From 27bba27356ea5f4caeb154286d926cd4449c182c Mon Sep 17 00:00:00 2001 From: rcfeliz Date: Tue, 24 Oct 2023 19:39:26 -0300 Subject: [PATCH] =?UTF-8?q?att=20slide=20de=20introdu=C3=A7=C3=A3o=20e=20t?= =?UTF-8?q?ira=20ementa=20do=20time=20series?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- slides/a00_introducao.html | 39 ++- slides/a00_introducao.qmd | 264 +++++++----------- slides/a_time_series.html | 89 +++--- slides/a_time_series.qmd | 22 -- .../figure-revealjs/unnamed-chunk-2-1.png | Bin 15509 -> 67474 bytes .../figure-revealjs/unnamed-chunk-3-1.png | Bin 22386 -> 133473 bytes .../libs/quarto-html/light-border.css | 1 + .../libs/revealjs/dist/theme/quarto.css | 4 +- 8 files changed, 162 insertions(+), 257 deletions(-) create mode 100644 slides/a_time_series_files/libs/quarto-html/light-border.css diff --git a/slides/a00_introducao.html b/slides/a00_introducao.html index 1cb7800..1e69263 100644 --- a/slides/a00_introducao.html +++ b/slides/a00_introducao.html @@ -350,9 +350,7 @@

Ricardo Feliz

Para nós conhecermos vocês melhor

-

Respondam este formulário por favor!

-

https://forms.gle/HStRPDK2jVsJNDts5

-

Demora de 5 a 10 minutos para responder!

+

Respondam este formulário por favor! https://forms.gle/bkGTyYk4UgJEWmXU9 Demora de 5 a 10 minutos para responder!

@@ -417,13 +415,13 @@

Informações sobre as aulas

Aulas assíncronas

Aulas síncronas

    -
  • São 6 encontros, contando com a aula de hoje, de 3 horas de duração.
    • +
  • São 6 encontros, contando com a aula de hoje, todos de 3 horas de duração.
  • O método de aula é o Peer Instruction
    • Logo no início das aulas, iremos dar uma lista de exercícios.
      • @@ -492,7 +490,7 @@

      3 Tabela de frequência Estatística -27 min +17 min Aula @@ -527,7 +525,7 @@

      4 Medidas de dispersão II Estatística -23 min +24 min Extra @@ -546,7 +544,7 @@

      Aula 5 -Teorem de Priest & Klein +Teorema de Priest & Klein Metodologia 60 min @@ -665,8 +663,7 @@

      Planejamento da Semana 2

-

Preparação para a aula: 24/10/2023 - 31/10/2023

-

Data e hora da aula: 31/10/2023 das 19 às 22hrs

+

Preparação para a aula: 24/10/2023 - 31/10/2023 Data e hora da aula: 31/10/2023 das 19 às 22hrs

@@ -693,7 +690,7 @@

Planejamento da Semana 3

Aula Tabela de frequência Estatística -27 min +17 min Aula @@ -705,7 +702,7 @@

Planejamento da Semana 3

Total - - -96 min +86 min Extra @@ -720,8 +717,7 @@

Planejamento da Semana 3

-

Preparação para a aula: 31/10/2023 - 07/11/2023

-

Data e hora da aula: 07/11/2023 das 19 às 22hrs

+

Preparação para a aula: 31/10/2023 - 07/11/2023 Data e hora da aula: 07/11/2023 das 19 às 22hrs

@@ -754,13 +750,13 @@

Planejamento da Semana 4

Aula Medidas de dispersão II Estatística -23 min +24 min Total - - -92 min +93 min Extra @@ -775,8 +771,7 @@

Planejamento da Semana 4

-

Preparação para a aula: 07/11/2023 - 14/11/2023

-

Data e hora da aula: 14/11/2023 das 19 às 22hrs

+

Preparação para a aula: 07/11/2023 - 14/11/2023 Data e hora da aula: 14/11/2023 das 19 às 22hrs

