{"id":484,"date":"2025-07-24T18:30:34","date_gmt":"2025-07-24T22:30:34","guid":{"rendered":"https:\/\/literaciadigital.ufms.br\/?page_id=484"},"modified":"2025-10-06T15:35:16","modified_gmt":"2025-10-06T19:35:16","slug":"8-0","status":"publish","type":"page","link":"https:\/\/literaciadigital.ufms.br\/en\/data8\/8-0\/","title":{"rendered":"Cap\u00edtulo 8"},"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\"><img fetchpriority=\"high\" decoding=\"async\" class=\"alignnone size-medium wp-image-959\" src=\"https:\/\/literaciadigital.ufms.br\/files\/2025\/10\/python-300x180.png\" alt=\"\" width=\"300\" height=\"180\" srcset=\"https:\/\/literaciadigital.ufms.br\/files\/2025\/10\/python-300x180.png 300w, https:\/\/literaciadigital.ufms.br\/files\/2025\/10\/python-768x461.png 768w, https:\/\/literaciadigital.ufms.br\/files\/2025\/10\/python-534x320.png 534w, https:\/\/literaciadigital.ufms.br\/files\/2025\/10\/python.png 842w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/>\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 matplotlib\r\npath_data = '..\/..\/assets\/data\/'\r\nmatplotlib.use('Agg')\r\n%matplotlib inline\r\nimport matplotlib.pyplot as plots\r\nplots.style.use('fivethirtyeight')\r\nimport numpy as np<\/span><\/code><\/pre>\n<h1 id=\"fun-es-e-tabelas\" style=\"text-align: center\">Fun\u00e7\u00f5es e Tabelas<\/h1>\n<p style=\"text-align: justify\">Estamos construindo um invent\u00e1rio \u00fatil de t\u00e9cnicas para identificar padr\u00f5es e temas em um conjunto de dados usando fun\u00e7\u00f5es j\u00e1 dispon\u00edveis em Python. Agora vamos explorar um recurso central da linguagem de programa\u00e7\u00e3o Python: a defini\u00e7\u00e3o de fun\u00e7\u00f5es.<\/p>\n<p style=\"text-align: justify\">J\u00e1 usamos fun\u00e7\u00f5es extensivamente neste texto, mas nunca definimos uma fun\u00e7\u00e3o pr\u00f3pria. O objetivo de definir uma fun\u00e7\u00e3o \u00e9 dar um nome a um processo computacional que pode ser aplicado v\u00e1rias vezes. Existem muitas situa\u00e7\u00f5es na computa\u00e7\u00e3o que exigem c\u00e1lculos repetidos. Por exemplo, frequentemente queremos realizar a mesma manipula\u00e7\u00e3o em cada valor em uma coluna de uma tabela.<\/p>\n<h2>Definindo uma Fun\u00e7\u00e3o<\/h2>\n<p>A defini\u00e7\u00e3o da fun\u00e7\u00e3o <code>double<\/code> abaixo simplesmente duplica um n\u00famero.<\/p>\n<pre><code><span style=\"color: black\"># Nossa primeira defini\u00e7\u00e3o de fun\u00e7\u00e3o\r\n\r\ndef double(x):\r\n    \"\"\" Double x \"\"\"\r\n    return 2*x<\/span><\/code><\/pre>\n<p>Come\u00e7amos qualquer defini\u00e7\u00e3o de fun\u00e7\u00e3o escrevendo `def`. Aqui est\u00e1 um detalhamento das outras partes (a *sintaxe*) desta pequena fun\u00e7\u00e3o:<\/p>\n<p><img decoding=\"async\" class=\"aligncenter wp-image-959\" src=\"https:\/\/literaciadigital.ufms.br\/files\/2025\/10\/python-300x180.png\" alt=\"\" width=\"672\" height=\"403\" srcset=\"https:\/\/literaciadigital.ufms.br\/files\/2025\/10\/python-300x180.png 300w, https:\/\/literaciadigital.ufms.br\/files\/2025\/10\/python-768x461.png 768w, https:\/\/literaciadigital.ufms.br\/files\/2025\/10\/python-534x320.png 534w, https:\/\/literaciadigital.ufms.br\/files\/2025\/10\/python.png 842w\" sizes=\"(max-width: 672px) 100vw, 672px\" \/><\/p>\n<p style=\"text-align: justify\">Quando executamos a c\u00e9lula acima, nenhum n\u00famero espec\u00edfico \u00e9 duplicado, e o c\u00f3digo dentro do corpo de <code>double<\/code> ainda n\u00e3o \u00e9 avaliado. Nesse aspecto, nossa fun\u00e7\u00e3o \u00e9 an\u00e1loga a uma <em>receita<\/em>. Cada vez que seguimos as instru\u00e7\u00f5es em uma receita, precisamos come\u00e7ar com ingredientes. Cada vez que queremos usar nossa fun\u00e7\u00e3o para dobrar um n\u00famero, precisamos especificar um n\u00famero.