From b9d44ed6dcffa4d035161ed238e3661ad4322b8d Mon Sep 17 00:00:00 2001 From: Quarto GHA Workflow Runner Date: Tue, 21 Nov 2023 22:51:33 +0000 Subject: [PATCH] Built site for gh-pages --- .nojekyll | 2 +- index.html | 61 +- index.xml | 74 +- listings.json | 1 + .../2023-03-evento-open-data-day/english.html | 2 +- posts/2023-03-evento-open-data-day/index.html | 2 +- ...14\247a\314\203o_feminina_de_handebol.jpg" | Bin 0 -> 312433 bytes .../2023-11-evento-intro-r/images/anigif.gif | Bin 0 -> 136735 bytes .../images/ballerina-ballet.gif | Bin 0 -> 4057356 bytes posts/2023-11-evento-intro-r/index.html | 582 ++++++++++++ search.json | 883 +++++++++--------- sitemap.xml | 90 +- sobre.html | 4 +- 13 files changed, 1206 insertions(+), 495 deletions(-) create mode 100644 "posts/2023-11-evento-intro-r/images/Selec\314\247a\314\203o_feminina_de_handebol.jpg" create mode 100644 posts/2023-11-evento-intro-r/images/anigif.gif create mode 100644 posts/2023-11-evento-intro-r/images/ballerina-ballet.gif create mode 100644 posts/2023-11-evento-intro-r/index.html diff --git a/.nojekyll b/.nojekyll index ab3f53d..2348f8e 100644 --- a/.nojekyll +++ b/.nojekyll @@ -1 +1 @@ -8d20d1ab \ No newline at end of file +f9f48a66 \ No newline at end of file diff --git a/index.html b/index.html index d1575dc..7f905a9 100644 --- a/index.html +++ b/index.html @@ -272,7 +272,38 @@

Blog

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diff --git a/index.xml b/index.xml index 682f567..d86b996 100644 --- a/index.xml +++ b/index.xml @@ -10,7 +10,79 @@ Site da R-Ladies São Paulo, com informações sobre a comunidade e textos escritos por participantes. quarto-1.3.450 -Tue, 31 Oct 2023 00:00:00 GMT +Tue, 21 Nov 2023 00:00:00 GMT + + Conhecendo o R, o Tidyverse e as R-Ladies + Bianca Muniz + Gabriela Morita + Karina Ferreira + https://rladies-sp.org/posts/2023-11-evento-intro-r/index.html + Quando eu, Bianca, comecei no “mundinho dos dados”, as comunidades de tecnologia me ofereceram um espaço acolhedor para aprender sem o medo de errar. Falar de “espaço acolhedor”, pode parecer exagero e até contraditório; se errar faz parte do aprendizado, porque seria intimidador fazer isso enquanto se aprende, né? Mas, infelizmente, é muito fácil se sentir desencorajado quando é a primeira vez que você tem contato com uma tecnologia ou setor de atuação. A situação fica ainda mais chata quando se é integrante de um grupo sub-representado nesta área.
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+Os relatos deste post são de participantes do último meetup organizado pela R-Ladies São Paulo. Ambas vivenciaram sua primeira experiência num evento das R-Ladies e ressaltam o sentimento de acolhimento para dar um primeiro passo no R. Mesmo sendo facilitadora do workshop, também estava ali fazendo algo pela primeira vez: apresentando a organização! Até pouco tempo, estava acompanhando de longe as atividades da comunidade (deixo aqui o convite para apresentarem também! Vamos hablar hehe)

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Boa leitura!

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“Acolhe pessoas com vontade de aprender R”

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por Gabriela Morita

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Em 28 de outubro de 2023 participei do meu primeiro curso sobre a linguagem R. O curso “Introdução ao R - um curso para quem quer começar” foi organizado e desenvolvido pela equipe potente da #RLadiesSP, que faz parte da organização mundial R-Ladies, com o propósito de promover a diversidade de gênero na comunidade da linguagem R.

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O curso acolhe pessoas com vontade de aprender R, mesmo sem ter experiência ou contato prévio. O contato com as ferramentas é incentivado antes do encontro presencial, com tutoriais para a instalação do R e do RStudio, que são utilizados para desenvolver as atividades.

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Screenshot dos slides de Introdução ao R
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No dia do curso, são estabelecidas duas etapas:

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  • A etapa 1 (pela manhã), com introdução sobre a organização RLadies, e também apresentação sobre vantagens de usar o R

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  • E a etapa 2, à tarde, em que é apresentado os pacotes do Tidyverse e suas aplicações.

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Agradeço demais às R-Ladies SP - Bianca Muniz, Geovana Lopes, Haydee Svab e a Renata Hirota - que compartilharam seus conhecimentos e práticas neste encontro, foi um espaço de muito aprendizado, partilhas e num formato muito acolhedor e colaborativo.

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Divagações de uma iniciante em R

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por Karina Ferrara Barros

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No dia 28 de outubro de 2023 ocorreu o Evento R-Ladies São Paulo, do qual participei como iniciante no 'mundo R'. Em uma manhã e tarde de sábado mergulhei em um momento de aprendizagem proporcionado por uma equipe dedicada e disposta a ensinar e compartilhar conhecimento.

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A Oficina de Introdução ao R iniciou com a apresentação da comunidade R-Ladies, esforço global presente em 16 localidades brasileiras, seguindo com motivações para aprender linguagem R. Em preparo para adentrar no tema da Oficina, foi construído um ambiente muito acolhedor a partir da reflexão sobre o sentimento de exclusão compartilhado por diversos indivíduos, que se consideram inaptos a aprender este tipo de conhecimento por razões como "ser de humanas demais" ou "não se dar bem com matemática".

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Da minha parte, durante muito tempo me encaixei nesses rótulos e, após uma longa jornada de autoconhecimento e estudo, descobri que contextualizar conhecimentos que se mostram (a princípio) muito distantes de nossas afinidades torna a aprendizagem mais palpável e leve. Por esse motivo, no assunto seguinte abordado na Oficina, que eram os conceitos iniciais de programação, busquei algumas contextualizações para aproximar os ensinamentos sobre R.

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Em meio à dificuldade de materializar conceitos, passei por algumas divagações que me ajudaram a estabelecer pontes entre o meu "eu" de "antes e depois" do evento. Compartilho aqui estas divagações para explicar os conceitos de função e pacote, a partir dos aprendizados de um sábado com as R-Ladies.

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De jogadas de handebol às funções do R

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No handebol existem jogadas preestabelecidas que auxiliam atletas no momento do ataque. Essas jogadas consistem em um conjunto de movimentações e passes da bola que criam oportunidade para o arremesso ao gol. Praticantes treinam estas jogadas e as conhecem por nomes: "araraquara", "argentina", "circulação", "loose", "roda"... Ou seja, estas jogadas estão armazenadas nas memórias de jogadores e são identificadas por nomes, que significam determinadas movimentações.

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No Evento R-Ladies aprendemos que funções são palavras que dão comandos ao computador. Por exemplo, mean é a palavra que dá o comando de obter média. As funções estão gravadas no programa, assim como as jogadas estão registradas nas memórias de atletas de handebol. No handebol, ao utilizar a palavra que expressa a jogada, a movimentação é realizada. No R, ao utilizar a palavra que expressa a função, o comando é realizado.

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Dos métodos de Ballet aos pacotes do R

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Existem diferentes métodos da prática do Ballet, dos quais os mais famosos são o Vaganova (russo) e o Royal (inglês). Estes métodos abrigam conjuntos de passos de ballet que são executados pelos praticantes. A maioria dos passos tem nomes em comum nos métodos mencionados. Entretanto, apesar de compartilharem o mesmo nome, podem ocorrer diferenças na execução. Por exemplo, ao executar uma sequência de piruetas (aquele rodopio), é necessário conectá-las com um passo denominado fouetté, que se caracteriza como uma movimentação de perna em 90º graus seguido do recolhimento até o joelho. O fouetté em Royal tem o desenho de um quarto de círculo, levando a perna à frente e deslocando até o lado antes de ser recolhida. Já o fouetté em Vaganova a perna é levada diretamente ao lado e depois recolhida.

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+Na Oficina aprendemos que as funções do R estão organizadas em conjuntos denominados pacotes. Ou seja, os pacotes são apanhados de palavras que dão comandos ao computador (funções). São exemplos de pacotes: dplyr, ggplot2, lubridate. Por comparação, da mesma forma que os métodos de ballet reúnem passos, os pacotes do R agrupam funções. Além disso, é possível que estes pacotes tenham nomes de funções em comum, mas que expressam diferenças no comando para o computador, assim como o fouetté em Vaganova e em Royal.

+

Finalizando com as divagações, ressalto que o Evento R-Ladies não foi feito só de conceitos, dedicando uma parte considerável de tempo à prática e exercícios assistidos pela equipe. Cumprindo com a proposta de ser uma oficina, o evento se mostrou um excelente ponto de partida para quem deseja iniciar os caminhos na aprendizagem de linguagem R.

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+ + ]]>
+ Eventos + https://rladies-sp.org/posts/2023-11-evento-intro-r/index.html + Tue, 21 Nov 2023 00:00:00 GMT + +
Raspando a página do Studio Ghibli, na Wikipédia Ornella Scardua Ferreira diff --git a/listings.json b/listings.json index 4f5bb8d..5ce0ce7 100644 --- a/listings.json +++ b/listings.json @@ -2,6 +2,7 @@ { "listing": "/index.html", "items": [ + "/posts/2023-11-evento-intro-r/index.html", "/posts/2023-10-ws-ghibli/index.html", "/posts/2023-06-05-increasing-diversity-sao-paulo/index.html", "/posts/2023-06-rita-com-r/index.html", diff --git a/posts/2023-03-evento-open-data-day/english.html b/posts/2023-03-evento-open-data-day/english.html index 7c2eba8..0186210 100644 --- a/posts/2023-03-evento-open-data-day/english.html +++ b/posts/2023-03-evento-open-data-day/english.html @@ -803,7 +803,7 @@

Event: Open Data Analysis with R

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Evento: Análise de dados abertos com R

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zVV9oA-KC{gNFwL0%z4mm8q2GRqMMhz=Uq!*{@hj{f9&gdM*pl%&j{o8Sxu6F9%o%3O{biUKR7ATv#5D{Jc=hRQd>iAB#$Cae_!&EbmfbP0eYh3kQh4?Zijj?M4;$Q2CZWy zL@pVsjkd7ZN16O=0`s&$1>q^%M{QJAYotS^xk5 literal 0 HcmV?d00001 diff --git a/posts/2023-11-evento-intro-r/index.html b/posts/2023-11-evento-intro-r/index.html new file mode 100644 index 0000000..f607278 --- /dev/null +++ b/posts/2023-11-evento-intro-r/index.html @@ -0,0 +1,582 @@ + + + + + + + + + + + + +R-Ladies São Paulo - Conhecendo o R, o Tidyverse e as R-Ladies + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

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Conhecendo o R, o Tidyverse e as R-Ladies

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Relato de evento a partir de membros da comunidade

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Eventos
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Autoras
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Bianca Muniz

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Gabriela Morita

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Karina Ferreira

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Data de Publicação
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21 de novembro de 2023

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Quando eu, Bianca, comecei no “mundinho dos dados”, as comunidades de tecnologia me ofereceram um espaço acolhedor para aprender sem o medo de errar. Falar de “espaço acolhedor”, pode parecer exagero e até contraditório; se errar faz parte do aprendizado, porque seria intimidador fazer isso enquanto se aprende, né? Mas, infelizmente, é muito fácil se sentir desencorajado quando é a primeira vez que você tem contato com uma tecnologia ou setor de atuação. A situação fica ainda mais chata quando se é integrante de um grupo sub-representado nesta área.
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+Os relatos deste post são de participantes do último meetup organizado pela R-Ladies São Paulo. Ambas vivenciaram sua primeira experiência num evento das R-Ladies e ressaltam o sentimento de acolhimento para dar um primeiro passo no R. Mesmo sendo facilitadora do workshop, também estava ali fazendo algo pela primeira vez: apresentando a organização! Até pouco tempo, estava acompanhando de longe as atividades da comunidade (deixo aqui o convite para apresentarem também! Vamos hablar hehe)

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Boa leitura!

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“Acolhe pessoas com vontade de aprender R”

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por Gabriela Morita

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Em 28 de outubro de 2023 participei do meu primeiro curso sobre a linguagem R. O curso “Introdução ao R - um curso para quem quer começar” foi organizado e desenvolvido pela equipe potente da #RLadiesSP, que faz parte da organização mundial R-Ladies, com o propósito de promover a diversidade de gênero na comunidade da linguagem R.

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O curso acolhe pessoas com vontade de aprender R, mesmo sem ter experiência ou contato prévio. O contato com as ferramentas é incentivado antes do encontro presencial, com tutoriais para a instalação do R e do RStudio, que são utilizados para desenvolver as atividades.

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Screenshot dos slides de Introdução ao R
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No dia do curso, são estabelecidas duas etapas:

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  • A etapa 1 (pela manhã), com introdução sobre a organização RLadies, e também apresentação sobre vantagens de usar o R

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  • E a etapa 2, à tarde, em que é apresentado os pacotes do Tidyverse e suas aplicações.

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Agradeço demais às R-Ladies SP - Bianca Muniz, Geovana Lopes, Haydee Svab e a Renata Hirota - que compartilharam seus conhecimentos e práticas neste encontro, foi um espaço de muito aprendizado, partilhas e num formato muito acolhedor e colaborativo.

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Divagações de uma iniciante em R

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por Karina Ferrara Barros

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No dia 28 de outubro de 2023 ocorreu o Evento R-Ladies São Paulo, do qual participei como iniciante no 'mundo R'. Em uma manhã e tarde de sábado mergulhei em um momento de aprendizagem proporcionado por uma equipe dedicada e disposta a ensinar e compartilhar conhecimento.

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A Oficina de Introdução ao R iniciou com a apresentação da comunidade R-Ladies, esforço global presente em 16 localidades brasileiras, seguindo com motivações para aprender linguagem R. Em preparo para adentrar no tema da Oficina, foi construído um ambiente muito acolhedor a partir da reflexão sobre o sentimento de exclusão compartilhado por diversos indivíduos, que se consideram inaptos a aprender este tipo de conhecimento por razões como "ser de humanas demais" ou "não se dar bem com matemática".

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Da minha parte, durante muito tempo me encaixei nesses rótulos e, após uma longa jornada de autoconhecimento e estudo, descobri que contextualizar conhecimentos que se mostram (a princípio) muito distantes de nossas afinidades torna a aprendizagem mais palpável e leve. Por esse motivo, no assunto seguinte abordado na Oficina, que eram os conceitos iniciais de programação, busquei algumas contextualizações para aproximar os ensinamentos sobre R.

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Em meio à dificuldade de materializar conceitos, passei por algumas divagações que me ajudaram a estabelecer pontes entre o meu "eu" de "antes e depois" do evento. Compartilho aqui estas divagações para explicar os conceitos de função e pacote, a partir dos aprendizados de um sábado com as R-Ladies.

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De jogadas de handebol às funções do R

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No handebol existem jogadas preestabelecidas que auxiliam atletas no momento do ataque. Essas jogadas consistem em um conjunto de movimentações e passes da bola que criam oportunidade para o arremesso ao gol. Praticantes treinam estas jogadas e as conhecem por nomes: "araraquara", "argentina", "circulação", "loose", "roda"... Ou seja, estas jogadas estão armazenadas nas memórias de jogadores e são identificadas por nomes, que significam determinadas movimentações.

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No Evento R-Ladies aprendemos que funções são palavras que dão comandos ao computador. Por exemplo, mean é a palavra que dá o comando de obter média. As funções estão gravadas no programa, assim como as jogadas estão registradas nas memórias de atletas de handebol. No handebol, ao utilizar a palavra que expressa a jogada, a movimentação é realizada. No R, ao utilizar a palavra que expressa a função, o comando é realizado.

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Dos métodos de Ballet aos pacotes do R

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Existem diferentes métodos da prática do Ballet, dos quais os mais famosos são o Vaganova (russo) e o Royal (inglês). Estes métodos abrigam conjuntos de passos de ballet que são executados pelos praticantes. A maioria dos passos tem nomes em comum nos métodos mencionados. Entretanto, apesar de compartilharem o mesmo nome, podem ocorrer diferenças na execução. Por exemplo, ao executar uma sequência de piruetas (aquele rodopio), é necessário conectá-las com um passo denominado fouetté, que se caracteriza como uma movimentação de perna em 90º graus seguido do recolhimento até o joelho. O fouetté em Royal tem o desenho de um quarto de círculo, levando a perna à frente e deslocando até o lado antes de ser recolhida. Já o fouetté em Vaganova a perna é levada diretamente ao lado e depois recolhida.

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+Na Oficina aprendemos que as funções do R estão organizadas em conjuntos denominados pacotes. Ou seja, os pacotes são apanhados de palavras que dão comandos ao computador (funções). São exemplos de pacotes: dplyr, ggplot2, lubridate. Por comparação, da mesma forma que os métodos de ballet reúnem passos, os pacotes do R agrupam funções. Além disso, é possível que estes pacotes tenham nomes de funções em comum, mas que expressam diferenças no comando para o computador, assim como o fouetté em Vaganova e em Royal.

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Finalizando com as divagações, ressalto que o Evento R-Ladies não foi feito só de conceitos, dedicando uma parte considerável de tempo à prática e exercícios assistidos pela equipe. Cumprindo com a proposta de ser uma oficina, o evento se mostrou um excelente ponto de partida para quem deseja iniciar os caminhos na aprendizagem de linguagem R.

