NaN NaN \n", "3 26.0 0.0 NaN NaN \n", "4 20.0 0.0 NaN NaN \n", "5 34.0 0.0 NaN NaN \n", "6 23.0 0.0 NaN NaN \n", "7 35.0 0.0 NaN NaN \n", "8 33.0 0.0 NaN NaN \n", "9 33.0 0.0 NaN NaN \n", "10 57.0 0.0 NaN NaN \n", "11 23.0 0.0 NaN NaN \n", "12 47.0 0.0 NaN NaN \n", "13 NaN 0.0 NaN NaN \n", "14 37.0 0.0 NaN NaN \n", "15 31.0 0.0 NaN NaN \n", "16 27.0 0.0 NaN NaN \n", "17 29.0 0.0 NaN NaN \n", "18 30.0 0.0 NaN NaN \n", "19 30.0 0.0 NaN NaN \n", "20 32.0 0.0 NaN NaN \n", "21 25.0 0.0 NaN NaN \n", "22 29.0 0.0 NaN NaN \n", "23 44.0 0.0 NaN NaN \n", "24 21.0 0.0 NaN NaN \n", "25 21.0 0.0 NaN NaN \n", "26 28.0 0.0 NaN NaN \n", "27 28.0 0.0 NaN NaN \n", "28 25.0 0.0 NaN NaN \n", "29 35.0 0.0 NaN NaN \n", "... ... ... ... ... \n", "15590 25.0 0.0 NaN NaN \n", "15591 25.0 0.0 NaN NaN \n", "15592 43.0 0.0 NaN NaN \n", "15593 29.0 1.0 0.0 NaN \n", "15594 36.0 0.0 NaN NaN \n", "15595 30.0 0.0 NaN NaN \n", "15596 30.0 0.0 NaN NaN \n", "15597 30.0 0.0 NaN NaN \n", "15598 28.0 0.0 NaN NaN \n", "15599 37.0 0.0 NaN NaN \n", "15600 28.0 1.0 1.0 1.0 \n", "15601 25.0 0.0 NaN NaN \n", "15602 22.0 0.0 NaN NaN \n", "15603 33.0 0.0 NaN NaN \n", "15604 35.0 0.0 NaN NaN \n", "15605 31.0 0.0 NaN NaN \n", "15606 43.0 0.0 NaN NaN \n", "15607 25.0 0.0 NaN NaN \n", "15608 43.0 0.0 NaN NaN \n", "15609 33.0 0.0 NaN NaN \n", "15610 29.0 0.0 NaN NaN \n", "15611 37.0 0.0 NaN NaN \n", "15612 45.0 0.0 NaN NaN \n", "15613 30.0 0.0 NaN NaN \n", "15614 47.0 0.0 NaN NaN \n", "15615 39.0 0.0 NaN NaN \n", "15616 27.0 0.0 NaN NaN \n", "15617 37.0 0.0 NaN NaN \n", "15618 26.0 0.0 NaN NaN \n", "15619 22.0 0.0 NaN NaN \n", "\n", " BootcampLoanYesNo BootcampMonthsAgo BootcampName \\\n", "0 NaN NaN NaN \n", "1 NaN NaN NaN \n", "2 NaN NaN NaN \n", "3 NaN NaN NaN \n", "4 NaN NaN NaN \n", "5 NaN NaN NaN \n", "6 NaN NaN NaN \n", "7 NaN NaN NaN \n", "8 NaN NaN NaN \n", "9 NaN NaN NaN \n", "10 NaN NaN NaN \n", "11 NaN NaN NaN \n", "12 NaN NaN NaN \n", "13 NaN NaN NaN \n", "14 NaN NaN NaN \n", "15 NaN NaN NaN \n", "16 NaN NaN NaN \n", "17 NaN NaN NaN \n", "18 NaN NaN NaN \n", "19 NaN NaN NaN \n", "20 NaN NaN NaN \n", "21 NaN NaN NaN \n", "22 NaN NaN NaN \n", "23 NaN NaN NaN \n", "24 NaN NaN NaN \n", "25 NaN NaN NaN \n", "26 NaN NaN NaN \n", "27 NaN NaN NaN \n", "28 NaN NaN NaN \n", "29 NaN NaN NaN \n", "... ... ... ... \n", "15590 NaN NaN NaN \n", "15591 NaN NaN NaN \n", "15592 NaN NaN NaN \n", "15593 0.0 NaN Camp Code Away \n", "15594 NaN NaN NaN \n", "15595 NaN NaN NaN \n", "15596 NaN NaN NaN \n", "15597 NaN NaN NaN \n", "15598 NaN NaN NaN \n", "15599 NaN NaN NaN \n", "15600 0.0 4.0 Epicodus \n", "15601 NaN NaN NaN \n", "15602 NaN NaN NaN \n", "15603 NaN NaN NaN \n", "15604 NaN NaN NaN \n", "15605 NaN NaN NaN \n", "15606 NaN NaN NaN \n", "15607 NaN NaN NaN \n", "15608 NaN NaN NaN \n", "15609 NaN NaN NaN \n", "15610 NaN NaN NaN \n", "15611 NaN NaN NaN \n", "15612 NaN NaN NaN \n", "15613 NaN NaN NaN \n", "15614 NaN NaN NaN \n", "15615 NaN NaN NaN \n", "15616 NaN NaN NaN \n", "15617 NaN NaN NaN \n", "15618 NaN NaN NaN \n", "15619 NaN NaN NaN \n", "\n", " BootcampPostSalary BootcampRecommend ChildrenNumber ... \\\n", "0 NaN NaN NaN ... \n", "1 NaN NaN NaN ... \n", "2 NaN NaN NaN ... \n", "3 NaN NaN NaN ... \n", "4 NaN NaN NaN ... \n", "5 NaN NaN NaN ... \n", "6 NaN NaN NaN ... \n", "7 NaN NaN NaN ... \n", "8 NaN NaN NaN ... \n", "9 NaN NaN NaN ... \n", "10 NaN NaN NaN ... \n", "11 NaN NaN NaN ... \n", "12 NaN NaN NaN ... \n", "13 NaN NaN NaN ... \n", "14 NaN NaN 1.0 ... \n", "15 NaN NaN NaN ... \n", "16 NaN NaN NaN ... \n", "17 NaN NaN NaN ... \n", "18 NaN NaN NaN ... \n", "19 NaN NaN NaN ... \n", "20 NaN NaN 1.0 ... \n", "21 NaN NaN NaN ... \n", "22 NaN NaN NaN ... \n", "23 NaN NaN NaN ... \n", "24 NaN NaN NaN ... \n", "25 NaN NaN NaN ... \n", "26 NaN NaN NaN ... \n", "27 NaN NaN 2.0 ... \n", "28 NaN NaN NaN ... \n", "29 NaN NaN 1.0 ... \n", "... ... ... ... ... \n", "15590 NaN NaN NaN ... \n", "15591 NaN NaN NaN ... \n", "15592 NaN NaN 1.0 ... \n", "15593 NaN 0.0 NaN ... \n", "15594 NaN NaN 2.0 ... \n", "15595 NaN NaN NaN ... \n", "15596 NaN NaN 2.0 ... \n", "15597 NaN NaN NaN ... \n", "15598 NaN NaN 1.0 ... \n", "15599 NaN NaN NaN ... \n", "15600 36000.0 1.0 NaN ... \n", "15601 NaN NaN NaN ... \n", "15602 NaN NaN NaN ... \n", "15603 NaN NaN NaN ... \n", "15604 NaN NaN NaN ... \n", "15605 NaN NaN NaN ... \n", "15606 NaN NaN 3.0 ... \n", "15607 NaN NaN NaN ... \n", "15608 NaN NaN 2.0 ... \n", "15609 NaN NaN NaN ... \n", "15610 NaN NaN NaN ... \n", "15611 NaN NaN 1.0 ... \n", "15612 NaN NaN NaN ... \n", "15613 NaN NaN 2.0 ... \n", "15614 NaN NaN NaN ... \n", "15615 NaN NaN NaN ... \n", "15616 NaN NaN NaN ... \n", "15617 NaN NaN NaN ... \n", "15618 NaN NaN NaN ... \n", "15619 NaN NaN NaN ... \n", "\n", " ResourceSoloLearn ResourceStackOverflow ResourceTreehouse \\\n", "0 NaN NaN NaN \n", "1 NaN NaN NaN \n", "2 NaN NaN NaN \n", "3 NaN NaN NaN \n", "4 NaN NaN NaN \n", "5 NaN NaN NaN \n", "6 NaN NaN NaN \n", "7 NaN NaN NaN \n", "8 NaN NaN NaN \n", "9 NaN NaN NaN \n", "10 NaN NaN NaN \n", "11 NaN NaN NaN \n", "12 NaN NaN NaN \n", "13 NaN NaN NaN \n", "14 NaN NaN NaN \n", "15 NaN NaN NaN \n", "16 NaN NaN NaN \n", "17 NaN NaN NaN \n", "18 NaN NaN NaN \n", "19 NaN NaN NaN \n", "20 NaN NaN NaN \n", "21 NaN NaN NaN \n", "22 NaN NaN NaN \n", "23 NaN NaN NaN \n", "24 NaN NaN NaN \n", "25 NaN NaN NaN \n", "26 NaN NaN NaN \n", "27 NaN NaN 1.0 \n", "28 NaN NaN NaN \n", "29 NaN NaN NaN \n", "... ... ... ... \n", "15590 NaN NaN NaN \n", "15591 NaN NaN NaN \n", "15592 NaN NaN NaN \n", "15593 NaN NaN NaN \n", "15594 NaN NaN NaN \n", "15595 NaN NaN NaN \n", "15596 NaN NaN NaN \n", "15597 NaN NaN NaN \n", "15598 NaN NaN NaN \n", "15599 NaN NaN NaN \n", "15600 NaN NaN NaN \n", "15601 NaN NaN NaN \n", "15602 NaN NaN NaN \n", "15603 NaN NaN NaN \n", "15604 NaN NaN NaN \n", "15605 NaN NaN NaN \n", "15606 NaN NaN NaN \n", "15607 NaN NaN NaN \n", "15608 NaN NaN NaN \n", "15609 NaN NaN NaN \n", "15610 NaN NaN NaN \n", "15611 NaN NaN NaN \n", "15612 NaN NaN NaN \n", "15613 NaN NaN NaN \n", "15614 NaN NaN NaN \n", "15615 NaN NaN NaN \n", "15616 NaN NaN 1.0 \n", "15617 NaN NaN NaN \n", "15618 NaN NaN NaN \n", "15619 NaN NaN NaN \n", "\n", " ResourceUdacity ResourceUdemy ResourceW3Schools ResourceYouTube \\\n", "0 NaN NaN NaN NaN \n", "1 NaN 1.0 NaN NaN \n", "2 NaN NaN NaN NaN \n", "3 NaN NaN NaN NaN \n", "4 NaN NaN NaN NaN \n", "5 NaN NaN NaN NaN \n", "6 NaN NaN NaN NaN \n", "7 NaN NaN NaN NaN \n", "8 1.0 NaN NaN NaN \n", "9 NaN NaN NaN NaN \n", "10 NaN NaN NaN NaN \n", "11 NaN NaN NaN NaN \n", "12 1.0 1.0 NaN NaN \n", "13 NaN NaN NaN NaN \n", "14 1.0 NaN NaN NaN \n", "15 NaN NaN NaN NaN \n", "16 1.0 NaN NaN NaN \n", "17 NaN NaN NaN NaN \n", "18 NaN NaN NaN NaN \n", "19 1.0 NaN NaN NaN \n", "20 1.0 1.0 NaN NaN \n", "21 NaN NaN NaN NaN \n", "22 NaN NaN NaN NaN \n", "23 1.0 1.0 NaN NaN \n", "24 1.0 NaN NaN NaN \n", "25 NaN NaN NaN NaN \n", "26 NaN NaN NaN NaN \n", "27 NaN NaN NaN NaN \n", "28 NaN NaN NaN NaN \n", "29 NaN NaN NaN NaN \n", "... ... ... ... ... \n", "15590 NaN NaN NaN NaN \n", "15591 NaN NaN NaN NaN \n", "15592 NaN NaN NaN NaN \n", "15593 NaN NaN NaN NaN \n", "15594 NaN NaN NaN NaN \n", "15595 NaN NaN NaN NaN \n", "15596 NaN NaN NaN NaN \n", "15597 NaN NaN NaN NaN \n", "15598 1.0 NaN NaN NaN \n", "15599 NaN NaN NaN NaN \n", "15600 NaN NaN NaN NaN \n", "15601 1.0 1.0 NaN NaN \n", "15602 1.0 NaN NaN NaN \n", "15603 NaN NaN NaN NaN \n", "15604 NaN 1.0 NaN NaN \n", "15605 NaN NaN NaN NaN \n", "15606 NaN 1.0 NaN NaN \n", "15607 NaN 1.0 NaN NaN \n", "15608 1.0 NaN NaN NaN \n", "15609 NaN NaN NaN NaN \n", "15610 NaN NaN NaN NaN \n", "15611 1.0 NaN NaN NaN \n", "15612 NaN 1.0 NaN NaN \n", "15613 NaN 1.0 NaN NaN \n", "15614 NaN NaN NaN NaN \n", "15615 NaN 1.0 NaN NaN \n", "15616 NaN NaN NaN NaN \n", "15617 NaN NaN NaN NaN \n", "15618 NaN 1.0 NaN NaN \n", "15619 NaN NaN NaN NaN \n", "\n", " SchoolDegree \\\n", "0 some college credit, no degree \n", "1 some college credit, no degree \n", "2 high school diploma or equivalent (GED) \n", "3 bachelor's degree \n", "4 some college credit, no degree \n", "5 bachelor's degree \n", "6 bachelor's degree \n", "7 master's degree (non-professional) \n", "8 bachelor's degree \n", "9 master's degree (non-professional) \n", "10 bachelor's degree \n", "11 some college credit, no degree \n", "12 bachelor's degree \n", "13 bachelor's degree \n", "14 some college credit, no degree \n", "15 professional degree (MBA, MD, JD, etc.) \n", "16 bachelor's degree \n", "17 bachelor's degree \n", "18 bachelor's degree \n", "19 some college credit, no degree \n", "20 master's degree (non-professional) \n", "21 bachelor's degree \n", "22 bachelor's degree \n", "23 bachelor's degree \n", "24 bachelor's degree \n", "25 some college credit, no degree \n", "26 high school diploma or equivalent (GED) \n", "27 trade, technical, or vocational training \n", "28 bachelor's degree \n", "29 master's degree (non-professional) \n", "... ... \n", "15590 bachelor's degree \n", "15591 professional degree (MBA, MD, JD, etc.) \n", "15592 high school diploma or equivalent (GED) \n", "15593 bachelor's degree \n", "15594 bachelor's degree \n", "15595 some high school \n", "15596 high school diploma or equivalent (GED) \n", "15597 professional degree (MBA, MD, JD, etc.) \n", "15598 associate's degree \n", "15599 some college credit, no degree \n", "15600 bachelor's degree \n", "15601 bachelor's degree \n", "15602 bachelor's degree \n", "15603 bachelor's degree \n", "15604 some college credit, no degree \n", "15605 high school diploma or equivalent (GED) \n", "15606 bachelor's degree \n", "15607 no high school (secondary school) \n", "15608 professional degree (MBA, MD, JD, etc.) \n", "15609 bachelor's degree \n", "15610 master's degree (non-professional) \n", "15611 professional degree (MBA, MD, JD, etc.) \n", "15612 some college credit, no