<\/p>\n<p style=\"text-align: justify\">Podemos chamar <code>double<\/code> exatamente da mesma forma que chamamos outras fun\u00e7\u00f5es. Cada vez que fazemos isso, o c\u00f3digo no corpo \u00e9 executado, com o valor do argumento recebendo o nome <code>x<\/code>.<\/p>\n<pre><code><span style=\"color: black\">double(17)<\/span><\/code><\/pre>\n<table style=\"font-family: monospace;border-spacing: 0;border-collapse: collapse;width: auto;margin-left: 1em\">\n<tbody>\n<tr>\n<td style=\"text-align: right;color: #888;padding-right: 0.5em\">Out[1]:<\/td>\n<td style=\"text-align: left\">34<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<pre><code><span style=\"color: black\">double(-0.6\/4)<\/span><\/code><\/pre>\n<table style=\"font-family: monospace;border-spacing: 0;border-collapse: collapse;width: auto;margin-left: 1em\">\n<tbody>\n<tr>\n<td style=\"text-align: right;color: #888;padding-right: 0.5em\">Out[2]:<\/td>\n<td style=\"text-align: left\">-0.3<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p style=\"text-align: justify\">As duas express\u00f5es acima s\u00e3o ambas <em>express\u00f5es de chamada<\/em>. Na segunda, o valor da express\u00e3o <code>-0.6\/4<\/code> \u00e9 calculado e ent\u00e3o passado como o argumento nomeado <code>x<\/code> para a fun\u00e7\u00e3o <code>double<\/code>. Cada express\u00e3o de chamada resulta na execu\u00e7\u00e3o do corpo de <code>double<\/code>, mas com um valor diferente de <code>x<\/code>.<\/p>\n<p>O corpo de <code>double<\/code> tem apenas uma \u00fanica linha:<\/p>\n<p><code>return 2*x<\/code><\/p>\n<p>Executar esta <em>instru\u00e7\u00e3o <code>return<\/code><\/em> completa a execu\u00e7\u00e3o do corpo da fun\u00e7\u00e3o <code>double<\/code> e calcula o valor da express\u00e3o de chamada.<\/p>\n<p style=\"text-align: justify\">O argumento para <code>double<\/code> pode ser qualquer express\u00e3o, desde que seu valor seja um n\u00famero. Por exemplo, pode ser um nome. A fun\u00e7\u00e3o <code>double<\/code> n\u00e3o sabe ou se importa com a forma como seu argumento \u00e9 calculado ou armazenado; seu \u00fanico trabalho \u00e9 executar seu pr\u00f3prio corpo usando os valores dos argumentos passados para ela.<\/p>\n<pre><code><span style=\"color: black\">any_name = 42\r\ndouble(any_name)<\/span><\/code><\/pre>\n<table style=\"font-family: monospace;border-spacing: 0;border-collapse: collapse;width: auto;margin-left: 1em\">\n<tbody>\n<tr>\n<td style=\"text-align: right;color: #888;padding-right: 0.5em\">Out[3]:<\/td>\n<td style=\"text-align: left\">84<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p style=\"text-align: justify\">O argumento tamb\u00e9m pode ser qualquer valor que possa ser duplicado. Por exemplo, uma matriz inteira de n\u00fameros pode ser passada como argumento para <code>double<\/code> e o resultado ser\u00e1 outra matriz.<\/p>\n<pre><code><span style=\"color: black\">double(make_array(3, 4, 5))<\/span><\/code><\/pre>\n<table style=\"font-family: monospace;border-spacing: 0;border-collapse: collapse;width: auto;margin-left: 1em\">\n<tbody>\n<tr>\n<td style=\"text-align: right;color: #888;padding-right: 0.5em\">Out[4]:<\/td>\n<td style=\"text-align: left\">array([ 6, 8, 10])<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p style=\"text-align: justify\">No entanto, nomes que s\u00e3o definidos dentro de uma fun\u00e7\u00e3o, incluindo argumentos como <code>x<\/code> de <code>double<\/code>, t\u00eam apenas uma exist\u00eancia passageira. Eles s\u00e3o definidos apenas enquanto a fun\u00e7\u00e3o est\u00e1 sendo chamada e s\u00f3 s\u00e3o acess\u00edveis dentro do corpo da fun\u00e7\u00e3o. N\u00e3o podemos nos referir a <code>x<\/code> fora do corpo de <code>double<\/code>. A terminologia t\u00e9cnica \u00e9 que <code>x<\/code> tem <em>escopo local<\/em>.