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+ + + + \ No newline at end of file diff --git a/search.json b/search.json index aa92e23..8bed8e0 100644 --- a/search.json +++ b/search.json @@ -1,255 +1,143 @@ [ { - "objectID": "contribuir-com-o-blog.html", - "href": "contribuir-com-o-blog.html", - "title": "Como contribuir com o blog?", + "objectID": "videos.html", + "href": "videos.html", + "title": "Videos", "section": "", - "text": "Se você faz parte da comunidade R-Ladies São Paulo ou outros capítulos do Brasil, e gostaria contribuir com algum post ou conteúdo para o blog, a contribuição será muito bem vinda!" + "text": "Todos os vídeos podem ser encontrados no canal da R-Ladies São Paulo no Youtube." }, { - "objectID": "contribuir-com-o-blog.html#tipos-de-contribuição", - "href": "contribuir-com-o-blog.html#tipos-de-contribuição", - "title": "Como contribuir com o blog?", - "section": "Tipos de contribuição", - "text": "Tipos de contribuição\nExistem várias formas de contribuir, como:\n\ncaso encontre alguma informação desatualizada e/ou que precise de correção, pode fazer a atualização/correção;\nescrever algum texto não-técnico relacionado às atividades do grupo;\nescrever algum texto técnico para o blog (por exemplo, mostrando alguma análise feita com R por você);\nescrever algum tutorial sobre uso de algum pacote para o blog;\nenviar algum texto técnico já escrito no seu blog pessoal, que possa ser re-compartilhado aqui;\nentre outros!" + "objectID": "videos.html#ciência-de-dados-gênero-e-raça-nas-políticas-públicas", + "href": "videos.html#ciência-de-dados-gênero-e-raça-nas-políticas-públicas", + "title": "Videos", + "section": "Ciência de Dados, Gênero e Raça nas Políticas Públicas", + "text": "Ciência de Dados, Gênero e Raça nas Políticas Públicas\n\nMaterial completo" }, { - "objectID": "contribuir-com-o-blog.html#como-contribuir", - "href": "contribuir-com-o-blog.html#como-contribuir", - "title": "Como contribuir com o blog?", - "section": "Como contribuir?", - "text": "Como contribuir?\nAs alterações no código costumam ser feitas através do GitHub. Você pode criar uma conta gratuita e seguir o passo-a-passo indicado abaixo.\n\n\n\n\n\n\nNota\n\n\n\nCaso você não use GitHub, pode enviar a contribuição escrevendo em um arquivo Google Documentos, word/.docx ou RMarkdown/Quarto, por exemplo, e enviando para a gente através de uma issue no GitHub." + "objectID": "videos.html#como-escolher-o-teste-estatístico-adequado", + "href": "videos.html#como-escolher-o-teste-estatístico-adequado", + "title": "Videos", + "section": "Como escolher o teste estatístico adequado?", + "text": "Como escolher o teste estatístico adequado?\n\nApresentado por Fernanda Peres\nSlides" }, { - "objectID": "contribuir-com-o-blog.html#contribuindo-com-alguma-página-que-já-existe", - "href": "contribuir-com-o-blog.html#contribuindo-com-alguma-página-que-já-existe", - "title": "Como contribuir com o blog?", - "section": "Contribuindo com alguma página que já existe", - "text": "Contribuindo com alguma página que já existe\nCaso queira sugerir uma alteração em uma página já existente, siga os passos abaixo:\n1 - Primeiro confira se na barra do lado direito aparece o link chamado “Edite essa página”:\n\n\n\n\n\nEsse link te encaminhará para o arquivo que deve ser alterado no GitHub.\n2 - Caso não encontre o link “Editar essa página”, procure o arquivo referente à página que deseja alterar no repositório no GitHub. Os arquivos de texto que devem ser alterados são apenas os que tem extensão .qmd.\n3 - Fazendo a alteração no GitHub: EM BREVE!" + "objectID": "videos.html#conhecendo-o-ggplot2-criando-gráficos-com-r", + "href": "videos.html#conhecendo-o-ggplot2-criando-gráficos-com-r", + "title": "Videos", + "section": "Conhecendo o ggplot2: criando gráficos com R", + "text": "Conhecendo o ggplot2: criando gráficos com R\n\nApresentado por Letícia Thomaz\nSlides" }, { - "objectID": "contribuir-com-o-blog.html#contribuindo-com-um-textopost-para-o-blog", - "href": "contribuir-com-o-blog.html#contribuindo-com-um-textopost-para-o-blog", - "title": "Como contribuir com o blog?", - "section": "Contribuindo com um texto/post para o blog", - "text": "Contribuindo com um texto/post para o blog\nOs arquivos que geram os posts do blog estão na pasta posts/.\n1 - Faça uma cópia da pasta template-post/. Nomeie a pasta iniciando com o ano e mês, e algumas palavras que indicam o conteúdo do texto de uma forma “limpa”, sem usar acentos, espaços, e outros caracteres especiais. Ex: 2022-12-tutorial-tidyverse.\nNessa pasta, tem arquivos para gerar um post:\n\nindex.qmd: esse é o arquivo principal! Neste arquivo, estão descritos os metadados do arquivo (quem escreveu o post, data, categorias, entre outros), e o texto do post. Tem vários exemplos e comentários neste arquivo para ajudar quem ainda não tem muita familiaridade com Quarto!\nimages/: é uma pasta onde pode guardar as imagens que você queira usar no post.\npacotes.bib: é um arquivo opcional e gerado automaticamente, contém as referências dos pacotes utilizados no post.\n\n2 - Edite os conteúdos na pasta copiada!\n3 - Envie suas mudanças como um Pull request no GitHub: EM BREVE!." + "objectID": "videos.html#visualização-interativa-de-dados-uma-aplicação-usando-shiny", + "href": "videos.html#visualização-interativa-de-dados-uma-aplicação-usando-shiny", + "title": "Videos", + "section": "Visualização Interativa de Dados – uma aplicação usando Shiny", + "text": "Visualização Interativa de Dados – uma aplicação usando Shiny\n\nApresentado por Marina Muradian" }, { - "objectID": "posts/2023-06-rita-com-r/index.html", - "href": "posts/2023-06-rita-com-r/index.html", - "title": "Rita com R", - "section": "", - "text": "No dia 8 de maio o mundo da música ficou mais careta: Rita Lee, a rainha do rock brasileiro, padroeira da liberdade, a santa rita de sampa, nos deixou, mas não sem antes deixar um grande legado de obras, letras, frases.\nO intuito desse artigo é homenagear Rita Lee a partir de uma análise de sua obra usando R. Das R-Ladies de São Paulo para a mais icônica “Mina de Sampa”." + "objectID": "videos.html#people-analytics-a-ciência-de-dados-no-rh", + "href": "videos.html#people-analytics-a-ciência-de-dados-no-rh", + "title": "Videos", + "section": "People Analytics a Ciência de Dados no RH", + "text": "People Analytics a Ciência de Dados no RH\n\nApresentado por Sabrina Vasconcellos" }, { - "objectID": "posts/2023-06-rita-com-r/index.html#esse-tal-de-r", - "href": "posts/2023-06-rita-com-r/index.html#esse-tal-de-r", - "title": "Rita com R", - "section": "1.1. Esse tal de R", - "text": "1.1. Esse tal de R\nPara começar, é preciso carregar alguns pacotes:\n\nlibrary(tidyverse)\nlibrary(spotifyr)\nlibrary(highcharter)\nlibrary(ggridges)\nlibrary(DT)\n\n\ngerar_tabela <- function(tbl) {\n # knitr::kable(\n # tbl\n # )\n gt::gt(tbl)\n}\n\n\nPrimeiro, devemos configurar os dados da API do Spotify. Aqui tem um tutorialzinho explicando como obter seu Client ID e o token de acesso. No blog da Curso-R também mostra como criar seus tokens de acesso na API do Spotify (com o pacote Rspotify, que é diferente do que vamos usar aqui, mas o início é o mesmo!).\nCom o ambiente configurado, podemos requisitar as características de áudio das faixas qualquer artista presente na plataforma! Isso é feito com a função get_artist_audio_features do pacote spotifyR.\nNessa análise, vamos coletar os atributos das faixas da Rita Lee e analisar alguns deles.\n\nrita_features <- read_csv(\"data-raw/rita_features.csv\")\nglimpse(rita_features)\n\nRows: 411\nColumns: 39\n$ artist_name <chr> \"Rita Lee\", \"Rita Lee\", \"Rita Lee\", \"Rita…\n$ artist_id <chr> \"7dnT2FUXhjirperXaH22IJ\", \"7dnT2FUXhjirpe…\n$ album_id <chr> \"0rZu9DYrrdzdOUQ7Nm2QB8\", \"0rZu9DYrrdzdOU…\n$ album_type <chr> \"album\", \"album\", \"album\", \"album\", \"albu…\n$ album_images <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…\n$ album_release_date <chr> \"2021-06-25\", \"2021-06-25\", \"2021-06-25\",…\n$ album_release_year <dbl> 2021, 2021, 2021, 2021, 2021, 2021, 2021,…\n$ album_release_date_precision <chr> \"day\", \"day\", \"day\", \"day\", \"day\", \"day\",…\n$ danceability <dbl> 0.735, 0.802, 0.755, 0.821, 0.852, 0.656,…\n$ energy <dbl> 0.513, 0.638, 0.712, 0.769, 0.715, 0.734,…\n$ key <dbl> 2, 2, 5, 9, 0, 4, 2, 2, 5, 0, 0, 2, 6, 11…\n$ loudness <dbl> -9.369, -7.968, -7.696, -9.791, -8.402, -…\n$ mode <dbl> 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 0,…\n$ speechiness <dbl> 0.0299, 0.0319, 0.0397, 0.0707, 0.0427, 0…\n$ acousticness <dbl> 0.031100, 0.005490, 0.000466, 0.001490, 0…\n$ instrumentalness <dbl> 0.414000, 0.023400, 0.258000, 0.726000, 0…\n$ liveness <dbl> 0.1160, 0.2160, 0.2210, 0.0469, 0.0426, 0…\n$ valence <dbl> 0.5470, 0.6850, 0.8350, 0.4380, 0.6770, 0…\n$ tempo <dbl> 119.978, 127.982, 127.986, 125.000, 123.0…\n$ track_id <chr> \"4CFOKrbwh1FuR5xBvOWG2R\", \"1VM1W9cMkrHmrX…\n$ analysis_url <chr> \"https://api.spotify.com/v1/audio-analysi…\n$ time_signature <dbl> 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,…\n$ artists <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…\n$ available_markets <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…\n$ disc_number <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…\n$ duration_ms <dbl> 356886, 216585, 369843, 524638, 320488, 2…\n$ explicit <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,…\n$ track_href <chr> \"https://api.spotify.com/v1/tracks/4CFOKr…\n$ is_local <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,…\n$ track_name <chr> \"Só De Você - Coppola Remix\", \"Pega Rapaz…\n$ track_preview_url <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…\n$ track_number <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13…\n$ type <chr> \"track\", \"track\", \"track\", \"track\", \"trac…\n$ track_uri <chr> \"spotify:track:4CFOKrbwh1FuR5xBvOWG2R\", \"…\n$ external_urls.spotify <chr> \"https://open.spotify.com/track/4CFOKrbwh…\n$ album_name <chr> \"Rita Lee & Roberto - Classix Remix Vol. …\n$ key_name <chr> \"D\", \"D\", \"F\", \"A\", \"C\", \"E\", \"D\", \"D\", \"…\n$ mode_name <chr> \"major\", \"major\", \"major\", \"major\", \"majo…\n$ key_mode <chr> \"D major\", \"D major\", \"F major\", \"A major…\n\n\n\nAqui já conseguimos ver que o dataframe resultante dessa requisição tem 39 colunas e 411 linhas, que correspondem a cada faixa da cantora. Há uma coluna com o formato errado, a album_release_date, que é a data de lançamento do álbum (não usaremos esse atributo na análise, mas é bom saber :D)\n\n\n\n\n\n\nImportante\n\n\n\nAlguns álbuns são homônimos (ou seja, têm o mesmo nome), são coletâneas e/ou remixes. Tem que considerar isso na análise!\n\n\n\nQuantas faixas cada álbum tem? Há algumas maneiras de fazer isso, mas vou utilizar o “GSA” (as funções group_by,summarise e arrange do pacote dplyr):\n\nrita_features |>\n group_by(album_name, album_release_year) |>\n summarise(faixas = n()) |>\n arrange(desc(faixas)) |>\n gerar_tabela()\n\n\n\n\n\nQuantidade de faixas por álbum \n\nalbum_release_year\nfaixas\n\n\n\nEm Bossa 'N Roll (Edição Comemorativa - 25 Anos) - Ao Vivo\n\n\n1991\n21\n\n\nAcustico (Live)\n\n\n1998\n18\n\n\nLanca Perfume E Outras Manias\n\n\n1998\n18\n\n\nRita Lee Em Bossa 'N Roll (Ao Vivo)\n\n\n1991\n18\n\n\nRita Lee & Roberto - Classix Remix Vol. III\n\n\n2021\n17\n\n\nRita Lee\n\n\n1979\n16\n\n\n1993\n13\n\n\n1980\n8\n\n\nRita Releeda\n\n\n2000\n16\n\n\nAo Vivo\n\n\n2004\n14\n\n\nAqui, Ali, Em Qualquer Lugar\n\n\n2006\n14\n\n\nMultishow Ao Vivo\n\n\n2009\n14\n\n\nReza\n\n\n2012\n14\n\n\nBombom\n\n\n1983\n13\n\n\nPérolas\n\n\n2016\n13\n\n\nRita Lee & Roberto - Classix Remix Vol. II\n\n\n2021\n13\n\n\nBalacobaco\n\n\n2003\n12\n\n\nRita Lee & Roberto – Classix Remix Vol. l\n\n\n2021\n12\n\n\nRita Lee 3001\n\n\n2000\n12\n\n\nSanta Rita De Sampa\n\n\n1997\n12\n\n\nBuild Up\n\n\n1970\n11\n\n\nRefestança (Ao Vivo)\n\n\n1977\n11\n\n\nAtrás Do Porto Tem Uma Cidade\n\n\n1974\n10\n\n\nFlerte Fatal\n\n\n1987\n10\n\n\nHoje É O Primeiro Dia Do Resto Da Sua Vida\n\n\n1972\n10\n\n\nRita Lee E Roberto De Carvalho\n\n\n1990\n10\n\n\nBabilônia\n\n\n1978\n9\n\n\nEntradas E Bandeiras\n\n\n1976\n9\n\n\nFlagra\n\n\n1982\n9\n\n\nFruto Proibido\n\n\n1975\n9\n\n\nRita E Roberto\n\n\n1985\n9\n\n\nSaúde\n\n\n1981\n8\n\n\nZona Zen\n\n\n1988\n8" + "objectID": "videos.html#tidymodels-estruturando-o-processo-de-machine-learning", + "href": "videos.html#tidymodels-estruturando-o-processo-de-machine-learning", + "title": "Videos", + "section": "Tidymodels: Estruturando o processo de Machine Learning", + "text": "Tidymodels: Estruturando o processo de Machine Learning\n\nApresentado por Viviane Sanchez e Bruna Wundervald\nSlides:\n\nApresentação da Bruna Wundervald\nApresentação da Viviane Sanchez" }, { - "objectID": "posts/2023-03-tidytuesday-paraolimpiadas/index.html", - "href": "posts/2023-03-tidytuesday-paraolimpiadas/index.html", - "title": "#TidyTuesday: Explorando dados sobre as Paraolimpíadas", + "objectID": "posts/2023-03-evento-open-data-day/english.html", + "href": "posts/2023-03-evento-open-data-day/english.html", + "title": "Event: Open Data Analysis with R", "section": "", - "text": "Autoria\n\n\n\n\n\n\n\n\nIanní Muliterno\n\n \n\nEste post foi escrito por Ianní Muliterno, um integrante da comunidade R-Ladies São Paulo! É graduado em Estatística pela Universidade Federal de Pernambuco (UFPE) e atua como cientista de dados na Unilever.\nOlá, pessoal!\nSe você já é um entusiasta de ciência de dados, provavelmente já ouviu falar do TidyTuesday. Se está iniciando, este é um ótimo lugar para conseguir dados reais para praticar e criar um portfolio. O tidytuesday é um projeto semanal do R for Data Science Community, que tem como objetivo ajudar as pessoas a aprender e praticar a análise de dados em R usando o pacote Tidyverse, conheça aqui: https://github.com/rfordatascience/tidytuesday.\nCada semana, é lançado um novo conjunto de dados, geralmente em formato de planilha, que pode ser baixado gratuitamente. A comunidade é então convidada a explorar, visualizar e analisar esses dados usando as ferramentas do tidyverse, como o ggplot2 para gráficos e o dplyr para manipulação de dados." - }, - { - "objectID": "posts/2023-03-tidytuesday-paraolimpiadas/index.html#base-de-dados", - "href": "posts/2023-03-tidytuesday-paraolimpiadas/index.html#base-de-dados", - "title": "#TidyTuesday: Explorando dados sobre as Paraolimpíadas", - "section": "Base de dados", - "text": "Base de dados\nHoje vamos dar uma olhada na base do início de agosto de 2021, quando o TidyTuesday lançou um conjunto de dados fascinante sobre as paraolimpíadas dos anos 1980 até 2016. O conjunto de dados inclui informações sobre características dos atletas, o país de origem, o tipo de prova, entre outras variáveis." - }, - { - "objectID": "posts/2023-03-tidytuesday-paraolimpiadas/index.html#importação", - "href": "posts/2023-03-tidytuesday-paraolimpiadas/index.html#importação", - "title": "#TidyTuesday: Explorando dados sobre as Paraolimpíadas", - "section": "Importação", - "text": "Importação\nPara começar vamos carregar os dados! Lembrando de manter a boa prática de iniciar o script carregando as bibliotecas necessárias.\n\nlibrary(tidyverse)\nlibrary(readr)\nlibrary(ggplot2)\n\n\ndados_olimpiadas <- read_csv(\"https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2021/2021-08-03/athletes.csv\")\n\nRows: 19547 Columns: 10\n── Column specification ────────────────────────────────────────────────────────\nDelimiter: \",\"\nchr (8): gender, event, medal, athlete, abb, country, type, guide\ndbl (2): grp_id, year\n\nℹ Use `spec()` to retrieve the full column specification for this data.\nℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.\n\n\nO bacana da função read_csv() é que ela já dá uma descrição geral com nome das variáveis e tipo. No caso, temos 8 variáveis tipo chr ou character (textos) e 2 tipo dbl ou double (numéricos).\nAntes de começar, outra boa prática é conhecer os dados. Quais colunas possui? Como está o preenchimento das variáveis? Existem dados faltantes (NAs)?\n\n# Quantos NAs temos em cada coluna?\ncolSums(is.na(dados_olimpiadas))\n\n gender event medal athlete abb country grp_id type year guide \n 144 0 0 435 49 14428 14428 0 0 19494 \n\n\nNo tidytuesday os dados costumam vir mais arrumados, porém no mundo real é comum encontrarmos erros no preenchimento, sejam eles sistemáticos (por exemplo: a ferramenta que mede velocidade dos competidores falha e traz valores muito grandes ou negativos), ou também erros de preenchimento (exemplo: alguém que preencheu errado o campo de medalha e colocou por exemplo “metal” ao invés de “prata”).\nNo repositório desta base, está descrito o que cada coluna representa. Te convido para escrever como lição de casa o código que checa as variáveis categóricas em busca de nomes estranhos que não condizem com o que deveria estar naquela variável. Como incentivo, deixo aqui o check de variáveis numéricas.\n\ndados_olimpiadas %>% \n select(where(is.numeric)) %>%\n pivot_longer(1:2, names_to = 'variaveis', values_to = 'valor') %>% \n ggplot(aes(x = valor)) +\n geom_histogram() +\n facet_wrap(~variaveis,scales = 'free') +\n theme(panel.background = element_rect(fill = \"white\"))" - }, - { - "objectID": "posts/2023-03-tidytuesday-paraolimpiadas/index.html#explorando-e-visualizando-dados-para-natação", - "href": "posts/2023-03-tidytuesday-paraolimpiadas/index.html#explorando-e-visualizando-dados-para-natação", - "title": "#TidyTuesday: Explorando dados sobre as Paraolimpíadas", - "section": "Explorando e visualizando dados para Natação!", - "text": "Explorando e visualizando dados para Natação!\nPara não ficar um post massivo, vamos focar em natação.\nAo analisar esses dados, podemos responder várias perguntas interessantes. Por exemplo, qual país obteve mais medalhas na natação nos Jogos Olímpicos de 2021? Há alguma diferença significativa na quantidade de medalhas conquistadas entre os atletas homens e mulheres?\nPaíses com mais metalhas\nPara criar um gráfico mostrando os países com mais medalhas, primeiro é necessário trabalhar os dados para criar uma base onde tenha a contagem de medalhas por país e por tipo de medalha!\n\n# Fazendo uma contagem de medalhas de natação por país:\n\nparalympic_total <- dados_olimpiadas %>%\n # Filtrando medalhas de natação (Swimming)\n filter(type == \"Swimming\") %>%\n # Contando quantas medalhas tem por país (abb),\n # ordenando pelos maiores números!\n count(abb, sort = TRUE)\n\n# Fazendo uma contagem de medalhas de natação por país e tipo de medalha:\nparalympic_byMedal <- dados_olimpiadas %>%\n # Filtrando medalhas de natação (Swimming)\n filter(type == \"Swimming\") %>%\n # Contando quantas medalhas tem por país (abb) e tipo de medalha,\n # ordenando pelos maiores números!\n count(abb, medal) \n\nparalympic_swimming <- paralympic_byMedal %>%\n # unindo as duas bases criadas acima, \n # usando a coluna \"abb\" como chave\n left_join(paralympic_total, by = \"abb\") %>%\n # renomeando as colunas\n rename(number = n.x, total_medals = n.y)\n\n# Uma \"olhada\" na base criada!\nparalympic_swimming |> \n glimpse()\n\nRows: 174\nColumns: 4\n$ abb <chr> \"ARG\", \"ARG\", \"ARG\", \"AUS\", \"AUS\", \"AUS\", \"AUT\", \"AUT\", \"…\n$ medal <chr> \"Bronze\", \"Gold\", \"Silver\", \"Bronze\", \"Gold\", \"Silver\", \"…\n$ number <int> 9, 5, 10, 160, 147, 158, 2, 2, 4, 1, 7, 1, 13, 6, 12, 9, …\n$ total_medals <int> 24, 24, 24, 465, 465, 465, 8, 8, 8, 8, 8, 1, 31, 31, 31, …\n\n\nUtilizando essa base com a contagem de medalhas, podemos filtrar os 5 países com mais medalhas:\n\ntop5 <- paralympic_total |> \n # fatiar: apenas as primeiras 5 linhas\n slice(1:5) |> \n # retornar como um vetor a coluna abb\n pull(abb)\n\n\ntable_top5 <- paralympic_swimming %>%\n # filtrar os países do top 5\n filter(abb %in% top5) %>%\n # transformar a coluna abb em fator, \n # para facilitar a ordenação no gráfico\n mutate(abb = factor(abb, levels = top5),\n medal = factor(medal, levels = c(\"Bronze\", \"Silver\", \"Gold\"))) \n\nCom os dados preparados, podemos fazer o gráfico! Mas antes disso, vamos salvar as configurações de tema do gráfico em um objeto, para utilizarmos depois e deixar o código do gráfico mais fácil para ler!\n\ntema_olimpiadas <- \n theme_minimal() +\n theme(\n legend.position = \"none\",\n plot.title.position = \"plot\",\n plot.title = element_text(\n family = \"mono\",\n face = \"bold\",\n size = 10\n ),\n panel.grid.major.x = element_blank(),\n panel.grid.minor.x = element_blank(),\n panel.grid.major.y = element_blank(),\n panel.grid.minor.y = element_blank(),\n axis.text = element_text(\n family = \"mono\",\n face = \"bold\",\n size = 8\n ),\n panel.background = element_rect(fill = \"white\")\n ) \n\nAgora sim, vamos ao gráfico!\n\ntable_top5 %>%\n ggplot(aes(x = abb, y = number, fill = medal)) +\n geom_col() +\n scale_fill_manual(values = c(\"#D89581\", \"#C0C0C0\", \"#D4AF37\")) +\n scale_x_discrete(expand = c(0, 0)) +\n labs(x = \"\",\n y = \"\", \n title = \"Medalhas de ouro, prata e bronze conquistada pelos países de melhor desempenho\") +\n tema_olimpiadas\n\n\n\n\n\n\n\nA Grã-Bretanha é o país com mais medalhas no total, porém os Estados Unidos é o país com mais medalhas de ouro!\nApesar de algumas alterações que fiz, os créditos deste gráfico de barras são da Erin, professora que vocês podem encontrar aqui: https://github.com/efranke22.\nDiferença de medalhas por gênero\nContinuando, podemos ver a diferença entre a quantidade de medalhas conquistadas entre os atletas homens e mulheres. Para isso, veremos primeiro o histograma do percentual de mulheres que os países levam em cada olimpíada, em seguida o box plot das medalhas conquistadas por cada um, agrupado também pelo tipo de medalha.\nUma observação: o gênero misto foi removido, porque ele está na base devido a algumas provas serem mistas e não porque os participantes são não-binários. Com isso, perdemos 21 linhas.\nVamos então preparar a base de dados, calculando o percentual de mulheres por país:\n\ndt_perc_gender <- dados_olimpiadas %>%\n # Filtrar para Natação\n filter(type == \"Swimming\") %>%\n # Filtrar: remover linhas onde o gênero seja \"misto\" (ex: duplas de homens e mulheres)\n filter(gender != 'Mixed') %>%\n # Deixar apenas uma linha para a combinação atleta/ano/país/gênero\n distinct(abb, year, gender, athlete) %>%\n # Contar quantas pessoas participaram por país e gênero\n count(abb, gender) %>%\n # Alterar a base para formato longo\n pivot_wider(names_from = gender, values_from = n) %>%\n # Substituir NA por 0 nas colunas Woman e Men\n mutate(across(any_of(c(\"Women\", \"Men\")), ~ ifelse(is.na(.), 0, .))) %>%\n # Agrupar por país\n group_by(abb) %>%\n # Calcular o porcentual de mulheres\n summarize(perc_mulheres = mean(Women / (Women + Men))) %>%\n # Ordenar de forma decrescente por perc_mulheres\n arrange(desc(perc_mulheres))\n\nlinha_mediana <- median(dt_perc_gender$perc_mulheres)\n\nAgora podemos criar o histograma:\n\ndt_perc_gender %>%\n ggplot(aes(x = perc_mulheres)) +\n geom_histogram() +\n geom_vline(\n mapping = aes(xintercept = linha_mediana),\n linetype = 2,\n color = 'red'\n ) +\n annotate(\n \"text\",\n x = linha_mediana + 0.06,\n y = 15,\n label = \"Mediana\",\n color = 'red'\n ) +\n ggtitle(\"Histograma do percentual de mulheres que os países levam em cada olimpíada\") +\n theme(panel.background = element_rect(fill = \"white\")) \n\n\n\n\n\n\n\nComo vimos no histograma, muitos países nem enviam mulheres para as olimpíadas e os que enviam, tem em média 34% de mulheres na composição do time. Sendo assim, essa diferença impacta na diferença que vemos na quantidade de medalhas conquistadas por gênero.\nVamos explorar estes dados em um boxplot:\n\ndados_olimpiadas %>%\n mutate(medal = factor(medal, levels = c(\"Bronze\", \"Silver\", \"Gold\"))) |> \n # Filtrar para Natação\n filter(type == \"Swimming\") %>%\n # Filtrar: remover linhas onde o gênero seja \"misto\"\n filter(gender != 'Mixed') %>%\n # Contar quantas pessoas participaram por país, gênero e tipo de medalha\n count(abb, gender, medal) %>%\n ggplot(aes(y = n, fill = gender, x = medal)) +\n geom_boxplot() +\n labs(title = \"Box-plot das medalhas conquistadas por tipo de medalha e gênero em cada país\", \n y = \"Quantidade de medalhas\",\n x = \"Tipo de medalha\",\n fill = \"Gênero\") +\n theme(panel.background = element_rect(fill = \"white\")) +\n scale_fill_brewer(type = \"qual\")" - }, - { - "objectID": "posts/2023-03-tidytuesday-paraolimpiadas/index.html#vamos-para-a-modelagem", - "href": "posts/2023-03-tidytuesday-paraolimpiadas/index.html#vamos-para-a-modelagem", - "title": "#TidyTuesday: Explorando dados sobre as Paraolimpíadas", - "section": "Vamos para a modelagem!", - "text": "Vamos para a modelagem!\nAgora, pensando em usar modelos, podemos brincar de criar métricas, pensando em como prever se um atleta conquistará medalhas na olimpíada seguinte. Opções diretas de variáveis são: quantas medalhas já ganhou, de quantas olimpíadas já participou, proporção de medalhas por tipo, e uma métrica de quantidade de medalhas por olimpíada (chamarei de medal_olympics_kpi - kpi vem do inglês Key Performance Indicators e é uma sigla bem conhecida no meio da análise de dados para se referir a indicadores de performance), por fim, teremos a variável de gênero.\nUm exercício bom de fazer aqui é observar correlação entre as variáveis resposta. As contagens de medalhas são correlacionadas entre si, pois por exemplo, quanto mais medalhas ganhas no total, maior serão os valores nas contagens de medalha por tipo, por isso que decidi utilizar proporção. A quantidade de olimpíadas que o atleta já participou também tem certa relação com sua idade, o que é bom, porque não temos a informação da idade na base.\n\n# variável resposta : última olimpíada de cada atleta\nresposta <- dados_olimpiadas %>%\n # Remover linhas onde não temos o nome do atleta\n filter(athlete != '-') %>%\n # Filtrar para natação\n filter(type == \"Swimming\") %>%\n # Filtrar por ano\n filter(year == 2016) %>%\n # Contar quantas medalhas cada atleta teve\n count(athlete, sort = TRUE) \n\nA variável resposta é a quantidade de medalhas conquistadas por atleta nas olimpíadas de natação de 2016. A base vai contar com informações dos atletas e das suas participações anteriores.\n\nbase <- dados_olimpiadas %>%\n # Unindo a tabela resposta a base total para manter apenas \n # os atletas dos quais conseguimos montar variável resposta\n inner_join(resposta, by = 'athlete') %>%\n # Removendo dados de 2016 (pois deste ano tiramos a variável resposta)\n filter(year != 2016) %>%\n # Remove a coluna n (que veio ao juntar as bases)\n select(-n) %>% \n # agrupando por atleta\n group_by(athlete) %>% \n # montando variáveis independentes para cada atleta\n summarize(total_medalhas = n(),\n ouro = sum(medal == 'Gold'),\n prata = sum(medal == 'Silver'),\n bronze = sum(medal == 'Bronze'),\n total_olympics = n_distinct(year),\n medal_olympics_kpi = n()/n_distinct(year),\n gender = unique(gender[gender != 'Mixed']),\n n_eventos = n_distinct(event)) %>% \n mutate(ouro = ouro/total_medalhas,\n prata = prata/total_medalhas,\n bronze = bronze/total_medalhas)\n\nbase_final <- base %>% \n # unir novamente com a base de resposta\n inner_join(resposta, by = 'athlete') %>% \n # renomear coluna n para y\n rename(y = n) %>% \n # desagrupar\n ungroup() %>% \n # remover a coluna com nome\n select(-athlete)\n\nCom isto estamos prontos para checar o quanto essas variáveis podem prever quantas medalhas um atleta conquistará em 2016. Por se tratar de uma variável resposta de contagem, não é adequado usar uma regressão linear simples, duas alternativas são modelos de poisson e binomial negativa. Aqui utilizaremos um modelo de poisson.\n\nmodelo <- glm(y ~ ., data = base_final, family = 'poisson')\nsummary(modelo)\n\n\nCall:\nglm(formula = y ~ ., family = \"poisson\", data = base_final)\n\nDeviance Residuals: \n Min 1Q Median 3Q Max \n-2.03793 -0.59747 -0.07415 0.46524 1.76581 \n\nCoefficients: (1 not defined because of singularities)\n Estimate Std. Error z value Pr(>|z|) \n(Intercept) 0.31605 0.36604 0.863 0.3879 \ntotal_medalhas -0.01995 0.05408 -0.369 0.7122 \nouro 0.19491 0.22641 0.861 0.3893 \nprata 0.14087 0.26165 0.538 0.5903 \nbronze NA NA NA NA \ntotal_olympics -0.21896 0.18431 -1.188 0.2348 \nmedal_olympics_kpi 0.28235 0.13744 2.054 0.0399 *\ngenderWomen 0.19268 0.12956 1.487 0.1370 \nn_eventos 0.01706 0.12647 0.135 0.8927 \n---\nSignif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n\n(Dispersion parameter for poisson family taken to be 1)\n\n Null deviance: 111.157 on 106 degrees of freedom\nResidual deviance: 59.115 on 99 degrees of freedom\nAIC: 355.94\n\nNumber of Fisher Scoring iterations: 4\n\n\nAqui observamos pela coluna Pr(>|z|) o p-valor de cada variável. Por padrão, quando este valor é <= 0.10 aparece um símbolo chamado Signif. codes a direita. Quanto menor o p-valor, maior esse símbolo, ou seja, quanto maior a importância da variável, maior o símbolo.\nPelo summary(modelo) descobrimos que a proporção de medalhas de bronze não está gerando nenhum resultado para predição do modelo, por isso os campos em NA aparecem para ela.\nDaqui para frente, por se tratar de um modelo com poucas variáveis e um exemplo simples, fui criando novos modelos, onde em cada um deles removia uma variável. Primeiro bronze, depois n_eventos e assim por diante. A cada novo modelo eu chequei qual a variável de menor importância, ou seja, maior p-valor e removo-a, isto é importante porque cada remoção vai impactar na importância de todas as outras. No fim, quando cheguei num modelo onde todas as variáveis eram relevantes, obtive o seguinte modelo:\n\nmodelo5 <-\n glm(y ~ medal_olympics_kpi + total_olympics,\n data = base_final,\n family = 'poisson')\nsummary(modelo5)\n\n\nCall:\nglm(formula = y ~ medal_olympics_kpi + total_olympics, family = \"poisson\", \n data = base_final)\n\nDeviance Residuals: \n Min 1Q Median 3Q Max \n-1.84737 -0.69446 -0.09312 0.45457 1.68875 \n\nCoefficients:\n Estimate Std. Error z value Pr(>|z|) \n(Intercept) 0.64174 0.15547 4.128 3.66e-05 ***\nmedal_olympics_kpi 0.26467 0.03805 6.956 3.49e-12 ***\ntotal_olympics -0.28385 0.08063 -3.521 0.000431 ***\n---\nSignif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n\n(Dispersion parameter for poisson family taken to be 1)\n\n Null deviance: 111.157 on 106 degrees of freedom\nResidual deviance: 61.791 on 104 degrees of freedom\nAIC: 348.61\n\nNumber of Fisher Scoring iterations: 4\n\n\nObserve que temos o kpi com influência positiva, ou seja, quanto mais medalhas por olimpíada um atleta tem em olimpíadas anteriores, mais medalhas ele pode conseguir em 2016. Do contrário temos a variável total_olympics que tem influência negativa, ou seja, quanto mais olimpíadas o atleta tiver participado, menos medalhas ele pode ganhar em 2016. Essa interpretação pode parecer estranha, mas lembre-se da sua relação com a idade, quanto mais olimpíadas nas costas, mais velho o atleta é.\nAgora vamos buscar evidências do poder de predição do modelo, no próprio summary(model) temos o AIC, uma métrica que fica menor a medida que o poder de predição melhora. Se compararmos o AIC do primeiro e do último modelo, vemos uma diminuição, mas precisamos verificar os resíduos por exemplo.\n\nggplot(modelo5, aes(x = .fitted, y = .resid)) +\n geom_point() +\n geom_hline(yintercept = 0) +\n ggtitle(\"Gráfico de resíduos versus valor predito\") +\n theme(panel.background = element_rect(fill = \"white\"))\n\n\n\n\n\n\n\nQuando plotamos o gráfico de resíduos versus os valores preditos, a distribuição deveria ser aleatória em torno de 0, mas vemos que existe certa tendência, o que demonstra que o modelo precisa de melhorias. No nosso caso, mais observações e variáveis, provavelmente matariam a charada.\nALERTAAAA: A partir daqui, a leitura é recomendada para quem já tem conhecimento de regressão linear simples. \nConhecedores de LM e dispostos a ler, venham comigo!\nUm outro meio de checar a bondade do ajuste de um modelo poisson, é usar o desvio residual. Ele é similar a soma de quadrado dos resíduos que vemos na regressão linear, é calculada como a diferença entre o desvio dos valores preditos do modelo e o desvio do modelo nulo, que é o modelo que contém apenas o intercepto: residual deviance = deviance(fitted_model) - deviance(null_model).\nO desvio residual mede quanto de variabilidade dos dados não pode ser explicada depois de considerar o efeito dos preditores. Um desvio residual mais baixo, indica um melhor ajuste. Em geral, um desvio residual que é muito menor que os graus de liberdade do modelo, sugerem um bom ajuste. Os graus de liberdade de uma regressão poisson são iguais ao número de observações menos o número de coeficientes estimados.\nPodemos usar o desvio residual para rodar um teste de ajuste para regressão poisson. A hipótese nula diz que o modelo se ajusta bem aos dados, a alternativa diz o contrário. O teste estatístico de desvio residual e o p-valor, são calculados com base na distribuição qui-quadrado com graus de liberdade iguais a diferença entre os graus de liberdade do modelo ajustado e o modelo nulo.\n\nexpected <- fitted(modelo5)\n\n# Calculate the Pearson's chi-squared statistic and p-value\npearson_chisq <- sum((base_final$y - expected)^2 / expected)\np_value <- 1 - pchisq(pearson_chisq, df = df.residual(modelo5))\n\n# Display the results\ncat(\"Pearson's chi-squared test:\\n\")\n\nPearson's chi-squared test:\n\ncat(\"X-squared = \", pearson_chisq, \", df = \", df.residual(modelo5), \", p-value = \", p_value, \"\\n\")\n\nX-squared = 62.90335 , df = 104 , p-value = 0.9995126 \n\n\nO p-valor alto indica que não há evidência de falta de ajuste, juntando tudo que vimos sobre precisão do modelo, podemos concluir que “estamos no caminho certo para modelar a nossa variável resposta, mas o modelo carece de melhorias”. Uma base maior, além de melhorar a precisão como já mencionei, nos permitiria separar um grupo de teste onde poderíamos ter uma noção mais clara do quão bem o modelo prevê a partir de entradas inéditas.\nAgora sim, me despeço oficialmente, quem quiser saber mais sobre o modelo de poisson, segue uma ótima referência!\nRegressão Poisson: https://online.stat.psu.edu/stat462/node/209/" - }, - { - "objectID": "posts/2023-03-tidytuesday-paraolimpiadas/index.html#concluindo", - "href": "posts/2023-03-tidytuesday-paraolimpiadas/index.html#concluindo", - "title": "#TidyTuesday: Explorando dados sobre as Paraolimpíadas", - "section": "Concluindo", - "text": "Concluindo\nEssa foi uma breve demonstração do quanto o Tidytuesday é interessante e como podemos praticar nossas habilidades em tratamento de dados e análise. Esperamos que este artigo tenha inspirado você a explorar o mundo do TidyTuesday, e colocar a mão na massa no R, usando essa fonte de dados incrível para aprimorar suas habilidades em ciência de dados. Lembre-se que a comunidade tá aqui para te ajudar a alcançar seu objetivo em ciência de dados!" + "text": "R-Ladies São Paulo organized, on March 18, 2023, the event “Open Data Analysis with R - Open Data Day.” The activity took place on a Saturday, during the morning and afternoon, with 6 hours of activities.\nInsper, a non-profit institution dedicated to teaching and research, once again supported the group by providing the space for the event. Another support received was from Curso-R, which provided two teaching assistants to help out participants. The main objective of this event was to offer information about what open data is and its importance. Also, we aimed to promote the opportunity to do a “hands-on” activity exploring open data and tracking the current scenario of public data access at various levels of government and topics." }, { - "objectID": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html", - "href": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html", - "title": "Ações para ampliar a diversidade na comunidade R-Ladies São Paulo", + "objectID": "posts/2023-03-evento-open-data-day/english.html#introduction", + "href": "posts/2023-03-evento-open-data-day/english.html#introduction", + "title": "Event: Open Data Analysis with R", "section": "", - "text": "A R-Ladies é uma organização global cuja missão é promover a diversidade de gênero na comunidade R. A R-Ladies São Paulo, orgulhosamente, é um capítulo da R-Ladies Global, promovendo a diversidade de gênero na comunidade de R em São Paulo, no Brasil.\nNeste post, o nosso objetivo é discutir questões de diversidade atualmente na comunidade R-Ladies São Paulo, e as ações que têm sido feitas para ampliar a diversidade.\n\nEste post foi escrito em abril de 2023. Desde então, R-Ladies São Paulo recebeu um auxílio do R Consortium, o que permitiu à comunidade ampliar as ações para aumentar a diversidade.\n\n\n\n\nPicture of participants in a recent event.\n\n\nPara isso, dois pontos são importantes de serem discutidos: o conceito de interseccionalidade e questões relacionadas ao contexto brasileiro." + "text": "R-Ladies São Paulo organized, on March 18, 2023, the event “Open Data Analysis with R - Open Data Day.” The activity took place on a Saturday, during the morning and afternoon, with 6 hours of activities.\nInsper, a non-profit institution dedicated to teaching and research, once again supported the group by providing the space for the event. Another support received was from Curso-R, which provided two teaching assistants to help out participants. The main objective of this event was to offer information about what open data is and its importance. Also, we aimed to promote the opportunity to do a “hands-on” activity exploring open data and tracking the current scenario of public data access at various levels of government and topics." }, { - "objectID": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#introdução", - "href": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#introdução", - "title": "Ações para ampliar a diversidade na comunidade R-Ladies São Paulo", - "section": "", - "text": "A R-Ladies é uma organização global cuja missão é promover a diversidade de gênero na comunidade R. A R-Ladies São Paulo, orgulhosamente, é um capítulo da R-Ladies Global, promovendo a diversidade de gênero na comunidade de R em São Paulo, no Brasil.\nNeste post, o nosso objetivo é discutir questões de diversidade atualmente na comunidade R-Ladies São Paulo, e as ações que têm sido feitas para ampliar a diversidade.\n\nEste post foi escrito em abril de 2023. Desde então, R-Ladies São Paulo recebeu um auxílio do R Consortium, o que permitiu à comunidade ampliar as ações para aumentar a diversidade.\n\n\n\n\nPicture of participants in a recent event.\n\n\nPara isso, dois pontos são importantes de serem discutidos: o conceito de interseccionalidade e questões relacionadas ao contexto brasileiro." + "objectID": "posts/2023-03-evento-open-data-day/english.html#what-is-open-data-day", + "href": "posts/2023-03-evento-open-data-day/english.html#what-is-open-data-day", + "title": "Event: Open Data Analysis with R", + "section": "What is Open Data Day?", + "text": "What is Open Data Day?\nOpen Data Day is an annual celebration of open data worldwide, organized and supported by the Open Knowledge Foundation. If you want to know more, check the official Open Data Day website and the project page on the Open Knowledge Brasil website." }, { - "objectID": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#o-que-é-interseccionalidade", - "href": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#o-que-é-interseccionalidade", - "title": "Ações para ampliar a diversidade na comunidade R-Ladies São Paulo", - "section": "O que é Interseccionalidade?", - "text": "O que é Interseccionalidade?\nO público-alvo da R-Ladies são minorias de gênero, portanto: mulheres cis, mulheres trans, homens trans, pessoas não binárias e pessoas queer. O objetivo da comunidade é incluir esses grupos minoritários na comunidade de R. Porém, para cada um desses grupos de minorias de gêneros, existem pessoas que fazem parte de outros grupos que também podem sofrer outros tipos de exclusões e opressões, como: cor e raça, orientação sexual, maternidade, deficiências, idade, entre outros. Portanto, as opressões não são apenas baseadas no gênero da pessoa, e sim se relacionam e se sobrepõem. Esse entendimento é um conceito chamado “interseccionalidade”:\nSegundo Bridie Taylor (2019):\n\n“Interseccionalidade é o reconhecimento de que cada pessoa tem suas próprias experiências únicas de discriminação e opressão, e devemos considerar tudo e qualquer coisa que possa marginalizar as pessoas - gênero, raça, classe social, orientação sexual, habilidade física, etc.”\n\nAqui está um exemplo simples que pode ilustrar esse conceito: imagine uma mulher cisgênero branca e uma mulher cisgênero negra. Ambas sofrem opressão de gênero, mas somente a mulher negra sofre o racismo. Agora, considere uma mulher cisgênero, negra, bissexual, com filhos atípicos. Mesmo que a primeira e a última sofram opressão de gênero, não há dúvida de que a última sempre tem caminhos mais longos e difíceis para alcançar as mesmas posições.\nPortanto, é importante considerar a questão da diversidade de gênero, mas não se limitar às questões de gênero. É importante considerar também nas atividades da comunidade as intersecções que as pessoas participantes estão incluídas, para buscar ampliar a diversidade em diversos aspectos." + "objectID": "posts/2023-03-evento-open-data-day/english.html#main-activity", + "href": "posts/2023-03-evento-open-data-day/english.html#main-activity", + "title": "Event: Open Data Analysis with R", + "section": "Main activity", + "text": "Main activity\nWith about 40 people, we structured the event in four blocks. The first block was instructive and featured a sequence of brief presentations such as: what is the R-Ladies São Paulo community, what is Open Data Day and what is Open Data.\n\n\n\n\nThe objective was to make people feel free to work with open data, so we split the class into small working groups. Each group worked on a specific dataset and worked with a Teaching Assistant with experience analyzing that dataset, who guided the group to look into the data and understand them. So, the second block consisted of the following activities:\n\nThe explanation of how this activity would happen;\nA brief speech (about 5 minutes) by each Teaching Assistant on the topic of their expertise and on the dataset that the group would work on, to facilitate the identification of participants with the subject;\nAnd the separation of participants into groups according to the affinity of interests - everyone could choose the topic with more interest, and there was no need to resize or redistribute groups.\n\nThe topics and respective teaching assistants were:\n\nData on violence - Fernanda Peres, biomedical\nEnvironmental data on fires - Bianca Muniz, journalist\nEducational data - Ana Carolina Moreno, journalist\nEmployment data - Ana Paula Rocha, economist\nElection data - Cecília do Lago, journalist\nPrison data - Thandara Santos, sociologist\n\nIn addition, teaching assistants were available to help with questions about R:\n\nBeatriz Milz (R-Ladies SP co-organizer)\nIanní Muliterno (R-Ladies SP co-organizer)\nGeovana Lopes Batista (R-Ladies SP co-organizer)\nHaydee Svab (R-Ladies SP co-organizer)\nJulio Trecenti (Curso-R)\nWilliam Amorim (Curso-R)\n\nWe created a Google Document so the groups could take and share notes.\n\n\n\n\n\n\n\n\n\n\nThen, in the third block, the groups worked on importing, understanding, and starting to explore the open data of their respective themes. As many people pointed out that they had no experience creating data visualizations and were interested in getting started, co-organizer Beatriz Milz gave a short live coding presentation on using the Esquisse package to generate data visualizations with ggplot2.\n\n\n\n\nIn the fourth and last block, the groups presented some of their difficulties, lessons learned, and results (some even showed visualizations made!). In addition, interesting presentations reflected the topics addressed in the initial presentations on open data - for example, some groups indicated dealing with an outdated database, others pointed out that data was aggregated and could be made available with a greater level of detail, etc.\nThe experience was outstanding, and the organizers and participants demonstrated that they enjoyed the activity a lot (especially the children!). Each group had between two to six people in addition to the teaching assistants, which allowed for a more individualized follow-up to answer questions." }, { - "objectID": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#contexto-brasileiro", - "href": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#contexto-brasileiro", - "title": "Ações para ampliar a diversidade na comunidade R-Ladies São Paulo", - "section": "Contexto brasileiro", - "text": "Contexto brasileiro\nPor questões históricas, o Brasil apresenta uma composição racial diferente dependendo da região do país. A cidade de São Paulo está localizada na região Sudeste, onde 50,7% da população se auto-declara como branca, 38,7% como parda e 9,6% como preta (segundo dados da Pesquisa Nacional por Amostra de Domicílios Contínua (PNAD Contínua) do IBGE, referente à 20211). Considerando que a população negra é composta por pessoas pretas e pardas, quase metade da população na região Sudeste é negra.\nApesar de representarem cerca de metade da população da região, a população negra foi marginalizada, e segue sub-representada em espaços de poder, como na política, no ensino superior, em posições de liderança nas empresas entre outros.\n Fonte: IBGE - PNAD Contínua, 2021.\nOutra constatação relevante para entender o contexto brasileiro e os resultados apresentados neste texto é a informação de que o Brasil é um país violento com pessoas LGBTQIA+ e principalmente pessoas trans.\nOs resultados do estudo de Monitoramento de Assassinatos Trans (TMM) em 2022 podem ser vistos no mapa abaixo: o Brasil é o país com os maiores valores absolutos de assassinatos de pessoas transgêneras desde o início da série histórica obtida pelo TMM.\n Fonte: Trans Murder Monitoring (TMM) - 2022\nO tópico de trabalho e renda também é particularmente delicado para a população trans. Segundo o mapeamento de pessoas trans no município de São Paulo realizado em 20202, aproximadamente metade das pessoas entrevistadas saiu de casa entre 16 e 20 anos e destes, 30% por conta de brigas e 17% por conta de expulsão. Essa saída precoce impacta o acesso dessa população aos meios de gerar renda, considerando que 57% dos entrevistados não possui formação técnica ou específica e 42% não estava realizando nenhuma atividade remunerada no período da entrevista.\nEssas características da população brasileira são importantes para considerar na análise da diversidade das pessoas da comunidade." + "objectID": "posts/2023-03-evento-open-data-day/english.html#strengthening-the-community", + "href": "posts/2023-03-evento-open-data-day/english.html#strengthening-the-community", + "title": "Event: Open Data Analysis with R", + "section": "Strengthening the community", + "text": "Strengthening the community\nTwo interesting points to highlight are the collaborative coffee and the Gugudadados Space.