{"id":416,"date":"2025-07-22T18:43:44","date_gmt":"2025-07-22T22:43:44","guid":{"rendered":"https:\/\/literaciadigital.ufms.br\/?page_id=416"},"modified":"2025-09-28T01:12:51","modified_gmt":"2025-09-28T05:12:51","slug":"6-4","status":"publish","type":"page","link":"https:\/\/literaciadigital.ufms.br\/en\/data8\/6-0\/6-4\/","title":{"rendered":"Cap\u00edtulo 6.4"},"content":{"rendered":"<div style=\"position: relative\">\n<div style=\"float: left;width: 300px;background-color: #f5f5f5;border: 1px solid #ddd;border-radius: 5px;padding: 15px;margin-right: 20px;margin-bottom: 5px;overflow: hidden\">\n<h3 style=\"margin: 0 0 10px 0;padding-bottom: 8px;border-bottom: 1px solid #ddd\">\u00cdndice<\/h3>\n<ol style=\"margin: 0;padding-left: 0;list-style-type: none\">\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/1-0\/\">1. O que \u00e9 Ci\u00eancia de Dados?<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/1-0\/1-1\/\">1.1. Introdu\u00e7\u00e3o<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/1-0\/1-1\/1-1\/\">1.1.1. Ferramentas Computacionais<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/1-0\/1-1\/1-2\/\">1.1.2. T\u00e9cnicas Estat\u00edsticas<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/1-0\/1-2\/\">1.2. Por que Ci\u00eancia de Dados?<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/1-0\/1-3\/\">1.3. Tra\u00e7ando os Cl\u00e1ssicos<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/1-0\/1-3\/3-1\/\">1.3.1. Personagens Liter\u00e1rios<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/1-0\/1-3\/3-2\/\">1.3.2. Outro Tipo de Personagem<\/a><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/2-0\/\">2. Causalidade e Experimentos<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/2-0\/2-1\/\">2.1. John Snow e a Bomba da Broad Street<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/2-0\/2-2\/\">2.2. O &#8220;Grande Experimento&#8221; de Snow<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/2-0\/2-3\/\">2.3. Estabelecendo Causalidade<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/2-0\/2-4\/\">2.4. Randomiza\u00e7\u00e3o<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/2-0\/2-5\/\">2.5. Notas Finais<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/3-0\/\">3. Progamando em Python<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/3-0\/3-1\/\">3.1. Express\u00f5es<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/3-0\/3-2\/\">3.2. Nomes<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/3-0\/3-2\/2-1\/\">3.2.1. Exemplo: Taxas de Crescimento<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/3-0\/3-3\/\">3.3. Chamadas<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/3-0\/3-4\/\">3.4. Introdu\u00e7\u00e3o \u00e0s Tabelas<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/4-0\/\">4. Tipos de Dados<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/4-0\/4-1\/\">4.1. N\u00fameros<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/4-0\/4-2\/\">4.2. Strings<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/4-0\/4-2\/2-1\/\">4.2.1. M\u00e9todos de Strings<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/4-0\/4-3\/\">4.3. Compara\u00e7\u00f5es<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/5-0\/\">5. Sequ\u00eancias<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/5-0\/5-1\/\">5.1. Arrays<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/5-0\/5-2\/\">5.2. Ranges<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/5-0\/5-3\/\">5.3. Mais sobre Arrays<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/6-0\/\">6. Tabelas<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/6-0\/6-1\/\">6.1. Ordenando Linhas<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/6-0\/6-2\/\">6.2. Selecionando Linhas<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/6-0\/6-3\/\">6.3. Exemplo: Tend\u00eancias Populacionais<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/6-0\/6-4\/\">6.4. Examplo: Propor\u00e7\u00f5es de Sexos<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/7-0\/\">7. Visualiza\u00e7\u00e3o<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/7-0\/7-1\/\">7.1. Visualizando Distribui\u00e7\u00f5es<br \/>\nCateg\u00f3ricas<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/7-0\/7-2\/\">7.2. Visualizando Distribui\u00e7\u00f5es Num\u00e9ricas<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/7-0\/7-3\/\">7.3. Gr\u00e1ficos Sobrepostos<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/8-0\/\">8. Fun\u00e7\u00f5es e Tabelas<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/8-0\/8-1\/\">8.1. Aplicando Fun\u00e7\u00e3o a uma Coluna<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/8-0\/8-2\/\">8.2. Classificando por uma Vari\u00e1vel<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/8-0\/8-3\/\">8.3. Classifica\u00e7\u00e3o Cruzada<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/8-0\/8-4\/\">8.4. Unindo Tabelas por Colunas<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/8-0\/8-5\/\">8.5. Compartilhamento de Bicicletas<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/9-0\/\">9. Aleatoriedade<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/9-0\/9-1\/\">9.1. Declara\u00e7\u00f5es Condicionais<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/9-0\/9-2\/\">9.2. Itera\u00e7\u00e3o<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/9-0\/9-3\/\">9.3. Simula\u00e7\u00e3o<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/9-0\/9-4\/\">9.4. O