degree \n", "15613 trade, technical, or vocational training \n", "15614 trade, technical, or vocational training \n", "15615 bachelor's degree \n", "15616 bachelor's degree \n", "15617 bachelor's degree \n", "15618 master's degree (non-professional) \n", "15619 bachelor's degree \n", "\n", " SchoolMajor StudentDebtOwe \n", "0 NaN 20000.0 \n", "1 NaN NaN \n", "2 NaN NaN \n", "3 Cinematography And Film 7000.0 \n", "4 NaN NaN \n", "5 English NaN \n", "6 Computer Science NaN \n", "7 Education NaN \n", "8 Business Administration NaN \n", "9 Business Administration 180000.0 \n", "10 Computer Science NaN \n", "11 NaN NaN \n", "12 Mechanical Engineering NaN \n", "13 Business Administration 12000.0 \n", "14 NaN NaN \n", "15 Math NaN \n", "16 Economics NaN \n", "17 Music NaN \n", "18 Music NaN \n", "19 NaN NaN \n", "20 Geology NaN \n", "21 Computer Science NaN \n", "22 Computer Science NaN \n", "23 Political Science 50000.0 \n", "24 Computer Science NaN \n", "25 NaN 40000.0 \n", "26 NaN NaN \n", "27 NaN NaN \n", "28 Political Science NaN \n", "29 Physics NaN \n", "... ... ... \n", "15590 Computer Science NaN \n", "15591 Computer Systems Networking and Telecommunicat... NaN \n", "15592 NaN NaN \n", "15593 Accounting NaN \n", "15594 Engineering NaN \n", "15595 NaN NaN \n", "15596 NaN NaN \n", "15597 Law NaN \n", "15598 Computer and Information Systems Security 12000.0 \n", "15599 NaN NaN \n", "15600 Marketing NaN \n", "15601 Criminal Justice and Safety Studies NaN \n", "15602 Mathematics NaN \n", "15603 Computer Science NaN \n", "15604 NaN NaN \n", "15605 NaN NaN \n", "15606 Physics NaN \n", "15607 NaN NaN \n", "15608 Electrical Engineering NaN \n", "15609 Software Engineering 15000.0 \n", "15610 Religious Studies 26000.0 \n", "15611 Electrical and Electronics Engineering NaN \n", "15612 NaN 30000.0 \n", "15613 NaN NaN \n", "15614 NaN NaN \n", "15615 Chemistry NaN \n", "15616 Electrical Engineering NaN \n", "15617 Chemistry NaN \n", "15618 Math NaN \n", "15619 Graphic Design 40000.0 \n", "\n", "[15620 rows x 113 columns]" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " Age AttendedBootcamp BootcampFinish BootcampFullJobAfter \\\n", "count 13613.000000 15380.000000 933.000000 635.000000 \n", "mean 29.175421 0.061964 0.689175 0.584252 \n", "std 9.017716 0.241097 0.463080 0.493239 \n", "min 10.000000 0.000000 0.000000 0.000000 \n", "25% 23.000000 0.000000 0.000000 0.000000 \n", "50% 27.000000 0.000000 1.000000 1.000000 \n", "75% 33.000000 0.000000 1.000000 1.000000 \n", "max 86.000000 1.000000 1.000000 1.000000 \n", "\n", " BootcampLoanYesNo BootcampMonthsAgo BootcampPostSalary \\\n", "count 934.000000 631.000000 330.000000 \n", "mean 0.332976 9.055468 63740.506061 \n", "std 0.471531 12.968035 26347.200265 \n", "min 0.000000 0.000000 6000.000000 \n", "25% 0.000000 3.000000 50000.000000 \n", "50% 0.000000 6.000000 60000.000000 \n", "75% 1.000000 12.000000 77000.000000 \n", "max 1.000000 220.000000 200000.000000 \n", "\n", " BootcampRecommend ChildrenNumber CodeEventBootcamp ... \\\n", "count 937.000000 2554.000000 42.0 ... \n", "mean 0.785486 1.896241 1.0 ... \n", "std 0.410704 1.115975 0.0 ... \n", "min 0.000000 0.000000 1.0 ... \n", "25% 1.000000 1.000000 1.0 ... \n", "50% 1.000000 2.000000 1.0 ... \n", "75% 1.000000 2.000000 1.0 ... \n", "max 1.000000 18.000000 1.0 ... \n", "\n", " ResourceReddit ResourceSkillCrush ResourceSoloLearn \\\n", "count 29.0 36.0 30.0 \n", "mean 1.0 1.0 1.0 \n", "std 0.0 0.0 0.0 \n", "min 1.0 1.0 1.0 \n", "25% 1.0 1.0 1.0 \n", "50% 1.0 1.0 1.0 \n", "75% 1.0 1.0 1.0 \n", "max 1.0 1.0 1.0 \n", "\n", " ResourceStackOverflow ResourceTreehouse ResourceUdacity \\\n", "count 191.0 422.0 3306.0 \n", "mean 1.0 1.0 1.0 \n", "std 0.0 0.0 0.0 \n", "min 1.0 1.0 1.0 \n", "25% 1.0 1.0 1.0 \n", "50% 1.0 1.0 1.0 \n", "75% 1.0 1.0 1.0 \n", "max 1.0 1.0 1.0 \n", "\n", " ResourceUdemy ResourceW3Schools ResourceYouTube StudentDebtOwe \n", "count 4130.0 121.0 121.0 3514.000000 \n", "mean 1.0 1.0 1.0 34556.143711 \n", "std 0.0 0.0 0.0 54423.139781 \n", "min 1.0 1.0 1.0 0.000000 \n", "25% 1.0 1.0 1.0 10000.000000 \n", "50% 1.0 1.0 1.0 20000.000000 \n", "75% 1.0 1.0 1.0 40000.000000 \n", "max 1.0 1.0 1.0 1000000.000000 \n", "\n", "[8 rows x 85 columns]\n" ] } ], "source": [ "print(df.describe())" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['Age',\n", " 'AttendedBootcamp',\n", " 'BootcampFinish',\n", " 'BootcampFullJobAfter',\n", " 'BootcampLoanYesNo',\n", " 'BootcampMonthsAgo',\n", " 'BootcampName',\n", " 'BootcampPostSalary',\n", " 'BootcampRecommend',\n", " 'ChildrenNumber',\n", " 'CityPopulation',\n", " 'CodeEventBootcamp',\n", " 'CodeEventCoffee',\n", " 'CodeEventConferences',\n", " 'CodeEventDjangoGirls',\n", " 'CodeEventGameJam',\n", " 'CodeEventGirlDev',\n", " 'CodeEventHackathons',\n", " 'CodeEventMeetup',\n", " 'CodeEventNodeSchool',\n", " 'CodeEventNone',\n", " 'CodeEventOther',\n", " 'CodeEventRailsBridge',\n", " 'CodeEventRailsGirls',\n", " 'CodeEventStartUpWknd',\n", " 'CodeEventWomenCode',\n", " 'CodeEventWorkshop',\n", " 'CommuteTime',\n", " 'CountryCitizen',\n", " 'CountryLive',\n", " 'EmploymentField',\n", " 'EmploymentFieldOther',\n", " 'EmploymentStatus',\n", " 'EmploymentStatusOther',\n", " 'ExpectedEarning',\n", " 'FinanciallySupporting',\n", " 'Gender',\n", " 'HasChildren',\n", " 'HasDebt',\n", " 'HasFinancialDependents',\n", " 'HasHighSpdInternet',\n", " 'HasHomeMortgage',\n", " 'HasServedInMilitary',\n", " 'HasStudentDebt',\n", " 'HomeMortgageOwe',\n", " 'HoursLearning',\n", " 'ID.x',\n", " 'ID.y',\n", " 'Income',\n", " 'IsEthnicMinority',\n", " 'IsReceiveDiabilitiesBenefits',\n", " 'IsSoftwareDev',\n", " 'IsUnderEmployed',\n", " 'JobApplyWhen',\n", " 'JobPref',\n", " 'JobRelocateYesNo',\n", " 'JobRoleInterest',\n", " 'JobRoleInterestOther',\n", " 'JobWherePref',\n", " 'LanguageAtHome',\n", " 'MaritalStatus',\n", " 'MoneyForLearning',\n", " 'MonthsProgramming',\n", " 'NetworkID',\n", " 'Part1EndTime',\n", " 'Part1StartTime',\n", " 'Part2EndTime',\n", " 'Part2StartTime',\n", " 'PodcastChangeLog',\n", " 'PodcastCodeNewbie',\n", " 'PodcastCodingBlocks',\n", " 'PodcastDeveloperTea',\n", " 'PodcastDotNetRocks',\n", " 'PodcastHanselminutes',\n", " 'PodcastJSJabber',\n", " 'PodcastJsAir',\n", " 'PodcastNone',\n", " 'PodcastOther',\n", " 'PodcastProgrammingThrowDown',\n", " 'PodcastRubyRogues',\n", " 'PodcastSEDaily',\n", " 'PodcastShopTalk',\n", " 'PodcastTalkPython',\n", " 'PodcastWebAhead',\n", " 'ResourceBlogs',\n", " 'ResourceBooks',\n", " 'ResourceCodeWars',\n", " 'ResourceCodecademy',\n", " 'ResourceCoursera',\n", " 'ResourceDevTips',\n", " 'ResourceEdX',\n", " 'ResourceEggHead',\n", " 'ResourceFCC',\n", " 'ResourceGoogle',\n", " 'ResourceHackerRank',\n", " 'ResourceKhanAcademy',\n", " 'ResourceLynda',\n", " 'ResourceMDN',\n", " 'ResourceOdinProj',\n", " 'ResourceOther',\n", " 'ResourcePluralSight',\n", " 'ResourceReddit',\n", " 'ResourceSkillCrush',\n", " 'ResourceSoloLearn',\n", " 'ResourceStackOverflow',\n", " 'ResourceTreehouse',\n", " 'ResourceUdacity',\n", " 'ResourceUdemy',\n", " 'ResourceW3Schools',\n", " 'ResourceYouTube',\n", " 'SchoolDegree',\n", " 'SchoolMajor',\n", " 'StudentDebtOwe']" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Lista todas as colunas\n", "list(df)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Distribuição de Idade" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Qual a distribuição de idade dos participantes da pesquisa?\n", "# A maioria dos profissionais que trabalham como programadores de \n", "# software estão na faixa de idade entre 20 e 30 anos, sendo 25 anos \n", "# a idade mais frequente.\n", "\n", "# Gerando um histograma\n", "df.Age.hist(bins = 60)\n", "plt.xlabel(\"Idade\")\n", "plt.ylabel(\"Número de Profissionais\")\n", "plt.title(\"Distribuição de Idade\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Distribuição de Sexo" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Qual é a distribuição de sexo dos participantes da pesquisa?\n", "# A grande maioria dos programadores é do sexo masculino\n", "\n", "# Definindo a quantidade\n", "labels = df.Gender.value_counts().index\n", "num = len(df.EmploymentField.value_counts().index)\n", "\n", "# Criando a lista de cores\n", "listaHSV = [(x*1.0/num, 0.5, 0.5) for x in range(num)]\n", "listaRGB = list(map(lambda x: colorsys.hsv_to_rgb(*x), listaHSV))\n", "\n", "# Gráfico de Pizza\n", "fatias, texto = plt.pie(df.Gender.value_counts(), colors = listaRGB, startangle = 90)\n", "plt.axes().set_aspect('equal', 'datalim')\n", "plt.legend(fatias, labels, bbox_to_anchor = (1.05,1))\n", "plt.title(\"Sexo\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Distribuição de Interesses" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Quais sãos os principais interesses dos participantes da pesquisa?\n", "# O principal interesse profissional dos programadores é o desenvolvimento web (Full-Stack, Front-End e Back-End), \n", "# seguido pela área de Data Science.\n", "\n", "# Definindo a quantidade\n", "num = len(df.JobRoleInterest.value_counts().index)\n", "\n", "# Criando a lista de cores\n", "listaHSV = [(x*1.0/num, 0.5, 0.5) for x in range(num)]\n", "listaRGB = list(map(lambda x: colorsys.hsv_to_rgb(*x), listaHSV))\n", "labels = df.JobRoleInterest.value_counts().index\n", "colors = ['OliveDrab', 'Orange', 'OrangeRed', 'DarkCyan', 'Salmon', 'Sienna', 'Maroon', 'LightSlateGrey', 'DimGray']\n", "\n", "# Gráfico de Pizza\n", "fatias, texto = plt.pie(df.JobRoleInterest.value_counts(), colors = listaRGB, startangle = 90)\n", "plt.axes().set_aspect('equal', 'datalim')\n", "plt.legend(fatias, labels, bbox_to_anchor = (1.25, 1))\n", "plt.title(\"Interesse Profissional\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Distribuição de Empregabilidade" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Quais as áreas de negócio em que os participantes da pesquisa trabalham?