\nCollaborative coffee\n\n\n\n\n\n\n\n\nWe made a collaborative coffee with items purchased by the organizing group (with the money received from the scholarship offered by OKBR) and food brought by participants. This way, people could get up and get coffee and something to eat at any time during the event. This coffee format (available the entire time of the event) is very good for three reasons: (i) it respects the time of the groups who can take their breaks as the work progresses; (ii) it welcomes participants who, for health reasons, cannot go without eating for many hours and (iii) welcomes participants who, due to socio-economic conditions, are unable to have a meal during their lunch break. Given the nature of the R-Ladies group, it is an important aspect to provide a welcoming environment so that everyone can enjoy the experience of the event regardless of having something to eat throughout the day, in addition to the fact that the collaborative coffee is also a way to encourage integration between people!\nGugudadados Space\nWe created the Gugudadados Space to facilitate the participation of people responsible for kids and babies (e.g., mothers, fathers, and caregivers). A baby and four children between 7 and 10 years old participated in this event. With the money from the scholarship offered by OKBR, it was possible to hire a recreational teacher in the Gugudadados Space (a room next to the event room, on the same floor) throughout the activity. The R-Ladies organizers also took toys, drawings, markers, games, and temporary tattoos to entertain and amuse the children." }, { - "objectID": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#pesquisa---2020", - "href": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#pesquisa---2020", - "title": "Ações para ampliar a diversidade na comunidade R-Ladies São Paulo", - "section": "Pesquisa - 2020", - "text": "Pesquisa - 2020\nEm 2020, realizamos um questionário online com as pessoas participantes da comunidade, com o objetivo de saber mais sobre a composição da comunidade, e como podemos ampliar a diversidade. O questionário foi divulgado nos nossos grupos, como Meetup e o Telegram, e obteve 161 respostas válidas.\nAbaixo, destacamos alguns pontos levantados ao analisar as respostas do questionário, tratando dos temas: diversidade de gênero, diversidade racial, inclusão de mães/pais/pessoas cuidadoras, inclusão de pessoas LGBTQIA+, alimentação e acesso geográfico. Esses gráficos são importantes para entender a composição da comunidade em 2020 e que ações precisamos fazer para ampliar a diversidade em grupos menos representados.\n\nDiversidade de gênero\n\n\n\nGráfico de barras onde o eixo X mostra a porcentagem de respondentes da pesquisa, e o eixo Y representa o gênero. Cerca de 93% das pessoas respondentes disseram que são mulheres cis ou transgênero; cerca de 3% disseram que são homens cis ou transgênero; e cerca de 3% disseram que são pessoas não-binárias.\n\n\nEm relação à diversidade de gênero, as respostas obtidas no questionário apontam a predominância de mulheres (cis ou trans). Um problema identificado posteriormente na estruturação do questionário é: as perguntas não permitiam identificar quantas pessoas trans faziam parte da comunidade. Portanto, não temos dados sobre quantas pessoas trans participavam da comunidade. Essa pergunta deverá ser incorporada em um questionário futuro.\n\n\nDiversidade racial\n\n\n\nGráfico de barras onde o eixo X mostra a porcentagem de respondentes da pesquisa, e o eixo Y representa a cor/raça. Cerca de 73% das pessoas respondentes disseram que são brancas; cerca de 14% disseram que são pardas; cerca de 9% disseram que são pretas; e cerca de 4% disseram que são amarelas.\n\n\nEm relação à diversidade racial na comunidade em 2020, é importante destacar que 73,3% das pessoas se auto-declaravam brancas, apesar da população branca nessa região do Brasil representar cerca de metade da população. Ou seja, temos uma sub-representação de pessoas negras na comunidade R-Ladies São Paulo e necessitamos agir com seriedade para promover inclusão étnico-racial.\nÉ importante também citar o texto escrito pela equipe da R-Ladies Global e a R Forwards sobre o #VidasNegrasImportam, em 2020. Na ocasião, o texto foi traduzido para português pela comunidade R-Ladies São Paulo e está disponível no blog da comunidade. Neste texto, a R-Ladies Global se comprometeu a melhorar a forma como a organização apoia pessoas negras, indígenas e de outros grupos não-brancos:\n\n“Como a missão da R-Ladies é focada em melhorar a diversidade de gênero na comunidade R, também reconhecemos a luta que as pessoas negras enfrentam e o efeito composto interseccional quando uma pessoa integrante se identifica com vários grupos sub-representados. […] Nos comprometemos a tornar os espaços da nossa comunidade lugares que ofereçam não apenas segurança para todas as pessoas que a integram, mas também um trabalho ativo em prol da equidade e da justiça.” Fonte: R-Ladies Global Blog.\n\nNo questionário, deixamos uma pergunta em formato aberto para que as pessoas pudessem oferecer sugestões para ampliar a diversidade étnico-racial na comunidade, e abaixo estão algumas sugestões oferecidas:\n\nDivulgar a R-Ladies em grupos que abordam a questão racial;\nCriar cotas para participação de pessoas negras;\nConvidar pessoas negras para palestrar;\nDivulgar estatísticas do grupo sobre essa lacuna de representatividade;\nPromover eventos focados com a temática de raça;\nRealizar eventos em regiões periféricas;\nPromover eventos focados para pessoas negras;\nTer pessoas negras participantes na organização da comunidade.\n\n\n\nInclusão de mães/pais/pessoas cuidadoras\n\n\n\nGráfico de barras onde o eixo X mostra a porcentagem de respondentes da pesquisa, e o eixo Y representa se a pessoa é mãe/pai/responsável. Cerca de 87% das pessoas respondentes disseram SIM e 13% disseram NÃO.\n\n\nEm 2020, 13% das pessoas respondentes apontaram que possuem filhos. Para incluir mais pessoas com filhos, algumas sugestões oferecidas por meio do questionário foram:\n\nDisponibilizarum espaço para deixar as crianças durante os eventos;\nRealizar a gravação dos eventos para que as mães/pais/pessoas cuidadoras possam assistir quando for mais cômodo;\nRealizar a transmissão online dos eventos para promover a participação de pessoas que não podem participar pessoalmente.\n\n\n\nInclusão de pessoas LGBTQIA+\n\n\n\nGráfico de barras onde o eixo X mostra a porcentagem de respondentes da pesquisa, e o eixo Y representa se a pessoa faz parte da comunidade LGBTQIA+. Cerca de 70% dos respondentes disseram NÃO e 30% disseram SIM.\n\n\nEm 2020, 30% das pessoas respondentes apontaram que fazem parte da comunidade LGBTQIA+. Apesar de não existirem dados sobre a porcentagem da população brasileira que faz parte da comunidade LGBTQIA+, os resultados desse questionário apontam que a comunidade está no caminho certo em termos de inclusão da população LGBTQIA+.\nDentre as sugestões oferecidas pela comunidade no formulário, com o objetivo de ampliar a participação de pessoas LGBTQIA+, destaca-se a questão do nome da comunidade. Algumas pessoas respondentes apontaram que o nome R-Ladies sugere que o grupo é apenas para mulheres, e desestimula pessoas de outros grupos a participarem por não ficar claro que são bem vindas.\n\n\nRegiões geográficas\nO mapa a seguir apresenta a Região Metropolitana de São Paulo (o maior polígono), e o município de São Paulo (separado por regiões). A maioria das pessoas que participam do evento são das regiões Oeste e Sul da cidade. Para ampliar a participação de pessoas das regiões Leste e Norte, é interessante realizar eventos nessas regiões.\n\n\n\nMapa da cidade de São Paulo: a maior parte dos respondentes disse que é das regiões Sul e Oeste da cidade." + "objectID": "posts/2023-03-evento-open-data-day/english.html#results-from-the-groups-during-the-event", + "href": "posts/2023-03-evento-open-data-day/english.html#results-from-the-groups-during-the-event", + "title": "Event: Open Data Analysis with R", + "section": "Results from the groups during the event", + "text": "Results from the groups during the event\nEducational data (T.A. Ana Carolina Moreno)\nThe T.A. presented the group with an R code for analyzing data from the Census of Basic Education used to produce a series of special reports on the impact of the pandemic on early childhood education, which aired in November 2022. The monitor also prepared a presentation on educational data to assist in understanding the different sources and databases available on education.\nThe data used can be obtained from the INEP website.\nElectoral data (T.A. Cecília do Lago):\nThis group explored electoral data for the 2022 elections, made available by the TSE. The group wanted to find out how many candidates did not receive one or zero votes in the 2022 election.\nThe data used can be obtained from the TSE’s Open Data Portal.\nEnvironmental data on Fires (T.A. Bianca Muniz):\nThis group explored data on fires in INPE’s BDQueimadas system. This system allows anyone to download data for up to one year. The T.A. prepared apresentation about how to download and import this dataset. The group exported data from 2020 to 2022, and the graph below shows the number of fires per month according to the biome where the fires occurred. It is possible to see in the graph that the biomes with the biggest amount of fires are the Amazon and the Cerrado, and they show seasonal patterns. For example, the highest peak of fires in the Amazon, from 2020 to 2022, was the second semester of 2022.\n\n\n\n\nThe data used can be obtained from the INPE - BD QUEIMADAS website.\nPrison data (T.A. Thandara Santos):\nThis group explored data from SISDEPEN - Statistical Data of the Brazilian Penitentiary System. These data come from the Prison Information Form, answered electronically every six months by government employees.\nOne of the difficulties presented by the group is the availability of data to be aggregated by prison unit rather than by individuals, which makes it impossible to do several fundamental analyses on the prison population in Brazil. Another area for improvement is the lack of standardization of the answers presented in the database, which implies low data reliability.\nThe data can be obtained from the National Secretariat for Penal Policies website.\nViolence data (T.A. Fernanda Peres):\nThis group explored public data on violence using data from SINAN - Information System for Aggravation of Notifications, filtering occurrences involving only adults and removing self-inflicted violence (for example, suicide). The group found that the public data on Violence in DataSUS were outdated. The dataset for 2020 was incomplete, so the group explored data for 2019. The group generated a series of graphs, such as the one below, showing that the largest number of victims are woman. In addition, it is noteworthy that the author of the aggression is most often male (whether the victim is a woman or a man).\n\n\n\n\nAnother thing pointed out by the group is that when the victims were women, the aggressor tended to be someone they knew, such as a spouse, ex-spouse, boyfriend, or ex-boyfriend. On the other hand, among men, the most common aggressor is a stranger.\n\n\n\n\nThis data can be downloaded from DATASUS. The T.A. gave a presentation on how to get this data.\nEmployment data group (T.A. Ana Paula):\nThe T.A. gave apresentation on how to import this data. First, the group explored two databases from Caged (General Register of Employed and Unemployed) from the Central Bank: the number of total jobs from 2000 to 2023; and the number of jobs in the manufacturing industry (any raw material that is processed) from 2000 to 2023.  The data can be obtained with the GetBCBData package, making it possible to search for updated data aggregated by month/year and time series I.D.\n\n# Loading packages\nlibrary(tidyverse)\nlibrary(GetBCBData)\n\n# Importing data\ndados_sgs <- GetBCBData::gbcbd_get_series(\n id = c('NCaged' = 28763, 'NCaged_IndTransf'= 28766),\n first.date = '2020-01-01',\n last.date = Sys.Date(),\n format.data = 'wide'\n)\n\n# Looking at the content\nglimpse(dados_sgs)\n\nRows: 37\nColumns: 3\n$ ref.date <date> 2020-01-01, 2020-02-01, 2020-03-01, 2020-04-01, 2020…\n$ NCaged <dbl> 37938640, 38155900, 37860843, 36879150, 36480704, 364…\n$ NCaged_IndTransf <dbl> 6924768, 6961283, 6918309, 6705220, 6600422, 6593132,…\n\n# Pivoting in order to prepare the dataset to ggplot2\ndados_sgs_longo <- dados_sgs %>% \n pivot_longer(cols = c(NCaged, NCaged_IndTransf))\n\n# Creating a graph\nggplot(dados_sgs_longo) +\n aes(x = ref.date, y = value, colour = name) +\n geom_line(show.legend = FALSE) +\n scale_color_hue(direction = 1) +\n theme_minimal() +\n facet_wrap(vars(name), scales = \"free_y\")\n\n\n\n\n\n\n\nTo learn more about this database, consult the Central Bank of Brazil Time Series Management System website." }, { - "objectID": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#ações-realizadas-para-aumentar-a-diversidade", - "href": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#ações-realizadas-para-aumentar-a-diversidade", - "title": "Ações para ampliar a diversidade na comunidade R-Ladies São Paulo", - "section": "Ações realizadas para aumentar a diversidade", - "text": "Ações realizadas para aumentar a diversidade\nO levantamento realizado em 2020 e as discussões estabelecidas acima, apontam a necessidade de um esforço coletivo da comunidade em busca da ampliação da diversidade.\nPara isso, algumas ações têm sido realizadas e serão brevemente comentadas a seguir. Em textos referentes à eventos recentes, as atividades foram descritas com maior detalhe, por exemplo:\n\nEvento: Análise de dados abertos com R\nEvento: Oficina de Introdução ao R\n\n\n\n\nFoto de participantes em eventos recentes.\n\n\n\nPolítica de ações afirmativas\nPara buscar ampliar a diversidade na participação nos evento, reservamos as vagas pensando em três grupos:\n\npessoas negras, pardas e indígenas\nmães\nmulheres e outras minorias de gênero\n\nAs vagas reservadas são também divulgadas nas redes sociais da comunidade (principalmente Instagram), para assim deixar claro que a presença desses grupos é bem vinda.\n\n\nEspaço GugudaDados\nO GuGuDaDados é um espaço colaborativo e experimental que as RLadies São Paulo propõem com o objetivo de deixar as crianças entretidas e cuidadas enquanto as pessoas responsáveis podem participar deatividades da comunidade com tranquilidade.\nCom o apoio financeiro de outras organizações, buscamos contratar uma professora recreadora para acompanhar as crianças no espaço Gugudadados (uma sala ao lado da sala das atividades dos adultos, no mesmo andar) durante todo o evento.\nAs organizadoras da R-Ladies também levam brinquedos, desenhos, canetinhas, jogos e tatuagens temporárias para entreter e divertir as crianças.\n\n\n\nFotos do espaço Gugudadados em eventos recentes.\n\n\n\n\nCafé colaborativo\nO café colaborativo é montado com itens comprados com o apoio financeiro de outras organizações e também comitens trazidos por participantes. Assim, as pessoas podem se alimentar em qualquer momento do evento.\nEsse formato de café (disponível ao longo detodo do evento) é muito bom por 3 motivos: (i) é um ótimo momento para conhecer e conversar com pessoas da comunidade; (ii) acolhe participantes que por questões de saúde não podem permanecer muitas horas sem comer e (iii) acolhe participantes que por condição socioeconômica não têm como fazer uma refeição no intervalo do almoço.\nDada a natureza do grupo R-Ladies, é um quesito importante prover um acolhimento mínimo necessário para que todas as pessoas tenham condições de usufruir da experiência do evento independente de ter o que comer ao longo do dia, além de que o café colaborativo também é uma forma de incentivar a integração entre as pessoas!\n\n\nAuxílio transporte e alimentação\nPara permitir que pessoas com pouca condição financeira tenham acesso e aproveitamento dos eventos, uma ação importante é o oferecimento de auxílio transporte e alimentação. O auxílio alimentação é oferecido em eventos presenciais que duram um dia inteiro. O auxílio transporte é oferecido em todos os eventos presenciais. Um ponto em destaque é que muitas pessoas que solicitam auxílio transporte são de cidades do interior (fora da Região Metropolitana de São Paulo), o que mostra o potencial de criação de novos capítulos da R-Ladies nessas cidades.\n\nR-Ladies São Paulo recebeu um auxílio da R Consortium, o que permitiu à comunidade oferecer auxílio financeiro nos eventos.\n\n\n\nTrabalho em duplas\nNem todas as pessoas participantes possuem um notebook para levar para a atividade. Nós esperamos que todas as pessoas possam participar independente da condição financeira. Portanto, na divulgação, incentivamos que as pessoas participem independente de poder levar um computador. Assim, nos casos onde isso acontece, incentivamos que as pessoas formem duplas e trabalhem juntas durante o evento. Isso sempre funcionou e acaba estimulando uma maior proximidade e solidariedade entre as pessoas.\n\n\nIncentivo à caronas\nA cidade de São Paulo é muito grande, e dependendo de onde você precisa ir, é comum demorar 2 horas (ou mais!) em transporte público para se deslocar. Portanto, uma das dificuldades de se participar em um evento presencial é a mobilidade. Para amenizar essa dificuldade, incentivamos que as pessoas, ao final do evento, ofereçam caronas caso estejam de carro para as pessoas que moram em regiões próximas na cidade. Ainda é necessário aprimorar este incentivo para combinar, de forma segura, caronas também na ida ao evento (e não apenas no final)." + "objectID": "posts/2023-03-evento-open-data-day/english.html#information-about-participants", + "href": "posts/2023-03-evento-open-data-day/english.html#information-about-participants", + "title": "Event: Open Data Analysis with R", + "section": "Information about participants", + "text": "Information about participants\nWe want to increase the diversity in the events, so, in this edition, we separated a percentage of spots thinking about three groups:\n- BIPOC (Black, Indigenous, and people of color)\n- mothers;\n- women and other gender minorities.\nIn this event, 54 people signed up, and 37 participated. Below are some graphs showing information about the diversity of the participants.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThere is still a lot of work to do to include unrepresented groups at events, but compared to pre-pandemic events, we are making progress. It is essential to expand the publicity for the following events, especially for BIPOC (Black, Indigenous, and people of color), mothers, and trans and non-binary people. Also, it is important to look for venues to make events in the periphery." }, { - "objectID": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#ações-necessárias", - "href": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#ações-necessárias", - "title": "Ações para ampliar a diversidade na comunidade R-Ladies São Paulo", - "section": "Ações necessárias", - "text": "Ações necessárias\nBaseado no questionário de 2020 e na experiência da comunidade ao longo do tempo, percebe-se como necessidade as seguintes melhorias na dinâmica da organização:\n\nEstimular a aproximação e participação de pessoas que constituem alguma minoria social por meio de cotas, uma postura interna de discriminação positiva; incluir essas pessoas na organização; convidar para oferecer palestras/workshops; promover visibilidade e ceder espaço para que essas pessoas tragam seu olhar, experiência e percepção para a contínua estruturação da comunidade R-ladies.\nBuscar parcerias em regiões periféricas para conseguir realizar eventos nessas regiões, facilitando o acesso de pessoas que moram longe dos bairros centrais da cidade." + "objectID": "posts/2023-03-evento-open-data-day/english.html#difficulties", + "href": "posts/2023-03-evento-open-data-day/english.html#difficulties", + "title": "Event: Open Data Analysis with R", + "section": "Difficulties", + "text": "Difficulties\nThe main difficulty in organizing the event was the short time available for publicizing the activity, since the date and place were defined only six days in advance. Despite the available room having a capacity for 100 people, only 40 had enough time to organize themselves and register as participants.\nHowever, the presence of more than 40 people, including people from the organization, was enough to carry out the activity, with the presence of people really interested in the topic." }, { - "objectID": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#equipe-de-organização-atual", - "href": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#equipe-de-organização-atual", - "title": "Ações para ampliar a diversidade na comunidade R-Ladies São Paulo", - "section": "Equipe de organização atual", - "text": "Equipe de organização atual\nExistem várias pessoas envolvidas na organização atualmente na comunidade R-Ladies São Paulo. É importante citar que estão envolvidas pessoas pertencentes a diferentes grupos minoritários (como mulheres negras, mães, pessoas trans, pessoas não-binárias, pessoas LGBTQIA+, pessoas neurodivergentes e pessoas com mais de 40 anos), e isso é necessário para oferecer diferentes visões e experiências. Além disso, cabe destacar que a participação da organização é feita de forma voluntária.Portanto, aqui listamos e agradecemos as pessoas que atualmente participam das diversas etapas de organização da comunidade:\n \n\nAna Carolina Moreno\nAna Paula Rocha\nAngélica Custódio\nBeatriz Milz\nFernanda Peres\nGeovana Lopes Batista\nHaydee Svab\nIanní Muliterno\nJean Gabriel Reis do Prado\nLuana Antunes Tolentino Souza\nNathália Demétrio\nTatyane Paz Dominguez" + "objectID": "posts/2023-03-evento-open-data-day/english.html#commentaries", + "href": "posts/2023-03-evento-open-data-day/english.html#commentaries", + "title": "Event: Open Data Analysis with R", + "section": "Commentaries", + "text": "Commentaries\nIn addition to the description offered by the organization’s team, we would also like to share two commentaries shared by people who participated in the event:\nTatiana Peixoto:\n\nHello, I’m Tatiana, a 42-year-old cis woman, black, environmental engineer, and passionate about studying. I signed up for the event, not only for the training but also for the search for optimism, thus creating strength to enter the professional market again, as I spent a long time in the academic environment. On 18.03.23th, I understood that R-ladies is much more than an introductory programming event. This team brings a new look at programming, removing blockages and obstacles for all those who want to follow a beautiful path in data science. The event is of excellent quality. I felt welcomed, cared for, and very well treated. I would definitely attend other R-ladies events. In addition to all the kindness of the Insper team in receiving us. I hope that R-ladies SP will continue with new events and new projects because, like me, they will make a lot of people happy.\n\nJuliana Soprani:\n\nI take this opportunity to reinforce my congratulations on the event! It was really relevant!!! Not only technically, in learning data analysis and the use of R, but also on the issue of welcoming, triggering a sense of belonging to a group or purpose. For someone starting in the data area, or in a career transition, as in my case, it was very important to see so many women from different areas, ages, and backgrounds working with data and R and engaged in expanding access to the tool for minorities. I am grateful for the opportunity and hope to contribute to health data analysis in the future.\nLooking forward to upcoming meetings." }, { - "objectID": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#footnotes", - "href": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#footnotes", - "title": "Ações para ampliar a diversidade na comunidade R-Ladies São Paulo", - "section": "Notas de rodapé", - "text": "Notas de rodapé\n\n\nIBGE: Instituto Brasileiro de Geografia e Estatística. O IBGE é um órgão de estatísticas nacionais que realiza censos e é responsável pela coleta, armazenamento e disseminação de dados socioeconômicos sobre a população brasileira.↩︎\nO mapeamento de pessoas trans do município de São Paulo foi um dos primeiros do Brasil, ou seja, ainda não há dados para o contexto nacional. Fonte: Centro de estudo de cultura contemporânea, 2021.↩︎" + "objectID": "posts/2023-03-evento-open-data-day/english.html#support", + "href": "posts/2023-03-evento-open-data-day/english.html#support", + "title": "Event: Open Data Analysis with R", + "section": "Support", + "text": "Support\n\n\n\n\n\n\n\n\nIt is important to emphasize the importance of OKBR ’s financial support, which enabled the purchase of items for the coffee break, stickers, and hiring a recreator. \nThe rooms offered by Insper were crucial for the event to take place. The building is easily accessible by public transport. The meeting took place in a large space with internet access, tables, comfortable chairs, and easy access to a restaurant for lunch. The toboggan that is part of the building’s facilities is also a success and makes up one of the most joyful experiences for children who stay at Gugudadados.\nCurso-R also supported the event, providing two R teachers to assist in the activity and being available to help with questions from the participants." }, { - "objectID": "posts/2023-05-aprendendo-carol-moreno/index.html", - "href": "posts/2023-05-aprendendo-carol-moreno/index.html", - "title": "Aprendendo a programar em quatro capítulos", - "section": "", - "text": "Autoria\n\n\n\n\n\n\n\n\nCarol Moreno\n\n\n\nEste post foi escrito por Ana Carolina Moreno e publicado no Linkedin.\nA Carol é uma integrante da comunidade R-Ladies São Paulo, e atua como Jornalista de Dados Senior na TV Globo.\n\n\n\nDesde que comecei a dar cursos de programação, sempre vejo nos rostos de grande parte das pessoas participantes aquele “medo” de não conseguir. Faz um pouquinho de sentido, afinal, porque só dou cursos introdutórios, pra quem nunca programou, e boa parte deles têm como público minorias de gênero, porque são organizados pelo capítulo de São Paulo R-Ladies Global, do qual faço parte. Sabemos que, infelizmente, muitos grupos da população são ensinados desde cedo que “não servem” para a área de tecnologia…\nMas eu sempre começo essas aulas com um resuminho da minha trajetória, justamente pra derrubar vários mitos, e mostrar que é possível aprender novas habilidades, especialmente se você:\n\ntiver apoio adequado no aprendizado;\natrelar o aprendizado à sua realidade;\nidentificar os contextos em que você aprende melhor;\ninvestir na prática o que aprendeu;\ntiver incentivos pra aprender;\nconseguir compartilhar teus aprendizados.\n\nInspirada nessa reportagem excelente do Darlan Helder, compartilho abaixo um pouco dessa história.\n(Prólogo: eu sempre fiquei de recuperação em matemática, física, química, biologia… Minha mãe, que quase fez faculdade de matemática de tanto que gosta da área, até hoje acha estranho que eu seja referência no assunto pra qualquer pessoa que seja, quanto mais uma redação enorme.)\nCapítulo 1 - Carol Excel\nNos idos de 2012 tentei aprender R, mas o RStudio ainda estava nascendo… Eu tentei fuçar naquele site r-project.com, mas fracassei de forma retumbante. Achei que “aquilo não era pra mim”.\nUm pesquisador me sugeriu ir pro Stata, mas nunca encontrei muito sentido em softwares proprietários.\nNos cinco anos seguintes, continuei interessada nos dados educacionais, mas só conseguia fazer reportanges com base em análises feitas por outras pessoas. Algumas delas por sugestão minha, como essa comparando o perfil de quem estuda pedagogia com as demais carreiras de graduação.\nCapítulo 2 - Carol Query\nEm 2017, o incrível Leandro Bispo Oliveira apareceu na redação do g1 com uma apostilinha de SQL básico encadernada, e me ensinou em duas horas a acessar o datalake e fazer queries com a base do Bolsa Família. Graças a ele consegui fazer uma análise que ninguém tinha feito até então no jornalismo: “testar” as notas de cortes do Sisu (a USP, por exemplo, tinha umas notas altíssimas) para saber se elas eram compatíveis com a realidade do desempenho dos candidatos no Enem.\nNão tem nada como atrelar um conhecimento à aplicação prática na nossa realidade. E a minha realidade era: trabalho cobrindo educação, os dados abertos educacionais são muitos, ótimos, mas não tenho as técnicas pra fazer todas as reportagens que quero. E não quero depender de pesquisadores fazerem essa parte da produção de notícias.\nFoi por isso que decidi continuar aprendendo. Entrei num curso online de python para jornalistas. Fracassei, larguei pela metade.\nDaí entrei em outro curso online, de R para jornalistas. Tive problemas até pra instalar os programas. Larguei no comecinho.\nMas continuava de olho nas oportunidades pra aprender. Até que, no começo de 2019, o capítulo de São Paulo das R-Ladies Global anunciou um curso presencial, num sábado em que eu não estava de plantão, e passei o dia todo aprendendo com uma didática incrível, num ambiente acolhedor e inspirador. Resultado: comecei a finalmente conseguir responder a perguntas que sempre me pareceram relevantes e que ainda não tinham lido no jornalismo, como a desigualdade racial entre professores universitários e a evolução ao longo dos anos de escolas batizadas com nomes de generais da ditatura militar.\nAté então, penava bastante pra conseguir virar reportagens dirigidas porque meu trabalho envolvia muitas pautas que não usavam dados. Então nem sempre conseguia praticar o que aprendi (outro ponto fundamental pra avançar no aprendizado de qualquer coisa).\nEntendi também que, quando eu preciso aprender sobre um assunto desde o início, meu negócio é curso presencial (pode ser diferente pra outras pessoas). Quando já estou mais avançada, tudo bem fazer virtualmente algum curso pontual, para aprender melhor alguma habilidade que ainda acho que preciso praticar mais (nessa quinta, começo um curso de raspagem de dados, mal posso esperar!)\nCapítulo 3 - Carol Dados\nEm janeiro de 2020, passei de “repórter de Educação” para “produtora de dados” na redação de São Paulo da Globo (ganhei apelidos como “Carol Dados” e “Balcão da Média Móvel”). A partir de então, minha função principal era fuçar em dados, então a prática virou rotina. E não só os educacionais, de ciência, saúde e meio ambiente aos quais eu estava acostumada. Dados do Waze, do TSE, da Câmara Municipal de São Paulo, das reclamações do Disque 156…\nDois meses depois, veio a pandemia, que obrigou o poder público a criar novos indicadores baseados em dados e o jornalismo a explicar todos esses novos conceitos para uma sociedade confusa e aterrorizada.\nAí veio a necessidade de escrever códigos pra otimizar análises que eram feitas diariamente ou mesmo escrever códigos para permitir análises que, da forma como vinham do poder público, eram impossíveis de fazer de outras formas. Aqui entra o tal do incentivo pra aprender novas funções e formas de automatizar scripts pra não perder tempo com eles.\n(Pausa para agredecer todas as pessoas que manjam de R, SQL e Datasus e que eu atazanei durante meses a fio, em qualquer dia da semana e até de madrugada.)\nAlguns códigos saíam em menos de duas horas, outros viraram dashboard pra todas as equipes consultarem, um levou uns três meses pra ficar azeitadinho.\nTodo esse esforço valeu a pena, e me deu muito mais autonomia.\nO mais legal é que, ao contrário da maioria das pessoas no chamado “jornalismo de dados”, eu não fico em uma equipe “de dados”: sou parte de uma grande equipe de produção, mas sou a única com foco maior na missão de escarafunchar dados. Por isso, não fico longe da produção diária, nem me debruço meses produzindo uma única reportagem especial. Sigo cobrindo o chamado “hardnews”, mas consigo fazer isso aplicando o que aprendi sobre análise estatística e técnicas de ciências de dados pra qualificar a cobertura. Acredito que o impacto das reportagens acaba sendo muito mais abrangente.\nCapítulo 4 - Teacher Carol\nAinda sigo atazando muita gente com meus códigos, dependendo do que aparece (obrigada de novo!). Também tenho sempre buscado aprender coisas novas, quando o tempo permite, pra facilitar análises futuras.\nMas a principal mudança, desde 2020, é poder compartilhar o que aprendi com outras pessoas, principalmente jornalistas, e principalmente mulheres e minorias de gênero, que tenha interesse nessas habilidades. Nos últimos anos já dei vários cursos introdutórios de R, de SQL, de dados educacionais, de Lei de Acesso à Informação, de tudo isso junto e misturado.\nToda vez que elaboro um novo curso, consigo revisar o que já sei, aprender coisas novas, aprofundar alguns conhecimentos. Ensinar é uma das melhores formas de aprender.\nSempre é desafiador, mas pra mim sempre esteve claro que só aprendi o que sei hoje porque muitas pessoas investiram o tempo delas em me ajudar. Não acho que seria possível fazer de outra forma. Por isso, enxergo o ensino como uma forma de manter acesa essa corrente colaborativa.\nPS: Se você é jornalista ou estudante de jornalismo, a Jeduca: Associação de Jornalistas de Educação, em parceria com a Abraji - Associação Brasileira de Jornalismo Investigativo, vai dar mais uma vez o curso Jornalismo de educação: bases para a cobertura. É gratuito e, na minha opinião, é o curso mais completo de jornalismo educacional que existe hoje. São 12 aulas, e eu vou ministrar as duas sobre reportar com dados =)\nClique aqui para saber mais!" + "objectID": "posts/2023-03-evento-open-data-day/english.html#team", + "href": "posts/2023-03-evento-open-data-day/english.html#team", + "title": "Event: Open Data Analysis with R", + "section": "Team", + "text": "Team\nThis event was only possible with the collaboration of several people. Therefore, here is a list of people who participated in the various stages of organizing the event:\n\nAna Paula Rocha - organization, teaching assistant\nAna Carolina Moreno - organization, teaching assistant\nBeatriz Milz - organization, teaching assistant\nBianca Muniz - teaching assistant\nCecília do Lago - teaching assistant\nCélia Oliveira - Gugudadados space\nDiego Rabatone Oliveira - Gugudadados space\nFernanda Peres - organization, teaching assistant\nGeovana Lopes Batista - teaching assistant\nHaydee Svab - organization, teaching assistant, Gugudadados space\nIanní Muliterno - teaching assistant\nJulio Trecenti - teaching assistant\nTatyane Paz Dominguez - organization, Gugudadados space\nThandara Santos - teaching assistant\nWilliam Amorim - teaching assistant\n\nThe event would not be the same without your collaboration - we appreciate and greatly appreciate your participation!\nIn addition, we also thank everyone who participated!" }, { - "objectID": "posts/2023-03-evento-open-data-day/index.html", - "href": "posts/2023-03-evento-open-data-day/index.html", - "title": "Evento: Análise de dados abertos com R", - "section": "", - "text": "A R-Ladies São Paulo organizou, em 18 de março de 2023, o evento “Análise de Dados Abertos com R - Open Data Day”. A atividade aconteceu em um sábado, durante os períodos da manhã e da tarde, totalizando 6 horas efetivas de atividade.\nO Insper, uma instituição sem fins lucrativos dedicada ao ensino e à pesquisa, mais uma vez apoiou o grupo cedendo o espaço para a realização do evento. Outro apoio recebido foi da Curso-R, que cedeu dois monitores para auxiliar na monitoria, ajudando nas dúvidas. O principal objetivo deste encontro foi oferecer informações a respeito do que são e da importância dos dados abertos e promover oportunidade de pôr a “mão-na-massa” manipulando dados abertos, além de traçar o cenário atual de acesso a esses dados em vários níveis governamentais e áreas do conhecimento." + "objectID": "posts/2023-03-evento-open-data-day/english.html#next-events", + "href": "posts/2023-03-evento-open-data-day/english.html#next-events", + "title": "Event: Open Data Analysis with R", + "section": "Next events", + "text": "Next events\nThis was the first time we held an event with the idea of ​​working in “groups”, and it is certainly a format that worked well (the participants indicated that they preferred this way to expository lectures). We intend to organize other events in this format!\nThe next R-Ladies São Paulo event is scheduled for May, with a theme yet to be defined. If you are interested in participating, we recommend following our social media!" }, { - "objectID": "posts/2023-03-evento-open-data-day/index.html#introdução", - "href": "posts/2023-03-evento-open-data-day/index.html#introdução", - "title": "Evento: Análise de dados abertos com R", + "objectID": "posts/2023-05-open-data-day-educacao/index.html", + "href": "posts/2023-05-open-data-day-educacao/index.html", + "title": "Dados abertos de Educação: um exemplo aplicado ao jornalismo", "section": "", - "text": "A R-Ladies São Paulo organizou, em 18 de março de 2023, o evento “Análise de Dados Abertos com R - Open Data Day”. A atividade aconteceu em um sábado, durante os períodos da manhã e da tarde, totalizando 6 horas efetivas de atividade.\nO Insper, uma instituição sem fins lucrativos dedicada ao ensino e à pesquisa, mais uma vez apoiou o grupo cedendo o espaço para a realização do evento. Outro apoio recebido foi da Curso-R, que cedeu dois monitores para auxiliar na monitoria, ajudando nas dúvidas. O principal objetivo deste encontro foi oferecer informações a respeito do que são e da importância dos dados abertos e promover oportunidade de pôr a “mão-na-massa” manipulando dados abertos, além de traçar o cenário atual de acesso a esses dados em vários níveis governamentais e áreas do conhecimento." - }, - { - "objectID": "posts/2023-03-evento-open-data-day/index.html#o-que-é-o-open-data-day", - "href": "posts/2023-03-evento-open-data-day/index.html#o-que-é-o-open-data-day", - "title": "Evento: Análise de dados abertos com R", - "section": "O que é o Open Data Day?", - "text": "O que é o Open Data Day?\nO Open Data Day, ou “Dia dos Dados Abertos”, é uma celebração anual dos dados abertos em todo o mundo, organizado e apoiado pela Open Knowledge Foundation. Caso queira saber mais, consulte o site oficial do Open Data Day e a página do projeto no site da Open Knowledge Brasil." - }, - { - "objectID": "posts/2023-03-evento-open-data-day/index.html#atividade-principal", - "href": "posts/2023-03-evento-open-data-day/index.html#atividade-principal", - "title": "Evento: Análise de dados abertos com R", - "section": "Atividade principal", - "text": "Atividade principal\nContando com cerca de 40 pessoas, o dia foi estruturado em quatro blocos. O primeiro bloco teve caráter informativo e contou com uma sequência de breves apresentações como: o que é a comunidade R-Ladies São Paulo, o que é Open Data Day e o que são Dados Abertos.\n\n\n\n\nComo era objetivo que as pessoas se sentissem à vontade para mexer nas bases de dados abertos, experimentou-se o formato de dividir a turma em pequenos grupos de trabalho. Cada grupo trabalhou uma base específica e foi acompanhado de uma monitora com experiência na análise desses dados, que orientou o grupo a buscar os dados e entendê-los. Assim, o segundo bloco consistiu:\n\nda explicação de como aconteceria essa dinâmica;\nde uma fala breve (cerca de 5 minutos) de cada monitora sobre o tema de sua expertise e sobre a base de dados abertos que seria trabalhada, para facilitar a identificação das participantes com o tema;\ne da separação das participantes nos grupos segundo afinidade de interesses - a adesão foi livre e não houve necessidade de redimensionar ou redistribuir os grupos.\n\nOs temas e respectivas monitoras foram:\n\nDados sobre violência - Fernanda Peres, biomédica\nDados ambientais sobre queimadas - Bianca Muniz, jornalista\nDados educacionais - Ana Carolina Moreno, jornalista\nDados sobre emprego - Ana Paula Rocha, economista\nDados eleitorais - Cecília do Lago, jornalista\nDados prisionais - Thandara Santos, socióloga\n\nAlém disso, havia pessoas monitoras disponíveis para ajudar em dúvidas sobre R: \n\nBeatriz Milz (Organização R-Ladies SP)\nIanní Muliterno (Organização R-Ladies SP)\nGeovana Lopes Batista (Organização R-Ladies SP)\nHaydee Svab (Organização R-Ladies SP)\nJulio Trecenti (Curso-R)\nWilliam Amorim (Curso-R)\n\nFoi criado um Google Docs aberto para que os grupos pudessem fazer e compartilhar anotações.\n\n\n\n\n\n\n\n\n\n\nEntão, no terceiro bloco, os grupos trabalharam em importar, entender e começar a explorar os dados abertos de seus respectivos temas. Como muitas pessoas apontaram que não tinham experiência para criar visualizações de dados e tinham interesse em começar, a co-organizadora Beatriz Milz fez uma apresentação curta, em formato live coding, sobre o uso do pacote esquisse para gerar visualizações de dados com ggplot2.\n\n\n\n\nNo quarto e último bloco, os grupos apresentaram um pouco de suas dificuldades, aprendizados e resultados (alguns inclusive apresentaram visualizações feitas!). Foram apresentações interessantes que refletiram os tópicos abordados nas apresentações iniciais sobre dados abertos - por exemplo, alguns grupos indicaram lidar com base desatualizada, outros apontaram que dados estavam agregados e poderiam ser disponibilizados em forma de microdados, entre outros.\nA experiência foi muito boa, e as pessoas organizadoras e participantes demonstraram ter gostado bastante da atividade (principalmente as crianças!). Cada grupo teve entre duas e seis pessoas além das monitorias, o que permitiu um acompanhamento mais individualizado para sanar dúvidas e garantir o aproveitamento da atividade." - }, - { - "objectID": "posts/2023-03-evento-open-data-day/index.html#fortalecendo-a-comunidade", - "href": "posts/2023-03-evento-open-data-day/index.html#fortalecendo-a-comunidade", - "title": "Evento: Análise de dados abertos com R", - "section": "Fortalecendo a comunidade", - "text": "Fortalecendo a comunidade\nDois pontos interessantes a destacar são o café colaborativo e o Espaço Gugudadados.\nCafé Colaborativo\n\n\n\n\n\n\n\n\nO café colaborativo foi montado com itens comprados com o valor da bolsa oferecida pela OKBR, e também por itens trazidos por participantes. Assim, as pessoas puderam levantar e buscar café e algo para comer em qualquer momento do evento. Esse formato de café (disponível o tempo todo do evento) é muito bom por 3 motivos: (i) respeita o tempo dos grupos que podem fazer suas pausas conforme o andar dos trabalhos; (ii) acolhe participantes que por questões de saúde não podem permanecer muitas horas sem comer e (iii) acolhe participantes que por condição sócio-econômica não têm como fazer uma refeição no intervalo do almoço. Dada a natureza do grupo R-Ladies, é um quesito importante prover um acolhimento mínimo necessário para que todas as pessoas tenham condição de usufruir da experiência do evento independente de ter o que comer ao longo do dia, além de que o café colaborativo também é uma forma de incentivar a integração entre as pessoas!\nEspaço Gugudadados\nO Espaço Gugudadados é um espaço feito para facilitar a participação de mães e pessoas cuidadoras. Participaram um bebê e quatro crianças na faixa de 7 a 10 anos. Com o valor da bolsa oferecida pela OKBR foi possível contratar uma professora recreadora que esteve no espaço Gugudadados (uma sala ao lado da sala das atividades dos adultos, no mesmo andar) durante toda a atividade. As organizadoras da R-Ladies também levaram brinquedos, desenhos, canetinhas, jogos e tatuagens temporárias para entreter e divertir as crianças." - }, - { - "objectID": "posts/2023-03-evento-open-data-day/index.html#resultados-dos-grupos", - "href": "posts/2023-03-evento-open-data-day/index.html#resultados-dos-grupos", - "title": "Evento: Análise de dados abertos com R", - "section": "Resultados dos grupos", - "text": "Resultados dos grupos\nGrupo de dados educacionais (Monitora Ana Carolina Moreno)\nA monitora apresentou ao grupo um código em R de análise de dados do Censo da Educação Básica usado para a produção de uma série de reportagens especiais sobre o impacto da pandemia na educação infantil, que foi ao ar em novembro de 2022. A monitora também preparou uma apresentação sobre dados educacionais, para auxiliar no entendimento das diferentes fontes e bases de dados disponíveis sobre educação.\nOs dados utilizados podem ser obtidos no site do INEP. \nGrupo de dados eleitorais (Monitora Cecília do Lago):\nEste grupo explorou dados eleitorais referentes às eleições de 2022, disponibilizados pelo TSE. Uma curiosidade do grupo era descobrir quantos candidatos não receberam um ou nenhum voto na eleição de 2022.\nOs dados utilizados podem ser obtidos no Portal de Dados Abertos do TSE.\nGrupo de dados ambientais (Bianca Muniz):\nEste grupo explorou dados sobre focos de queimadas, no sistema BDQueimadas do INPE. Esse sistema permite fazer downloads de dados num período de até um ano. A monitora preparou uma apresentação sobre os dados utilizados. O grupo exportou os dados referentes à 2020 até 2022, e o gráfico a seguir permite ver a quantidade de focos de queimada por mês, segundo o bioma onde o foco de queimada acontece. É possível perceber no gráfico que os biomas com maiores focos de incêndio são a Amazônia e o Cerrado, e apresentam padrões sazonais. O maior pico de focos de queimadas na Amazônia no período pesquisado aconteceu no segundo semestre de 2022.\n\n\n\n\nOs dados utilizados podem ser obtidos no site do INPE - BD QUEIMADAS.\nGrupo de dados prisionais (Monitora Thandara Santos):\nEste grupo explorou dados do SISDEPEN - Dados Estatísticos do Sistema Penitenciário Brasileiro. Esses dados são provenientes do Formulário de Informações Prisionais, respondido de forma eletrônica semestralmente, por servidores indicados pelas Secretarias de administrações prisionais dos Estados e Distrito Federal e do Sistema Penitenciário Federal1.\nUma das dificuldades apresentadas pelo grupo é a disponibilização dos dados serem agregadas por unidade prisional, e não indivíduos, o que inviabiliza diversas análises importantes sobre a população carcerária do Brasil. Outra dificuldade apresentada é a falta de padronização às respostas apresentadas na base, o que implica em uma baixa confiabilidade dos dados. \nOs dados utilizados podem ser obtidos no site da Secretaria Nacional de Políticas Penais.