Problema de Monty Hall<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/9-0\/9-5\/\">9.5. Encontrando Probabilidades<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/10-0\/\">10. Amostragem e Distribui\u00e7\u00f5es Emp\u00edricas<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/10-0\/10-1\/\">10.1. Distribui\u00e7\u00f5es Emp\u00edricas<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/10-0\/10-2\/\">10.2. Amostragem de uma Popula\u00e7\u00e3o<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/10-0\/10-3\/\">10.3. Distribui\u00e7\u00e3o Emp\u00edrica de uma<br \/>\nEstat\u00edstica<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/10-0\/10-4\/\">10.4. Amostragem Aleat\u00f3ria em Python <\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/11-0\/\">11. Testando Hip\u00f3teses<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/11-0\/11-1\/\">11.1. Avaliando um Modelo<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/11-0\/11-2\/\">11.2. M\u00faltiplas Categorias<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/11-0\/11-3\/\">11.3. Decis\u00f5es e Incertezas<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/11-0\/11-4\/\">11.4. Probabilidades de Erro<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/12-0\/\">12. Comparando Duas Amostras<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/12-0\/12-1\/\">12.1. Teste A\/B<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/12-0\/12-2\/\">12.2. Causalidade<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/12-0\/12-3\/\">12.3. Esvaziar<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/13-0\/\">13. Estima\u00e7\u00e3o<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/13-0\/13-1\/\">13.1. Percentis<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/13-0\/13-2\/\">13.2. O Bootstrap<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/13-0\/13-3\/\">13.3. Intervalos de Confian\u00e7a<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/13-0\/13-4\/\">13.4. Usando Intervalos de Confian\u00e7a<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/14-0\/\">14. Por que a M\u00e9dia \u00e9 Importante<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/14-0\/14-1\/\">14.1. Propriedades da M\u00e9dia<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/14-0\/14-2\/\">14.2. Variabilidade<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/14-0\/14-3\/\">14.3. O DP e a Curva Normal<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/14-0\/14-4\/\">14.4. Teorema Central do Limite<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/14-0\/14-5\/\">14.5. Variabilidade da M\u00e9dia da Amostra<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/14-0\/14-6\/\">14.6. Escolhendo um Tamanho de Amostra<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/15-0\/\">15. Previs\u00e3o<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/15-0\/15-1\/\">15.1. Correla\u00e7\u00e3o<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/15-0\/15-2\/\">15.2. Linha de Regress\u00e3o<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/15-0\/15-3\/\">15.3. M\u00e9todo dos M\u00ednimos Quadrados<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/15-0\/15-4\/\">15.4. Regress\u00e3o de M\u00ednimos Quadrados<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/15-0\/15-5\/\">15.5. Diagn\u00f3sticos Visuais<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/15-0\/15-6\/\">15.6. Diagn\u00f3stico Num\u00e9rico<\/a><\/li>\n<\/ul>\n<\/li>\n<\/ol>\n<\/div>\n<p><!-- Main Content --><\/p>\n<div style=\"overflow: hidden\">\n<p><!--###########################################################################################################################################################--><\/p>\n<pre><code><span style=\"color: black\">from datascience import *\r\nimport numpy as np\r\npath_data = '..\/..\/..\/assets\/data\/'\r\nimport matplotlib\r\nmatplotlib.use('Agg')\r\n%matplotlib inline\r\nimport matplotlib.pyplot as plots\r\nplots.style.use('fivethirtyeight')<\/span><\/code><\/pre>\n<p>&nbsp;<\/p>\n<pre><code><span style=\"color: black\"># Em agosto de 2021, este arquivo do censo est\u00e1 online aqui:\r\ndata = 'http:\/\/www2.census.gov\/programs-surveys\/popest\/technical-documentation\/file-layouts\/2010-2019\/nc-est2019-agesex-res.csv'\r\n\r\n# Uma c\u00f3pia local pode ser acessada aqui caso census.gov mova o arquivo:\r\n# data = path_data + 'nc-est2019-agesex-res.csv'\r\n\r\nfull_census_table = Table.read_table(data)\r\n#full_census_table\r\n\r\npartial_census_table = full_census_table.select('SEX', 'AGE', 'POPESTIMATE2014', 'POPESTIMATE2019')\r\n#partial_census_table\r\n\r\nus_pop = partial_census_table.relabeled('POPESTIMATE2014', '2014').relabeled('POPESTIMATE2019', '2019')<\/span><\/code><\/pre>\n<h1 id=\"example-propor-es-de-sexos\" style=\"text-align: center\">Example: Propor\u00e7\u00f5es de Sexos<\/h1>\n<p style=\"text-align: justify\">Nesta se\u00e7\u00e3o continuaremos usando a tabela <code>us_pop<\/code> da se\u00e7\u00e3o anterior. Mas desta vez vamos nos concentrar nas tend\u00eancias populacionais em rela\u00e7\u00e3o \u00e0 coluna <code>SEX<\/code>.