\n", "# A maioria dos programadores trabalha na área de desenvolvimento de \n", "# softwares e TI, mas outras áreas como finanças e saúde também são \n", "# significativas.\n", "\n", "# Definindo a quantidade\n", "num = len(df.EmploymentField.value_counts().index)\n", "\n", "# Criando a lista de cores\n", "listaHSV = [(x*1.0/num, 0.5, 0.5) for x in range(num)]\n", "listaRGB = list(map(lambda x: colorsys.hsv_to_rgb(*x), listaHSV))\n", "labels = df.EmploymentField.value_counts().index\n", "\n", "# Gráfico de Pizza\n", "fatias, texto = plt.pie(df.EmploymentField.value_counts(), colors = listaRGB, startangle = 90)\n", "plt.axes().set_aspect('equal', 'datalim')\n", "plt.legend(fatias, labels, bbox_to_anchor = (1.3, 1))\n", "plt.title(\"Área de trabalho Atual\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "## Preferências de Trabalho por Idade" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Quais são as preferências de trabalho por idade?\n", "# Perceba que à medida que a idade aumenta, o interesse por trabalho \n", "# freelance também aumenta, sendo o modelo preferido por profissionais \n", "# acima de 60 anos. Profissionais mais jovens preferem trabalhar em \n", "# Startups ou no seu próprio negócio. Profissionais entre 20 e 50 anos \n", "# preferem trabalhar em empresas de tamanho médio.\n", "\n", "# Agrupando os dados\n", "df_ageranges = df.copy()\n", "bins=[0, 20, 30, 40, 50, 60, 100]\n", "\n", "df_ageranges['AgeRanges'] = pd.cut(df_ageranges['Age'], \n", " bins, \n", " labels=[\"< 20\", \"20-30\", \"30-40\", \"40-50\", \"50-60\", \"< 60\"]) \n", "\n", "df2 = pd.crosstab(df_ageranges.AgeRanges, \n", " df_ageranges.JobPref).apply(lambda r: r/r.sum(), axis=1)\n", "\n", "# Definindo a quantidade\n", "num = len(df_ageranges.AgeRanges.value_counts().index)\n", "\n", "# Criando a lista de cores\n", "listaHSV = [(x*1.0/num, 0.5, 0.5) for x in range(num)]\n", "listaRGB = list(map(lambda x: colorsys.hsv_to_rgb(*x), listaHSV))\n", "\n", "# Gráfico de Barras (Stacked)\n", "ax1 = df2.plot(kind = \"bar\", stacked = True, color = listaRGB, title = \"Preferência de Trabalho por Idade\")\n", "lines, labels = ax1.get_legend_handles_labels()\n", "ax1.legend(lines, labels, bbox_to_anchor = (1.51, 1))" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Help on function crosstab in module pandas.core.reshape.pivot:\n", "\n", "crosstab(index, columns, values=None, rownames=None, colnames=None, aggfunc=None, margins=False, margins_name='All', dropna=True, normalize=False)\n", " Compute a simple cross-tabulation of two (or more) factors. By default\n", " computes a frequency table of the factors unless an array of values and an\n", " aggregation function are passed\n", " \n", " Parameters\n", " ----------\n", " index : array-like, Series, or list of arrays/Series\n", " Values to group by in the rows\n", " columns : array-like, Series, or list of arrays/Series\n", " Values to group by in the columns\n", " values : array-like, optional\n", " Array of values to aggregate according to the factors.\n", " Requires `aggfunc` be specified.\n", " aggfunc : function, optional\n", " If specified, requires `values` be specified as well\n", " rownames : sequence, default None\n", " If passed, must match number of row arrays passed\n", " colnames : sequence, default None\n", " If passed, must match number of column arrays passed\n", " margins : boolean, default False\n", " Add row/column margins (subtotals)\n", " margins_name : string, default 'All'\n", " Name of the row / column that will contain the totals\n", " when margins is True.\n", " \n", " .. versionadded:: 0.21.0\n", " \n", " dropna : boolean, default True\n", " Do not include columns whose entries are all NaN\n", " normalize : boolean, {'all', 'index', 'columns'}, or {0,1}, default False\n", " Normalize by dividing all values by the sum of values.\n", " \n", " - If passed 'all' or `True`, will normalize over all values.\n", " - If passed 'index' will normalize over each row.\n", " - If passed 'columns' will normalize over each column.\n", " - If margins is `True`, will also normalize margin values.\n", " \n", " .. versionadded:: 0.18.1\n", " \n", " \n", " Notes\n", " -----\n", " Any Series passed will have their name attributes used unless row or column\n", " names for the cross-tabulation are specified.\n", " \n", " Any input passed containing Categorical data will have **all** of its\n", " categories included in the cross-tabulation, even if the actual data does\n", " not contain any instances of a particular category.\n", " \n", " In the event that there aren't overlapping indexes an empty DataFrame will\n", " be returned.\n", " \n", " Examples\n", " --------\n", " >>> a = np.array([\"foo\", \"foo\", \"foo\", \"foo\", \"bar\", \"bar\",\n", " ... \"bar\", \"bar\", \"foo\", \"foo\", \"foo\"], dtype=object)\n", " >>> b = np.array([\"one\", \"one\", \"one\", \"two\", \"one\", \"one\",\n", " ... \"one\", \"two\", \"two\", \"two\", \"one\"], dtype=object)\n", " >>> c = np.array([\"dull\", \"dull\", \"shiny\", \"dull\", \"dull\", \"shiny\",\n", " ... \"shiny\", \"dull\", \"shiny\", \"shiny\", \"shiny\"],\n", " ... dtype=object)\n", " \n", " >>> pd.crosstab(a, [b, c], rownames=['a'], colnames=['b', 'c'])\n", " ... # doctest: +NORMALIZE_WHITESPACE\n", " b one two\n", " c dull shiny dull shiny\n", " a\n", " bar 1 2 1 0\n", " foo 2 2 1 2\n", " \n", " >>> foo = pd.Categorical(['a', 'b'], categories=['a', 'b', 'c'])\n", " >>> bar = pd.Categorical(['d', 'e'], categories=['d', 'e', 'f'])\n", " >>> crosstab(foo, bar) # 'c' and 'f' are not represented in the data,\n", " ... # but they still will be counted in the output\n", " ... # doctest: +SKIP\n", " col_0 d e f\n", " row_0\n", " a 1 0 0\n", " b 0 1 0\n", " c 0 0 0\n", " \n", " Returns\n", " -------\n", " crosstab : DataFrame\n", "\n" ] } ], "source": [ "# Visualizando o help\n", "help(pd.crosstab)" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "## Realocação por Idade" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAE+CAYAAACA8heHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAIABJREFUeJzt3XmYHFXZ/vHvTRaWhCwQwhoIoAkoEmTfROANS1C2sImAiiwGBBGJLIovIC87/ljiwiay72ERECIgCApBdgQhgSAQwpIFspEEMsnz++PUhE6nZ9KT6Zme7ro/19XXTFedqnpO90w9VaeqzlFEYGZm+bVUtQMwM7PqciIwM8s5JwIzs5xzIjAzyzknAjOznHMiMDPLOSeCnJF0uqQoeM2W9IKkw9phuw1tuY1KkHSFpGmSfiVpe0lPVDumSij385d0sqSK3FMuaZXsb+wHlViftR0ngnyaB2yVvfYHJgJXSdqnqlFVmaTlge8A3wd2BO4Ffl/VoMzaQedqB2DVERGjG3+X9AgwHjgCGFm1oKosImYAPbK3d1czliUhadmImF3tOKz2+IzAiIhZwJvAWsXzJA2W9LikT7Mmkzsk9Ssqc5akFyXNkPSRpPslrb+47UrqJemybJk5kl6WdFCJcgMk3SZpctaU9Zqk4wrmHyzp79n8aZKelvStEutZVdIfJX0g6TNJ4ySdXTB/iKQHs3hmZnX6QYn1rCHpZkkfZ/E8LWmXMup7jaQ3Je2YrXuOpFck7Vqi7KHZvM+yeH+bnbE0zu+fNbscKel3kiYB/1lcDEXbWEXSyOy7/VDSmRTtEyQtK+nS7DP/VNJ7km6RtHqJ9Z0kaUJW7kGgfxPbPUDSs9lnNzn7Tnq3JHarLJ8RGJKWAtYAXiyavgdwF3ArcB7QDTgdeFTSoIj4NCu6CnABMAHoCfwIeErSehHxYRPb7AT8Bfgq8AtgHHAgcIOkpSPi6qzcusDTwEfACaQzl4HAOgWr6w/cQkpmAnYF7pX0rYh4IFvPCsCTwNLAr4ExpMS3TcF61gZGARcDc7N5V0haJiIuy9bTHfg7sAzwM2AScBRwv6QhEfFQU59zZkXgauDMrE4/Af4saaOI+E+2jaNITVJXZ3UeAJwNbCBph1i4X5jTgYeBg4Gui9l2sbuAL2UxfAT8lPTZFlo2q+tpWZmVgeOBf2bf75ws5mHAucAI4D7SZ3dr8QYl/Ri4FPgD8EvS387ZwHqSvhER81tYB6uEiPArRy/SjqOBdBDQGViVtOObBWxdVHYccHfRtP7A58DRTay/E2lnOwU4vni7Be93BwLYp2j5UaSEouz9DcAnwApl1m+prF5/Bu4pmP5/pJ37gBauZwTwUsH0Y7O4Ny0q+x/gqcWs85ps2d0KpnUF3gNuLPj8JgL3Fi17YLbsLgXfQwB/b8n3XvB+lxKxLJ199tHMejoBfYH5wN4F9X8PuK2o7IXZNn6Qve8OTAcuLiq3TXEsfrXvy01D+dSJtFOcC7wPHAf8KCKebCwg6cuko+5bJXVufJH+4V8Hti0oO0TSE5I+ISWZOcAKLHp0WegbwGeko9JCNwOrkY5UAQaTktHHTa1I0vpZk9UH2fbnkhJN4fYHA/+IiLHNrGcNSX+SNJ4vPp9jitbzDeDNiHi2cUKko9jbgM0lLdNMnSF9Ng8ULPs5KWltmU0aCKxEOsMpdHtWt+2Kpt+3mO01ZcsSsXwG3FNcMGt6e1bS9CyGj0hnXo2fSz9gdRb9Lm8rer8VsDyL/k09TUoQ22JV4USQT/OAzYDNgQOAsaQmkK8UlOmb/byJL3aKja+vkZo4kLQZaUc2mXS3zRbZut8jNSk0ZQVgUizaFPBhwXyy7UxoaiVZu/lfSTulE0g7k81IO7TC7S9uPUuR7hL6H1IzyDez9VxGOlIujLtUc9eHpP+nnk1tIzM5ssPgAh+Rkl/j+hvXt0BENJDOslZgYSWb3sqwajOxLCBpb+B6UrPh/nzx/c7ji8931eznxObWxRd/U0+y6N9UD7K/KWt/vkaQUwVHtM9IegZ4ldTO33iRdUr28wTg8RKrmJ793It0ZLlftrNCklj8P/XHwEqSlipKBisXzIeUYBa5MFlgS9L1jf1i4TuhipPQ4tazLrARcGBELDgal3R4ibg3KrH8yqTmkmnNbAOgjyQV7YBXBj4oWH/jtAWyI+cVC+Y3WtJ7/j9oJpZC+wJjImLB5yBpFdJZZeG64IsdfVPravybOpB0PafYpHICt8rzGYEREf8FLgF2k7RJNnkM8A4wMCKeLfFqbGJZjtRcULgz2Zd0kbE5T5COtPcomv4dUnNV447iYWCv7GJvKctlPz9vnCBpDWD7onIPA9tKGtCC9XQD9i4R95clfb2g3FKko+V/RXbxtBnLAEMKlu1K+gwak9gY0pH1/kXL7UM6cCuVlJfE0yViWRrYs6jcchR8JplDit6PJ31nxZ9VcR2eBGYCazfxN/XOEtTDKqHaFyn8at8XRRcNC6avSDrKH1kwbXfSaft1pCP/7YHvAleSXeQl3aETwJ9IzSrHkXYMk4Frmtou6YjySdKF4KNJFy//lK3rhwXl1s3KvE5qetqB9LzD+dn8vlncT5F2ageSdqbjgLcL1rMC8DapeWhYtp5DgCuy+V2Bd7Nl9wKGknbO4yi4eEq64Dkuq+P3SWdQ95KaSnZazGd/TVaXt4EfZsuOyj7jrxaUOyr7HK7MPpdjsjo+xhcX0ftnZQ5e0u+dlAwmZbF8m5Qs3yuq77BsO+dm3++vSEl6LnB6Qbmjs3KXADsDZ5AOJBZcLC4o9znpzqFvkx7c+wGpCXLrcuriVxvsF6odgF/t/IU3kQiyeWdlO7T1CqZ9I9tZTQNmZzuBP5LOFBrLHJ/9088m7dy3IO24r2luu0Av4HLSEfBnwL9L7diA9YA7s53obNIdOscWzN8JeInURDUm27FcRkEiyMqtlu2MJ2U7qDeB/yuYv3EW/6ysPj8HTqboLhpSU9TNWTxzsh3qrmV89tdk2xwMvJzV+VVK3C2T7ZxfzXaaHwK/A5YvmN+f1ieCVUkXeGdl38E5pFs6o6BMJ1IS+AD4NPtbGJDV+/Si9Z1COjOYRbpusxVFiSArtwfpzGpm9nqNdHfWqtX+/8jrq/HowixXJF1JuvXyhnbc5jXAthHxpcWVNWtPvkZguSLpK5J2IN2lsl+14zHrCHzXkOXNxqTmqFmkh8PMcs9NQ2ZmOeemITOznHMiMDPLuZq4RtCnT5/o379/tcMwM6sZzz333OSIWKmcsjWRCPr378+zzz67+IJmZgaApLKf1HbTkJlZzjkRmJnlnBOBmVnOORGYmeVcTVwsNrP8igjmzp3L/PkezriRJLp06cJSS1XmWL6stUj6TjYU4XRJDWWU31TSvyTNkjRO0sGtD9XM8iYimDp1Kp9/XjwkQr7NmzePadOmMWPGjIqsr9wzgk+A35MGG7miuYKSepLGQb2Q1IXxdsBdksZFxFOtiNXMcmbu3Ll06dKF7t27VzuUDme55ZZj2rRpNDQ00Llz6xp3yjojiIhREXEz8FYZxYeS+ow/PyI+i4iHSH2eH9mSwCStKGmApAENDYs9CTGzOjR//vxW7+TqWdeuXanE/rEtPuFBwPOxcG92z7Po8HaLcyxpEHEmTiweE7s8Z5yxwxIttyROO+3RdtsWtG/dwPWrNNevPN26rcT++59B587NH7OuttrAimyvXO+/P6bdttVc3dLw4K3XFncNLc+iA3hPJfX/3hIjgIHAwL59i8fENjOzSmmLRDAD6Fk0rRdpzNWyRcSUiBgbEWN9amhm9eDhhx/jq1/dgmuuuYnLLruae+65v9ohAW3TNPQSsHfRtK9n083MWu3Kg4a1y3ZOe7T8JrV99z2Ep556