\nGrupo de dados de violência (Monitora Fernanda Peres):\nEste grupo explorou dados públicos sobre violência usando os dados do SINAN - Sistema de Informações de Agravo de Notificações, filtrando ocorrências envolvendo apenas adultos e removendo cacos de violência auto-provocada (por exemplo, suicídio). O grupo constatou que os dados públicos de Violência no DataSUS estavam desatualizados. A base referente à 2020 estava incompleta, portanto o grupo explorou dados referentes a 2019. O grupo gerou uma série de gráficos, como o apresentado a seguir, que mostra que a maior quantidade de vítimas é do sexo feminino. Além disso, destaca-se que o autor da agressão na maioria das vezes é do sexo masculino (seja a vítima mulher ou homem).\n\n\n\n\nOutra ponto percebido é que quando as vítimas são mulheres, o agressor tende a ser alguém conhecido, como cônjuge, ex-cônjuge, namorado ou ex-namorado. Entre os homens, o agressor mais comum é um desconhecido.\n\n\n\n\nOs dados podem ser obtidos no DATASUS. A monitora fez uma apresentação sobre como obter esses dados.\nGrupo de dados de emprego (Monitora Ana Paula):\nA monitora fez uma apresentação sobre como obter esses dados. O grupo explorou duas bases de dados provenientes do Caged (Cadastro Geral de Empregados e Desempregados) a partir do Banco Central, sendo elas: número de empregos totais de 2000 a 2023; e número de empregos pela indústria de transformação (qualquer matéria prima que é transformada) de 2000 a 2023.  Os dados podem ser obtidos com o pacote GetBCBData, sendo possível buscar dados atualizados, porém agregados por mês/ano e ID da série temporal.\n\n# Carregando pacotes\nlibrary(tidyverse)\nlibrary(GetBCBData)\n\n# importando os dados\ndados_sgs <- GetBCBData::gbcbd_get_series(\n id = c('NCaged' = 28763, 'NCaged_IndTransf'= 28766),\n first.date = '2020-01-01',\n last.date = Sys.Date(),\n format.data = 'wide'\n)\n\n# espiar dados importados\nglimpse(dados_sgs)\n\nRows: 37\nColumns: 3\n$ ref.date <date> 2020-01-01, 2020-02-01, 2020-03-01, 2020-04-01, 2020…\n$ NCaged <dbl> 37938640, 38155900, 37860843, 36879150, 36480704, 364…\n$ NCaged_IndTransf <dbl> 6924768, 6961283, 6918309, 6705220, 6600422, 6593132,…\n\n# comparando a tendência de 2 séries\ndados_sgs_longo <- dados_sgs %>% \n pivot_longer(cols = c(NCaged, NCaged_IndTransf))\n\n# criando uma visualização\nggplot(dados_sgs_longo) +\n aes(x = ref.date, y = value, colour = name) +\n geom_line(show.legend = FALSE) +\n scale_color_hue(direction = 1) +\n theme_minimal() +\n facet_wrap(vars(name), scales = \"free_y\")\n\n\n\n\n\n\n\nPara saber mais sobre essa base de dados, consulte também a página do Sistema Gerenciador de Séries Temporais do Banco Central do Brasil." - }, - { - "objectID": "posts/2023-03-evento-open-data-day/index.html#perfil-das-pessoas-participantes", - "href": "posts/2023-03-evento-open-data-day/index.html#perfil-das-pessoas-participantes", - "title": "Evento: Análise de dados abertos com R", - "section": "Perfil das pessoas participantes", - "text": "Perfil das pessoas participantes\nPara buscar ampliar a diversidade na participação do evento, nesta edição reservamos as vagas pensando em três grupos:\n-   pessoas negras, pardas e indígenas;\n-   mães;\n-   mulheres e outras minorias de gênero.\nNeste evento, 54 pessoas se inscreveram, e dessas, 37 participaram. A seguir, apresentamos alguns gráficos que mostram informações sobre questões de diversidade coletadas das pessoas participantes.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nAinda há muito trabalho a fazer para incluir grupos menos representados nos eventos, mas acreditamos que, em comparação aos eventos anteriores à pandemia, estamos avançando. Para os próximos eventos, é importante ampliar a divulgação dos eventos para os grupos de pessoas pretas, pardas e indígenas; para mães, e para pessoas trans e não binárias, além de estarmos em busca de parcerias para realizar esse tipo de atividade na periferia." - }, - { - "objectID": "posts/2023-03-evento-open-data-day/index.html#dificuldades", - "href": "posts/2023-03-evento-open-data-day/index.html#dificuldades", - "title": "Evento: Análise de dados abertos com R", - "section": "Dificuldades", - "text": "Dificuldades\nA principal dificuldade na organização do evento foi o pouco tempo disponível para divulgação da atividade, já a definição da data e local foram feitas com apenas seis dias de antecedência. Apesar de a sala disponível ter capacidade para 100 pessoas, apenas 40 tiveram tempo hábil para se organizar e se inscrever como participantes. \nNo entanto, a presença final de mais de 40 pessoas, incluindo as pessoas das monitorias e organização, foi o suficiente para realizar a atividade, tendo a presença de pessoas muito interessadas!" - }, - { - "objectID": "posts/2023-03-evento-open-data-day/index.html#relatos", - "href": "posts/2023-03-evento-open-data-day/index.html#relatos", - "title": "Evento: Análise de dados abertos com R", - "section": "Relatos", - "text": "Relatos\nAlém do relato oferecido pela equipe da organização, gostaríamos de compartilhar também dois relatos compartilhados por pessoas que participaram do evento:\nTatiana Peixoto:\n\nOlá, eu sou a Tatiana, uma mulher de 42 anos, cis, negra, engenheira ambiental e apaixonada por estudar. Eu me inscrevi no evento, não só pela capacitação, mas também pela busca de otimismo e assim criar forças para me inserir novamente no mercado profissional, pois fiquei muito tempo no meio acadêmico. No dia 18.03.23, compreendi que a R-ladies é muito mais que um evento introdutório de programação. Essa equipe traz um novo olhar sobre a programação, tirando os bloqueios e os obstáculos para todes aqueles que querem seguir uma bela trajetória na ciência de dados. O evento é de ótima qualidade. Eu me senti acolhida, cuidada e muito bem tratada. Eu com certeza participaria de outros eventos da R-ladies. Além de toda a gentileza da equipe do Insper em nos receber. Espero que a R-ladies SP, siga com novos eventos e novos projetos, pois assim como eu, vocês farão muitas pessoas felizes.\n\nJuliana Soprani:\n\nAproveito para reforçar minhas parabenizações pelo evento! Foi realmente muito relevante!!! Não só tecnicamente, no aprendizado de análise de dados e do uso do R, mas também sobre a questão do acolhimento, desencadeando uma sensação de pertencimento a um grupo ou propósito. Para quem está iniciando na área de dados, ou em transição de carreira, como no meu caso, foi muito importante ver tantas mulheres de diferentes áreas, idades e cenários trabalhando com dados e R e engajadas em ampliar o acesso à ferramenta para as minorias. Agradeço a oportunidade e espero futuramente poder contribuir com análise de dados em saúde. Ansiosa pelos próximos encontros." - }, - { - "objectID": "posts/2023-03-evento-open-data-day/index.html#apoios", - "href": "posts/2023-03-evento-open-data-day/index.html#apoios", - "title": "Evento: Análise de dados abertos com R", - "section": "Apoios", - "text": "Apoios\n\n\n\n\n\n\n\n\nÉ importante ressaltar a importância do apoio financeiro da OKBR, que possibilitou a compra de itens para o coffee break, adesivos e também a contratação de uma recreadora. \nAs salas oferecidas pelo Insper foram cruciais para a realização do evento. O prédio é de fácil acesso por transporte público. O encontro aconteceu em um espaço amplo, que conta com acesso à internet, mesas, cadeiras confortáveis e facilidade de acesso a restaurante para o almoço. O tobogã que faz parte das instalações do prédio também é um sucesso e compõe uma das experiências mais alegres para as crianças que ficaram no Gugudadados.\nA Curso-R também apoiou o evento, cedendo dois monitores para auxiliar na monitoria, ficando à disposição para ajudar nas dúvidas das pessoas participantes." - }, - { - "objectID": "posts/2023-03-evento-open-data-day/index.html#equipe", - "href": "posts/2023-03-evento-open-data-day/index.html#equipe", - "title": "Evento: Análise de dados abertos com R", - "section": "Equipe", - "text": "Equipe\nEste evento não teria sido possível se não fosse a colaboração de várias pessoas. Portanto, aqui listamos pessoas que participaram das diversas etapas de organização do evento:\n\nAna Paula Rocha - organização, monitoria temática\nAna Carolina Moreno - organização, monitoria temática\nBeatriz Milz - organização, monitoria em R\nBianca Muniz - monitoria temática\nCecília do Lago - monitoria temática\nCélia Oliveira - recreadora do espaço Gugudadados\nDiego Rabatone Oliveira - espaço Gugudadados\nFernanda Peres - organização, monitoria temática\nGeovana Lopes Batista - monitoria em R\nHaydee Svab - organização, monitoria em R, espaço Gugudadados\nIanní Muliterno - monitoria em R\nJulio Trecenti - monitoria em R\nTatyane Paz Dominguez - organização, espaço Gugudadados\nThandara Santos - monitoria temática\nWilliam Amorim - monitoria em R\n\nO evento não seria o mesmo sem a colaboração de vocês - agradecemos e valorizamos muito a sua participação!\nAlém disso, agradecemos também todas as pessoas que participaram!" - }, - { - "objectID": "posts/2023-03-evento-open-data-day/index.html#próximos-eventos", - "href": "posts/2023-03-evento-open-data-day/index.html#próximos-eventos", - "title": "Evento: Análise de dados abertos com R", - "section": "Próximos eventos", - "text": "Próximos eventos\nEssa foi a primeira vez que realizamos evento com a ideia de trabalhar em “grupos”, e com certeza é um formato que funcionou (as participantes apontaram que preferiam assim do que palestras expositivas). Pretendemos organizar outros eventos nesse formato!\nO próximo evento da R-Ladies São Paulo está previsto para acontecer em maio, com tema ainda a ser definido. Caso tenha interesse em participar, recomendamos acompanhar nossas redes sociais!\n\n\n\n\n\n\n\n\nAté o próximo encontro!" - }, - { - "objectID": "posts/2023-03-evento-open-data-day/index.html#footnotes", - "href": "posts/2023-03-evento-open-data-day/index.html#footnotes", - "title": "Evento: Análise de dados abertos com R", - "section": "Notas de rodapé", - "text": "Notas de rodapé\n\nFonte: SISDEPEN.↩︎" + "text": "Este post é um relato realizado a partir da atividade de um dos grupos participantes do evento “Análise de dados abertos com R”, vinculado ao Open Data Day. Este grupo trabalhou com dados abertos educacionais.\nA monitora do grupo foi Ana Carolina Moreno, jornalista e produtora de dados da TV Globo. Especializada há mais de dez anos na cobertura de dados educacionais, ela apresentou ao grupo um código em R de análise de dados do Censo da Educação Básica usado para a produção de uma série de reportagens especiais sobre o impacto da pandemia na educação infantil, que foi ao ar em novembro de 2022.  Os dados utilizados podem ser obtidosno site do Inep.\nSeis pessoas se interessaram por explorar dados abertos educacionais: Aline Durans, Cristiane Lacerda, Hayane Sena De Jesus, Katia Mine, Larissa Souza, e Natasha Meneguelli. Além disso, Geovana Lopes, do R-Ladies São Paulo, participou como monitora.\nPrimeiramente, foi feita uma introdução mostrando quais são e onde encontrar os dados abertos educacionais, além das mudanças recentes, com a retirada de bases de dados que antes eram públicas, com a justificativa de adequação à Lei Geral de Proteção de Dados (LGPD). A apresentação utilizada está disponível neste link.\n\n\n\n\nAntes de partirmos para a análise de fato dos dados, o código que gerou as tabelas foi apresentado ao grupo. Como parte das pessoas ainda tinha um contato inicial com o R e o RStudio, e como houve interesse em entender o código apresentado, acabamos priorizando uma explicação introdutória da linguagem de programação R.\nAcompanhamos as participantes desde a instalação das aplicações e o primeiro olhar geral sobre o que é a linguagem e como ela é bastante adequada para pessoas que querem fazer análise estatística em cima de bases de dados já existentes.\n\n# As funções descritas abaixo fazem parte do \n# pacote tidyverse!\n# Clique no nome da função para ler a sua documentação.\nlibrary(tidyverse)\n\nO código já escrito (link) serviu de base para mostrar às participantes algumas funções (read_csv(), write_csv(), select(), filter(), rename(), mutate(), left_join(), reduce() e case_when()), além de explicações sobre a sintaxe básica do R, como quando usar os parênteses, e os diferentes operadores: o de atribuição, o pipe e os operações lógicos para fazer filtros ou manipular valores nas colunas.\nDada a escassez de tempo, esse grupo não chegou a ver todo o código, até a geração de gráficos e a análise de fato dos dados. Mas as participantes consideraram que as explicações introdutórias sobre R foram mais produtivas para ajudá-las a dar o primeiro passo no aprendizado da linguagem.\nFinalmente, destaca-se que, apesar de os dados do Inep serem bem organizados, eles não estão isentos de obstáculos e dificuldades de análises. Para evitar incorrer em conclusões equivocadas, a dica é consultar técnicos e especialistas dos bancos de dados para checar possíveis erros de interpretação e até direcionamentos, no caso de obstáculos do processo analítico. Essas pessoas também conseguem explicar até que ponto as bases de dados disponíveis conseguem responder às perguntas que temos.\nPara finalizar este post, deixamos um relato de uma das pessoas participantes sobre a experiência da atividade:\n\nParticipar deste grupo foi uma experiência de aprendizagem incrível. Carol é uma excelente tradutora da linguagem R. Nos fez entender, acompanhar a lógica e ver que sim: é possível aprender R! Para além disto, é necessário e importante termos contato e analisar os dados abertos. Desde então duas reflexões rodeiam meus pensamentos: primeira, não é só desenvolver uma habilidade, trabalhar com dados exige responsabilidade com a transparência das informações. Segunda: Mais pessoas precisam ter contato com o R. A comunidade R Ladies é acolhedora, respeitadora e muito responsável com o processo de transferência de conhecimento. Foi um dia de muita aprendizagem, acolhida e entusiasmo!\n\nPara pessoas que tem interesse em saber mais sobre dados abertos educacionais, indicamos este vídeo:\n\n\n\n\nAté a próxima!" }, { "objectID": "posts/2023-01-evento-oficina-intro-R/index.html", @@ -329,88 +217,151 @@ "text": "Autoria\n\n\n\n\n\n\n\n\nFernanda Peres\n\n \n\nEste post foi escrito pela Fernanda Peres, uma integrante da comunidade R-Ladies São Paulo. Saiba mais sobre ela em sua página pessoal!\nA Fernanda tem um Canal no Youtube sobre estatística aplicada à vida real. Confira também a gravação do meetup apresentado pela Fernanda na R-Ladies SP, sobre como escolher o teste estatístico adequado!\nPost publicado originalmente no blog fernandafperes.com.br\n\n\n\n\n\n\n\n\n\n\n\nOs gráficos de barras com barras de erros\nSe você já teve contato com algum artigo científico, é provável que você tenha visto um gráfico como o acima. Trata-se de um gráfico de barras usado para representar medidas numéricas em diferentes grupos. Nesses gráficos, a altura da barra é determinada pela média do grupo e o T que se projeta para além da barra representa uma medida de dispersão baseada na média, como o desvio-padrão, o erro-padrão da média ou o intervalo de confiança para essa média.\n\n\n\n\n\n\n\n\nNo entanto, apesar de muito utilizado - principalmente em contextos acadêmicos - esse tipo de gráfico é alvo de críticas, algumas vezes fervorosas, e tem sido chamado pejorativamente de gráfico dinamite. O nome é uma brincadeira com a semelhança desse tipo de gráfico com um detonador de dinamite antigo, aqueles que aparecem em desenhos animados.\n\n\n\n\n\n\n\n\n\nUma breve busca pelo termo em inglês, dynamite plots, traz textos com títulos como Por que gráficos dinamite são péssimos, Gráficos dinamite: um mal absoluto? e até uma open letter intitulada Gráficos dinamite têm que morrer.\nO que eu sinto é que essa discussão é ainda bem rara aqui no Brasil. E mesmo publicando em revistas internacionais, apenas uma vez, há uns cinco anos, ouvimos da editora: “os gráficos têm que ser refeitos porque eu não publico gráficos de barras”. E nós ficamos perdidas: como representar os dados, então? Curiosamente, pesquisar outros artigos da mesma revista não ajudou muito porque, adivinhem, só tinha gráfico de barras.\nA proposta do post é: explicar quais as críticas aos “gráficos dinamite” e discutir quais as alternativas e esse tipo de gráfico, explicando como fazê-las usando o R - mais especificamente, o pacote ggplot2.\nPor que gráficos de barra não são ideais para representar variáveis numéricas?\nUma das principais críticas é que esse tipo gráfico resume o conjunto de dados a apenas duas informações: a média e a medida de variação. Dada essa simplificação, mesmo conjuntos de dados com distribuições bem diferentes podem dar origem ao mesmo gráfico de barras – desde que apresentem a mesma média e desvio-padrão, por exemplo.\nO gráfico de barras também não permite a visualização dos dados brutos – ao olharmos um gráfico de barras, não sabemos o tamanho de cada grupo, se há outliers (valores discrepantes) ou se a distribuição tem mais de uma moda.\nAlém disso, é importante lembrar que esses gráficos representam a média e medidas de dispersão baseadas nela. Mas, há dados que não são adequadamente representados pela média. Isso acontece quando temos distribuições assimétricas, ou conjuntos de dados com outliers. Nesses casos, a mediana será uma medida mais apropriada e devemos usar gráficos que se baseiem nela (os quais discutiremos a seguir).\nQuais as alternativas ao gráfico de dinamite?\nFazer gráfico de barras para variáveis numéricas é errado? Não. Por mais que você vá encontrar pessoas que digam que sim - mas, isso não é um consenso. O que é um fato é que esse tipo gráfico não será a escolha mais adequada para representar dados numéricos em muitas situações. Então, vejamos as alternativas ao gráfico de barras, com seus prós e contras.\nPara discutir as alternativas, vamos construir diferentes gráficos utilizando um mesmo banco de dados. Abaixo, temos um gráfico de barras com a altura da coluna representando a média e a barra de erros representando o desvio-padrão. Observe como os grupos A e C apresentam barras praticamente idênticas:\n\n\n\n\nGráfico de barras (“gráfico dinamite”) representando as médias e os desvios-padrão de três grupos: A, B e C.\n\n\n\n\nGráficos dotplot\nUma alternativa ao gráfico dinamite é o dotplot. Nesse gráfico, cada sujeito é representado por um ponto – ou seja, estamos visualizando os dados brutos.\nAlém disso, é comum sobrepor a esses pontos uma linha horizontal representando a média e uma barra de erros indicando uma medida de dispersão (que, assim como no gráfico de barras, pode ser o desvio-padrão, o erro-padrão da média ou o intervalo de confiança para a média).\n\n\n\n\nGráfico dot plot representando as médias e os desvios-padrão de três grupos: A, B e C.\n\n\n\n\nNote que o dotplot mostra muito mais informações que o gráfico de barras. Ao analisarmos o dotplot, conseguimos perceber que o grupo B é bem menor que os outros dois, sendo formado por apenas 10 sujeitos. Também notamos que nesse grupo parece haver valores discrepantes, bem superiores aos demais. O grupo C parece ser formado por dois subgrupos: há um grupo de pontos acima da média que está separado dos pontos abaixo da média. Esse padrão não é observado no grupo A (apesar de os grupos A e C terem médias e desvios-padrão praticamente idênticos).\nO que eu vejo como vantagens do dotplot? Além de ser um gráfico que nos permite visualizar os dados brutos, é um gráfico baseado em média. Se usamos um teste paramétrico para comparar os grupos, como o teste-t ou a ANOVA, a análise será baseada na média e em medidas de dispersão baseadas na média. Portanto, eu gosto de poder visualizar essas medidas no gráfico.\nPor outro lado, é um gráfico que não mostra diretamente quais pontos são outliers (ao contrário do boxplot, que discutiremos a seguir). Além disso, se estivermos trabalhando com amostras muito grandes, teremos muitos pontos no gráfico e a visualização ficará comprometida.\nEm resumo:\nVantagens do dotplot:\n\nPermite visualizar dos dados brutos\n\nInclui a média e uma medida de dispersão baseada na média - medidas utilizadas pelos testes paramétricos em seus cálculos\n\nDesvantagens do dotplot:\n\nNão mostra diretamente os outliers\n\nÉ de difícil visualização quando os grupos são grandes – deve ser usado preferencialmente em amostras menores\n\nComo fazer um dot plot no R?\nSegue o código usado para gerar o dot plot acima, usando o ggplot2.\nSe você não tem o hábito de usar o ggplot2, o código abaixo pode parecer assustador. Mas, ele é razoavelmente simples quando se entende a lógica de funcionamento do ggplot2. Se tiver interesse no pacote, recomendo essa playlist explicando como construir gráficos no ggplot2 do zero.\n\nlibrary(ggplot2)\n\nggplot(dados, aes(x = Grupo, y = Escores)) +\n geom_dotplot(binaxis = \"y\", stackdir = \"center\", alpha = 0.3,\n dotsize = 1, binwidth = 2, stackratio = 1.4,\n position = position_dodge(width = 0.9), show.legend = F,\n fill = \"grey70\") +\n geom_errorbar(stat = \"summary\", fun.data = \"mean_sd\",\n position = position_dodge(width = 0.9), width = 0.15) +\n geom_crossbar(stat = \"summary\", fun = \"mean\", aes(ymin = ..y.., ymax = ..y..),\n fatten = 0.2, width = 0.5, position = position_dodge(width = 0.9),\n show.legend = F) +\n theme_classic()\n\nGráficos boxplot\nOutra alternativa é o boxplot. O boxplot resume, em uma única figura, cinco medidas de posição: limite inferior, quartil 1 (percentil 25%), mediana, quartil 3 (percentil 75%) e limite superior. Além disso, ele é um gráfico excelente para visualizar valores discrepantes (outliers). Caso tenha interesse em entender melhor a estrutura do boxplot, recomendo a leitura desse post\n\n\n\n\nEstrutura básica de um gráfico boxplot.\n\n\n\n\nAplicando aos nossos dados, obtemos o gráfico abaixo. Observe que rapidamente conseguimos detectar que o grupo B apresenta dois valores outliers acima do limite superior:\n\n\n\n\nGráfico boxplot para três grupos: A, B e C.\n\n\n\n\nAssim como o dot plot, o boxplot mostra muito mais informações que o gráfico de barras: cinco medidas de posição + outliers. Além disso, conseguimos avaliar a dispersão dos dados através da altura da caixa (que representa a amplitude interquartil) e da distância entre o limite inferior e o superior.\nPorém, é importante entender que as medidas representadas em um boxplot não são aquelas usadas em testes paramétricos - o que significa que esse pode não ser o gráfico ideal para representar dados analisados por esses testes. Além disso, o boxplot só pode ser usado em amostras maiores. O n mínimo para estimar as 5 medidas é n = 5, mas o ideal mesmo é usá-lo em amostras superiores a isso (ainda que não haja na literatura um consenso de qual seria esse n ideal).\nE, assim como o gráfico de barras, o boxplot não mostra os dados brutos. Ao olharmos para o boxplot não temos como saber o tamanho dos grupos ou se a distribuição tem mais de uma moda.\nEm resumo:\nVantagens do boxplot:\n\nInclui cinco medidas de posição\n\nMostra os valores que são outliers\n\n\nDesvantagens do boxplot:\n\nNão mostra os dados brutos\n\nNão deve ser usado quando o tamanho do grupo é pequeno (n < 5)\n\nNão mostra as medidas avaliadas por testes paramétricos\n\nAh, dada essa limitação do boxplot não mostrar os dados brutos, sugere-se que um dotplot seja sobreposto a ele, como no gráfico abaixo:\n\n\n\n\nGráfico boxplot com dot plot sobreposto representando três grupos: A, B e C.\n\n\n\n\nComo fazer um boxplot com dot plot sobreposto no R?\nSegue o código usado para gerar o boxplot acima, usando o ggplot2.\n\nlibrary(ggplot2)\n\nggplot(dados, aes(x = Grupo, y = Escores)) +\n geom_errorbar(stat = \"boxplot\", width = 0.2) +\n geom_boxplot(fill = \"white\", outlier.alpha = 0) +\n geom_dotplot(binaxis = \"y\", stackdir = \"center\", alpha = 0.3,\n dotsize = 1, binwidth = 1.6, stackratio = 1.4,\n position = position_dodge(width = 0.9), show.legend = F,\n fill = \"grey40\") +\n theme_classic()\n\nGráficos violino (violin plot)\nA terceira alternativa é o gráfico violino, em inglês violin plot. O gráfico violino é um gráfico que mostra a distribuição dos dados através de uma curva de densidade. Além disso, esse gráfico pode incluir em seu interior um boxplot. Se quiser entender mais sobre a construção de um gráfico violino, recomendo a leitura desse post.\nAplicando aos nossos dados, obtemos o gráfico a seguir:\n\n\n\n\nGráfico de violino representando as distribuições de três grupos: A, B e C.\n\n\n\n\nO gráfico nos permite observar que, apesar de terem a mesma média e desvio-padrão, os grupos A e C apresentam distribuições diferentes. Além disso, o grupo C apresenta uma distribuição bimodal (há dois picos).\nPor ter um boxplot em seu interior, o gráfico violino apresentará muitas das mesmas vantagens e desvantagens. Além disso, o n exigido para um gráfico de violino é superior ao n necessário para um boxplot. O gráfico violino não deve ser usado quando o tamanho do grupo é pequeno, já que nesses casos não será possível determinar corretamente a distribuição.\nOutra desvantagem é: trata-se de um gráfico recente e muito pouco conhecido (poucas pessoas declaram saber interpretá-lo).\nEm resumo:\nVantagens do gráfico de violino:\n\nPermite visualizar a distribuição dos dados\n\nSe incluir um boxplot em seu interior, mostra cinco medidas de posição\n\nDesvantagens do gráfico de violino:\n\nNão deve ser usado quando o tamanho do grupo é pequeno – nesses casos, não será possível determinar corretamente a distribuição\n\nNão mostra as medidas avaliadas por testes paramétricos\n\nNão mostra os dados brutos\n\nComo fazer um gráfico violino no R?\nSegue o código usado para gerar o gráfico violino acima, usando o ggplot2.\n\nlibrary(ggplot2)\n\nggplot(dados, aes(x = Grupo, y = Escores)) +\n geom_violin(fill = \"grey90\", trim = F) +\n geom_boxplot(width = 0.1, outlier.shape = 1) +\n theme_classic()\n\nAfinal, usar ou não o gráfico de barras para variáveis numéricas?\nUma desvantagem que se aplica a todas as alternativas ao gráfico de barras, na minha opinião, é: são gráficos muito menos difundidos e, por isso, uma audiência não-técnica terá dificuldade em interpretá-los. Acho esses gráficos incríveis para artigos científicos, para uso pelo time de análise de dados em uma empresa? Com certeza. Acho que são gráficos adequados para matérias jornalísticas ou para divulgação científica? Não. Nesses últimos cenários, mesmo com todas as críticas (válidas) ao gráfico de barras, eu tendo a preferi-lo. Afinal, um gráfico só é bom quando ele comunica com a sua audiência.\nO gráfico mais adequado vai depender: do teste estatístico que foi feito, do tamanho dos grupos, do seu público.\nSe gráficos são um assunto que te interessa, recomendo um livro que ganhou meu coração: o livro Storytelling com dados, escrito pela Cole Nussbaumer Knaflic.\nRecomendo também a leitura do artigo de Weissgerber et al. (2019), que resume as informações discutidas aqui.\nReferências:\n\n\n\n\nReferências\n\nWeissgerber, Tracey L, Stacey J Winham, Ethan P Heinzen, Jelena S Milin-Lazovic, Oscar Garcia-Valencia, Zoran Bukumiric, Marko D Savic, Vesna D Garovic, e Natasa M Milic. 2019. «Reveal, don’t conceal: transforming data visualization to improve transparency». Circulation 140 (18): 1506–18." }, { - "objectID": "eventos.html", - "href": "eventos.html", - "title": "Próximos eventos", + "objectID": "posts/2023-10-ws-ghibli/index.html", + "href": "posts/2023-10-ws-ghibli/index.html", + "title": "Raspando a página do Studio Ghibli, na Wikipédia", "section": "", - "text": "Acompanhe as novidades nas nossas redes sociais!" + "text": "Autoria\n\n\n\n\n\n\n\n\nFoto\n\n \n\nEste post foi escrito por Ornella Scardua Ferreira: .\n“Amo gráficos como amo cavalos. Gosto de música ruim e de cinema (bom). Sou apaixonada pelo Botafogo e pelo Bayern de Munique. Prefiro Vila Velha a qualquer lugar no mundo. Não tenho sonhos, mas um dia espero ver a Palestina livre.”\nFundado em 1985 pelos cineastas japoneses Hayao Miyazaki, Isao Takahata, Toshio Suzuki e Yasuyoshi Tokuma, o Studio Ghibli é um dos estúdios de animação japonesa mais famosos ao redor do mundo.\nAlém de serem reconhecidos pelos traços e cores muito singulares de seus personagens e cenários, os filmes, curtas e comercias do Studio Ghibli são muito aclamados pela crítica e pelo público devido, principalmente, à sensibilidade dos temas que cerceiam suas histórias e a maneira como elas são contadas para nós.\nPor isso tudo, que tal “scrapear” (ou raspar) a página do Studio Ghibli, na Wikipédia a maior enciclopédia colaborativa web do mundo, e coletar os dados de todos os filmes já lançados por esse estúdio de cinema? Scrapers e Ghibli-fãs, uni-vos!\nFigura 1: Imagem da página do Studio Ghibli, no Wikipédia.\nPara quem não conhece os filmes, muitos estão disponíveis na Netflix!" + }, + { + "objectID": "posts/2023-10-ws-ghibli/index.html#requisição", + "href": "posts/2023-10-ws-ghibli/index.html#requisição", + "title": "Raspando a página do Studio Ghibli, na Wikipédia", + "section": "Requisição", + "text": "Requisição\nInicialmente, inspecionamos a página do Studio Ghibli na Wikipédia para encontrar os elementos em HTML que estão associados exclusivamente às informações dos filmes (como título, ano de lançamento, duração, diretor, elenco etc). Felizmente, esses dados estão todos resumidos em uma única tabela dentre a única tabela que existe na página (na Seção Filmografia, para ser mais exata) - o que deixou a tarefa de raspagem muito mais fácil, por sinal.\n\n\n\n\nFigura 2: Imagem da inspeção na página do Studio Ghibli, no Wikipédia.\n\n\n\nEm primeiro lugar, vamos coletar somente os dados apresentados nessa tabela. Assim, simulamos a requisição apenas com a URL do site, sem deixar de salvar (com o nome filmes_ghibli.html) a página requerida no diretório output/. Como coletar essa tabela se trata de um scraping muito simples, já no próximo passo é possível ler o elemento HTML cujo parâmetro XPath é igual a //*[@id='mw-content-text']/div[1]/table[3], obtido conforme mostra a Figura 2.\nO código para o processo da requisição e leitura da tabela em HTML pode ser visto a seguir. Obs.: usamos a função xml_find_first() pois, nesse caso, existia uma única tabela.\n\n# URL da página do Wikipédia\n\nu_ghibli <- \"https://pt.wikipedia.org/wiki/Studio_Ghibli\"\n\n# requisicao GET\n\nr_ghibli <- httr::GET(\n u_ghibli, \n httr::write_disk(\"output/filmes_ghibli.html\", overwrite = TRUE) # salvar pagina no disco\n)\n\n# coletando a tabela\n\ntabela_ghibli <- r_ghibli |> \n xml2::read_html() |> # ler arquivo HTML\n xml2::xml_find_first(\"//*[@id='mw-content-text']/div[1]/table[3]\") # parametro XPath\n\nA tabela (ainda em HTML, lembrando) que acabamos de obter só contém as informações mais gerais dos filmes do Studio Ghibli. Mas… e se quisermos montar uma base de dados em que seja possível, por exemplo, analisar sobre a duração, gênero e elenco dos filmes? Bem, para esse fim, vamos continuar utilizando a tabela anterior, que, como podemos observar na Figura 2, está sob a tag <table> e o atributo class='wikitable unsortable'. Percebam, ainda, agora na Figura 3, que os títulos são links (identificados com a tag <a>) que direcionam para as páginas individuais de cada um dos filmes, locais onde estão as informações pelas quais estamos interessados.\n\n\n\n\nFigura 3: Imagem da inspeção dos títulos na tabela da página do Studio Ghibli, no Wikipédia.\n\n\n\nPara extrair esses links, precisamos encontrar todos os links disponíveis na tabela cuja classe é do tipo 'wikitable unsortable'. Logo, lemos a página HTML e coletamos todos os elementos (ou nós) que fazem parte das tags <a> e os atrbiutos do tipo href. Para tal tarefa, construímos o seguinte código:\n\nlinks_filmes <- r_ghibli |> \n xml2::read_html() |> # ler arquivo HTML\n xml2::xml_find_all(\"//table[@class='wikitable unsortable']//a\") |> # coletar todos os nos da tabela dentro das tags <a>\n xml2::xml_attr(\"href\") # coletar atributos href\n\nlinks_filmes\n #> [1] \"/wiki/Tenk%C5%AB_no_Shiro_Rapyuta\" \n #> [2] \"/wiki/Hayao_Miyazaki\" \n #> [3] \"/wiki/Isao_Takahata\" \n #> [4] \"/wiki/Joe_Hisaishi\" \n #> [5] \"/wiki/Hotaru_no_Haka\" \n #> [6] \"/wiki/Isao_Takahata\" \n #> [7] \"/wiki/Tonari_no_Totoro\" \n #> [8] \"/wiki/Majo_no_Takky%C5%ABbin\" \n #> [9] \"/wiki/Omoide_Poro_Poro\" \n #> [10] \"/wiki/Kurenai_no_Buta\" \n #> [11] \"/wiki/Umi_ga_Kikoeru\" \n #> [12] \"/wiki/Heisei_Tanuki_Gassen_Ponpoko\" \n #> [13] \"/wiki/Mimi_wo_Sumaseba\" \n #> [14] \"/wiki/Mononoke_Hime\" \n #> [15] \"/wiki/H%C5%8Dhokekyo_Tonari_no_Yamada-kun\"\n #> [16] \"/wiki/A_Viagem_de_Chihiro\" \n #> [17] \"/wiki/O_Reino_dos_Gatos\" \n #> [18] \"/wiki/Hiroyuki_Morita\" \n #> [19] \"/wiki/Hauru_no_Ugoku_Shiro\" \n #> [20] \"/wiki/Contos_de_Terramar\" \n #> [21] \"/wiki/Goro_Miyazaki\" \n #> [22] \"/wiki/Gake_no_ue_no_Ponyo\" \n #> [23] \"/wiki/Kari-gurashi_no_Arietti\" \n #> [24] \"/wiki/Hiromasa_Yonebayashi\" \n #> [25] \"/wiki/Kokuriko-zaka_Kara\" \n #> [26] \"/wiki/Kaze_Tachinu\" \n #> [27] \"/wiki/O_Conto_da_Princesa_Kaguya\" \n #> [28] \"/wiki/Yoshiaki_Nishimura\" \n #> [29] \"/wiki/Omoide_no_Marnie\" \n #> [30] \"/wiki/%C4%80ya_to_Majo\" \n #> [31] \"/wiki/Kimitachi_wa_Dou_Ikiru_ka\"\n\nNo entanto, os 31 links gerados são da forma /wiki/nome_do_filme, ou seja, inválidos. Validamo-os com o próximo código:\n\nlinks_filmes <- paste0(\"https://pt.wikipedia.org\", links_filmes)\n\nhead(links_filmes)\n #> [1] \"https://pt.wikipedia.org/wiki/Tenk%C5%AB_no_Shiro_Rapyuta\"\n #> [2] \"https://pt.wikipedia.org/wiki/Hayao_Miyazaki\" \n #> [3] \"https://pt.wikipedia.org/wiki/Isao_Takahata\" \n #> [4] \"https://pt.wikipedia.org/wiki/Joe_Hisaishi\" \n #> [5] \"https://pt.wikipedia.org/wiki/Hotaru_no_Haka\" \n #> [6] \"https://pt.wikipedia.org/wiki/Isao_Takahata\"\n\nUma vez corrigidos, podemos fazer a requisição de todas as páginas dos filmes de uma só vez, iterando o processo de tal maneira que algum erro que aconteça em alguma requisição seja identificado.\nA primeira função que vamos criar é a get_links(), cujo papel é simplesmente obter uma requisição da mesma forma que havíamos feito inicialmente.\n\nget_links <- function(links, ids) {\n arquivo <- paste0(\"output/\", ids, \".html\")\n r <- httr::GET(links, write_disk(arquivo, overwrite = TRUE))\n \n arquivo\n}\n\nA segunda função que vamos constuir, a get_progresso(), vai obter as requisições por meio da função get_links() adicionada da informação de erro com o auxílio da função purrr::possibly(). Vejam que, caso aconteça algum problema durante a requisição feita pela get_links(), a seguinte mensagem de erro aparecerá: “ERRO NA REQUISIÇÃO”. A mensagem pode ser escrita de acordo com o gosto do leitor, vale frisar.\nBom, já ao utilizar a função progressr::with_progress(), incluímos uma barra de progresso à iteração. Dois comentários importantes a serem feitos: (1) a função purrr::possibly() permite o andamento da iteração mesmo se houver algum erro no meio do caminho, e se ocorrer algum erro, ela identifica exatamente em qual momento o erro aconteceu; e (2) a barra de progresso serve para o acompanhamento de cada passo da iteração (Figura 4).\n\n# funcao para obter as requisicoes com erro\n\nget_progresso <- function(links, ids, progresso) {\n # progresso\n progresso()\n # mapear erros nas requisicoes\n get_erro <- purrr::possibly(get_links, otherwise = \"ERRO NA REQUISIÇÃO\")\n get_erro(links, ids)\n}\n\n# obtendo as requisicoes com erro e barra de progresso\n\nprogressr::with_progress({\n # barra de progresso\n progresso <- progressr::progressor(length(links_filmes))\n purrr::map2(\n links_filmes, seq_along(links_filmes), \n get_progresso, p = progresso\n )\n})\n #> [[1]]\n #> [1] \"output/1.html\"\n #> \n #> [[2]]\n #> [1] \"output/2.html\"\n #> \n #> [[3]]\n #> [1] \"output/3.html\"\n #> \n #> [[4]]\n #> [1] \"output/4.html\"\n #> \n #> [[5]]\n #> [1] \"output/5.html\"\n #> \n #> [[6]]\n #> [1] \"output/6.html\"\n #> \n #> [[7]]\n #> [1] \"output/7.html\"\n #> \n #> [[8]]\n #> [1] \"output/8.html\"\n #> \n #> [[9]]\n #> [1] \"output/9.html\"\n #> \n #> [[10]]\n #> [1] \"output/10.html\"\n #> \n #> [[11]]\n #> [1] \"output/11.html\"\n #> \n #> [[12]]\n #> [1] \"output/12.html\"\n #> \n #> [[13]]\n #> [1] \"output/13.html\"\n #> \n #> [[14]]\n #> [1] \"output/14.html\"\n #> \n #> [[15]]\n #> [1] \"output/15.html\"\n #> \n #> [[16]]\n #> [1] \"output/16.html\"\n #> \n #> [[17]]\n #> [1] \"output/17.html\"\n #> \n #> [[18]]\n #> [1] \"output/18.html\"\n #> \n #> [[19]]\n #> [1] \"output/19.html\"\n #> \n #> [[20]]\n #> [1] \"output/20.html\"\n #> \n #> [[21]]\n #> [1] \"output/21.html\"\n #> \n #> [[22]]\n #> [1] \"output/22.html\"\n #> \n #> [[23]]\n #> [1] \"output/23.html\"\n #> \n #> [[24]]\n #> [1] \"output/24.html\"\n #> \n #> [[25]]\n #> [1] \"output/25.html\"\n #> \n #> [[26]]\n #> [1] \"output/26.html\"\n #> \n #> [[27]]\n #> [1] \"output/27.html\"\n #> \n #> [[28]]\n #> [1] \"output/28.html\"\n #> \n #> [[29]]\n #> [1] \"output/29.html\"\n #> \n #> [[30]]\n #> [1] \"output/30.html\"\n #> \n #> [[31]]\n #> [1] \"output/31.html\"\n\nNenhum “ERRO NA REQUISIÇÃO”, yes!\nAh, na Figura 4 é possível ter uma ideia de como é uma barra de progresso.\n\n\n\n\nFigura 4: Barra de progresso na prática." + }, + { + "objectID": "posts/2023-10-ws-ghibli/index.html#parsing", + "href": "posts/2023-10-ws-ghibli/index.html#parsing", + "title": "Raspando a página do Studio Ghibli, na Wikipédia", + "section": "Parsing", + "text": "Parsing\nAo realizar raspagem de dados, a etapa de parsing nada mais é do que processar os dados brutos, que geralmente estão nos formatos .html ou .json, e posteriormente organizá-los de modo que consigamos realizar análises. Em nosso caso, coletamos dados .html tanto no cenário em que queríamos as informações expostas na tabelona da página do Studio Ghibli quanto no cenário em que buscamos as informações dos filmes em cada um dos links direcionáveis dispostos nessa mesma tabela. Em ambas as situações, transformamos os dados para um data frame (ou um tibble) ao fazer uma aplicação simples com a função rvest::html_table().\nNotem que, no segundo cenário, optamos pelo arquivo 5.html. Ele se refere ao filme “O Túmulo de Vagalumes”, o filme do Studio Ghibli preferido desta que vos escreve - mas o processo de parsing para qualquer um dos 31 arquivos gerados é o mesmo, caso seu filme favorito seja outro. Nesse caso, quando aplicamos a função mágica rvest::html_table(), o R retorna uma lista com 8 elementos, pois lembre-se que foram coletados todos os nós das tags <a> e todos os atributos da forma href.\n\n\n\n\nFigura 5: Box da página do Studio Ghibli, no Wikipédia, referente ao elemento [[1]].\n\n\n\nPara esse post, vamos nos limitar ao primeiro elemento ([[1]]), que corresponde ao box à direita na página https://pt.wikipedia.org/wiki/Hotaru_no_Haka (Figura 5), o qual contém informações bastante interessantes para uma análise sucinta do filme.\n\n# primeiro cenario\n\ntabela_ghibli <- tabela_ghibli |> \n rvest::html_table(header = TRUE) # transformar dados HTML em tibble\n\ntabela_ghibli\n #> # A tibble: 23 × 6\n #> Ano Título Diretor `Roteirista(s)` `Produtor(es)` Música\n #> <chr> <chr> <chr> <chr> <chr> <chr> \n #> 1 1986 Tenkū no Shiro Rapyuta Hayao … Hayao Miyazaki Isao Takahata Joe H…\n #> 2 1988 Hotaru no Haka Isao T… Isao Takahata Toru Hara Michi…\n #> 3 1988 Tonari no Totoro Hayao … Hayao Miyazaki Toru Hara Joe H…\n #> 4 1989 Majo no Takkyūbin Hayao … Hayao Miyazaki Hayao Miyazaki Joe H…\n #> 5 1991 Omoide Poro Poro Isao T… Isao Takahata Toshio Suzuki Katsu…\n #> 6 1992 Kurenai no Buta Hayao … Hayao Miyazaki Toshio Suzuki Joe H…\n #> 7 1993 Umi ga Kikoeru Tomomi… Keiko Niwa Toshio Suzuki Shige…\n #> 8 1994 Heisei Tanuki Gassen Pon… Isao T… Isao Takahata Toshio Suzuki Shang…\n #> 9 1995 Mimi wo Sumaseba Yoshif… Hayao Miyazaki Toshio Suzuki Yuji …\n #> 10 1997 Mononoke Hime Hayao … Hayao Miyazaki Toshio Suzuki Joe H…\n #> # ℹ 13 more rows\n\n\n# segundo cenario\n\ntumulo_vagalumes <- xml2::read_html(\"output/5.html\") |> \n rvest::html_table() # transformar dados HTML em tibble\n\ntumulo_vagalumes\n #> [[1]]\n #> # A tibble: 19 × 2\n #> `Hotaru no Haka` `Hotaru no Haka` \n #> <chr> <chr> \n #> 1 .mw-parser-output .noitalic{font-style:normal}火垂るの墓 \".mw-parser-output …\n #> 2 Hotaru no Haka \"Hotaru no Haka\" \n #> 3 No Brasil \"O Túmulo dos Vagal…\n #> 4 Em Portugal \"O Túmulo dos Piril…\n #> 5 Japão1988 •  cor •  89 min \"Japão1988 •  cor •…\n #> 6 Gênero \"drama[4]guerra[5]\" \n #> 7 Direção \"Isao Takahata\" \n #> 8 Produção \"Toru Hara\" \n #> 9 Roteiro \"Isao Takahata\" \n #> 10 Baseado em \"\\\"Hotaru no Haka\\\"…\n #> 11 Elenco \"Tsutomu TatsumiAya…\n #> 12 Música \"Michio Mamiya\" \n #> 13 Cinematografia \"Nobuo Koyama\" \n #> 14 Edição \"Takeshi Seyama\" \n #> 15 Companhia(s) produtora(s) \"Studio Ghibli\" \n #> 16 Distribuição \"Toho\" \n #> 17 Lançamento \"16 de abril de 198…\n #> 18 Idioma \"japonês\" \n #> 19 Receita \"¥ 590 milhões[6]\" \n #> \n #> [[2]]\n #> # A tibble: 20 × 4\n #> X1 X2 X3 X4 \n #> <chr> <chr> <chr> <lgl>\n #> 1 N.º \"Título\" Dura… NA \n #> 2 1. \"\\\"Setsuko to Seita ~ Main Title (節子と清太~メ… 2:57 NA \n #> 3 2. \"\\\"Yake Nohara (焼野原, Yake Nohara?)\\\"\" 6:51 NA \n #> 4 3. \"\\\"Haha no Shi (母の死, Haha no Shi?)\\\"\" 6:34 NA \n #> 5 4. \"\\\"Shoka (初夏, Shoka?)\\\"\" 3:14 NA \n #> 6 5. \"\\\"Ike no Hotori (池のほとり, Ike no Hotori?)\\\"\" 2:21 NA \n #> 7 6. \"\\\"Umi he (海へ, Umi he?)\\\"\" 1:37 NA \n #> 8 7. \"\\\"Namiuchigiwa (波打際, Namiuchigiwa?)\\\"\" 1:37 NA \n #> 9 8. \"\\\"Higasa (日傘, Higasa?)\\\"\" 2:26 NA \n #> 10 9. \"\\\"Sakura no Shita (桜の下, Sakura no Shita?)\\\"\" 1:31 NA \n #> 11 10. \"\\\"Dorobbusu (ドロップス, Dorobbusu?)\\\"\" 2:13 NA \n #> 12 11. \"\\\"Hikkoshi (引越し, Hikkoshi?)\\\"\" 2:17 NA \n #> 13 12. \"\\\"Keimai (兄弟, Keimai?)\\\"\" 2:15 NA \n #> 14 13. \"\\\"Hotaru (ほたる, Hotaru?)\\\"\" 4:12 NA \n #> 15 14. \"\\\"Hotaru no Haka (ほたるの墓, Hotaru no Haka?)\\\"\" 1:46 NA \n #> 16 15. \"\\\"Yuuyake (夕焼け, Yuuyake?)\\\"\" 0:53 NA \n #> 17 16. \"\\\"Shura (修羅, Shura?)\\\"\" 3:08 NA \n #> 18 17. \"\\\"Hika (悲劇, Hika?)\\\"\" 3:12 NA \n #> 19 18. \"\\\"Futari ~ End Title (ふたり~エンドタイトル, Fu… 8:52 NA \n #> 20 Duração total: \"Duração total:\" 58:13 NA \n #> \n #> [[3]]\n #> # A tibble: 3 × 2\n #> Classificação Classificação \n #> <chr> <chr> \n #> 1 Brasil: L[40]/12[34][35]\n #> 2 Japão: G[41] \n #> 3 Portugal: M/12[37] \n #> \n #> [[4]]\n #> # A tibble: 3 × 6\n #> Ano Premiação Categoria `Destinatário(s)` Resultado Ref. \n #> <int> <chr> <chr> <chr> <chr> <chr>\n #> 1 1988 Blue Ribbon Awards Prêmio E… Isao Takahata Venceu [30] \n #> 2 1994 Chicago International Child… Prêmio d… Isao Takahata Venceu [30] \n #> 3 1994 Chicago International Child… Prêmio d… Isao Takahata Venceu [30] \n #> \n #> [[5]]\n #> # A tibble: 4 × 2\n #> X1 X2 \n #> <chr> <chr>\n #> 1 \"Outros projetos Wikimedia também contêm material sobre Hotaru no Haka:\" Outr…\n #> 2 \"\" Cita…\n #> 3 \"\" Cate…\n #> 4 \"\" Base…\n #> \n #> [[6]]\n #> # A tibble: 8 × 9\n #> `vdeStudio Ghibli` `vdeStudio Ghibli` `vdeStudio Ghibli` `` `` `` \n #> <chr> <chr> <chr> <chr> <chr> <chr>\n #> 1 \"Hayao Miyazaki\\nIsao… \"Hayao Miyazaki\\n… \"Hayao Miyazaki\\n… <NA> <NA> <NA>\n #> 2 \"Filmografia\" \"Longas-metragens… \"Longas-metragens\" \"Ten… Curt… \"On …\n #> 3 \"Longas-metragens\" \"Tenkū no Shiro R… <NA> <NA> <NA> <NA>\n #> 4 \"Curtas-metragens\" \"On Your Mark (19… <NA> <NA> <NA> <NA>\n #> 5 \"Coproduções\" \"Shiki-Jitsu (200… <NA> <NA> <NA> <NA>\n #> 6 \"Jogos eletrônicos\" \"Jade Cocoon 2 (2… <NA> <NA> <NA> <NA>\n #> 7 \"Ver também\" \"Ghibli Museum Li… <NA> <NA> <NA> <NA>\n #> 8 \".mw-parser-output .s… \".mw-parser-outpu… \".mw-parser-outpu… <NA> <NA> <NA>\n #> # ℹ 3 more variables: `` <chr>, `` <chr>, `` <chr>\n #> \n #> [[7]]\n #> # A tibble: 3 × 2\n #> X1 X2 \n #> <chr> <chr> \n #> 1 Longas-metragens \"Tenkū no Shiro Rapyuta (1986)\\nHotaru no Haka (1988)\\nTonar…\n #> 2 Curtas-metragens \"On Your Mark (1995)\\nGiburīzu (2000)\\nFirumu Guru Guru (200…\n #> 3 Coproduções \"Shiki-Jitsu (2000)\\nInosensu: Kôkaku kidôtai (2004)\\nLa Tor…\n #> \n #> [[8]]\n #> # A tibble: 1 × 2\n #> X1 X2 \n #> <chr> <chr> \n #> 1 Controle de autoridade \": Q274520\\n WorldCat\\nVIAF: 316752206\\nANN (animé): 1…" + }, + { + "objectID": "posts/2023-11-evento-intro-r/index.html", + "href": "posts/2023-11-evento-intro-r/index.html", + "title": "Conhecendo o R, o Tidyverse e as R-Ladies", + "section": "", + "text": "Quando eu, Bianca, comecei no “mundinho dos dados”, as comunidades de tecnologia me ofereceram um espaço acolhedor para aprender sem o medo de errar. Falar de “espaço acolhedor”, pode parecer exagero e até contraditório; se errar faz parte do aprendizado, porque seria intimidador fazer isso enquanto se aprende, né? Mas, infelizmente, é muito fácil se sentir desencorajado quando é a primeira vez que você tem contato com uma tecnologia ou setor de atuação. A situação fica ainda mais chata quando se é integrante de um grupo sub-representado nesta área.\n\nOs relatos deste post são de participantes do último meetup organizado pela R-Ladies São Paulo. Ambas vivenciaram sua primeira experiência num evento das R-Ladies e ressaltam o sentimento de acolhimento para dar um primeiro passo no R. Mesmo sendo facilitadora do workshop, também estava ali fazendo algo pela primeira vez: apresentando a organização! Até pouco tempo, estava acompanhando de longe as atividades da comunidade (deixo aqui o convite para apresentarem também! Vamos hablar hehe)\nBoa leitura!" + }, + { + "objectID": "posts/2023-11-evento-intro-r/index.html#acolhe-pessoas-com-vontade-de-aprender-r", + "href": "posts/2023-11-evento-intro-r/index.html#acolhe-pessoas-com-vontade-de-aprender-r", + "title": "Conhecendo o R, o Tidyverse e as R-Ladies", + "section": "“Acolhe pessoas com vontade de aprender R”", + "text": "“Acolhe pessoas com vontade de aprender R”\npor Gabriela Morita\nEm 28 de outubro de 2023 participei do meu primeiro curso sobre a linguagem R. O curso “Introdução ao R - um curso para quem quer começar” foi organizado e desenvolvido pela equipe potente da #RLadiesSP, que faz parte da organização mundial R-Ladies, com o propósito de promover a diversidade de gênero na comunidade da linguagem R.\nO curso acolhe pessoas com vontade de aprender R, mesmo sem ter experiência ou contato prévio. O contato com as ferramentas é incentivado antes do encontro presencial, com tutoriais para a instalação do R e do RStudio, que são utilizados para desenvolver as atividades.\n\n\n\nNo dia do curso, são estabelecidas duas etapas:\n\nA etapa 1 (pela manhã), com introdução sobre a organização RLadies, e também apresentação sobre vantagens de usar o R\nE a etapa 2, à tarde, em que é apresentado os pacotes do Tidyverse e suas aplicações.\n\nAgradeço demais às R-Ladies SP - Bianca Muniz, Geovana Lopes, Haydee Svab e a Renata Hirota - que compartilharam seus conhecimentos e práticas neste encontro, foi um espaço de muito aprendizado, partilhas e num formato muito acolhedor e colaborativo." + }, + { + "objectID": "posts/2023-11-evento-intro-r/index.html#divagações-de-uma-iniciante-em-r", + "href": "posts/2023-11-evento-intro-r/index.html#divagações-de-uma-iniciante-em-r", + "title": "Conhecendo o R, o Tidyverse e as R-Ladies", + "section": "Divagações de uma iniciante em R", + "text": "Divagações de uma iniciante em R\npor Karina Ferrara Barros\nNo dia 28 de outubro de 2023 ocorreu o Evento R-Ladies São Paulo, do qual participei como iniciante no 'mundo R'. Em uma manhã e tarde de sábado mergulhei em um momento de aprendizagem proporcionado por uma equipe dedicada e disposta a ensinar e compartilhar conhecimento.