<\/p>\n<pre><code><span style=\"color: black\">us_pop<\/span><\/code><\/pre>\n<table style=\"font-family: monospace;border-collapse: collapse;width: auto;margin-left: 1em\" border=\"1\">\n<thead>\n<tr style=\"background-color: #f0f0f0;border-bottom: 2px solid #ddd\">\n<th style=\"text-align: left;padding: 4px 8px\">SEX<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">AGE<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">2014<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">2019<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">3954787<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">3783052<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">3948891<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">3829599<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">3958711<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">3922044<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">3<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">4005928<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">3998665<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">4<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">4004032<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">4043323<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">5<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">4004576<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">4028281<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">6<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">4133372<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">4017227<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">7<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">4152666<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">4022319<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">8<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">4118349<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">4066194<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">9<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">4106068<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">4061874<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd;text-align: center;font-style: italic\" colspan=\"4\">&#8230; (296 rows omitted)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2 id=\"o-c-digo-usado-na-coluna-sex-\">O C\u00f3digo Usado na Coluna <code>SEX<\/code><\/h2>\n<p style=\"text-align: justify\">O conte\u00fado das colunas <code>AGE<\/code>, <code>2014<\/code> e <code>2019<\/code> \u00e9 f\u00e1cil de entender. A coluna <code>AGE<\/code> cont\u00e9m idades em anos completos. O valor especial <code>999<\/code> representa toda a popula\u00e7\u00e3o, independentemente da idade, e <code>100<\/code> representa &#8220;100 anos ou mais&#8221;. As colunas <code>2014<\/code> e <code>2019<\/code> cont\u00eam estimativas da popula\u00e7\u00e3o dos EUA em cada um dos dois anos.<\/p>\n<p style=\"text-align: justify\">A coluna SEX, no entanto, \u00e9 mais dif\u00edcil de interpretar.<\/p>\n<p style=\"text-align: justify\">O formul\u00e1rio do Censo solicita aos entrevistados que forne\u00e7am o sexo de cada membro do agregado familiar marcando uma das duas caixas rotuladas Masculino e Feminino. A coluna <code>SEX<\/code> cont\u00e9m c\u00f3digos num\u00e9ricos: <code>1<\/code> para masculino, <code>2<\/code> para feminino e <code>0<\/code> para o total.<\/p>\n<p style=\"text-align: justify\">Essa pergunta \u00e9 feita essencialmente da mesma maneira desde 1790. Mas desde ent\u00e3o houve consider\u00e1vel <a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/11534012\/\">pesquisa<\/a> sobre se o sexo dos seres humanos se presta \u00e0 categoriza\u00e7\u00e3o bin\u00e1ria simples. Por exemplo, pessoas n\u00e3o bin\u00e1rias n\u00e3o se identificam exclusivamente como masculinas ou femininas. Um <a href=\"https:\/\/williamsinstitute.law.ucla.edu\/publications\/nonbinary-lgbtq-adults-us\/\">estudo<\/a> do Instituto Williams da Faculdade de Direito da UCLA em 2021 estimou que pelo menos 1,2 milh\u00e3o de indiv\u00edduos nos Estados Unidos se identificam como n\u00e3o bin\u00e1rios.<\/p>\n<p style=\"text-align: justify\">Ao continuar usando a forma hist\u00f3rica da pergunta, o Censo falha em refletir a complexidade da classifica\u00e7\u00e3o de sexo. A <a href=\"https:\/\/www2.census.gov\/programs-surveys\/decennial\/2020\/partners\/outreach-materials\/handouts\/why-we-ask-the-sex-question.pdf\">explica\u00e7\u00e3o<\/a> fornecida no Censo de 2020 e reproduzida na cita\u00e7\u00e3o abaixo n\u00e3o inclui instru\u00e7\u00f5es para aqueles que n\u00e3o se identificam como Masculino ou Feminino.<\/p>\n<blockquote><p><strong>Responder \u00e0 pergunta sobre sexo \u00e9 f\u00e1cil.<\/strong><\/p>\n<p>Uma pergunta sobre sexo foi inclu\u00edda desde o primeiro censo em 1790. Todas as perguntas do Censo de 2020 que envolvem caracter\u00edsticas pessoais s\u00e3o baseadas na auto-identifica\u00e7\u00e3o. Ao completar o seu censo, selecione a caixa para o sexo biol\u00f3gico com o qual voc\u00ea se identifica.<\/p><\/blockquote>\n<p style=\"text-align: justify\">Independentemente da opini\u00e3o expressa acima, responder a esta pergunta n\u00e3o \u00e9 f\u00e1cil para todos. Dificuldades para responder \u00e0 pergunta podem levar a n\u00e3o-respostas ou respostas imprecisas. Isso pode reduzir a precis\u00e3o dos dados do Censo para informar decis\u00f5es pol\u00edticas e alocar recursos.