hpEjr2fLLTdbMH2bbXbmJz8ZxgEHDOUf/3iKm266iltuuZOxY9/g6qt/3xZht1hZiUBSJ6AL0DV7v0w267NYdGSbu4DzJf0cuIR059BQ0gDjZmZ1q3fvXpx55vncd99tJdvvTz/9FAAGDfpae4fWrHKbhg4h3Qk0CuiU/T4bWEvSNyTNlLQmQERMBXYjjQc7DbgSGOZbR82s3h100H588MGH3H33fYvMmz17NocffiwbbbQtAwduwi67DOXxx/+5UJn77x/F4MF7st56mzJ48J488MBD7RJ3ubePXhMRKvF6OyKeiIjuEfFuQflnImLziFg2ItaJiBvargpmZh3Dsssux/DhP+Hccy/is88Wfghu/vz5DBmyE//4x4O88spo9trrWxxxxE+YMuVjAJ599gWOPfbn/OIXJ/DKK6M5+eTj+fGPT+Dpp59u87jd15CZWQUdcMBQunfvxh//eN1C07t168Y+++xB9+7d6dKlC0cddRhdunThxRf/DcBtt93JbrvtzI47bkfnzp0ZPHh7dt11MFdffXWbx+xEYGZWQZ06deKXv/w5I0Zczscff7Jg+uzZczj11DPZaqvBDBy4CeuvvxnTpk1fcEbw/vsfsuaa/RZa11prrcn48ePbPGbfl2lmVmE77rgdG230NS6++Iu7gq644hpGj36GW2+9hn79VkcSG2ywJY3326y22iqMH//eQut5993x9Ou3cHJoCz4jMDNrA6eeeiI33njbgiP+mTNn0rVrV3r37sXnn8/loot+x/TpX3Qat99+e/OXv/yVxx57gnnz5vG3vz3OAw88xKGHHtrmsToRmJm1ga9+dT322GM3ZsyYCcCRR/6AHj16sPHG27H11jux7LLL0K/f6gvKb7bZxlx00bmceeb5fOUrm3PWWRdw6aXns+WWW7Z5rG4aMrOac8SNly30vr37GirljjuuX2TaRRedw0UXnbPg/S23LHzhd9iwwxZ6v8ceQ9hjjyFtE2AzfEZgZpZzTgRmZjnnRGBmlnNOBGZmOedEYGaWc04EZmY550RgZpZzTgRmZjnnRGBm1g7uvPNeBg/es9phlOQni82s5lx5ZTsNVXla+UNVArzzznjOOutC/vWv5/j001n07NmDQYM24A9/+H8MHbo7Q4fu3kaRto4TgZlZhRxyyJF885vb8PjjD7D88t354IOPePjhx1hkQN8Oxk1DZmYV8PHHnzBu3H855JDv0KPH8khitdVW4Xvf+w5LL92VW2+9k2222XlB+X33PYTTTz+Hww47hgEDNmbrrXfiiSee4vHHn2THHXdn4MBNOOywY5gxY0YzW60MJwIzswpYYYXeDBz4ZYYPP5Xbb7+bsWPfXDDWQFNGjvwzRx99OK+99gy77z6E445LXVePHHk9o0c/wrhx/2XEiBFtHrsTgZlZhdxxx3VstdXmXHXVdey8894MGrQNF130+yYTwu67D2GTTTaiU6dO7LPPHnz00SSOOuowevfuRe/evRg8eHueeeaZNo/b1wjMzCpkhRV6c8opP+OUU37G7Nmz+fOfH+DEE/+XVVddGUmLlO/bd6UFvy+77DIlp7lpyMysRi277LIccMBQ1l9/AK+++lq1w2mWE4GZWQVMnTqNc875Da+/Ppa5c+fS0NDA/fePYsyYN9h8802rHV6z3DRkZlYBXbt2YfLkjzn88GOZOHESnTt3Zo01VufMM09l99135dZb76x2iE1yIjCzmnPEER1vqMrllluO3/zmrCbnH3DAUA44YOiC98VDW/brtwYTJry+0LQTTji2XermpiEzs5xzIjAzyzknAjOznHMiMDPLOScCM7MatbguLMrlRGBmHdb8+Q3Mnft5tcPosObNm8dSS7V+N17WGiR1knSBpEmSZkgaKalPM+WHSxqXlX1D0tGtjtTMcuezz2YwZcoH1Q6jQ4oI5syZQ5cuXVq9rnKfIzgZ2BPYApgCXA1cDwwpLihpD+AM4H8iYrSkrYCHJb0REQ+1OmIzy4358xt4+eUH6d79QLp160GJ7noAmDNnTrvG1dAwv922VVy3iGDevHnMmTOHXr16lezDqKXKTQRHAr+OiLcAJJ0IvCmpf0S8XVT2S8BLETE6C/opSS8DgwAnAjNrkQkTXuLuu9+ga9duTZY55pjr2jEiuO2209ptW8V1k0TXrl3p1q1bRZIAlJEIJPUE1gSea5wWEeMkTQc2BN4uWuQW4IeStgGeArYBBgAPtiQwSSsCKwIMGjSoJYuaWZ2ZO3cWc+fOanL+Msss047RwKefTmq3bbVH3co5I+iR/ZxWNH1qwbxCE4E7gEf54hrETyPilRbGdixwGsDEiRNbuKiZmZWrnIvFjZ1h9yya3guYXqL8r4DvAhsBXUhNQsdLOqyFsY0ABgID+/bt28JFzcysXItNBBExFXgX2LhxmqR1SGcDL5dYZBPgroj4TySvAncD325JYBExJSLGRsTYzp3dN56ZWVsp9wbUK4CTJK0tqQdwHjCqxIVigH8Ce0n6MoCk9YG9gOcrEK+ZmVVYuYfa5wK9gWeApUl3/xwMIOkg4PKI6J6VvYDUjPRQ9qzBx8Dt2TrMzKyDKSsRRMQ8YHj2Kp53I3BjwfsG0nMHJ1coRjMza0PuYsLMLOecCMzMcs6JwMws55wIzMxyzonAzCznnAjMzHLOicDMLOecCMzMcs6JwMws55wIzMxyzonAzCznnAjMzHLOicDMLOecCMzMcs6JwMws55wIzMxyzonAzCznnAjMzHLOicDMLOecCMzMcs6JwMws55wIzMxyzonAzCznnAjMzHLOicDMLOecCMzMcs6JwMws55wIzMxyzonAzCznnAjMzHLOicDMLOfKSgSSOkm6QNIkSTMkjZTUp5nyfSVdK2mKpOmSXpS0WuXCNjOzSin3jOBkYE9gC2CNbNr1pQpKWgZ4BPgcGAj0Ag4CZrYqUjMzaxOdyyx3JPDriHgLQNKJwJuS+kfE20Vlv0/a+R8dEXOzaa9WIlgzM6u8xZ4RSOoJrAk81zgtIsYB04ENSyyyA/Af4PKsaeh1ST9raWCSVpQ0QNKAhoaGli5uZmZlKqdpqEf2c1rR9KkF8wr1AXYGXgJWBQ4GfiHpoBbGdiwwBhgzceLEFi5qZmblKicRzMh+9iya3ot0VlCq/ISIuCQiPo+IZ4EbSNcYWmIE6RrDwL59+7ZwUTMzK9diE0FETAXeBTZunCZpHdLZwMslFnkRiFKraklgETElIsZGxNjOncu9lGFmZi1V7l1DVwAnSVpbUg/gPGBUiQvFANcAK0r6cXbb6SDSXUN3ViJgMzOrrHITwbnAvcAzwASgE6ntH0kHSVpwa2hEvAPsBhxOajq6Azg9Im6tYNxmZlYhZbW5RMQ8YHj2Kp53I3Bj0bTHgK9XID4zM2tjbnw3s8p7rJ23d1o7b6/OuK8hM7OccyIwM8s5JwIzs5xzIjAzyzknAjOznHMiMDPLOScCM7OccyIwM8s5JwIzs5xzIjAzyzknAjOznHMiMDPLOScCM7OccyIwM8s5d0NtZtZSj7Xjttqhi22fEZiZ5ZwTgZlZzjkRmJnlnBOBmVnOORGYmeWcE4GZWc45EZiZ5ZyfIzCrhsfaeXvtcC+61S6fEZiZ5ZwTgZlZzjkRmJnlnBOBmVnOORGYmeWcE4GZWc45EZiZ5ZwTgZlZzpWVCCR1knSBpEmSZkgaKalPGcsdJSkkndr6UM3MrC2Ue0ZwMrAnsAWwRjbt+uYWkLQWcALw7yWOzszM2ly5ieBI4LyIeCsipgEnArtK6t/MMn8Efgl83KoIzcysTS02EUjqCawJPNc4LSLGAdOBDZtY5kfArIi4dUkDk7SipAGSBjQ0NCzpaszMbDHKOSPokf2cVjR9asG8BSStCZwKHNW60DgWGAOMmThxYitXZWZmTSknEczIfvYsmt6LdFZQ7Crg/yJiQmsCA0YAA4GBffv2beWqzMysKYtNBBExFXgX2LhxmqR1SGcDL5dYZCfgbEmTJU0GtgFOkfRESwKLiCkRMTYixnbu7N6yzczaSrl72CuAkyQ9CkwBzgNGRcTbJcr2K3p/O/AE8JslDdLMzNpOuYngXKA38AywNPAQcDCApIOAyyOiO0BEvFe4oKTPgOkR8VGlgjYzs8opKxFExDxgePYqnncjcGMzy26/pMGZmVnbcxcTZmY550RgZpZzTgRmZjnnRGBmlnNOBGZmOedEYGaWc04EZmY5574brGN6rJ23d1o7b8+sA/EZgZlZzjkRmJnlnBOBmVnOORGYmeWcE4GZWc45EZiZ5ZwTgZlZzjkRmJnlnBOBmVnOORGYmeWcE4GZWc45EZiZ5ZwTgZlZzjkRmJnlnBOBmVnOORGYmeWcE4GZWc45EZiZ5ZwTgZlZzjkRmJnlnBOBmVnOORGYmeWcE4GZWc6VlQgkdZJ0gaRJkmZIGimpTxNld5P0N0mTJX0i6QlJ36hs2GZmVimdyyx3MrAnsAUwBbgauB4YUqJsb2AE8CgwEzgCeEDS+hExvtURW/JYO2/vtHbenpm1m3Kbho4EzouItyJiGnAisKuk/sUFI+LGiLgrIqZGRENE/AGYDWxaqaDNzKxyFpsIJPUE1gSea5wWEeOA6cCGZSy/IbAi8EpLApO0oqQBkgY0NDS0ZFEzM2uBcpqGemQ/pxVNn1owryRJfYE7gPMj4o0WxnYsWYPExIkTW7ho5rElW2yJuOnEzGpUOU1DM7KfPYum9yKdFZQkaTXSdYK/AqcsQWwjgIHAwL59+y7B4mZmVo7FJoKImAq8C2zcOE3SOqSzgZdLLZNdO3gCeCAijomIaGlgETElIsZGxNjOncu9pm1mZi1V7sXiK4CTJK0tqQdwHjAqIt4uLihpPeAfwM0RMbxikZqZWZsoNxGcC9wLPANMADoBBwNIOkjSzIKyJwGrAz+VNLPgdVAF4zYzswopq80lIuYBw7NX8bwbgRsL3h8KHFqpAM3MrG25iwkzs5xzIjAzyzknAjOznHMiMDPLOScCM7OccyIwM8s5JwIzs5xzIjAzyzknAjOznHMiMDPLOScCM7OccyIwM8s5JwIzs5xzIjAzyzknAjOznHMiMDPLOScCM7OccyIwM8s5JwIzs5xzIjAzyzknAjOznHMiMDPLOScCM7OccyIwM8s5JwIzs5xzIjAzyzknAjOznHMiMDPLOScCM7OccyIwM8s5JwIzs5xzIjAzy7myEoGkTpIukDRJ0gxJIyX1aab8rpJelTRb0iuSdq5cyGZmVknlnhGcDOwJbAGskU27vlRBSesAdwLnAD2zn3dJ6t+aQM3MrG2UmwiOBM6LiLciYhpwIrBrEzv37wPPRcQNEfF5RNwIPJ9NNzOzDmaxiUBST2BN4LnGaRExDpgObFhikUGFZTPPZ9PLJmlFSQMkDWhoaGjJomZm1gKKiOYLSP2Ad4F1IuK/BdPfAX4ZETcUlX8E+EdEnFYw7Qxgm4gYXHZg0ulA4zpmAa+Vu2wrdAJWBj4C5rXD9tqb61fbXL/aVY26rRURK5VTsHMZZWZkP3sWTe9FOisoVb7css0ZAdyU/T4lIqa0cPkWkzQAGANsHxFj23p77c31q22uX+3q6HVbbNNQREwlnRFs3DgtuyDcA3i5xCIvFZbNfD2bXraImBIRY7NXmycBM7O8Kvdi8RXASZLWltQDOA8YFRFvlyh7HbCppAMldZF0ILAJcG1FIjYzs4oqNxGcC9wLPANMILV3HQwg6SBJMxsLZheShwKnkpqDTgX2biJpdDRTgDOyn/XI9attrl/t6tB1W+zFYjMzq2/uYsLMLOecCMzMcs6JwMws55wIzMxyzonAzCznnAjMzHLOicDMLOecCMzMcq6cTufqlqTuwN6kLrJ7kJ6Efgm4KyJmNresmVlTam3fktsniyVtDPwF+Ax4AZhK6iV1I2BpYEhEvFi9CCtD0pqkQYGK/yCvjYh3qxlbJdRz/eq5blC/9avFfUueE8FTwJ0RcUGJecOBfSNiy/aPrHIk7QTcRRoY6Hm++IP8OqmH2L0i4pHqRdg69Vy/eq4b1Hf9anLfEhG5fAEzgS5NzOsCfFrtGCtQx5eB7zYx70Dg39WO0fXLX93qvX61uG/J8xnBm8CPosRRh6QdgKsiYt32j6xyJM0CekTEImN9SuoMTIuIbu0fWWXUc/3quW5Q3/WrxX1Lni8W/xq4R9JI0hjL00gjq21M6kb76CrGVilvAfsBN5eYtw/w3xLTa0k916+e6wb1Xb+a27fk9owAQNK2wOGki1XLk4bZfAm4MiL+Wc3YKkHSrsBI4FkW/YPcFBgaEX+tXoStU8/1q+e6QS7qV1P7llwngjyQtDZf3JlR+Ad5XUS8Vc3YKqGe61fPdYP6r18tcSIwM2tD2fC+WwMBPBkRM6oc0iJy+2SxpN6S7pb0iaS/SxpUNH96tWKrtOzhlsbfB0raTdKK1YypLUk6O/vnqyvZmOHrVDuOtpDVbZikH0laq9rxtIak30raKPt9E+AN4CbS9ZDXJW1YzfhKyW0iAM4DugIHkdooH5e0XcF8VSWqCpL0NUnjgWmSzpE0FBgN3A6MafxjrVWSti71AoYB22e/1yRJ5xT83kfSP4FxwBuSnpa0cvWia73sIGyT7PedgFeBH5G+u1eK/hdrzf7Af7LfLwAujogVImIF4BLgoqpF1oTcNg1Jeg8YFBFTsvf7AJcD346I0ZKmR0RNH1VKegB4CJgPXAgcD/wW6JT9XCUi9qpehK0jaT7pdLuppB0R0akdQ6qYwr8/SVcAqwNHkOr7B2ByRBxexRBbRdIUoG9EzJM0GvhtRNyQzTsQOC462kNXZZI0A+gdEQ2SJgGrNt4mK6kTMClLCh1GnhPBNGCFiJhXMG0/0j/ZLsCjdZAIJgGrks78ZpP+OKdn8/oAL0fEalUMsVUk3QqsABwREW8XTJ9ESvLvVyu21pI0IyKWz34fB+wYEe9k71cntTXXbBNK1vTaNyLmSJoMrNz4vyhJwNSI6FnVIJdQ9mTx+RFxl6TngO9FxKvZvPWBv0XEqlUNskienyMYD2xAuksBgIi4PWtPH0XqE6TWdS44EpnemAQAImKypOWrF1rrRcQBkvYGHpZ0aURcWu2YKqjwCG35xiQAEBET6uAaz9PAIcCVwCvAlkDjbZVbAp9UKa5K+BVwu6RNgT8DD0q6Opt3KKnloUPJcyK4j/RAy0uFEyPiT9m/kEYoAAAJrUlEQVQO8uKqRFVZEyWtEBEfA98unJEdVdb8BfHsqOtxYETWpHA4C+9Ea9Wykhrvo19G0hoR8R4sOJubVb3QKuIk4G/Zk7YvAA9IuiubtzdwctUia6WIeDg7QDkb2Jx0Rv4r4G3g0oi4sIrhlZTbpqE8kHQMcH9ELPKUpqQjgc1ruZ25mKS9SBfjVgX613jT0GlFk26LiNeyeXsD+0TEwe0fWeVIWg/4X2AHoA/pOYIXgd9HxB3VjK1SJC0H9AZmFJ6RdzROBFZXJPUGNiS1oc+tdjxmtSDPt4/mkqSaPeUu048i4u/1mATq/bur9/p1ZD4jyJl6uC22OfVcv3quG9R//ToynxHkT80/KLcY9Vy/eq4b1H/9Oiwngvx5Z/FFalo916+e6wb1X78OK9eJQNJKSkPHFU//QfbgR92JiA2qHUNbquf61XPdoL7qV2v7llxfI5C0FPAesGtEvJxNWx6YAKwTEZOrGV8lZA/I7c2iA4TfFREzqxlbJdRz/eq5blDf9au1fUuuEwGApIuA2RHxi+z9wcAhEbFLdSNrPUkbA38BPiM9tNM4QPhGpCenh0TEi9WLsHXquX71XDeo//pBbe1bnAikzYBbGscQlXQPcGdEXFvdyFov6/Pkzoi4oMS84cC+tdqxF9R3/eq5blD/9YPa2rfkPhEASHoD+C4wFngXWKMjDh7RUpJmkjqaW+SeekldSB171eQA4VDf9avnukH9169Rrexbcn2xuMDNwIHAXsAjHfGLWkIfAk31675tNr+W1XP96rluUP/1a1QT+5Y8dzpX6GZSv/1fIfWGWC9+DdwjaSSLDhA+FDi6irFVQj3Xr57rBvVfv0Y1sW9x01BG0otAf1K/6J9VOZyKkbQtqUfO4gHCr4yIfza3bC2o5/o1UbcXgatqvW5Q399doVrYtzgRZLIRytaIiEuqHYstuazTuVWB1yNifrXjqTRJw4DrIqLWu6HOjVrYtzgRWM2S1A+4BRgAnEYa4OR+YDngv8BOpbrgrgWSikeOaxyS82VgJ+CjWu5mu5TsIrEi4vNqx5I3vlhcxyT1Vhok/BNJf5c0qGh+h+0fvUy/AUYD15IGBN8GWAfoB/yb1A5dq94jjaL3XsFrPGlozuey32tWdmbT+Hs3STcBnwIzJN2WPWxm7cRnBHVMadDzNUgD1Q8GDgN2j4jHs/kLxsWtRZI+JLW9diK1L68SEROzeWsAT0VEv+pFuOQkPQnMBIaTLqRCOiN4DtgN+LBw+MpaU9jTqKTzgW8Cx5POfC4kjSfx8yqGmCtOBHVM0nukQdynZO/3IY2X+u2IGF3r3f5KmtY4wLmkqRHRq2h+zSa6bAD3nwHDgOERcU82fRLpO63pZqHC70bS68DeBSOwfRl4sPFBLGt7bhqqb8uTHt0HICJGAkcB90napGpRVc6UrP8WSPVaQNJKpKaGmhTJb4BvAcMl3SqpL/UxHjMsXI8+jUkAICLeAPq2f0j55ecI6tt4YAPSLXkARMTtWfvrKFKfLrXsJtIdQjMi4uaiefuTmlFqWkSMlbQd8FNSfWryDKeEZbKmS0gnQCtFxKTsTU9SH0TWTtw0VMcknQs0RMSpJeb9BLg4IuryrDBrWiHq6A9c0rqkp25vjYg51Y6nNST9qWjSpRHxQjbvAGBYROzQ/pHlkxOBmVnO1eXRoJmZlc+JwMws55wIzMxyzonAaoakNSV9LuntbCjASq+/v6QoeE2X9LykQyq9LbOOxInAasnhwG3AXGDnNtzOnqTbUjcG7gKuk9SW2zOrKicCqwmSOgE/JPUrdD1wRNH8dSU9ImmOpLckfVfSm5JOLyizvKTfSfpA0kxJoyWVukXx44j4MCLejIgzgY+BXQvW01vSDZLelTRb0lhJPy88S5F0jaSHJQ2T9E52dnF39qBbYdzDJb0v6VNJIyUdJymKyuwq6elsW+9KukRSt4L535T0pKQZ2eslSYOX5HO2fPIDZVYrvpX9fAR4AxgjaZWI+DDbAd9F6m9oW9JTqxeRjuqBBc8V3Ec6mxgKTAT2Bh6UtElEvFK8wSz57E/q6K3wAaelSZ3a/T/gE1Jnd5eREsYfC8ptBkzKYu9FGqTkPFJCQ9J+wDmkh8UeIvUqulBHedkOfSRwAvAw6YnbEcBVwIGSOgN3A9cBP8jqvgEwu+mP0qxIRPjlV4d/kXbi5xS8fww4Oft9Z9IOcN2C+etm007P3u8AzAGWL1rvKOC32e/9s2VmkTp8a8jeTypcdxPxXQI8VPD+GlKyWbpg2qnA+IL3T5LGFihcz/Vkz8Fl7/8OnF1UZqssrpWA3tnv21X7O/Krdl9uGrIOL+tJdFfSUW+ja4HDsyP99YFJETGucWb2++SC8psCXYHGZqGZSgOo7wh8uWiThwIbAUOAV4GjC9ctaamsKegFSZOz9QwD1ipaz2ux8IhUE4CVC96vT+pGu1Dx+02BnxXF/HA270sR8Qnp7OCvkv6SxTUAsxZw05DVgsNJXU3/O+s5olEn4H/KXMdSpO6cNysxr7gZZUJEvAm8mXV3MFrSvyPi9Wz+z4BfkbpNfp7UJHU8XzRfNZpb9D5o+XW5pUjNSdeXmDcBICKOkHQJqavxnYGzJP04IjrsGLnWsTgRWIeWtf//EDiTdMdQoTNIF43/CKwkaZ2IeCtbbh2gT0HZ50jt9EtHxKvlbj8iXpV0L3A+sEc2+ZvAAxGx4HpA1nVyS70GbAH8vmDa5kVlngO+kiWm5uJ8hTRC28WSLiOdoTgRWFmcCKyj2400uM7lETGhcIaka4HbgZ+QdoLXSjqONIDLhaS2/sY7cB4BHgVGSjqRdLG3D7A9MC4i7mwmhguA5yVtHRFPAmOAQ7I7jiYA3yPt0D9pYd0uAm6UNJrU3DOYRc8qTgNGKQ3ecgPp7GU90gBDR0pam9QF959Jvc2uBnwDeKGFsViO+RqBdXRHAP8sTgKZB0k7xu+R7gCaCzxFSg5XkMZimAMLeiH9NnAv6a6bMcA9pDt+mh3pK1KvmA8DZ2eTziRdxL0n296KwKUtrVhE3A78Evhf4EVSIriwMeaszCPZ9M2zbb0AnAV8kBWZRbowfgswlnSH0ZPAMS2Nx/LLvY9aXVIa/P09YN/FHO13KJIuB7aKiA2rHYvlh5uGrC5I2oN0RvA6qXnkPOB90llDhySpC+nC819IZwFDSHcsDa9mXJY/TgRWL5YDTifdwjmd1IzyvYiYVc2gFiNIt6/+HOgGjCMlht9VMyjLHzcNmZnlnC8Wm5nlnBOBmVnOORGYmeWcE4GZWc45EZiZ5ZwTgZlZzv1/fVwGFTBNm3IAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Qual o objetivo de realocação?