\nA Oficina de Introdução ao R iniciou com a apresentação da comunidade R-Ladies, esforço global presente em 16 localidades brasileiras, seguindo com motivações para aprender linguagem R. Em preparo para adentrar no tema da Oficina, foi construído um ambiente muito acolhedor a partir da reflexão sobre o sentimento de exclusão compartilhado por diversos indivíduos, que se consideram inaptos a aprender este tipo de conhecimento por razões como \"ser de humanas demais\" ou \"não se dar bem com matemática\".\nDa minha parte, durante muito tempo me encaixei nesses rótulos e, após uma longa jornada de autoconhecimento e estudo, descobri que contextualizar conhecimentos que se mostram (a princípio) muito distantes de nossas afinidades torna a aprendizagem mais palpável e leve. Por esse motivo, no assunto seguinte abordado na Oficina, que eram os conceitos iniciais de programação, busquei algumas contextualizações para aproximar os ensinamentos sobre R.\nEm meio à dificuldade de materializar conceitos, passei por algumas divagações que me ajudaram a estabelecer pontes entre o meu \"eu\" de \"antes e depois\" do evento. Compartilho aqui estas divagações para explicar os conceitos de função e pacote, a partir dos aprendizados de um sábado com as R-Ladies.\n\nDe jogadas de handebol às funções do R\nNo handebol existem jogadas preestabelecidas que auxiliam atletas no momento do ataque. Essas jogadas consistem em um conjunto de movimentações e passes da bola que criam oportunidade para o arremesso ao gol. Praticantes treinam estas jogadas e as conhecem por nomes: \"araraquara\", \"argentina\", \"circulação\", \"loose\", \"roda\"... Ou seja, estas jogadas estão armazenadas nas memórias de jogadores e são identificadas por nomes, que significam determinadas movimentações.\n\n\n\n\n\nNo Evento R-Ladies aprendemos que funções são palavras que dão comandos ao computador. Por exemplo, mean é a palavra que dá o comando de obter média. As funções estão gravadas no programa, assim como as jogadas estão registradas nas memórias de atletas de handebol. No handebol, ao utilizar a palavra que expressa a jogada, a movimentação é realizada. No R, ao utilizar a palavra que expressa a função, o comando é realizado.\n\n\nDos métodos de Ballet aos pacotes do R\nExistem diferentes métodos da prática do Ballet, dos quais os mais famosos são o Vaganova (russo) e o Royal (inglês). Estes métodos abrigam conjuntos de passos de ballet que são executados pelos praticantes. A maioria dos passos tem nomes em comum nos métodos mencionados. Entretanto, apesar de compartilharem o mesmo nome, podem ocorrer diferenças na execução. Por exemplo, ao executar uma sequência de piruetas (aquele rodopio), é necessário conectá-las com um passo denominado fouetté, que se caracteriza como uma movimentação de perna em 90º graus seguido do recolhimento até o joelho. O fouetté em Royal tem o desenho de um quarto de círculo, levando a perna à frente e deslocando até o lado antes de ser recolhida. Já o fouetté em Vaganova a perna é levada diretamente ao lado e depois recolhida.\n\n\n\n\n\n\nNa Oficina aprendemos que as funções do R estão organizadas em conjuntos denominados pacotes. Ou seja, os pacotes são apanhados de palavras que dão comandos ao computador (funções). São exemplos de pacotes: dplyr, ggplot2, lubridate. Por comparação, da mesma forma que os métodos de ballet reúnem passos, os pacotes do R agrupam funções. Além disso, é possível que estes pacotes tenham nomes de funções em comum, mas que expressam diferenças no comando para o computador, assim como o fouetté em Vaganova e em Royal.\nFinalizando com as divagações, ressalto que o Evento R-Ladies não foi feito só de conceitos, dedicando uma parte considerável de tempo à prática e exercícios assistidos pela equipe. Cumprindo com a proposta de ser uma oficina, o evento se mostrou um excelente ponto de partida para quem deseja iniciar os caminhos na aprendizagem de linguagem R." + }, + { + "objectID": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html", + "href": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html", + "title": "Ações para ampliar a diversidade na comunidade R-Ladies São Paulo", + "section": "", + "text": "A R-Ladies é uma organização global cuja missão é promover a diversidade de gênero na comunidade R. A R-Ladies São Paulo, orgulhosamente, é um capítulo da R-Ladies Global, promovendo a diversidade de gênero na comunidade de R em São Paulo, no Brasil.\nNeste post, o nosso objetivo é discutir questões de diversidade atualmente na comunidade R-Ladies São Paulo, e as ações que têm sido feitas para ampliar a diversidade.\n\nEste post foi escrito em abril de 2023. Desde então, R-Ladies São Paulo recebeu um auxílio do R Consortium, o que permitiu à comunidade ampliar as ações para aumentar a diversidade.\n\n\n\n\nPicture of participants in a recent event.\n\n\nPara isso, dois pontos são importantes de serem discutidos: o conceito de interseccionalidade e questões relacionadas ao contexto brasileiro." + }, + { + "objectID": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#introdução", + "href": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#introdução", + "title": "Ações para ampliar a diversidade na comunidade R-Ladies São Paulo", + "section": "", + "text": "A R-Ladies é uma organização global cuja missão é promover a diversidade de gênero na comunidade R. A R-Ladies São Paulo, orgulhosamente, é um capítulo da R-Ladies Global, promovendo a diversidade de gênero na comunidade de R em São Paulo, no Brasil.\nNeste post, o nosso objetivo é discutir questões de diversidade atualmente na comunidade R-Ladies São Paulo, e as ações que têm sido feitas para ampliar a diversidade.\n\nEste post foi escrito em abril de 2023. Desde então, R-Ladies São Paulo recebeu um auxílio do R Consortium, o que permitiu à comunidade ampliar as ações para aumentar a diversidade.\n\n\n\n\nPicture of participants in a recent event.\n\n\nPara isso, dois pontos são importantes de serem discutidos: o conceito de interseccionalidade e questões relacionadas ao contexto brasileiro." + }, + { + "objectID": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#o-que-é-interseccionalidade", + "href": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#o-que-é-interseccionalidade", + "title": "Ações para ampliar a diversidade na comunidade R-Ladies São Paulo", + "section": "O que é Interseccionalidade?", + "text": "O que é Interseccionalidade?\nO público-alvo da R-Ladies são minorias de gênero, portanto: mulheres cis, mulheres trans, homens trans, pessoas não binárias e pessoas queer. O objetivo da comunidade é incluir esses grupos minoritários na comunidade de R. Porém, para cada um desses grupos de minorias de gêneros, existem pessoas que fazem parte de outros grupos que também podem sofrer outros tipos de exclusões e opressões, como: cor e raça, orientação sexual, maternidade, deficiências, idade, entre outros. Portanto, as opressões não são apenas baseadas no gênero da pessoa, e sim se relacionam e se sobrepõem. Esse entendimento é um conceito chamado “interseccionalidade”:\nSegundo Bridie Taylor (2019):\n\n“Interseccionalidade é o reconhecimento de que cada pessoa tem suas próprias experiências únicas de discriminação e opressão, e devemos considerar tudo e qualquer coisa que possa marginalizar as pessoas - gênero, raça, classe social, orientação sexual, habilidade física, etc.”\n\nAqui está um exemplo simples que pode ilustrar esse conceito: imagine uma mulher cisgênero branca e uma mulher cisgênero negra. Ambas sofrem opressão de gênero, mas somente a mulher negra sofre o racismo. Agora, considere uma mulher cisgênero, negra, bissexual, com filhos atípicos. Mesmo que a primeira e a última sofram opressão de gênero, não há dúvida de que a última sempre tem caminhos mais longos e difíceis para alcançar as mesmas posições.\nPortanto, é importante considerar a questão da diversidade de gênero, mas não se limitar às questões de gênero. É importante considerar também nas atividades da comunidade as intersecções que as pessoas participantes estão incluídas, para buscar ampliar a diversidade em diversos aspectos." + }, + { + "objectID": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#contexto-brasileiro", + "href": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#contexto-brasileiro", + "title": "Ações para ampliar a diversidade na comunidade R-Ladies São Paulo", + "section": "Contexto brasileiro", + "text": "Contexto brasileiro\nPor questões históricas, o Brasil apresenta uma composição racial diferente dependendo da região do país. A cidade de São Paulo está localizada na região Sudeste, onde 50,7% da população se auto-declara como branca, 38,7% como parda e 9,6% como preta (segundo dados da Pesquisa Nacional por Amostra de Domicílios Contínua (PNAD Contínua) do IBGE, referente à 20211). Considerando que a população negra é composta por pessoas pretas e pardas, quase metade da população na região Sudeste é negra.\nApesar de representarem cerca de metade da população da região, a população negra foi marginalizada, e segue sub-representada em espaços de poder, como na política, no ensino superior, em posições de liderança nas empresas entre outros.\n Fonte: IBGE - PNAD Contínua, 2021.\nOutra constatação relevante para entender o contexto brasileiro e os resultados apresentados neste texto é a informação de que o Brasil é um país violento com pessoas LGBTQIA+ e principalmente pessoas trans.\nOs resultados do estudo de Monitoramento de Assassinatos Trans (TMM) em 2022 podem ser vistos no mapa abaixo: o Brasil é o país com os maiores valores absolutos de assassinatos de pessoas transgêneras desde o início da série histórica obtida pelo TMM.\n Fonte: Trans Murder Monitoring (TMM) - 2022\nO tópico de trabalho e renda também é particularmente delicado para a população trans. Segundo o mapeamento de pessoas trans no município de São Paulo realizado em 20202, aproximadamente metade das pessoas entrevistadas saiu de casa entre 16 e 20 anos e destes, 30% por conta de brigas e 17% por conta de expulsão. Essa saída precoce impacta o acesso dessa população aos meios de gerar renda, considerando que 57% dos entrevistados não possui formação técnica ou específica e 42% não estava realizando nenhuma atividade remunerada no período da entrevista.\nEssas características da população brasileira são importantes para considerar na análise da diversidade das pessoas da comunidade." }, { - "objectID": "index.html#textos-em-português", - "href": "index.html#textos-em-português", - "title": "Blog", - "section": "Textos em Português", - "text": "Textos em Português\n\n\n \n \n \n\n\n\n\n\n \n\n\n\n\nRaspando a página do Studio Ghibli, na Wikipédia\n\n\n\n\n\n\n\nWeb Scraping\n\n\nTutorial\n\n\n \n\n\n\n\n31 de out. de 2023\n\n\nOrnella Scardua Ferreira\n\n\n\n\n\n\n \n\n\n\n\nAções para ampliar a diversidade na comunidade R-Ladies São Paulo\n\n\n\n\n\n\n\nR-Ladies\n\n\nComunidade\n\n\n \n\n\n\n\n2 de out. de 2023\n\n\nBeatriz Milz, Haydee Svab, Tatyane Paz Dominguez, Ianni Muliterno, Ana Paula Rocha\n\n\n\n\n\n\n \n\n\n\n\nRita com R\n\n\nAnalisando a padroeira da liberdade com código\n\n\n\n\nAnálise exploratória\n\n\nAnálise de texto\n\n\nMúsica\n\n\n \n\n\n\n\n2 de jun. de 2023\n\n\nBianca Muniz\n\n\n\n\n\n\n \n\n\n\n\nDados abertos de Educação: um exemplo aplicado ao jornalismo\n\n\nResultados do evento Open Data Day\n\n\n\n\nComunidade\n\n\nEnsino\n\n\nJornalismo de dados\n\n\nOpen data day\n\n\nEducação\n\n\n \n\n\n\n\n24 de mai. de 2023\n\n\nAna Carolina Moreno, Beatriz Milz, Geovana Lopes, Katia Mine, Natasha Meneguelli, Cristiane Souza de Lacerda\n\n\n\n\n\n\n \n\n\n\n\nAprendendo a programar em quatro capítulos\n\n\n\n\n\n\n\nComunidade\n\n\nEnsino\n\n\nJornalismo de dados\n\n\n \n\n\n\n\n10 de mai. de 2023\n\n\nAna Carolina Moreno\n\n\n\n\n\n\n \n\n\n\n\nEvento: Análise de dados abertos com R\n\n\nUm evento parte da iniciativa Open Data Day\n\n\n\n\nEventos\n\n\nComunidade\n\n\nDiversidade\n\n\n \n\n\n\n\n27 de mar. de 2023\n\n\nTatyane Paz Dominguez, Haydée Svab, Beatriz Milz, Ana Carolina Moreno, Ana Paula Rocha\n\n\n\n\n\n\n \n\n\n\n\nTidyTuesday: Explorando dados sobre as Paraolimpíadas\n\n\n\n\n\n\n\nTidytuesday\n\n\nAnálise exploratória\n\n\nVisualização de dados\n\n\nModelagem\n\n\n \n\n\n\n\n1 de mar. de 2023\n\n\nIanní Muliterno\n\n\n\n\n\n\n \n\n\n\n\nE aí, vamos falar de Quarto?\n\n\nTutorial: Relatório em Quarto\n\n\n\n\nQuarto\n\n\nTutorial\n\n\nRelatórios\n\n\n \n\n\n\n\n7 de fev. de 2023\n\n\nAriane Hayana\n\n\n\n\n\n\n \n\n\n\n\nEvento: Oficina de Introdução ao R\n\n\nPrimeiro evento presencial desde o início da pandemia\n\n\n\n\nEventos\n\n\nComunidade\n\n\nDiversidade\n\n\n \n\n\n\n\n31 de jan. de 2023\n\n\nBeatriz Milz, Tatyane Paz Dominguez\n\n\n\n\n\n\n \n\n\n\n\nGráficos de barras com barras de erros: críticas e alternativas\n\n\n\n\n\n\n\nGráficos\n\n\nTutorial\n\n\nDataviz\n\n\n \n\n\n\n\n14 de dez. de 2022\n\n\nFernanda Peres\n\n\n\n\n\n\n \n\n\n\n\nBoas vindas ao blog da R-Ladies São Paulo!\n\n\n\n\n\n\n\nNovidades\n\n\n \n\n\n\n\n5 de dez. de 2022\n\n\nEquipe R-Ladies SP, Beatriz Milz\n\n\n\n\n\n\n \n\n\n\n\nVidasNegrasImportam: Uma declaração conjunta de Forwards e R-Ladies\n\n\n#VidasNegrasImportam: Uma declaração conjunta de Forwards e R-Ladies\n\n\n\n\nDiversidade\n\n\nJustiça Social\n\n\n \n\n\n\n\n6 de jun. de 2020\n\n\nR-Ladies Global Leadership Team, R Forwards\n\n\n\n\n\n\nNenhum item correspondente" + "objectID": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#pesquisa---2020", + "href": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#pesquisa---2020", + "title": "Ações para ampliar a diversidade na comunidade R-Ladies São Paulo", + "section": "Pesquisa - 2020", + "text": "Pesquisa - 2020\nEm 2020, realizamos um questionário online com as pessoas participantes da comunidade, com o objetivo de saber mais sobre a composição da comunidade, e como podemos ampliar a diversidade. O questionário foi divulgado nos nossos grupos, como Meetup e o Telegram, e obteve 161 respostas válidas.\nAbaixo, destacamos alguns pontos levantados ao analisar as respostas do questionário, tratando dos temas: diversidade de gênero, diversidade racial, inclusão de mães/pais/pessoas cuidadoras, inclusão de pessoas LGBTQIA+, alimentação e acesso geográfico. Esses gráficos são importantes para entender a composição da comunidade em 2020 e que ações precisamos fazer para ampliar a diversidade em grupos menos representados.\n\nDiversidade de gênero\n\n\n\nGráfico de barras onde o eixo X mostra a porcentagem de respondentes da pesquisa, e o eixo Y representa o gênero. Cerca de 93% das pessoas respondentes disseram que são mulheres cis ou transgênero; cerca de 3% disseram que são homens cis ou transgênero; e cerca de 3% disseram que são pessoas não-binárias.\n\n\nEm relação à diversidade de gênero, as respostas obtidas no questionário apontam a predominância de mulheres (cis ou trans). Um problema identificado posteriormente na estruturação do questionário é: as perguntas não permitiam identificar quantas pessoas trans faziam parte da comunidade. Portanto, não temos dados sobre quantas pessoas trans participavam da comunidade. Essa pergunta deverá ser incorporada em um questionário futuro.\n\n\nDiversidade racial\n\n\n\nGráfico de barras onde o eixo X mostra a porcentagem de respondentes da pesquisa, e o eixo Y representa a cor/raça. Cerca de 73% das pessoas respondentes disseram que são brancas; cerca de 14% disseram que são pardas; cerca de 9% disseram que são pretas; e cerca de 4% disseram que são amarelas.\n\n\nEm relação à diversidade racial na comunidade em 2020, é importante destacar que 73,3% das pessoas se auto-declaravam brancas, apesar da população branca nessa região do Brasil representar cerca de metade da população. Ou seja, temos uma sub-representação de pessoas negras na comunidade R-Ladies São Paulo e necessitamos agir com seriedade para promover inclusão étnico-racial.\nÉ importante também citar o texto escrito pela equipe da R-Ladies Global e a R Forwards sobre o #VidasNegrasImportam, em 2020. Na ocasião, o texto foi traduzido para português pela comunidade R-Ladies São Paulo e está disponível no blog da comunidade. Neste texto, a R-Ladies Global se comprometeu a melhorar a forma como a organização apoia pessoas negras, indígenas e de outros grupos não-brancos:\n\n“Como a missão da R-Ladies é focada em melhorar a diversidade de gênero na comunidade R, também reconhecemos a luta que as pessoas negras enfrentam e o efeito composto interseccional quando uma pessoa integrante se identifica com vários grupos sub-representados. […] Nos comprometemos a tornar os espaços da nossa comunidade lugares que ofereçam não apenas segurança para todas as pessoas que a integram, mas também um trabalho ativo em prol da equidade e da justiça.” Fonte: R-Ladies Global Blog.\n\nNo questionário, deixamos uma pergunta em formato aberto para que as pessoas pudessem oferecer sugestões para ampliar a diversidade étnico-racial na comunidade, e abaixo estão algumas sugestões oferecidas:\n\nDivulgar a R-Ladies em grupos que abordam a questão racial;\nCriar cotas para participação de pessoas negras;\nConvidar pessoas negras para palestrar;\nDivulgar estatísticas do grupo sobre essa lacuna de representatividade;\nPromover eventos focados com a temática de raça;\nRealizar eventos em regiões periféricas;\nPromover eventos focados para pessoas negras;\nTer pessoas negras participantes na organização da comunidade.\n\n\n\nInclusão de mães/pais/pessoas cuidadoras\n\n\n\nGráfico de barras onde o eixo X mostra a porcentagem de respondentes da pesquisa, e o eixo Y representa se a pessoa é mãe/pai/responsável. Cerca de 87% das pessoas respondentes disseram SIM e 13% disseram NÃO.\n\n\nEm 2020, 13% das pessoas respondentes apontaram que possuem filhos. Para incluir mais pessoas com filhos, algumas sugestões oferecidas por meio do questionário foram:\n\nDisponibilizarum espaço para deixar as crianças durante os eventos;\nRealizar a gravação dos eventos para que as mães/pais/pessoas cuidadoras possam assistir quando for mais cômodo;\nRealizar a transmissão online dos eventos para promover a participação de pessoas que não podem participar pessoalmente.\n\n\n\nInclusão de pessoas LGBTQIA+\n\n\n\nGráfico de barras onde o eixo X mostra a porcentagem de respondentes da pesquisa, e o eixo Y representa se a pessoa faz parte da comunidade LGBTQIA+. Cerca de 70% dos respondentes disseram NÃO e 30% disseram SIM.\n\n\nEm 2020, 30% das pessoas respondentes apontaram que fazem parte da comunidade LGBTQIA+. Apesar de não existirem dados sobre a porcentagem da população brasileira que faz parte da comunidade LGBTQIA+, os resultados desse questionário apontam que a comunidade está no caminho certo em termos de inclusão da população LGBTQIA+.\nDentre as sugestões oferecidas pela comunidade no formulário, com o objetivo de ampliar a participação de pessoas LGBTQIA+, destaca-se a questão do nome da comunidade. Algumas pessoas respondentes apontaram que o nome R-Ladies sugere que o grupo é apenas para mulheres, e desestimula pessoas de outros grupos a participarem por não ficar claro que são bem vindas.\n\n\nRegiões geográficas\nO mapa a seguir apresenta a Região Metropolitana de São Paulo (o maior polígono), e o município de São Paulo (separado por regiões). A maioria das pessoas que participam do evento são das regiões Oeste e Sul da cidade. Para ampliar a participação de pessoas das regiões Leste e Norte, é interessante realizar eventos nessas regiões.\n\n\n\nMapa da cidade de São Paulo: a maior parte dos respondentes disse que é das regiões Sul e Oeste da cidade." }, { - "objectID": "index.html#textos-traduzidos-para-o-inglês", - "href": "index.html#textos-traduzidos-para-o-inglês", - "title": "Blog", - "section": "Textos traduzidos para o Inglês", - "text": "Textos traduzidos para o Inglês\n\n\n \n \n \n\n\n\n\n\n \n\n\n\n\nActions to increase diversity in the R-Ladies São Paulo community\n\n\n\n\n\n\n\nR-Ladies\n\n\ncommunity\n\n\nlatin america\n\n\n \n\n\n\n\n2 de out. de 2023\n\n\nBeatriz Milz, Haydee Svab, Tatyane Paz Dominguez, Ianni Muliterno, Ana Paula Rocha\n\n\n\n\n\n\n \n\n\n\n\nEvent: Open Data Analysis with R\n\n\nAn event part of the Open Data Day initiative\n\n\n\n\nEvents\n\n\nCommunity\n\n\nDiversity\n\n\nEnglish\n\n\n \n\n\n\n\n26 de mar. de 2023\n\n\nTatyane Paz Dominguez, Haydée Svab, Beatriz Milz, Ana Carolina Moreno, Ana Paula Rocha\n\n\n\n\n\n\nNenhum item correspondente" + "objectID": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#ações-realizadas-para-aumentar-a-diversidade", + "href": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#ações-realizadas-para-aumentar-a-diversidade", + "title": "Ações para ampliar a diversidade na comunidade R-Ladies São Paulo", + "section": "Ações realizadas para aumentar a diversidade", + "text": "Ações realizadas para aumentar a diversidade\nO levantamento realizado em 2020 e as discussões estabelecidas acima, apontam a necessidade de um esforço coletivo da comunidade em busca da ampliação da diversidade.\nPara isso, algumas ações têm sido realizadas e serão brevemente comentadas a seguir. Em textos referentes à eventos recentes, as atividades foram descritas com maior detalhe, por exemplo:\n\nEvento: Análise de dados abertos com R\nEvento: Oficina de Introdução ao R\n\n\n\n\nFoto de participantes em eventos recentes.\n\n\n\nPolítica de ações afirmativas\nPara buscar ampliar a diversidade na participação nos evento, reservamos as vagas pensando em três grupos:\n\npessoas negras, pardas e indígenas\nmães\nmulheres e outras minorias de gênero\n\nAs vagas reservadas são também divulgadas nas redes sociais da comunidade (principalmente Instagram), para assim deixar claro que a presença desses grupos é bem vinda.\n\n\nEspaço GugudaDados\nO GuGuDaDados é um espaço colaborativo e experimental que as RLadies São Paulo propõem com o objetivo de deixar as crianças entretidas e cuidadas enquanto as pessoas responsáveis podem participar deatividades da comunidade com tranquilidade.\nCom o apoio financeiro de outras organizações, buscamos contratar uma professora recreadora para acompanhar as crianças no espaço Gugudadados (uma sala ao lado da sala das atividades dos adultos, no mesmo andar) durante todo o evento.\nAs organizadoras da R-Ladies também levam brinquedos, desenhos, canetinhas, jogos e tatuagens temporárias para entreter e divertir as crianças.\n\n\n\nFotos do espaço Gugudadados em eventos recentes.\n\n\n\n\nCafé colaborativo\nO café colaborativo é montado com itens comprados com o apoio financeiro de outras organizações e também comitens trazidos por participantes. Assim, as pessoas podem se alimentar em qualquer momento do evento.\nEsse formato de café (disponível ao longo detodo do evento) é muito bom por 3 motivos: (i) é um ótimo momento para conhecer e conversar com pessoas da comunidade; (ii) acolhe participantes que por questões de saúde não podem permanecer muitas horas sem comer e (iii) acolhe participantes que por condição socioeconômica não têm como fazer uma refeição no intervalo do almoço.\nDada a natureza do grupo R-Ladies, é um quesito importante prover um acolhimento mínimo necessário para que todas as pessoas tenham condições de usufruir da experiência do evento independente de ter o que comer ao longo do dia, além de que o café colaborativo também é uma forma de incentivar a integração entre as pessoas!\n\n\nAuxílio transporte e alimentação\nPara permitir que pessoas com pouca condição financeira tenham acesso e aproveitamento dos eventos, uma ação importante é o oferecimento de auxílio transporte e alimentação. O auxílio alimentação é oferecido em eventos presenciais que duram um dia inteiro. O auxílio transporte é oferecido em todos os eventos presenciais. Um ponto em destaque é que muitas pessoas que solicitam auxílio transporte são de cidades do interior (fora da Região Metropolitana de São Paulo), o que mostra o potencial de criação de novos capítulos da R-Ladies nessas cidades.\n\nR-Ladies São Paulo recebeu um auxílio da R Consortium, o que permitiu à comunidade oferecer auxílio financeiro nos eventos.\n\n\n\nTrabalho em duplas\nNem todas as pessoas participantes possuem um notebook para levar para a atividade. Nós esperamos que todas as pessoas possam participar independente da condição financeira. Portanto, na divulgação, incentivamos que as pessoas participem independente de poder levar um computador. Assim, nos casos onde isso acontece, incentivamos que as pessoas formem duplas e trabalhem juntas durante o evento. Isso sempre funcionou e acaba estimulando uma maior proximidade e solidariedade entre as pessoas.\n\n\nIncentivo à caronas\nA cidade de São Paulo é muito grande, e dependendo de onde você precisa ir, é comum demorar 2 horas (ou mais!) em transporte público para se deslocar. Portanto, uma das dificuldades de se participar em um evento presencial é a mobilidade. Para amenizar essa dificuldade, incentivamos que as pessoas, ao final do evento, ofereçam caronas caso estejam de carro para as pessoas que moram em regiões próximas na cidade. Ainda é necessário aprimorar este incentivo para combinar, de forma segura, caronas também na ida ao evento (e não apenas no final)." }, { - "objectID": "index.html#apoio-financeirosponsor", - "href": "index.html#apoio-financeirosponsor", - "title": "Blog", - "section": "Apoio financeiro/Sponsor", - "text": "Apoio financeiro/Sponsor\n\n\nR Consortium" + "objectID": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#ações-necessárias", + "href": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#ações-necessárias", + "title": "Ações para ampliar a diversidade na comunidade R-Ladies São Paulo", + "section": "Ações necessárias", + "text": "Ações necessárias\nBaseado no questionário de 2020 e na experiência da comunidade ao longo do tempo, percebe-se como necessidade as seguintes melhorias na dinâmica da organização:\n\nEstimular a aproximação e participação de pessoas que constituem alguma minoria social por meio de cotas, uma postura interna de discriminação positiva; incluir essas pessoas na organização; convidar para oferecer palestras/workshops; promover visibilidade e ceder espaço para que essas pessoas tragam seu olhar, experiência e percepção para a contínua estruturação da comunidade R-ladies.\nBuscar parcerias em regiões periféricas para conseguir realizar eventos nessas regiões, facilitando o acesso de pessoas que moram longe dos bairros centrais da cidade." }, { - "objectID": "videos.html", - "href": "videos.html", - "title": "Videos", - "section": "", - "text": "Todos os vídeos podem ser encontrados no canal da R-Ladies São Paulo no Youtube." + "objectID": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#equipe-de-organização-atual", + "href": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#equipe-de-organização-atual", + "title": "Ações para ampliar a diversidade na comunidade R-Ladies São Paulo", + "section": "Equipe de organização atual", + "text": "Equipe de organização atual\nExistem várias pessoas envolvidas na organização atualmente na comunidade R-Ladies São Paulo. É importante citar que estão envolvidas pessoas pertencentes a diferentes grupos minoritários (como mulheres negras, mães, pessoas trans, pessoas não-binárias, pessoas LGBTQIA+, pessoas neurodivergentes e pessoas com mais de 40 anos), e isso é necessário para oferecer diferentes visões e experiências. Além disso, cabe destacar que a participação da organização é feita de forma voluntária.Portanto, aqui listamos e agradecemos as pessoas que atualmente participam das diversas etapas de organização da comunidade:\n \n\nAna Carolina Moreno\nAna Paula Rocha\nAngélica Custódio\nBeatriz Milz\nFernanda Peres\nGeovana Lopes Batista\nHaydee Svab\nIanní Muliterno\nJean Gabriel Reis do Prado\nLuana Antunes Tolentino Souza\nNathália Demétrio\nTatyane Paz Dominguez" }, { - "objectID": "videos.html#ciência-de-dados-gênero-e-raça-nas-políticas-públicas", - "href": "videos.html#ciência-de-dados-gênero-e-raça-nas-políticas-públicas", - "title": "Videos", - "section": "Ciência de Dados, Gênero e Raça nas Políticas Públicas", - "text": "Ciência de Dados, Gênero e Raça nas Políticas Públicas\n\nMaterial completo" + "objectID": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#footnotes", + "href": "posts/2023-06-05-increasing-diversity-sao-paulo/index.html#footnotes", + "title": "Ações para ampliar a diversidade na comunidade R-Ladies São Paulo", + "section": "Notas de rodapé", + "text": "Notas de rodapé\n\n\nIBGE: Instituto Brasileiro de Geografia e Estatística. O IBGE é um órgão de estatísticas nacionais que realiza censos e é responsável pela coleta, armazenamento e disseminação de dados socioeconômicos sobre a população brasileira.↩︎\nO mapeamento de pessoas trans do município de São Paulo foi um dos primeiros do Brasil, ou seja, ainda não há dados para o contexto nacional. Fonte: Centro de estudo de cultura contemporânea, 2021.↩︎" }, { - "objectID": "videos.html#como-escolher-o-teste-estatístico-adequado", - "href": "videos.html#como-escolher-o-teste-estatístico-adequado", - "title": "Videos", - "section": "Como escolher o teste estatístico adequado?", - "text": "Como escolher o teste estatístico adequado?\n\nApresentado por Fernanda Peres\nSlides" + "objectID": "posts/2023-03-tidytuesday-paraolimpiadas/index.html", + "href": "posts/2023-03-tidytuesday-paraolimpiadas/index.html", + "title": "#TidyTuesday: Explorando dados sobre as Paraolimpíadas", + "section": "", + "text": "Autoria\n\n\n\n\n\n\n\n\nIanní Muliterno\n\n \n\nEste post foi escrito por Ianní Muliterno, um integrante da comunidade R-Ladies São Paulo! É graduado em Estatística pela Universidade Federal de Pernambuco (UFPE) e atua como cientista de dados na Unilever.\nOlá, pessoal!\nSe você já é um entusiasta de ciência de dados, provavelmente já ouviu falar do TidyTuesday. Se está iniciando, este é um ótimo lugar para conseguir dados reais para praticar e criar um portfolio. O tidytuesday é um projeto semanal do R for Data Science Community, que tem como objetivo ajudar as pessoas a aprender e praticar a análise de dados em R usando o pacote Tidyverse, conheça aqui: https://github.com/rfordatascience/tidytuesday.\nCada semana, é lançado um novo conjunto de dados, geralmente em formato de planilha, que pode ser baixado gratuitamente. A comunidade é então convidada a explorar, visualizar e analisar esses dados usando as ferramentas do tidyverse, como o ggplot2 para gráficos e o dplyr para manipulação de dados." }, { - "objectID": "videos.html#conhecendo-o-ggplot2-criando-gráficos-com-r", - "href": "videos.html#conhecendo-o-ggplot2-criando-gráficos-com-r", - "title": "Videos", - "section": "Conhecendo o ggplot2: criando gráficos com R", - "text": "Conhecendo o ggplot2: criando gráficos com R\n\nApresentado por Letícia Thomaz\nSlides" + "objectID": "posts/2023-03-tidytuesday-paraolimpiadas/index.html#base-de-dados", + "href": "posts/2023-03-tidytuesday-paraolimpiadas/index.html#base-de-dados", + "title": "#TidyTuesday: Explorando dados sobre as Paraolimpíadas", + "section": "Base de dados", + "text": "Base de dados\nHoje vamos dar uma olhada na base do início de agosto de 2021, quando o TidyTuesday lançou um conjunto de dados fascinante sobre as paraolimpíadas dos anos 1980 até 2016. O conjunto de dados inclui informações sobre características dos atletas, o país de origem, o tipo de prova, entre outras variáveis." }, { - "objectID": "videos.html#visualização-interativa-de-dados-uma-aplicação-usando-shiny", - "href": "videos.html#visualização-interativa-de-dados-uma-aplicação-usando-shiny", - "title": "Videos", - "section": "Visualização Interativa de Dados – uma aplicação usando Shiny", - "text": "Visualização Interativa de Dados – uma aplicação usando Shiny\n\nApresentado por Marina Muradian" + "objectID": "posts/2023-03-tidytuesday-paraolimpiadas/index.html#importação", + "href": "posts/2023-03-tidytuesday-paraolimpiadas/index.html#importação", + "title": "#TidyTuesday: Explorando dados sobre as Paraolimpíadas", + "section": "Importação", + "text": "Importação\nPara começar vamos carregar os dados! Lembrando de manter a boa prática de iniciar o script carregando as bibliotecas necessárias.\n\nlibrary(tidyverse)\nlibrary(readr)\nlibrary(ggplot2)\n\n\ndados_olimpiadas <- read_csv(\"https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2021/2021-08-03/athletes.csv\")\n\nRows: 19547 Columns: 10\n── Column specification ────────────────────────────────────────────────────────\nDelimiter: \",\"\nchr (8): gender, event, medal, athlete, abb, country, type, guide\ndbl (2): grp_id, year\n\nℹ Use `spec()` to retrieve the full column specification for this data.\nℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.\n\n\nO bacana da função read_csv() é que ela já dá uma descrição geral com nome das variáveis e tipo. No caso, temos 8 variáveis tipo chr ou character (textos) e 2 tipo dbl ou double (numéricos).\nAntes de começar, outra boa prática é conhecer os dados. Quais colunas possui? Como está o preenchimento das variáveis? Existem dados faltantes (NAs)?\n\n# Quantos NAs temos em cada coluna?\ncolSums(is.na(dados_olimpiadas))\n\n gender event medal athlete abb country grp_id type year guide \n 144 0 0 435 49 14428 14428 0 0 19494 \n\n\nNo tidytuesday os dados costumam vir mais arrumados, porém no mundo real é comum encontrarmos erros no preenchimento, sejam eles sistemáticos (por exemplo: a ferramenta que mede velocidade dos competidores falha e traz valores muito grandes ou negativos), ou também erros de preenchimento (exemplo: alguém que preencheu errado o campo de medalha e colocou por exemplo “metal” ao invés de “prata”).\nNo repositório desta base, está descrito o que cada coluna representa. Te convido para escrever como lição de casa o código que checa as variáveis categóricas em busca de nomes estranhos que não condizem com o que deveria estar naquela variável. Como incentivo, deixo aqui o check de variáveis numéricas.\n\ndados_olimpiadas %>% \n select(where(is.numeric)) %>%\n pivot_longer(1:2, names_to = 'variaveis', values_to = 'valor') %>% \n ggplot(aes(x = valor)) +\n geom_histogram() +\n facet_wrap(~variaveis,scales = 'free') +\n theme(panel.background = element_rect(fill = \"white\"))" }, { - "objectID": "videos.html#people-analytics-a-ciência-de-dados-no-rh", - "href": "videos.html#people-analytics-a-ciência-de-dados-no-rh", - "title": "Videos", - "section": "People Analytics a Ciência de Dados no RH", - "text": "People Analytics a Ciência de Dados no RH\n\nApresentado por Sabrina Vasconcellos" + "objectID": "posts/2023-03-tidytuesday-paraolimpiadas/index.html#explorando-e-visualizando-dados-para-natação", + "href": "posts/2023-03-tidytuesday-paraolimpiadas/index.html#explorando-e-visualizando-dados-para-natação", + "title": "#TidyTuesday: Explorando dados sobre as Paraolimpíadas", + "section": "Explorando e visualizando dados para Natação!", + "text": "Explorando e visualizando dados para Natação!\nPara não ficar um post massivo, vamos focar em natação.\nAo analisar esses dados, podemos responder várias perguntas interessantes. Por exemplo, qual país obteve mais medalhas na natação nos Jogos Olímpicos de 2021? Há alguma diferença significativa na quantidade de medalhas conquistadas entre os atletas homens e mulheres?\nPaíses com mais metalhas\nPara criar um gráfico mostrando os países com mais medalhas, primeiro é necessário trabalhar os dados para criar uma base onde tenha a contagem de medalhas por país e por tipo de medalha!\n\n# Fazendo uma contagem de medalhas de natação por país:\n\nparalympic_total <- dados_olimpiadas %>%\n # Filtrando medalhas de natação (Swimming)\n filter(type == \"Swimming\") %>%\n # Contando quantas medalhas tem por país (abb),\n # ordenando pelos maiores números!\n count(abb, sort = TRUE)\n\n# Fazendo uma contagem de medalhas de natação por país e tipo de medalha:\nparalympic_byMedal <- dados_olimpiadas %>%\n # Filtrando medalhas de natação (Swimming)\n filter(type == \"Swimming\") %>%\n # Contando quantas medalhas tem por país (abb) e tipo de medalha,\n # ordenando pelos maiores números!\n count(abb, medal) \n\nparalympic_swimming <- paralympic_byMedal %>%\n # unindo as duas bases criadas acima, \n # usando a coluna \"abb\" como chave\n left_join(paralympic_total, by = \"abb\") %>%\n # renomeando as colunas\n rename(number = n.x, total_medals = n.y)\n\n# Uma \"olhada\" na base criada!\nparalympic_swimming |> \n glimpse()\n\nRows: 174\nColumns: 4\n$ abb <chr> \"ARG\", \"ARG\", \"ARG\", \"AUS\", \"AUS\", \"AUS\", \"AUT\", \"AUT\", \"…\n$ medal <chr> \"Bronze\", \"Gold\", \"Silver\", \"Bronze\", \"Gold\", \"Silver\", \"…\n$ number <int> 9, 5, 10, 160, 147, 158, 2, 2, 4, 1, 7, 1, 13, 6, 12, 9, …\n$ total_medals <int> 24, 24, 24, 465, 465, 465, 8, 8, 8, 8, 8, 1, 31, 31, 31, …\n\n\nUtilizando essa base com a contagem de medalhas, podemos filtrar os 5 países com mais medalhas:\n\ntop5 <- paralympic_total |> \n # fatiar: apenas as primeiras 5 linhas\n slice(1:5) |> \n # retornar como um vetor a coluna abb\n pull(abb)\n\n\ntable_top5 <- paralympic_swimming %>%\n # filtrar os países do top 5\n filter(abb %in% top5) %>%\n # transformar a coluna abb em fator, \n # para facilitar a ordenação no gráfico\n mutate(abb = factor(abb, levels = top5),\n medal = factor(medal, levels = c(\"Bronze\", \"Silver\", \"Gold\"))) \n\nCom os dados preparados, podemos fazer o gráfico! Mas antes disso, vamos salvar as configurações de tema do gráfico em um objeto, para utilizarmos depois e deixar o código do gráfico mais fácil para ler!\n\ntema_olimpiadas <- \n theme_minimal() +\n theme(\n legend.position = \"none\",\n plot.title.position = \"plot\",\n plot.title = element_text(\n family = \"mono\",\n face = \"bold\",\n size = 10\n ),\n panel.grid.major.x = element_blank(),\n panel.grid.minor.x = element_blank(),\n panel.grid.major.y = element_blank(),\n panel.grid.minor.y = element_blank(),\n axis.text = element_text(\n family = \"mono\",\n face = \"bold\",\n size = 8\n ),\n panel.background = element_rect(fill = \"white\")\n ) \n\nAgora sim, vamos ao gráfico!\n\ntable_top5 %>%\n ggplot(aes(x = abb, y = number, fill = medal)) +\n geom_col() +\n scale_fill_manual(values = c(\"#D89581\", \"#C0C0C0\", \"#D4AF37\")) +\n scale_x_discrete(expand = c(0, 0)) +\n labs(x = \"\",\n y = \"\", \n title = \"Medalhas de ouro, prata e bronze conquistada pelos países de melhor desempenho\") +\n tema_olimpiadas\n\n\n\n\n\n\n\nA Grã-Bretanha é o país com mais medalhas no total, porém os Estados Unidos é o país com mais medalhas de ouro!\nApesar de algumas alterações que fiz, os créditos deste gráfico de barras são da Erin, professora que vocês podem encontrar aqui: https://github.com/efranke22.\nDiferença de medalhas por gênero\nContinuando, podemos ver a diferença entre a quantidade de medalhas conquistadas entre os atletas homens e mulheres. Para isso, veremos primeiro o histograma do percentual de mulheres que os países levam em cada olimpíada, em seguida o box plot das medalhas conquistadas por cada um, agrupado também pelo tipo de medalha.\nUma observação: o gênero misto foi removido, porque ele está na base devido a algumas provas serem mistas e não porque os participantes são não-binários. Com isso, perdemos 21 linhas.\nVamos então preparar a base de dados, calculando o percentual de mulheres por país:\n\ndt_perc_gender <- dados_olimpiadas %>%\n # Filtrar para Natação\n filter(type == \"Swimming\") %>%\n # Filtrar: remover linhas onde o gênero seja \"misto\" (ex: duplas de homens e mulheres)\n filter(gender != 'Mixed') %>%\n # Deixar apenas uma linha para a combinação atleta/ano/país/gênero\n distinct(abb, year, gender, athlete) %>%\n # Contar quantas pessoas participaram por país e gênero\n count(abb, gender) %>%\n # Alterar a base para formato longo\n pivot_wider(names_from = gender, values_from = n) %>%\n # Substituir NA por 0 nas colunas Woman e Men\n mutate(across(any_of(c(\"Women\", \"Men\")), ~ ifelse(is.na(.), 0, .))) %>%\n # Agrupar por país\n group_by(abb) %>%\n # Calcular o porcentual de mulheres\n summarize(perc_mulheres = mean(Women / (Women + Men))) %>%\n # Ordenar de forma decrescente por perc_mulheres\n arrange(desc(perc_mulheres))\n\nlinha_mediana <- median(dt_perc_gender$perc_mulheres)\n\nAgora podemos criar o histograma:\n\ndt_perc_gender %>%\n ggplot(aes(x = perc_mulheres)) +\n geom_histogram() +\n geom_vline(\n mapping = aes(xintercept = linha_mediana),\n linetype = 2,\n color = 'red'\n ) +\n annotate(\n \"text\",\n x = linha_mediana + 0.06,\n y = 15,\n label = \"Mediana\",\n color = 'red'\n ) +\n ggtitle(\"Histograma do percentual de mulheres que os países levam em cada olimpíada\") +\n theme(panel.background = element_rect(fill = \"white\")) \n\n\n\n\n\n\n\nComo vimos no histograma, muitos países nem enviam mulheres para as olimpíadas e os que enviam, tem em média 34% de mulheres na composição do time. Sendo assim, essa diferença impacta na diferença que vemos na quantidade de medalhas conquistadas por gênero.\nVamos explorar estes dados em um boxplot:\n\ndados_olimpiadas %>%\n mutate(medal = factor(medal, levels = c(\"Bronze\", \"Silver\", \"Gold\"))) |> \n # Filtrar para Natação\n filter(type == \"Swimming\") %>%\n # Filtrar: remover linhas onde o gênero seja \"misto\"\n filter(gender != 'Mixed') %>%\n # Contar quantas pessoas participaram por país, gênero e tipo de medalha\n count(abb, gender, medal) %>%\n ggplot(aes(y = n, fill = gender, x = medal)) +\n geom_boxplot() +\n labs(title = \"Box-plot das medalhas conquistadas por tipo de medalha e gênero em cada país\", \n y = \"Quantidade de medalhas\",\n x = \"Tipo de medalha\",\n fill = \"Gênero\") +\n theme(panel.background = element_rect(fill = \"white\")) +\n scale_fill_brewer(type = \"qual\")" }, { - "objectID": "videos.html#tidymodels-estruturando-o-processo-de-machine-learning", - "href": "videos.html#tidymodels-estruturando-o-processo-de-machine-learning", - "title": "Videos", - "section": "Tidymodels: Estruturando o processo de Machine Learning", - "text": "Tidymodels: Estruturando o processo de Machine Learning\n\nApresentado por Viviane Sanchez e Bruna Wundervald\nSlides:\n\nApresentação da Bruna Wundervald\nApresentação da Viviane Sanchez" + "objectID": "posts/2023-03-tidytuesday-paraolimpiadas/index.html#vamos-para-a-modelagem", + "href": "posts/2023-03-tidytuesday-paraolimpiadas/index.html#vamos-para-a-modelagem", + "title": "#TidyTuesday: Explorando dados sobre as Paraolimpíadas", + "section": "Vamos para a modelagem!", + "text": "Vamos para a modelagem!\nAgora, pensando em usar modelos, podemos brincar de criar métricas, pensando em como prever se um atleta conquistará medalhas na olimpíada seguinte. Opções diretas de variáveis são: quantas medalhas já ganhou, de quantas olimpíadas já participou, proporção de medalhas por tipo, e uma métrica de quantidade de medalhas por olimpíada (chamarei de medal_olympics_kpi - kpi vem do inglês Key Performance Indicators e é uma sigla bem conhecida no meio da análise de dados para se referir a indicadores de performance), por fim, teremos a variável de gênero.\nUm exercício bom de fazer aqui é observar correlação entre as variáveis resposta. As contagens de medalhas são correlacionadas entre si, pois por exemplo, quanto mais medalhas ganhas no total, maior serão os valores nas contagens de medalha por tipo, por isso que decidi utilizar proporção. A quantidade de olimpíadas que o atleta já participou também tem certa relação com sua idade, o que é bom, porque não temos a informação da idade na base.\n\n# variável resposta : última olimpíada de cada atleta\nresposta <- dados_olimpiadas %>%\n # Remover linhas onde não temos o nome do atleta\n filter(athlete != '-') %>%\n # Filtrar para natação\n filter(type == \"Swimming\") %>%\n # Filtrar por ano\n filter(year == 2016) %>%\n # Contar quantas medalhas cada atleta teve\n count(athlete, sort = TRUE) \n\nA variável resposta é a quantidade de medalhas conquistadas por atleta nas olimpíadas de natação de 2016. A base vai contar com informações dos atletas e das suas participações anteriores.\n\nbase <- dados_olimpiadas %>%\n # Unindo a tabela resposta a base total para manter apenas \n # os atletas dos quais conseguimos montar variável resposta\n inner_join(resposta, by = 'athlete') %>%\n # Removendo dados de 2016 (pois deste ano tiramos a variável resposta)\n filter(year != 2016) %>%\n # Remove a coluna n (que veio ao juntar as bases)\n select(-n) %>% \n # agrupando por atleta\n group_by(athlete) %>% \n # montando variáveis independentes para cada atleta\n summarize(total_medalhas = n(),\n ouro = sum(medal == 'Gold'),\n prata = sum(medal == 'Silver'),\n bronze = sum(medal == 'Bronze'),\n total_olympics = n_distinct(year),\n medal_olympics_kpi = n()/n_distinct(year),\n gender = unique(gender[gender != 'Mixed']),\n n_eventos = n_distinct(event)) %>% \n mutate(ouro = ouro/total_medalhas,\n prata = prata/total_medalhas,\n bronze = bronze/total_medalhas)\n\nbase_final <- base %>% \n # unir novamente com a base de resposta\n inner_join(resposta, by = 'athlete') %>% \n # renomear coluna n para y\n rename(y = n) %>% \n # desagrupar\n ungroup() %>% \n # remover a coluna com nome\n select(-athlete)\n\nCom isto estamos prontos para checar o quanto essas variáveis podem prever quantas medalhas um atleta conquistará em 2016. Por se tratar de uma variável resposta de contagem, não é adequado usar uma regressão linear simples, duas alternativas são modelos de poisson e binomial negativa. Aqui utilizaremos um modelo de poisson.\n\nmodelo <- glm(y ~ ., data = base_final, family = 'poisson')\nsummary(modelo)\n\n\nCall:\nglm(formula = y ~ ., family = \"poisson\", data = base_final)\n\nDeviance Residuals: \n Min 1Q Median 3Q Max \n-2.03793 -0.59747 -0.07415 0.46524 1.76581 \n\nCoefficients: (1 not defined because of singularities)\n Estimate Std. Error z value Pr(>|z|) \n(Intercept) 0.31605 0.36604 0.863 0.3879 \ntotal_medalhas -0.01995 0.05408 -0.369 0.7122 \nouro 0.19491 0.22641 0.861 0.3893 \nprata 0.14087 0.26165 0.538 0.5903 \nbronze NA NA NA NA \ntotal_olympics -0.21896 0.18431 -1.188 0.2348 \nmedal_olympics_kpi 0.28235 0.13744 2.054 0.0399 *\ngenderWomen 0.19268 0.12956 1.487 0.1370 \nn_eventos 0.01706 0.12647 0.135 0.8927 \n---\nSignif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n\n(Dispersion parameter for poisson family taken to be 1)\n\n Null deviance: 111.157 on 106 degrees of freedom\nResidual deviance: 59.115 on 99 degrees of freedom\nAIC: 355.94\n\nNumber of Fisher Scoring iterations: 4\n\n\nAqui observamos pela coluna Pr(>|z|) o p-valor de cada variável. Por padrão, quando este valor é <= 0.10 aparece um símbolo chamado Signif. codes a direita. Quanto menor o p-valor, maior esse símbolo, ou seja, quanto maior a importância da variável, maior o símbolo.