<\/p>\n<p style=\"text-align: justify\">Antes do Censo de 2020, o Census Bureau considerou revisar esta pergunta ou incluir perguntas mais abrangentes sobre orienta\u00e7\u00e3o sexual e identidade de g\u00eanero. No final, o Bureau decidiu <a href=\"https:\/\/www.census.gov\/newsroom\/blogs\/director\/2017\/03\/planned_subjects_2020.html\">n\u00e3o alterar<\/a> o censo planejado.<\/p>\n<p style=\"text-align: justify\">No entanto, o diretor do censo, John Thompson, escreveu: &#8220;O Census Bureau continua comprometido em refletir as necessidades de informa\u00e7\u00e3o de nossa sociedade em mudan\u00e7a&#8221;. Os formul\u00e1rios do censo mudam. Por exemplo, <a href=\"https:\/\/www.census.gov\/library\/stories\/2021\/08\/improved-race-ethnicity-measures-reveal-united-states-population-much-more-multiracial.html\">novas perguntas sobre ra\u00e7a e etnia<\/a> no Censo de 2020 levaram a uma compreens\u00e3o mais precisa da<br \/>\ndemografia dos<br \/>\nEUA. Podemos esperar que o Censo de 2030 seja mais inclusivo e preciso em todos os aspectos.<\/p>\n<p style=\"text-align: justify\">No que segue, usaremos os dados fornecidos pelo Censo tendo em mente as quest\u00f5es descritas acima. Usaremos o termo &#8220;masculino&#8221; para significar um indiv\u00edduo para quem &#8220;Masculino&#8221; (<code>SEX<\/code> c\u00f3digo 1) foi selecionado no formul\u00e1rio do Censo. Usaremos &#8220;feminino&#8221; para significar um indiv\u00edduo para quem &#8220;Feminino&#8221; (<code>SEX<\/code> codigo 2) foi selecionado.<\/p>\n<h2 id=\"propor-es-gerais\">Propor\u00e7\u00f5es Gerais<\/h2>\n<p style=\"text-align: justify\">Agora vamos come\u00e7ar a examinar as propor\u00e7\u00f5es de sexo em 2019. Primeiro, vamos olhar para todos os grupos et\u00e1rios juntos. Lembre-se de que isso significa olhar para as linhas em que a &#8220;idade&#8221; \u00e9 codificada como 999. A tabela <code>all_ages<\/code> cont\u00e9m essa informa\u00e7\u00e3o. H\u00e1 tr\u00eas linhas: uma para a popula\u00e7\u00e3o total, uma para os homens e uma para as mulheres.<\/p>\n<pre><code><span style=\"color: black\">us_pop_2019 = us_pop.drop('2014')\r\nall_ages = us_pop_2019.where('AGE', are.equal_to(999))\r\nall_ages<\/span><\/code><\/pre>\n<table style=\"font-family: monospace;border-collapse: collapse;width: auto;margin-left: 1em\" border=\"1\">\n<thead>\n<tr style=\"background-color: #f0f0f0;border-bottom: 2px solid #ddd\">\n<th style=\"text-align: left;padding: 4px 8px\">SEX<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">AGE<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">2019<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">999<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">328239523<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">999<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">161657324<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">999<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">166582199<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p style=\"text-align: justify\">A linha 0 de <code>all_ages<\/code> cont\u00e9m a popula\u00e7\u00e3o total dos EUA em cada um dos dois anos. Os Estados Unidos tinham cerca de 330 milh\u00f5es de pessoas em 2019.<\/p>\n<p style=\"text-align: justify\">A linha 1 cont\u00e9m as contagens para os homens e a linha 2 para as mulheres. Compare estas duas linhas para ver que em 2019, havia mais mulheres do que homens nos Estados Unidos.<\/p>\n<p style=\"text-align: justify\">As contagens populacionais nas linhas 1 e 2 somam a popula\u00e7\u00e3o total na linha 0.<\/p>\n<p style=\"text-align: justify\">Para comparabilidade com outras quantidades, precisaremos converter essas contagens em percentuais da popula\u00e7\u00e3o total. Vamos acessar o total para 2019 e nome\u00e1-lo. Em seguida, mostraremos uma tabela de popula\u00e7\u00e3o com uma coluna de propor\u00e7\u00e3o. Conforme nossa observa\u00e7\u00e3o anterior de que havia mais mulheres do que homens, 50,75% da popula\u00e7\u00e3o em 2019 era feminina e cerca de 49,25% era masculina.<\/p>\n<pre><code><span style=\"color: black\">pop_2019 = all_ages.column('2019').item(0)\r\nall_ages.with_column(\r\n    'Proportion', all_ages.column('2019')\/pop_2019\r\n).set_format('Proportion', PercentFormatter)<\/span><\/code><\/pre>\n<table style=\"font-family: monospace;border-collapse: collapse;width: auto;margin-left: 1em\" border=\"1\">\n<thead>\n<tr style=\"background-color: #f0f0f0;border-bottom: 2px solid #ddd\">\n<th style=\"text-align: left;padding: 4px 8px\">SEX<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">AGE<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">2019<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">Proportion<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">999<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">328239523<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">100.00%<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">999<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">161657324<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">49.25%<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">999<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">166582199<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">50.75%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2 id=\"propor-es-entre-beb-s\">Propor\u00e7\u00f5es Entre Beb\u00eas<\/h2>\n<p style=\"text-align: justify\">Quando olhamos para os beb\u00eas, no entanto, o oposto \u00e9 verdadeiro. Vamos definir beb\u00eas como crian\u00e7as que ainda n\u00e3o completaram um ano, representadas nas linhas correspondentes a <code>AGE<\/code> 0. Aqui est\u00e3o seus n\u00fameros na popula\u00e7\u00e3o. Voc\u00ea pode ver que os beb\u00eas do sexo masculino superaram os beb\u00eas do sexo feminino.