@@ -801,7 +796,7 @@

Planejamento da Semana 5

Aula -Teorem de Priest & Klein +Teorema de Priest & Klein Metodologia 60 min @@ -836,8 +831,7 @@

Planejamento da Semana 5

-

Preparação para a aula: 14/11/2023 - 21/11/2023

-

Data e hora da aula: 21/11/2023 das 19 às 22hrs

+

Preparação para a aula: 14/11/2023 - 21/11/2023 Data e hora da aula: 21/11/2023 das 19 às 22hrs

@@ -903,8 +897,7 @@

Planejamento da Semana 6

-

Preparação para a aula: 21/11/2023 - 28/11/2023

-

Data e hora da aula: 28/11/2023 das 19 às 22hrs

+

Preparação para a aula: 21/11/2023 - 28/11/2023 Data e hora da aula: 28/11/2023 das 19 às 22hrs

diff --git a/slides/a00_introducao.qmd b/slides/a00_introducao.qmd index 2a8af26..8416791 100644 --- a/slides/a00_introducao.qmd +++ b/slides/a00_introducao.qmd @@ -1,6 +1,6 @@ --- title: "Introdução à jurimetria" -format: +format: revealjs: logo: "img/logo-abj-colorido.png" footer: "Introdução à Pesquisa Jurimétrica." @@ -10,13 +10,12 @@ format: mainfont: Yaldevi editor: visual lang: pt -title-slide-attributes: +title-slide-attributes: data-background-color: "#233262" border-start-end-radius: 50%; writing-mode: vertical-rl; preview-links: true --- - ```{r setup, include=FALSE} knitr::opts_chunk$set( echo = FALSE, @@ -25,49 +24,47 @@ knitr::opts_chunk$set( message = FALSE, warning = FALSE ) - cores_abj <- viridis::viridis(2, 1, .2, .8) ``` - ```{r da-aulas} da_aulas <- tibble::tibble( semana=1, tipo_conteudo="", duracao=0, conteudo="" -) |> +) |> dplyr::add_row( semana=2, tipo_conteudo="Metodologia", duracao=42, conteudo="Operacionalização de conceitos" - ) |> + ) |> dplyr::add_row( semana=2, tipo_conteudo="Estatística", duracao=18, conteudo="Tipos de variáveis" - ) |> + ) |> dplyr::add_row( semana=2, tipo_conteudo="Programação", duracao=90, conteudo="Introdução ao R" - ) |> + ) |> dplyr::add_row( semana=3, tipo_conteudo="Metodologia", duracao=25, conteudo="Definição de escopo" - ) |> + ) |> dplyr::add_row( - semana=3, + semana=3, tipo_conteudo="Estatística", - duracao=27, + duracao=17, conteudo="Tabela de frequência" - ) |> + ) |> dplyr::add_row( - semana=3, + semana=3, tipo_conteudo="Técnicas", duracao=44, conteudo="Medidas de centro" @@ -77,97 +74,97 @@ da_aulas <- tibble::tibble( tipo_conteudo="Programação", duracao=27, conteudo="Tabela de frequência no R" - ) |> + ) |> dplyr::add_row( semana=4, tipo_conteudo="Metodologia", duracao=39, conteudo="Processo de geração de dados" - ) |> + ) |> dplyr::add_row( - semana=4, + semana=4, tipo_conteudo="Estatística", duracao=30, conteudo="Medidas de dispersão I" - ) |> + ) |> dplyr::add_row( - semana=4, + semana=4, tipo_conteudo="Estatística", - duracao=23, + duracao=24, conteudo="Medidas de dispersão II" - ) |> + ) |> dplyr::add_row( - semana=4, + semana=4, tipo_conteudo="Programação", duracao=32, conteudo="Como calcular medidas no R" - ) |> + ) |> dplyr::add_row( - semana=5, + semana=5, tipo_conteudo="Metodologia", duracao=37, conteudo="Viés