\nPelo summary(modelo) descobrimos que a proporção de medalhas de bronze não está gerando nenhum resultado para predição do modelo, por isso os campos em NA aparecem para ela.\nDaqui para frente, por se tratar de um modelo com poucas variáveis e um exemplo simples, fui criando novos modelos, onde em cada um deles removia uma variável. Primeiro bronze, depois n_eventos e assim por diante. A cada novo modelo eu chequei qual a variável de menor importância, ou seja, maior p-valor e removo-a, isto é importante porque cada remoção vai impactar na importância de todas as outras. No fim, quando cheguei num modelo onde todas as variáveis eram relevantes, obtive o seguinte modelo:\n\nmodelo5 <-\n glm(y ~ medal_olympics_kpi + total_olympics,\n data = base_final,\n family = 'poisson')\nsummary(modelo5)\n\n\nCall:\nglm(formula = y ~ medal_olympics_kpi + total_olympics, family = \"poisson\", \n data = base_final)\n\nDeviance Residuals: \n Min 1Q Median 3Q Max \n-1.84737 -0.69446 -0.09312 0.45457 1.68875 \n\nCoefficients:\n Estimate Std. Error z value Pr(>|z|) \n(Intercept) 0.64174 0.15547 4.128 3.66e-05 ***\nmedal_olympics_kpi 0.26467 0.03805 6.956 3.49e-12 ***\ntotal_olympics -0.28385 0.08063 -3.521 0.000431 ***\n---\nSignif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n\n(Dispersion parameter for poisson family taken to be 1)\n\n Null deviance: 111.157 on 106 degrees of freedom\nResidual deviance: 61.791 on 104 degrees of freedom\nAIC: 348.61\n\nNumber of Fisher Scoring iterations: 4\n\n\nObserve que temos o kpi com influência positiva, ou seja, quanto mais medalhas por olimpíada um atleta tem em olimpíadas anteriores, mais medalhas ele pode conseguir em 2016. Do contrário temos a variável total_olympics que tem influência negativa, ou seja, quanto mais olimpíadas o atleta tiver participado, menos medalhas ele pode ganhar em 2016. Essa interpretação pode parecer estranha, mas lembre-se da sua relação com a idade, quanto mais olimpíadas nas costas, mais velho o atleta é.\nAgora vamos buscar evidências do poder de predição do modelo, no próprio summary(model) temos o AIC, uma métrica que fica menor a medida que o poder de predição melhora. Se compararmos o AIC do primeiro e do último modelo, vemos uma diminuição, mas precisamos verificar os resíduos por exemplo.\n\nggplot(modelo5, aes(x = .fitted, y = .resid)) +\n geom_point() +\n geom_hline(yintercept = 0) +\n ggtitle(\"Gráfico de resíduos versus valor predito\") +\n theme(panel.background = element_rect(fill = \"white\"))\n\n\n\n\n\n\n\nQuando plotamos o gráfico de resíduos versus os valores preditos, a distribuição deveria ser aleatória em torno de 0, mas vemos que existe certa tendência, o que demonstra que o modelo precisa de melhorias. No nosso caso, mais observações e variáveis, provavelmente matariam a charada.\nALERTAAAA: A partir daqui, a leitura é recomendada para quem já tem conhecimento de regressão linear simples. \nConhecedores de LM e dispostos a ler, venham comigo!\nUm outro meio de checar a bondade do ajuste de um modelo poisson, é usar o desvio residual. Ele é similar a soma de quadrado dos resíduos que vemos na regressão linear, é calculada como a diferença entre o desvio dos valores preditos do modelo e o desvio do modelo nulo, que é o modelo que contém apenas o intercepto: residual deviance = deviance(fitted_model) - deviance(null_model).\nO desvio residual mede quanto de variabilidade dos dados não pode ser explicada depois de considerar o efeito dos preditores. Um desvio residual mais baixo, indica um melhor ajuste. Em geral, um desvio residual que é muito menor que os graus de liberdade do modelo, sugerem um bom ajuste. Os graus de liberdade de uma regressão poisson são iguais ao número de observações menos o número de coeficientes estimados.\nPodemos usar o desvio residual para rodar um teste de ajuste para regressão poisson. A hipótese nula diz que o modelo se ajusta bem aos dados, a alternativa diz o contrário. O teste estatístico de desvio residual e o p-valor, são calculados com base na distribuição qui-quadrado com graus de liberdade iguais a diferença entre os graus de liberdade do modelo ajustado e o modelo nulo.\n\nexpected <- fitted(modelo5)\n\n# Calculate the Pearson's chi-squared statistic and p-value\npearson_chisq <- sum((base_final$y - expected)^2 / expected)\np_value <- 1 - pchisq(pearson_chisq, df = df.residual(modelo5))\n\n# Display the results\ncat(\"Pearson's chi-squared test:\\n\")\n\nPearson's chi-squared test:\n\ncat(\"X-squared = \", pearson_chisq, \", df = \", df.residual(modelo5), \", p-value = \", p_value, \"\\n\")\n\nX-squared = 62.90335 , df = 104 , p-value = 0.9995126 \n\n\nO p-valor alto indica que não há evidência de falta de ajuste, juntando tudo que vimos sobre precisão do modelo, podemos concluir que “estamos no caminho certo para modelar a nossa variável resposta, mas o modelo carece de melhorias”. Uma base maior, além de melhorar a precisão como já mencionei, nos permitiria separar um grupo de teste onde poderíamos ter uma noção mais clara do quão bem o modelo prevê a partir de entradas inéditas.\nAgora sim, me despeço oficialmente, quem quiser saber mais sobre o modelo de poisson, segue uma ótima referência!\nRegressão Poisson: https://online.stat.psu.edu/stat462/node/209/" }, { - "objectID": "eventos/2023-05-20/index.html#palestrantes", - "href": "eventos/2023-05-20/index.html#palestrantes", - "title": "Ciência de Dados, Gênero e Raça nas Políticas Públicas", - "section": "Palestrantes", - "text": "Palestrantes\n\nRita Santos (Elas no Orçamento)\nDoutora em Políticas Públicas e Gestão para o Desenvolvimento pela Universidade de Manchester (Reino Unido) e mestre em Economia pela Universidade de Brasília. É Consultora de Orçamentos do Senado Federal, co-fundadora da iniciativa Elas No Orçamento, docente em cursos de pós-graduação no IBMEC, FGV, IDP, ENAP, TCU, ILB, Escola do Legislativo de Minas Gerais e outras. Foi Secretária-Adjunta de Planejamento do Estado do Maranhão, EPPGG no Ministério da Economia e Subchefe Adjunta de Políticas Sociais e Assessora Especial para assuntos relacionados à acessão do Brasil à OCDE na Casa Civil da Presidência da República.\nSlides: https://rladies-sp.org/eventos/2023-05-20/Rita-Santos.pdf\n\n\n\n\n\n\nHaydee Svab (R-Ladies e ASK-R)\nSócia e co-fundadora da ASK-AR (consultoria em análise de dados), atualmente, é membro do Conselho de Governança da Open Knowledge Brasil e coordenadora do capítulo RLadies-São Paulo. Foi membro do Conselho Deliberativo da AEAMESP (Associação dos Engenheiros e Arquitetos de Metrô) nos triênios 2017/2019 e 2020/2022 e da comunidade Transparência Hacker. Foi consultora do BID, Banco Mundial, engenheira do Metrô-SP e co-fundadora dos grupos RLadies | São Paulo, PoliGNU e PoliGen. É mestra em Engenharia e Planejamento de Transportes (Poli-USP), especialista em Democracia Participativa, Repúblicas e Movimentos Sociais (UFMG) e formada em Engenharia Civil/Arquitetura pela USP (Programa Poli-FAU).\nSlides: https://rladies-sp.org/eventos/2023-05-20/Haydee-Svab.pdf\n\n\n\n\n\n\nEliane Barbosa (Unilab-CE)\nDoutora em Administração de Empresas pela FGV-EAESP, professora do curso de Administração Pública da Unilab-CE e pesquisadora do Centro de Estudo em Administração Pública e Governo da FGV-SP. É uma das coordenadoras do projeto de pesquisa (CNPq) “Origens e destinos: uma avaliação da política de cotas universitárias e seus efeitos no mercado de trabalho”. Coordenadora do projeto “Tributação Justa, Reparação Histórica”. Tem como principais temas de pesquisa as desigualdades raciais e de gênero nas organizações; políticas públicas de promoção da igualdade racial; política fiscal e desigualdades; e a relação governo e sociedade em países da África lusófona.\nSlides: https://rladies-sp.org/eventos/2023-05-20/Eliane-Barbosa.pdf\n\n\n\n\n\n\nFernando Barbalho (Tesouro Nacional)\nDoutor em Administração pela Universidade de Brasília (2014). Atualmente é auditor federal de finanças e controle da Secretaria do Tesouro Nacional (STN). A trajetória profissional e acadêmica mais recente está principalmente relacionada a dados abertos e desenvolvimento de produtos que resultem em maior transparência do Setor Público brasileiro. Nos finais de semana costuma utilizar o R para investigar perguntas de pesquisa que escapam ao mundo das finanças públicas.\nSlides: https://rladies-sp.org/eventos/2023-05-20/Fernando-Barbalho.pdf\n\n\n\n\n\n\nBeatriz Jardim (R-Ladies e INCA)\nDoutora em Epidemiologia pelo Instituto de Medicina Social Hesio Cordeiro da UERJ, Mestre em Epidemiologia e especialista em Saúde Pública pela FIOCRUZ. É tecnologista do Instituto Nacional de Câncer, onde é docente nos programas de pós-graduação. Atua na disponibilização de dados do Painel-Oncologia e dos sistemas de informação em câncer: SISCOLO, SISMAMA e SISCAN, possibilitando a utilização dos dados pelos gestores e pesquisadores.\nSlides: https://rladies-sp.org/eventos/2023-05-20/Beatriz-Jardim.pdf" + "objectID": "posts/2023-03-tidytuesday-paraolimpiadas/index.html#concluindo", + "href": "posts/2023-03-tidytuesday-paraolimpiadas/index.html#concluindo", + "title": "#TidyTuesday: Explorando dados sobre as Paraolimpíadas", + "section": "Concluindo", + "text": "Concluindo\nEssa foi uma breve demonstração do quanto o Tidytuesday é interessante e como podemos praticar nossas habilidades em tratamento de dados e análise. Esperamos que este artigo tenha inspirado você a explorar o mundo do TidyTuesday, e colocar a mão na massa no R, usando essa fonte de dados incrível para aprimorar suas habilidades em ciência de dados. Lembre-se que a comunidade tá aqui para te ajudar a alcançar seu objetivo em ciência de dados!" }, { "objectID": "sobre.html", @@ -483,165 +434,109 @@ "text": "Fonte / Saiba mais\n\nAbout us - R-Ladies\nMeetup - São Paulo\nR Community Explorer" }, { - "objectID": "sugestoes.html", - "href": "sugestoes.html", - "title": "Sugestão de conteúdos", - "section": "", - "text": "Tem algum conteúdo que gostaria de ver por aqui? Algum tema para eventos? Aproveite o espaço de comentários abaixo para fazer a sugestão!\nCaso alguém já tenha sugerido algo que você tem interesse, você também pode reagir com emojis em um comentário existente para demonstrar seu apoio!\nOs comentários são vinculados à sua conta do GitHub. Caso não tenha, crie uma gratuitamente." - }, - { - "objectID": "posts/2022-12-boas-vindas-ao-blog/index.html", - "href": "posts/2022-12-boas-vindas-ao-blog/index.html", - "title": "Boas vindas ao blog da R-Ladies São Paulo!", - "section": "", - "text": "A R-Ladies São Paulo é uma comunidade que iniciou em 2018, e desde então buscamos promover a diversidade de gênero na comunidade da linguagem R: organizando eventos presenciais e online, tirando dúvidas no nosso grupo do telegram, disponibilizando os materiais utilizados nos eventos, entre outros.\nCaso queira saber mais, consulte a página Sobre a R-Ladies São Paulo." - }, - { - "objectID": "posts/2022-12-boas-vindas-ao-blog/index.html#o-que-é-a-r-ladies-são-paulo", - "href": "posts/2022-12-boas-vindas-ao-blog/index.html#o-que-é-a-r-ladies-são-paulo", - "title": "Boas vindas ao blog da R-Ladies São Paulo!", - "section": "", - "text": "A R-Ladies São Paulo é uma comunidade que iniciou em 2018, e desde então buscamos promover a diversidade de gênero na comunidade da linguagem R: organizando eventos presenciais e online, tirando dúvidas no nosso grupo do telegram, disponibilizando os materiais utilizados nos eventos, entre outros.\nCaso queira saber mais, consulte a página Sobre a R-Ladies São Paulo." - }, - { - "objectID": "posts/2022-12-boas-vindas-ao-blog/index.html#por-que-um-blog", - "href": "posts/2022-12-boas-vindas-ao-blog/index.html#por-que-um-blog", - "title": "Boas vindas ao blog da R-Ladies São Paulo!", - "section": "Por que um blog?", - "text": "Por que um blog?\nTer um site/blog é uma forma de facilitar a divulgar o conteúdo que produzimos, além de ser uma forma de incentivar as pessoas da comunidade a compartilharem seus conhecimentos por aqui também! Essa é uma vontade que as pessoas da comunidade expressaram algumas vezes no passado: já discutimos anteriormente sobre criar um blog das R-Ladies na América Latina (R-Ladies LATAM) e a ideia foi liderada pela Bruna Wundervald, uma das co-organizadoras da R-Ladies São Paulo na época (em janeiro de 2019); em junho de 2021 a ideia voltou para criar um blog para a comunidade em São Paulo, mas infelizmente nenhuma dessas versões chegou a ser utilizada e divulgada.\nA volta dos eventos presenciais (em novembro de 2022) foi um impulso para voltar a trabalhar na criação de um blog para a comunidade!" - }, - { - "objectID": "posts/2022-12-boas-vindas-ao-blog/index.html#posso-contribuir-com-o-blog", - "href": "posts/2022-12-boas-vindas-ao-blog/index.html#posso-contribuir-com-o-blog", - "title": "Boas vindas ao blog da R-Ladies São Paulo!", - "section": "Posso contribuir com o blog?", - "text": "Posso contribuir com o blog?\nSim! Começamos a preparar uma página com informações para pessoas que queiram enviar seus textos por aqui: Como contribuir com o blog?. Também é possível contribuir sugerindo novos conteúdos, avisando caso tenha alguma informação desatualizada, entre outros." - }, - { - "objectID": "posts/2022-12-boas-vindas-ao-blog/index.html#inscreva-se-para-receber-novidades", - "href": "posts/2022-12-boas-vindas-ao-blog/index.html#inscreva-se-para-receber-novidades", - "title": "Boas vindas ao blog da R-Ladies São Paulo!", - "section": "Inscreva-se para receber novidades", - "text": "Inscreva-se para receber novidades\nNeste blog, existe um formulário simples para inscrição do seu email, caso queira receber as novidades! O formulário se encontra na coluna à direita do texto principal, e se parece com a imagem a seguir:" - }, - { - "objectID": "posts/2022-12-boas-vindas-ao-blog/index.html#o-que-esperar", - "href": "posts/2022-12-boas-vindas-ao-blog/index.html#o-que-esperar", - "title": "Boas vindas ao blog da R-Ladies São Paulo!", - "section": "O que esperar?", - "text": "O que esperar?\nA ideia é que este seja um espaço onde as pessoas da comunidade R-Ladies possam publicar textos relacionados à atuação da comunidade, programação em R, ciência de dados e muito mais.\n\n\n\nArte por Allison Horst.\n\n\nEsperamos que seja um lugar rico de troca e compartilhamento! Até logo!" + "objectID": "eventos/2023-05-20/index.html#palestrantes", + "href": "eventos/2023-05-20/index.html#palestrantes", + "title": "Ciência de Dados, Gênero e Raça nas Políticas Públicas", + "section": "Palestrantes", + "text": "Palestrantes\n\nRita Santos (Elas no Orçamento)\nDoutora em Políticas Públicas e Gestão para o Desenvolvimento pela Universidade de Manchester (Reino Unido) e mestre em Economia pela Universidade de Brasília. É Consultora de Orçamentos do Senado Federal, co-fundadora da iniciativa Elas No Orçamento, docente em cursos de pós-graduação no IBMEC, FGV, IDP, ENAP, TCU, ILB, Escola do Legislativo de Minas Gerais e outras. Foi Secretária-Adjunta de Planejamento do Estado do Maranhão, EPPGG no Ministério da Economia e Subchefe Adjunta de Políticas Sociais e Assessora Especial para assuntos relacionados à acessão do Brasil à OCDE na Casa Civil da Presidência da República.\nSlides: https://rladies-sp.org/eventos/2023-05-20/Rita-Santos.pdf\n\n\n\n\n\n\nHaydee Svab (R-Ladies e ASK-R)\nSócia e co-fundadora da ASK-AR (consultoria em análise de dados), atualmente, é membro do Conselho de Governança da Open Knowledge Brasil e coordenadora do capítulo RLadies-São Paulo. Foi membro do Conselho Deliberativo da AEAMESP (Associação dos Engenheiros e Arquitetos de Metrô) nos triênios 2017/2019 e 2020/2022 e da comunidade Transparência Hacker. Foi consultora do BID, Banco Mundial, engenheira do Metrô-SP e co-fundadora dos grupos RLadies | São Paulo, PoliGNU e PoliGen. É mestra em Engenharia e Planejamento de Transportes (Poli-USP), especialista em Democracia Participativa, Repúblicas e Movimentos Sociais (UFMG) e formada em Engenharia Civil/Arquitetura pela USP (Programa Poli-FAU).\nSlides: https://rladies-sp.org/eventos/2023-05-20/Haydee-Svab.pdf\n\n\n\n\n\n\nEliane Barbosa (Unilab-CE)\nDoutora em Administração de Empresas pela FGV-EAESP, professora do curso de Administração Pública da Unilab-CE e pesquisadora do Centro de Estudo em Administração Pública e Governo da FGV-SP. É uma das coordenadoras do projeto de pesquisa (CNPq) “Origens e destinos: uma avaliação da política de cotas universitárias e seus efeitos no mercado de trabalho”. Coordenadora do projeto “Tributação Justa, Reparação Histórica”. Tem como principais temas de pesquisa as desigualdades raciais e de gênero nas organizações; políticas públicas de promoção da igualdade racial; política fiscal e desigualdades; e a relação governo e sociedade em países da África lusófona.\nSlides: https://rladies-sp.org/eventos/2023-05-20/Eliane-Barbosa.pdf\n\n\n\n\n\n\nFernando Barbalho (Tesouro Nacional)\nDoutor em Administração pela Universidade de Brasília (2014). Atualmente é auditor federal de finanças e controle da Secretaria do Tesouro Nacional (STN). A trajetória profissional e acadêmica mais recente está principalmente relacionada a dados abertos e desenvolvimento de produtos que resultem em maior transparência do Setor Público brasileiro. Nos finais de semana costuma utilizar o R para investigar perguntas de pesquisa que escapam ao mundo das finanças públicas.\nSlides: https://rladies-sp.org/eventos/2023-05-20/Fernando-Barbalho.pdf\n\n\n\n\n\n\nBeatriz Jardim (R-Ladies e INCA)\nDoutora em Epidemiologia pelo Instituto de Medicina Social Hesio Cordeiro da UERJ, Mestre em Epidemiologia e especialista em Saúde Pública pela FIOCRUZ. É tecnologista do Instituto Nacional de Câncer, onde é docente nos programas de pós-graduação. Atua na disponibilização de dados do Painel-Oncologia e dos sistemas de informação em câncer: SISCOLO, SISMAMA e SISCAN, possibilitando a utilização dos dados pelos gestores e pesquisadores.\nSlides: https://rladies-sp.org/eventos/2023-05-20/Beatriz-Jardim.pdf" }, { - "objectID": "posts/2023-03-evento-open-data-day/english.html", - "href": "posts/2023-03-evento-open-data-day/english.html", - "title": "Event: Open Data Analysis with R", + "objectID": "eventos.html", + "href": "eventos.html", + "title": "Próximos eventos", "section": "", - "text": "R-Ladies São Paulo organized, on March 18, 2023, the event “Open Data Analysis with R - Open Data Day.” The activity took place on a Saturday, during the morning and afternoon, with 6 hours of activities.\nInsper, a non-profit institution dedicated to teaching and research, once again supported the group by providing the space for the event. Another support received was from Curso-R, which provided two teaching assistants to help out participants. The main objective of this event was to offer information about what open data is and its importance. Also, we aimed to promote the opportunity to do a “hands-on” activity exploring open data and tracking the current scenario of public data access at various levels of government and topics." + "text": "Acompanhe as novidades nas nossas redes sociais!" }, { - "objectID": "posts/2023-03-evento-open-data-day/english.html#introduction", - "href": "posts/2023-03-evento-open-data-day/english.html#introduction", - "title": "Event: Open Data Analysis with R", + "objectID": "contribuir-com-o-blog.html", + "href": "contribuir-com-o-blog.html", + "title": "Como contribuir com o blog?", "section": "", - "text": "R-Ladies São Paulo organized, on March 18, 2023, the event “Open Data Analysis with R - Open Data Day.” The activity took place on a Saturday, during the morning and afternoon, with 6 hours of activities.\nInsper, a non-profit institution dedicated to teaching and research, once again supported the group by providing the space for the event. Another support received was from Curso-R, which provided two teaching assistants to help out participants. The main objective of this event was to offer information about what open data is and its importance. Also, we aimed to promote the opportunity to do a “hands-on” activity exploring open data and tracking the current scenario of public data access at various levels of government and topics." - }, - { - "objectID": "posts/2023-03-evento-open-data-day/english.html#what-is-open-data-day", - "href": "posts/2023-03-evento-open-data-day/english.html#what-is-open-data-day", - "title": "Event: Open Data Analysis with R", - "section": "What is Open Data Day?", - "text": "What is Open Data Day?\nOpen Data Day is an annual celebration of open data worldwide, organized and supported by the Open Knowledge Foundation. If you want to know more, check the official Open Data Day website and the project page on the Open Knowledge Brasil website." - }, - { - "objectID": "posts/2023-03-evento-open-data-day/english.html#main-activity", - "href": "posts/2023-03-evento-open-data-day/english.html#main-activity", - "title": "Event: Open Data Analysis with R", - "section": "Main activity", - "text": "Main activity\nWith about 40 people, we structured the event in four blocks. The first block was instructive and featured a sequence of brief presentations such as: what is the R-Ladies São Paulo community, what is Open Data Day and what is Open Data.\n\n\n\n\nThe objective was to make people feel free to work with open data, so we split the class into small working groups. Each group worked on a specific dataset and worked with a Teaching Assistant with experience analyzing that dataset, who guided the group to look into the data and understand them. So, the second block consisted of the following activities:\n\nThe explanation of how this activity would happen;\nA brief speech (about 5 minutes) by each Teaching Assistant on the topic of their expertise and on the dataset that the group would work on, to facilitate the identification of participants with the subject;\nAnd the separation of participants into groups according to the affinity of interests - everyone could choose the topic with more interest, and there was no need to resize or redistribute groups.\n\nThe topics and respective teaching assistants were:\n\nData on violence - Fernanda Peres, biomedical\nEnvironmental data on fires - Bianca Muniz, journalist\nEducational data - Ana Carolina Moreno, journalist\nEmployment data - Ana Paula Rocha, economist\nElection data - Cecília do Lago, journalist\nPrison data - Thandara Santos, sociologist\n\nIn addition, teaching assistants were available to help with questions about R:\n\nBeatriz Milz (R-Ladies SP co-organizer)\nIanní Muliterno (R-Ladies SP co-organizer)\nGeovana Lopes Batista (R-Ladies SP co-organizer)\nHaydee Svab (R-Ladies SP co-organizer)\nJulio Trecenti (Curso-R)\nWilliam Amorim (Curso-R)\n\nWe created a Google Document so the groups could take and share notes.\n\n\n\n\n\n\n\n\n\n\nThen, in the third block, the groups worked on importing, understanding, and starting to explore the open data of their respective themes. As many people pointed out that they had no experience creating data visualizations and were interested in getting started, co-organizer Beatriz Milz gave a short live coding presentation on using the Esquisse package to generate data visualizations with ggplot2.\n\n\n\n\nIn the fourth and last block, the groups presented some of their difficulties, lessons learned, and results (some even showed visualizations made!). In addition, interesting presentations reflected the topics addressed in the initial presentations on open data - for example, some groups indicated dealing with an outdated database, others pointed out that data was aggregated and could be made available with a greater level of detail, etc.\nThe experience was outstanding, and the organizers and participants demonstrated that they enjoyed the activity a lot (especially the children!). Each group had between two to six people in addition to the teaching assistants, which allowed for a more individualized follow-up to answer questions." + "text": "Se você faz parte da comunidade R-Ladies São Paulo ou outros capítulos do Brasil, e gostaria contribuir com algum post ou conteúdo para o blog, a contribuição será muito bem vinda!" }, { - "objectID": "posts/2023-03-evento-open-data-day/english.html#strengthening-the-community", - "href": "posts/2023-03-evento-open-data-day/english.html#strengthening-the-community", - "title": "Event: Open Data Analysis with R", - "section": "Strengthening the community", - "text": "Strengthening the community\nTwo interesting points to highlight are the collaborative coffee and the Gugudadados Space.\nCollaborative coffee\n\n\n\n\n\n\n\n\nWe made a collaborative coffee with items purchased by the organizing group (with the money received from the scholarship offered by OKBR) and food brought by participants. This way, people could get up and get coffee and something to eat at any time during the event. This coffee format (available the entire time of the event) is very good for three reasons: (i) it respects the time of the groups who can take their breaks as the work progresses; (ii) it welcomes participants who, for health reasons, cannot go without eating for many hours and (iii) welcomes participants who, due to socio-economic conditions, are unable to have a meal during their lunch break. Given the nature of the R-Ladies group, it is an important aspect to provide a welcoming environment so that everyone can enjoy the experience of the event regardless of having something to eat throughout the day, in addition to the fact that the collaborative coffee is also a way to encourage integration between people!\nGugudadados Space\nWe created the Gugudadados Space to facilitate the participation of people responsible for kids and babies (e.g., mothers, fathers, and caregivers). A baby and four children between 7 and 10 years old participated in this event. With the money from the scholarship offered by OKBR, it was possible to hire a recreational teacher in the Gugudadados Space (a room next to the event room, on the same floor) throughout the activity. The R-Ladies organizers also took toys, drawings, markers, games, and temporary tattoos to entertain and amuse the children." + "objectID": "contribuir-com-o-blog.html#tipos-de-contribuição", + "href": "contribuir-com-o-blog.html#tipos-de-contribuição", + "title": "Como contribuir com o blog?", + "section": "Tipos de contribuição", + "text": "Tipos de contribuição\nExistem várias formas de contribuir, como:\n\ncaso encontre alguma informação desatualizada e/ou que precise de correção, pode fazer a atualização/correção;\nescrever algum texto não-técnico relacionado às atividades do grupo;\nescrever algum texto técnico para o blog (por exemplo, mostrando alguma análise feita com R por você);\nescrever algum tutorial sobre uso de algum pacote para o blog;\nenviar algum texto técnico já escrito no seu blog pessoal, que possa ser re-compartilhado aqui;\nentre outros!" }, { - "objectID": "posts/2023-03-evento-open-data-day/english.html#results-from-the-groups-during-the-event", - "href": "posts/2023-03-evento-open-data-day/english.html#results-from-the-groups-during-the-event", - "title": "Event: Open Data Analysis with R", - "section": "Results from the groups during the event", - "text": "Results from the groups during the event\nEducational data (T.A. Ana Carolina Moreno)\nThe T.A. presented the group with an R code for analyzing data from the Census of Basic Education used to produce a series of special reports on the impact of the pandemic on early childhood education, which aired in November 2022. The monitor also prepared a presentation on educational data to assist in understanding the different sources and databases available on education.\nThe data used can be obtained from the INEP website.\nElectoral data (T.A. Cecília do Lago):\nThis group explored electoral data for the 2022 elections, made available by the TSE. The group wanted to find out how many candidates did not receive one or zero votes in the 2022 election.\nThe data used can be obtained from the TSE’s Open Data Portal.\nEnvironmental data on Fires (T.A. Bianca Muniz):\nThis group explored data on fires in INPE’s BDQueimadas system. This system allows anyone to download data for up to one year. The T.A. prepared apresentation about how to download and import this dataset. The group exported data from 2020 to 2022, and the graph below shows the number of fires per month according to the biome where the fires occurred. It is possible to see in the graph that the biomes with the biggest amount of fires are the Amazon and the Cerrado, and they show seasonal patterns. For example, the highest peak of fires in the Amazon, from 2020 to 2022, was the second semester of 2022.\n\n\n\n\nThe data used can be obtained from the INPE - BD QUEIMADAS website.\nPrison data (T.A. Thandara Santos):\nThis group explored data from SISDEPEN - Statistical Data of the Brazilian Penitentiary System. These data come from the Prison Information Form, answered electronically every six months by government employees.\nOne of the difficulties presented by the group is the availability of data to be aggregated by prison unit rather than by individuals, which makes it impossible to do several fundamental analyses on the prison population in Brazil. Another area for improvement is the lack of standardization of the answers presented in the database, which implies low data reliability.\nThe data can be obtained from the National Secretariat for Penal Policies website.\nViolence data (T.A. Fernanda Peres):\nThis group explored public data on violence using data from SINAN - Information System for Aggravation of Notifications, filtering occurrences involving only adults and removing self-inflicted violence (for example, suicide). The group found that the public data on Violence in DataSUS were outdated. The dataset for 2020 was incomplete, so the group explored data for 2019. The group generated a series of graphs, such as the one below, showing that the largest number of victims are woman. In addition, it is noteworthy that the author of the aggression is most often male (whether the victim is a woman or a man).\n\n\n\n\nAnother thing pointed out by the group is that when the victims were women, the aggressor tended to be someone they knew, such as a spouse, ex-spouse, boyfriend, or ex-boyfriend. On the other hand, among men, the most common aggressor is a stranger.\n\n\n\n\nThis data can be downloaded from DATASUS. The T.A. gave a presentation on how to get this data.\nEmployment data group (T.A. Ana Paula):\nThe T.A. gave apresentation on how to import this data. First, the group explored two databases from Caged (General Register of Employed and Unemployed) from the Central Bank: the number of total jobs from 2000 to 2023; and the number of jobs in the manufacturing industry (any raw material that is processed) from 2000 to 2023.  The data can be obtained with the GetBCBData package, making it possible to search for updated data aggregated by month/year and time series I.D.\n\n# Loading packages\nlibrary(tidyverse)\nlibrary(GetBCBData)\n\n# Importing data\ndados_sgs <- GetBCBData::gbcbd_get_series(\n id = c('NCaged' = 28763, 'NCaged_IndTransf'= 28766),\n first.date = '2020-01-01',\n last.date = Sys.Date(),\n format.data = 'wide'\n)\n\n# Looking at the content\nglimpse(dados_sgs)\n\nRows: 37\nColumns: 3\n$ ref.date <date> 2020-01-01, 2020-02-01, 2020-03-01, 2020-04-01, 2020…\n$ NCaged <dbl> 37938640, 38155900, 37860843, 36879150, 36480704, 364…\n$ NCaged_IndTransf <dbl> 6924768, 6961283, 6918309, 6705220, 6600422, 6593132,…\n\n# Pivoting in order to prepare the dataset to ggplot2\ndados_sgs_longo <- dados_sgs %>% \n pivot_longer(cols = c(NCaged, NCaged_IndTransf))\n\n# Creating a graph\nggplot(dados_sgs_longo) +\n aes(x = ref.date, y = value, colour = name) +\n geom_line(show.legend = FALSE) +\n scale_color_hue(direction = 1) +\n theme_minimal() +\n facet_wrap(vars(name), scales = \"free_y\")\n\n\n\n\n\n\n\nTo learn more about this database, consult the Central Bank of Brazil Time Series Management System website." + "objectID": "contribuir-com-o-blog.html#como-contribuir", + "href": "contribuir-com-o-blog.html#como-contribuir", + "title": "Como contribuir com o blog?", + "section": "Como contribuir?", + "text": "Como contribuir?\nAs alterações no código costumam ser feitas através do GitHub. Você pode criar uma conta gratuita e seguir o passo-a-passo indicado abaixo.\n\n\n\n\n\n\nNota\n\n\n\nCaso você não use GitHub, pode enviar a contribuição escrevendo em um arquivo Google Documentos, word/.docx ou RMarkdown/Quarto, por exemplo, e enviando para a gente através de uma issue no GitHub." }, { - "objectID": "posts/2023-03-evento-open-data-day/english.html#information-about-participants", - "href": "posts/2023-03-evento-open-data-day/english.html#information-about-participants", - "title": "Event: Open Data Analysis with R", - "section": "Information about participants", - "text": "Information about participants\nWe want to increase the diversity in the events, so, in this edition, we separated a percentage of spots thinking about three groups:\n- BIPOC (Black, Indigenous, and people of color)\n- mothers;\n- women and other gender minorities.\nIn this event, 54 people signed up, and 37 participated. Below are some graphs showing information about the diversity of the participants.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThere is still a lot of work to do to include unrepresented groups at events, but compared to pre-pandemic events, we are making progress. It is essential to expand the publicity for the following events, especially for BIPOC (Black, Indigenous, and people of color), mothers, and trans and non-binary people. Also, it is important to look for venues to make events in the periphery." + "objectID": "contribuir-com-o-blog.html#contribuindo-com-alguma-página-que-já-existe", + "href": "contribuir-com-o-blog.html#contribuindo-com-alguma-página-que-já-existe", + "title": "Como contribuir com o blog?", + "section": "Contribuindo com alguma página que já existe", + "text": "Contribuindo com alguma página que já existe\nCaso queira sugerir uma alteração em uma página já existente, siga os passos abaixo:\n1 - Primeiro confira se na barra do lado direito aparece o link chamado “Edite essa página”:\n\n\n\n\n\nEsse link te encaminhará para o arquivo que deve ser alterado no GitHub.\n2 - Caso não encontre o link “Editar essa página”, procure o arquivo referente à página que deseja alterar no repositório no GitHub. Os arquivos de texto que devem ser alterados são apenas os que tem extensão .qmd.\n3 - Fazendo a alteração no GitHub: EM BREVE!" }, { - "objectID": "posts/2023-03-evento-open-data-day/english.html#difficulties", - "href": "posts/2023-03-evento-open-data-day/english.html#difficulties", - "title": "Event: Open Data Analysis with R", - "section": "Difficulties", - "text": "Difficulties\nThe main difficulty in organizing the event was the short time available for publicizing the activity, since the date and place were defined only six days in advance. Despite the available room having a capacity for 100 people, only 40 had enough time to organize themselves and register as participants.\nHowever, the presence of more than 40 people, including people from the organization, was enough to carry out the activity, with the presence of people really interested in the topic." + "objectID": "contribuir-com-o-blog.html#contribuindo-com-um-textopost-para-o-blog", + "href": "contribuir-com-o-blog.html#contribuindo-com-um-textopost-para-o-blog", + "title": "Como contribuir com o blog?", + "section": "Contribuindo com um texto/post para o blog", + "text": "Contribuindo com um texto/post para o blog\nOs arquivos que geram os posts do blog estão na pasta posts/.\n1 - Faça uma cópia da pasta template-post/. Nomeie a pasta iniciando com o ano e mês, e algumas palavras que indicam o conteúdo do texto de uma forma “limpa”, sem usar acentos, espaços, e outros caracteres especiais. Ex: 2022-12-tutorial-tidyverse.\nNessa pasta, tem arquivos para gerar um post:\n\nindex.qmd: esse é o arquivo principal! Neste arquivo, estão descritos os metadados do arquivo (quem escreveu o post, data, categorias, entre outros), e o texto do post. Tem vários exemplos e comentários neste arquivo para ajudar quem ainda não tem muita familiaridade com Quarto!\nimages/: é uma pasta onde pode guardar as imagens que você queira usar no post.\npacotes.bib: é um arquivo opcional e gerado automaticamente, contém as referências dos pacotes utilizados no post.\n\n2 - Edite os conteúdos na pasta copiada!\n3 - Envie suas mudanças como um Pull request no GitHub: EM BREVE!." }, { - "objectID": "posts/2023-03-evento-open-data-day/english.html#commentaries", - "href": "posts/2023-03-evento-open-data-day/english.html#commentaries", - "title": "Event: Open Data Analysis with R", - "section": "Commentaries", - "text": "Commentaries\nIn addition to the description offered by the organization’s team, we would also like to share two commentaries shared by people who participated in the event:\nTatiana Peixoto:\n\nHello, I’m Tatiana, a 42-year-old cis woman, black, environmental engineer, and passionate about studying. I signed up for the event, not only for the training but also for the search for optimism, thus creating strength to enter the professional market again, as I spent a long time in the academic environment. On 18.03.23th, I understood that R-ladies is much more than an introductory programming event. This team brings a new look at programming, removing blockages and obstacles for all those who want to follow a beautiful path in data science. The event is of excellent quality. I felt welcomed, cared for, and very well treated. I would definitely attend other R-ladies events. In addition to all the kindness of the Insper team in receiving us. I hope that R-ladies SP will continue with new events and new projects because, like me, they will make a lot of people happy.\n\nJuliana Soprani:\n\nI take this opportunity to reinforce my congratulations on the event! It was really relevant!!! Not only technically, in learning data analysis and the use of R, but also on the issue of welcoming, triggering a sense of belonging to a group or purpose. For someone starting in the data area, or in a career transition, as in my case, it was very important to see so many women from different areas, ages, and backgrounds working with data and R and engaged in expanding access to the tool for minorities. I am grateful for the opportunity and hope to contribute to health data analysis in the future.\nLooking forward to upcoming meetings." + "objectID": "index.html#textos-em-português", + "href": "index.html#textos-em-português", + "title": "Blog", + "section": "Textos em Português", + "text": "Textos em Português\n\n\n \n \n \n\n\n\n\n\n \n\n\n\n\nConhecendo o R, o Tidyverse e as R-Ladies\n\n\nRelato de evento a partir de membros da comunidade\n\n\n\n\nEventos\n\n\n \n\n\n\n\n21 de nov. de 2023\n\n\nBianca Muniz, Gabriela Morita, Karina Ferreira\n\n\n\n\n\n\n \n\n\n\n\nRaspando a página do Studio Ghibli, na Wikipédia\n\n\n\n\n\n\n\nWeb Scraping\n\n\nTutorial\n\n\n \n\n\n\n\n31 de out. de 2023\n\n\nOrnella Scardua Ferreira\n\n\n\n\n\n\n \n\n\n\n\nAções para ampliar a diversidade na comunidade R-Ladies São Paulo\n\n\n\n\n\n\n\nR-Ladies\n\n\nComunidade\n\n\n \n\n\n\n\n2 de out. de 2023\n\n\nBeatriz Milz, Haydee Svab, Tatyane Paz Dominguez, Ianni Muliterno, Ana Paula Rocha\n\n\n\n\n\n\n \n\n\n\n\nRita com R\n\n\nAnalisando a padroeira da liberdade com código\n\n\n\n\nAnálise exploratória\n\n\nAnálise de texto\n\n\nMúsica\n\n\n \n\n\n\n\n2 de jun. de 2023\n\n\nBianca Muniz\n\n\n\n\n\n\n \n\n\n\n\nDados abertos de Educação: um exemplo aplicado ao jornalismo\n\n\nResultados do evento Open Data Day\n\n\n\n\nComunidade\n\n\nEnsino\n\n\nJornalismo de dados\n\n\nOpen data day\n\n\nEducação\n\n\n \n\n\n\n\n24 de mai. de 2023\n\n\nAna Carolina Moreno, Beatriz Milz, Geovana Lopes, Katia Mine, Natasha Meneguelli, Cristiane Souza de Lacerda\n\n\n\n\n\n\n \n\n\n\n\nAprendendo a programar em quatro capítulos\n\n\n\n\n\n\n\nComunidade\n\n\nEnsino\n\n\nJornalismo de dados\n\n\n \n\n\n\n\n10 de mai. de 2023\n\n\nAna Carolina Moreno\n\n\n\n\n\n\n \n\n\n\n\nEvento: Análise de dados abertos com R\n\n\nUm evento parte da iniciativa Open Data Day\n\n\n\n\nEventos\n\n\nComunidade\n\n\nDiversidade\n\n\n \n\n\n\n\n27 de mar. de 2023\n\n\nTatyane Paz Dominguez, Haydée Svab, Beatriz Milz, Ana Carolina Moreno, Ana Paula Rocha\n\n\n\n\n\n\n \n\n\n\n\nTidyTuesday: Explorando dados sobre as Paraolimpíadas\n\n\n\n\n\n\n\nTidytuesday\n\n\nAnálise exploratória\n\n\nVisualização de dados\n\n\nModelagem\n\n\n \n\n\n\n\n1 de mar. de 2023\n\n\nIanní Muliterno\n\n\n\n\n\n\n \n\n\n\n\nE aí, vamos falar de Quarto?\n\n\nTutorial: Relatório em Quarto\n\n\n\n\nQuarto\n\n\nTutorial\n\n\nRelatórios\n\n\n \n\n\n\n\n7 de fev. de 2023\n\n\nAriane Hayana\n\n\n\n\n\n\n \n\n\n\n\nEvento: Oficina de Introdução ao R\n\n\nPrimeiro evento presencial desde o início da pandemia\n\n\n\n\nEventos\n\n\nComunidade\n\n\nDiversidade\n\n\n \n\n\n\n\n31 de jan. de 2023\n\n\nBeatriz Milz, Tatyane Paz Dominguez\n\n\n\n\n\n\n \n\n\n\n\nGráficos de barras com barras de erros: críticas e alternativas\n\n\n\n\n\n\n\nGráficos\n\n\nTutorial\n\n\nDataviz\n\n\n \n\n\n\n\n14 de dez. de 2022\n\n\nFernanda Peres\n\n\n\n\n\n\n \n\n\n\n\nBoas vindas ao blog da R-Ladies São Paulo!\n\n\n\n\n\n\n\nNovidades\n\n\n \n\n\n\n\n5 de dez. de 2022\n\n\nEquipe R-Ladies SP, Beatriz Milz\n\n\n\n\n\n\n \n\n\n\n\nVidasNegrasImportam: Uma declaração conjunta de Forwards e R-Ladies\n\n\n#VidasNegrasImportam: Uma declaração conjunta de Forwards e R-Ladies\n\n\n\n\nDiversidade\n\n\nJustiça Social\n\n\n \n\n\n\n\n6 de jun. de 2020\n\n\nR-Ladies Global Leadership Team, R Forwards\n\n\n\n\n\n\nNenhum item correspondente" }, { - "objectID": "posts/2023-03-evento-open-data-day/english.html#support", - "href": "posts/2023-03-evento-open-data-day/english.html#support", - "title": "Event: Open Data Analysis with R", - "section": "Support", - "text": "Support\n\n\n\n\n\n\n\n\nIt is important to emphasize the importance of OKBR ’s financial support, which enabled the purchase of items for the coffee break, stickers, and hiring a recreator. \nThe rooms offered by Insper were crucial for the event to take place. The building is easily accessible by public transport. The meeting took place in a large space with internet access, tables, comfortable chairs, and easy access to a restaurant for lunch. The toboggan that is part of the building’s facilities is also a success and makes up one of the most joyful experiences for children who stay at Gugudadados.\nCurso-R also supported the event, providing two R teachers to assist in the activity and being available to help with questions from the participants." + "objectID": "index.html#textos-traduzidos-para-o-inglês", + "href": "index.html#textos-traduzidos-para-o-inglês", + "title": "Blog", + "section": "Textos traduzidos para o Inglês", + "text": "Textos traduzidos para o Inglês\n\n\n \n \n \n\n\n\n\n\n \n\n\n\n\nActions to increase diversity in the R-Ladies São Paulo community\n\n\n\n\n\n\n\nR-Ladies\n\n\ncommunity\n\n\nlatin america\n\n\n \n\n\n\n\n2 de out. de 2023\n\n\nBeatriz Milz, Haydee Svab, Tatyane Paz Dominguez, Ianni Muliterno, Ana Paula Rocha\n\n\n\n\n\n\n \n\n\n\n\nEvent: Open Data Analysis with R\n\n\nAn event part of the Open Data Day initiative\n\n\n\n\nEvents\n\n\nCommunity\n\n\nDiversity\n\n\nEnglish\n\n\n \n\n\n\n\n26 de mar. de 2023\n\n\nTatyane Paz Dominguez, Haydée Svab, Beatriz Milz, Ana Carolina Moreno, Ana Paula Rocha\n\n\n\n\n\n\nNenhum item correspondente" }, { - "objectID": "posts/2023-03-evento-open-data-day/english.html#team", - "href": "posts/2023-03-evento-open-data-day/english.html#team", - "title": "Event: Open Data Analysis with R", - "section": "Team", - "text": "Team\nThis event was only possible with the collaboration of several people. Therefore, here is a list of people who participated in the various stages of organizing the event:\n\nAna Paula Rocha - organization, teaching assistant\nAna Carolina Moreno - organization, teaching assistant\nBeatriz Milz - organization, teaching assistant\nBianca Muniz - teaching assistant\nCecília do Lago - teaching assistant\nCélia Oliveira - Gugudadados space\nDiego Rabatone Oliveira - Gugudadados space\nFernanda Peres - organization, teaching assistant\nGeovana Lopes Batista - teaching assistant\nHaydee Svab - organization, teaching assistant, Gugudadados space\nIanní Muliterno - teaching assistant\nJulio Trecenti - teaching assistant\nTatyane Paz Dominguez - organization, Gugudadados space\nThandara Santos - teaching assistant\nWilliam Amorim - teaching assistant\n\nThe event would not be the same without your collaboration - we appreciate and greatly appreciate your participation!\nIn addition, we also thank everyone who participated!" + "objectID": "index.html#apoio-financeirosponsor", + "href": "index.html#apoio-financeirosponsor", + "title": "Blog", + "section": "Apoio financeiro/Sponsor", + "text": "Apoio financeiro/Sponsor\n\n\nR Consortium" }, { - "objectID": "posts/2023-03-evento-open-data-day/english.html#next-events", - "href": "posts/2023-03-evento-open-data-day/english.html#next-events", - "title": "Event: Open Data Analysis with R", - "section": "Next events", - "text": "Next events\nThis was the first time we held an event with the idea of ​​working in “groups”, and it is certainly a format that worked well (the participants indicated that they preferred this way to expository lectures). We intend to organize other events in this format!\nThe next R-Ladies São Paulo event is scheduled for May, with a theme yet to be defined. If you are interested in participating, we recommend following our social media!" + "objectID": "sugestoes.html", + "href": "sugestoes.html", + "title": "Sugestão de conteúdos", + "section": "", + "text": "Tem algum conteúdo que gostaria de ver por aqui? Algum tema para eventos? Aproveite o espaço de comentários abaixo para fazer a sugestão!\nCaso alguém já tenha sugerido algo que você tem interesse, você também pode reagir com emojis em um comentário existente para demonstrar seu apoio!\nOs comentários são vinculados à sua conta do GitHub. Caso não tenha, crie uma gratuitamente." }, { - "objectID": "posts/2023-02-tutorial-quarto/index.html", - "href": "posts/2023-02-tutorial-quarto/index.html", - "title": "E aí, vamos falar de Quarto?", + "objectID": "como-participar.html", + "href": "como-participar.html", + "title": "Como fazer parte da R-Ladies São Paulo?", "section": "", - "text": "Autoria\n\n\n\n\n\n\n\n\nAriane Hayana\n\n \n\nEste post foi escrito pela Ariane Hayana, uma integrante da comunidade R-Ladies São Paulo! Criadora da página @ _estatistica, é graduada em Economia e finalista em sua segunda graduação no curso de Bacharelado em Estatística na Universidade Federal do Amazonas (UFAM), atuando como estagiária no Supremo Tribunal Federal (STF).