<\/p>\n<pre><code><span style=\"color: black\">infants = us_pop_2019.where('AGE', are.equal_to(0))\r\ninfants<\/span><\/code><\/pre>\n<table style=\"font-family: monospace;border-collapse: collapse;width: auto;margin-left: 1em\" border=\"1\">\n<thead>\n<tr style=\"background-color: #f0f0f0;border-bottom: 2px solid #ddd\">\n<th style=\"text-align: left;padding: 4px 8px\">SEX<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">AGE<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">2019<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">3783052<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1935117<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1847935<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p style=\"text-align: justify\">Como antes, podemos converter essas contagens em porcentagens do n\u00famero total de crian\u00e7as. A tabela resultante mostra que em 2019, pouco mais de 51% das crian\u00e7as nos EUA eram do sexo masculino.<\/p>\n<pre><code><span style=\"color: black\">infants_2019 = infants.column('2019').item(0)\r\ninfants.with_column(\r\n    'Proportion', infants.column('2019')\/infants_2019\r\n).set_format('Proportion', PercentFormatter)<\/span><\/code><\/pre>\n<table style=\"font-family: monospace;border-collapse: collapse;width: auto;margin-left: 1em\" border=\"1\">\n<thead>\n<tr style=\"background-color: #f0f0f0;border-bottom: 2px solid #ddd\">\n<th style=\"text-align: left;padding: 4px 8px\">SEX<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">AGE<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">2019<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">Proportion<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">3783052<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">100.00%<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1935117<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">51.15%<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1847935<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">48.85%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p style=\"text-align: justify\">Na verdade, h\u00e1 muito tempo se observa que a propor\u00e7\u00e3o de meninos entre os rec\u00e9m-nascidos \u00e9 ligeiramente superior a 1\/2. A raz\u00e3o para isso n\u00e3o \u00e9 totalmente compreendida, e <a href=\"http:\/\/www.npr.org\/sections\/health-shots\/2015\/03\/30\/396384911\/why-are-more-baby-boys-born-than-girls\">os cientistas ainda est\u00e3o trabalhando nisso<\/a>.<\/p>\n<h2 id=\"propor-o-de-sexo-em-cada-idade\">Propor\u00e7\u00e3o de Sexo em Cada Idade<\/h2>\n<p style=\"text-align: justify\">Vimos que enquanto h\u00e1 mais beb\u00eas do sexo masculino do que feminino, h\u00e1 mais mulheres do que homens na popula\u00e7\u00e3o em geral. Isso significa que a divis\u00e3o entre os sexos deve variar entre os grupos et\u00e1rios.<\/p>\n<p style=\"text-align: justify\">Para estudar essa varia\u00e7\u00e3o, vamos separar os dados para as mulheres e para os homens, e eliminar a linha onde todas as idades s\u00e3o agregadas e <code>AGE<\/code> \u00e9 codificado como 999.<\/p>\n<p>As tabelas <code>females<\/code> e <code>males<\/code> cont\u00eam os dados para cada um dos dois c\u00f3digos de sexo.<\/p>\n<pre><code><span style=\"color: black\">females_all_rows = us_pop_2019.where('SEX', are.equal_to(2))\r\nfemales = females_all_rows.where('AGE', are.not_equal_to(999))\r\nfemales<\/span><\/code><\/pre>\n<table style=\"font-family: monospace;border-collapse: collapse;width: auto;margin-left: 1em\" border=\"1\">\n<thead>\n<tr style=\"background-color: #f0f0f0;border-bottom: 2px solid #ddd\">\n<th style=\"text-align: left;padding: 4px 8px\">SEX<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">AGE<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">2019<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1847935<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1871014<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1916500<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">3<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1955655<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">4<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1976372<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">5<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1967081<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">6<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1964271<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">7<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1966584<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">8<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1986471<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">9<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1988726<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd;text-align: center;font-style: italic\" colspan=\"3\">&#8230; (91 rows omitted)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<pre><code><span style=\"color: black\">males_all_rows = us_pop_2019.where('SEX', are.equal_to(1))\r\nmales = males_all_rows.where('AGE', are.not_equal_to(999))\r\nmales<\/span><\/code><\/pre>\n<table style=\"font-family: monospace;border-collapse: collapse;width: auto;margin-left: 1em\" border=\"1\">\n<thead>\n<tr style=\"background-color: #f0f0f0;border-bottom: 2px solid #ddd\">\n<th style=\"text-align: left;padding: 4px 8px\">SEX<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">AGE<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">2019<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1935117<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1958585<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2005544<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">3<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2043010<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">4<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2066951<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">5<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2061200<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">6<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2052956<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">7<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2055735<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">8<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2079723<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">9<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2073148<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd;text-align: center;font-style: italic\" colspan=\"3\">&#8230; (91 rows omitted)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p style=\"text-align: justify\">O plano agora \u00e9 comparar o n\u00famero de mulheres e o n\u00famero de homens em cada idade, para cada um dos dois anos. Os m\u00e9todos Array e Table nos fornecem maneiras simples de fazer isso. Ambas as tabelas t\u00eam uma linha para cada idade.<\/p>\n<pre><code><span style=\"color: black\">males.column('AGE')<\/span><\/code><\/pre>\n<pre style=\"font-family: monospace;margin-left: 1em\">array([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,  11,  12,\r\n        13,  14,  15,  16,  17,  18,  19,  20,  21,  22,  23,  24,  25,\r\n        26,  27,  28,  29,  30,  31,  32,  33,  34,  35,  36,  37,  38,\r\n        39,  40,  41,  42,  43,  44,  45,  46,  47,  48,  49,  50,  51,\r\n        52,  53,  54,  55,  56,  57,  58,  59,  60,  61,  62,  63,  64,\r\n        65,  66,  67,  68,  69,  70,  71,  72,  73,  74,  75,  76,  77,\r\n        78,  79,  80,  81,  82,  83,  84,  85,  86,  87,  88,  89,  90,\r\n        91,  92,  93,  94,  95,  96,  97,  98,  99, 100])<\/pre>\n<p>&nbsp;<\/p>\n<pre><code><span style=\"color: black\">females.column('AGE')<\/span><\/code><\/pre>\n<pre style=\"font-family: monospace;margin-left: 1em\">array([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,  11,  12,\r\n        13,  14,  15,  16,  17,  18,  19,  20,  21,  22,  23,  24,  25,\r\n        26,  27,  28,  29,  30,  31,  32,  33,  34,  35,  36,  37,  38,\r\n        39,  40,  41,  42,  43,  44,  45,  46,  47,  48,  49,  50,  51,\r\n        52,  53,  54,  55,  56,  57,  58,  59,  60,  61,  62,  63,  64,\r\n        65,  66,  67,  68,  69,  70,  71,  72,  73,  74,  75,  76,  77,\r\n        78,  79,  80,  81,  82,  83,  84,  85,  86,  87,  88,  89,  90,\r\n        91,  92,  93,  94,  95,  96,  97,  98,  99, 100])<\/pre>\n<p style=\"text-align: justify\">Para qualquer idade espec\u00edfica, podemos obter a propor\u00e7\u00e3o de sexo Feminino:Masculino dividindo o n\u00famero de mulheres pelo n\u00famero de homens.<\/p>\n<p style=\"text-align: justify\">Para fazer isso em um \u00fanico passo, podemos usar <code>column<\/code> para extrair a matriz de contagens de mulheres e a matriz correspondente de contagens de homens, e ent\u00e3o simplesmente dividir uma matriz pela outra. A divis\u00e3o elemento por elemento criar\u00e1 uma matriz de propor\u00e7\u00f5es de sexo para todos os anos.<\/p>\n<pre><code><span style=\"color: black\">ratios = Table().with_columns(\r\n    'AGE', females.column('AGE'),\r\n    '2019 F:M RATIO', females.column('2019')\/males.column('2019')\r\n)\r\nratios<\/span><\/code><\/pre>\n<table style=\"font-family: monospace;border-collapse: collapse;width: auto;margin-left: 1em\" border=\"1\">\n<thead>\n<tr style=\"background-color: #f0f0f0;border-bottom: 2px solid #ddd\">\n<th style=\"text-align: left;padding: 4px 8px\">AGE<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">2019 F:M RATIO<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0.954947<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0.955289<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0.955601<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">3<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0.957242<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">4<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0.956177<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">5<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0.954338<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">6<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0.956801<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">7<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0.956633<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">8<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0.955161<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">9<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0.959278<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd;text-align: center;font-style: italic\" colspan=\"2\">&#8230; (91 rows omitted)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p style=\"text-align: justify\">Voc\u00ea pode ver pela exibi\u00e7\u00e3o que as propor\u00e7\u00f5es est\u00e3o todas em torno de 0.96 para crian\u00e7as com nove anos ou menos. Quando a propor\u00e7\u00e3o Feminino:Masculino \u00e9 menor que 1, h\u00e1 menos mulheres do que homens. Assim, estamos vendo que havia menos meninas do que meninos em cada um dos grupos et\u00e1rios 0, 1, 2, e assim por diante at\u00e9 9. Mais precisamente, em cada um desses grupos et\u00e1rios havia cerca de 96 meninas para cada 100 meninos.<\/p>\n<p style=\"text-align: justify\">Ent\u00e3o, como a propor\u00e7\u00e3o geral de mulheres na popula\u00e7\u00e3o pode ser maior do que a dos homens?<\/p>\n<p style=\"text-align: justify\">Algo bem diferente acontece quando examinamos o outro extremo da faixa et\u00e1ria. Aqui est\u00e3o as propor\u00e7\u00f5es Feminino:Masculino para pessoas com mais de 75 anos.<\/p>\n<pre><code><span style=\"color: black\">ratios.where('AGE', are.above(75)).show()<\/span><\/code><\/pre>\n<table style=\"font-family: monospace;border-collapse: collapse;width: auto;margin-left: 1em\" border=\"1\">\n<thead>\n<tr style=\"background-color: #f0f0f0;border-bottom: 2px solid #ddd\">\n<th style=\"text-align: left;padding: 4px 8px\">AGE<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">2019 F:M RATIO<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">76<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1.21422<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">77<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1.23558<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">78<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1.26373<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">79<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1.28129<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">80<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1.29209<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">81<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1.32745<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">82<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1.36101<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">83<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1.39749<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">84<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1.44603<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">85<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1.48588<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">86<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1.53967<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">87<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1.59775<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">88<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1.66125<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">89<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1.73365<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">90<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1.80539<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">91<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1.90275<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">92<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1.99252<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">93<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2.10192<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">94<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2.2271<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">95<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2.34042<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">96<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2.41969<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">97<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2.5868<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">98<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2.65926<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">99<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2.91367<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">100<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">3.27411<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p style=\"text-align: justify\">N\u00e3o apenas todas essas propor\u00e7\u00f5es s\u00e3o maiores que 1, indicando mais mulheres do que homens em todos esses grupos et\u00e1rios, muitas delas s\u00e3o consideravelmente maiores que 1.<\/p>\n<ul style=\"text-align: justify\">\n<li>Aos 92 e 93 anos, as propor\u00e7\u00f5es est\u00e3o pr\u00f3ximas de 2, o que significa que havia cerca de duas vezes mais mulheres do que homens nessas idades em 2019.<\/li>\n<li>Aos 99 anos, havia cerca de 3 vezes mais mulheres do que homens.