\n", "# A vontade de buscar um novo emprego diminui com a idade. \n", "# Quase 80% das pessoas abaixo dos 30 anos estão preparadas para isso.\n", "\n", "# Agrupando os dados\n", "df3 = pd.crosstab(df_ageranges.AgeRanges, \n", " df_ageranges.JobRelocateYesNo).apply(lambda r: r/r.sum(), axis = 1)\n", "\n", "# Definindo a quantidade\n", "num = len(df_ageranges.AgeRanges.value_counts().index)\n", "\n", "# Criando a lista de cores\n", "listaHSV = [(x*1.0/num, 0.5, 0.5) for x in range(num)]\n", "listaRGB = list(map(lambda x: colorsys.hsv_to_rgb(*x), listaHSV))\n", "\n", "# Gráfico de Barras (Stacked)\n", "ax1 = df3.plot(kind = \"bar\", stacked = True, color = listaRGB, title = \"Realocação por Idade\")\n", "lines, labels = ax1.get_legend_handles_labels()\n", "ax1.legend(lines,[\"Não\", \"Sim\"], loc = 'best')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Idade x Horas de Aprendizagem" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZgAAAElCAYAAADZb/T+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAIABJREFUeJzsnXl4VNXd+D/fzGSykJAAIQLGGAEBEWURQS0CdatLa9VqtXW3Wv1RtWpbtLa1tva1Wqv27aJttXWptrZV27dVi4oWV0RlcUcEBARFNoHELJNJzu+Pe2cy994z4UxmyXY+z5MH7nfOdpeZc8/5bqKUwmKxWCyWbFPQ3QOwWCwWS9/ETjAWi8ViyQl2grFYLBZLTrATjMVisVhygp1gLBaLxZIT7ARjsVgslpxgJ5gejohcKyIxg3JXiUhWbM5FZJiIKBE5JxvtdRciUueexxkpPm8WkWvzPKysISIHuec3O8N2FrjtdPa3JktjvkFEGrLRVk9GRKrc7+747h5LdxLu7gFYLJZuZw4wMOn4NiAGXJoka8lSX78BHspSWz2ZKuCHwJvA2908lm7DTjCWXo2IFABhpVS0G8dQopRq6q7+M0Up5fkBFJGdQEwp9dKu6opICAiZXn+l1AfAB10aqKXXYbfIeiHuFtZDIvKpiGwUkevw3UsRKRGRX4rIO2659SLygIjsrmnvShHZ4JabB9Sl6PdUEXlVRJpEZIuI/EFEBu1irLPdLZYvuv3Xi8hmEfmZ++OUXHa8iDwiIjvdsTwlIgf6yiwQkfkicpqIvI3zZn2I0YUzQEQ+LyKvJJ3jn0RkmK+MEpEfish1IvIh8KkrHyMi94vIWrf+CndLqMRX/2wReV1EGkVku3tNv7iLcYVF5Cb32tWLyAPAkBRlLxaRt0SkRUQ+EpGbRaQosyuTaPsl9x6dKSLLca7/FPezCveZW+/2/Y6InO2r79kiE5Fx7vU8XUR+4V7zLSJyr4gMTCpXLiK/FpHl7nX7QETu09yb+Pi+4l7/JveZqRORwSLyZ/f5Wisi39Cc33QRedwt0yAij4nI2KTPi93xfkdEvu9+b7aLyL9EZHj8nIB33Cp/l45txoPcz0vcexK/Tst1Y+kTKKXsXw/+A67FeZtMli0ENgNfAz4PzMd5K1RJZQYDvwe+DMxy/10IrAGKk8pdBCjgl8BRwI+Ata7snKRy3wDagF8DnwPOBjYALwAFnYx/ttvW+qQ+rsXZgvlJUrkaYCvOdsKpwInueBuBCUnlFgAfA8uBr7pjqUnRd53b91k4q3X/XzNwbVL544B24J/u/88FNuL8WJQmlVPAh8Bj7vU/xZV/FvgJ8EX3ml/onvcDSXVnuvVvAQ4DjgGuTL7WKc7lBveaXetew1/H7zkwO6ncTTg/+j8BjnTv2/bkMRg8cwuA+Sk+e8m9Jm+59+loYDhQBLzqnu/XgSOAW93reY7vPBqSjse557AW+J17Py91781tSeWGAbcDp7jX9lTgFWAFUOgb3wZgEXCCW+4jnOd0vnv9jgT+4PZ7UFLdQ9x+H3HrnuC28zFQ7ZYpThrvg8CxwDnANuCxpDKnuuW+Cxzk/pW5n/8f0ATMde/lL92yV3f3703Wf7+6ewD2bxc3yDfBuF9ABRybJCtyv1Sqk3ZCQLX7hT/RlRW4Pwh/85X9OUkTDFAG7AR+4Sv3Gf9YNP3Odsv4+/gZ0ABUusc3u1/uEUllynAmnb8kyRbg/NDubXDt6ty+O/u7Nqn8YuA1QJJkB7vlLkySKWA1ztZcqr4FZxI7GWdiHuLKvw1sS/MZGISzSvqZT/4gSRMMsJfb12W+cqe75cYb9reAzieYKLCnT/51975M8Mn/BKxNOk41wfzDV++Ozq6T+zzv4dY9xje+T4GhSbJvu+V+liSLAJ8AtybJXsR5qUm+/4NxJugfu8fxCWaJr9z3XPlA33md7Bv3ga78Gz75PUA9MCCdZ6On/9ktst7HQTg/xP+JC5RSLThvRR5E5Ax3+2Unzpf/Y5wfvviSfw9gd+Afvqp/8x0fDJQDf3W3asIiEsZ5u9sJzDAYt7+PB4EBwH7u8aHAc0qpD5POqwH4N85bfzLvKqXeM+gzzjU4X2z/X0JvICJlwGSciTBhjaeUWojztuofw3+UUh7rPnf75Ici8h7OG2or8HeciXxvt9hiYJC79Xak2++u2B8oZdf36Qi3r7/57tMT7ucm98mEN5RSa32yzwFvAMt9fT8O1IpI7S7afMx3/CbOdUpcHxE5V0SWiEg9zvO8zv1orK/uMqXU5qTjFe6/T8YFytEZvY/zHUBEKnC+W38FQknj34mzUvJfu/8kPyfueAF2dZ6Huv8+4JP/BeeFasou6vcqrJK/9zEc2OJ7uMGZPBKIyIk4b49/AL6Ps4Rvx3nDK05qC2BTZ23hrHzAecPTodUF+EjVxwj338HAu5p6G93P/LJ0eF8p9apfKF6z7kqcyVfXtukYbsTZcvwhzuRbD0zCeRsvBlBK/VdEvgJ8E+cloU1EHsVZdazTtAnp36cNKdoxuU8m6M69GudcWzvpO9X5gbOaSCZutVYMNLjX7I/Ab3G2nbbhTKbJz3OqtqKdyON1q3Du/63un5/X0xhvZwzG2ZHY6pNvTPq8z2AnmN7HR0CViIhvktnNV+5knDf98+MCVyGarFj/yP23Gi/+tuJfhq8AKzVj2qyR+UnVR3wM2zT9xstt88lykWNiu9tuqjGsMhjDycBdSqkb4gIRGe0vpJR6AHhARMpxdD23APcRXCXFSb5PyeNIdZ9m4xoe+Eg18aSL7ty34vwIfy1FHd3LQzqcDLymlPp/cYGI1GXYZjLxZ+x6gitFcFak2eonLCKDlVLJz/VuSZ/3GewE0/tYhPOWdAzutoJrIeS3QiolaQvI5Uzf8Qc4yuoTcZbocb7sK/cijr5kL/fHsSv4+zgZ50fwDff4OWCOiAxTSm0EEJEBwBdI2trIFUqpBhFZCpwsIj+NT94iMh1Hl3NDZ/VdTK55cp/1OBPNNBxFcSpex/mBixs+xPHfp/k4q9QRSqm/kF8exzEw2KiUWp+D9tO6tumilPpERF7G0SF9LwtNplrRPOf++2Wc1Vic03C+Y0uy0HePwU4wvQyl1Dz3i3CPiFyJs21yGcG3yseB20XkBpwf6ENwLL9iSW21i8j/AL8Rkf8FHsVR3J/i63On29cvXFPMJ3Csu2pxLZqUUqm2z+IcktTHwcAVOErX+FbDrTg/sk+KY3YdxbGyKQX+x+jiZM41ODqfh0TkTpwVw/U4b99/Mqj/OHCuiLyJsx30VRxlbwIR+ZHb7n9xtkVGA2fQoScJ4P74/Rq4QkQ+xZlkvgBM95VbKSI/B+4QkX2B53GU/nU4K6VvanQn2eKPOFZ3z4jIzTiWd2XAPsBkpdRXMmz/ceBW99lYgLPaOy3DNv1cDjwlIv8A7sdZmQ/D0b+8oZT6fRptrcfZIj1DnCgIzcA7SqlXRORfwC2ufuk1nHtzDvA9pZRu5dl76W4rA/vX+R96M+XhOMv4RpwJ5qe4VixJZUI4b90f4awUHgfG4DPNdct+F2cl04jzQxe3nDrHV+54nDewBvfvHeBXwPBOxj/bbeuLOArvepztlJ/js8ICxuNMQPXumJ8GpvnKLCCFhZOm7zq37zNSfK67Fl/AMbdtxtmuuA8Y5iujgO9r2hvqnuN29xzvwDGJTbb0Og5nwv8Y5y13Dc7kWr6LcynEsbTb6l6fv+OYSHvMlN2y57nn0ATswPkRuxHXTNbguqW8xjg6j0dSfFbm9rMK5wVhE/AM8PWkMqmsyPzWVnHz+Sr3OOye/0b32XsMGOmWuaqz8eGYUitg6q7OBcfQ45/uvW/GMQS4H5jifh63Ivv2rvrA2VJ+D+elTuGaRAMl7rlscK/Tu8DFuf4t6Y4/cU/YYskJ4sTJ+i9wqFLq+W4ejsViySPWTNlisVgsOcFOMBaLxWLJCXaLzGKxWCw5wa5gLBaLxZIT7ARjsVgslpzQr/1gqqqqVF1dXXcPw2KxWHoNixcv3qKUGmpStl9PMHV1dbz6aiBElcVisVhSICLGzrp2i8xisVgsOcFOMBaLxWLJCXaCsVgsFktOsBOMxWKxWHJCXicYETlNRJ4TkZ0iEtN8frSIvCUiTSLypogc5ft8tIjMF5FPRWS9iHwrf6O3WCwWSzrkewXzCXAbTnh5DyIyEngYJzJwhfvvP+JJhUQkhBNK/R2cqLXHA1eKyKn5GLjFYrFY0iOvZspKqcchEWHXz9nAYqXUfe7x/SJykSv/EU7+hz2B7yqlGoElIvI7nLDef8312PNNa1s7tzy5gmXrtjOptpIrjhxDYSj4PqArBwRkrW3tnH7nIlZtamBUdRn3n++kEvHLSiNhGqOxgLwxGmPmzxbQGG2jNBLi2bmzqSiJGI1R116qvnXo6uvKml4L3Rjzhe5cCkMFPWqMPRHT74OlZ9EtscjcCWa+UiqcJPsnsEYpdVmS7H+BPZRSJ4nIZTj5SSYlfX4i8AellHEeaxEZgpubfOLEie8uW7Ys4/PJBTfOW87tCzqy486ZPYq5R48zKqcgIFu4eitL121PyKbUVqIgIHt4zmc48bYXAvLlG+tpjLYlZKWREGcfUmc0Rl17qfrWoauvK2t6LXRjzBe6c5k+ckiPGmNPxPT7YMk9IrJYKTXVpGxPcrQsx0mOlMx2YN9dfD4wzX4uAX4IsGnTpjSr5o9lST9CAMs+2G5czv/OsOyD7aza1OCRrdrcECi3arNTRlc2eXIBaIy2GY/R395K33Fy3yb1U5U1vRbdie5cisIhj6y7x9gTMX3WLD2LnrTGrMfRvSRTCew0/NyUXwFjgbHV1dXpjjFvTKqt9B7vUWlcTicbVV3mkY0aWqaVAVp5acT7I1gaCRmPscRXtyQSStm3DtOypteiO9GdS08bY0/EXqPeSU9awbwGfNYnmww8lfT5GBEZoDryVk925cYopbbipJ1l6lSjVV63cMWRYxCcN7VJe1RyuatPMC3nl13c1s4Zdy5i1eYGRg0t4z5XD6KT3X/+9IA8lQ7GZIx7Dinl450tieO6IQO469wDtX3r0I0nk2vRnejOpTBU0KPG2BMx/T5YehZ51cG4lmCFOAr7x3ByeIOTm3wk8AbwNeBB4GTgTmBfpdQat+6bODnjr8JZhTwOfFMp9UBXxjN16lRlY5HlHrt/brH0HXqyDuZM4K6k4yb3372UUqtE5CTgZuCPwGrgRKXUGgClVJuIfAH4Hc4KZDtwU1cnF0v+sG+fFkv/pF9ntLQrGIvFYkmPnryCsWQZUx8Ri8ViyTc9yYrM0gVOv3MRS9dtZ2dzjKXrtnPGnYu6e0gWi8UC2Amm12PqI2KxWCz5xk4wvZx0/EksFosln9gJppdz//nTmVJbSUVJmCm1lZ36k1gsFks+sdrgXk5pJJwyhpfFYrF0J3YFY7FYLJacYCcYi8ViseQEO8FYLBaLJSfYCcZisVgsOcFOMBaLxWLJCdaKrA9iml42VZgZ09TDOplpGtt0UuBmkj46X2l1bUpfiyWInWD6ILc8uSIRHn/h6q0IaMPjx8PMAIkwMw/P+Yy2fnLq4c5kpmH4TceYTtl02sw23dm3xdJTsRNMH6SrqYzjYWZMUw9nko44nRS4maSPzhc2pa/FEsSu4fsgpullU4WZMU09nEka23TqZpI+Ol/YlL4WSxDjFYyI7A18Gxjvit4Cfq6UWpmLgVm6jmmCr1SpiNNJPdzVRGLpJCHLNH10PrBJ1SyWIEYJx0TkKODfwNvA8674EGACcJxSan7ORphDbMIxi8ViSY9cJBy7HrhNKXW5r6NbgJ8CvXKCsVgsFkvuMNXBTABu18h/635msVgsFosH0wnmE2BvjXw0YM1lLBaLxRLAdIvsr8CdIvId4AUcF4jPADcCD+RobBaLxWLpxZhOMFcCEeCPQMiVtQG/B67KwbgslgTWS95i6Z0YTTBKqRZgjoh8F4jbX65QSu3I2cgsFhfrJW+x9E6MJhgRuQ2Y604oryTJS3F8YebkaHyWLJGL2F/5YsnaTzzHi33H6WJjlnWN3jx2S/dgukV2IXAt0OCTl7if2Qmmh5OL2F/5Ys3WTzs9Thcbs6xr9OaxW7oH09ePeGxDP1OBrdkbjiVX5CL2V75obIl5jpuisRQlzbAxy7pGbx67pXvodIIRkSYRacSZXNaKSGPSXwvwGPCXfAzUkhm5iP2VL0bvVu49ri5PUdIMG7Osa/TmsVu6h11tkV2Ms3r5PfA9YGfSZ1FgtVLqhRyNzZJFchH7K1+kipnWVWzMsq7Rm8du6R5MY5F9DnhaKdWa+yHlDxuLzGKxWNIj67HIlFKPJzVeiW9rTSm1La0RWiwWi6XPY6TkF5E9ROQREWnCUepvdv+2uP9mBREZJiJ/FZHNIvKJiDwtIhOTPj9LRFa5OqBFInJAtvq2WCwWS3YxNVP+A7A7jk5mA3qLsmxwG1AOjMUxif4J8IiI1OKEprkdOBF4Bvgm8JiI7K2U2pmivT5FYzTG6XcuYtWmBkZVl3H/+dMpDBUY+SZsaWhm5s8W0BhtozQS4tm5s6koiWTk12DqF7GjKcpRtz7LloYoVWURnrh8JqWRsHHfpucNGMla29oD7ZVG9F8F3Tnq2myMxozOMZ2+s30fejP94Rz7IqY6mHpgplJqaU4HI/I68Gul1O/d47HAcmAocDNQoJQ60/1MgLXAD5RS96TRxxBgCMDEiRPfXbZsWXZPIoeceNsLLE0yFZ1SW8n0kUMSvgkAc2aP0vomjL9mHo3RtsRxaSTE2YfUGdVNxY3zlhvVn379fD7e2ZI43m1gESdNqTHu2/S8FRjJFq7eGmjv4TmfMT5HXZsPLVlvdI7p9G2K6X3ozfSHc+wt5CIfzEac2GO55ibgDBF5GGcF83XgeaXUFner7O54QaWUEpGlwERtS6m5BPghwKZNm7Iy6HyxapPXz3XV5gaKwiGPLJVvQvLkEj/O1K/BtP6WhmjgOJ2+Tc/b/66USqZrLxW6ceraND3HdPo2pT/4p/SHc+yLmK4xvwf8j4gMzOVgcCI1h3D0Og3AScAF7mflgD/22XYg3TH9CmcLbmx1dXXXR9oNjKou8x4PLTP2TSiNhALHmfo1mNavKosEjtPp2/S8TWW69lJh2qbpOabTtyn9wT+lP5xjX8R0BfMDoA7YKCJrAY+5slJq/0wHIiIFOJkx5+FMLM3AWcBzIjIBqAcqfNUqgVWkgVJqK270galTjVZ5PQadP0hhqMDIN+HZubO1OphM/BpM/SKeuHymVj9h2nc6520iu7it3divJtU5+mXnzajzXN9HL52hvb7p9G1Kf/BP6Q/n2Bcx1cH8tLPPlVLfzXggIlU4K5fxSql3kuRbgfNwJh1RSp3lygVYA1yTjg4mGesHY8kWVkdg6S/kwg8m4wnEoI8tIrICJy3AVUALzgqmHHgDZ9UxT0TuAZ4DLgWKgX/kemyW7JMvq6B89WN1BBZLEGP7SBEJA0fhpE6+Sym1U0T2AHZk0Uz4BBxF/1qgEFgJnKKUWg2sFpE5wB3AcJxJ59j+YqLc18hXZN589TOptpKFqzvivlodgcVing+mBngS2Mut82+cuGTfwllFXJSNwbhbY5/v5PN7gXuz0Zele8nXG3+++rE6AosliOkK5hfAa8BkvJ77/8QJhGmxpEW+3vjz1U9hqMDqXCwWH6YTzExgllKq2dGtJ1gD1GR7UJbM6A1ez/l6479o1kgeXrI+YcF24ayRadU39eTvadfXYukJmE4wRUC7Rj4MaMzecCzZoDdkHszXG/85d72S8LD/eGcL5971Slqe87prmezJ31Ovr8XSEzB97XoWx1Q4jhKREHAV8FTWR2XJCGvR1EGmnvO6a2mvr8VihukEcyVwvojMByLALTgxwg4Gcm7CbEkP6/XcQaae86ae/BaLJYipH8zbIrI/ThwvcDzq/wn8Qim1IVeDs3QNa9HUQabZME09+S0WSxAjT/6+ivXkt1gslvTIRTTleGiWvYBqghktX0xrhJa8kwvLskza7E5Lt3T67g0WeRZLT8XU0XI6cD/OBCO+jxVOBGRLDyYXlmWZtNmdlm7p9N0bLPIslp6K6QrmDpzQLKfh5Ibpv/tqvZRcWD5l0mZ3WmKl07e1GLNYuo7pWn8k8B2l1KtKqfVKqQ3Jf7kcoCU75MLyKZM2u9MSK52+rcWYxdJ1TFcwC4FxOMEnLXlAt/evy+euy02v0xGcPq2G3y5YhcLZ4/zqtBptrvvSSJgtDc2B3DGlkXCg7NkH13LHs6uJtSvCBcJZB9eyoykayP3S2tYeaE83HiDlmEyuj6lu5Gsz6rjnxTWJ8Zw3oy5lm7qypn33tYjRvVXnZuk+TPPB1AF/BP4OvE4w4djLORhbzunJVmS6/CK6fO663PQ6HcHoqx8j1t5xr8MFwn41Fdr88OOvmedJsVwaCTF2WHmg7PKN9YFy5cXhQG76+uZYoFw01h4Yz8rrj+XE214wylmfSf6V6dfPD4xx0dVHaNt8aMn6QNmTptQY9Z2vHDG9oR+bL6fvkAsrsuE422S/0Xxmlfw5wDSfuy43vY7kH/P4cSov9+TJIH6sK6sr1xLzRhTa0hClzde3v17y+Ew97zPRjWxpiGqPdW3qyurK6d7Q+1rE6N6qc7N0H6Zr1DuAt3CCXo7ByQkT/7NeZjnANJ+7qY4gXCCB41Re7qUR76RVGglpy+rK6XLT68rpxgPmnveZ6EZ0Y0zVpq6srlzc2mzh6q3cvmAVtz65Im/6m97Qj9Vl9U9MVzAjgROUUlYHkyd0HuS6fO6pctP7ef7K2cy4cUFCX/L8lbMZWBLRerk/O3e2VgfjL9sYjQXKFYYKjHQwsbb2wHjA3PM+k2gFT1w+MzDGVG1eOGtkoGxpJBwod9YfvLvEyz7Yzj3nTcuLx3++Ijdk0o+NLtE/MdXBzAduVkr9J/dDyh89WQdj6V1YHYOlv5ALHczvgFvdzJY6Jf+S9IZosfQt7Bu6xRLEdIL5q/vv75JkcQtTq+S39HtsRkuLJYjpBLNPTkdhsVgslj6Habj+d3M9EIvFYrH0LdKJplwATAT2xEk6lkAp9bcsj8uSB1J5V2fb6zoX0YszKQd023gslv6EaTTl0TgJxsbToXuBjqCXdoLphaSKFJztCMK5iF6cSTkF3TYei6U/YbqCuQVYCxwJrAAOAYYCNwGX52ZollyTyrs6217XmUYvzsRLXlfOb5mfjWjK1lPdYgliuoY/GPi+UuojnBfAFqXU08B3gZtzNThLbknlXZ1tr+tMoxdn4iWvK5eLaMrWU91iCWK6gokA8VeyrcBuOCuZ94B9czAuSx64aNZIHl6yPuGlfuGskQBccthoXlq9NRHR+OLDRmvrm+o30vER0ZXNxEs+Vd+ZjCeTchZLf8LUk/9l4Bql1DwReRhoxlm9fBP4glJq79wOMzf0d0/+VJGLTb3SdeWS9Rud1U0H6yVvsfQccuHJ/2tgd/f/1wFPAqfiePSfnfYILT2CVJGL86XfMMWuDiyW3ompH8y9Sf9fKiIjgQnA+65extILGVVd5lnBxCMXT6qtZOHqrQl5Z3oHfzkFRnXTwXrJWyy9E2M/mGSUUjuBF7M8FgBE5AjgJzgTWDPwN6XUHPezs4Af4uSneQOYo5RanItx9AdSRS7OVO+QyWrD+pNYLH0HIx0MgIgcCByBo+D3fOOVUpdmZTAis3H8bc4H/o3zWzVeKbVERGYAjwMnAs/g6H++BeztTnhp0991MD0Rq2+xWHo2WdfBiMilwC+A9cCHdDhY4vt/pvwU+K1S6sEkWTxS8wXAw0qpJ9wx3QRcjDPh3JPFMfQIsp3//OMdjRz6s2cSXrLPzZ3FbhWl2j5eXbmRk+/sWBg+eP4B1A2rNMrpsr2hmaN/tTBRd94lB7P90xZO+2NHwO0HzptCWXEhn79tUUL2yJzpTKitYuGqTZ5zWbhqM2s2j2D2zc8lZAu+dSjFkbBR38MHlwXyuTRFY4G6wypKWblxO0f84oVE/fmXfYbiSDhw3cKhgkD9kkg40E9hqIDT71yUsMa7383fY3pfdzRFs9qm7rnY0RQN3NeqsmJjC0FTWb5Woabfm8ZoLHAdSyNd2tCxdIKpFdla4Dal1I05G4jIAGAnjhHB8UAt8CbwbaXUqyKyDLhbKfWLpDr/B6xSSl2RRj9DgCEAEydOfHfZsmVZPIvske3857cvWOV5ExDgIlfu76PuqkcDbZZGQp5Ux6WRENFYuycVc7hAAqmZ02HNDcdp+9bh7ytV37sNLOLjnS2e460N0UDdldcfq+077vmffBzS9D2kLBLoZ0RlScBKb/rIIcb3dfr187Papu65uPvFNYH7+vaPjza2EDSV5WsVavq9SWVBadk1ubAiGwz8vetDMmIQztbbBcAxwHLg28BjIjIGKAd2+OpsBwam2c8lOHocNm3atIui3Ue285/7f3pVmn0k/wjpjoGMJpd08feVqu8tDdHAcZthXQguz1WKvnX9NPmu0arNDRSFvZktOrvm2W5Td79T3VdTC0FTWb4wfaZTWVBasovpuvVR4NBcDgSod/+9Syn1ulIqirNlVogTmqYeqPDVqcRZ9aTDr4CxwNjq6uoMhptbsp3/XHxlJM0+SiOhwHG4wNuq/7gr6Mapw7TvqrJI4DidcevGo6uv62dUdZlHNmpoWVrXPNtt6srp7muqspnI8oVp37rraMk+piuYp4D/EZFxwDKCGS0fznQgSqkdIrIGvU5HAa8BU+ICERFgEpBW30qprTjRCJg61WiV1y1kO//5V6fVaHUwuj4ePP+AbtHB4I7LP85YW3vOdTDg6FyyrYPxW+kVhgqM7+sTl8/Mapu65+K8GXWB+5qqLOgtBLNtSZgJpt+bVBaUluxiqoNp7+RjpZTKSkZLEfkOjnXYUTihaK7ACaY5DtgPmAd8EXgOuBT4DtaKzGKxWPJGLnQwJRmMJx1+jqNreRooBpYCxyildgDPi8gc4A46/GCO7erkYum/WF8biyU/mHryt+y6VOYoZzl1jfun+/xe4F7dZxaLKTZ3i8WSH1JOMCJyEvBvpVSr+/+UZEPnoGXDAAAgAElEQVQHY8kepv4TgNYXQPeG39rWnlX/C9D7Spj6J2SSqfLVNdu8x2u3BcpYLJbM6WwF8yAwDNjk/j8VCsiKDsaSHY669dmE/8THO1s46tZnPf4TS9dt54w7F6Hc/yfLHp7zGe0b/sLVWwNlk/0vspVV8vQ7F2nHlEmbftZta/Qcr93aGChjsVgyp7MJpiRpayxfOhhLFjD1n/Dbd8R9AZas/cQjX7LuE1Z+XO+RrdxUn5H/RSpfCZ1/gmlGy3Zfo0vX6cfT2BLr9DhbZKrrsboiS28n5QSTrHfJlw7Gkh2qfF7lVWWRgAf4qKFlnhVMXAYQbfMaDUZj7ZQWhalv6ZikSiLhnERd1kV41q1WdG0mHwO0xILOoEDgXEqLchMiJFNdj9UVWXo7xt8sEZmJE/trb5wkY+tF5BxgtVLq2RyNz9IFTP0nAK2sKOx9Sy4Kh6gbMsAzadUNGWCc+TIdnwqdf8LX7vaakqfKaLn4zkWecpGw/m1fdy65IJNoDNmob7F0N6bBLo8H/gY8AOyDk0IZYABwFWAnmB5ERUmERVcfEZDrdBk62eTaQby0elvSsbPiWPR+h+yAPQfxq6dXevQlv356pfYNO1U+F52sNBIOjEm3WtG1OWXPQZ4xTqkdFGhfV+6APfXlMsV0hZer+hZLd2O6grkG+IZS6g8i8qUk+YvA97M/LIspudinN11xnOFbMSxZ90mwsSyQaX6arpbL17hzVd9i6W5MPfk/xcnLslZE6oGJSqnVIrIX8I5SqjjXA80FfcGTvzvzp9iItBZL/yMdT37TV92tOOHz/UwFPjAdmCX7dOc+vU5XY7FYLHFMJ5i/ADeJSA2Ou0FYRD6LE9qlzyX76k10Z+TayT4dx+RaqyOwWCwdmOpgfgDcB6xzj9/G2ZL/K05IfUs30Z379FZHYLFYOsM0FlkU+LKI7AMcgLPyWayUeiuXg+trZKqQ14VRKQwVoAClOvIcmIaKWbFhGyf87pVE+/+88EAm7VXNSys+CoTXDxdIIIT/9uYYt7n6nxdXbWVKTRllkVCgbqxdccbdSxOy+86ZzLDK0kBo/NHDKrVpiwEjWUNTNHA+sbb2wLjLSiKBsP7jdh/Mxh2NgTD8A0sigevW2tYeuL5AQFYaCQfu99aG5kAfQ8qKtc/FlobmQCj9ipJIoGxjNGbUt2kYn3RSOFeURALldM8p6MMS6TAdU7bLWbLPLpX8IlIEvA6coJR6Jy+jyhP5VvJnqpDXKdV16XIfWrLeKNXuEo2nezppi7NNd/c9+urHAqmQ96upCFy3DdubAtcXCMhOmlITuDe/f3Z1oI8LZo7UPhfjr5kXSGd89iF1Rvdb17dpGuV0UjjrzOF1z6nfqbczgxDTMWW7nMWMrIbrV0q1iEgFoHeLthiTqUJeF0ZFF65FFyrGHw5l5SZv6BeLPhWy7po3tHi/Cv7rHZfp7reuj1TPhS6dsa6s7n6bPmvpPJO6fnTorlmqsESZjCkX52jJLqbrxHuA/5fLgfQHMlXIm6bL1aXa9YdDKUmxPdGf0aVC1l1z3fXVyXT3RtdHqudCl87Y9H5nkkY5Fbp+dOiuWTopirM99u40hOnvmP7KlAOni8hhwCuAJ/ysUurSbA+sL5KOUly3b3z3uQd69sDvOvdACkMFgXAtF84aGdgr//q9iwPhUW4+aXxANwIwvrqYtzc1J+T7VhfznaPHcc69yxKyu8+aRHOsnYv+/HpC9tuv7k9ZJBRoM9auAnWHVZQE9CDgpE72p1IujoSNdDDbG5oD+hYgICuOhLXpmp+/crZWB+MPXZOODsZ/v886uFarg9E9F8/Ona3VwfjL6u63rm8d6TyTuhBEOlKlIzZNUdxbHWstQUwdLRd28rFSSh2SvSHlj57saKnbN04OR9+ZzHQfWrd3v+jqI7R76Dq9g26f33SMqcadifOm3ZO3WHJP1lMmK6UOzmxIlnQxDXGfKuy9H91b3O+eXe0pE99T1zlQmu7zm44xnXD9ptg9eYulZ9GpDkZE2kSkOl+DsXSg2zc2lemIB4f88wUHMffocRSGClLuqescKE33+TMddzp79X7snrzF0rPY1QpGdvG5JUekE+K+q/vLqfbUdX2b7vO3trUHdEKFoYKMwvVnes26Ws5isWRGpzoYEWkHhimlNuVvSPmjJ+tgeitWv2Gx9G2yrYM5UEQ6jcOulHrRaGSWjNBZlgEBWWtbu5HXtM7jOpV3ta6szppq0ftbPPUWvb81J57dmZx3LlIZ68aTC2/x/uCVnsk5pvNM56K+xYvJCkbR+VaZUkr1yjC6vW0FY2pZtnD1ViNLrHQstkwty7Y2RI284TP17M7kvDNdZZmOJxcrt/6wQszkHDNNIWFTUOyabK9gpgObMxuSJRuYWm2ZWmKlY7Fl6tHeZugNn45n91JfIrOl64JWX+mcdy5SGZta82VKf7CAy+QcM7FCzEZ9ixeTdec6pdTazv5yPkoLYG5ZZmqJlY7FlqlHu877PFPP7pZYu++4LaPzztSKLBNrvkzpDxZwmZxjJlaI2ahv8WI3F3sRppZlF7e1G1lipWOxpSur08G0trUHvM9LI+Fd1r3r3ANT9h3x7b9HwgXaa2F63rlKZdwb0jD3BjI5x0ysELNR3+JlVzqY94GpSqmt+RtS/uhtOpi+RDr77P1B72Cx9BaypoNRSu2VnSH1P3Jh7WNqjaWTFYYKjPKIVJREtHk/IBhrS5cLxNTC6qXVXrXeS6u3pDxH3RttJtc3Vd3utA7LhP5gWWbpnRjFIuur5HIFk4u3btM8GzqZad6YRVcfoc37AcF8J7pcIKYWVrcvWEXykyfA+zccZ2zFk8n1TVW3O63DMsGu8Cz5JOuxyCzpY2L5lC6m1lg6mS5vzOb6Fo8sfmyS9yNVLhDj+GS+evHjfFiCparbndZhmdAfLMssvZMeuY4WkQIReVFElIjUJMnPEpFVItIoIotE5IDuHGdn6CyfMsXUGss0b0xxoXfSiR+b5jvRYWphpcuLAuZWPJlYGqWq253WYZnQG8Zo6Z/01BXM5fhyzojIDOB24ETgGeCbwGMisrdSamf+h9g5OsundNDtq99++mRPLpHbTp9MczTG7JufS9S75ZT9WL+1wZOT5YrD9mJbY6un/XHVJQwtK2Ttto6Jr7qsEICjRg3mT0s/SsiPGjWYSGGIP7y8PiH7/Lih3PTIm/zm+Q4r9W/M2JMVG732IO+u/5iRVd7gma3NUc6cMoK7Xt2QkJ05ZQQAx4yr8qz2jh5XxQ//tpR7lnyYkJ09ZQSTRnrb3LuqmOsefs0zxq9Nq2HMiHKu/GdHpu8bT9iHz9QN5PakuofUDQRg1sgKbl/QIZ85soJwgXhkh42uZN7rHwTy4FQWhzntj0sSsgfOm0JzrD2QB6duaLnnfi341qHE2toDuW1GD6vkzXVbAnlrhg0uC1jpnT6tht+6W44CfHVaDSs3bg+0WVYSCeSiCYcKAu1VlRWzflsDh/7smUSbz82dRXlJxMhqsDkaC9TdraLUWE+UbV0jBPVoO5qi2vPW9a1rUzd203Gbtge9X79mrIMRkSOBS4DRwOeUUh+IyAXAaqXUU1kbkMgY4D/Al4ClwB5KqfUicg9QoJQ60y0nwFrgB0qpe9JofwgwBGDixInvLlu2bBc1ukYuvMV1OhOd57w/LW86rLnhOOquerTL9TOhv/atI9V4SiMhTyrl0kiIaKzd6Bnwy8MFQiRcEGjv7R8fzV5XPRrQkVUPLAo8f/XNsUD9pmhboO5Frt4tTmffh2zrGnV6tLtfXKM9b13fujZ1Yzcdt2l70DP1a1nXwYjIycC97t+RQKH7UQj4DpCVCUZECoA/um36N5InAnfHD5RSSkSWuvJ0uAT4IcCmTbmL4Zmpv4Jp7nWd57yl75L8o6g7htTPgF8ea1fEUrSn05GZPH+68SjS0xNlW9eo06Oluo66vnVtZjJu0/ag9+vXTNdaVwP/Tyl1ERBLkr8ETMrieL4JbFRKPaz5rBzY4ZNtBwam2cevgLHA2Orq3KW60eVfSQfT3OupdBmWvokuUoLpM6Arp2sPgsEHBb1uTldfVzcdPVG2dY06WarzNm0zk3Gncy16u37NVAczDligke8EsnLGIjIa+BaQaulVD1T4ZJXAKk3ZlLhOo1sBpk41WuV1C6Y5WZqiscC++pqPdwT0AVsbW/nGA28kZL85bT92NLZy9b+WJ2TXH+8svb82rSagyyiOhAL6lrZ2xW9fXJeQXXRILas2f8KT79UnZEfuXc6ooYMC5SLhAn757JqE7NKZdQBce+wYrn1sRUJ+7bFjeH9jg1YHc/mDbyVkt568L2+u22Gkg9lzcEng+gA8eP4BnHzn4oT8wfMdGxK/bEtja1Z1MN98YBmvbei4ZpNqygFH52Kig4m1tQeegYamaJd1MODoTbKtgzFd0afypjeRmeYeOm9Gnfa8dX2narOr4zZtD3p/5AYjHYyIrAHOVko9IyL1wESl1GoR+QpwrVJqbMYDETkH+B3ORALO6moQ8AnwfZygm6KUOsstL8Aa4Jp0dDDJ9FVP/nzt23bn/nBfOseeuM9usaQiF34w9wE3i8hpOFuqJSJyDHAT8OuuDTPA34D5Scc1wELgKGA58Dowz1X2PwdcChQD/8hS/32GfO3bduf+cF86x97+lmqxpMJ0grkWqAXiexfx/YF7gJ9lYyBKqUaSTJNFJD62jUqpBuB5EZkD3AEMB94Aju2JJsrdzaTaShau7jAXzmVk33z0051956OfuL7OYulrpBUqRkRGAlNwtq+WKKVW5mpg+aCvbpGZxhIrDBVkPfsfmPkrZJq9EuDWJ1d43vpzkfXQZji0WLyks0VmY5H1wQnGNPvkiMqSjLL36XQHuqySuchemckbfzpZC61+xGLxkhUdjIj80bRDpdR5pmUtQUzfkk1XJu99XO+pt+Lj+oDd/+b6FnY0eGORvb3B+dHVeYEXR8IBy6AFb33gqf/ftz9g3faYR/buxp049hgdvPdxPcs3bOPoXy1MyOZdcjDjdh/MS6u8UZYXrt6C35lg4arN7GgKWtR9sHlnwOpqj6EDA+Xe/chr7b7cPV6zeWfAwuvVNds8ZV9Zsy2jlZtOlsqz23Q119rW3uVVVi4iS2fqfZ5J/Z624uxp48k3KVcwIvKkTzQNx7HybZzfmHFAG/CyUuqoXA4yV/SUFYzpG7VplOPk4zgCAe9q3Z1P5UFuWj8T0vGm959nqvM2LZeO5/zYYeVd9jRPx7PbdDWnWzWarkRzEVk6F1EsTOunszrNBz1tPNkgKysYpdSRSQ1eDjQDZyqltruyShwl/7OZDddiGkE4kyjHmU4QqaIfdxcm1yKdcqloaW0LHPvv18pNwfuVqfc5mEd3ziSPfC4iS2dqeZdJ/UyuRS7oaePJN6br1iuA78YnFwD3/993P7NkgGkEYdMoxzpP6mKf57L/eFfo2swXpl7lOkzLpaLIF3G6qDBEie/alURCWfc+B/Pozpnkkc9FZOlMvc8zqZ/JtcgFPW08+cZ0M3Aweo/9yhRySxqY5gF/4vKZRjqY+qZoQF9y2V9f59W1HTlq9h0xkO99bjQn/O6VhOyfFx4IODoXEx3M+i31Ae/1YYMGBPQYQEDWHI0FdDAAU2orWLKuQ0cypbaCX542ycir3FQH89G2Bm3fC751aGCc33noTV5Z471uIt5tybohA7jr3AOz7n2eyj/GL7u4rb3LeeRT9WHadzptZjomE0y/S/mip40n35h68j8E7Av8PxznR4CDgNuAt5VSJ+dshDmkp+hg8kFv2QvuaVZbvTXLpcWSK3LhyX8hjr7lKbzb74+5n1nygKl1ja6cLj9NT8w1Yfr2mknejmyMxy/L5N509zXPhP5uJWXpnHQdLfcG9nEP31FKvZeTUeWJ3raCMX27N33r7s1v4pnk7cgFmdyb3nLNdfSWlbEle+RiBQOAO6H06kmlN2NqXaMrd8950wJv3Wf+YZGn3NJ16Vn7dCeZ5O3IBZncm95Mf7eSsnRO712b90MyseLR5adpibV7yrXEgsmieiqZ5tnINvmysOpp9HcrKUvn2M3SPJKp1/RFs0by8JL1CYuoC2eN1OZOP3x0ZSCP/J9fXBXI/fLBR9635/jxt+5bxENvbknIvzShinBBAX99vSMD6Kn7V7O9uZnHV3TEGv3cmIEMKysL5G5piEYD7QEB2c1nTOfXT7zDz59enZB/+7CRvL9pZ6Ds1BFeZ8cDRpRTEPNGEZBYjL++tDqQD2bDtqZALporjt1Xe40qSgsDeXTa2hWX/u3NhOyXX57ArJEVnms+c2QFy97fFLDSO31aDb9dsCpxv746rSZlVANdZIHtDc2BNptb2wLWfKNHDDLK0wIEZDWDy7TPVXM0FrAuvPWU/TxjvOWU/bR1tzc0G1n4VZREtOddNzSYV9D0e7OjKRq4FqWRcNbj4/VmXVqusLHI8qiDydRrWuexvXTd9qx62Hdnbvr+0He4QDypi/3H2RqPLgJBU7Qt8KxA0AH3/RuOY6+rHjV6rnTn09aujOrqoiwsuvoI7XmvueG4gMz0e3P3i2uMojF0Z3y83kTOdDCWzMjUa1qb89vXR/99Xegd+CcT3eSSDVLlnE9G17NK8VmqUZqcT6q6mUZZMP3e6K5FOrqjTKIa9HeM1nQiMkFE9kk6PlpE/i4iP0rK22LZBbnw2O5OD3tL+oQLpNPjbKHLOa97VlI9P6bPle58TOtmGmXB9Hujuxbp6I4yiWrQ3zHdNLwDmAggIrsDDwNlwPnAT3IztJ5Ja1s7N85bzld+/xI3zltOa1u7tlxjNMaJt73A/tc+zom3vUBjNMYVR45hzuxRHDJqCHNmj/J4TfvlF80ayW4DiwgVCLsNLOLCWSO5//zpTKmtpKIkzJTaSu47fzr/dT3l4/z3W4dy3zmTPbL7zpnM1