de seleção" - ) |> + ) |> dplyr::add_row( - semana=5, + semana=5, tipo_conteudo="Metodologia", duracao=60, - conteudo="Teorem de Priest & Klein" - ) |> + conteudo="Teorema de Priest & Klein" + ) |> dplyr::add_row( - semana=5, + semana=5, tipo_conteudo="Estatística", duracao=28, conteudo="Gráfico de barras" - ) |> + ) |> dplyr::add_row( - semana=5, + semana=5, tipo_conteudo="Estatística", duracao=18, conteudo="Histograma" - ) |> + ) |> dplyr::add_row( - semana=5, + semana=5, tipo_conteudo="Programação", duracao=17, conteudo="Introdução à visualização no R (ggplot2)" - ) |> + ) |> dplyr::add_row( - semana=6, + semana=6, tipo_conteudo="Metodologia", duracao=46, conteudo="Técnica de pesquisa I" - ) |> + ) |> dplyr::add_row( - semana=6, + semana=6, tipo_conteudo="Metodologia", duracao=27, conteudo="Técnica de pesquisa II" - ) |> + ) |> dplyr::add_row( - semana=6, + semana=6, tipo_conteudo="Estatística", duracao=22, conteudo="Boxplot" - ) |> + ) |> dplyr::add_row( - semana=6, + semana=6, tipo_conteudo="Estatística", duracao=15, conteudo="Séries temporais" - ) |> + ) |> dplyr::add_row( - semana=6, + semana=6, tipo_conteudo="Estatística", duracao=10, conteudo="Gráfico de dispersão" - ) |> + ) |> dplyr::add_row( - semana=6, + semana=6, tipo_conteudo="Programação", duracao=50, conteudo="Como criar as visualizações no R" - ) |> + ) |> dplyr::mutate( semana = as.character(semana), extra = tipo_conteudo == "Programação", @@ -175,12 +172,11 @@ da_aulas <- tibble::tibble( extra ~ "Extra", TRUE ~ "Aula" ) - ) |> + ) |> dplyr::select(tipo_aula, semana, conteudo, tipo_conteudo, duracao, extra) - -total_semanas <- da_aulas |> - dplyr::filter(semana != "1", !extra) |> - dplyr::group_by(semana) |> +total_semanas <- da_aulas |> + dplyr::filter(semana != "1", !extra) |> + dplyr::group_by(semana) |> dplyr::summarise( tipo_aula = "Total", semana, @@ -188,57 +184,42 @@ total_semanas <- da_aulas |> tipo_conteudo = "-", duracao = sum(duracao), extra = FALSE - ) |> + ) |> dplyr::distinct() - datas <- c(as.Date("2023-10-24")) dt_aula <- datas[1] for(i in seq(1:5)) { dt_aula <- dt_aula + lubridate::days(7) - datas <- c(datas, dt_aula) + datas <- c(datas, dt_aula) } data_semana <- tibble::tibble( semana = c(1:6), data = format(datas, "%d/%m/20%y") ) ``` - # Nos conhecendo melhor - ## Para vocês nos conhecerem melhor - ::: columns ::: column #### Julio Trecenti - ![](img/julio.jpg){width="500"} ::: - ::: column #### Ricardo Feliz - ![](img/ricardo.jpeg){width="375"} ::: ::: - ## Para nós conhecermos vocês melhor - ::: center-middle **Respondam este formulário por favor!** - - - + Demora de 5 a 10 minutos para responder! ::: - # Sobre o curso - -## Ementa do curso {style='font-size: 22px'} - +## Ementa do curso {style="font-size: 22px"} ::: columns ::: {.column width="33%"} #### Metodologia - 1. Operacionalização de conceitos 2. Definição de escopo 3. Processo de geração de dados @@ -246,10 +227,8 @@ Demora de 5 a 10 minutos para responder! 