<\/p>\n<p>Portanto, o nome <code>x<\/code> n\u00e3o \u00e9 reconhecido fora do corpo da fun\u00e7\u00e3o, mesmo que tenhamos chamado <code>double<\/code> nas c\u00e9lulas acima.<\/p>\n<pre><code><span style=\"color: black\">x<\/span><\/code><\/pre>\n<table style=\"font-family: monospace;border-spacing: 0;border-collapse: collapse;width: auto;margin-left: 1em\">\n<tbody>\n<tr>\n<td style=\"text-align: right;color: #888;padding-right: 0.5em\">Out[5]:<\/td>\n<td style=\"text-align: left\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;<br \/>\nNameError Traceback (most recent call last)<br \/>\n&lt;ipython-input-7-6fcf9dfbd479&gt; in &lt;module&gt;<br \/>\n&#8212;-&gt; 1 xNameError: name &#8216;x&#8217; is not defined<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p style=\"text-align: justify\">**Docstrings.** Embora `double` seja relativamente f\u00e1cil de entender, muitas fun\u00e7\u00f5es realizam tarefas complicadas e s\u00e3o dif\u00edceis de usar sem explica\u00e7\u00e3o. (Voc\u00ea pode ter descoberto isso por si mesmo!) Portanto, uma fun\u00e7\u00e3o bem elaborada tem um nome que evoca seu comportamento, bem como documenta\u00e7\u00e3o. Em Python, isso \u00e9 chamado de *docstring* \u2014 uma descri\u00e7\u00e3o de seu comportamento e expectativas sobre seus argumentos. A docstring tamb\u00e9m pode mostrar chamadas de exemplo para a fun\u00e7\u00e3o, onde a chamada \u00e9 precedida por `&gt;&gt;&gt;`.<\/p>\n<p style=\"text-align: justify\">Uma docstring pode ser qualquer string, desde que seja a primeira coisa no corpo de uma fun\u00e7\u00e3o. Docstrings geralmente s\u00e3o definidas usando aspas triplas no in\u00edcio e no fim, o que permite que uma string abranja v\u00e1rias linhas. A primeira linha \u00e9 convencionalmente uma descri\u00e7\u00e3o completa, mas curta, da fun\u00e7\u00e3o, enquanto as linhas seguintes fornecem orienta\u00e7\u00e3o adicional para futuros usu\u00e1rios da fun\u00e7\u00e3o.<\/p>\n<p>Aqui est\u00e1 uma defini\u00e7\u00e3o de uma fun\u00e7\u00e3o chamada `percent` que recebe dois argumentos. A defini\u00e7\u00e3o inclui uma docstring.<\/p>\n<pre><code><span style=\"color: black\"># Uma fun\u00e7\u00e3o com mais de um argumento\r\n\r\ndef percent(x, total):\r\n    \"\"\"Converte x em uma porcentagem do total.\r\n\r\n    Mais precisamente, esta fun\u00e7\u00e3o divide x por total,\r\n    multiplica o resultado por 100 e arredonda o resultado\r\n    para duas casas decimais.\r\n\r\n    &gt;&gt;&gt; percent(4, 16)\r\n    25.0\r\n    &gt;&gt;&gt; percent(1, 6)\r\n    16.67\r\n    \"\"\"\r\n    return round((x\/total)*100, 2)<\/span><\/code><\/pre>\n<pre><code><span style=\"color: black\">percent(33, 200)<\/span><\/code><\/pre>\n<table style=\"font-family: monospace;border-spacing: 0;border-collapse: collapse;width: auto;margin-left: 1em\">\n<tbody>\n<tr>\n<td style=\"text-align: right;color: #888;padding-right: 0.5em\">Out[6]:<\/td>\n<td style=\"text-align: left\">16.5<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p style=\"text-align: justify\">Compare a fun\u00e7\u00e3o <code>percent<\/code> definida acima com a fun\u00e7\u00e3o <code>percents<\/code> definida abaixo. Esta \u00faltima toma uma matriz como argumento e converte todos os n\u00fameros da matriz em porcentagens do total dos valores na matriz. As porcentagens s\u00e3o todos arredondados para duas casas decimais, desta vez substituindo <code>round<\/code> por <code>np.round<\/code> porque o argumento \u00e9 uma matriz e n\u00e3o um n\u00famero.<\/p>\n<pre><code><span style=\"color: black\">def percents(counts):\r\n    \"\"\"Converta os valores em array_x em porcentagens do total de array_x.