UeN9siuPmo0p+w31COLHx83zvtlOW5cJSfuO8QjO3HfIRw+2vulPHx0WUK/EudLE6r4wj6DPLIv7DMI/9c5fnzBQXt45BcctIe2/kWH1HpkFx1Sy6Uz6zyyS2fWceMJ+3hkN56wj7YuwLXHen1urj12DL85bT+P7Den7ccvvzzBI/vllyfw4PkHeGQPnn9AIjJCnH9eeCDPXzk78aMcLhCev3J2IpJAnPjxpBqv3mHyHgO1bT5w3hSP7IHzprh6BueHNa53eG7uLM8E8tzcWdrnB/czf9n5l3m3kOZf9hnt+ejafGSO14P9kTnTeeLymZ5nPB6ZQteP6fdJJ9NdC913KRWm/ViCmHryfwIcpJR6V0QuBk5WSs0WkcOBO5VSe+V6oLmgKzoYUz+GTP0DTOvrxvPQkvWBve365lhgH1q3bbLmhuMYf828QNny4rBRPhmdTqhas9e+tSEa2Ltfef2xjL76sYB8SFkkUP+kKTVZj7jb03w68jGeXPjl5CKaciYRoy3ZJRc6mAgQ/4Z/Fohr4VYAw9IbXu/G1I8hU/8A0/q68ej2ttt8e+O6ySXVZ43RtoBJ85aGKE2+cql0QibjiU8quj19Xf1cRNztaT4duugL2SYXfjm5iKbc0+6NxQzTJ3YFcIqI1ABHAP915cOBT1LW6oOY7r1m6h9gWl83Ht3etm4fOhW6sro2TXVC6YxHt6evq5+LiLs9zadjyp7ercEptYNSlOw6udAl5CKack+7NxYzTLfITgIewEk49rhS6lhX/n2crbPP53SUOaIrW2Stbe1GueAbo7FAFNV0YjTpsldWlASVoLpYUK1t7YG6TdEYM25cQKxdJfbKm6Mxrb/BlobmgN9AYagg0GZrW7uRr4Uu8rFuPMMqSrU+FLr6pZGw0X3QkeremF7zfGH6rPW0PjJtU1e/VRMx2sY86x7S2SIz9oMRkd1wViyvK6XaXdl0YLtS6t2uDrY76cmxyLId2yoXe+2Z6AjS8QnqafHELJb+TE78YJRSHwMf+2SLUhS3pIHOU9ifC/7Vtfpc8MFyn2jfxF9Y4bl1vPDex7w6upKT71yckD14/gFMHT2M+W+u5/z7XkvI7zxjIpt2tgS83N/Z4N0rf+fD7dzy2FsBL/lpIwdxxt1LE7L7zpnME0tXeeo+vnQVc48exyNL1nrkjyxZy95VxVz+4FsJ2a0n78vQskigzW2NrQEP+9JIKHAuZZFQwPP9oDHDeWnVZk/fC1dt5s11VQEP9Ibm1kD9mqpyIy953WoMgjl9Kkoi2kgAwwaXBVZ+QEAWDhUEVpdVZcX42bijUbuS1KErO6SsOPDstra1B57TnU1Ro7qpIlvo2tStYEy97lO1l0mUbtPI0plG1O5NEbnTWcGMAb4E7Imj9E+glDov+0PLPT1lBWNqCaaz2lq+sd7I4kuXh15Hf/Cmz0XfupTUaGQ6izrA2KNd5zkPBGSRcEHguXj7x0cH2tNZ7a28/ljtOerKXjBzpJHF1+vrdxjVTbWKNbUiyyQqRipLQtMo3ZlYfmZqZZfPlXbWVzAicgzwT+AdYDzwGjASRyfzchfH2e9I9eaxZK3XTmLJuk8CFlpNGu/jlZsaaPbljG9ubQvkkd9Sbza5WLqOied7Kos6/0ve5k7ul4nnfKxdETPw5O+sPd2zqiu7dJ332V26Tm/xpaubytpM930wtSLz11289hMKxGs40plVWiZRujOx/EyH3hSR23Rd9WPgRqXUJBxz5VOBWuBZ4P9yNLY+xy1PruD2BatYuHorty9Yxa1PrgAg6nPWjMbatXnfdbJiX8744sIQ/t+cHEUjsSRh6iWvs4jz/wD6j5PRWdnpZKZWg6kiC+ieVV1ZXURuU+vCVNZmuu+DqRXZmq2fBo7TsUrLJEp3Jpaf6dCbogiYTjDjgHvd/8eAEqXUp8A1wLdzMbC+SKo3jyKff0NROETtYO8++J5DStlziFdWN2QA+wwv98jGjyjH//skAkU+WVEet2wLfceRLERHKfH9XpakWIuPGewtOGZISOv5DhDyjSskaD3n/X2VhPWe7zqZzntd9+IAMGFYiUc+YXip1nNeJ9N5r+vQ1QX9s6orq/PV0XnJT9rDG5VgUu3AlN7wuu+Dqed9Y4s3onZTCo//VO3p5KZe+6ZjzDQKQG+KImCq5G/E2Q4D2AjUAW/hTDbV2R9W32RSbSULV2/tOHbfPCbXDuKl1R3K+sm1lSjglTUdy/2pew5GAS+/3yE7YM9BKGDx2o4fg2l1Q/hgW5NnT39oeVB/s2+NXn8Den1CiWF03pBGRzChpsLT94Q9KtmwvUmri9DpGHT6BH803H1G6KMIHL5/HSuS9quP2K+Og8YM10bnrSr36keqyot4/F2vEcUT725jnNtXct81g8t4X9OmTrbo6iM8x6Oryzzt7e2+CR86bgRvbuwY+8yxwxlWUarVkehkOp2Ln1Tt6Z5VXdkpew5i0fsd12hK7SBKI+GA7uGgUUNZ+kFHaoeDRw5N5Cjyo/s+6NrUMXo373Mxurpc209hqEDbXqp+THQcpmNMdd6mZFo/n5hOMIuBacC7wHzgp67T5enA0s4qWjpIld/dNO+7qey8GXUeC6JHL51BaSQc8CM4+48veyaxfUc4b5nPzZ0VsH4Khwo8VkBPf2smF977Kq9tqE/Un7h7ORISlq7r+CHZv2Yg950/PdC3zlcHYP7lMzy+OfMvn0FZSUSbz8Pf5rrNOz15Vf5zycGMGlYZuD6prH2euHxmYEwX/anDWgy3nfs155MJd597oKffu851Vk2pnot8YNp3tsulW9ZPtu+NJTNMHS0nAwOVUs+IyGCc7bKZOBPOOUqptzptoIfSU6zIsk0ufGN0ZX//7OrAamM/32olVzHYdEy/fr7WGiuTPvJhsdPdVkEWSzpk1YpMRAqAHcByAKXUNiAnnvsicqPb9h5AA07MsyvdPuNlzgJ+iOP0+QYwRym1WNNct5KOrbqurGkWPp2Nvs43Ruedr8uuCGi96Z9/9yNPm8+t+EhrGRRrbfXKYq3aFcO2hmZtJkWdpZzO/0Ln56Gz0NJd25Uf1/v6cI51/kO6LKLZznCos5rKF73Jp8LS+9jlCkZEQkATsK9S6r2cDkbkeuDvwJtAJc5KKaqU+qL7+QzgceBE4Bngm8C3gL2VUju1jXZCLlcwma4OTLPw6Wz0dXWBgCwaa9f6QJhmMzRlcm2lUdTl91NEctaNU6eX0ZXT+VrofIwWXX2EdgWk8z3SXfNMMhx2ZxRnu3qypEtWVzBKqTYRWQ1UZDyyXfd1ddLhZhH5NfDnJNkFwMNKqScAROQm4GKcCeeeXI8vHXRWOKn2/hev9a44Fq/9RBvR+N2Pdnhkyz/aQX2j12fiybc+NMpmqJPFf5yznSVzqe9aLFkXtNuP92EydlM/j1i78vx4Aty2YBV+g92t7qTid0b9eGdLQLZk3XbW+Mb/wDOrKC332sr9a8k62qOt/PbFdQnZRYfUsl9tBd944I2E7Den7ccn2733ddt2513p7mff49rHViTk1x47hkl7VAS8+9/f2hiIdLB3dVkgAkFzNBaI3PDE0vc9fT+x7H3mHj2O55d/GIiU0BxrD0RFqCwOB9oMhwoCY9ze1Mo59y5LyO4+axI1gwdwxC9eSMjmX/YZRg+rZM3mnYEYecWRcGAVu72h2aNzm3fJwVSWFRtFDNDtEFSVFRvvJlSURIyiA+h2GEzLFYYKjCMLQNdX0LnEVAdzKnAhcIZS6sOcj6qj31uAA5VSh7rHy4C7lVK/SCrzf8AqpdQVhm0OAYYATJw48d1ly5btokbXSMcbWffmbOp5n216szd9b+1bR3+9Fqn61lkX6pxMdeV0q1jdKv/tHx9tvJtw9iF1Rt9v3WrXtNzco8cZRxbIZAWdLrmIRfYTYASwTkQ24pgtJ1BKZd28RUS+hLNimZUkLsfRByWzHRiIOZfg6HDYtGlTJkPsFJ0lzH3XPTWUQHkAACAASURBVOkpE/f01XnthwTakr4//mOLpT9hEsEgVTn9boJ+BWxa1jRnjS4KQDrRAkzL+tcJPcW733QNdR/wM+A6nPTJ9/v+soqInOL2c7xSKtlOtJ7gVl0lkI7+5VfAWGBsdXXuXHjitup/vuAg5h49jsJQgbH38OjqMqrKizwy/7HF0p9IFXHApJzO8z1VpAPTsqbRATIpB+aRBXqqd7/RCkYp9aNcDySOiJwL3Ax8QSn1gu/j14ApSWUFmAQ8bNq+UmorsBVg6lSjVV7WSGWjr5M3RmMBX5aN2xoC++qrt3waiCC8rSEa2Lt/Y902HnpzS0L2pQlVrNm+ncXrOzyfD6hxHoexlfBu0gvQ2Eqor4cPk17kRoQgEoE1TR2yuhLY0ATJdmSFOMvOZC3TYByl/tYk2RD332ogeV1ZDRQXwbqkHcPaIhhbW86T73VYgx25dzlvv1/PhiRH7t3DUFUFr23skE0cBtEovJM0oH0GO/9+bsxAHl/R8a7yuTEDibW389TKjrfIw0eXMaK8nD8t7bCqO3PycAaVFwWiSEdj7QEdzFPvbeG9zR0bAHsPLeWs6Xvwg0c6Ml5c9/mxAPzg6L25bl6HXc0Pjt6biTUDAzqPD7Y3d1kHs2pLI1f+852E7MYT9gEcHYlfZ9Ica+eiP7+ekP32q/tTVVpopIPZ8mk0oL+pqyoL6GDA0blkWwezK1+xeKQD3c6DrmxFSSRQ7mJNzprCUEGXy4H+tyFV2e7ymeqMtDL2iMhncYJdAryplHomm4MRkUtxtq8+p5R6RVPkDmCeiNwDPAdcChQD/8jmOHJFKk9fnfxXT69MLM0bo2388fk1AWX7Y29vYe7R4zh+yp4e+Y3zlnuONzW2UV1VAXRMMLtVVVBdVcHi9R37ttNHO+0cNmkU7ybt5x4+ydk3/jBpW2DY7k4kAOiYdTa1hSiMQGvSlkJhJMSpvv3q09x96K1J7e3pvoHtXlvJpiR5Ta3j9U9LxwzTUlTElhbvW+XWlhCx0iJI0l3FSosoiJTg7KI6hCKVFEeAbR2ykjKn703N3gX95uYCpo8c6plgxtbsxtyjx3HdqZ6igWseKwhx1fH7ctXx+3nki257geQd5vKSCB82eMObfOQeb2n2xuTa2tzOUyu9Wx9Pr9zu7NVPrcOPLlqBX/bUSu+41253TL0XrfOacr+8rj7w/L3+4afMPXqcUT/+67NkfQNHTKjR1q0bOlAr90cRGFZRalQOgp74VWXF2kgHOi/5VGVNowN0tRykF1mgJ1r/mUZTHo6zSphOx4vnEBF5CThJKbUxZeX0+F+c8DP/laSAWkqpMvff50VkDs5EE/eDObYrJso9Hd0er+k+q2nddp8wrkzU1ff7jrz3cb2xtZou4u57G7237L2PnWOdH8ynvna3NEQDMadWbqrn0xZ/uZaAfmvlpmCE284i6YZ8Wy6v+iz+4phGuNXF7kpVN5NnwNS/JZ2+Uz0vJvSWCMDWLyi7mF65/8XZ7RivlBqqlBoK7IMzQf2i05ppoJQSpVShUqos+c9X5l6l1EilVIlSalpPdLLMBpnss5rW1UXCTVXfb2DQpvT73br9al0/7b74um3KOdYFfgwGPyygtCjsKxemyBdZuiisj0CdTiTddds89iys3eo9jmN6b6bsOch7XDsoZd1MnoFUkbtNx53O82JCT9UR+DG9bhYzTLfIjsLZtkqsc5VS74rIJTiOj/2HaBRmzYKXXspN+yUlUFzM3JISvq7CNEiY8IBSdnthEJQUc1JDO1tahbJB5YzfsRs8WZqoQ0kJlJRwWWGE8KYNrGtsZ3BVBZcWlkJJMR+Gt7FyZ4xhwwZx8aTBvLbiI1CKePjlsBtOWOfhf+/CNZ5hFghM2L2MZR90rGz2272c676wj2fv/2/nT+UH//Zuj4AKvNnE56rdK4s9Jtq7VxYTjUZ5c2OHsmfkkAiF4UigXFtbuyc22pihpUiBeMqNqCzm9tMne/bpbzt9MoBWftjPF3jGWd8U1Xr8X3LYaF5avTXhr3DxYaO1Pgy6cqn21L82o457XBPZ0kiI82bUaff+dehWjTp04wG9LmLxnd4EtpGw+Zu9rr1Mo12YrizSqdtbVlq9BVM/mAbgYKXUGz75/sCL/lVGb6FLnvxr1sBee+VkPJYgDZES6iOlNEZK2FYykOf2mkxzOEJrYRGNoUKawxGaw0W0RpzjllCE5kJH1hyOEIsU8WmBU669IES4QBhSFjH25Nf5I/nluw0s4qQpNRn5O+gwja2mIxfZFbPt9Z+vvrvzHPsiufCDeQG4UUS+opTa4XYyEMc/5rlOa/Y16urg0Udh7lxoavL+tXSPc2RfpizaRFnUWb2MAg7c8HZuOvoeLNp1qU65MvngRuefmBTQXOhMdi3hCO3FxXyBcGJiLPxXCZtvGcLzGxodWWERh0+soXaPak5asCZRLl5/2W/W87PnNtAcLqKlMML3TtyfsoEDOO+hdx1ZuJC/fH06bW3emHBtbTFtPLoX39vsKffiys3AOJZv2Baw0NKtqFZu3B6wBCsriQQsuUoi4cCqL9VqQTfOl1Z5x7lw9WYao6MDK0QgINNFytDFtxtWUZpyRefH1MNe57VfGgn+7OZL95NvHZPpCmYfnK2wQcDbOJE9xgOf4Ns6603kOxZZKm9bXdnb3S2qOKlyvKPaibTFKIpFKW5toaitleLWFopjUYpjzr9FsdbE/4tjUYoC5ZyyRbFWvjh2EM+8ts6t15Kou9cn3mCXFksy7Uhi5RgNF9LkTowt4QgthUW0FxWxk3BisiwoLWHP3Yfw0keNNBc65aaP352jDqjjin+/y07c1WlhBCkuZocK01RYREuoMFF+/F5DWfpBh9/1FDePkn/lpss9tLUhqo3DZ7qCMfWwTxW9w0++Vk7Z6CfrKxil1DsiMhYn/8s+rvgO4H6lVHNao+sn6N7O2nxexovdKLrB6MfbjHO8IwXOlzgcYWdx5juVX7zhOM7uYWFCAFCKoliUwva2jomztWNiTJ5AA7JWd7JMmlSLEmWd8lOGFrPqg60UJbfT2kJYtevHY/FQgKK0tYXS1vRW8dOSD552/rkla6NKk586q1DdStRDURH3SHwSdf5ihUWEBpRycMz5PjaHIwx8tpy6qHCchBOrWFlSDGpZQl8a15+2zF/NxE3NibrrXm+DA4d26FcLsrPKyLeOydgPRinVBNyZw7H0KXQZAR9ast5TJp4/3NRSqV8jQkthES1AQ1HpLouny5objuPwHhKLLNTexqprDmPK1f/yTpat0cDKUjuptkYpaot6JuHiWJTitlaKNKtWZ/KN7XpgFoeWFgbSoo1PZbQWeDIoukZX7kqdMDP+4v7735EHMOeL3825NV+nE4yIHGLSiFLqxewMp++gs5r508I1njJN0Zj7bzAWmaVzdGmduzNU24RhJR5LtwnDS3nzo+CLwr7Dy3jro4ak43Le21hPNDnuXCgEZWVsKw0GMB8zOMSKbR3Px5ghITbU4/EVGhAJ8eglhwS84a/4++ssWZe0pbRnBa3RGG989GlCtv+IAfzr0tmM+96jNCc9hiUhCBeGqW/umIjKi8P846LpAR3M3Iff9PZTW4GIeFJ7T62rJAIseW9jYmI8ZEQptx4/jqvuW8Tq9VsTq819BkU4b0o1t/zrdQpbWyhta+Xr04ZT1BrlqSVraKn/lCGhdg4aMQBpamL5+5tQTY0MVDFqSgrYvnUHBS3NiYnVAp9dvZjrKjfzxRx7/O9qBfM8JKxV8f2fJJk/Anq/R+cRrMsXDo7/hVdepg1pr7Ne2rSzJfBDGzKMPNudlEZC2pw1pkzy5ZiZXFupvWa6fsqLw4HrmApddF5dLppDx43gzY0de9szxw7nrY+CerSZY3fzTDCzxlYTKQx5zmWC+1apG/vh+9exImkP/Yj96gL7/GOHlWu94aePrPL88B+0V5VnlQ0QDjtpB/bZ3Xt999k9qN/Yu7rMCa+/q35GVqHAM8FMqxuCAl5cs53mwmJ2UM7wA0bBfuMY9NlCXk46x9GzR1Fx9Dh+9A0CBP3rYV/f8R3dbRmmlOPekGwQ1Nys/382Ze2dbO+efDInf/ssyLET6a4mmGR7XMFJBHYssDZnI+rDpMq9rpOf/YdFLFvf4e0+eY+B3PSl/Txvi/efN5WGpqgn7tM/LjyQH/z7Hd74sONHbPywAZx1UC3ffrjDAuvnJ43n5/95m6SXboaXOP+GccIpxAkDZ0+r4Q8vd2zxfW1aDQ3NUf76ekfksFP3r+bR1zeR7A9fBhSXFLClqeNhH1oS4tLDR3vib333KMdaZ8QA+LDjhZrdB8AJk/fkN893PHLfmLEnY0d4J+tzDqrhxP13C8T0KomEPOf948+P5U+LPvBMMMMHRgAnhpc/pld5cdgTQ+u3X92fqgERzzX/87lTGDa4jDvcFNLhAuGsg2t5bsVHvPFhxypmvxEDOPvg2kC5Q+oGenKvXHGY87V74rIZnqyfT1w2g+JIOGDJdeGskYHnR2eJpev75TXeCSYeueCOsw7w1P/9WQfQHI15xvPL0yZqral0WUA/aWj2/Mh/+YARVFeUai22TLOI6qyfdOV0lmGp2sskW2m2M532BYysyBKFReqBiUqp1bkbUv7IpRWZjlQWHKa5Y15fvyPwNg1kdbXSE3OB9Ia+dasN00ycuhA7a244TmuppLOI0vngmGY11a3mFl19hLbv5RvrA/V1WVZ1lly6DKYXudaSyeNOJweKbhViar2ZjkWnaa6VTOr2JnLhB2PJAunEffLHrCoMFRjlxOhpW2H9hWxm4oyji43WEIi3Fk0r34lf5g/3E9f/6frWtakr539nXbW5QWsVmer7kE6+FD+m8dtSxXTLRwzA/kT/Wav1ANKJ+xRt8+6ftrb5o3c5b4GmeTIsucU0LluqPCQ6dLHRdHHZTHOY6GS6XESp+japP2pomVame3YzzYGiwzR+Wy7iv/WmPC35oisTjH1F9tHa1s6N85bzld+/xI3zltPa1q6VXXLYaCbXVjKwOMzk2srEnvOXJg3ztHfSpGG0Rr3+BNHWKCMHeRecIwcVcvbU3T2ys6fuzqF7lXhkh+5VwmdHDfDIPjtqAOW+8/AfJxPZxXFPRffDNsrnLhQ/HuMz2hpTAeO8sSkZNwiqfG1WASHfyjHcrjhmjLfyMWMGMWeGN7XCnBl7csxYb8fx4ynDvAOdPKyMsnbvKqKsvY0RZd7nYnhZmEtm1nlkl8ys47LZ3hBHl83ei6PGDPHIjnSPz5rmfa7OnLY7N5003iO76aTx/Oq0iYlrHNfL/PCYvT3lrjlmb2452at6v+Xkffnc2MEe2VHusa6+7juyZvNO6q56NPG3ZvNOzj64NjHZx/VMurpfm1GXmDDjuixw4vAln89Xp9Vov7c7mqJMv34+o65+jOnXz2dHU5SLZo1kt4FFhAqE3QYWceGskdq6jdEYJ972Avtf+zgn3vYCjdHUJuK6fnS/LT2VTnUwIvKET/RZ4CWgKVmolDoq+0PLPdnSwWS672tzwffvvnX0lmuh0z11tu2Xzb4zGY/OInPR1Ucw+urHAnqzC2aODHxvH1qyPlB/RGVJVr37QR+PTqdzy6deJ5s6mA2+4/u6NqS+jYnX/hJfdFtIL5+GxdITMdH15BPT8WxpiGqPdXpO3fdbV9/vv5ZKd6TTMaVC109vivjc6QSjlDo3XwPpzei89v3+BdFYe2BvMZ18GhZLTyTbK5hM0fkt6QxfinzWfHHdlq6+7vu9anODZ2VRVRYJrGDiuiN/3abWtkC5VFT5In9XlUW0bfZUrJI/TXT7n1ccOYY5s0dxyKghzJk9isuPHKNRxoYoDHk1AnF7+HmXHOyRz7vkYB44b4pH9sB5U9hriFe3steQEk737S/7j+McPrqs02OLXt9S573k1JUEdVXlwL4+xcy+VcEvV4jg/Tl90rCUOphT9hvqkZ+y31DOnDzcIztz8nAuOqTWI7vokFquPsobBfjqo0Zz3efHemTXfX4swzX6G4Drj/duuVx//DjuPGOiR3bnGRN5du5sjy7j2bmzefD8AzzlHjz/AH755Qke2S+/PEH7jIP++zCpxhuYZXLNQCbVeO/EpJpy9veV23+PCuZf5t1+mn/ZZ9hnuLdu/Pj/t3fmwXUUZwL/fe89nZYtWcIG20IStsMVwCDLGIPDsSGEJWR3U4QqrrBAhSMsx5oFk9rNVpbskoXsQW2Rg8M4HCG1hGCW3SWAoRIIxMbYGIyPAOtDHDa2sHzKtmxLr/ePmSfN9PQTT9YbSyO+X9Wrp+7pmenvaXq+7v66v++lWTPDZWfNdLbvp647JWSreeq6U3jw8qmh3+KBy6c6z33829NpbqihuiJDc0MNv/C9QLt49qaZoWs+e5O7PkMVXabcT3IR7wAWrm1H8GJh23OgU+preH1trxPLKYdXh9LgjWoAbn96ZSj/u0+vZP22sA/Rm361gjZruLyufQ/r2kPmMB5/2x29OhhX3pVW4N2tfacBWvdE83YCKzeH8+w0QDfR/4/r//Xce94u+CeXh13U22mAx96Kerm+b8GHjKkKL8OYs+BDzj9hfChv3Za9fNIRNjDn0naQuL//n3c5vj6sCH/ySitPH1cfiVd/3hOhsFFc/8RytuwKP7u3/HoFtSPCHhRufnIli/5uHEdPqI14BxDL2aOdBkil0tEVSAaesn7jeW9vxLaL59KzngzX/ZYnl/PEtTMweBvyc9e/4L7Xe/42fnp8TUXPqGj3vm6uefRN5l1/WuTdUJJO5bW52Dz0WmvomnNfa3W+b4YqqmD6SaHzn5F1/wY27Qi/nTbt8JTI8vXh+PTL1++IhCi2lYui9MWn1vPS1rGPxxaFHXDY6SCuENmrNoSf01WfhNM99965L5K220NXFj7tCK+UbOvI74nZ3hdWmklF9pjky3O1Wbsttvlt0WUfcXUqC7XBDJQk2Vtc6BRZP3Gta3dNmy2zHoRlH29DJDxFZqdz6DpwJQ72W1rDTn8WdojkknTKuYw2E5kKdj/n+fZwudpTc2N4/rK5YTTHTwiPqI6fUO3Mc7XZfG1x4pjwcv6Jh4xwvuRrK0tCeXWVJc79Oy76s8w46ftodATTT1xekl09HHuj5L6uLOefMJ4Hft/rZef8E7z59JQI2UDXy04rysGmPCN0dvU+gxUZobI0E/IkUOlHqcwZoTft2Ms59/yeb53SyNw/tPaU+9aMRh56rTedo7o8zeZdXaE0uKehXe3uwvsWhq63uDU6p7m4dStPXjcjcm531nB/oC1+fYrXFluaank7EMSspamWTDoVMap3dHaFRonjaip4/NvTuWzOItZ82sGkMVV5bSv5ptlduOROEqpg+onLS/Jiy2Hg4tYtpK0eUjolXDJtQkjBXDzN28xmL2m204pysJlYW8qqtt4pqyPqyljXHrYL7tyzl05rj2Dbjr1cMm1CSMFc3DLBqWA69nQ504vWhg1Yr6/dzKbt9T1RXheuaeeSk+sjU1BrP+2IdMzWtO1kf3eWhb6zyz37u7mhO8v1Z03iv95e3+NQ8ztnTgLgLWs7wVsfbeXRq6ZHnGU+9np4enHd5l2UpFNMn1hHWSbNiQ01eZ1aukZE+Zxvut43Awl7fLBDJquCKQKrNuwMpVduiM5Nr9ywg7MC8TkAzvq3V1l319cKil6pKAeToHIBWLUpGrh2j2MDuoGQx28c6RydWXc66Oo/l855cc7d40s/eoUKy3VNV9b0LJzpqeP+LJfOWdSzLPitD7dx2ZxFGAiNvK78+WLmXX8af/wk3JZXbdjJvb9dHTr/x79dHekEdmVNwSMT1zLj/oxq+lO2mOceCGqDKQJ7rYd6b1eWzv1hg1/n/m5VJIpygLjaTrfVxrq7uslaL/5s1rB6U1hprG7bmXezo6stR0Y1H27DNiulpXCDvMt9TL5zXfaagRj+D/aiAVUwRcDlgLC8JNy7stOKogyMvZbW2Zt1K6LKsvBETUVpJq9B/hBrefchVaUOpdPN5EPD+2i+cOjIgg3yuRHRjs6unhFRvnNzI46Fa9v52ctruOfF9wdk+D/YiwZ0iqwIHDt+JEtae3sCXxw/iqwxoQh+x4wbyYqPtrE38KyWq3pXPsekgKyVHigihJYqpwQaaitDu+Eb60bw4OVTncH/5s86PZQ/f9bpXPPom6F7lGZSzL1imtOgb9tqXAHZXKOIR6462WnM709ZG5e95WAvGlAFUwSmNdWFFMy0ptqIqxhjYJ8157x36DpBVZSCEMKjhmBs9XxlcpRbbmXK+whdUKgLmPKS8DXLStJR/2LdWe57ZW3IBnP/K2uZfe7RVFeUsuhvzw6Vb24czaJ1vZukmxtGU1maiWyWvPv5dyO2mqBjy5z9Z/rEuogNxmXMB7e9Jl9Zm0I3hceJ9qGLgMt1gx2WJZVyD98VJclEwiEIvGi5Znnxr0+jwurKVmTgaCscQS49ojT8WhpRmqIsE75TWUYKcgFz7PhRYMI9OUOWpR+E7SouZ7Q5XO3bZRtxXXO1ZetZ3dbRL1cv+UJ82BTbVlMsdARTBFw9io+3hncKf7TF4WNEURKOy2PFbfPCro9mz1sZWXG2pwve3Rh++ebSu62hvp3O5blcwNiDmmzWsHx92Mi//OOdEbc39uqzIK72HQzR0dfeN9dqs0JHIIBzBZvrXNdoZSg4xVQFExO22wg7rSjDAdvmIRJ1t2L34nPkayOFjPQNREYMb36w1elQ1uWC3xWSPB8uW4ZrtOJycGvPZKSlf3tRCh1pDcRWEyeJUzAikgbuAq4AyoH5wLXGGId7wcFj0tiqkEvuyWOrWL9tTyR4kKK47AsDxWUbGeiUbL562l4oKkrT7AjswLTTwfygvaQi4DXYDgEARPJa23eFrtfavovxNWH317lQ4/Zv4QpJno9CPXVMn1gXcmh7UkMNazd3hL0flGX6tRfFdR8XA7HVxEkSbTDfBf4cmA7U+3mPDV513POfLpfc82edHgqpOn/W6QBRV+SHj3LdZkBMqg6/tCZXD/wlphQHl4t4gHLL5m2ne/JT0XRzY3g6ZGpjDWWOcvlwhZp2ucK3bSPlGeHw2vBLvqG20nmPL44PX+8434+YKwSAK2/33rDS2r23K+rfLC1UloTzKkvE6TwzH67RgWu04rKt2LI31lX2yzbiuo+LQu1EB5vEjWCAa4AfGGPWAojIbGC1iDQZY1o/62QRqQPqAKZMmfIZpQsjX4/E5ZLbXqECMGPyGN7+uHf3/4xJY3jrI7en2gNlVHU1bN+WN60MjEJXOblwuYifd/1pHDOhJjQKPnZCDe9u3BnpyY8sz9AZGBlXV5Vx8hF1oWXyJx9RR7cJR1E9tt59PXCPLoytdgxUlZewa1/vvUeUlzhc4RvnKKKlqTbkP6zFd2h5SFV5JAQAEMmrLMuw0xodRFeMGY4cVx2S+6hx1c6VYflwjQ4MREYrrhFDVMZaz91NgbaRkxpGR+7jolA70cEe0SRKwYhINdAA9CxMN8asEZEdwAlAawGXuRH4PkBbW1tR6jXQ1RqutekPvbImtJGsPBV1rZGPEaUpdgUMo94qnGhP6LhxFaz4pHfxwfHj3D3NzzMjSlLs2h/+LSePrWTZx712hRPrR5JOp0Mv9BMbaujs7GTFxt7f97jDKkin0yxb33vulPqqvLvKXc4Td+/r4vQfvczufd09Pfnv/GKptc+j0vlM3dCdLeh64N7blbL865VmUjTVjQjdu6ku7I04V64iA7sDA47KkoE7cmysq4zc23ZQXpZJ89AVLRG5S9Kpgu+dr56FnD+Qc/s6vxB0FVn/yY2pt1v52wLHPot7gV8CjB079r1iVGqgqzVcvY9jD68pqLc5sjwTsevYoVuPOmyUsydkqGHFJ2t68r50lOdRNt9ceyE9dNe53VkT6b2OHVXmtEcVOv/uytvXlY3cu84KOZu7jyvvUEedXL/l9Il1IQVz6uSxGAiPGJq8nuqKjb2/7+lHj8dASMGcNvlQUql2Zwhd116LytJMpCfv6iW7nilXoCvX9cC9t8tApNdv501tjOY1N4z2Xa4ERxEDtxFMbazljXVbA+nRzpGF63eEwnvz+epZyPkDObev8wtBV5H1n9x6w2orvwYoaE7JGNMOtAO0tLQUpVJx7I4ttPdakk5Fdh6XpFMF99hcea/dfiYz736ZrqwhkxJeu/1MgEjeto5Ozr2312X68zfOoKaqPFKuqzvb46xQgFdnn8HIitJIvcGbf3f1qAvJ6+rORu5d4buUt+/jynPt4h7ob1lInmtk0R/ieP760/M+GDIOtI6fR4aCq38xCYs7IiIfAHcYY+b66YnAGuCIQmwwQVpaWsySJUuKX0lFUZRhioi8aYwpqHeexFVkDwC3i8gRIjIKuBt4ob/KRVEURYmXpE2RgbcHZjSwGCgDXgQuG9QaKYqiKBESp2CMMd3Arf5HURRFGaIkcYpMURRFSQCqYBRFUZRYUAWjKIqixELilikXExH5FPjgAE5NA4cCm4Cku0keTrKAyjOUGU6ywPCSpz+yNBpjxhRy0c+1gjlQRORI4D3gKGPM+4Ndn4EwnGQBlWcoM5xkgeElT1yy6BSZoiiKEguqYBRFUZRYUAVzYLQDd/jfSWc4yQIqz1BmOMkCw0ueWGRRG4yiKIoSCzqCURRFUWJBFYyiKIoSC6pgFEVRlFhQBaMoiqLEgioYRVEUJRZUwSiKoiixoApGURRFiQVVMIqiKEosqILpAxG5SEReFZEdItLlOH6uiKwUkT0iskJEzhmMehaCiNzt13WHiGwQkQdFpNYqc7mIrBGR3SKySESmDlZ9C0FE7hSRdb5MbSLyaxFpCBxPlDwAIpISkQUiYkSkPpCfGFlE5GER2S8iHYHP9VaZxMgDICJni8jrviybReSngWOJkcV/BwT/L3v8Z63ZP17cWOe/1AAABhpJREFUd5oxRj95PsBXgYuBq4Au69hEYDdwGVAKXArsApoGu955ZPkhcBJQAowBngOeCRyf6df/HKAMmI3nunvUYNe9D5mOBqr9vyuBfwcWJFUev95/A7wEGKA+ibIADwNz+jieNHnOBLYB3/TrWw40J1EWh2x3Aiv9v4v+Tht0AZPw8R8wW8HcAbxq5b0KfH+w61ugTF8DtgfSjwCPBdICfAj85WDXtUB5RgD/CrQnVR7gSGANcKKlYBIlSwEKJmnyLATuGg6yWHXPAJ8AN/npor/TdIrswJkCvGnlLfXzk8CXgXcC6ZA8xnu63mKIyyMil4jIdqADuBn4B/9QouQRkRQwF7gNr7ccJFGy+FwgIltE5H0R+RcRqQocS4w8IjICOBnoFJGl/vTYyyLS4hdJjCwO/gKoBh7100V/p6mCOXBGAtutvG3AqEGoS78QkQuAq/FeyDkSKY8x5pfGmGpgHJ5yWe4fSpo8NwMbjTHzHMeSJsu9eNOXhwDfAM4AHgwcT5I8o/Hek1cDVwDjgfnAb0SkhmTJYnMt8IQxJtehKbosqmAOnJ142j9IDbBjEOpSMCJyIV5j/zNjzNLAoUTKk8MYsxFPrv/1Fy8kRh4RmYxne7khT5HEyAJgjHnTGLPJGJM1xqwEZgHfFJEyv0iS5Nnpf//cGPOOMWYf8M94tsxTSZYsPYjIJLxZjPsC2UWXRRXMgbMMaLbyTvLzhyQiciVwP/B1Y8zvrMMheURE8GwBQ1YeBxk8W8x4kiXPTLyFFytEZDPetATAO/7qqyTJ4iLrf4v/nRh5jDHbgVY8m1jkMAmSxeJaYJkxZlEgr/jvtME2NA3lD5DGWzFyDtDl/12O11Am4a24uBivN3MxQ3sV2U14wYSm5Tk+E8+O8WW8FSS3MoRXw+B1jm4AxvrpeuBpYB2eokmMPHgr4OoDn1PwXl4tQFWSZPHluQio8f/+ArAAeCrBz9ptwMfAsf6zNRvPOF6dNFl8eUqBNuBaK7/o77RBF3Yof/DmXI3j0+QfPxdYCezxv88Z7Dr3IYsB9vuNoedjlbkcWOvL8wYwdbDr3Yc8KeA3fkPZBawHHgcmJVEeS7YmAqvIkiYL8DKwxf+/rMNbPj7KKpMkeQT4AbARzybxO+DEJMri1/civOmwKsexor7TNKKloiiKEgtqg1EURVFiQRWMoiiKEguqYBRFUZRYUAWjKIqixIIqGEVRFCUWVMEoiqIosaAKRlEOIiLyPRFpLcJ1XhKRhwdeI0WJD1UwilJE/GBbLw12PRRlKKAKRlEURYkFVTCKEhMikvZDVW/2wzrPASqsMs0i8pwf8rlDRJaIyHlWmTEi8pQfkne9iNziuFeJiPyTiHzgh7t92/ecrSiDhioYRYmPW4C/wov1Mg3Pl9WNVplRwH/iRU1tBp4HnhGRowNlHgaOB/7U//wJXhCsIA8B5wFX4jll/A/gMRH5atGkUZR+or7IFKWI+Ib3emPM2SKyAZhrjPle4PgCYLwxpqmPaywDfmWMuVNEjgTeA75ijHnJPz4az7vvk8aYK0RkIl6o5aOMMe8HrnM/MMEYc37RBVWUAsgMdgUUZTgiIqPwomwusA79AbgwUK4OLxLnV4DD8NpkOdDoFznG/+65jjFmq4isClxzqv+91AtH0kMJXiwTRRkUVMEoSjxIgfmP4Lnnn43n2n4P3pRZaT+un5vqPhUvnkeQ/Z9VUUWJC7XBKEoMGC8S4ga84GFBZljpM4CfGGP+2xizHC+Q1cTA8T/63z3X8WPBB200uQiYhxtjVlufDwYqi6IcKDqCUZT4uAf4voi8CywBLsMz1m8JlHkPuFREXsOLoPqPBNqlMeZ9EXkW+KmIXANsBe6kNwwxxpj/820/D4rIrcAivMUDpwBZY8z98YmoKPnREYyixMc9wM+AH+MpmMOBe60yV+K1wzeAZ4D5/t92mVXAC/7xVx1lrvbvcwfeqOcF4Bt4kRYVZVDQVWSKoihKLOgIRlEURYkFVTCKoihKLKiCURRFUWJBFYyiKIoSC6pgFEVRlFhQBaMoiqLEgioYRVEUJRZUwSiKoiixoApGURRFiYX/B7w9gkVfutonAAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Qual a relação entre idade e horas de aprendizagem?\n", "# A idade dos profissionais não afeta a quantidade de tempo gasto com capacitação e treinamento.\n", "\n", "import warnings\n", "warnings.filterwarnings('ignore')\n", "\n", "# Criando subset dos dados\n", "df9 = df.copy()\n", "df9 = df9.dropna(subset=[\"HoursLearning\"])\n", "df9 = df9[df['Age'].isin(range(0,70))]\n", "\n", "# Definindo os valores de x e y\n", "x = df9.Age\n", "y = df9.HoursLearning\n", "\n", "# Computando os valores e gerando o gráfico\n", "m, b = np.polyfit(x, y, 1)\n", "plt.plot(x, y, '.')\n", "plt.plot(x, m*x + b, '-', color = \"red\")\n", "plt.xlabel(\"Idade\")\n", "plt.ylabel(\"Horas de Treinamento\")\n", "plt.title(\"Idade por Horas de Treinamento\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Investimento em Capacitação x Expectativa Salarial" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Qual a relação entre investimento em capacitação e expectativa salarial?\n", "# Os profissionais que investem tempo e dinheiro em capacitação e \n", "# treinamento, em geral, conseguem salários mais altos, embora alguns \n", "# profisisonais esperem altos salários, investindo 0 em treinamento.\n", "\n", "import warnings\n", "warnings.filterwarnings('ignore')\n", "\n", "# Criando subset dos dados\n", "df5 = df.copy()\n", "df5 = df5.dropna(subset=[\"ExpectedEarning\"])\n", "df5 = df5[df['MoneyForLearning'].isin(range(0,60000))]\n", "\n", "# Definindo os valores de x e y\n", "x = df5.MoneyForLearning\n", "y = df5.ExpectedEarning\n", "\n", "# Computando os valores e gerando o gráfico\n", "m, b = np.polyfit(x, y, 1)\n", "plt.plot(x, y, '.')\n", "plt.plot(x, m*x + b, '-', color = \"red\")\n", "plt.xlabel(\"Investimento em Treinamento\")\n", "plt.ylabel(\"Expectativa Salarial\")\n", "plt.title(\"Investimento em Treinamento vs Expectativa Salarial\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Conheça a Formação Cientista de Dados, um programa completo, 100% online e 100% em português, com 340 horas, mais de 1.200 aulas em vídeos e 26 projetos, que vão ajudá-lo a se tornar um dos profissionais mais cobiçados do mercado de análise de dados. Clique no link abaixo, faça sua inscrição, comece hoje mesmo e aumente sua empregabilidade:\n", "\n", "https://www.datascienceacademy.com.br/pages/formacao-cientista-de-dados" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "# Fim" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "### Obrigado - Data Science Academy - facebook.com/dsacademybr" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.5" } }, "nbformat": 4, "nbformat_minor": 1 }