5. Teorema de Priest & Klein 6. Técnica de pesquisa ::: - ::: {.column width="32%"} #### Estatística - 1. Tipos de variáveis 2. Medidas de variáveis categóricas: Tabelas de frequência 3. Medidas de variáveis numéricas I: Medidas de centro @@ -263,191 +242,154 @@ Demora de 5 a 10 minutos para responder! 4. Amplitude 5. IQR ::: - ::: {.column width="32%"} - -5. Visualizações de variáveis categóricas - 1. Gráfico de barras -6. Visualizações de variáveis numéricas - 1. Histograma - 2. Boxplot - 3. Séries temporais - 4. Gráfico de dispersão - +5. Visualizações de variáveis categóricas + 1. Gráfico de barras +6. Visualizações de variáveis numéricas + 1. Histograma + 2. Boxplot + 3. Séries temporais + 4. Gráfico de dispersão ::: ::: - ## Informações sobre as aulas {.smaller} - ::: columns ::: {.column width="30%"} ### Aulas assíncronas - ```{r} -da_duracao_aulas <- da_aulas |> - dplyr::group_by(extra) |> +da_duracao_aulas <- da_aulas |> + dplyr::group_by(extra) |> dplyr::summarise( n_aulas = dplyr::n(), duracao = sum(duracao) ) - -duracao_aulas <- floor(da_duracao_aulas |> - dplyr::filter(!extra) |> +duracao_aulas <- floor(da_duracao_aulas |> + dplyr::filter(!extra) |> dplyr::pull(duracao) / 60 ) - -n_aulas <- da_duracao_aulas |> - dplyr::filter(!extra) |> - dplyr::pull(n_aulas) - -n_extra <- da_duracao_aulas |> - dplyr::filter(extra) |> - dplyr::pull(n_aulas) +n_aulas <- da_duracao_aulas |> + dplyr::filter(!extra) |> + dplyr::pull(n_aulas) +n_extra <- da_duracao_aulas |> + dplyr::filter(extra) |> + dplyr::pull(n_aulas) ``` - - São mais de `r duracao_aulas` horas de gravação. - Há `r n_aulas + n_extra` materiais gravados, divididos em `r n_aulas` aulas e `r n_extra` materiais extras. - Os materiais ficarão disponíveis a partir de hoje e poderão ser acessados a qualquer momento. ::: - ::: {.column width="70%"} ### Aulas síncronas - - São `r max(da_aulas$semana, na.rm = TRUE)` encontros, contando com a aula de hoje, todos de 3 horas de duração. - O método de aula é o Peer Instruction - Logo no início das aulas, iremos dar uma lista de exercícios. - Vocês terão 2 horas para realizar os exercícios em grupos. - Depois, haverá um pequeno intervalo. Na volta do intervalo, iremos nos reunir para discutir a resolução dos exercícios em conjunto. - - Esses exercício pressupõe que vocês tenham se preparado para assistir às aulas + - Esses exercício pressupõe que vocês tenham se preparado para assistir às aulas - Ficará como atividade para casa refazer os exercícios e enviar uma lista *individual* - A entrega individual destes exercícios será a avaliação para receber o certificado ::: ::: - -## {.scrollable} - +## {.scrollable} ```{r} -da_aulas |> - dplyr::select(-extra) |> - dplyr::mutate(duracao=paste0(duracao," min")) |> +da_aulas |> + dplyr::select(-extra) |> + dplyr::mutate(duracao=paste0(duracao," min")) |> knitr::kable( col.names=c("Tipo", "Semana", "Conteúdo", "Tipo