<\/li>\n<\/ul>\n<p style=\"text-align: justify\">Se voc\u00ea est\u00e1 se perguntando quantas pessoas havia nessas idades avan\u00e7adas, voc\u00ea pode usar o Python para descobrir:<\/p>\n<pre><code><span style=\"color: black\">males.where('AGE', are.contained_in(make_array(92, 93, 99)))<\/span><\/code><\/pre>\n<table style=\"font-family: monospace;border-collapse: collapse;width: auto;margin-left: 1em\" border=\"1\">\n<thead>\n<tr style=\"background-color: #f0f0f0;border-bottom: 2px solid #ddd\">\n<th style=\"text-align: left;padding: 4px 8px\">SEX<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">AGE<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">2019<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">92<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">131684<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">93<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">103415<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">99<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">14596<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<pre><code><span style=\"color: black\">females.where('AGE', are.contained_in(make_array(92, 93, 99)))<\/span><\/code><\/pre>\n<table style=\"font-family: monospace;border-collapse: collapse;width: auto;margin-left: 1em\" border=\"1\">\n<thead>\n<tr style=\"background-color: #f0f0f0;border-bottom: 2px solid #ddd\">\n<th style=\"text-align: left;padding: 4px 8px\">SEX<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">AGE<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">2019<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">92<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">262383<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">93<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">217370<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">99<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">42528<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>O gr\u00e1fico abaixo mostra as propor\u00e7\u00f5es de sexo plotadas contra a idade. A curva azul mostra as propor\u00e7\u00f5es de 2019 por idade.<\/p>\n<p style=\"text-align: justify\">As propor\u00e7\u00f5es s\u00e3o quase 1 (significando n\u00fameros quase iguais de homens e mulheres) para idades de 0 a 60. Mas elas come\u00e7am a subir dramaticamente (mais mulheres do que homens) a partir da faixa et\u00e1ria de 65 a 70 anos.<\/p>\n<p>O fato de as mulheres superarem os homens nos EUA se deve em parte ao desequil\u00edbrio acentuado a favor das mulheres entre os idosos.<\/p>\n<pre><code><span style=\"color: black\">ratios.plot('AGE')<\/span><\/code><\/pre>\n<p><img fetchpriority=\"high\" decoding=\"async\" class=\"size-full wp-image-421 alignleft\" src=\"https:\/\/literaciadigital.ufms.br\/files\/2025\/07\/6-4.png\" alt=\"\" width=\"360\" height=\"320\" \/><br \/>\n<!--###########################################################################################################################################################--><\/p>\n<table width=\"100%\">\n<tbody>\n<tr>\n<td align=\"left\"><a class=\"next-page-link\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/6-0\/6-3\/\">\u2190 Cap\u00edtulo 6.3 &#8211; Exemplo: Tend\u00eancias Populacionais<\/a><\/td>\n<td align=\"right\"><a class=\"next-page-link\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/7-0\/\">Cap\u00edtulo 7 &#8211; Visualiza\u00e7\u00e3o \u2192<\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><!--###########################################################################################################################################################--><\/p>\n<\/div>\n<\/div>\n<div style=\"clear: both;height: 1px;margin-top: -1px\"><\/div>\n","protected":false},"excerpt":{"rendered":"<p>\u00cdndice 1. O que \u00e9 Ci\u00eancia de Dados? 1.1. Introdu\u00e7\u00e3o 1.1.1. Ferramentas Computacionais 1.1.2. T\u00e9cnicas Estat\u00edsticas 1.2. Por que Ci\u00eancia de Dados? 1.3. Tra\u00e7ando os Cl\u00e1ssicos 1.3.1. Personagens Liter\u00e1rios 1.3.2. Outro Tipo de Personagem 2. Causalidade e Experimentos 2.1. John Snow e a Bomba da Broad Street 2.2. O &#8220;Grande Experimento&#8221; de Snow 2.3. Estabelecendo [&hellip;]<\/p>\n","protected":false},"author":21894,"featured_media":0,"parent":394,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"page-templates\/full-width.php","meta":{"footnotes":""},"coauthors":[14],"class_list":["post-416","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/literaciadigital.ufms.br\/en\/wp-json\/wp\/v2\/pages\/416","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/literaciadigital.ufms.br\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/literaciadigital.ufms.br\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/literaciadigital.ufms.br\/en\/wp-json\/wp\/v2\/users\/21894"}],"replies":[{"embeddable":true,"href":"https:\/\/literaciadigital.ufms.br\/en\/wp-json\/wp\/v2\/comments?post=416"}],"version-history":[{"count":10,"href":"https:\/\/literaciadigital.ufms.br\/en\/wp-json\/wp\/v2\/pages\/416\/revisions"}],"predecessor-version":[{"id":944,"href":"https:\/\/literaciadigital.ufms.br\/en\/wp-json\/wp\/v2\/pages\/416\/revisions\/944"}],"up":[{"embeddable":true,"href":"https:\/\/literaciadigital.ufms.br\/en\/wp-json\/wp\/v2\/pages\/394"}],"wp:attachment":[{"href":"https:\/\/literaciadigital.ufms.br\/en\/wp-json\/wp\/v2\/media?parent=416"}],"wp:term":[{"taxonomy":"author","embeddable":true,"href":"https:\/\/literaciadigital.ufms.br\/en\/wp-json\/wp\/v2\/coauthors?post=416"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}