\nSaiba mais sobre ela em seu LinkedIn." + "text": "Os eventos realizados pela R-Ladies São Paulo são gratuitos e são divulgados na plataforma Meetup. Se quiser acompanhar os próximos eventos, recomendamos inscrever-se na plataforma Meetup e seguir as nossas redes sociais, principalmente o Instagram." }, { - "objectID": "posts/2023-02-tutorial-quarto/index.html#e-aí-vamos-falar-de-quarto", - "href": "posts/2023-02-tutorial-quarto/index.html#e-aí-vamos-falar-de-quarto", - "title": "E aí, vamos falar de Quarto?", - "section": "E aí, vamos falar de Quarto?", - "text": "E aí, vamos falar de Quarto?\n\n\nArte de pinguins abraçados feita por Allison Horst: Artwork from “Hello, Quarto” keynote by Julia Lowndes and Mine Çetinkaya-Rundel, presented at RStudio Conference 2022. Illustrated by Allison Horst.\n\nHello, world!\nVocê que gosta da nossa querida linguagem R provavelmente já deve ter ouvido falar sobre Quarto. Por definição, segundo Quarto.org,\n\n“Quarto é uma versão multilíngue da próxima geração do R Markdown (do RStudio) e inclui dezenas de novos recursos, ao mesmo tempo em que é capaz de renderizar a maioria dos arquivos .Rmd existentes sem modificação.”\n\nExistem diversas possibilidades de criação com Quarto, especialmente pelo fato de que ele é independente de R, portanto, é possível criar diferentes conteúdos dinâmicos com Python, R, Julia e Observable, por exemplo.\nA base para edição em textos é a linguagem de marcação Markdown e ao trabalharmos com códigos, os chunks continuam sendo o nosso melhor amigo. Quanto às publicações, temos a possibilidade de criar relatórios em diversos formatos (HTML, PDF, por exemplo), apresentações, sites, blogs, livros e outros.\nAssim, hoje apresento a vocês um mini tutorial de como criar o nosso primeiro relatório em HTML com Quarto no RStudio. Para tanto, como o Quarto é independente de R, você precisa configurar o ambiente para explorar da melhor forma possível as infinitas possibilidades que o Quarto oferece.\nAqui vão alguns pontos são importantes:\n\n\n\n\n\n\nPré-requisitos\n\n\n\n\nBaixar e instalar a versão mais recente do Quarto;\nBaixar e instalar a versão mais recente do R. Caso já tenha, verifique se o seu R está atualizado para R 4.1 ou R 4.2;\nBaixar e instalar a versão mais recente do RStudio.\n\nPara mais detalhes, clique aqui.\nOutra opção bem bacana é utilizar o Posit Cloud, que permite você explorar as ferramentas do RStudio na nuvem de maneira simples e sem grandes dificuldades para configurar. Caso você nunca tenha explorado o Posit Cloud, acesse o link aqui e crie uma conta através dos seguintes passos:\n\n\n\n\nPara saber sobre como criar um projeto no Posit Cloud, acesse a demonstração aqui." + "objectID": "como-participar.html#participe-dos-eventos", + "href": "como-participar.html#participe-dos-eventos", + "title": "Como fazer parte da R-Ladies São Paulo?", + "section": "", + "text": "Os eventos realizados pela R-Ladies São Paulo são gratuitos e são divulgados na plataforma Meetup. Se quiser acompanhar os próximos eventos, recomendamos inscrever-se na plataforma Meetup e seguir as nossas redes sociais, principalmente o Instagram." }, { - "objectID": "posts/2023-02-tutorial-quarto/index.html#o-primeiro-passo", - "href": "posts/2023-02-tutorial-quarto/index.html#o-primeiro-passo", - "title": "E aí, vamos falar de Quarto?", - "section": "O primeiro passo", - "text": "O primeiro passo\nAgora, considerando que você já está com o ambiente preparado, vamos colocar a mão na massa!\nSupondo que você está começando do zero no Quarto, o primeiro passo é criar o documento (.qmd) no RStudio. Sugiro fortemente que você crie um projeto antes de tudo. São apenas seis passos simples:\n\n\n\n\nVoilà! Temos o nosso projeto e primeiro documento criados. Este é o modelo básico para publicação em Quarto e o formato de saída será, por padrão, em HTML. Para verificarmos o resultado final precisamos renderizar o nosso arquivo .qmd. Para isso, clique em Render ou utilize o atalho do teclado CTRL + SHIFT + K.\n\n\n\n\nE temos como resultado final:\n\n\n\n\nPerceba que na tela acima eu estou trabalhando com o Visual selecionado (botão localizado na barra de ferramentas), o que permite a visualização das alterações em tempo real e é uma ótima opção para quem ainda não está tão familiarizado(a) com Markdown. Vale a pena conferir as diversas possibilidades de utilização do Visual Editor em um post da Posit intitulado Exploring RStudio’s Visual Markdown Editor, cuja autoria é de Isabella Velásquez.\nCaso você prefira, ao clicar em Source (botão à esquerda do Visual na barra de ferramentas), é possível escrever seu documento no modo de origem ou mesmo ir alternando entre o Source e Visual.\nE aí, o que achou? Chegamos até aqui e você deu os seus primeiros passos com Quarto (uhuul!! 😍)! Agora se liga nessas dicas:\n\n\n\n\n\n\nDicas\n\n\n\n\nSeja curioso(a): aqui eu apresentei uma das diversas formas para criar documentos, projetos, usar o RStudio na nuvem, etc, entretanto, existem outras possibilidades que você pode aprender explorando a documentação;\nSe você já trabalha com R Markdown, possivelmente vai achar muitas semelhanças nas aplicações com o Quarto. Assim, sugiro também explorar a documentação;\nPor fim, uma dica final: explore a documentação 😂😂 e acompanhe as novidades em Quarto.org." + "objectID": "como-participar.html#eventos-anteriores", + "href": "como-participar.html#eventos-anteriores", + "title": "Como fazer parte da R-Ladies São Paulo?", + "section": "Eventos anteriores", + "text": "Eventos anteriores\nAs gravações dos eventos que acontecem online ficam disponíveis no canal do Youtube." }, { - "objectID": "posts/2023-02-tutorial-quarto/index.html#subindo-um-degrau", - "href": "posts/2023-02-tutorial-quarto/index.html#subindo-um-degrau", - "title": "E aí, vamos falar de Quarto?", - "section": "Subindo um degrau", - "text": "Subindo um degrau\nAgora que você já sabe criar um documento com Quarto, vamos explorar algumas ferramentas para incrementar as nossas criações.\nCriei um modelo de relatório .qmd cuja saída é em HTML e está disponível aqui. Assim, vamos desvendar cada etapa de criação juntos.\nPrimeiramente, é importante compreender a estrutura de um documento em Quarto. Veja a representação básica apresentada abaixo:\n\n\n\n\nEssas três partes são:\n\nYAML (Yet Another Markup Language): cabeçalho onde são inseridas as configurações do documento (formatação, data, título, autor, entre outros). É sempre inserido no início do documento e delimitado por ---;\nTexto: usa markdown como sua sintaxe de documento principal;\nCódigos: versão multilíngue, portanto, nos chunks (blocos de códigos) podemos inserir códigos em R, Python, Julia e outros.\n\nAssim, no exemplo que vamos explorar, veja que temos alguns elementos interessantes que foram inseridos.\nNote que no canto superior direito é possível identificar uma chave, em que o(a) leitor(a) pode selecionar o tema desejado, conforme a figura a seguir:\n\n\n\n\n\n\n\n\nObserve na figura acima que o documento possui um título, subtítulo, nome da autora e a data de publicação. Tais informações são configuradas no YAML, onde também foram definidas outras configurações do documento, conforme o código a seguir:\n\n\n\n\n\n\nYAML\n\n\n\n---\ntitle: \"Meu primeiro relatório\" # -----> Título\nsubtitle: \"Exemplo: Relatório em Quarto\" # -----> Subtítulo\nauthor: \"Ariane Hayana\" # -----> Autoria\ndate: \"2023-02-08\" # -----> Data de publicação\ndate-format: short # -----> Formato de data curto: dd/mm/aaaa\nlang: pt # -----> Linguagem: português\nformat: \n html: \n code-fold: true # -----> code-fold: `true` para \"ocultar\" o bloco de códigos\n theme: \n light: [pulse,custom.scss] # Tema modo claro\n dark: [cyborg,custom.scss] # Tema modo escuro\ntitle-block-banner: true # -----> Estilo de banner no topo do documento\nbibliography: references.bib # -----> Referências do documento\n---\n\n\nDeixei alguns comentários sobre as configurações no código, mas alguns pontos cabem atenção especial:\n\ndate-format: neste exemplo, apresentei o formato curto de data, entretanto, existem diversos formatos possíveis que podem ser consultados em Quarto.org;\nlang: esta opção é usada para identificar o idioma principal do documento. Outras idiomas podem ser considerados, como o espanhol (lang: es) e francês (lang: fr), por exemplo;\ncode-fold: quando esta opção é igual a true, o bloco de códigos é ocultado, podendo ser consultado ao clicar na palavra “Código”;\ntheme: light: [pulse,custom.scss] ou dark: [cyborg,custom.scss]: é nesta configuração que definimos qual tema utilizar em nosso documento e quais outras características podemos customizar utilizando um arquivo .scss (veja mais em Quarto.pub);\ntitle-block-banner: true: se igual a true, esta configuração insere um bloco de título no estilo de banner no topo do documento;\nbibliography: aqui estão as referências utilizadas no documento gerado. Trata-se de um arquivo .bib.\n\nApós as configurações do cabeçalho estarem definidas, então vamos para o texto. No modelo, temos uma arte feita pela Allison Horst, que foi inserida no documento com o include_graphics do knitr. Se você é familiarizado(a) com R Markdown, provavelmente vai achar um pouco estranho a configuração dos chunks. Perceba que cada linha é precedida por um #|:\n```{r}\n#| echo: false\n#| out.width: \"100%\"\n#| fig-cap: \"Arte por [Allison Horst.](https://github.com/allisonhorst/stats-illustrations/blob/main/julie-mine-quarto-keynote/quarto_thankyou.png)\"\n\nknitr::include_graphics(\"images/img-1.png\")\n```\nJá na margem direita podemos verificar algumas informações sobre a R-Ladies, que são inseridas no documento Quarto utilizando column-margin. Veja um trecho exemplificativo:\n```{r}\n::: column-margin\n\n#### O que é a R-Ladies?\n\n[R-Ladies](https://rladies.org/) é uma organização mundial cuja missão é promover \na diversidade de gênero na comunidade da linguagem R.\n\n**R-Ladies São Paulo** integra, orgulhosamente, a organização R-Ladies Global,\nem São Paulo.\n\nAs atividades incluem meetups e mentorias em um ambiente seguro e amigável.\n\n:::\n```\nPara exemplificar a utilização de chunks, no modelo temos o conjunto de dados de Gapminder sobre expectativa de vida, PIB per capita e população por país. Neste exemplo foram explorados os pacotes dados (Quiroga et al. 2022), reactable (Lin 2022) e dplyr (Wickham et al. 2022):\n```{r}\n#| warning: false\n#| message: false\n\nlibrary(dados)\nlibrary(reactable)\nlibrary(dplyr)\n\ndados_gapminder |> # Base do pacote {dados}\n select(continente, pais, ano, pib_per_capita) |> # Selecionando algumas colunas\n reactable(\n groupBy = \"continente\", # Agrupando pela coluna 'continente'\n searchable = TRUE, # Inserindo uma busca na tabela\n outlined = TRUE, # Linhas na tabela\n columns = list(ano = colDef(sortable = TRUE)) # Ordem crescente na coluna 'ano'\n )\n```\nComo resultado, temos:\n\n\n\n\n\nParticularmente, gosto bastante do visual elegante que resultam as tabelas com reactable. Na estrutura acima é possível pesquisar informações dentro da própria tabela com o “Search” e ao clicar em cada um dos continentes é possível explorar outras informações.\nJá nas visualizações gráficas, trouxe um exemplo que utiliza dados sobre nomes de bebês do pacote dados (Quiroga et al. 2022), gganimate (Pedersen e Robinson 2020) e ggplot2 (Wickham 2016). Para tanto, utilizei apenas dois nomes para elaborar o gráfico animado com o gganimate. Mais detalhes sobre o pacote podem ser encontrados em um post da Curso-R.\n```{r}\n#| fig-width: 8\n#| fig-height: 5\n#| warning: false\n#| message: false\n\nlibrary(gganimate)\nlibrary(ggplot2)\n\nbebes |>\n filter(nome %in% c(\"Patricia\", \"Helen\")) |> \n ggplot(aes(x = ano, y = n, group = nome, color = nome)) +\n geom_line() +\n geom_point() +\n xlab(\"Ano\") + \n ylab(\"Número de bebês nascidos\") +\n transition_reveal(ano) +\n theme_classic()\n```\nO resultado final será:\n\n\n\n\n\nE assim passamos por todas as etapas:\n\n\n\n\n\nE aí, gostaram? Espero que sim!\nE lembre-se:\n\n“O primeiro passo não te leva onde você quer ir, mas te tira de onde você está.”\n\nDê o primeiro passo, explore a documentação do Quarto.org e pratique! 😉\n\n\n\n\n\n\nMateriais do tutorial:\n\n\n\n\nModelo em HTML: https://a-hayana.github.io/quarto_report_post/quarto_report_post.html\n\nCódigos: https://github.com/a-hayana/quarto_report_post/blob/master/quarto_report_post.qmd\n\nRepositório: https://github.com/a-hayana/quarto_report_post\n\n\n\n\nAté breve!\n Ariane Hayana" + "objectID": "como-participar.html#grupo-no-telegram", + "href": "como-participar.html#grupo-no-telegram", + "title": "Como fazer parte da R-Ladies São Paulo?", + "section": "Grupo no Telegram", + "text": "Grupo no Telegram\nExiste um grupo no telegram da R-Ladies São Paulo! O acesso é apenas para pessoas que fazem parte do público-alvo da R-Ladies: mulheres cis, mulheres trans, homens trans, pessoas não-binárias e queer.\nPortanto, o grupo não é aberto e é necessário solicitar o convite. Caso você faça parte do público-alvo e queira participar do grupo, solicite o convite enviando uma mensagem privada no nosso perfil do Instagram." }, { "objectID": "posts/2023-06-05-increasing-diversity-sao-paulo/english.html", @@ -707,25 +602,60 @@ "text": "Notas de rodapé\n\n\nIBGE: Brazilian Institute of Geography and Statistics. IBGE is a national bureau of statistics that conducts census and is responsible for the collection, storage, and dissemination of socioeconomic data on the Brazilian population, as well as the regulation of the Brazilian territory, including its biomes and physical and geographic aspects, and the relationship of society in its occupation.↩︎\nThe trans people mapping made by the city hall of São Paulo was one of the first in Brazil, but unfortunately, we still do not have this data for the whole country. Source: Center for Contemporary Culture Studies, 2021.↩︎" }, { - "objectID": "posts/2023-10-ws-ghibli/index.html", - "href": "posts/2023-10-ws-ghibli/index.html", - "title": "Raspando a página do Studio Ghibli, na Wikipédia", + "objectID": "posts/2022-12-boas-vindas-ao-blog/index.html", + "href": "posts/2022-12-boas-vindas-ao-blog/index.html", + "title": "Boas vindas ao blog da R-Ladies São Paulo!", "section": "", - "text": "Autoria\n\n\n\n\n\n\n\n\nFoto\n\n \n\nEste post foi escrito por Ornella Scardua Ferreira: .\n“Amo gráficos como amo cavalos. Gosto de música ruim e de cinema (bom). Sou apaixonada pelo Botafogo e pelo Bayern de Munique. Prefiro Vila Velha a qualquer lugar no mundo. Não tenho sonhos, mas um dia espero ver a Palestina livre.”\nFundado em 1985 pelos cineastas japoneses Hayao Miyazaki, Isao Takahata, Toshio Suzuki e Yasuyoshi Tokuma, o Studio Ghibli é um dos estúdios de animação japonesa mais famosos ao redor do mundo.\nAlém de serem reconhecidos pelos traços e cores muito singulares de seus personagens e cenários, os filmes, curtas e comercias do Studio Ghibli são muito aclamados pela crítica e pelo público devido, principalmente, à sensibilidade dos temas que cerceiam suas histórias e a maneira como elas são contadas para nós.\nPor isso tudo, que tal “scrapear” (ou raspar) a página do Studio Ghibli, na Wikipédia a maior enciclopédia colaborativa web do mundo, e coletar os dados de todos os filmes já lançados por esse estúdio de cinema? Scrapers e Ghibli-fãs, uni-vos!\nFigura 1: Imagem da página do Studio Ghibli, no Wikipédia.\nPara quem não conhece os filmes, muitos estão disponíveis na Netflix!" + "text": "A R-Ladies São Paulo é uma comunidade que iniciou em 2018, e desde então buscamos promover a diversidade de gênero na comunidade da linguagem R: organizando eventos presenciais e online, tirando dúvidas no nosso grupo do telegram, disponibilizando os materiais utilizados nos eventos, entre outros.\nCaso queira saber mais, consulte a página Sobre a R-Ladies São Paulo." }, { - "objectID": "posts/2023-10-ws-ghibli/index.html#requisição", - "href": "posts/2023-10-ws-ghibli/index.html#requisição", - "title": "Raspando a página do Studio Ghibli, na Wikipédia", - "section": "Requisição", - "text": "Requisição\nInicialmente, inspecionamos a página do Studio Ghibli na Wikipédia para encontrar os elementos em HTML que estão associados exclusivamente às informações dos filmes (como título, ano de lançamento, duração, diretor, elenco etc). Felizmente, esses dados estão todos resumidos em uma única tabela dentre a única tabela que existe na página (na Seção Filmografia, para ser mais exata) - o que deixou a tarefa de raspagem muito mais fácil, por sinal.\n\n\n\n\nFigura 2: Imagem da inspeção na página do Studio Ghibli, no Wikipédia.\n\n\n\nEm primeiro lugar, vamos coletar somente os dados apresentados nessa tabela. Assim, simulamos a requisição apenas com a URL do site, sem deixar de salvar (com o nome filmes_ghibli.html) a página requerida no diretório output/. Como coletar essa tabela se trata de um scraping muito simples, já no próximo passo é possível ler o elemento HTML cujo parâmetro XPath é igual a //*[@id='mw-content-text']/div[1]/table[3], obtido conforme mostra a Figura 2.\nO código para o processo da requisição e leitura da tabela em HTML pode ser visto a seguir. Obs.: usamos a função xml_find_first() pois, nesse caso, existia uma única tabela.\n\n# URL da página do Wikipédia\n\nu_ghibli <- \"https://pt.wikipedia.org/wiki/Studio_Ghibli\"\n\n# requisicao GET\n\nr_ghibli <- httr::GET(\n u_ghibli, \n httr::write_disk(\"output/filmes_ghibli.html\", overwrite = TRUE) # salvar pagina no disco\n)\n\n# coletando a tabela\n\ntabela_ghibli <- r_ghibli |> \n xml2::read_html() |> # ler arquivo HTML\n xml2::xml_find_first(\"//*[@id='mw-content-text']/div[1]/table[3]\") # parametro XPath\n\nA tabela (ainda em HTML, lembrando) que acabamos de obter só contém as informações mais gerais dos filmes do Studio Ghibli. Mas… e se quisermos montar uma base de dados em que seja possível, por exemplo, analisar sobre a duração, gênero e elenco dos filmes? Bem, para esse fim, vamos continuar utilizando a tabela anterior, que, como podemos observar na Figura 2, está sob a tag <table> e o atributo class='wikitable unsortable'. Percebam, ainda, agora na Figura 3, que os títulos são links (identificados com a tag <a>) que direcionam para as páginas individuais de cada um dos filmes, locais onde estão as informações pelas quais estamos interessados.\n\n\n\n\nFigura 3: Imagem da inspeção dos títulos na tabela da página do Studio Ghibli, no Wikipédia.\n\n\n\nPara extrair esses links, precisamos encontrar todos os links disponíveis na tabela cuja classe é do tipo 'wikitable unsortable'. Logo, lemos a página HTML e coletamos todos os elementos (ou nós) que fazem parte das tags <a> e os atrbiutos do tipo href. Para tal tarefa, construímos o seguinte código:\n\nlinks_filmes <- r_ghibli |> \n xml2::read_html() |> # ler arquivo HTML\n xml2::xml_find_all(\"//table[@class='wikitable unsortable']//a\") |> # coletar todos os nos da tabela dentro das tags <a>\n xml2::xml_attr(\"href\") # coletar atributos href\n\nlinks_filmes\n #> [1] \"/wiki/Tenk%C5%AB_no_Shiro_Rapyuta\" \n #> [2] \"/wiki/Hayao_Miyazaki\" \n #> [3] \"/wiki/Isao_Takahata\" \n #> [4] \"/wiki/Joe_Hisaishi\" \n #> [5] \"/wiki/Hotaru_no_Haka\" \n #> [6] \"/wiki/Isao_Takahata\" \n #> [7] \"/wiki/Tonari_no_Totoro\" \n #> [8] \"/wiki/Majo_no_Takky%C5%ABbin\" \n #> [9] \"/wiki/Omoide_Poro_Poro\" \n #> [10] \"/wiki/Kurenai_no_Buta\" \n #> [11] \"/wiki/Umi_ga_Kikoeru\" \n #> [12] \"/wiki/Heisei_Tanuki_Gassen_Ponpoko\" \n #> [13] \"/wiki/Mimi_wo_Sumaseba\" \n #> [14] \"/wiki/Mononoke_Hime\" \n #> [15] \"/wiki/H%C5%8Dhokekyo_Tonari_no_Yamada-kun\"\n #> [16] \"/wiki/A_Viagem_de_Chihiro\" \n #> [17] \"/wiki/O_Reino_dos_Gatos\" \n #> [18] \"/wiki/Hiroyuki_Morita\" \n #> [19] \"/wiki/Hauru_no_Ugoku_Shiro\" \n #> [20] \"/wiki/Contos_de_Terramar\" \n #> [21] \"/wiki/Goro_Miyazaki\" \n #> [22] \"/wiki/Gake_no_ue_no_Ponyo\" \n #> [23] \"/wiki/Kari-gurashi_no_Arietti\" \n #> [24] \"/wiki/Hiromasa_Yonebayashi\" \n #> [25] \"/wiki/Kokuriko-zaka_Kara\" \n #> [26] \"/wiki/Kaze_Tachinu\" \n #> [27] \"/wiki/O_Conto_da_Princesa_Kaguya\" \n #> [28] \"/wiki/Yoshiaki_Nishimura\" \n #> [29] \"/wiki/Omoide_no_Marnie\" \n #> [30] \"/wiki/%C4%80ya_to_Majo\" \n #> [31] \"/wiki/Kimitachi_wa_Dou_Ikiru_ka\"\n\nNo entanto, os 31 links gerados são da forma /wiki/nome_do_filme, ou seja, inválidos. Validamo-os com o próximo código:\n\nlinks_filmes <- paste0(\"https://pt.wikipedia.org\", links_filmes)\n\nhead(links_filmes)\n #> [1] \"https://pt.wikipedia.org/wiki/Tenk%C5%AB_no_Shiro_Rapyuta\"\n #> [2] \"https://pt.wikipedia.org/wiki/Hayao_Miyazaki\" \n #> [3] \"https://pt.wikipedia.org/wiki/Isao_Takahata\" \n #> [4] \"https://pt.wikipedia.org/wiki/Joe_Hisaishi\" \n #> [5] \"https://pt.wikipedia.org/wiki/Hotaru_no_Haka\" \n #> [6] \"https://pt.wikipedia.org/wiki/Isao_Takahata\"\n\nUma vez corrigidos, podemos fazer a requisição de todas as páginas dos filmes de uma só vez, iterando o processo de tal maneira que algum erro que aconteça em alguma requisição seja identificado.\nA primeira função que vamos criar é a get_links(), cujo papel é simplesmente obter uma requisição da mesma forma que havíamos feito inicialmente.\n\nget_links <- function(links, ids) {\n arquivo <- paste0(\"output/\", ids, \".html\")\n r <- httr::GET(links, write_disk(arquivo, overwrite = TRUE))\n \n arquivo\n}\n\nA segunda função que vamos constuir, a get_progresso(), vai obter as requisições por meio da função get_links() adicionada da informação de erro com o auxílio da função purrr::possibly(). Vejam que, caso aconteça algum problema durante a requisição feita pela get_links(), a seguinte mensagem de erro aparecerá: “ERRO NA REQUISIÇÃO”. A mensagem pode ser escrita de acordo com o gosto do leitor, vale frisar.\nBom, já ao utilizar a função progressr::with_progress(), incluímos uma barra de progresso à iteração. Dois comentários importantes a serem feitos: (1) a função purrr::possibly() permite o andamento da iteração mesmo se houver algum erro no meio do caminho, e se ocorrer algum erro, ela identifica exatamente em qual momento o erro aconteceu; e (2) a barra de progresso serve para o acompanhamento de cada passo da iteração (Figura 4).\n\n# funcao para obter as requisicoes com erro\n\nget_progresso <- function(links, ids, progresso) {\n # progresso\n progresso()\n # mapear erros nas requisicoes\n get_erro <- purrr::possibly(get_links, otherwise = \"ERRO NA REQUISIÇÃO\")\n get_erro(links, ids)\n}\n\n# obtendo as requisicoes com erro e barra de progresso\n\nprogressr::with_progress({\n # barra de progresso\n progresso <- progressr::progressor(length(links_filmes))\n purrr::map2(\n links_filmes, seq_along(links_filmes), \n get_progresso, p = progresso\n )\n})\n #> [[1]]\n #> [1] \"output/1.html\"\n #> \n #> [[2]]\n #> [1] \"output/2.html\"\n #> \n #> [[3]]\n #> [1] \"output/3.html\"\n #> \n #> [[4]]\n #> [1] \"output/4.html\"\n #> \n #> [[5]]\n #> [1] \"output/5.html\"\n #> \n #> [[6]]\n #> [1] \"output/6.html\"\n #> \n #> [[7]]\n #> [1] \"output/7.html\"\n #> \n #> [[8]]\n #> [1] \"output/8.html\"\n #> \n #> [[9]]\n #> [1] \"output/9.html\"\n #> \n #> [[10]]\n #> [1] \"output/10.html\"\n #> \n #> [[11]]\n #> [1] \"output/11.html\"\n #> \n #> [[12]]\n #> [1] \"output/12.html\"\n #> \n #> [[13]]\n #> [1] \"output/13.html\"\n #> \n #> [[14]]\n #> [1] \"output/14.html\"\n #> \n #> [[15]]\n #> [1] \"output/15.html\"\n #> \n #> [[16]]\n #> [1] \"output/16.html\"\n #> \n #> [[17]]\n #> [1] \"output/17.html\"\n #> \n #> [[18]]\n #> [1] \"output/18.html\"\n #> \n #> [[19]]\n #> [1] \"output/19.html\"\n #> \n #> [[20]]\n #> [1] \"output/20.html\"\n #> \n #> [[21]]\n #> [1] \"output/21.html\"\n #> \n #> [[22]]\n #> [1] \"output/22.html\"\n #> \n #> [[23]]\n #> [1] \"output/23.html\"\n #> \n #> [[24]]\n #> [1] \"output/24.html\"\n #> \n #> [[25]]\n #> [1] \"output/25.html\"\n #> \n #> [[26]]\n #> [1] \"output/26.html\"\n #> \n #> [[27]]\n #> [1] \"output/27.html\"\n #> \n #> [[28]]\n #> [1] \"output/28.html\"\n #> \n #> [[29]]\n #> [1] \"output/29.html\"\n #> \n #> [[30]]\n #> [1] \"output/30.html\"\n #> \n #> [[31]]\n #> [1] \"output/31.html\"\n\nNenhum “ERRO NA REQUISIÇÃO”, yes!\nAh, na Figura 4 é possível ter uma ideia de como é uma barra de progresso.\n\n\n\n\nFigura 4: Barra de progresso na prática." + "objectID": "posts/2022-12-boas-vindas-ao-blog/index.html#o-que-é-a-r-ladies-são-paulo", + "href": "posts/2022-12-boas-vindas-ao-blog/index.html#o-que-é-a-r-ladies-são-paulo", + "title": "Boas vindas ao blog da R-Ladies São Paulo!", + "section": "", + "text": "A R-Ladies São Paulo é uma comunidade que iniciou em 2018, e desde então buscamos promover a diversidade de gênero na comunidade da linguagem R: organizando eventos presenciais e online, tirando dúvidas no nosso grupo do telegram, disponibilizando os materiais utilizados nos eventos, entre outros.\nCaso queira saber mais, consulte a página Sobre a R-Ladies São Paulo." }, { - "objectID": "posts/2023-10-ws-ghibli/index.html#parsing", - "href": "posts/2023-10-ws-ghibli/index.html#parsing", - "title": "Raspando a página do Studio Ghibli, na Wikipédia", - "section": "Parsing", - "text": "Parsing\nAo realizar raspagem de dados, a etapa de parsing nada mais é do que processar os dados brutos, que geralmente estão nos formatos .html ou .json, e posteriormente organizá-los de modo que consigamos realizar análises. Em nosso caso, coletamos dados .html tanto no cenário em que queríamos as informações expostas na tabelona da página do Studio Ghibli quanto no cenário em que buscamos as informações dos filmes em cada um dos links direcionáveis dispostos nessa mesma tabela. Em ambas as situações, transformamos os dados para um data frame (ou um tibble) ao fazer uma aplicação simples com a função rvest::html_table().\nNotem que, no segundo cenário, optamos pelo arquivo 5.html. Ele se refere ao filme “O Túmulo de Vagalumes”, o filme do Studio Ghibli preferido desta que vos escreve - mas o processo de parsing para qualquer um dos 31 arquivos gerados é o mesmo, caso seu filme favorito seja outro. Nesse caso, quando aplicamos a função mágica rvest::html_table(), o R retorna uma lista com 8 elementos, pois lembre-se que foram coletados todos os nós das tags <a> e todos os atributos da forma href.\n\n\n\n\nFigura 5: Box da página do Studio Ghibli, no Wikipédia, referente ao elemento [[1]].\n\n\n\nPara esse post, vamos nos limitar ao primeiro elemento ([[1]]), que corresponde ao box à direita na página https://pt.wikipedia.org/wiki/Hotaru_no_Haka (Figura 5), o qual contém informações bastante interessantes para uma análise sucinta do filme.\n\n# primeiro cenario\n\ntabela_ghibli <- tabela_ghibli |> \n rvest::html_table(header = TRUE) # transformar dados HTML em tibble\n\ntabela_ghibli\n #> # A tibble: 23 × 6\n #> Ano Título Diretor `Roteirista(s)` `Produtor(es)` Música\n #> <chr> <chr> <chr> <chr> <chr> <chr> \n #> 1 1986 Tenkū no Shiro Rapyuta Hayao … Hayao Miyazaki Isao Takahata Joe H…\n #> 2 1988 Hotaru no Haka Isao T… Isao Takahata Toru Hara Michi…\n #> 3 1988 Tonari no Totoro Hayao … Hayao Miyazaki Toru Hara Joe H…\n #> 4 1989 Majo no Takkyūbin Hayao … Hayao Miyazaki Hayao Miyazaki Joe H…\n #> 5 1991 Omoide Poro Poro Isao T… Isao Takahata Toshio Suzuki Katsu…\n #> 6 1992 Kurenai no Buta Hayao … Hayao Miyazaki Toshio Suzuki Joe H…\n #> 7 1993 Umi ga Kikoeru Tomomi… Keiko Niwa Toshio Suzuki Shige…\n #> 8 1994 Heisei Tanuki Gassen Pon… Isao T… Isao Takahata Toshio Suzuki Shang…\n #> 9 1995 Mimi wo Sumaseba Yoshif… Hayao Miyazaki Toshio Suzuki Yuji …\n #> 10 1997 Mononoke Hime Hayao … Hayao Miyazaki Toshio Suzuki Joe H…\n #> # ℹ 13 more rows\n\n\n# segundo cenario\n\ntumulo_vagalumes <- xml2::read_html(\"output/5.html\") |> \n rvest::html_table() # transformar dados HTML em tibble\n\ntumulo_vagalumes\n #> [[1]]\n #> # A tibble: 19 × 2\n #> `Hotaru no Haka` `Hotaru no Haka` \n #> <chr> <chr> \n #> 1 .mw-parser-output .noitalic{font-style:normal}火垂るの墓 \".mw-parser-output …\n #> 2 Hotaru no Haka \"Hotaru no Haka\" \n #> 3 No Brasil \"O Túmulo dos Vagal…\n #> 4 Em Portugal \"O Túmulo dos Piril…\n #> 5 Japão1988 •  cor •  89 min \"Japão1988 •  cor •…\n #> 6 Gênero \"drama[4]guerra[5]\" \n #> 7 Direção \"Isao Takahata\" \n #> 8 Produção \"Toru Hara\" \n #> 9 Roteiro \"Isao Takahata\" \n #> 10 Baseado em \"\\\"Hotaru no Haka\\\"…\n #> 11 Elenco \"Tsutomu TatsumiAya…\n #> 12 Música \"Michio Mamiya\" \n #> 13 Cinematografia \"Nobuo Koyama\" \n #> 14 Edição \"Takeshi Seyama\" \n #> 15 Companhia(s) produtora(s) \"Studio Ghibli\" \n #> 16 Distribuição \"Toho\" \n #> 17 Lançamento \"16 de abril de 198…\n #> 18 Idioma \"japonês\" \n #> 19 Receita \"¥ 590 milhões[6]\" \n #> \n #> [[2]]\n #> # A tibble: 20 × 4\n #> X1 X2 X3 X4 \n #> <chr> <chr> <chr> <lgl>\n #> 1 N.º \"Título\" Dura… NA \n #> 2 1. \"\\\"Setsuko to Seita ~ Main Title (節子と清太~メ… 2:57 NA \n #> 3 2. \"\\\"Yake Nohara (焼野原, Yake Nohara?)\\\"\" 6:51 NA \n #> 4 3. \"\\\"Haha no Shi (母の死, Haha no Shi?)\\\"\" 6:34 NA \n #> 5 4. \"\\\"Shoka (初夏, Shoka?)\\\"\" 3:14 NA \n #> 6 5. \"\\\"Ike no Hotori (池のほとり, Ike no Hotori?)\\\"\" 2:21 NA \n #> 7 6. \"\\\"Umi he (海へ, Umi he?)\\\"\" 1:37 NA \n #> 8 7. \"\\\"Namiuchigiwa (波打際, Namiuchigiwa?)\\\"\" 1:37 NA \n #> 9 8. \"\\\"Higasa (日傘, Higasa?)\\\"\" 2:26 NA \n #> 10 9. \"\\\"Sakura no Shita (桜の下, Sakura no Shita?)\\\"\" 1:31 NA \n #> 11 10. \"\\\"Dorobbusu (ドロップス, Dorobbusu?)\\\"\" 2:13 NA \n #> 12 11. \"\\\"Hikkoshi (引越し, Hikkoshi?)\\\"\" 2:17 NA \n #> 13 12. \"\\\"Keimai (兄弟, Keimai?)\\\"\" 2:15 NA \n #> 14 13. \"\\\"Hotaru (ほたる, Hotaru?)\\\"\" 4:12 NA \n #> 15 14. \"\\\"Hotaru no Haka (ほたるの墓, Hotaru no Haka?)\\\"\" 1:46 NA \n #> 16 15. \"\\\"Yuuyake (夕焼け, Yuuyake?)\\\"\" 0:53 NA \n #> 17 16. \"\\\"Shura (修羅, Shura?)\\\"\" 3:08 NA \n #> 18 17. \"\\\"Hika (悲劇, Hika?)\\\"\" 3:12 NA \n #> 19 18. \"\\\"Futari ~ End Title (ふたり~エンドタイトル, Fu… 8:52 NA \n #> 20 Duração total: \"Duração total:\" 58:13 NA \n #> \n #> [[3]]\n #> # A tibble: 3 × 2\n #> Classificação Classificação \n #> <chr> <chr> \n #> 1 Brasil: L[40]/12[34][35]\n #> 2 Japão: G[41] \n #> 3 Portugal: M/12[37] \n #> \n #> [[4]]\n #> # A tibble: 3 × 6\n #> Ano Premiação Categoria `Destinatário(s)` Resultado Ref. \n #> <int> <chr> <chr> <chr> <chr> <chr>\n #> 1 1988 Blue Ribbon Awards Prêmio E… Isao Takahata Venceu [30] \n #> 2 1994 Chicago International Child… Prêmio d… Isao Takahata Venceu [30] \n #> 3 1994 Chicago International Child… Prêmio d… Isao Takahata Venceu [30] \n #> \n #> [[5]]\n #> # A tibble: 4 × 2\n #> X1 X2 \n #> <chr> <chr>\n #> 1 \"Outros projetos Wikimedia também contêm material sobre Hotaru no Haka:\" Outr…\n #> 2 \"\" Cita…\n #> 3 \"\" Cate…\n #> 4 \"\" Base…\n #> \n #> [[6]]\n #> # A tibble: 8 × 9\n #> `vdeStudio Ghibli` `vdeStudio Ghibli` `vdeStudio Ghibli` `` `` `` \n #> <chr> <chr> <chr> <chr> <chr> <chr>\n #> 1 \"Hayao Miyazaki\\nIsao… \"Hayao Miyazaki\\n… \"Hayao Miyazaki\\n… <NA> <NA> <NA>\n #> 2 \"Filmografia\" \"Longas-metragens… \"Longas-metragens\" \"Ten… Curt… \"On …\n #> 3 \"Longas-metragens\" \"Tenkū no Shiro R… <NA> <NA> <NA> <NA>\n #> 4 \"Curtas-metragens\" \"On Your Mark (19… <NA> <NA> <NA> <NA>\n #> 5 \"Coproduções\" \"Shiki-Jitsu (200… <NA> <NA> <NA> <NA>\n #> 6 \"Jogos eletrônicos\" \"Jade Cocoon 2 (2… <NA> <NA> <NA> <NA>\n #> 7 \"Ver também\" \"Ghibli Museum Li… <NA> <NA> <NA> <NA>\n #> 8 \".mw-parser-output .s… \".mw-parser-outpu… \".mw-parser-outpu… <NA> <NA> <NA>\n #> # ℹ 3 more variables: `` <chr>, `` <chr>, `` <chr>\n #> \n #> [[7]]\n #> # A tibble: 3 × 2\n #> X1 X2 \n #> <chr> <chr> \n #> 1 Longas-metragens \"Tenkū no Shiro Rapyuta (1986)\\nHotaru no Haka (1988)\\nTonar…\n #> 2 Curtas-metragens \"On Your Mark (1995)\\nGiburīzu (2000)\\nFirumu Guru Guru (200…\n #> 3 Coproduções \"Shiki-Jitsu (2000)\\nInosensu: Kôkaku kidôtai (2004)\\nLa Tor…\n #> \n #> [[8]]\n #> # A tibble: 1 × 2\n #> X1 X2 \n #> <chr> <chr> \n #> 1 Controle de autoridade \": Q274520\\n WorldCat\\nVIAF: 316752206\\nANN (animé): 1…" + "objectID": "posts/2022-12-boas-vindas-ao-blog/index.html#por-que-um-blog", + "href": "posts/2022-12-boas-vindas-ao-blog/index.html#por-que-um-blog", + "title": "Boas vindas ao blog da R-Ladies São Paulo!", + "section": "Por que um blog?", + "text": "Por que um blog?\nTer um site/blog é uma forma de facilitar a divulgar o conteúdo que produzimos, além de ser uma forma de incentivar as pessoas da comunidade a compartilharem seus conhecimentos por aqui também! Essa é uma vontade que as pessoas da comunidade expressaram algumas vezes no passado: já discutimos anteriormente sobre criar um blog das R-Ladies na América Latina (R-Ladies LATAM) e a ideia foi liderada pela Bruna Wundervald, uma das co-organizadoras da R-Ladies São Paulo na época (em janeiro de 2019); em junho de 2021 a ideia voltou para criar um blog para a comunidade em São Paulo, mas infelizmente nenhuma dessas versões chegou a ser utilizada e divulgada.\nA volta dos eventos presenciais (em novembro de 2022) foi um impulso para voltar a trabalhar na criação de um blog para a comunidade!" + }, + { + "objectID": "posts/2022-12-boas-vindas-ao-blog/index.html#posso-contribuir-com-o-blog", + "href": "posts/2022-12-boas-vindas-ao-blog/index.html#posso-contribuir-com-o-blog", + "title": "Boas vindas ao blog da R-Ladies São Paulo!", + "section": "Posso contribuir com o blog?", + "text": "Posso contribuir com o blog?\nSim! Começamos a preparar uma página com informações para pessoas que queiram enviar seus textos por aqui: Como contribuir com o blog?. Também é possível contribuir sugerindo novos conteúdos, avisando caso tenha alguma informação desatualizada, entre outros." + }, + { + "objectID": "posts/2022-12-boas-vindas-ao-blog/index.html#inscreva-se-para-receber-novidades", + "href": "posts/2022-12-boas-vindas-ao-blog/index.html#inscreva-se-para-receber-novidades", + "title": "Boas vindas ao blog da R-Ladies São Paulo!", + "section": "Inscreva-se para receber novidades", + "text": "Inscreva-se para receber novidades\nNeste blog, existe um formulário simples para inscrição do seu email, caso queira receber as novidades! O formulário se encontra na coluna à direita do texto principal, e se parece com a imagem a seguir:" + }, + { + "objectID": "posts/2022-12-boas-vindas-ao-blog/index.html#o-que-esperar", + "href": "posts/2022-12-boas-vindas-ao-blog/index.html#o-que-esperar", + "title": "Boas vindas ao blog da R-Ladies São Paulo!", + "section": "O que esperar?", + "text": "O que esperar?\nA ideia é que este seja um espaço onde as pessoas da comunidade R-Ladies possam publicar textos relacionados à atuação da comunidade, programação em R, ciência de dados e muito mais.\n\n\n\nArte por Allison Horst.\n\n\nEsperamos que seja um lugar rico de troca e compartilhamento! Até logo!" + }, + { + "objectID": "posts/2023-06-rita-com-r/index.html", + "href": "posts/2023-06-rita-com-r/index.html", + "title": "Rita com R", + "section": "", + "text": "No dia 8 de maio o mundo da música ficou mais careta: Rita Lee, a rainha do rock brasileiro, padroeira da liberdade, a santa rita de sampa, nos deixou, mas não sem antes deixar um grande legado de obras, letras, frases.\nO intuito desse artigo é homenagear Rita Lee a partir de uma análise de sua obra usando R. Das R-Ladies de São Paulo para a mais icônica “Mina de Sampa”." + }, + { + "objectID": "posts/2023-06-rita-com-r/index.html#esse-tal-de-r", + "href": "posts/2023-06-rita-com-r/index.html#esse-tal-de-r", + "title": "Rita com R", + "section": "1.1. Esse tal de R", + "text": "1.1. Esse tal de R\nPara começar, é preciso carregar alguns pacotes:\n\nlibrary(tidyverse)\nlibrary(spotifyr)\nlibrary(highcharter)\nlibrary(ggridges)\nlibrary(DT)\n\n\ngerar_tabela <- function(tbl) {\n # knitr::kable(\n # tbl\n # )\n gt::gt(tbl)\n}\n\n\nPrimeiro, devemos configurar os dados da API do Spotify. Aqui tem um tutorialzinho explicando como obter seu Client ID e o token de acesso. No blog da Curso-R também mostra como criar seus tokens de acesso na API do Spotify (com o pacote Rspotify, que é diferente do que vamos usar aqui, mas o início é o mesmo!).\nCom o ambiente configurado, podemos requisitar as características de áudio das faixas qualquer artista presente na plataforma! Isso é feito com a função get_artist_audio_features do pacote spotifyR.\nNessa análise, vamos coletar os atributos das faixas da Rita Lee e analisar alguns deles.\n\nrita_features <- read_csv(\"data-raw/rita_features.csv\")\nglimpse(rita_features)\n\nRows: 411\nColumns: 39\n$ artist_name <chr> \"Rita Lee\", \"Rita Lee\", \"Rita Lee\", \"Rita…\n$ artist_id <chr> \"7dnT2FUXhjirperXaH22IJ\", \"7dnT2FUXhjirpe…\n$ album_id <chr> \"0rZu9DYrrdzdOUQ7Nm2QB8\", \"0rZu9DYrrdzdOU…\n$ album_type <chr> \"album\", \"album\", \"album\", \"album\", \"albu…\n$ album_images <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…\n$ album_release_date <chr> \"2021-06-25\", \"2021-06-25\", \"2021-06-25\",…\n$ album_release_year <dbl> 2021, 2021, 2021, 2021, 2021, 2021, 2021,…\n$ album_release_date_precision <chr> \"day\", \"day\", \"day\", \"day\", \"day\", \"day\",…\n$ danceability <dbl> 0.735, 0.802, 0.755, 0.821, 0.852, 0.656,…\n$ energy <dbl> 0.513, 0.638, 0.712, 0.769, 0.715, 0.734,…\n$ key <dbl> 2, 2, 5, 9, 0, 4, 2, 2, 5, 0, 0, 2, 6, 11…\n$ loudness <dbl> -9.369, -7.968, -7.696, -9.791, -8.402, -…\n$ mode <dbl> 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 0,…\n$ speechiness <dbl> 0.0299, 0.0319, 0.0397, 0.0707, 0.0427, 0…\n$ acousticness <dbl> 0.031100, 0.005490, 0.000466, 0.001490, 0…\n$ instrumentalness <dbl> 0.414000, 0.023400, 0.258000, 0.726000, 0…\n$ liveness <dbl> 0.1160, 0.2160, 0.2210, 0.0469, 0.0426, 0…\n$ valence <dbl> 0.5470, 0.6850, 0.8350, 0.4380, 0.6770, 0…\n$ tempo <dbl> 119.978, 127.982, 127.986, 125.000, 123.0…\n$ track_id <chr> \"4CFOKrbwh1FuR5xBvOWG2R\", \"1VM1W9cMkrHmrX…\n$ analysis_url <chr> \"https://api.spotify.com/v1/audio-analysi…\n$ time_signature <dbl> 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,…\n$ artists <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…\n$ available_markets <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…\n$ disc_number <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…\n$ duration_ms <dbl> 356886, 216585, 369843, 524638, 320488, 2…\n$ explicit <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,…\n$ track_href <chr> \"https://api.spotify.com/v1/tracks/4CFOKr…\n$ is_local <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,…\n$ track_name <chr> \"Só De Você - Coppola Remix\", \"Pega Rapaz…\n$ track_preview_url <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…\n$ track_number <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13…\n$ type <chr> \"track\", \"track\", \"track\", \"track\", \"trac…\n$ track_uri <chr> \"spotify:track:4CFOKrbwh1FuR5xBvOWG2R\", \"…\n$ external_urls.spotify <chr> \"https://open.spotify.com/track/4CFOKrbwh…\n$ album_name <chr> \"Rita Lee & Roberto - Classix Remix Vol. …\n$ key_name <chr> \"D\", \"D\", \"F\", \"A\", \"C\", \"E\", \"D\", \"D\", \"…\n$ mode_name <chr> \"major\", \"major\", \"major\", \"major\", \"majo…\n$ key_mode <chr> \"D major\", \"D major\", \"F major\", \"A major…\n\n\n\nAqui já conseguimos ver que o dataframe resultante dessa requisição tem 39 colunas e 411 linhas, que correspondem a cada faixa da cantora. Há uma coluna com o formato errado, a album_release_date, que é a data de lançamento do álbum (não usaremos esse atributo na análise, mas é bom saber :D)\n\n\n\n\n\n\nImportante\n\n\n\nAlguns álbuns são homônimos (ou seja, têm o mesmo nome), são coletâneas e/ou remixes. Tem que considerar isso na análise!\n\n\n\nQuantas faixas cada álbum tem? Há algumas maneiras de fazer isso, mas vou utilizar o “GSA” (as funções group_by,summarise e arrange do pacote dplyr):\n\nrita_features |>\n group_by(album_name, album_release_year) |>\n summarise(faixas = n()) |>\n arrange(desc(faixas)) |>\n gerar_tabela()\n\n\n\n\n\nQuantidade de faixas por álbum \n\nalbum_release_year\nfaixas\n\n\n\nEm Bossa 'N Roll (Edição Comemorativa - 25 Anos) - Ao Vivo\n\n\n1991\n21\n\n\nAcustico (Live)\n\n\n1998\n18\n\n\nLanca Perfume E Outras Manias\n\n\n1998\n18\n\n\nRita Lee Em Bossa 'N Roll (Ao Vivo)\n\n\n1991\n18\n\n\nRita Lee & Roberto - Classix Remix Vol. III\n\n\n2021\n17\n\n\nRita Lee\n\n\n1979\n16\n\n\n1993\n13\n\n\n1980\n8\n\n\nRita Releeda\n\n\n2000\n16\n\n\nAo Vivo\n\n\n2004\n14\n\n\nAqui, Ali, Em Qualquer Lugar\n\n\n2006\n14\n\n\nMultishow Ao Vivo\n\n\n2009\n14\n\n\nReza\n\n\n2012\n14\n\n\nBombom\n\n\n1983\n13\n\n\nPérolas\n\n\n2016\n13\n\n\nRita Lee & Roberto - Classix Remix Vol. II\n\n\n2021\n13\n\n\nBalacobaco\n\n\n2003\n12\n\n\nRita Lee & Roberto – Classix Remix Vol. l\n\n\n2021\n12\n\n\nRita Lee 3001\n\n\n2000\n12\n\n\nSanta Rita De Sampa\n\n\n1997\n12\n\n\nBuild Up\n\n\n1970\n11\n\n\nRefestança (Ao Vivo)\n\n\n1977\n11\n\n\nAtrás Do Porto Tem Uma Cidade\n\n\n1974\n10\n\n\nFlerte Fatal\n\n\n1987\n10\n\n\nHoje É O Primeiro Dia Do Resto Da Sua Vida\n\n\n1972\n10\n\n\nRita Lee E Roberto De Carvalho\n\n\n1990\n10\n\n\nBabilônia\n\n\n1978\n9\n\n\nEntradas E Bandeiras\n\n\n1976\n9\n\n\nFlagra\n\n\n1982\n9\n\n\nFruto Proibido\n\n\n1975\n9\n\n\nRita E Roberto\n\n\n1985\n9\n\n\nSaúde\n\n\n1981\n8\n\n\nZona Zen\n\n\n1988\n8" }, { "objectID": "posts/2020-06-rladies-global-blm/index.html", @@ -756,38 +686,129 @@ "text": "Declaração de encerramento\nNós trabalharemos mais para ouvir e amplificar as vozes de pessoas percententes a grupos minoritários de nossas respectivas comunidades em todo o mundo. Estamos engajadas no trabalho contínuo de romper sistemas injustos e em abrir espaço para que aquelas pessoas que atualmente sofrem nesses sistemas participem plenamente, e ocupem posições de liderança. Pedimos a todas as pessoas da comunidade R que façam o mesmo.\nTime principal da R Forwards: Heather Turner, Noa Tamir, Tatjana Kecojevic, Emily Dodwell, Kevin O’Brien, Julie Josse.\nR-Ladies Global: Claudia Vitolo, Erin LeDell, Hannah Frick, Laura Ación, Athanasia Monika Mowinckel, Yanina Bellini Saibene, Noa Tamir, Maëlle Salmon, Jennifer Thompson, Florencia D’Andrea, Patricia A. Loto, Saranjeet Kaur Bhogal, Christin Zasada, Nadejda Sero, Sheila Saia.\nPessoas organizadoras de capítulos R-Ladies (atuais e anteriores) com outras fortemente envolvidas nas comunidades R-Ladies e R: gwynn sturdevant, Paola Corrales, Paloma Rojas-Saunero, Riva Quiroga, Roxana Noelia Villafañe, Monica L. Alonso, Danielle Navarro, Mine Çetinkaya-Rundel, Sara Mortara, Genelle Denzin, Divya Seernani, Elisa Schneider, Kyla McConnel, Ana Laura Diedrichs, Liza Dosso, Mariel Lovatto, María Nanton, Ludmila Janda, Hazel Kavili, Ines Teacã, Lucía Rodríguez Planes, Andrea Sánchez-Tapia, Disha Patil, Ayanthi Gunawardana, Jan Strappa, Kaelen Medeiros, Vebashini Naidoo, Emily Dodwell, Julia Silge, Marcela Alfaro, Jenny Bryan, Lucy D’Agostino McGowan, Alison Hill, Andrea Gómez Vargas, Angela Li, Beatriz Milz, Haydee Svab, Tijana Blagojev, Katarina Kosmina, Jovana Savic.\n\nTradução por Beatriz Milz, revisão por Haydee Svab, Monique Freitas e Regina Albanese." }, { - "objectID": "posts/2023-05-open-data-day-educacao/index.html", - "href": "posts/2023-05-open-data-day-educacao/index.html", - "title": "Dados abertos de Educação: um exemplo aplicado ao jornalismo", + "objectID": "posts/2023-02-tutorial-quarto/index.html", + "href": "posts/2023-02-tutorial-quarto/index.html", + "title": "E aí, vamos falar de Quarto?", "section": "", - "text": "Este post é um relato realizado a partir da atividade de um dos grupos participantes do evento “Análise de dados abertos com R”, vinculado ao Open Data Day. Este grupo trabalhou com dados abertos educacionais.\nA monitora do grupo foi Ana Carolina Moreno, jornalista e produtora de dados da TV Globo. Especializada há mais de dez anos na cobertura de dados educacionais, ela apresentou ao grupo um código em R de análise de dados do Censo da Educação Básica usado para a produção de uma série de reportagens especiais sobre o impacto da pandemia na educação infantil, que foi ao ar em novembro de 2022.  Os dados utilizados podem ser obtidosno site do Inep.\nSeis pessoas se interessaram por explorar dados abertos educacionais: Aline Durans, Cristiane Lacerda, Hayane Sena De Jesus, Katia Mine, Larissa Souza, e Natasha Meneguelli. Além disso, Geovana Lopes, do R-Ladies São Paulo, participou como monitora.\nPrimeiramente, foi feita uma introdução mostrando quais são e onde encontrar os dados abertos educacionais, além das mudanças recentes, com a retirada de bases de dados que antes eram públicas, com a justificativa de adequação à Lei Geral de Proteção de Dados (LGPD). A apresentação utilizada está disponível neste link.\n\n\n\n\nAntes de partirmos para a análise de fato dos dados, o código que gerou as tabelas foi apresentado ao grupo. Como parte das pessoas ainda tinha um contato inicial com o R e o RStudio, e como houve interesse em entender o código apresentado, acabamos priorizando uma explicação introdutória da linguagem de programação R.\nAcompanhamos as participantes desde a instalação das aplicações e o primeiro olhar geral sobre o que é a linguagem e como ela é bastante adequada para pessoas que querem fazer análise estatística em cima de bases de dados já existentes.\n\n# As funções descritas abaixo fazem parte do \n# pacote tidyverse!\n# Clique no nome da função para ler a sua documentação.\nlibrary(tidyverse)\n\nO código já escrito (link) serviu de base para mostrar às participantes algumas funções (read_csv(), write_csv(), select(), filter(), rename(), mutate(), left_join(), reduce() e case_when()), além de explicações sobre a sintaxe básica do R, como quando usar os parênteses, e os diferentes operadores: o de atribuição, o pipe e os operações lógicos para fazer filtros ou manipular valores nas colunas.\nDada a escassez de tempo, esse grupo não chegou a ver todo o código, até a geração de gráficos e a análise de fato dos dados. Mas as participantes consideraram que as explicações introdutórias sobre R foram mais produtivas para ajudá-las a dar o primeiro passo no aprendizado da linguagem.\nFinalmente, destaca-se que, apesar de os dados do Inep serem bem organizados, eles não estão isentos de obstáculos e dificuldades de análises. Para evitar incorrer em conclusões equivocadas, a dica é consultar técnicos e especialistas dos bancos de dados para checar possíveis erros de interpretação e até direcionamentos, no caso de obstáculos do processo analítico. Essas pessoas também conseguem explicar até que ponto as bases de dados disponíveis conseguem responder às perguntas que temos.\nPara finalizar este post, deixamos um relato de uma das pessoas participantes sobre a experiência da atividade:\n\nParticipar deste grupo foi uma experiência de aprendizagem incrível. Carol é uma excelente tradutora da linguagem R. Nos fez entender, acompanhar a lógica e ver que sim: é possível aprender R! Para além disto, é necessário e importante termos contato e analisar os dados abertos. Desde então duas reflexões rodeiam meus pensamentos: primeira, não é só desenvolver uma habilidade, trabalhar com dados exige responsabilidade com a transparência das informações. Segunda: Mais pessoas precisam ter contato com o R. A comunidade R Ladies é acolhedora, respeitadora e muito responsável com o processo de transferência de conhecimento. Foi um dia de muita aprendizagem, acolhida e entusiasmo!