de conteúdo", "Duração"), format = "html", escape = FALSE, table.attr = "class=\"striped\"" ) ``` - ## Planejamento da Semana 2 {.smaller} - ```{r} -da_aulas |> - dplyr::bind_rows(total_semanas) |> - dplyr::filter(semana==2) |> - dplyr::arrange(extra) |> - dplyr::select(-extra, -semana) |> - dplyr::mutate(duracao=paste0(duracao," min")) |> +da_aulas |> + dplyr::bind_rows(total_semanas) |> + dplyr::filter(semana==2) |> + dplyr::arrange(extra) |> + dplyr::select(-extra, -semana) |> + dplyr::mutate(duracao=paste0(duracao," min")) |> knitr::kable( col.names=c("Tipo", "Conteúdo", "Tipo de conteúdo", "Duração"), format = "html", escape = FALSE, table.attr = "class=\"striped\"" ) ``` - ::: center **Preparação para a aula:** `r data_semana$data[1]` - `r data_semana$data[2]` - **Data e hora da aula:** `r data_semana$data[2]` das 19 às 22hrs ::: - ## Planejamento da Semana 3 {.smaller} - ```{r} -da_aulas |> - dplyr::bind_rows(total_semanas) |> - dplyr::filter(semana==3) |> - dplyr::arrange(extra) |> - dplyr::select(-extra, -semana) |> - dplyr::mutate(duracao=paste0(duracao," min")) |> +da_aulas |> + dplyr::bind_rows(total_semanas) |> + dplyr::filter(semana==3) |> + dplyr::arrange(extra) |> + dplyr::select(-extra, -semana) |> + dplyr::mutate(duracao=paste0(duracao," min")) |> knitr::kable( col.names=c("Tipo", "Conteúdo", "Tipo de conteúdo", "Duração"), format = "html", escape = FALSE, table.attr = "class=\"striped\"" ) ``` - ::: center **Preparação para a aula:** `r data_semana$data[2]` - `r data_semana$data[3]` - **Data e hora da aula:** `r data_semana$data[3]` das 19 às 22hrs ::: - ## Planejamento da Semana 4 {.smaller} - ```{r} -da_aulas |> - dplyr::bind_rows(total_semanas) |> - dplyr::filter(semana==4) |> - dplyr::arrange(extra) |> - dplyr::select(-extra, -semana) |> - dplyr::mutate(duracao=paste0(duracao," min")) |> +da_aulas |> + dplyr::bind_rows(total_semanas) |> + dplyr::filter(semana==4) |> + dplyr::arrange(extra) |> + dplyr::select(-extra, -semana) |> + dplyr::mutate(duracao=paste0(duracao," min")) |> knitr::kable( col.names=c("Tipo", "Conteúdo", "Tipo de conteúdo", "Duração"), format = "html", escape = FALSE, table.attr = "class=\"striped\"" ) ``` - ::: center **Preparação para a aula:** `r data_semana$data[3]` - `r data_semana$data[4]` - **Data e hora da aula:** `r data_semana$data[4]` das 19 às 22hrs ::: - ## Planejamento da Semana 5 {.smaller} - ```{r} -da_aulas |> - dplyr::bind_rows(total_semanas) |> - dplyr::filter(semana==5) |> - dplyr::arrange(extra) |> - dplyr::select(-extra, -semana) |> - dplyr::mutate(duracao=paste0(duracao," min")) |> +da_aulas |> + dplyr::bind_rows(total_semanas) |> + dplyr::filter(semana==5) |> + dplyr::arrange(extra) |> + dplyr::select(-extra, -semana) |> + dplyr::mutate(duracao=paste0(duracao," min")) |> knitr::kable( col.names=c("Tipo", "Conteúdo", "Tipo de conteúdo", "Duração"), format = "html", escape = FALSE, table.attr = "class=\"striped\"" ) ``` - ::: center **Preparação para a aula:** `r data_semana$data[4]` - `r data_semana$data[5]` - **Data e hora da aula:** `r data_semana$data[5]` das 19 às 22hrs ::: - ## Planejamento da Semana 6 {.smaller} - ```{r} -da_aulas |> - dplyr::bind_rows(total_semanas) |> - dplyr::filter(semana==6) |> - dplyr::arrange(extra) |> - dplyr::select(-extra, -semana) |> - dplyr::mutate(duracao=paste0(duracao," min")) |> +da_aulas |> + dplyr::bind_rows(total_semanas) |> + dplyr::filter(semana==6) |> + dplyr::arrange(extra) |> + dplyr::select(-extra, -semana) |> + dplyr::mutate(duracao=paste0(duracao," min")) |> knitr::kable( col.names=c("Tipo", "Conteúdo", "Tipo de conteúdo", "Duração"), format = "html", escape = FALSE, table.attr = "class=\"striped\"" ) ``` - ::: center **Preparação para a aula:** `r data_semana$data[5]` - `r data_semana$data[6]` - **Data e hora da aula:** `r data_semana$data[6]` das 19 às 22hrs ::: - # Dúvidas? Comentários? - # {background="#fff"} - ![](img/logo-abj-colorido.png){width="500"} diff --git a/slides/a_time_series.html b/slides/a_time_series.html index 835e2ff..bf7f855 100644 --- a/slides/a_time_series.html +++ b/slides/a_time_series.html @@ -5,9 +5,10 @@ + - + Visualizações @@ -24,11 +25,11 @@ ul.task-list{list-style: none;} ul.task-list li input[type="checkbox"] { width: 0.8em; - margin: 0 0.8em 0.2em -1.6em; + margin: 0 0.8em 0.2em -1em; /* quarto-specific, see https://github.com/quarto-dev/quarto-cli/issues/4556 */ vertical-align: middle; } - + @@ -71,44 +72,44 @@ font-weight: 400; } - .callout.callout-captioned.callout-style-simple .callout-body { + .callout.callout-titled.callout-style-simple .callout-body { margin-top: 0.2em; } - .callout:not(.callout-captioned) .callout-body { + .callout:not(.callout-titled) .callout-body { display: flex; } - .callout:not(.no-icon).callout-captioned.callout-style-simple .callout-content { + .callout:not(.no-icon).callout-titled.callout-style-simple .callout-content { padding-left: 1.6em; } - .callout.callout-captioned .callout-header { + .callout.callout-titled .callout-header { padding-top: 0.2em; margin-bottom: -0.2em; } - .callout.callout-captioned .callout-caption p { + .callout.callout-titled .callout-title p { margin-top: 0.5em; margin-bottom: 0.5em; } - .callout.callout-captioned.callout-style-simple .callout-content p { + .callout.callout-titled.callout-style-simple .callout-content p { margin-top: 0; } - .callout.callout-captioned.callout-style-default .callout-content p { + .callout.callout-titled.callout-style-default .callout-content p { margin-top: 0.7em; } - .callout.callout-style-simple div.callout-caption { + .callout.callout-style-simple div.callout-title { border-bottom: none; font-size: .9rem; font-weight: 600; opacity: 75%; } - .callout.callout-style-default div.callout-caption { + .callout.callout-style-default div.callout-title { border-bottom: none; font-weight: 600; opacity: 85%; @@ -140,7 +141,7 @@ background-size: 