\"\"\"\r\n    total = counts.sum()\r\n    return np.round((counts\/total)*100, 2)<\/span><\/code><\/pre>\n<p>A fun\u00e7\u00e3o <code>percents<\/code> retorna uma matriz de porcentagens que somam 100, sem arredondamento.<\/p>\n<pre><code><span style=\"color: black\">some_array = make_array(7, 10, 4)\r\npercents(some_array)<\/span><\/code><\/pre>\n<table style=\"font-family: monospace;border-spacing: 0;border-collapse: collapse;width: auto;margin-left: 1em\">\n<tbody>\n<tr>\n<td style=\"text-align: right;color: #888;padding-right: 0.5em\">Out[7]:<\/td>\n<td style=\"text-align: left\">array([33.33, 47.62, 19.05])<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p style=\"text-align: justify\">\u00c9 \u00fatil entender as etapas que o Python executa para executar uma fun\u00e7\u00e3o. Para facilitar isso, colocamos uma defini\u00e7\u00e3o de fun\u00e7\u00e3o e uma chamada para essa fun\u00e7\u00e3o na mesma c\u00e9lula abaixo.<\/p>\n<pre><code><span style=\"color: black\">def biggest_difference(array_x):\r\n    \"\"\"Encontre a maior diferen\u00e7a em valor absoluto entre dois elementos adjacentes de array_x.\"\"\"\r\n    diffs = np.diff(array_x)\r\n    absolute_diffs = abs(diffs)\r\n    return max(absolute_diffs)\r\n\r\nsome_numbers = make_array(2, 4, 5, 6, 4, -1, 1)\r\nbig_diff = biggest_difference(some_numbers)\r\nprint(\"The biggest difference is\", big_diff)<\/span><\/code><\/pre>\n<table style=\"font-family: monospace;border-spacing: 0;border-collapse: collapse;width: auto;margin-left: 1em\">\n<tbody>\n<tr>\n<td style=\"text-align: right;color: #888;padding-right: 0.5em\">Out[8]:<\/td>\n<td style=\"text-align: left\">The biggest difference is 5<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>Aqui est\u00e1 o que acontece quando executamos aquela c\u00e9lula:<\/p>\n<p><img decoding=\"async\" class=\"alignnone wp-image-966 size-full\" src=\"https:\/\/literaciadigital.ufms.br\/files\/2025\/10\/editadopython2.jpg\" alt=\"\" width=\"984\" height=\"924\" srcset=\"https:\/\/literaciadigital.ufms.br\/files\/2025\/10\/editadopython2.jpg 984w, https:\/\/literaciadigital.ufms.br\/files\/2025\/10\/editadopython2-300x282.jpg 300w, https:\/\/literaciadigital.ufms.br\/files\/2025\/10\/editadopython2-768x721.jpg 768w, https:\/\/literaciadigital.ufms.br\/files\/2025\/10\/editadopython2-341x320.jpg 341w\" sizes=\"(max-width: 984px) 100vw, 984px\" \/><\/p>\n<h2>Argumentos M\u00faltiplos<\/h2>\n<p style=\"text-align: justify\">Pode haver v\u00e1rias maneiras de generalizar uma express\u00e3o ou bloco de c\u00f3digo e, portanto, uma fun\u00e7\u00e3o pode receber v\u00e1rios argumentos, cada um determinando diferentes aspectos do resultado. Por exemplo, a fun\u00e7\u00e3o <code>percents<\/code> que definimos anteriormente, arredondada para duas casas decimais a cada vez .A defini\u00e7\u00e3o de dois argumentos a seguir permite que chamadas diferentes sejam arredondadas para valores diferentes.<\/p>\n<pre><code><span style=\"color: black\">def percents(counts, decimal_places):\r\n    \"\"\"Convert the values in array_x to percents out of the total of array_x.\"\"\"\r\n    total = counts.sum()\r\n    return np.round((counts\/total)*100, decimal_places)\r\n\r\nparts = make_array(2, 1, 4)\r\nprint(\"Rounded to 1 decimal place: \", percents(parts, 1))\r\nprint(\"Rounded to 2 decimal places:\", percents(parts, 2))\r\nprint(\"Rounded to 3 decimal places:\", percents(parts, 3))<\/span><\/code><\/pre>\n<table style=\"font-family: monospace;border-spacing: 0;border-collapse: collapse;width: auto;margin-left: 1em\">\n<tbody>\n<tr>\n<td style=\"text-align: right;color: #888;padding-right: 0.5em\">Out[9]:<\/td>\n<td style=\"text-align: left\">Rounded to 1 decimal place: [28.6 14.3 57.1]\nRounded to 2 decimal places: [28.57 14.29 57.14]\nRounded to 3 decimal places: [28.571 14.286 57.143]<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p