\n\nPara pessoas que tem interesse em saber mais sobre dados abertos educacionais, indicamos este vídeo:\n\n\n\n\nAté a próxima!" + "text": "Autoria\n\n\n\n\n\n\n\n\nAriane Hayana\n\n \n\nEste post foi escrito pela Ariane Hayana, uma integrante da comunidade R-Ladies São Paulo! Criadora da página @ _estatistica, é graduada em Economia e finalista em sua segunda graduação no curso de Bacharelado em Estatística na Universidade Federal do Amazonas (UFAM), atuando como estagiária no Supremo Tribunal Federal (STF).\nSaiba mais sobre ela em seu LinkedIn." }, { - "objectID": "como-participar.html", - "href": "como-participar.html", - "title": "Como fazer parte da R-Ladies São Paulo?", + "objectID": "posts/2023-02-tutorial-quarto/index.html#e-aí-vamos-falar-de-quarto", + "href": "posts/2023-02-tutorial-quarto/index.html#e-aí-vamos-falar-de-quarto", + "title": "E aí, vamos falar de Quarto?", + "section": "E aí, vamos falar de Quarto?", + "text": "E aí, vamos falar de Quarto?\n\n\nArte de pinguins abraçados feita por Allison Horst: Artwork from “Hello, Quarto” keynote by Julia Lowndes and Mine Çetinkaya-Rundel, presented at RStudio Conference 2022. Illustrated by Allison Horst.\n\nHello, world!\nVocê que gosta da nossa querida linguagem R provavelmente já deve ter ouvido falar sobre Quarto. Por definição, segundo Quarto.org,\n\n“Quarto é uma versão multilíngue da próxima geração do R Markdown (do RStudio) e inclui dezenas de novos recursos, ao mesmo tempo em que é capaz de renderizar a maioria dos arquivos .Rmd existentes sem modificação.”\n\nExistem diversas possibilidades de criação com Quarto, especialmente pelo fato de que ele é independente de R, portanto, é possível criar diferentes conteúdos dinâmicos com Python, R, Julia e Observable, por exemplo.\nA base para edição em textos é a linguagem de marcação Markdown e ao trabalharmos com códigos, os chunks continuam sendo o nosso melhor amigo. Quanto às publicações, temos a possibilidade de criar relatórios em diversos formatos (HTML, PDF, por exemplo), apresentações, sites, blogs, livros e outros.\nAssim, hoje apresento a vocês um mini tutorial de como criar o nosso primeiro relatório em HTML com Quarto no RStudio. Para tanto, como o Quarto é independente de R, você precisa configurar o ambiente para explorar da melhor forma possível as infinitas possibilidades que o Quarto oferece.\nAqui vão alguns pontos são importantes:\n\n\n\n\n\n\nPré-requisitos\n\n\n\n\nBaixar e instalar a versão mais recente do Quarto;\nBaixar e instalar a versão mais recente do R. Caso já tenha, verifique se o seu R está atualizado para R 4.1 ou R 4.2;\nBaixar e instalar a versão mais recente do RStudio.\n\nPara mais detalhes, clique aqui.\nOutra opção bem bacana é utilizar o Posit Cloud, que permite você explorar as ferramentas do RStudio na nuvem de maneira simples e sem grandes dificuldades para configurar. Caso você nunca tenha explorado o Posit Cloud, acesse o link aqui e crie uma conta através dos seguintes passos:\n\n\n\n\nPara saber sobre como criar um projeto no Posit Cloud, acesse a demonstração aqui." + }, + { + "objectID": "posts/2023-02-tutorial-quarto/index.html#o-primeiro-passo", + "href": "posts/2023-02-tutorial-quarto/index.html#o-primeiro-passo", + "title": "E aí, vamos falar de Quarto?", + "section": "O primeiro passo", + "text": "O primeiro passo\nAgora, considerando que você já está com o ambiente preparado, vamos colocar a mão na massa!\nSupondo que você está começando do zero no Quarto, o primeiro passo é criar o documento (.qmd) no RStudio. Sugiro fortemente que você crie um projeto antes de tudo. São apenas seis passos simples:\n\n\n\n\nVoilà! Temos o nosso projeto e primeiro documento criados. Este é o modelo básico para publicação em Quarto e o formato de saída será, por padrão, em HTML. Para verificarmos o resultado final precisamos renderizar o nosso arquivo .qmd. Para isso, clique em Render ou utilize o atalho do teclado CTRL + SHIFT + K.\n\n\n\n\nE temos como resultado final:\n\n\n\n\nPerceba que na tela acima eu estou trabalhando com o Visual selecionado (botão localizado na barra de ferramentas), o que permite a visualização das alterações em tempo real e é uma ótima opção para quem ainda não está tão familiarizado(a) com Markdown. Vale a pena conferir as diversas possibilidades de utilização do Visual Editor em um post da Posit intitulado Exploring RStudio’s Visual Markdown Editor, cuja autoria é de Isabella Velásquez.\nCaso você prefira, ao clicar em Source (botão à esquerda do Visual na barra de ferramentas), é possível escrever seu documento no modo de origem ou mesmo ir alternando entre o Source e Visual.\nE aí, o que achou? Chegamos até aqui e você deu os seus primeiros passos com Quarto (uhuul!! 😍)! Agora se liga nessas dicas:\n\n\n\n\n\n\nDicas\n\n\n\n\nSeja curioso(a): aqui eu apresentei uma das diversas formas para criar documentos, projetos, usar o RStudio na nuvem, etc, entretanto, existem outras possibilidades que você pode aprender explorando a documentação;\nSe você já trabalha com R Markdown, possivelmente vai achar muitas semelhanças nas aplicações com o Quarto. Assim, sugiro também explorar a documentação;\nPor fim, uma dica final: explore a documentação 😂😂 e acompanhe as novidades em Quarto.org." + }, + { + "objectID": "posts/2023-02-tutorial-quarto/index.html#subindo-um-degrau", + "href": "posts/2023-02-tutorial-quarto/index.html#subindo-um-degrau", + "title": "E aí, vamos falar de Quarto?", + "section": "Subindo um degrau", + "text": "Subindo um degrau\nAgora que você já sabe criar um documento com Quarto, vamos explorar algumas ferramentas para incrementar as nossas criações.\nCriei um modelo de relatório .qmd cuja saída é em HTML e está disponível aqui. Assim, vamos desvendar cada etapa de criação juntos.\nPrimeiramente, é importante compreender a estrutura de um documento em Quarto. Veja a representação básica apresentada abaixo:\n\n\n\n\nEssas três partes são:\n\nYAML (Yet Another Markup Language): cabeçalho onde são inseridas as configurações do documento (formatação, data, título, autor, entre outros). É sempre inserido no início do documento e delimitado por ---;\nTexto: usa markdown como sua sintaxe de documento principal;\nCódigos: versão multilíngue, portanto, nos chunks (blocos de códigos) podemos inserir códigos em R, Python, Julia e outros.\n\nAssim, no exemplo que vamos explorar, veja que temos alguns elementos interessantes que foram inseridos.\nNote que no canto superior direito é possível identificar uma chave, em que o(a) leitor(a) pode selecionar o tema desejado, conforme a figura a seguir:\n\n\n\n\n\n\n\n\nObserve na figura acima que o documento possui um título, subtítulo, nome da autora e a data de publicação. Tais informações são configuradas no YAML, onde também foram definidas outras configurações do documento, conforme o código a seguir:\n\n\n\n\n\n\nYAML\n\n\n\n---\ntitle: \"Meu primeiro relatório\" # -----> Título\nsubtitle: \"Exemplo: Relatório em Quarto\" # -----> Subtítulo\nauthor: \"Ariane Hayana\" # -----> Autoria\ndate: \"2023-02-08\" # -----> Data de publicação\ndate-format: short # -----> Formato de data curto: dd/mm/aaaa\nlang: pt # -----> Linguagem: português\nformat: \n html: \n code-fold: true # -----> code-fold: `true` para \"ocultar\" o bloco de códigos\n theme: \n light: [pulse,custom.scss] # Tema modo claro\n dark: [cyborg,custom.scss] # Tema modo escuro\ntitle-block-banner: true # -----> Estilo de banner no topo do documento\nbibliography: references.bib # -----> Referências do documento\n---\n\n\nDeixei alguns comentários sobre as configurações no código, mas alguns pontos cabem atenção especial:\n\ndate-format: neste exemplo, apresentei o formato curto de data, entretanto, existem diversos formatos possíveis que podem ser consultados em Quarto.org;\nlang: esta opção é usada para identificar o idioma principal do documento. Outras idiomas podem ser considerados, como o espanhol (lang: es) e francês (lang: fr), por exemplo;\ncode-fold: quando esta opção é igual a true, o bloco de códigos é ocultado, podendo ser consultado ao clicar na palavra “Código”;\ntheme: light: [pulse,custom.scss] ou dark: [cyborg,custom.scss]: é nesta configuração que definimos qual tema utilizar em nosso documento e quais outras características podemos customizar utilizando um arquivo .scss (veja mais em Quarto.pub);\ntitle-block-banner: true: se igual a true, esta configuração insere um bloco de título no estilo de banner no topo do documento;\nbibliography: aqui estão as referências utilizadas no documento gerado. Trata-se de um arquivo .bib.\n\nApós as configurações do cabeçalho estarem definidas, então vamos para o texto. No modelo, temos uma arte feita pela Allison Horst, que foi inserida no documento com o include_graphics do knitr. Se você é familiarizado(a) com R Markdown, provavelmente vai achar um pouco estranho a configuração dos chunks. Perceba que cada linha é precedida por um #|:\n```{r}\n#| echo: false\n#| out.width: \"100%\"\n#| fig-cap: \"Arte por [Allison Horst.](https://github.com/allisonhorst/stats-illustrations/blob/main/julie-mine-quarto-keynote/quarto_thankyou.png)\"\n\nknitr::include_graphics(\"images/img-1.png\")\n```\nJá na margem direita podemos verificar algumas informações sobre a R-Ladies, que são inseridas no documento Quarto utilizando column-margin. Veja um trecho exemplificativo:\n```{r}\n::: column-margin\n\n#### O que é a R-Ladies?\n\n[R-Ladies](https://rladies.org/) é uma organização mundial cuja missão é promover \na diversidade de gênero na comunidade da linguagem R.\n\n**R-Ladies São Paulo** integra, orgulhosamente, a organização R-Ladies Global,\nem São Paulo.\n\nAs atividades incluem meetups e mentorias em um ambiente seguro e amigável.\n\n:::\n```\nPara exemplificar a utilização de chunks, no modelo temos o conjunto de dados de Gapminder sobre expectativa de vida, PIB per capita e população por país. Neste exemplo foram explorados os pacotes dados (Quiroga et al. 2022), reactable (Lin 2022) e dplyr (Wickham et al. 2022):\n```{r}\n#| warning: false\n#| message: false\n\nlibrary(dados)\nlibrary(reactable)\nlibrary(dplyr)\n\ndados_gapminder |> # Base do pacote {dados}\n select(continente, pais, ano, pib_per_capita) |> # Selecionando algumas colunas\n reactable(\n groupBy = \"continente\", # Agrupando pela coluna 'continente'\n searchable = TRUE, # Inserindo uma busca na tabela\n outlined = TRUE, # Linhas na tabela\n columns = list(ano = colDef(sortable = TRUE)) # Ordem crescente na coluna 'ano'\n )\n```\nComo resultado, temos:\n\n\n\n\n\nParticularmente, gosto bastante do visual elegante que resultam as tabelas com reactable. Na estrutura acima é possível pesquisar informações dentro da própria tabela com o “Search” e ao clicar em cada um dos continentes é possível explorar outras informações.\nJá nas visualizações gráficas, trouxe um exemplo que utiliza dados sobre nomes de bebês do pacote dados (Quiroga et al. 2022), gganimate (Pedersen e Robinson 2020) e ggplot2 (Wickham 2016). Para tanto, utilizei apenas dois nomes para elaborar o gráfico animado com o gganimate. Mais detalhes sobre o pacote podem ser encontrados em um post da Curso-R.\n```{r}\n#| fig-width: 8\n#| fig-height: 5\n#| warning: false\n#| message: false\n\nlibrary(gganimate)\nlibrary(ggplot2)\n\nbebes |>\n filter(nome %in% c(\"Patricia\", \"Helen\")) |> \n ggplot(aes(x = ano, y = n, group = nome, color = nome)) +\n geom_line() +\n geom_point() +\n xlab(\"Ano\") + \n ylab(\"Número de bebês nascidos\") +\n transition_reveal(ano) +\n theme_classic()\n```\nO resultado final será:\n\n\n\n\n\nE assim passamos por todas as etapas:\n\n\n\n\n\nE aí, gostaram? Espero que sim!\nE lembre-se:\n\n“O primeiro passo não te leva onde você quer ir, mas te tira de onde você está.”\n\nDê o primeiro passo, explore a documentação do Quarto.org e pratique! 😉\n\n\n\n\n\n\nMateriais do tutorial:\n\n\n\n\nModelo em HTML: https://a-hayana.github.io/quarto_report_post/quarto_report_post.html\n\nCódigos: https://github.com/a-hayana/quarto_report_post/blob/master/quarto_report_post.qmd\n\nRepositório: https://github.com/a-hayana/quarto_report_post\n\n\n\n\nAté breve!\n Ariane Hayana" + }, + { + "objectID": "posts/2023-03-evento-open-data-day/index.html", + "href": "posts/2023-03-evento-open-data-day/index.html", + "title": "Evento: Análise de dados abertos com R", "section": "", - "text": "Os eventos realizados pela R-Ladies São Paulo são gratuitos e são divulgados na plataforma Meetup. Se quiser acompanhar os próximos eventos, recomendamos inscrever-se na plataforma Meetup e seguir as nossas redes sociais, principalmente o Instagram." + "text": "A R-Ladies São Paulo organizou, em 18 de março de 2023, o evento “Análise de Dados Abertos com R - Open Data Day”. A atividade aconteceu em um sábado, durante os períodos da manhã e da tarde, totalizando 6 horas efetivas de atividade.\nO Insper, uma instituição sem fins lucrativos dedicada ao ensino e à pesquisa, mais uma vez apoiou o grupo cedendo o espaço para a realização do evento. Outro apoio recebido foi da Curso-R, que cedeu dois monitores para auxiliar na monitoria, ajudando nas dúvidas. O principal objetivo deste encontro foi oferecer informações a respeito do que são e da importância dos dados abertos e promover oportunidade de pôr a “mão-na-massa” manipulando dados abertos, além de traçar o cenário atual de acesso a esses dados em vários níveis governamentais e áreas do conhecimento." }, { - "objectID": "como-participar.html#participe-dos-eventos", - "href": "como-participar.html#participe-dos-eventos", - "title": "Como fazer parte da R-Ladies São Paulo?", + "objectID": "posts/2023-03-evento-open-data-day/index.html#introdução", + "href": "posts/2023-03-evento-open-data-day/index.html#introdução", + "title": "Evento: Análise de dados abertos com R", "section": "", - "text": "Os eventos realizados pela R-Ladies São Paulo são gratuitos e são divulgados na plataforma Meetup. Se quiser acompanhar os próximos eventos, recomendamos inscrever-se na plataforma Meetup e seguir as nossas redes sociais, principalmente o Instagram." + "text": "A R-Ladies São Paulo organizou, em 18 de março de 2023, o evento “Análise de Dados Abertos com R - Open Data Day”. A atividade aconteceu em um sábado, durante os períodos da manhã e da tarde, totalizando 6 horas efetivas de atividade.\nO Insper, uma instituição sem fins lucrativos dedicada ao ensino e à pesquisa, mais uma vez apoiou o grupo cedendo o espaço para a realização do evento. Outro apoio recebido foi da Curso-R, que cedeu dois monitores para auxiliar na monitoria, ajudando nas dúvidas. O principal objetivo deste encontro foi oferecer informações a respeito do que são e da importância dos dados abertos e promover oportunidade de pôr a “mão-na-massa” manipulando dados abertos, além de traçar o cenário atual de acesso a esses dados em vários níveis governamentais e áreas do conhecimento." }, { - "objectID": "como-participar.html#eventos-anteriores", - "href": "como-participar.html#eventos-anteriores", - "title": "Como fazer parte da R-Ladies São Paulo?", - "section": "Eventos anteriores", - "text": "Eventos anteriores\nAs gravações dos eventos que acontecem online ficam disponíveis no canal do Youtube." + "objectID": "posts/2023-03-evento-open-data-day/index.html#o-que-é-o-open-data-day", + "href": "posts/2023-03-evento-open-data-day/index.html#o-que-é-o-open-data-day", + "title": "Evento: Análise de dados abertos com R", + "section": "O que é o Open Data Day?", + "text": "O que é o Open Data Day?\nO Open Data Day, ou “Dia dos Dados Abertos”, é uma celebração anual dos dados abertos em todo o mundo, organizado e apoiado pela Open Knowledge Foundation. Caso queira saber mais, consulte o site oficial do Open Data Day e a página do projeto no site da Open Knowledge Brasil." }, { - "objectID": "como-participar.html#grupo-no-telegram", - "href": "como-participar.html#grupo-no-telegram", - "title": "Como fazer parte da R-Ladies São Paulo?", - "section": "Grupo no Telegram", - "text": "Grupo no Telegram\nExiste um grupo no telegram da R-Ladies São Paulo! O acesso é apenas para pessoas que fazem parte do público-alvo da R-Ladies: mulheres cis, mulheres trans, homens trans, pessoas não-binárias e queer.\nPortanto, o grupo não é aberto e é necessário solicitar o convite. Caso você faça parte do público-alvo e queira participar do grupo, solicite o convite enviando uma mensagem privada no nosso perfil do Instagram." + "objectID": "posts/2023-03-evento-open-data-day/index.html#atividade-principal", + "href": "posts/2023-03-evento-open-data-day/index.html#atividade-principal", + "title": "Evento: Análise de dados abertos com R", + "section": "Atividade principal", + "text": "Atividade principal\nContando com cerca de 40 pessoas, o dia foi estruturado em quatro blocos. O primeiro bloco teve caráter informativo e contou com uma sequência de breves apresentações como: o que é a comunidade R-Ladies São Paulo, o que é Open Data Day e o que são Dados Abertos.\n\n\n\n\nComo era objetivo que as pessoas se sentissem à vontade para mexer nas bases de dados abertos, experimentou-se o formato de dividir a turma em pequenos grupos de trabalho. Cada grupo trabalhou uma base específica e foi acompanhado de uma monitora com experiência na análise desses dados, que orientou o grupo a buscar os dados e entendê-los. Assim, o segundo bloco consistiu:\n\nda explicação de como aconteceria essa dinâmica;\nde uma fala breve (cerca de 5 minutos) de cada monitora sobre o tema de sua expertise e sobre a base de dados abertos que seria trabalhada, para facilitar a identificação das participantes com o tema;\ne da separação das participantes nos grupos segundo afinidade de interesses - a adesão foi livre e não houve necessidade de redimensionar ou redistribuir os grupos.\n\nOs temas e respectivas monitoras foram:\n\nDados sobre violência - Fernanda Peres, biomédica\nDados ambientais sobre queimadas - Bianca Muniz, jornalista\nDados educacionais - Ana Carolina Moreno, jornalista\nDados sobre emprego - Ana Paula Rocha, economista\nDados eleitorais - Cecília do Lago, jornalista\nDados prisionais - Thandara Santos, socióloga\n\nAlém disso, havia pessoas monitoras disponíveis para ajudar em dúvidas sobre R: \n\nBeatriz Milz (Organização R-Ladies SP)\nIanní Muliterno (Organização R-Ladies SP)\nGeovana Lopes Batista (Organização R-Ladies SP)\nHaydee Svab (Organização R-Ladies SP)\nJulio Trecenti (Curso-R)\nWilliam Amorim (Curso-R)\n\nFoi criado um Google Docs aberto para que os grupos pudessem fazer e compartilhar anotações.\n\n\n\n\n\n\n\n\n\n\nEntão, no terceiro bloco, os grupos trabalharam em importar, entender e começar a explorar os dados abertos de seus respectivos temas. Como muitas pessoas apontaram que não tinham experiência para criar visualizações de dados e tinham interesse em começar, a co-organizadora Beatriz Milz fez uma apresentação curta, em formato live coding, sobre o uso do pacote esquisse para gerar visualizações de dados com ggplot2.\n\n\n\n\nNo quarto e último bloco, os grupos apresentaram um pouco de suas dificuldades, aprendizados e resultados (alguns inclusive apresentaram visualizações feitas!). Foram apresentações interessantes que refletiram os tópicos abordados nas apresentações iniciais sobre dados abertos - por exemplo, alguns grupos indicaram lidar com base desatualizada, outros apontaram que dados estavam agregados e poderiam ser disponibilizados em forma de microdados, entre outros.\nA experiência foi muito boa, e as pessoas organizadoras e participantes demonstraram ter gostado bastante da atividade (principalmente as crianças!). Cada grupo teve entre duas e seis pessoas além das monitorias, o que permitiu um acompanhamento mais individualizado para sanar dúvidas e garantir o aproveitamento da atividade." + }, + { + "objectID": "posts/2023-03-evento-open-data-day/index.html#fortalecendo-a-comunidade", + "href": "posts/2023-03-evento-open-data-day/index.html#fortalecendo-a-comunidade", + "title": "Evento: Análise de dados abertos com R", + "section": "Fortalecendo a comunidade", + "text": "Fortalecendo a comunidade\nDois pontos interessantes a destacar são o café colaborativo e o Espaço Gugudadados.\nCafé Colaborativo\n\n\n\n\n\n\n\n\nO café colaborativo foi montado com itens comprados com o valor da bolsa oferecida pela OKBR, e também por itens trazidos por participantes. Assim, as pessoas puderam levantar e buscar café e algo para comer em qualquer momento do evento. Esse formato de café (disponível o tempo todo do evento) é muito bom por 3 motivos: (i) respeita o tempo dos grupos que podem fazer suas pausas conforme o andar dos trabalhos; (ii) acolhe participantes que por questões de saúde não podem permanecer muitas horas sem comer e (iii) acolhe participantes que por condição sócio-econômica não têm como fazer uma refeição no intervalo do almoço. Dada a natureza do grupo R-Ladies, é um quesito importante prover um acolhimento mínimo necessário para que todas as pessoas tenham condição de usufruir da experiência do evento independente de ter o que comer ao longo do dia, além de que o café colaborativo também é uma forma de incentivar a integração entre as pessoas!\nEspaço Gugudadados\nO Espaço Gugudadados é um espaço feito para facilitar a participação de mães e pessoas cuidadoras. Participaram um bebê e quatro crianças na faixa de 7 a 10 anos. Com o valor da bolsa oferecida pela OKBR foi possível contratar uma professora recreadora que esteve no espaço Gugudadados (uma sala ao lado da sala das atividades dos adultos, no mesmo andar) durante toda a atividade. As organizadoras da R-Ladies também levaram brinquedos, desenhos, canetinhas, jogos e tatuagens temporárias para entreter e divertir as crianças." + }, + { + "objectID": "posts/2023-03-evento-open-data-day/index.html#resultados-dos-grupos", + "href": "posts/2023-03-evento-open-data-day/index.html#resultados-dos-grupos", + "title": "Evento: Análise de dados abertos com R", + "section": "Resultados dos grupos", + "text": "Resultados dos grupos\nGrupo de dados educacionais (Monitora Ana Carolina Moreno)\nA monitora apresentou ao grupo um código em R de análise de dados do Censo da Educação Básica usado para a produção de uma série de reportagens especiais sobre o impacto da pandemia na educação infantil, que foi ao ar em novembro de 2022. A monitora também preparou uma apresentação sobre dados educacionais, para auxiliar no entendimento das diferentes fontes e bases de dados disponíveis sobre educação.\nOs dados utilizados podem ser obtidos no site do INEP. \nGrupo de dados eleitorais (Monitora Cecília do Lago):\nEste grupo explorou dados eleitorais referentes às eleições de 2022, disponibilizados pelo TSE. Uma curiosidade do grupo era descobrir quantos candidatos não receberam um ou nenhum voto na eleição de 2022.\nOs dados utilizados podem ser obtidos no Portal de Dados Abertos do TSE.\nGrupo de dados ambientais (Bianca Muniz):\nEste grupo explorou dados sobre focos de queimadas, no sistema BDQueimadas do INPE. Esse sistema permite fazer downloads de dados num período de até um ano. A monitora preparou uma apresentação sobre os dados utilizados. O grupo exportou os dados referentes à 2020 até 2022, e o gráfico a seguir permite ver a quantidade de focos de queimada por mês, segundo o bioma onde o foco de queimada acontece. É possível perceber no gráfico que os biomas com maiores focos de incêndio são a Amazônia e o Cerrado, e apresentam padrões sazonais. O maior pico de focos de queimadas na Amazônia no período pesquisado aconteceu no segundo semestre de 2022.\n\n\n\n\nOs dados utilizados podem ser obtidos no site do INPE - BD QUEIMADAS.\nGrupo de dados prisionais (Monitora Thandara Santos):\nEste grupo explorou dados do SISDEPEN - Dados Estatísticos do Sistema Penitenciário Brasileiro. Esses dados são provenientes do Formulário de Informações Prisionais, respondido de forma eletrônica semestralmente, por servidores indicados pelas Secretarias de administrações prisionais dos Estados e Distrito Federal e do Sistema Penitenciário Federal1.\nUma das dificuldades apresentadas pelo grupo é a disponibilização dos dados serem agregadas por unidade prisional, e não indivíduos, o que inviabiliza diversas análises importantes sobre a população carcerária do Brasil. Outra dificuldade apresentada é a falta de padronização às respostas apresentadas na base, o que implica em uma baixa confiabilidade dos dados. \nOs dados utilizados podem ser obtidos no site da Secretaria Nacional de Políticas Penais.\nGrupo de dados de violência (Monitora Fernanda Peres):\nEste grupo explorou dados públicos sobre violência usando os dados do SINAN - Sistema de Informações de Agravo de Notificações, filtrando ocorrências envolvendo apenas adultos e removendo cacos de violência auto-provocada (por exemplo, suicídio). O grupo constatou que os dados públicos de Violência no DataSUS estavam desatualizados. A base referente à 2020 estava incompleta, portanto o grupo explorou dados referentes a 2019. O grupo gerou uma série de gráficos, como o apresentado a seguir, que mostra que a maior quantidade de vítimas é do sexo feminino. Além disso, destaca-se que o autor da agressão na maioria das vezes é do sexo masculino (seja a vítima mulher ou homem).\n\n\n\n\nOutra ponto percebido é que quando as vítimas são mulheres, o agressor tende a ser alguém conhecido, como cônjuge, ex-cônjuge, namorado ou ex-namorado. Entre os homens, o agressor mais comum é um desconhecido.\n\n\n\n\nOs dados podem ser obtidos no DATASUS. A monitora fez uma apresentação sobre como obter esses dados.\nGrupo de dados de emprego (Monitora Ana Paula):\nA monitora fez uma apresentação sobre como obter esses dados. O grupo explorou duas bases de dados provenientes do Caged (Cadastro Geral de Empregados e Desempregados) a partir do Banco Central, sendo elas: número de empregos totais de 2000 a 2023; e número de empregos pela indústria de transformação (qualquer matéria prima que é transformada) de 2000 a 2023.  Os dados podem ser obtidos com o pacote GetBCBData, sendo possível buscar dados atualizados, porém agregados por mês/ano e ID da série temporal.\n\n# Carregando pacotes\nlibrary(tidyverse)\nlibrary(GetBCBData)\n\n# importando os dados\ndados_sgs <- GetBCBData::gbcbd_get_series(\n id = c('NCaged' = 28763, 'NCaged_IndTransf'= 28766),\n first.date = '2020-01-01',\n last.date = Sys.Date(),\n format.data = 'wide'\n)\n\n# espiar dados importados\nglimpse(dados_sgs)\n\nRows: 37\nColumns: 3\n$ ref.date <date> 2020-01-01, 2020-02-01, 2020-03-01, 2020-04-01, 2020…\n$ NCaged <dbl> 37938640, 38155900, 37860843, 36879150, 36480704, 364…\n$ NCaged_IndTransf <dbl> 6924768, 6961283, 6918309, 6705220, 6600422, 6593132,…\n\n# comparando a tendência de 2 séries\ndados_sgs_longo <- dados_sgs %>% \n pivot_longer(cols = c(NCaged, NCaged_IndTransf))\n\n# criando uma visualização\nggplot(dados_sgs_longo) +\n aes(x = ref.date, y = value, colour = name) +\n geom_line(show.legend = FALSE) +\n scale_color_hue(direction = 1) +\n theme_minimal() +\n facet_wrap(vars(name), scales = \"free_y\")\n\n\n\n\n\n\n\nPara saber mais sobre essa base de dados, consulte também a página do Sistema Gerenciador de Séries Temporais do Banco Central do Brasil." + }, + { + "objectID": "posts/2023-03-evento-open-data-day/index.html#perfil-das-pessoas-participantes", + "href": "posts/2023-03-evento-open-data-day/index.html#perfil-das-pessoas-participantes", + "title": "Evento: Análise de dados abertos com R", + "section": "Perfil das pessoas participantes", + "text": "Perfil das pessoas participantes\nPara buscar ampliar a diversidade na participação do evento, nesta edição reservamos as vagas pensando em três grupos:\n-   pessoas negras, pardas e indígenas;\n-   mães;\n-   mulheres e outras minorias de gênero.\nNeste evento, 54 pessoas se inscreveram, e dessas, 37 participaram. A seguir, apresentamos alguns gráficos que mostram informações sobre questões de diversidade coletadas das pessoas participantes.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nAinda há muito trabalho a fazer para incluir grupos menos representados nos eventos, mas acreditamos que, em comparação aos eventos anteriores à pandemia, estamos avançando. Para os próximos eventos, é importante ampliar a divulgação dos eventos para os grupos de pessoas pretas, pardas e indígenas; para mães, e para pessoas trans e não binárias, além de estarmos em busca de parcerias para realizar esse tipo de atividade na periferia." + }, + { + "objectID": "posts/2023-03-evento-open-data-day/index.html#dificuldades", + "href": "posts/2023-03-evento-open-data-day/index.html#dificuldades", + "title": "Evento: Análise de dados abertos com R", + "section": "Dificuldades", + "text": "Dificuldades\nA principal dificuldade na organização do evento foi o pouco tempo disponível para divulgação da atividade, já a definição da data e local foram feitas com apenas seis dias de antecedência. Apesar de a sala disponível ter capacidade para 100 pessoas, apenas 40 tiveram tempo hábil para se organizar e se inscrever como participantes. \nNo entanto, a presença final de mais de 40 pessoas, incluindo as pessoas das monitorias e organização, foi o suficiente para realizar a atividade, tendo a presença de pessoas muito interessadas!" + }, + { + "objectID": "posts/2023-03-evento-open-data-day/index.html#relatos", + "href": "posts/2023-03-evento-open-data-day/index.html#relatos", + "title": "Evento: Análise de dados abertos com R", + "section": "Relatos", + "text": "Relatos\nAlém do relato oferecido pela equipe da organização, gostaríamos de compartilhar também dois relatos compartilhados por pessoas que participaram do evento:\nTatiana Peixoto:\n\nOlá, eu sou a Tatiana, uma mulher de 42 anos, cis, negra, engenheira ambiental e apaixonada por estudar. Eu me inscrevi no evento, não só pela capacitação, mas também pela busca de otimismo e assim criar forças para me inserir novamente no mercado profissional, pois fiquei muito tempo no meio acadêmico. No dia 18.03.23, compreendi que a R-ladies é muito mais que um evento introdutório de programação. Essa equipe traz um novo olhar sobre a programação, tirando os bloqueios e os obstáculos para todes aqueles que querem seguir uma bela trajetória na ciência de dados. O evento é de ótima qualidade. Eu me senti acolhida, cuidada e muito bem tratada. Eu com certeza participaria de outros eventos da R-ladies. Além de toda a gentileza da equipe do Insper em nos receber. Espero que a R-ladies SP, siga com novos eventos e novos projetos, pois assim como eu, vocês farão muitas pessoas felizes.\n\nJuliana Soprani:\n\nAproveito para reforçar minhas parabenizações pelo evento! Foi realmente muito relevante!!! Não só tecnicamente, no aprendizado de análise de dados e do uso do R, mas também sobre a questão do acolhimento, desencadeando uma sensação de pertencimento a um grupo ou propósito. Para quem está iniciando na área de dados, ou em transição de carreira, como no meu caso, foi muito importante ver tantas mulheres de diferentes áreas, idades e cenários trabalhando com dados e R e engajadas em ampliar o acesso à ferramenta para as minorias. Agradeço a oportunidade e espero futuramente poder contribuir com análise de dados em saúde. Ansiosa pelos próximos encontros." + }, + { + "objectID": "posts/2023-03-evento-open-data-day/index.html#apoios", + "href": "posts/2023-03-evento-open-data-day/index.html#apoios", + "title": "Evento: Análise de dados abertos com R", + "section": "Apoios", + "text": "Apoios\n\n\n\n\n\n\n\n\nÉ importante ressaltar a importância do apoio financeiro da OKBR, que possibilitou a compra de itens para o coffee break, adesivos e também a contratação de uma recreadora. \nAs salas oferecidas pelo Insper foram cruciais para a realização do evento. O prédio é de fácil acesso por transporte público. O encontro aconteceu em um espaço amplo, que conta com acesso à internet, mesas, cadeiras confortáveis e facilidade de acesso a restaurante para o almoço. O tobogã que faz parte das instalações do prédio também é um sucesso e compõe uma das experiências mais alegres para as crianças que ficaram no Gugudadados.\nA Curso-R também apoiou o evento, cedendo dois monitores para auxiliar na monitoria, ficando à disposição para ajudar nas dúvidas das pessoas participantes." + }, + { + "objectID": "posts/2023-03-evento-open-data-day/index.html#equipe", + "href": "posts/2023-03-evento-open-data-day/index.html#equipe", + "title": "Evento: Análise de dados abertos com R", + "section": "Equipe", + "text": "Equipe\nEste evento não teria sido possível se não fosse a colaboração de várias pessoas. Portanto, aqui listamos pessoas que participaram das diversas etapas de organização do evento:\n\nAna Paula Rocha - organização, monitoria temática\nAna Carolina Moreno - organização, monitoria temática\nBeatriz Milz - organização, monitoria em R\nBianca Muniz - monitoria temática\nCecília do Lago - monitoria temática\nCélia Oliveira - recreadora do espaço Gugudadados\nDiego Rabatone Oliveira - espaço Gugudadados\nFernanda Peres - organização, monitoria temática\nGeovana Lopes Batista - monitoria em R\nHaydee Svab - organização, monitoria em R, espaço Gugudadados\nIanní Muliterno - monitoria em R\nJulio Trecenti - monitoria em R\nTatyane Paz Dominguez - organização, espaço Gugudadados\nThandara Santos - monitoria temática\nWilliam Amorim - monitoria em R\n\nO evento não seria o mesmo sem a colaboração de vocês - agradecemos e valorizamos muito a sua participação!\nAlém disso, agradecemos também todas as pessoas que participaram!" + }, + { + "objectID": "posts/2023-03-evento-open-data-day/index.html#próximos-eventos", + "href": "posts/2023-03-evento-open-data-day/index.html#próximos-eventos", + "title": "Evento: Análise de dados abertos com R", + "section": "Próximos eventos", + "text": "Próximos eventos\nEssa foi a primeira vez que realizamos evento com a ideia de trabalhar em “grupos”, e com certeza é um formato que funcionou (as participantes apontaram que preferiam assim do que palestras expositivas). Pretendemos organizar outros eventos nesse formato!\nO próximo evento da R-Ladies São Paulo está previsto para acontecer em maio, com tema ainda a ser definido. Caso tenha interesse em participar, recomendamos acompanhar nossas redes sociais!\n\n\n\n\n\n\n\n\nAté o próximo encontro!" + }, + { + "objectID": "posts/2023-03-evento-open-data-day/index.html#footnotes", + "href": "posts/2023-03-evento-open-data-day/index.html#footnotes", + "title": "Evento: Análise de dados abertos com R", + "section": "Notas de rodapé", + "text": "Notas de rodapé\n\nFonte: SISDEPEN.↩︎" + }, + { + "objectID": "posts/2023-05-aprendendo-carol-moreno/index.html", + "href": "posts/2023-05-aprendendo-carol-moreno/index.html", + "title": "Aprendendo a programar em quatro capítulos", + "section": "", + "text": "Autoria\n\n\n\n\n\n\n\n\nCarol Moreno\n\n\n\nEste post foi escrito por Ana Carolina Moreno e publicado no Linkedin.\nA Carol é uma integrante da comunidade R-Ladies São Paulo, e atua como Jornalista de Dados Senior na TV Globo.\n\n\n\nDesde que comecei a dar cursos de programação, sempre vejo nos rostos de grande parte das pessoas participantes aquele “medo” de não conseguir. Faz um pouquinho de sentido, afinal, porque só dou cursos introdutórios, pra quem nunca programou, e boa parte deles têm como público minorias de gênero, porque são organizados pelo capítulo de São Paulo R-Ladies Global, do qual faço parte. Sabemos que, infelizmente, muitos grupos da população são ensinados desde cedo que “não servem” para a área de tecnologia…\nMas eu sempre começo essas aulas com um resuminho da minha trajetória, justamente pra derrubar vários mitos, e mostrar que é possível aprender novas habilidades, especialmente se você:\n\ntiver apoio adequado no aprendizado;\natrelar o aprendizado à sua realidade;\nidentificar os contextos em que você aprende melhor;\ninvestir na prática o que aprendeu;\ntiver incentivos pra aprender;\nconseguir compartilhar teus aprendizados.\n\nInspirada nessa reportagem excelente do Darlan Helder, compartilho abaixo um pouco dessa história.\n(Prólogo: eu sempre fiquei de recuperação em matemática, física, química, biologia… Minha mãe, que quase fez faculdade de matemática de tanto que gosta da área, até hoje acha estranho que eu seja referência no assunto pra qualquer pessoa que seja, quanto mais uma redação enorme.)\nCapítulo 1 - Carol Excel\nNos idos de 2012 tentei aprender R, mas o RStudio ainda estava nascendo… Eu tentei fuçar naquele site r-project.com, mas fracassei de forma retumbante. Achei que “aquilo não era pra mim”.\nUm pesquisador me sugeriu ir pro Stata, mas nunca encontrei muito sentido em softwares proprietários.\nNos cinco anos seguintes, continuei interessada nos dados educacionais, mas só conseguia fazer reportanges com base em análises feitas por outras pessoas. Algumas delas por sugestão minha, como essa comparando o perfil de quem estuda pedagogia com as demais carreiras de graduação.\nCapítulo 2 - Carol Query\nEm 2017, o incrível Leandro Bispo Oliveira apareceu na redação do g1 com uma apostilinha de SQL básico encadernada, e me ensinou em duas horas a acessar o datalake e fazer queries com a base do Bolsa Família. Graças a ele consegui fazer uma análise que ninguém tinha feito até então no jornalismo: “testar” as notas de cortes do Sisu (a USP, por exemplo, tinha umas notas altíssimas) para saber se elas eram compatíveis com a realidade do desempenho dos candidatos no Enem.\nNão tem nada como atrelar um conhecimento à aplicação prática na nossa realidade. E a minha realidade era: trabalho cobrindo educação, os dados abertos educacionais são muitos, ótimos, mas não tenho as técnicas pra fazer todas as reportagens que quero. E não quero depender de pesquisadores fazerem essa parte da produção de notícias.\nFoi por isso que decidi continuar aprendendo. Entrei num curso online de python para jornalistas. Fracassei, larguei pela metade.\nDaí entrei em outro curso online, de R para jornalistas. Tive problemas até pra instalar os programas. Larguei no comecinho.\nMas continuava de olho nas oportunidades pra aprender. Até que, no começo de 2019, o capítulo de São Paulo das R-Ladies Global anunciou um curso presencial, num sábado em que eu não estava de plantão, e passei o dia todo aprendendo com uma didática incrível, num ambiente acolhedor e inspirador. Resultado: comecei a finalmente conseguir responder a perguntas que sempre me pareceram relevantes e que ainda não tinham lido no jornalismo, como a desigualdade racial entre professores universitários e a evolução ao longo dos anos de escolas batizadas com nomes de generais da ditatura militar.\nAté então, penava bastante pra conseguir virar reportagens dirigidas porque meu trabalho envolvia muitas pautas que não usavam dados. Então nem sempre conseguia praticar o que aprendi (outro ponto fundamental pra avançar no aprendizado de qualquer coisa).\nEntendi também que, quando eu preciso aprender sobre um assunto desde o início, meu negócio é curso presencial (pode ser diferente pra outras pessoas). Quando já estou mais avançada, tudo bem fazer virtualmente algum curso pontual, para aprender melhor alguma habilidade que ainda acho que preciso praticar mais (nessa quinta, começo um curso de raspagem de dados, mal posso esperar!)\nCapítulo 3 - Carol Dados\nEm janeiro de 2020, passei de “repórter de Educação” para “produtora de dados” na redação de São Paulo da Globo (ganhei apelidos como “Carol Dados” e “Balcão da Média Móvel”). A partir de então, minha função principal era fuçar em dados, então a prática virou rotina. E não só os educacionais, de ciência, saúde e meio ambiente aos quais eu estava acostumada. Dados do Waze, do TSE, da Câmara Municipal de São Paulo, das reclamações do Disque 156…\nDois meses depois, veio a pandemia, que obrigou o poder público a criar novos indicadores baseados em dados e o jornalismo a explicar todos esses novos conceitos para uma sociedade confusa e aterrorizada.\nAí veio a necessidade de escrever códigos pra otimizar análises que eram feitas diariamente ou mesmo escrever códigos para permitir análises que, da forma como vinham do poder público, eram impossíveis de fazer de outras formas. Aqui entra o tal do incentivo pra aprender novas funções e formas de automatizar scripts pra não perder tempo com eles.\n(Pausa para agredecer todas as pessoas que manjam de R, SQL e Datasus e que eu atazanei durante meses a fio, em qualquer dia da semana e até de madrugada.)\nAlguns códigos saíam em menos de duas horas, outros viraram dashboard pra todas as equipes consultarem, um levou uns três meses pra ficar azeitadinho.\nTodo esse esforço valeu a pena, e me deu muito mais autonomia.\nO mais legal é que, ao contrário da maioria das pessoas no chamado “jornalismo de dados”, eu não fico em uma equipe “de dados”: sou parte de uma grande equipe de produção, mas sou a única com foco maior na missão de escarafunchar dados. Por isso, não fico longe da produção diária, nem me debruço meses produzindo uma única reportagem especial. Sigo cobrindo o chamado “hardnews”, mas consigo fazer isso aplicando o que aprendi sobre análise estatística e técnicas de ciências de dados pra qualificar a cobertura. Acredito que o impacto das reportagens acaba sendo muito mais abrangente.\nCapítulo 4 - Teacher Carol\nAinda sigo atazando muita gente com meus códigos, dependendo do que aparece (obrigada de novo!). Também tenho sempre buscado aprender coisas novas, quando o tempo permite, pra facilitar análises futuras.\nMas a principal mudança, desde 2020, é poder compartilhar o que aprendi com outras pessoas, principalmente jornalistas, e principalmente mulheres e minorias de gênero, que tenha interesse nessas habilidades. Nos últimos anos já dei vários cursos introdutórios de R, de SQL, de dados educacionais, de Lei de Acesso à Informação, de tudo isso junto e misturado.\nToda vez que elaboro um novo curso, consigo revisar o que já sei, aprender coisas novas, aprofundar alguns conhecimentos. Ensinar é uma das melhores formas de aprender.\nSempre é desafiador, mas pra mim sempre esteve claro que só aprendi o que sei hoje porque muitas pessoas investiram o tempo delas em me ajudar. Não acho que seria possível fazer de outra forma. Por isso, enxergo o ensino como uma forma de manter acesa essa corrente colaborativa.\nPS: Se você é jornalista ou estudante de jornalismo, a Jeduca: Associação de Jornalistas de Educação, em parceria com a Abraji - Associação Brasileira de Jornalismo Investigativo, vai dar mais uma vez o curso Jornalismo de educação: bases para a cobertura. É gratuito e, na minha opinião, é o curso mais completo de jornalismo educacional que existe hoje. São 12 aulas, e eu vou ministrar as duas sobre reportar com dados =)\nClique aqui para saber mais!" } ] \ No newline at end of file diff --git a/sitemap.xml b/sitemap.xml index cbee75b..6af160d 100644 --- a/sitemap.xml +++ b/sitemap.xml @@ -1,91 +1,95 @@ - https://rladies-sp.org/contribuir-com-o-blog.html - 2023-10-30T23:44:10.238Z - - - https://rladies-sp.org/posts/2023-06-rita-com-r/index.html - 2023-10-30T23:44:09.342Z + https://rladies-sp.org/videos.html + 2023-11-21T22:51:32.021Z - https://rladies-sp.org/posts/2023-03-tidytuesday-paraolimpiadas/index.html - 2023-10-30T23:43:56.750Z + https://rladies-sp.org/posts/2023-03-evento-open-data-day/english.html + 2023-11-21T22:51:30.449Z - https://rladies-sp.org/posts/2023-06-05-increasing-diversity-sao-paulo/index.html - 2023-10-30T23:43:41.349Z + https://rladies-sp.org/posts/2023-05-open-data-day-educacao/index.html + 2023-11-21T22:51:24.721Z - https://rladies-sp.org/posts/2023-05-aprendendo-carol-moreno/index.html - 2023-10-30T23:43:38.141Z + https://rladies-sp.org/posts/2023-01-evento-oficina-intro-R/index.html + 2023-11-21T22:51:19.665Z - https://rladies-sp.org/posts/2023-03-evento-open-data-day/index.html - 2023-10-30T23:43:31.681Z + https://rladies-sp.org/posts/2022-12-graficos-dinamite/index.html + 2023-11-21T22:51:17.337Z - https://rladies-sp.org/posts/2023-01-evento-oficina-intro-R/index.html - 2023-10-30T23:43:21.460Z + https://rladies-sp.org/posts/2023-10-ws-ghibli/index.html + 2023-11-21T22:51:12.445Z - https://rladies-sp.org/posts/2022-12-graficos-dinamite/index.html - 2023-10-30T23:43:18.440Z + https://rladies-sp.org/posts/2023-11-evento-intro-r/index.html + 2023-11-21T22:51:04.665Z - https://rladies-sp.org/eventos.html - 2023-10-30T23:43:14.320Z + https://rladies-sp.org/posts/2023-06-05-increasing-diversity-sao-paulo/index.html + 2023-11-21T22:51:02.657Z - https://rladies-sp.org/index.html - 2023-10-30T23:43:09.832Z + https://rladies-sp.org/posts/2023-03-tidytuesday-paraolimpiadas/index.html + 2023-11-21T22:50:58.977Z - https://rladies-sp.org/videos.html - 2023-10-30T23:43:05.576Z + https://rladies-sp.org/sobre.html + 2023-11-21T22:50:53.917Z https://rladies-sp.org/eventos/2023-05-20/index.html - 2023-10-30T23:43:06.568Z + 2023-11-21T22:50:50.373Z - https://rladies-sp.org/sobre.html - 2023-10-30T23:43:13.408Z + https://rladies-sp.org/eventos.html + 2023-11-21T22:50:47.733Z - https://rladies-sp.org/sugestoes.html - 2023-10-30T23:43:15.072Z + https://rladies-sp.org/contribuir-com-o-blog.html + 2023-11-21T22:50:46.617Z - https://rladies-sp.org/posts/2022-12-boas-vindas-ao-blog/index.html - 2023-10-30T23:43:19.452Z + https://rladies-sp.org/index.html + 2023-11-21T22:50:50.033Z - https://rladies-sp.org/posts/2023-03-evento-open-data-day/english.html - 2023-10-30T23:43:26.660Z + https://rladies-sp.org/sugestoes.html + 2023-11-21T22:50:51.001Z - https://rladies-sp.org/posts/2023-02-tutorial-quarto/index.html - 2023-10-30T23:43:36.141Z + https://rladies-sp.org/como-participar.html + 2023-11-21T22:50:54.185Z https://rladies-sp.org/posts/2023-06-05-increasing-diversity-sao-paulo/english.html - 2023-10-30T23:43:39.865Z + 2023-11-21T22:51:03.793Z - https://rladies-sp.org/posts/2023-10-ws-ghibli/index.html - 2023-10-30T23:43:51.157Z + https://rladies-sp.org/posts/2022-12-boas-vindas-ao-blog/index.html + 2023-11-21T22:51:05.421Z + + + https://rladies-sp.org/posts/2023-06-rita-com-r/index.html + 2023-11-21T22:51:15.261Z https://rladies-sp.org/posts/2020-06-rladies-global-blm/index.html - 2023-10-30T23:43:57.778Z + 2023-11-21T22:51:18.145Z - https://rladies-sp.org/posts/2023-05-open-data-day-educacao/index.html - 2023-10-30T23:44:04.706Z + https://rladies-sp.org/posts/2023-02-tutorial-quarto/index.html + 2023-11-21T22:51:22.445Z - https://rladies-sp.org/como-participar.html - 2023-10-30T23:44:09.742Z + https://rladies-sp.org/posts/2023-03-evento-open-data-day/index.html + 2023-11-21T22:51:27.673Z + + + https://rladies-sp.org/posts/2023-05-aprendendo-carol-moreno/index.html + 2023-11-21T22:51:31.737Z diff --git a/sobre.html b/sobre.html index 2493cad..35c4756 100644 --- a/sobre.html +++ b/sobre.html @@ -246,8 +246,8 @@

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