0.9rem 0.9rem; } - .callout-caption { + .callout-title { display: flex } @@ -153,16 +154,16 @@ display: none !important; } - .callout.callout-captioned .callout-body > .callout-content > :last-child { + .callout.callout-titled .callout-body > .callout-content > :last-child { margin-bottom: 0.5rem; } - .callout.callout-captioned .callout-icon::before { + .callout.callout-titled .callout-icon::before { margin-top: .5rem; padding-right: .5rem; } - .callout:not(.callout-captioned) .callout-icon::before { + .callout:not(.callout-titled) .callout-icon::before { margin-top: 1rem; padding-right: .5rem; } @@ -177,7 +178,7 @@ background-image: url('data:image/png;base64,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'); } - div.callout-note.callout-style-default .callout-caption { + div.callout-note.callout-style-default .callout-title { background-color: #dae6fb } @@ -189,7 +190,7 @@ background-image: url('data:image/png;base64,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'); } - div.callout-important.callout-style-default .callout-caption { + div.callout-important.callout-style-default .callout-title { background-color: #f7dddc } @@ -201,7 +202,7 @@ background-image: url('data:image/png;base64,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'); } - div.callout-warning.callout-style-default .callout-caption { + div.callout-warning.callout-style-default .callout-title { background-color: #fcefdc } @@ -213,7 +214,7 @@ background-image: url('data:image/png;base64,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'); } - div.callout-tip.callout-style-default .callout-caption { + div.callout-tip.callout-style-default .callout-title { background-color: #ccf1e3 } @@ -225,7 +226,7 @@ background-image: url('data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAAAXNSR0IArs4c6QAAAERlWElmTU0AKgAAAAgAAYdpAAQAAAABAAAAGgAAAAAAA6ABAAMAAAABAAEAAKACAAQAAAABAAAAIKADAAQAAAABAAAAIAAAAACshmLzAAACV0lEQVRYCdVWzWoUQRCuqp2ICBLJXgITZL1EfQDBW/bkzUMUD7klD+ATSHBEfAIfQO+iXsWDxJsHL96EHAwhgzlkg8nBg25XWb0zIb0zs9muYYWkoKeru+vn664fBqElyZNuyh167NXJ8Ut8McjbmEraKHkd7uAnAFku+VWdb3reSmRV8PKSLfZ0Gjn3a6Xlcq9YGb6tADjn+lUfTXtVmaZ1KwBIvFI11rRXlWlatwIAAv2asaa9mlB9wwygiDX26qaw1yYPzFXg2N1GgG0FMF8Oj+VIx7E/03lHx8UhvYyNZLN7BwSPgekXXLribw7w5/c8EF+DBK5idvDVYtEEwMeYefjjLAdEyQ3M9nfOkgnPTEkYU+sxMq0BxNR6jExrAI31H1rzvLEfRIdgcv1XEdj6QTQAS2wtstEALLG1yEZ3QhH6oDX7ExBSFEkFINXH98NTrme5IOaaA7kIfiu2L8A3qhH9zRbukdCqdsA98TdElyeMe5BI8Rs2xHRIsoTSSVFfCFCWGPn9XHb4cdobRIWABNf0add9jakDjQJpJ1bTXOJXnnRXHRf+dNL1ZV1MBRCXhMbaHqGI1JkKIL7+i8uffuP6wVQAzO7+qVEbF6NbS0LJureYcWXUUhH66nLR5rYmva+2tjRFtojkM2aD76HEGAD3tPtKM309FJg5j/K682ywcWJ3PASCcycH/22u+Bh7Aa0ehM2Fu4z0SAE81HF9RkB21c5bEn4Dzw+/qNOyXr3DCTQDMBOdhi4nAgiFDGCinIa2owCEChUwD8qzd03PG+qdW/4fDzjUMcE1ZpIAAAAASUVORK5CYII='); } - div.callout-caution.callout-style-default .callout-caption { + div.callout-caution.callout-style-default .callout-title { background-color: #ffe5d0 } @@ -329,35 +330,11 @@