style=\"text-align: justify\">A flexibilidade desta nova defini\u00e7\u00e3o tem um pre\u00e7o pequeno: cada vez que a fun\u00e7\u00e3o \u00e9 chamada, o n\u00famero de casas decimais deve ser especificado. Os valores padr\u00e3o dos argumentos permitem que uma fun\u00e7\u00e3o seja chamada com um n\u00famero vari\u00e1vel de argumentos; qualquer argumento que seja especificado na express\u00e3o de chamada recebe seu valor padr\u00e3o, que \u00e9 indicado na primeira linha da instru\u00e7\u00e3o <code>def<\/code>. Por exemplo, nesta defini\u00e7\u00e3o final de <code>percents<\/code>, o argumento opcional <code>decimal_places<\/code> recebe um valor padr\u00e3o de 2.<\/p>\n<pre><code><span style=\"color: black\">def percents(counts, decimal_places=2):\r\n    \"\"\"Converta os valores em array_x em porcentagens do total de array_x.\"\"\"\r\n    total = counts.sum()\r\n    return np.round((counts\/total)*100, decimal_places)\r\n\r\nparts = make_array(2, 1, 4)\r\nprint(\"Rounded to 1 decimal place:\", percents(parts, 1))\r\nprint(\"Rounded to the default number of decimal places:\", percents(parts))<\/span><\/code><\/pre>\n<table style=\"font-family: monospace;border-spacing: 0;border-collapse: collapse;width: auto;margin-left: 1em\">\n<tbody>\n<tr>\n<td style=\"text-align: right;color: #888;padding-right: 0.5em\">Out[10]:<\/td>\n<td style=\"text-align: left\">Rounded to 1 decimal place: [28.6 14.3 57.1]\nRounded to the default number of decimal places: [28.57 14.29 57.14]<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>Nota: M\u00e9todos<\/h2>\n<p style=\"text-align: justify\">As fun\u00e7\u00f5es s\u00e3o chamadas colocando express\u00f5es de argumento entre par\u00eanteses ap\u00f3s o nome da fun\u00e7\u00e3o. Qualquer fun\u00e7\u00e3o definida isoladamente \u00e9 chamada desta forma. Voc\u00ea tamb\u00e9m viu exemplos de m\u00e9todos, que s\u00e3o como fun\u00e7\u00f5es, mas s\u00e3o chamados usando nota\u00e7\u00e3o de ponto, como <code>some_table.sort(some_label)<\/code>. As fun\u00e7\u00f5es que voc\u00ea define sempre ser\u00e3o chamadas usando o nome da fun\u00e7\u00e3o primeiro, passando todos os argumentos.<\/p>\n<p><!--###########################################################################################################################################################--><\/p>\n<table width=\"100%\">\n<tbody>\n<tr>\n<td align=\"left\"><a class=\"next-page-link\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/7-0\/7-3\/\">\u2190 Cap\u00edtulo 7.3 &#8211; Gr\u00e1ficos Sobrepostos<\/a><\/td>\n<td align=\"right\"><a class=\"next-page-link\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/8-0\/8-1\/\">Cap\u00edtulo 8.1 &#8211; Aplicando Uma Fun\u00e7\u00e3o a Uma Coluna \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":141,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"page-templates\/full-width.php","meta":{"footnotes":""},"coauthors":[14],"class_list":["post-484","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/literaciadigital.ufms.br\/en\/wp-json\/wp\/v2\/pages\/484","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=484"}],"version-history":[{"count":13,"href":"https:\/\/literaciadigital.ufms.br\/en\/wp-json\/wp\/v2\/pages\/484\/revisions"}],"predecessor-version":[{"id":969,"href":"https:\/\/literaciadigital.ufms.br\/en\/wp-json\/wp\/v2\/pages\/484\/revisions\/969"}],"up":[{"embeddable":true,"href":"https:\/\/literaciadigital.ufms.br\/en\/wp-json\/wp\/v2\/pages\/141"}],"wp:attachment":[{"href":"https:\/\/literaciadigital.ufms.br\/en\/wp-json\/wp\/v2\/media?parent=484"}],"wp:term":[{"taxonomy":"author","embeddable":true,"href":"https:\/\/literaciadigital.ufms.br\/en\/wp-json\/wp\/v2\/coauthors?post=484"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}