Visualizações

-
-
-

Ementa do curso

-
-
-

Parte 1 - Metodologia

-
    -
  1. Processo de Geração de Dados
    2. -
  2. Teorema de Priest & Klein
    3. -
  3. Uma técnica de pesquisa
    4. -
-
-

Parte 2 - Visualizações

-
    -
  1. Gráfico de barras
    2. -
  2. Histograma
    3. -
  3. Boxplot
    4. -
  4. Séries temporais
    5. -
  5. Gráfico de dispersão
    6. -
-
-

Séries temporais

-
-

Como construir?

@@ -421,7 +398,7 @@

'autoAnimateEasing': "ease", 'autoAnimateDuration': 1, 'autoAnimateUnmatched': true, -'menu': {"side":"left","useTextContentForMissingTitles":true,"markers":false,"loadIcons":false,"custom":[{"title":"Tools","icon":"","content":""}],"openButton":true}, +'menu': {"side":"left","useTextContentForMissingTitles":true,"markers":false,"loadIcons":false,"custom":[{"title":"Tools","icon":"","content":""}],"openButton":true}, 'smaller': false, // Display controls in the bottom right corner @@ -663,9 +640,23 @@

tabsets.forEach(function(tabset) { const tabby = new Tabby('#' + tabset.id); }); + const isCodeAnnotation = (el) => { + for (const clz of el.classList) { + if (clz.startsWith('code-annotation-')) { + return true; + } + } + return false; + } const clipboard = new window.ClipboardJS('.code-copy-button', { - target: function(trigger) { - return trigger.previousElementSibling; + text: function(trigger) { + const codeEl = trigger.previousElementSibling.cloneNode(true); + for (const childEl of codeEl.children) { + if (isCodeAnnotation(childEl)) { + childEl.remove(); + } + } + return codeEl.innerText; } }); clipboard.on('success', function(e) { @@ -713,7 +704,7 @@

}, interactive: true, interactiveBorder: 10, - theme: 'quarto-reveal', + theme: 'light-border', placement: 'bottom-start' }; config['offset'] = [0,0]; diff --git a/slides/a_time_series.qmd b/slides/a_time_series.qmd index 1a70844..7040f5a 100644 --- a/slides/a_time_series.qmd +++ b/slides/a_time_series.qmd @@ -27,28 +27,6 @@ knitr::opts_chunk$set( ) ``` -## Ementa do curso {.smaller} - -::: columns -::: column -#### Parte 1 - Metodologia - -1. Processo de Geração de Dados -2. Teorema de Priest & Klein -3. Uma técnica de pesquisa -::: - -::: column -#### Parte 2 - Visualizações - -1. Gráfico de barras -2. Histograma -3. Boxplot -4. Séries temporais -5. Gráfico de dispersão -::: -::: - # Séries temporais {.slide-title} ```{r} diff --git a/slides/a_time_series_files/figure-revealjs/unnamed-chunk-2-1.png b/slides/a_time_series_files/figure-revealjs/unnamed-chunk-2-1.png index 30900d87386ccd0bf3863b257cc738adaa9d8ab7..779a62ec6472c4ed88074da64a466f8e4b939d53 100644 GIT binary patch literal 67474 zcmeFZbyO5y+cr9g1*oWqCK3J3^DcPU*%cPXVvN%u%eH%JU6NSAc?(A_z3 z_Q3GG@Atmn`TzWJSnF92KNsxTaqsKC?(4ob-#$o++{PxvhCm>c2gGuc?uDI`&!OEc4f@Y+23yFY;!sGeQ;CI z-*KnTpT!x%lnD&?ucrKd>(_6R{yQUEneM*o>W>H6&mR=4$Y1q;Cj3Fngsh;k%+;;5 z+O=`M$OwV3YFIvOM3%0X&@~?`;4V7MbHT)uGBQxpKz#{l^t3Qud<%i(y}$ME^7|w$ z_v`5IA6>&_Lw{RC{pcqK`g`F&klW~QnX#`MpucsOW){FifA9ANgAo0#)`S0lXb9y0 zI~!u6OK^TNHF6ZG$?II^O9$z6`y|PwLQU5O6H?>+;^OSH#wwFTe`?wf`BwS#TOhy^|OOe#PC3D0bf!bBsI^9GGz1_&9(G z(V9iae1B_Q`=VD4)5@Aj@^c78iQ@9dGo;H9IO>|)*K%(_YFaMWra0q>Ux7p5*zuj6 zP@<8;#(($*1cFm{acS~2esc`t-uUg-@x2lUE=R5UH_ZiHKxXtU$?VTn{r=EDlczJR zWbL_BB#G_{ANa)k=uea{EG#~>?XL;0=ZT-6u3z3`RIi>G33pfynZTKFt%$lr#r}AcP?YkkL+N`E 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